Trajectory analysis of land use and land cover maps to improve spatial-temporal patterns, and impact assessment on groundwater recharge

NASA Astrophysics Data System (ADS)

Zomlot, Z.; Verbeiren, B.; Huysmans, M.; Batelaan, O.

2017-11-01

Land use/land cover (LULC) change is a consequence of human-induced global environmental change. It is also considered one of the major factors affecting groundwater recharge. Uncertainties and inconsistencies in LULC maps are one of the difficulties that LULC timeseries analysis face and which have a significant effect on hydrological impact analysis. Therefore, an accuracy assessment approach of LULC timeseries is needed for a more reliable hydrological analysis and prediction. The objective of this paper is to assess the impact of land use uncertainty and to improve the accuracy of a timeseries of CORINE (coordination of information on the environment) land cover maps by using a new approach of identifying spatial-temporal LULC change trajectories as a pre-processing tool. This ensures consistency of model input when dealing with land-use dynamics and as such improves the accuracy of land use maps and consequently groundwater recharge estimation. As a case study the impact of consistent land use changes from 1990 until 2013 on groundwater recharge for the Flanders-Brussels region is assessed. The change trajectory analysis successfully assigned a rational trajectory to 99% of all pixels. The methodology is shown to be powerful in correcting interpretation inconsistencies and overestimation errors in CORINE land cover maps. The overall kappa (cell-by-cell map comparison) improved from 0.6 to 0.8 and from 0.2 to 0.7 for forest and pasture land use classes respectively. The study shows that the inconsistencies in the land use maps introduce uncertainty in groundwater recharge estimation in a range of 10-30%. The analysis showed that during the period of 1990-2013 the LULC changes were mainly driven by urban expansion. The results show that the resolution at which the spatial analysis is performed is important; the recharge differences using original and corrected CORINE land cover maps increase considerably with increasing spatial resolution. This study indicates that improving consistency of land use map timeseries is of critical importance for assessing land use change and its environmental impact.

Impacts of regional land-grab on regional hydroclimate in southeastern Africa via modeling and remote sensing

NASA Astrophysics Data System (ADS)

Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

2017-12-01

Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are significant enough to induce changes in the evolution of the planetary boundary layer and its interaction with the atmosphere above. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models or Earth System Models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from timber harvesting due to a land grab boom in Mozambique. We also focus more narrowly at quantifying regional impacts on Gorongosa National Park, a nationally important economic and biodiversity resource in southeastern Africa. After nationalizing all land in 1975 after Mozambique gained independence, complex social processes, including an extended low intensity conflict civil war and economic hardships, led to an escalation of land use rights grants to foreign governments. Between 2004 and 2009, large tracts of land were requested for timber. Here we use existing tree cover loss datasets to more accurately represent land cover within a regional weather model. LULC in a region encompassing Gorongosa is updated at three instances between 2001 and 2014 using a tree cover loss dataset. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the land grab. Results suggest that the land grab has impacted microclimate parameters in a significant way via direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional social dynamics are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

Regional Climate Modeling and Remote Sensing to Characterize Impacts of Civil War Driven Land Use Change on Regional Hydrology and Climate

NASA Astrophysics Data System (ADS)

Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

2016-12-01

Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are extensive enough. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from an extended civil conflict in Mozambique. Civil war from 1977-1992 in Mozambique led to land use change at a regional scale as a result of the collapse of large herbivore populations due to poaching. Since the war ended, farming has increased, poaching was curtailed, and animal populations were reintroduced. In this study LULC in a region encompassing Gorongosa is classified at three instances between 1977 to 2015 using Landsat imagery. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from conflict-driven land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the civil war. Analysis of the Landsat data shows measurable land cover change from 1977-present as tree cover encroached into grasslands. Initial tests show corresponding sensitivities to different LULC schemes within the WRF model. Preliminary results suggest that the war did indeed impact regional hydroclimate in a significant way via its direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional conflicts are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

Effects of Land Use and Land Cover, Stream Discharge, and Interannual Climate on the Magnitude and Timing of Nitrogen, Phosphorus, and Organic Carbon Concentrations in Three Coastal Plain Watersheds

EPA Science Inventory

In-stream nitrogen, phosphorus, organic carbon, and suspended sediment concentrations were measured in 18 sub-basins over two annual cycles to assess how land-use/land-cover (LULC) and stream discharge regulate water quality variables. LULC was a primary driver of in-stream const...

National climate assessment technical report on the impacts of climate and land use and land cover change

Treesearch

Thomas Loveland; Rezaul Mahmood; Toral Patel-Weynand; Krista Karstensen; Kari Beckendorf; Norman Bliss; Andrew Carleton

2012-01-01

This technical report responds to the recognition by the U.S. Global Change Research Program (USGCRP) and the National Climate Assessment (NCA) of the importance of understanding how land use and land cover (LULC) affects weather and climate variability and change and how that variability and change affects LULC. Current published, peer-reviewed, scientific literature...

Modeling the hydrological impacts of land use/land cover changes in the Andassa watershed, Blue Nile Basin, Ethiopia.

PubMed

Gashaw, Temesgen; Tulu, Taffa; Argaw, Mekuria; Worqlul, Abeyou W

2018-04-01

Understanding the hydrological response of a watershed to land use/land cover (LULC) changes is imperative for water resources management planning. The objective of this study was to analyze the hydrological impacts of LULC changes in the Andassa watershed for a period of 1985-2015 and to predict the LULC change impact on the hydrological status in year 2045. The hybrid land use classification technique for classifying Landsat images (1985, 2000 and 2015); Cellular-Automata Markov (CA-Markov) for prediction of the 2030 and 2045 LULC states; the Soil and Water Assessment Tool (SWAT) for hydrological modeling were employed in the analyses. In order to isolate the impacts of LULC changes, the LULC maps were used independently while keeping the other SWAT inputs constant. The contribution of each of the LULC classes was examined with the Partial Least Squares Regression (PLSR) model. The results showed that there was a continuous expansion of cultivated land and built-up area, and withdrawing of forest, shrubland and grassland during the 1985-2015 periods, which are expected to continue in the 2030 and 2045 periods. The LULC changes, which had occurred during the period of 1985 to 2015, had increased the annual flow (2.2%), wet seasonal flow (4.6%), surface runoff (9.3%) and water yield (2.4%). Conversely, the observed changes had reduced dry season flow (2.8%), lateral flow (5.7%), groundwater flow (7.8%) and ET (0.3%). The 2030 and 2045 LULC states are expected to further increase the annual and wet season flow, surface runoff and water yield, and reduce dry season flow, groundwater flow, lateral flow and ET. The change in hydrological components is a direct result of the significant transition from the vegetation to non-vegetation cover in the watershed. This suggests an urgent need to regulate the LULC in order to maintain the hydrological balance. Copyright © 2017 Elsevier B.V. All rights reserved.

Future scenarios of land-use and land-cover change in the United States--the Marine West Coast Forests Ecoregion

USGS Publications Warehouse

Wilson, Tamara S.; Sleeter, Benjamin M.; Sohl, Terry L.; Griffith, Glenn; Acevedo, William; Bennett, Stacie; Bouchard, Michelle; Reker, Ryan R.; Ryan, Christy; Sayler, Kristi L.; Sleeter, Rachel; Soulard, Christopher E.

2012-01-01

Detecting, quantifying, and projecting historical and future changes in land use and land cover (LULC) has emerged as a core research area for the U.S. Geological Survey (USGS). Changes in LULC are important drivers of changes to biogeochemical cycles, the exchange of energy between the Earth’s surface and atmosphere, biodiversity, water quality, and climate change. To quantify the rates of recent historical LULC change, the USGS Land Cover Trends project recently completed a unique ecoregion-based assessment of late 20th century LULC change for the western United States. To characterize present LULC, the USGS and partners have created the National Land Cover Database (NLCD) for the years 1992, 2001, and 2006. Both Land Cover Trends and NLCD projects continue to evolve in an effort to better characterize historical and present LULC conditions and are the foundation of the data presented in this report. Projecting future changes in LULC requires an understanding of the rates and patterns of change, the major driving forces, and the socioeconomic and biophysical determinants and capacities of regions. The data presented in this report is the result of an effort by USGS scientists to downscale the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) to ecoregions of the conterminous United States as part of the USGS Biological Carbon Sequestration Assessment. The USGS biological carbon assessment was mandated by Section 712 of the Energy Independence and Security Act of 2007. As part of the legislative mandate, the USGS is required to publish a methodology describing, in detail, the approach to be used for the assessment. The development of future LULC scenarios is described in chapter 3.2 and appendix A. Spatial modeling is described in chapter 3.3.2 and appendix B and in Sohl and others (2011). In this report, we briefly summarize the major components and methods used to downscale IPCC-SRES scenarios to ecoregions of the conterminous United States, followed by a description of the Marine West Coast Forests Ecoregion, and lastly a description of the data being published as part of this report.

Integrating multisource land use and land cover data

USGS Publications Warehouse

Wright, Bruce E.; Tait, Mike; Lins, K.F.; Crawford, J.S.; Benjamin, S.P.; Brown, Jesslyn F.

1995-01-01

As part of the U.S. Geological Survey's (USGS) land use and land cover (LULC) program, the USGS in cooperation with the Environmental Systems Research Institute (ESRI) is collecting and integrating LULC data for a standard USGS 1:100,000-scale product. The LULC data collection techniques include interpreting spectrally clustered Landsat Thematic Mapper (TM) images; interpreting 1-meter resolution digital panchromatic orthophoto images; and, for comparison, aggregating locally available large-scale digital data of urban areas. The area selected is the Vancouver, WA-OR quadrangle, which has a mix of urban, rural agriculture, and forest land. Anticipated products include an integrated LULC prototype data set in a standard classification scheme referenced to the USGS digital line graph (DLG) data of the area and prototype software to develop digital LULC data sets.This project will evaluate a draft standard LULC classification system developed by the USGS for use with various source material and collection techniques. Federal, State, and local governments, and private sector groups will have an opportunity to evaluate the resulting prototype software and data sets and to provide recommendations. It is anticipated that this joint research endeavor will increase future collaboration among interested organizations, public and private, for LULC data collection using common standards and tools.

Stormwater runoff quality in correlation to land use and land cover development in Yongin, South Korea.

PubMed

Paule, M A; Memon, S A; Lee, B-Y; Umer, S R; Lee, C-H

2014-01-01

Stormwater runoff quality is sensitive to land use and land cover (LULC) change. It is difficult to understand their relationship in predicting the pollution potential and developing watershed management practices to eliminate or reduce the pollution risk. In this study, the relationship between LULC change and stormwater runoff quality in two separate monitoring sites comprising a construction area (Site 1) and mixed land use (Site 2) was analyzed using geographic information system (GIS), event mean concentration (EMC), and correlation analysis. It was detected that bare land area increased, while other land use areas such as agriculture, commercial, forest, grassland, parking lot, residential, and road reduced. Based on the analyses performed, high maximum range and average EMCs were found in Site 2 for most of the water pollutants. Also, urban areas and increased conversion of LULC into bare land corresponded to degradation of stormwater quality. Correlation analysis between LULC and stormwater quality showed the influence of different factors such as farming practices, geographical location, and amount of precipitation, vegetation loss, and anthropogenic activities in monitoring sites. This research found that GIS application was an efficient tool for monthly monitoring, validation and statistical analysis of LULC change in the study area.

Impact of land use and land cover change on the water balance of a large agricultural watershed: Historical effects and future directions

USGS Publications Warehouse

Schilling, Keith E.; Jha, Manoj K.; Zhang, You‐Kuan; Gassman, Philip W.; Wolter, Calvin F.

2009-01-01

Over the last century, land use and land cover (LULC) in the United States Corn Belt region shifted from mixed perennial and annual cropping systems to primarily annual crops. Historical LULC change impacted the annual water balance in many Midwestern basins by decreasing annual evapotranspiration (ET) and increasing streamflow and base flow. Recent expansion of the biofuel industry may lead to future LULC changes from increasing corn acreage and potential conversion of the industry to cellulosic bioenergy crops of warm or cool season grasses. In this paper, the Soil and Water Assessment Tool (SWAT) model was used to evaluate potential impacts from future LULC change on the annual and seasonal water balance of the Raccoon River watershed in west‐central Iowa. Three primary scenarios for LULC change and three scenario variants were evaluated, including an expansion of corn acreage in the watershed and two scenarios involving expansion of land using warm season and cool season grasses for ethanol biofuel. Modeling results were consistent with historical observations. Increased corn production will decrease annual ET and increase water yield and losses of nitrate, phosphorus, and sediment, whereas increasing perennialization will increase ET and decrease water yield and loss of nonpoint source pollutants. However, widespread tile drainage that exists today may limit the extent to which a mixed perennial‐annual land cover would ever resemble pre‐1940s hydrologic conditions. Study results indicate that future LULC change will affect the water balance of the watershed, with consequences largely dependent on the future LULC trajectory.

Remote sensing based deforestation analysis in Mahanadi and Brahmaputra river basin in India since 1985.

PubMed

Behera, M D; Tripathi, P; Das, P; Srivastava, S K; Roy, P S; Joshi, C; Behera, P R; Deka, J; Kumar, P; Khan, M L; Tripathi, O P; Dash, T; Krishnamurthy, Y V N

2018-01-15

Land use and land cover (LULC) change has been recognized as a key driver of global climate change by influencing land surface processes. Being in constant change, river basins are always subjected to LULC changes, especially decline in forest cover to give way for agricultural expansion, urbanization, industrialization etc. We used on-screen digital interpretation technique to derive LULC maps from Landsat images at three decadal intervals i.e., 1985, 1995 and 2005 of two major river basins of India. Rain-fed, Mahanadi river basin (MRB) attributed to 55% agricultural area wherein glacier-fed, Brahmaputra river basin (BRB) had only 16% area under agricultural land. Though conversion of forest land for agricultural activities was the major LULC changes in both the basins, the rate was higher for BRB than MRB. While water body increased in MRB could be primarily attributed to creation of reservoirs and aquaculture farms; snow and ice melting attributed to creation of more water bodies in BRB. Scrub land acted as an intermediate class for forest conversion to barren land in BRB, while direct conversion of scrub land to waste land and crop land was seen in MRB. While habitation contributed primarily to LULC changes in BRB, the proximity zones around habitat and other socio-economic drivers contributed to LULC change in MRB. Comparing the predicted result with actual LULC of 2005, we obtained >97% modelling accuracy; therefore it is expected that the Dyna-CLUE model has very well predicted the LULC for the year 2025. The predicted LULC of 2025 and corresponding LULC changes in these two basins acting as early warning, and with the past 2-decadal change analysis this study is believed to help the land use planners for improved regional planning to create balanced ecosystem, especially in a changing climate. Copyright © 2017 Elsevier Ltd. All rights reserved.

Land cover changes induced by the great east Japan earthquake in 2011

NASA Astrophysics Data System (ADS)

Ishihara, Mitsunori; Tadono, Takeo

2017-03-01

The east Japan earthquake that occurred on March 11, 2011 was a big natural disaster, comprising the large earthquake shock, tsunami, and Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. These disasters caused changes in the land use and land cover (LULC) in Japan’s Tohoku district. While the LULC map created before the disaster is available, as yet there is no precise LULC map of the district after the disaster. In this study, we created a precise LULC map for the years 2013-2015 post-disaster with 30-m spatial resolution using the Landsat-8 with the Operational Land Imager (OLI) to evaluate the changes in LULC induced by the disaster. Our results indicate many changes in areas categorized as rice paddies primarily into grass categories along the coast damaged by the tsunami and in the evacuation zone around the FDNPP. Since there is a possibility of future LULC changes according to the change of the evacuation zone and implementation of reconstruction and revitalization efforts, we recommend continual monitoring of the changes in LULC by the use of satellite data in order to evaluate the long-term effects of the disaster.

Land cover changes induced by the great east Japan earthquake in 2011.

PubMed

Ishihara, Mitsunori; Tadono, Takeo

2017-03-31

The east Japan earthquake that occurred on March 11, 2011 was a big natural disaster, comprising the large earthquake shock, tsunami, and Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. These disasters caused changes in the land use and land cover (LULC) in Japan's Tohoku district. While the LULC map created before the disaster is available, as yet there is no precise LULC map of the district after the disaster. In this study, we created a precise LULC map for the years 2013-2015 post-disaster with 30-m spatial resolution using the Landsat-8 with the Operational Land Imager (OLI) to evaluate the changes in LULC induced by the disaster. Our results indicate many changes in areas categorized as rice paddies primarily into grass categories along the coast damaged by the tsunami and in the evacuation zone around the FDNPP. Since there is a possibility of future LULC changes according to the change of the evacuation zone and implementation of reconstruction and revitalization efforts, we recommend continual monitoring of the changes in LULC by the use of satellite data in order to evaluate the long-term effects of the disaster.

Spatiotemporal analysis of land use and land cover change in the Brazilian Amazon

PubMed Central

Li, Guiying; Moran, Emilio; Hetrick, Scott

2013-01-01

This paper provides a comparative analysis of land use and land cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired in the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach. A classification system composed of six classes – forest, savanna, other-vegetation (secondary succession and plantations), agro-pasture, impervious surface, and water, was designed for this study. A hierarchical-based classification method was used to classify Landsat images into thematic maps. This research shows different spatiotemporal change patterns, composition and rates among the three study areas and indicates the importance of analyzing LULC change at multiple scales. The LULC change analysis over time for entire study areas provides an overall picture of change trends, but detailed change trajectories and their spatial distributions can be better examined at a per-pixel scale. The LULC change at the polygon scale provides the information of the changes in patch sizes over time, while the LULC change at census sector scale gives new insights on how human-induced activities (e.g., urban expansion, roads, and land use history) affect LULC change patterns and rates. This research indicates the necessity to implement change detection at multiple scales for better understanding the mechanisms of LULC change patterns and rates. PMID:24127130

Riparian Land Use/Land Cover Data for Five Study Units in the Nutrient Enrichment Effects Topical Study of the National Water-Quality Assessment Program

USGS Publications Warehouse

Johnson, Michaela R.; Buell, Gary R.; Kim, Moon H.; Nardi, Mark R.

2007-01-01

This dataset was developed as part of the National Water-Quality Assessment (NAWQA) Program, Nutrient Enrichment Effects Topical (NEET) study for five study units distributed across the United States: Apalachicola-Chattahoochee-Flint River Basin, Central Columbia Plateau-Yakima River Basin, Central Nebraska Basins, Potomac River Basin and Delmarva Peninsula, and White, Great and Little Miami River Basins. One hundred forty-three stream reaches were examined as part of the NEET study conducted 2003-04. Stream segments, with lengths equal to the logarithm of the basin area, were delineated upstream from the downstream ends of the stream reaches with the use of digital orthophoto quarter quadrangles (DOQQ) or selected from the high-resolution National Hydrography Dataset (NHD). Use of the NHD was necessary when the stream was not distinguishable in the DOQQ because of dense tree canopy. The analysis area for each stream segment was defined by a buffer beginning at the segment extending to 250 meters lateral to the stream segment. Delineation of land use/land cover (LULC) map units within stream segment buffers was conducted using on-screen digitizing of riparian LULC classes interpreted from the DOQQ. LULC units were mapped using a classification strategy consisting of nine classes. National Wetlands Inventory (NWI) data were used to aid in wetland classification. Longitudinal transect sampling lines offset from the stream segments were generated and partitioned into the underlying LULC types. These longitudinal samples yielded the relative linear extent and sequence of each LULC type within the riparian zone at the segment scale. The resulting areal and linear LULC data filled in the spatial-scale gap between the 30-meter resolution of the National Land Cover Dataset and the reach-level habitat assessment data collected onsite routinely for NAWQA ecological sampling. The final data consisted of 12 geospatial datasets: LULC within 25 meters of the stream reach (polygon); LULC within 50 meters of the stream reach (polygon); LULC within 50 meters of the stream segment (polygon); LULC within 100 meters of the stream segment (polygon); LULC within 150 meters of the stream segment (polygon); LULC within 250 meters of the stream segment (polygon); frequency of gaps in woody vegetation LULC at the reach scale (arc); stream reaches (arc); longitudinal LULC at the reach scale (arc); frequency of gaps in woody vegetation LULC at the segment scale (arc); stream segments (arc); and longitudinal LULC at the segment scale (arc).

Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China.

PubMed

Yang, Xiaoyan; Chen, Longgao; Li, Yingkui; Xi, Wenjia; Chen, Longqian

2015-07-01

Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0% in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9% (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9% and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

The Application of Satellite-Derived, High-Resolution Land Use/Land Cover Data to Improve Urban Air Quality Model Forecasts

NASA Technical Reports Server (NTRS)

Quattrochi, D. A.; Lapenta, W. M.; Crosson, W. L.; Estes, M. G., Jr.; Limaye, A.; Kahn, M.

2006-01-01

Local and state agencies are responsible for developing state implementation plans to meet National Ambient Air Quality Standards. Numerical models used for this purpose simulate the transport and transformation of criteria pollutants and their precursors. The specification of land use/land cover (LULC) plays an important role in controlling modeled surface meteorology and emissions. NASA researchers have worked with partners and Atlanta stakeholders to incorporate an improved high-resolution LULC dataset for the Atlanta area within their modeling system and to assess meteorological and air quality impacts of Urban Heat Island (UHI) mitigation strategies. The new LULC dataset provides a more accurate representation of land use, has the potential to improve model accuracy, and facilitates prediction of LULC changes. Use of the new LULC dataset for two summertime episodes improved meteorological forecasts, with an existing daytime cold bias of approx. equal to 3 C reduced by 30%. Model performance for ozone prediction did not show improvement. In addition, LULC changes due to Atlanta area urbanization were predicted through 2030, for which model simulations predict higher urban air temperatures. The incorporation of UHI mitigation strategies partially offset this warming trend. The data and modeling methods used are generally applicable to other U.S. cities.

Clarity versus complexity: land-use modeling as a practical tool for decision-makers

USGS Publications Warehouse

Sohl, Terry L.; Claggett, Peter

2013-01-01

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

Riparian Land Use/Land Cover Data for Three Study Units in Group II of the Nutrient Enrichment Effects Topical Study of the National Water-Quality Assessment Program

USGS Publications Warehouse

Johnson, Michaela R.; Clark, Jimmy M.; Dickinson, Ross G.; Sanocki, Chris A.; Tranmer, Andrew W.

2009-01-01

This data set was developed as part of the National Water-Quality Assessment (NAWQA) Program, Nutrient Enrichment Effects Topical (NEET) study. This report is concerned with three of the eight NEET study units distributed across the United States: Ozark Plateaus, Upper Mississippi River Basin, and Upper Snake River Basin, collectively known as Group II of the NEET study. Ninety stream reaches were investigated during 2006-08 in these three study units. Stream segments, with lengths equal to the base-10 logarithm of the basin area, were delineated upstream from the stream reaches through the use of digital orthophoto quarter-quadrangle (DOQQ) imagery. The analysis area for each stream segment was defined by a streamside buffer extending laterally to 250 meters from the stream segment. Delineation of landuse and land-cover (LULC) map units within stream-segment buffers was completed using on-screen digitizing of riparian LULC classes interpreted from the DOQQ. LULC units were classified using a strategy consisting of nine classes. National Wetlands Inventory (NWI) data were used to aid in wetland classification. Longitudinal riparian transects (lines offset from the stream segments) were generated digitally, used to sample the LULC maps, and partitioned in accord with the intersected LULC map-unit types. These longitudinal samples yielded the relative linear extent and sequence of each LULC type within the riparian zone at the segment scale. The resulting areal and linear estimates of LULC extent filled in the spatial-scale gap between the 30-meter resolution of the 1990s National Land Cover Dataset and the reach-level habitat assessment data collected onsite routinely for NAWQA ecological sampling. The resulting data consisted of 12 geospatial data sets: LULC within 25 meters of the stream reach (polygon); LULC within 50 meters of the stream reach (polygon); LULC within 50 meters of the stream segment (polygon); LULC within 100 meters of the stream segment (polygon); LULC within 150 meters of the stream segment (polygon); LULC within 250 meters of the stream segment (polygon); frequency of gaps in woody vegetation at the reach scale (arc); stream reaches (arc); longitudinal LULC transect sample at the reach scale (arc); frequency of gaps in woody vegetation at the segment scale (arc); stream segments (arc); and longitudinal LULC transect sample at the segment scale (arc).

Land-Use and Land-Cover Change around Mobile Bay, Alabama from 1974-2008

NASA Technical Reports Server (NTRS)

Ellis, Jean; Spruce, Joseph P.; Swann, Roberta; Smooth, James C.

2009-01-01

This document summarizes the major findings of a Gulf of Mexico Application Pilot project led by NASA Stennis Space Center (SSC) in conjunction with a regional collaboration network of the Gulf of Mexico Alliance (GOMA). NASA researchers processed and analyzed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL between 1974 and 2008. Our goal was to create satellite-based LULC data products using methods that could be transferable to other coastal areas of concern within the Gulf of Mexico. The Mobile Bay National Estuary Program (MBNEP) is the primary end-user, however, several other state and local groups may benefit from the project s data products that will be available through NOAA-NCDDC s Regional Ecosystem Data Management program. Mobile Bay is a critical ecologic and economic region in the Gulf of Mexico and to the entire country. Mobile Bay was designated as an estuary of national significance in 1996. This estuary receives the fourth largest freshwater inflow in the United States. It provides vital nursery habitat for commercially and recreationally important fish species. It has exceptional aquatic and terrestrial bio-diversity, however, its estuary health is influenced by changing LULC patterns, such as urbanization. Mobile and Baldwin counties have experienced a population growth of 1.1% and 20.5% from 2000-2006. Urban expansion and population growth are likely to accelerate with the construction and operation of the ThyssenKrupp steel mill in the northeast portion of Mobile County. Land-use and land-cover change can negatively impact Gulf coast water quality and ecological resources. The conversion of forest to urban cover types impacts the carbon cycle and increases the freshwater and sediment in coastal waters. Increased freshwater runoff decreases salinity and increases the turbidity of coastal waters, thus impacting the growth potential of submerged aquatic vegetation (SAV), which is critical nursing ground for many Gulf fish species. A survey of Mobile Bay SAV showed widespread decreases since the 1940s. Prior to our project, coastal environmental managers in Baldwin and Mobile counties needed more understanding of the historical LULC for properly assessing the impacts of urbanization. In particular, more information on the location and extent of changing urbanization LULC patterns was needed to aid LULC planning and to assess predictions of future LULC patterns. Our products will assist the coastal environmental managers and land-use planners in making better community growth planning decisions. Our project also will help to establish a historical baseline of LULC distributions, which is a fundamental need in any stewardship plan. The primary research objective of our project was to produce historic and current geospatial LULC change products across a 34-year time frame. A multi-decadal coastal LULC change product was the major project deliverable. The geographic extent and nature of change was quantified and assessed for the upland herbaceous, barren, open water, urban, upland forest, woody wetland, and non-woody wetlanddominated land cover types. We focused on regional analyses of decadal-scale urban expansion and watershed-scaled analyses of LULC change for multiple areas of concern to the Mobile Bay NEP (Figure A). We used the following dates to derive LULC classification products from Landsat data: 1974, 1979, 1984, 1988, 1991, 1996, 2001, 2005, and 2008. We assessed the accuracy of our products using randomly sampled locations and digital geospatial reference data including field survey data, high resolution orthorectified aerial photography, high resolution multispectral and panchromatic satellite data displays (from QuickBird and Corona sensors), digital elevation model data, and National Wetlands Inventory wetland cover type data. NOAA s Coastal Change Assessment Program s (C-CAP) and National Land Cover Database (NLCD) procts were used for qualitative comparison in assessing map accuracy. We calculated an average overall classification accuracy of 87% with similar overall accuracies for the older (MSS) and newer (TM and ETM) Landsat LULC products.

Spatially targeting Culex quinquefasciatus aquatic habitats on modified land cover for implementing an Integrated Vector Management (IVM) program in three villages within the Mwea Rice Scheme, Kenya

PubMed Central

Jacob, Benjamin G; Shililu, Josephat; Muturi, Ephantus J; Mwangangi, Joseph M; Muriu, Simon M; Funes, Jose; Githure, John; Regens, James L; Novak, Robert J

2006-01-01

Background Continuous land cover modification is an important part of spatial epidemiology because it can help identify environmental factors and Culex mosquitoes associated with arbovirus transmission and thus guide control intervention. The aim of this study was to determine whether remotely sensed data could be used to identify rice-related Culex quinquefasciatus breeding habitats in three rice-villages within the Mwea Rice Scheme, Kenya. We examined whether a land use land cover (LULC) classification based on two scenes, IKONOS at 4 m and Landsat Thematic Mapper at 30 m could be used to map different land uses and rice planted at different times (cohorts), and to infer which LULC change were correlated to high density Cx. quinquefasciatus aquatic habitats. We performed a maximum likelihood unsupervised classification in Erdas Imagine V8.7® and generated three land cover classifications, rice field, fallow and built environment. Differentially corrected global positioning systems (DGPS) ground coordinates of Cx. quinquefasciatus aquatic habitats were overlaid onto the LULC maps generated in ArcInfo 9.1®. Grid cells were stratified by levels of irrigation (well-irrigated and poorly-irrigated) and varied according to size of the paddy. Results Total LULC change between 1988–2005 was 42.1 % in Kangichiri, 52.8 % in Kiuria and and 50.6 % Rurumi. The most frequent LULC changes was rice field to fallow and fallow to rice field. The proportion of aquatic habitats positive for Culex larvae in LULC change sites was 77.5% in Kangichiri, 72.9% in Kiuria and 73.7% in Rurumi. Poorly – irrigated grid cells displayed 63.3% of aquatic habitats among all LULC change sites. Conclusion We demonstrate that optical remote sensing can identify rice cultivation LULC sites associated with high Culex oviposition. We argue that the regions of higher Culex abundance based on oviposition surveillance sites reflect underlying differences in abundance of larval habitats which is where limited control resources could be concentrated to reduce vector larval abundance. PMID:16684354

Modelling catchment hydrological responses in a Himalayan Lake as a function of changing land use and land cover

NASA Astrophysics Data System (ADS)

Badar, Bazigha; Romshoo, Shakil A.; Khan, M. A.

2013-04-01

In this paper, we evaluate the impact of changing land use/land cover (LULC) on the hydrological processes in Dal lake catchment of Kashmir Himalayas by integrating remote sensing, simulation modelling and extensive field observations. Over the years, various anthropogenic pressures in the lake catchment have significantly altered the land system, impairing, inter-alia, sustained biotic communities and water quality of the lake. The primary objective of this paper was to help a better understanding of the LULC change, its driving forces and the overall impact on the hydrological response patterns. Multi-sensor and multi-temporal satellite data for 1992 and 2005 was used for determining the spatio-temporal dynamics of the lake catchment. Geographic Information System (GIS) based simulation model namely Generalized Watershed Loading Function (GWLF) was used to model the hydrological processes under the LULC conditions. We discuss spatio-temporal variations in LULC and identify factors contributing to these variations and analyze the corresponding impacts of the change on the hydrological processes like runoff, erosion and sedimentation. The simulated results on the hydrological responses reveal that depletion of the vegetation cover in the study area and increase in impervious and bare surface cover due to anthropogenic interventions are the primary reasons for the increased runoff, erosion and sediment discharges in the Dal lake catchment. This study concludes that LULC change in the catchment is a major concern that has disrupted the ecological stability and functioning of the Dal lake ecosystem.

Status and trends of land change in selected U.S. ecoregions - 2000 to 2011

USGS Publications Warehouse

Sayler, Kristi L.; Acevedo, William; Taylor, Janis

2016-01-01

U.S. Geological Survey scientists developed a dataset of 2006 and 2011 land-use and land-cover (LULC) information for selected 100-km2 sample blocks within 29 U.S. Environmental Protection Agency (EPA) Level III ecoregions across the conterminous United States. The data can be used with the previously published Land Cover Trends Dataset: 1973 to 2000 to assess landuse/land-cover change across a 37-year study period. Results from analysis of these data include ecoregion-based statistical estimates of the amount of LULC change per time period, ranking of the most common types of conversions, rates of change, and percent composition. Overall estimated amount of change per ecoregion from 2001 to 2011 ranged from a low of 370 km2 in the Northern Basin and Range Ecoregion to a high of 78,782 km2 in the Southeastern Plains Ecoregion. The Southeastern Plains continues to encompass one of the most intense forest harvesting and regrowth regions in the country, with 16.6 percent of the ecoregion changing between 2001 and 2011. These LULC change statistics provide a new, valuable resource that complements other reference data and field-verified LULC data. Researchers can use this resource to independently validate other land change products or to conduct regional land change assessments.

Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh.

PubMed

Rahman, M Tauhid Ur; Tabassum, Faheemah; Rasheduzzaman, Md; Saba, Humayra; Sarkar, Lina; Ferdous, Jannatul; Uddin, Syed Zia; Zahedul Islam, A Z M

2017-10-17

Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. "Bare lands" decreased by 21% being occupied by other land uses, especially by "shrimp farms." Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in "settlement" area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy cultivation to shrimp farming were related to each other. Around 31.3% of the total respondents stated that at least one of their family members had migrated. Climate-driven southwestern coastal people usually migrate from the vulnerable rural areas towards the nearest relatively safe city due to adverse effects of natural disasters. To control the unplanned development and reduce the internal migration in Assasuni and other coastal areas, a comprehensive land use management plan was suggested that would accommodate the diversified uses of coastal lands and eventually lessen the threats to the life and livelihood of the local people.

Relationship between landslide processes and land use-land cover changes in mountain regions: footprint identification approach.

NASA Astrophysics Data System (ADS)

Petitta, Marcello; Pregnolato, Marco; Pedoth, Lydia; Schneiderbauer, Stefan

2015-04-01

The present investigation aims to better understand the relationship between landslide events and land use-land cover (LULC) changes. Starting from the approach presented last year at national level ("In search of a footprint: an investigation about the potentiality of large datasets and territorial analysis in disaster and resilience research", Geophysical Research Abstracts Vol. 16, EGU2014-11253, 2014) we focused our study at regional scale considering South Tyrol, a mountain region in Italy near the Austrian border. Based on the concept exploited in the previous work, in which a disaster footprint was shown using land features and changes maps, in this study we start from the hypothesis that LULC can have a role in activation of landslides events. In this study, we used LULC data from CORINE and from a regional map called REAKART and we used the Italian national database IFFI (Inventario Fenomeni Franosi in Italia, Italian inventory of landslides) from which it is possible to select the landslides present in the national inventory together with other vector layers (the urban areas - Corine Land Cover 2000, the roads and railways, the administrative boundaries, the drainage system) and raster layers (the digital terrain model, digital orthophoto TerraItaly it2000, Landsat satellite images and IGM topographic map). Moreover it's possible to obtain information on the most important parameters of landslides, view documents, photos and videos. For South Tyrol, the IFFI database is updated in real time. In our investigation we analyzed: 1) LULC from CORINE and from REAKART, 2) landslides occurred nearby a border of two different LULC classes, 3) landslides occurred in a location in which a change in LULC classification in observed in time, 4) landslides occurred nearby road and railroad. Using classification methods and statistical approaches we investigated relationship between the LULC and the landslides events. The results confirm that specific LULC classes are more prone to landslides and LULC classification can be an instrument for supporting the identification of landslide area. However, it must be considered that other factors play a more relevant role in landslide occurrences and activations and that LULC classification can be used only as supplementary information, which can assist the identification of dangerous areas. Moreover, this approach, if appropriately developed, could prove useful in understanding how the community could use diverse LULC solutions to make the territory adapted and more resilient when prone to such phenomena.

Divergent projections of future land use in the United States arising from different models and scenarios

USGS Publications Warehouse

Sohl, Terry L.; Wimberly, Michael; Radeloff, Volker C.; Theobald, David M.; Sleeter, Benjamin M.

2016-01-01

A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there is a need for improvement in LULC theory and modeling capabilities to improve acceptance and use of regional- to national-scale LULC projections for the United States and elsewhere.

Modelling the Relationship Between Land Surface Temperature and Landscape Patterns of Land Use Land Cover Classification Using Multi Linear Regression Models

NASA Astrophysics Data System (ADS)

Bernales, A. M.; Antolihao, J. A.; Samonte, C.; Campomanes, F.; Rojas, R. J.; dela Serna, A. M.; Silapan, J.

2016-06-01

The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric "Effective mesh size" was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.

Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid SWAT Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Spruce, J.; Bolten, J. D.; Srinivasan, R.

2017-12-01

This presentation discusses research to develop Land Use Land Cover (LULC) maps for the Lower Mekong Basin (LMB). Funded by a NASA ROSES Disasters grant, the main objective was to produce updated LULC maps to aid the Mekong River Commission's (MRC's) Soil and Water Assessment Tool (SWAT) hydrologic model. In producing needed LULC maps, temporally processed MODIS monthly NDVI data for 2010 were used as the primary data source for classifying regionally prominent forest and agricultural types. The MODIS NDVI data was derived from processing MOD09 and MYD09 8-day reflectance data with the Time Series Product Tool, a custom software package. Circa 2010 Landsat multispectral data from the dry season were processed into top of atmosphere reflectance mosaics and then classified to derive certain locally common LULC types, such as urban areas and industrial forest plantations. Unsupervised ISODATA clustering was used to derive most LULC classifications. GIS techniques were used to merge MODIS and Landsat classifications into final LULC maps for Sub-Basins (SBs) 1-8 of the LMB. The final LULC maps were produced at 250-meter resolution and delivered to the MRC for use in SWAT modeling for the LMB. A map accuracy assessment was performed for the SB 7 LULC map with 14 classes. This assessment was performed by comparing random locations for sampled LULC types to geospatial reference data such as Landsat RGBs, MODIS NDVI phenologic profiles, high resolution satellite data from Google Map/Earth, and other reference data from the MRC (e.g., crop calendars). LULC accuracy assessment results for SB 7 indicated an overall agreement to reference data of 81% at full scheme specificity. However, by grouping 3 deciduous forest classes into 1 class, the overall agreement improved to 87%. The project enabled updated LULC maps, plus more specific rice types were classified compared to the previous LULC maps. The LULC maps from this project should improve the use of SWAT for modeling hydrology in the LMB, plus improve water and disaster management in a region vulnerable to flooding, droughts, and anthropogenic change (e.g., from dam building and other LULC change).

Long-Term Hydrologic Impact Assessment of Non-point Source Pollution Measured Through Land Use/Land Cover (LULC) Changes in a Tropical Complex Catchment

NASA Astrophysics Data System (ADS)

Abdulkareem, Jabir Haruna; Sulaiman, Wan Nor Azmin; Pradhan, Biswajeet; Jamil, Nor Rohaizah

2018-03-01

The contribution of non-point source pollution (NPS) to the contamination of surface water is an issue of growing concern. Non-point source (NPS) pollutants are of various types and altered by several site-specific factors making them difficult to control due to complex uncertainties involve in their behavior. Kelantan River basin, Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/land cover (LULC) changes making the area consistently flood prone thereby deteriorating the surface water quality in the area. This study was conducted to determine the spatio-temporal variation of NPS pollutant loads among different LULC changes and to establish a NPS pollutant loads relationships among LULC conditions and sub-basins in each catchment. Four pollutants parameters such as total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and ammonia nitrogen (AN) were chosen with their corresponding event mean concentration values (EMC). Soil map and LULC change maps corresponding to 1984, 2002 and 2013 were used for the calculation of runoff and NPS pollutant loads using numeric integration in a GIS environment. Analysis of Variance (ANOVA) was conducted for the comparison of NPS pollutant loads among the three LULC conditions used and the sub-basins in each catchment. The results showed that the spatio-temporal variation of pollutant loads in almost all the catchments increased with changes in LULC condition as one moves from 1984 to 2013, with 2013 LULC condition found as the dominant in almost all cases. NPS pollutant loads among different LULC changes also increased with changes in LULC condition from 1984 to 2013. While urbanization was found to be the dominant LULC change with the highest pollutant load in all the catchments. Results from ANOVA reveals that statistically most significant (p < 0.05) pollutant loads were obtained from 2013 LULC conditions, while statistically least significant (p < 0.05) pollutant loads were obtained under 1984 LULC condition. This reveals the clear effect of LULC changes on NPS pollution. The findings of this study may be useful to water resource planners in controlling water pollution for future planning.

Long-Term Hydrologic Impact Assessment of Non-point Source Pollution Measured Through Land Use/Land Cover (LULC) Changes in a Tropical Complex Catchment

NASA Astrophysics Data System (ADS)

Abdulkareem, Jabir Haruna; Sulaiman, Wan Nor Azmin; Pradhan, Biswajeet; Jamil, Nor Rohaizah

2018-05-01

The contribution of non-point source pollution (NPS) to the contamination of surface water is an issue of growing concern. Non-point source (NPS) pollutants are of various types and altered by several site-specific factors making them difficult to control due to complex uncertainties involve in their behavior. Kelantan River basin, Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/land cover (LULC) changes making the area consistently flood prone thereby deteriorating the surface water quality in the area. This study was conducted to determine the spatio-temporal variation of NPS pollutant loads among different LULC changes and to establish a NPS pollutant loads relationships among LULC conditions and sub-basins in each catchment. Four pollutants parameters such as total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and ammonia nitrogen (AN) were chosen with their corresponding event mean concentration values (EMC). Soil map and LULC change maps corresponding to 1984, 2002 and 2013 were used for the calculation of runoff and NPS pollutant loads using numeric integration in a GIS environment. Analysis of Variance (ANOVA) was conducted for the comparison of NPS pollutant loads among the three LULC conditions used and the sub-basins in each catchment. The results showed that the spatio-temporal variation of pollutant loads in almost all the catchments increased with changes in LULC condition as one moves from 1984 to 2013, with 2013 LULC condition found as the dominant in almost all cases. NPS pollutant loads among different LULC changes also increased with changes in LULC condition from 1984 to 2013. While urbanization was found to be the dominant LULC change with the highest pollutant load in all the catchments. Results from ANOVA reveals that statistically most significant ( p < 0.05) pollutant loads were obtained from 2013 LULC conditions, while statistically least significant ( p < 0.05) pollutant loads were obtained under 1984 LULC condition. This reveals the clear effect of LULC changes on NPS pollution. The findings of this study may be useful to water resource planners in controlling water pollution for future planning.

Searching for Feedbacks between Land-use/Land-cover Changes and the Water Budget in Complex Terrain at the Dry Creek Experimental Watershed in Idaho, USA

NASA Astrophysics Data System (ADS)

Huang, Y.; Engdahl, N.

2017-12-01

Proactive management to improve water resource sustainability is often limited by a lack of understanding about the hydrological consequences of human activities and climate induced land use and land cover (LULC) change. Changes in LULC can alter runoff, soil moisture, and evapotranspiration, but these effects are complex and traditional modeling techniques have had limited successes in realistically simulating the relevant feedbacks. Recent studies have investigated the coupled interactions but typically do so at coarse resolutions with simple topographic settings, so it is unclear if the previous conclusions remain valid in the steep, complex terrains that dominate the western USA. This knowledge gap was explored with a series of integrated hydrologic simulations based on the Dry Creek Experimental Watershed (DCEW) in southwestern Idaho, USA, using the ParFlow.CLM model. The DCEW has extensive monitoring data that allowed for a direct calibration and validation of the base-case simulation, which is not commonly done with integrated models. The effects of LULC change on the hydrologic and water budgets were then assessed at two grid resolutions (20m and 40m) under four LULC scenarios: 1) current LULC; 2) LULC change from a small but gradual decrease in potential recharge (PR); 3) LULC change from a large but rapid decrease in PR; and 4) LULC change from a large but gradual decrease in PR. The results show that the methods used for terrain processing and the grid resolution can both heavily impact the simulation results and that LULC change can significantly alter the relative amounts of groundwater storage and runoff.

Impacts of changes in climate and land use/land cover under IPCC RCP scenarios on streamflow in the Hoeya River Basin, Korea.

PubMed

Kim, Jinsoo; Choi, Jisun; Choi, Chuluong; Park, Soyoung

2013-05-01

This study examined the separate and combined impacts of future changes in climate and land use/land cover (LULC) on streamflow in the Hoeya River Basin, South Korea, using the representative concentration pathway (RCP) 4.5 and 8.5 scenarios of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). First, a LULC change model was developed using RCP 4.5 and RCP 8.5 storylines and logistic regression. Three scenarios (climate change only, LULC change only, and climate and LULC change combined) were established, and the streamflow in future periods under these scenarios was simulated by the Soil and Water Assessment Tool (SWAT) model. Each scenario showed distinct seasonal variations in streamflow. Under climate change only, streamflow increased in spring and winter but decreased in summer and autumn, whereas LULC change increased high flow during wet periods but decreased low flow in dry periods. Although the LULC change had less effect than climate change on the changes in streamflow, the effect of LULC change on streamflow was significant. The result for the combined scenario was similar to that of the climate change only scenario, but with larger seasonal changes in streamflow. Although the effects of LULC change were smaller than those caused by climate change, LULC changes may heighten the problems of increased seasonal variability in streamflow caused by climate change. The results obtained in this study provide further insight into the availability of future streamflow and can aid in water resource management planning in the study area. Copyright © 2013 Elsevier B.V. All rights reserved.

Scenario modelling of land use/land cover changes in Munessa-Shashemene landscape of the Ethiopian highlands.

PubMed

Kindu, Mengistie; Schneider, Thomas; Döllerer, Martin; Teketay, Demel; Knoke, Thomas

2018-05-01

Models under a set of scenarios are used to simulate and improve our understanding of land use/land cover (LULC) changes, which is central for sustainable management of a given natural resource. In this study, we simulated and examined the possible future LULC patterns and changes in Munessa-Shashemene landscape of the Ethiopian highlands covering four decades (2012-2050) using a spatially explicit GIS-based model. Both primary and secondary sources were utilized to identify relevant explanatory variables (drivers) and LULC datasets for the model. Three alternative scenarios, namely Business As Usual (BAU), Forest Conservation and Water Protection (FCWP) and Sustainable Intensification (SI) were used. The simulated LULC map of 2012 was compared with the actual for model validation and showed a good consistency. The results revealed that areas of croplands will increase widely under the BAU scenario and would expand to the remaining woodlands, natural forests and grasslands, reflecting vulnerability of these LULC types and potential loss of associated ecosystem service values (ESVs). FCWP scenario would bring competition among other LULC types, particularly more pressure to the grassland ecosystem. Hence, the two scenarios will result in severe LULC dynamics that lead to serious environmental crisis. The SI scenario, with holistic approach, demonstrated that expansion of croplands could vigorously be reduced, remaining forests better conserved and degraded land recovered, resulting in gains of the associated total ESVs. We conclude that a holistic landscape management, i.e. SI, is the best approach to ensure expected production while safeguarding the environment of the studied landscape and elsewhere with similar geographic settings. Further study is suggested to practically test our framework through a research for development approach in a test site so that it can be used as a model area for effective use and conservation of our natural resources. Copyright © 2017 Elsevier B.V. All rights reserved.

Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data.

PubMed

Fallati, Luca; Savini, Alessandra; Sterlacchini, Simone; Galli, Paolo

2017-08-01

The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe's WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product's overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.

Land use/land cover and land capability data for evaluating land utilization and official land use planning in Indramayu Regency, West Java, Indonesia

NASA Astrophysics Data System (ADS)

Ambarwulan, W.; Widiatmaka; Nahib, I.

2018-05-01

Land utilization in Indonesia is regulated in an official spatial land use planning (OSLUP), stipulated by government regulations. However in fact, land utilizations are often develops inconsistent with regulations. OSLUP itself is also not usually compatible with sustainable land utilizations. This study aims to evaluate current land utilizations and OSLUP in Indramayu Regency, West Java. The methodology used is the integrated analysis using land use and land cover (LU/LC) data, land capability data and spatial pattern in OSLUP. Actual LU/LC are interpreted using SPOT-6 imagery of 2014. The spatial data of land capabilities are derived from land capability classification using field data and laboratory analysis. The confrontation between these spatial data is interpreted in terms of future direction for sustainable land use planning. The results shows that Indramayu regency consists of 8 types of LU/LC. Land capability in research area range from class II to VIII. Only a small portion of the land in Indramayu has been used in accordance with land capability, but most of the land is used exceeding its land capability.

Nitrate-Nitrogen, Landuse/Landcover, and Soil Drainage Associations at Multiple Spatial Scales

EPA Science Inventory

Managing non–point-source pollution of water requires knowledge of land use/land cover (LULC) influences at altering watershed scales. To gain improved understanding of relationships among LULC, soil drainage, and dissolved nitrate-N dynamics within the Calapooia River Basin in w...

Recent land-use and land-cover changes and its driving factors in a fire-prone area of southwestern Turkey.

PubMed

Viedma, Olga; Moreno, José M; Güngöroglu, Cumhur; Cosgun, Ufuk; Kavgacı, Ali

2017-07-15

During the last decades, contrasted trends in forest fires among countries around the Mediterranean basin have been observed. In the northern/western countries, Land Use-Land Cover (LULC) changes led to more hazardous landscapes, with consequent increases in fires. This contrasted with fire trends in southern/eastern countries. The recent incidence of large fires in some of the latter prompted the question of whether they are now following the path of their neighbors decades earlier. In this study, we investigated recent LULC changes in southwestern Turkey, focusing on those that could affect fire, and the factors driving them. To this end, LULC maps at different time steps (1975, 1990, 2000 and 2010) were obtained from Landsat images, together with relevant socioeconomic data. Generalized linear mixed models (GLMMs) were applied to assess the effects of socioeconomic and geophysical factors on the dominant LULC changes over time. Over the whole period studied, the most important LULC changes were deforestation followed by afforestation. Deforestation was positively related to high livestock density and proximity to villages and increased forest interfaces with other LULC types. We found no evidence that LULC changes were making the landscape more hazardous as there was a net decrease in fuels biomass and the landscape became more fragmented over time. However, despite the area being heavily used and relatively fragmented, large fires can occur driven by severe weather. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantifying longitudinal land use change from land degradation to rehabilitation in the headwaters of Tekeze-Atbara Basin, Ethiopia.

PubMed

Gebremicael, T G; Mohamed, Y A; van der Zaag, P; Hagos, E Y

2018-05-01

The spatiotemporal variability of the Land Use/Cover (LULC) is a strong influence on the land management and hydrological processes of a river basin. In particular in semi-arid regions like the Tekeze-Atbara (T-A) basin, accurate information about LULC change is a prerequisite for improved land and water management. The human-induced landscape transformations in the T-A basin, one of the main tributaries of the Nile River, were investigated for the last four decades (1972-2014). Separate LULC maps for the years 1972, 1989, 2001, and 2014 were developed based on satellite images, Geographic Information System (GIS) and ground information. Change detection analysis based on the transitional probability matrix was applied to identify systematic transitions among the LULC categories. The results show that >72% of the landscape has changed its category during the past 43years. LULC in the basin experienced significant shifts from one category to other categories by 61%, 47%, and 45%, in 1972-1989, 1989-2001, and 2001-2014, respectively. Although both net and swap (simultaneous gain and loss of a given LULC during a certain period) change occurred, the latter is more dominant. Natural vegetation cover, including forests, reduced drastically with the rapid expansion of crops, grazing areas and bare lands during the first two decades. However, vegetation started to recover since the 1990s, when some of the agricultural and bare lands have turned into vegetated areas. Forest land showed a continuous decreasing pattern, however, it has increased by 28% in the last period (2001-2014). In contrast, plantation trees have increased by 254% in the last three decades. The increase of vegetation cover is a result of intensive watershed management programs during the last two decades. The driving forces of changes were also discussed and rapid population growth and changing government policies were found to be the most important. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of land use and land cover on selected soil quality indicators in the headwater area of the Blue Nile basin of Ethiopia.

PubMed

Teferi, Ermias; Bewket, Woldeamlak; Simane, Belay

2016-02-01

Understanding changes in soil quality resulting from land use and land management changes is important to design sustainable land management plans or interventions. This study evaluated the influence of land use and land cover (LULC) on key soil quality indicators (SQIs) within a small watershed (Jedeb) in the Blue Nile Basin of Ethiopia. Factor analysis based on principal component analysis (PCA) was used to determine different SQIs. Surface (0-15 cm) soil samples with four replications were collected from five main LULC types in the watershed (i.e., natural woody vegetation, plantation forest, grassland, cultivated land, and barren land) and at two elevation classes (upland and midland), and 13 soil properties were measured for each replicate. A factorial (2 × 5) multivariate analysis of variance (MANOVA) showed that LULC and altitude together significantly affected organic matter (OM) levels. However, LULC alone significantly affected bulk density and altitude alone significantly affected bulk density, soil acidity, and silt content. Afforestation of barren land with eucalypt trees can significantly increase the soil OM in the midland part but not in the upland part. Soils under grassland had a significantly higher bulk density than did soils under natural woody vegetation indicating that de-vegetation and conversion to grassland could lead to soil compaction. Thus, the historical LULC change in the Jedeb watershed has resulted in the loss of soil OM and increased soil compaction. The study shows that a land use and management system can be monitored if it degrades or maintains or improves the soil using key soil quality indicators.

Combining Landsat and MODIS Data to Assess Trends in Bioproductivity in the Context of Land Use/Land Cover Change in Semi-arid West Africa

NASA Astrophysics Data System (ADS)

Herrmann, S. M.; Tappan, G. G.

2015-12-01

Semi-arid West Africa is experiencing change at many levels (climatic, agricultural, socioeconomic), which leaves an imprint on the land surface that can be characterized by a range of long term satellite observations. This research addresses the questions of (1) what dominant trajectories of land use/land cover (LULC) change have occurred in the region and (2) whether particular LULC trajectories are associated with significant positive or negative trends in bioproductivity. Two types of satellite data were used in complementary fashion: (1) Landsat multispectral data were visually interpreted using the traditional dot grid method, whereby the interpreter identifies and attributes LULC at point locations spaced 2km apart. Interpreted LULC maps were produced for three points in time (1975, 2000, 2013), and LULC change statistics extracted from them. (2) The MODIS Normalized Difference Vegetation Index (NDVI) was used as a proxy for bioproductivity and temporal trends of annual mean, maximum and minimum NDVI extracted at the sampling dots of known LULC for the period 2000-2013. The trends were analyzed with respect to the most prominent LULC classes and transitions, in particular from agriculture to natural vegetation and vice versa, and stratified by regions of similar mean annual precipitation. The most important LULC change over the almost 40-year period is a progressive expansion of agricultural lands, which has been responsible for major incursions into the region's remaining savannas and woodlands. To a lesser extent, abandonment of agriculture has given rise to long term fallow and eventually reversion to steppe or savanna. Another important change observed is the expansion of open steppe at the expense of savanna in the Sahel region. In terms of bioproductivity, while no significant trends in NDVI predominate overall, there are more instances of positive than of negative significant trends across the region. Contrary to our initial expectations, preliminary results show little systematic association between LULC change and direction and magnitude of trends in NDVI over the same time period 2000-2013. Though drastically altering vegetation composition and biodiversity, the expansion of agriculture into savanna is not found to be associated with a widespread loss of bioproductivity.

Impacts of Land Use/Cover Uncertainty on Predictions of Ecologically Relevant Flow Metrics

NASA Astrophysics Data System (ADS)

Kalin, L.; Dosdogru, F.

2016-12-01

Streamflow regimes are crucial parts of the ecological integrity in river systems. Although species are adopted to natural flow variability, permanent changes in flow regimes as a result of alterations in land use/cover of the watersheds can adversely impact ecosystem health. This study assessed the impacts of land use/cover (LULC) changes on ecologically relevant flow (ERF) metrics in the rapidly urbanizing upper Cahaba River basin in north-central Alabama. Cahaba River is the longest free-flowing river in the state of Alabama and is identified by the Nature Conservancy as one of the only eight "Hotspot of Biodiversity" in the contiguous United States. Cahaba River and its major tributaries support 69 rare and imperiled species, making it one of the most various aquatic ecosystems in the United States. SWAT model was used to generate daily streamflows, which were then fed into the Indicators of Hydrological Alterations (IHA) software to generate 38 key ERF metrics that capture high, low, and median flow, as well as flashiness, which are known to have significant impacts on flora and fauna. SWAT was calibrated and validated twice with two different sources of LULC. Model performances during calibration and validations were very good and were very similar with both LULC. The flow duration curves generated based on each LULC also look very similar. However, when we compared the ERF metrics significant differences were observed signifying the importance of LULC sources. The biggest differences were in Oct-Dec low flows, rise and fall rates of daily flows, annual maximum flow and average during month od October. This study shows that although model calibration can compensate for the differences in differences in LULC sources, when it comes to key ERF metrics the use of the most reliable LULC source is evident.

Hotspots of uncertainty in land-use and land-cover change projections: A global-scale model comparison

DOE PAGES

Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D. A.; ...

2016-05-02

Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socio-economic conditions. We attribute components of uncertainty to input data, modelmore » structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g. boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process as well as improving the allocation mechanisms of LULC change models remain important challenges. Furthermore, current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.« less

Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

PubMed

Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D A; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David A; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Van Meijl, Hans; Van Vliet, Jasper; Verburg, Peter H

2016-12-01

Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Hotspots of uncertainty in land-use and land-cover change projections: A global-scale model comparison

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D. A.

Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socio-economic conditions. We attribute components of uncertainty to input data, modelmore » structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g. boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process as well as improving the allocation mechanisms of LULC change models remain important challenges. Furthermore, current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.« less

Analysis of Land Use Change and Urbanization in the Kucukcekmece Water Basin (Istanbul, Turkey) with Temporal Satellite Data using Remote Sensing and GIS.

PubMed

Coskun, H Gonca; Alganci, Ugur; Usta, Gokce

2008-11-13

Accurate and timely information about land use and land cover (LULC) and its changes in urban areas are crucial for urban land management decision-making, ecosystem monitoring and urban planning. Also, monitoring and representation of urban sprawl and its effects on the LULC patterns and hydrological processes of an urbanized watershed is an essential part of water resource planning and management. This paper presents an image analysis study using multi temporal digital satellite imagery of LULC and changes in the Kucukcekmece Watershed (Metropolitan Istanbul, Turkey) from 1992 to 2006. The Kucukcekmece Basin includes portions of the Kucukcekmece District within the municipality of Istanbul so it faces a dramatic urbanization. An urban monitoring analysis approach was first used to implement a land cover classification. A change detection method controlled with ground truth information was then used to determine changes in land cover. During the study period, the variability and magnitude of hydrological components based on land-use patterns were cumulatively influenced by urban sprawl in the watershed. The proposed approach, which uses a combination of Remote Sensing (RS) and Geographical Information System (GIS) techniques, is an effective tool that enhances land-use monitoring, planning, and management of urbanized watersheds.

Analysis of Land Use Change and Urbanization in the Kucukcekmece Water Basin (Istanbul, Turkey) with Temporal Satellite Data using Remote Sensing and GIS

PubMed Central

Coskun, H. Gonca; Alganci, Ugur; Usta, Gokce

2008-01-01

Accurate and timely information about land use and land cover (LULC) and its changes in urban areas are crucial for urban land management decision-making, ecosystem monitoring and urban planning. Also, monitoring and representation of urban sprawl and its effects on the LULC patterns and hydrological processes of an urbanized watershed is an essential part of water resource planning and management. This paper presents an image analysis study using multi temporal digital satellite imagery of LULC and changes in the Kucukcekmece Watershed (Metropolitan Istanbul, Turkey) from 1992 to 2006. The Kucukcekmece Basin includes portions of the Kucukcekmece District within the municipality of Istanbul so it faces a dramatic urbanization. An urban monitoring analysis approach was first used to implement a land cover classification. A change detection method controlled with ground truth information was then used to determine changes in land cover. During the study period, the variability and magnitude of hydrological components based on land-use patterns were cumulatively influenced by urban sprawl in the watershed. The proposed approach, which uses a combination of Remote Sensing (RS) and Geographical Information System (GIS) techniques, is an effective tool that enhances land-use monitoring, planning, and management of urbanized watersheds. PMID:27873924

Modelling landscape dynamics with LST in protected areas of Western Ghats, Karnataka.

PubMed

Ramachandra, T V; Bharath, Setturu; Gupta, Nimish

2018-01-15

Forest ecosystems sustain biota on the earth as they are habitat to diverse biotic species, arrests soil erosion, play a crucial role in water cycle, sequester carbon, and helps in mitigating the impacts of global warming. Large scale land use land cover (LULC) change leading to deforestation is one of the drivers of global climate changes and alteration of biogeochemical cycles with significant consequences in ecosystem services and biodiversity. This has necessitated the investigation of LULC by mapping, monitoring and modelling spatio-temporal patterns and evaluating these in the context of human-environment interactions. The current work investigates LULC changes with temperature dynamics of select protected areas in Western Ghats. The land use analyses reveal changes in the forest cover across Kudremukh National Park (KNP), Rajiv Gandhi Tiger Reserve (RTR), Bandipur Tiger Reserve (BTR). KNP region has lost evergreen forest cover during 1973-2016 from 33.46 to 27.22%, while BTR lost deciduous cover from 61.69 to 47.3% due to mining, horticulture plantations, human habitations, etc. The LST increase has impacted regeneration of species with the induced water stress, etc. CA-Markov modelling was used for forecasting the likely land uses in 2026 and validation was done through Kappa indices. Results highlight decline of evergreen cover in KNP (9%) and deciduous cover in RTR (2%) followed by BTR (3%) with further expansion of plantations, which will impact biodiversity, hydrology and ecology. Insights of LULC dynamics help natural resource managers in evolving appropriate strategies to ensure conservation of threatened biota in Western Ghats. Copyright © 2017 Elsevier Ltd. All rights reserved.

The transparency, reliability and utility of tropical rainforest land-use and land-cover change models.

PubMed

Rosa, Isabel M D; Ahmed, Sadia E; Ewers, Robert M

2014-06-01

Land-use and land-cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: (1) a lack of openness with regard to describing and making available the model inputs and model code; (2) the difficulties of conducting appropriate model validations; and (3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land-use policies based on plausible future scenarios, but, to do that reliably may require further improvements in the discipline. © 2014 John Wiley & Sons Ltd.

Influence of land development on stormwater runoff from a mixed land use and land cover catchment.

PubMed

Paule-Mercado, M A; Lee, B Y; Memon, S A; Umer, S R; Salim, I; Lee, C-H

2017-12-01

Mitigating for the negative impacts of stormwater runoff is becoming a concern due to increased land development. Understanding how land development influences stormwater runoff is essential for sustainably managing water resources. In recent years, aggregate low impact development-best management practices (LID-BMPs) have been implemented to reduce the negative impacts of stormwater runoff on receiving water bodies. This study used an integrated approach to determine the influence of land development and assess the ecological benefits of four aggregate LID-BMPs in stormwater runoff from a mixed land use and land cover (LULC) catchment with ongoing land development. It used data from 2011 to 2015 that monitored 41 storm events and monthly LULC, and a Personalized Computer Storm Water Management Model (PCSWMM). The four aggregate LID-BMPs are: ecological (S1), utilizing pervious covers (S2), and multi-control (S3) and (S4). These LID-BMPs were designed and distributed in the study area based on catchment characteristics, cost, and effectiveness. PCSWMM was used to simulate the monitored storm events from 2014 (calibration: R 2 and NSE>0.5; RMSE <11) and 2015 (validation: R 2 and NSE>0.5; RMSE <12). For continuous simulation and analyzing LID-BMPs scenarios, the five-year (2011 to 2015) stormwater runoff data and LULC change patterns (only 2015 for LID-BMPs) were used. Results show that the expansion of bare land and impervious cover, soil alteration, and high amount of precipitation influenced the stormwater runoff variability during different phases of land development. The four aggregate LID-BMPs reduced runoff volume (34%-61%), peak flow (6%-19%), and pollutant concentrations (53%-83%). The results of this study, in addition to supporting local LULC planning and land development activities, also could be applied to input data for empirical modeling, and designing sustainable stormwater management guidelines and monitoring strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of land use/land cover and climate changes on surface runoff in a semi-humid and semi-arid transition zone in northwest China

NASA Astrophysics Data System (ADS)

Yin, Jing; He, Fan; Jiu Xiong, Yu; Qiu, Guo Yu

2017-01-01

Water resources, which are considerably affected by land use/land cover (LULC) and climate changes, are a key limiting factor in highly vulnerable ecosystems in arid and semi-arid regions. The impacts of LULC and climate changes on water resources must be assessed in these areas. However, conflicting results regarding the effects of LULC and climate changes on runoff have been reported in relatively large basins, such as the Jinghe River basin (JRB), which is a typical catchment (> 45 000 km2) located in a semi-humid and arid transition zone on the central Loess Plateau, northwest China. In this study, we focused on quantifying both the combined and isolated impacts of LULC and climate changes on surface runoff. We hypothesized that under climatic warming and drying conditions, LULC changes, which are primarily caused by intensive human activities such as the Grain for Green Program, will considerably alter runoff in the JRB. The Soil and Water Assessment Tool (SWAT) was adopted to perform simulations. The simulated results indicated that although runoff increased very little between the 1970s and the 2000s due to the combined effects of LULC and climate changes, LULC and climate changes affected surface runoff differently in each decade, e.g., runoff increased with increased precipitation between the 1970s and the 1980s (precipitation contributed to 88 % of the runoff increase). Thereafter, runoff decreased and was increasingly influenced by LULC changes, which contributed to 44 % of the runoff changes between the 1980s and 1990s and 71 % of the runoff changes between the 1990s and 2000s. Our findings revealed that large-scale LULC under the Grain for Green Program has had an important effect on the hydrological cycle since the late 1990s. Additionally, the conflicting findings regarding the effects of LULC and climate changes on runoff in relatively large basins are likely caused by uncertainties in hydrological simulations.

Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries

USGS Publications Warehouse

Sohl, Terry L.; Dornbierer, Jordan; Wika, Steve; Sayler, Kristi L.; Quenzer, Robert

2017-01-01

Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.

Use of Land Use Land Cover Change Mapping Products in Aiding Coastal Habitat Conservation and Restoration Efforts of the Mobile Bay NEP

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Swann, Roberta; Smooth, James

2010-01-01

The Mobile Bay region has undergone significant land use land cover change (LULC) over the last 35 years, much of which is associated with urbanization. These changes have impacted the region s water quality and wildlife habitat availability. In addition, much of the region is low-lying and close to the Gulf, which makes the region vulnerable to hurricanes, climate change (e.g., sea level rise), and sometimes man-made disasters such as the Deepwater Horizon (DWH) oil spill. Land use land cover change information is needed to help coastal zone managers and planners to understand and mitigate the impacts of environmental change on the region. This presentation discusses selective results of a current NASA-funded project in which Landsat data over a 34-year period (1974-2008) is used to produce, validate, refine, and apply land use land cover change products to aid coastal habitat conservation and restoration needs of the Mobile Bay National Estuary Program (MB NEP). The project employed a user defined classification scheme to compute LULC change mapping products for the entire region, which includes the majority of Mobile and Baldwin counties. Additional LULC change products have been computed for select coastal HUC-12 sub-watersheds adjacent to either Mobile Bay or the Gulf of Mexico, as part of the MB NEP watershed profile assessments. This presentation will include results of additional analyses of LULC change for sub-watersheds that are currently high priority areas, as defined by MB NEP. Such priority sub-watersheds include those that are vulnerable to impacts from the DWH oil spill, as well as sub-watersheds undergoing urbanization. Results demonstrating the nature and permanence of LULC change trends for these higher priority sub-watersheds and results characterizing change for the entire 34-year period and at approximate 10-year intervals across this period will also be presented. Future work will include development of value-added coastal habitat quality assessment products that will be used by the MB NEP and its partners in the planning of coastal conservation and restoration activities.

A Landsat-Based Assessment of Mobile Bay Land Use and Land Cover Change from 1974 to 2008

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Ellis, Jean; Smoot, James; Swann, Roberta; Graham, William

2009-01-01

The Mobile Bay region has experienced noteworthy land use and land cover (LULC) change in the latter half of the 20th century. Accompanying this change has been urban expansion and a reduction of rural land uses. Much of this LULC change has reportedly occurred since the landfall of Hurricane Frederic in 1979. The Mobile Bay region provides great economic and ecologic benefits to the Nation, including important coastal habitat for a broad diversity of fisheries and wildlife. Regional urbanization threatens the estuary s water quality and aquatic-habitat dependent biota, including commercial fisheries and avian wildlife. Coastal conservation and urban land use planners require additional information on historical LULC change to support coastal habitat restoration and resiliency management efforts. This presentation discusses results of a Gulf of Mexico Application Pilot project that was conducted in 2008 to quantify and assess LULC change from 1974 to 2008. This project was led by NASA Stennis Space Center and involved multiple Gulf of Mexico Alliance (GOMA) partners, including the Mobile Bay National Estuary Program (NEP), the U.S. Army Corps of Engineers, the National Oceanic and Atmospheric Administration s (NOAA s) National Coastal Data Development Center (NCDDC), and the NOAA Coastal Services Center. Nine Landsat images were employed to compute LULC products because of their availability and suitability for the application. The project also used Landsat-based national LULC products, including coastal LULC products from NOAA s Coastal Change & Analysis Program (C-CAP), available at 5-year intervals since 1995. Our study was initiated in part because C-CAP LULC products were not available to assess the region s urbanization prior to 1995 and subsequent to post Hurricane Katrina in 2006. This project assessed LULC change across the 34-year time frame and at decadal and middecadal scales. The study area included the majority of Mobile and Baldwin counties that encompass Mobile Bay. In doing so, each date of Landsat data was classified using an end-user defined modified Anderson level 1 classification scheme. LULC classifications were refined using a decision rule approach in conjunction with available C-CAP products. Individual dates of LULC classifications were validated by image interpretation of stratified random locations on raw Landsat color composite imagery in combination with higher resolution remote sensing and in-situ reference data. The results indicate that during the 34-year study period, urban areas increased from 96,688 to 150,227 acres, representing a 55.37% increase, or 1.63% per annum. Most of the identified urban expansion results from conversion of rural forest and agriculture to urban cover types. Final LULC mapping and metadata products were produced for the entire study area as well as watersheds of concern within the study area. Final project products, including LULC trend information, were incorporated into the Mobile Bay NEP State of the Bay report. Products and metadata were transferred to NOAA NCDDC to allow free online accessibility and use by GOMA partners and by the public.

Spatial-Temporal Variations of Water Quality and Its Relationship to Land Use and Land Cover in Beijing, China

PubMed Central

Chen, Xiang; Zhou, Weiqi; Pickett, Steward T. A.; Li, Weifeng; Han, Lijian

2016-01-01

Rapid urbanization with intense land use and land cover (LULC) change and explosive population growth has a great impact on water quality. The relationship between LULC characteristics and water quality provides important information for non-point sources (NPS) pollution management. In this study, we first quantified the spatial-temporal patterns of five water quality variables in four watersheds with different levels of urbanization in Beijing, China. We then examined the effects of LULC on water quality across different scales, using Pearson correlation analysis, redundancy analysis, and multiple regressions. The results showed that water quality was improved over the sampled years but with no significant difference (p > 0.05). However, water quality was significantly different among nonurban and both exurban and urban sites (p < 0.05). Forest land was positively correlated with water quality and affected water quality significantly (p < 0.05) within a 200 m buffer zone. Impervious surfaces, water, and crop land were negatively correlated with water quality. Crop land and impervious surfaces, however, affected water quality significantly (p < 0.05) for buffer sizes greater than 800 m. Grass land had different effects on water quality with the scales. The results provide important insights into the relationship between LULC and water quality, and thus for controlling NPS pollution in urban areas. PMID:27128934

Analyzing the effects of urban expansion on land surface temperature patterns by landscape metrics: a case study of Isfahan city, Iran.

PubMed

Madanian, Maliheh; Soffianian, Ali Reza; Koupai, Saeid Soltani; Pourmanafi, Saeid; Momeni, Mehdi

2018-03-03

Urban expansion can cause extensive changes in land use and land cover (LULC), leading to changes in temperature conditions. Land surface temperature (LST) is one of the key parameters that should be considered in the study of urban temperature conditions. The purpose of this study was, therefore, to investigate the effects of changes in LULC due to the expansion of the city of Isfahan on LST using landscape metrics. To this aim, two Landsat 5 and Landsat 8 images, which had been acquired, respectively, on August 2, 1985, and July 4, 2015, were used. The support vector machine method was then used to classify the images. The results showed that Isfahan city had been encountered with an increase of impervious surfaces; in fact, this class covered 15% of the total area in 1985, while this value had been increased to 30% in 2015. Then LST zoning maps were created, indicating that the bare land and impervious surfaces categories were dominant in high temperature zones, while in the zones where water was present or NDVI was high, LST was low. Then, the landscape metrics in each of the LST zones were analyzed in relation to the LULC changes, showing that LULC changes due to urban expansion changed such landscape properties as the percentage of landscape, patch density, large patch index, and aggregation index. This information could be beneficial for urban planners to monitor and manage changes in the LULC patterns.

Creating high-resolution time series land-cover classifications in rapidly changing forested areas with BULC-U in Google Earth Engine

NASA Astrophysics Data System (ADS)

Cardille, J. A.; Lee, J.

2017-12-01

With the opening of the Landsat archive, there is a dramatically increased potential for creating high-quality time series of land use/land-cover (LULC) classifications derived from remote sensing. Although LULC time series are appealing, their creation is typically challenging in two fundamental ways. First, there is a need to create maximally correct LULC maps for consideration at each time step; and second, there is a need to have the elements of the time series be consistent with each other, without pixels that flip improbably between covers due only to unavoidable, stray classification errors. We have developed the Bayesian Updating of Land Cover - Unsupervised (BULC-U) algorithm to address these challenges simultaneously, and introduce and apply it here for two related but distinct purposes. First, with minimal human intervention, we produced an internally consistent, high-accuracy LULC time series in rapidly changing Mato Grosso, Brazil for a time interval (1986-2000) in which cropland area more than doubled. The spatial and temporal resolution of the 59 LULC snapshots allows users to witness the establishment of towns and farms at the expense of forest. The new time series could be used by policy-makers and analysts to unravel important considerations for conservation and management, including the timing and location of past development, the rate and nature of changes in forest connectivity, the connection with road infrastructure, and more. The second application of BULC-U is to sharpen the well-known GlobCover 2009 classification from 300m to 30m, while improving accuracy measures for every class. The greatly improved resolution and accuracy permits a better representation of the true LULC proportions, the use of this map in models, and quantification of the potential impacts of changes. Given that there may easily be thousands and potentially millions of images available to harvest for an LULC time series, it is imperative to build useful algorithms requiring minimal human intervention. Through image segmentation and classification, BULC-U allows us to use both the spectral and spatial characteristics of imagery to sharpen classifications and create time series. It is hoped that this study may allow us and other users of this new method to consider time series across ever larger areas.

Weakening of Indian Summer Monsoon Rainfall due to Changes in Land Use Land Cover

PubMed Central

Paul, Supantha; Ghosh, Subimal; Oglesby, Robert; Pathak, Amey; Chandrasekharan, Anita; Ramsankaran, RAAJ

2016-01-01

Weakening of Indian summer monsoon rainfall (ISMR) is traditionally linked with large-scale perturbations and circulations. However, the impacts of local changes in land use and land cover (LULC) on ISMR have yet to be explored. Here, we analyzed this topic using the regional Weather Research and Forecasting model with European Center for Medium range Weather Forecast (ECMWF) reanalysis data for the years 2000–2010 as a boundary condition and with LULC data from 1987 and 2005. The differences in LULC between 1987 and 2005 showed deforestation with conversion of forest land to crop land, though the magnitude of such conversion is uncertain because of the coarse resolution of satellite images and use of differential sources and methods for data extraction. We performed a sensitivity analysis to understand the impacts of large-scale deforestation in India on monsoon precipitation and found such impacts are similar to the observed changes in terms of spatial patterns and magnitude. We found that deforestation results in weakening of the ISMR because of the decrease in evapotranspiration and subsequent decrease in the recycled component of precipitation. PMID:27553384

Land-use/land-cover drives variation in the specific inherent optical properties of estuaries

EPA Science Inventory

Changes in land-use/land-cover (LULC) can impact the exports of optically and biogeochemically active constituents to estuaries. Specific inherent optical properties (SIOPs) of estuarine optically active constituents (OACs) are directly related to the composition of the OACs, and...

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

USGS Publications Warehouse

Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

2015-01-01

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

Relation between inherent optical properties and land use and land cover across Gulf Coast estuaries

EPA Science Inventory

Land use and land cover (LULC) can affect the watershed exports of optically active constituents such as suspended particulate matter and colored dissolved organic matter, and in turn affect estuarine optical properties. We collected optical data from six estuaries in the northea...

Combining Landsat and MODIS Long Term Data Records to Assess Trends in Bioproductivity in the Context of Land Use/Land Cover Change in Semi-Arid West Africa

NASA Astrophysics Data System (ADS)

Herrmann, S. M.; Tappan, G. G.

2014-12-01

Semi-arid West Africa is experiencing change at many levels (climatic, agricultural, socioeconomic), which leaves an imprint on the land surface that can be characterized by a range of long term satellite observations. This research addresses the questions of (1) what dominant trajectories of land use/land cover (LULC) change have occurred in the region and (2) whether particular LULC trajectories are associated with significant positive or negative trends in bioproductivity. Two types of satellite data were used in complementary fashion: (1) Landsat multispectral data were visually interpreted using the traditional dot grid method, whereby the interpreter identifies and attributes LULC at point locations spaced 2km apart. Interpreted LULC maps were produced for three points in time (1975, 2000, 2013), and LULC change statistics extracted from them. (2) The MODIS Normalized Difference Vegetation Index (NDVI) was used as a proxy for bioproductivity and temporal trends of annual mean, maximum and minimum NDVI extracted at the sampling dots of known LULC for the period 2000-2013. The trends were analyzed with respect to the most prominent LULC classes and transitions, in particular from agriculture to natural vegetation and vice versa, and stratified by regions of similar mean annual precipitation. The most important LULC change over the almost 40-year period is a progressive expansion of agricultural lands, which has been responsible for major incursions into the region's remaining savannas and woodlands. To a lesser extent, abandonment of agriculture has given rise to long term fallow and eventually reversion to steppe or savanna. Another important change observed is the expansion of open steppe at the expense of savanna in the Sahel region. In terms of bioproductivity, while no significant trends in NDVI predominate overall, there are more instances of positive than of negative significant trends across the region. Contrary to our initial expectations, preliminary results show little systematic association between LULC change and direction and magnitude of trends in NDVI over the same time period 2000-2013. Though drastically altering vegetation composition and biodiversity, the expansion of agriculture into savanna is not found to be associated with a widespread loss of bioproductivity.

Projecting the land cover change and its environmental impacts in the Cedar River Basin in the Midwestern United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Sohl, Terry L.; Young, Claudia

2013-01-01

The physical surface of the Earth is in constant change due to climate forcing and human activities. In the Midwestern United States, urban area, farmland, and dedicated energy crop (e.g., switchgrass) cultivation are predicted to expand in the coming decades, which will lead to changes in hydrological processes. This study is designed to (1) project the land use and land cover (LULC) by mid-century using the FORecasting SCEnarios of future land-use (FORE-SCE) model under the A1B greenhouse gas emission scenario (future condition) and (2) assess its potential impacts on the water cycle and water quality against the 2001 baseline condition in the Cedar River Basin using the physically based soil and water assessment tool (SWAT). We compared the baseline LULC (National Land Cover data 2001) and 2050 projection, indicating substantial expansions of urban area and pastureland (including the cultivation of bioenergy crops) and a decrease in rangeland. We then used the above two LULC maps as the input data to drive the SWAT model, keeping other input data (e.g., climate) unchanged to isolate the LULC change impacts. The modeling results indicate that quick-response surface runoff would increase significantly (about 10.5%) due to the projected urban expansion (i.e., increase in impervious areas), and the baseflow would decrease substantially (about 7.3%) because of the reduced infiltration. Although the net effect may cause an increase in water yield, the increased variability may impede its use for public supply. Additionally, the cultivation of bioenergy crops such as switchgrass in the newly added pasture lands may further reduce the soil water content and lead to an increase in nitrogen loading (about 2.5% increase) due to intensified fertilizer application. These study results will be informative to decision makers for sustainable water resource management when facing LULC change and an increasing demand for biofuel production in this area.

Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

USDA-ARS?s Scientific Manuscript database

In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified ...

Future integrated aquifer vulnerability assessment considering land use / land cover and climate change using DRASTIC and SWAT

NASA Astrophysics Data System (ADS)

Jang, W.; Engel, B.; Chaubey, I.

2015-12-01

Climate change causes significant changes to temperature regimes and precipitation patterns across the world. Such alterations in climate pose serious risks for not only inland freshwater ecosystems but also groundwater systems, and may adversely affect numerous critical services they provide to humans. All groundwater results from precipitation, and precipitation is affected by climate change. Climate change is also influenced by land use / land cover (LULC) change and vice versa. According to Intergovernmental Panel on Climate Change (IPCC) reports, climate change is caused by global warming which is generated by the increase of greenhouse gas (GHG) emissions in the atmosphere. LULC change is a major driving factor causing an increase in GHG emissions. LULC change data (years 2006-2100) will be produced by the Land Transformation Model (LTM) which simulates spatial patterns of LULC change over time. MIROC5 (years 2006-2100) will be obtained considering GCMs and ensemble characteristics such as resolution and trend of temperature and precipitation which is a consistency check with observed data from local weather stations and historical data from GCMs output data. Thus, MIROC5 will be used to account for future climate change scenarios and relationship between future climate change and alteration of groundwater quality in this study. For efficient groundwater resources management, integrated aquifer vulnerability assessments (= intrinsic vulnerability + hazard potential assessment) are required. DRASTIC will be used to evaluate intrinsic vulnerability, and aquifer hazard potential will be evaluated by Soil and Water Assessment Tool (SWAT) which can simulate pollution potential from surface and transport properties of contaminants. Thus, for effective integrated aquifer vulnerability assessment for LULC and climate change in the Midwestern United States, future projected LULC and climate data from the LTM and GCMs will be incorporated with DRASTIC and SWAT. It is hypothesized that: 1) long-term future hydrology and water quality in surface and subsurface drainage areas will be influenced by LULC and climate change, and 2) this approach will be useful to identify specific areas contributing the most pollutants to aquifers due to LULC and climate change.

National climate assessment technical report on the impacts of climate and land use and land cover change

USGS Publications Warehouse

Loveland, Thomas; Mahmood, Rezaul; Patel-Weynand, Toral; Karstensen, Krista; Beckendorf, Kari; Bliss, Norman; Carleton, Andrew

2012-01-01

This technical report responds to the recognition by the U.S. Global Change Research Program (USGCRP) and the National Climate Assessment (NCA) of the importance of understanding how land use and land cover (LULC) affects weather and climate variability and change and how that variability and change affects LULC. Current published, peer-reviewed, scientific literature and supporting data from both existing and original sources forms the basis for this report's assessment of the current state of knowledge regarding land change and climate interactions. The synthesis presented herein documents how current and future land change may alter environment processes and in turn, how those conditions may affect both land cover and land use by specifically investigating, * The primary contemporary trends in land use and land cover, * The land-use and land-cover sectors and regions which are most affected by weather and climate variability,* How land-use practices are adapting to climate change, * How land-use and land-cover patterns and conditions are affecting weather and climate, and * The key elements of an ongoing Land Resources assessment. These findings present information that can be used to better assess land change and climate interactions in order to better assess land management and adaptation strategies for future environmental change and to assist in the development of a framework for an ongoing national assessment.

Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

Seasonal Response of Overland Flow and Sediment Loading to Climate and Land Use Land Cover Change in the Apalachicola River, Florida

NASA Astrophysics Data System (ADS)

Hovenga, P. A.; Wang, D.; Medeiros, S. C.; Hagen, S. C.

2015-12-01

Located in Florida's panhandle, the Apalachicola River is the southernmost reach of the Apalachicola-Chattahoochee-Flint (ACF) River basin. Streamflow and sediment drains to Apalachicola Bay within the Northern Gulf of Mexico, resulting in a direct influence on the ecology of the region, in particular seagrass and oyster production. This study examines the seasonal response of overland flow and sediment loading in the Apalachicola River under projected climate change scenarios and land use land cover (LULC) change. A hydrologic model using the Soil Water Assessment Tool (SWAT) was developed for the Apalachicola region to simulate daily discharge and sediment load under present (circa 2000) and future conditions (circa 2100) to understand how parameters respond over a seasonal time frame to changes in climate only, LULC only, and coupled climate / LULC. These physically-based models incorporate digital elevation model (DEM), LULC, soil maps, climate data, and management controls. Long Ashton Research Station-Weather Generator (LARS-WG) was used to create stochastic temperature and precipitation inputs from four Global Climate Models (GCM), each under Intergovernmental Panel on Climate Change (IPCC) carbon emission scenarios for A1B, A2, and B1. These scenarios represent potential future emissions resulting from a range driving forces, e.g. social, economic, environmental, and technologic. Projected 2100 LULC data provided by the United States Geological Survey (USGS) EROS Center was incorporated for each corresponding IPCC scenario. Results from this study can be used to further understand climate and LULC implications to the Apalachicola Bay and surrounding region as well as similar fluvial estuaries while providing tools to better guide management and mitigation practices.

Characterizing human-environment interactions in the Galapagos Islands: A case study of land use/land cover dynamics in Isabela Island

NASA Astrophysics Data System (ADS)

McCleary, Amy L.

This dissertation examines contemporary land use and land cover (LULC) change in the communities and protected areas of Isabela Island to provide insights into human-environment interactions in the Galapagos Islands of Ecuador. The growing human presence in Galapagos over the last four decades has been accompanied by significant changes in LULC on inhabited islands in the archipelago. Local stakeholders and decision-makers have recently called for a more integrative approach to understanding interactions between people and the environment in the archipelago. This study is guided by two complementary bodies of work situated within the human-environment tradition of Geography---land change science and landscape ecology. First, support Vector Machine (SVM) and Object Based Image Analysis (OBIA) classifiers are evaluated for mapping LULC from high spatial resolution satellite images. The results show that thematic LULC classifications produced by OBIA are more accurate overall than those generated by SVM. However, important tradeoffs exist between improvements in classification accuracy and processing requirements. The composition and spatial configuration of LULC change are then mapped and quantified from a time series of QuickBird and WorldView-2 satellite images from 2003 to 2010. The pattern metric and change detection analyses reveal that land use change is extensive within the communities due to the expansion and consolidation of built-up areas, and fragmentation of and declines in agriculture. The Galapagos National Park is primarily transformed by exotic plant invasion, forests expansion, and shrinking coastal lagoons. Patterns of agricultural land abandonment, plant invasion, and forest expansion over the same period are described from pattern metric and overlay analyses. Potential drivers of these LULC transitions are identified from logistic regression models, descriptive statistics of agricultural surveys and population censuses, and interviews with landowners. The results reveal that agricultural abandonment is widespread throughout Isabela, and many abandoned fields are invaded by introduced plants, such as guava. Biophysical and geographic factors, such as topography and distance to roads, do not significantly explain patterns of agricultural land abandonment or associated land cover transitions at the pixel level. However, rural-urban migration, declines in the profitability of agriculture, and small labor pools appear to influence agricultural abandonment.

Monitoring urban expansion and its effects on land use and land cover changes in Guangzhou city, China.

PubMed

Wu, Yanyan; Li, Shuyuan; Yu, Shixiao

2016-01-01

There are widespread concerns about urban sprawl in China. In response, modeling and assessing urban expansion and subsequent land use and land cover (LULC) changes have become important approaches to support decisions about appropriate development and land resource use. Guangzhou, a major metropolitan city in South China, has experienced rapid urbanization and great economic growth in the past few decades. This study applied a series of Landsat images to assess the urban expansion and subsequent LULC changes over 35 years, from 1979 to 2013. From start to end, urban expansion increased by 1512.24 km(2) with an annual growth rate of 11.25 %. There were four stages of urban growth: low rates from 1979 to 1990, increased rates from 1990 to 2001, high rates from 2001 to 2009, and steady increased rates from 2009 to 2013. There were also three different urban growth types in these different stages: edge-expansion growth, infilling growth, and spontaneous growth. Other land cover, such as cropland, forest, and mosaics of cropland and natural vegetation, were severely impacted as a result. To analyze these changes, we used landscape metrics to characterize the changes in the spatial patterns across the Guangzhou landscape and the impacts of urban growth on other types of land cover. The significant changes in LULC and urban expansion were highly correlated with economic development, population growth, technical progress, policy elements, and other similar indexes.

US GeoData Available Through the Internet

USGS Publications Warehouse

,

2000-01-01

The U.S. Geological Survey (USGS) offers certain US GeoData data sets through the Internet. They can be retrieved using the World Wide Web or anonymous File Transfer Protocol (FTP). The data bases and their directory paths are as follows: * 1:24,000-scale digital line graph data in SDTS format (/pub/data/DLG/24K) * 1:2,000,000-scale digital line graph data in SDTS format (/pub/data/DLG/2M) * 1:100,000-scale digital line graph data (/pub/data/DLG/100K) * 1:100,000-scale land use and land cover data (/pub/data/LULC/100K) * 1:250,000-scale land use and land cover data (/pub/data/LULC/250K) * 1-degree digital elevation model data (/pub/data/DEM/250)

Afloat in a Boat: Linking Land Use / Land Cover to the Spatial Evolution of Water Quality along a Blackwater Stream

NASA Astrophysics Data System (ADS)

Neville, J.; Vose, J. M.; Nichols, E. G.; Jass, T. L.; Emanuel, R. E.; McRae, J.

2016-12-01

Water quality and land use/land cover (LULC) are linked intimately in many watersheds, although exact relationships are often nonlinear and sometimes complex. Together with watershed topography, LULC can affect water quality in various ways. As such, attributing water quality characteristics to LULC variations (either in space or time) can be difficult. Many studies seek to understand these relationships from a Eulerian reference frame, which typically involves many samples or observations through time at a fixed location. Here we explore an alternative approach to understanding relationships between LULC and water quality that relies on a Lagrangian, or moving, reference frame, in which the effects of LULC and watershed topography on water quality can be observed through a different lens. We studied three reaches of the Lumber River, a blackwater stream in North Carolina's Coastal Plain, to assess relationships between LULC and water quality in a watershed that is a patchwork of agriculture, forests, wetlands and developed land. Our study combines spatially intensive water quality measurements (temperature, specific conductance, dissolved oxygen, pH and nitrate concentration), collected by boat, with geospatial analyses of LULC to understand influences on the spatial evolution of reach-scale water quality. In particular, we investigate relationships between spatial patterns in nitrate and the changing spatial characteristics of the watershed integrated at sampling points along each reach. We also assess relationships between nitrate and other water quality variables, such as pH, temperature, and dissolved oxygen to better understand the potential role of in-stream nutrient processing in observed spatial patterns. This work has implications for the regulation and management of agriculture, wetlands, and forests in a region that has long struggled to balance agriculture, a major economic driver, with water quality, a major concern for recreation and cultural practices locally and for nutrient sensitive coastal environments downstream.

Estimation and comparision of curve numbers based on dynamic land use land cover change, observed rainfall-runoff data and land slope

NASA Astrophysics Data System (ADS)

Deshmukh, Dhananjay Suresh; Chaube, Umesh Chandra; Ekube Hailu, Ambaye; Aberra Gudeta, Dida; Tegene Kassa, Melaku

2013-06-01

The CN represents runoff potential is estimated using three different methods for three watersheds namely Barureva, Sher and Umar watershed located in Narmada basin. Among three watersheds, Sher watershed has gauging site for the runoff measurements. The CN computed from the observed rainfall-runoff events is termed as CN(PQ), land use and land cover (LULC) is termed as CN(LU) and the CN based on land slope is termed as SACN2. The estimated annual CN(PQ) varies from 69 to 87 over the 26 years data period with median 74 and average 75. The range of CN(PQ) from 70 to 79 are most significant values and these truly represent the AMC II condition for the Sher watershed. The annual CN(LU) was computed for all three watersheds using GIS and the years are 1973, 1989 and 2000. Satellite imagery of MSS, TM and ETM+ sensors are available for these years and obtained from the Global Land Cover Facility Data Center of Maryland University USA. The computed CN(LU) values show rising trend with the time and this trend is attributed to expansion of agriculture area in all watersheds. The predicted values of CN(LU) with time (year) can be used to predict runoff potential under the effect of change in LULC. Comparison of CN(LU) and CN(PQ) values shows close agreement and it also validates the classification of LULC. The estimation of slope adjusted SA-CN2 shows the significant difference over conventional CN for the hilly forest lands. For the micro watershed planning, SCS-CN method should be modified to incorporate the effect of change in land use and land cover along with effect of land slope.

Simulation of Urban Heat Island Mitigation Strategies in Atlanta, GA Using High-Resolution Land Use/Land Cover Data Set to Enhance Meteorological Modeling

NASA Technical Reports Server (NTRS)

Crosson, William L.; Dembek, Scott; Estes, Maurice G., Jr.; Limaye, Ashutosh S.; Lapenta, William; Quattrochi, Dale A.; Johnson, Hoyt; Khan, Maudood

2006-01-01

The specification of land use/land cover (LULC) and associated land surface parameters in meteorological models at all scales has a major influence on modeled surface energy fluxes and boundary layer states. In urban areas, accurate representation of the land surface may be even more important than in undeveloped regions due to the large heterogeneity within the urban area. Deficiencies in the characterization of the land surface related to the spatial or temporal resolution of the data, the number of LULC classes defined, the accuracy with which they are defined, or the degree of heterogeneity of the land surface properties within each class may degrade the performance of the models. In this study, an experiment was conducted to test a new high-resolution LULC data set for meteorological simulations for the Atlanta, Georgia metropolitan area using a mesoscale meteorological model and to evaluate the effects of urban heat island (UHI) mitigation strategies on modeled meteorology for 2030. Simulation results showed that use of the new LULC data set reduced a major deficiency of the land use data used previously, specifically the poor representation of urban and suburban land use. Performance of the meteorological model improved substantially, with the overall daytime cold bias reduced by over 30%. UHI mitigation strategies were projected to offset much of a predicted urban warming between 2000 and 2030. In fact, for the urban core, the cooling due to UHI mitigation strategies was slightly greater than the warming associated with urbanization over this period. For the larger metropolitan area, cooling only partially offset the projected warming trend.

Effects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States

USGS Publications Warehouse

Sleeter, Benjamin M.; Liu, Jinxun; Daniel, Colin; Rayfield, Bronwyn; Sherba, Jason; Hawbaker, Todd J.; Zhu, Zhiliang; Selmants, Paul; Loveland, Thomas R.

2018-01-01

Changes in land use and land cover (LULC) can have profound effects on terrestrial carbon dynamics, yet their effects on the global carbon budget remain uncertain. While land change impacts on ecosystem carbon dynamics have been the focus of numerous studies, few efforts have been based on observational data incorporating multiple ecosystem types spanning large geographic areas over long time horizons. In this study we use a variety of synoptic-scale remote sensing data to estimate the effect of LULC changes associated with urbanization, agricultural expansion and contraction, forest harvest, and wildfire on the carbon balance of terrestrial ecosystems (forest, grasslands, shrublands, and agriculture) in the conterminous United States (i.e. excluding Alaska and Hawaii) between 1973 and 2010. We estimate large net declines in the area of agriculture and forest, along with relatively small increases in grasslands and shrublands. The largest net change in any class was an estimated gain of 114 865 km2 of developed lands, an average rate of 3282 km2 yr−1. On average, US ecosystems sequestered carbon at an annual rate of 254 Tg C yr−1. In forest lands, the net sink declined by 35% over the study period, largely a result of land-use legacy, increasing disturbances, and reductions in forest area due to land use conversion. Uncertainty in LULC change data contributed to a ~16% margin of error in the annual carbon sink estimate prior to 1985 (approximately ±40 Tg C yr−1). Improvements in LULC and disturbance mapping starting in the mid-1980s reduced this uncertainty by ~50% after 1985. We conclude that changes in LULC are a critical component to understanding ecosystem carbon dynamics, and continued improvements in detection, quantification, and attribution of change have the potential to significantly reduce current uncertainties.

Effects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States

NASA Astrophysics Data System (ADS)

Sleeter, Benjamin M.; Liu, Jinxun; Daniel, Colin; Rayfield, Bronwyn; Sherba, Jason; Hawbaker, Todd J.; Zhu, Zhiliang; Selmants, Paul C.; Loveland, Thomas R.

2018-04-01

Changes in land use and land cover (LULC) can have profound effects on terrestrial carbon dynamics, yet their effects on the global carbon budget remain uncertain. While land change impacts on ecosystem carbon dynamics have been the focus of numerous studies, few efforts have been based on observational data incorporating multiple ecosystem types spanning large geographic areas over long time horizons. In this study we use a variety of synoptic-scale remote sensing data to estimate the effect of LULC changes associated with urbanization, agricultural expansion and contraction, forest harvest, and wildfire on the carbon balance of terrestrial ecosystems (forest, grasslands, shrublands, and agriculture) in the conterminous United States (i.e. excluding Alaska and Hawaii) between 1973 and 2010. We estimate large net declines in the area of agriculture and forest, along with relatively small increases in grasslands and shrublands. The largest net change in any class was an estimated gain of 114 865 km2 of developed lands, an average rate of 3282 km2 yr‑1. On average, US ecosystems sequestered carbon at an annual rate of 254 Tg C yr‑1. In forest lands, the net sink declined by 35% over the study period, largely a result of land-use legacy, increasing disturbances, and reductions in forest area due to land use conversion. Uncertainty in LULC change data contributed to a ~16% margin of error in the annual carbon sink estimate prior to 1985 (approximately ±40 Tg C yr‑1). Improvements in LULC and disturbance mapping starting in the mid-1980s reduced this uncertainty by ~50% after 1985. We conclude that changes in LULC are a critical component to understanding ecosystem carbon dynamics, and continued improvements in detection, quantification, and attribution of change have the potential to significantly reduce current uncertainties.

Impacts of land cover changes on climate trends in Jiangxi province China.

PubMed

Wang, Qi; Riemann, Dirk; Vogt, Steffen; Glaser, Rüdiger

2014-07-01

Land-use/land-cover (LULC) change is an important climatic force, and is also affected by climate change. In the present study, we aimed to assess the regional scale impact of LULC on climate change using Jiangxi Province, China, as a case study. To obtain reliable climate trends, we applied the standard normal homogeneity test (SNHT) to surface air temperature and precipitation data for the period 1951-1999. We also compared the temperature trends computed from Global Historical Climatology Network (GHCN) datasets and from our analysis. To examine the regional impacts of land surface types on surface air temperature and precipitation change integrating regional topography, we used the observation minus reanalysis (OMR) method. Precipitation series were found to be homogeneous. Comparison of GHCN and our analysis on adjusted temperatures indicated that the resulting climate trends varied slightly from dataset to dataset. OMR trends associated with surface vegetation types revealed a strong surface warming response to land barrenness and weak warming response to land greenness. A total of 81.1% of the surface warming over vegetation index areas (0-0.2) was attributed to surface vegetation type change and regional topography. The contribution of surface vegetation type change decreases as land cover greenness increases. The OMR precipitation trend has a weak dependence on surface vegetation type change. We suggest that LULC integrating regional topography should be considered as a force in regional climate modeling.

Landscape trends in Mid-Atlantic and Southeastern United States ecoregions

USGS Publications Warehouse

Griffith, J.A.; Stehman, S.V.; Loveland, Thomas R.

2003-01-01

Landscape pattern and composition metrics are potential indicators for broad-scale monitoring of change and for relating change to human and ecological processes. We used a probability sample of 20-km × 20-km sampling blocks to characterize landscape composition and pattern in five US ecoregions: the Middle Atlantic Coastal Plain, Southeastern Plains, Northern Piedmont, Piedmont, and Blue Ridge Mountains. Land use/land cover (LULC) data for five dates between 1972 and 2000 were obtained for each sample block. Analyses focused on quantifying trends in selected landscape pattern metrics by ecoregion and comparing trends in land cover proportions and pattern metrics among ecoregions. Repeated measures analysis of the landscape pattern documented a statistically significant trend in all five ecoregions towards a more fine-grained landscape from the early 1970s through 2000. The ecologically important forest cover class also became more fine-grained with time (i.e., more numerous and smaller forest patches). Trends in LULC, forest edge, and forest percent like adjacencies differed among ecoregions. These results suggest that ecoregions provide a geographically coherent way to regionalize the story of national land use and land cover change in the United States. This study provides new information on LULC change in the southeast United States. Previous studies of the region from the 1930s to the 1980s showed a decrease in landscape fragmentation and an increase in percent forest, while this study showed an increase in forest fragmentation and a loss of forest cover.

Future scenarios of land change based on empirical data and demographic trends

USGS Publications Warehouse

Sleeter, Benjamin M.; Wilson, Tamara; Sharygin, Ethan; Sherba, Jason

2017-01-01

Changes in land use and land cover (LULC) have important and fundamental interactions with the global climate system. Top-down global scale projections of land use change have been an important component of climate change research; however, their utility at local to regional scales is often limited. The goal of this study was to develop an approach for projecting changes in LULC based on land use histories and demographic trends. We developed a set of stochastic, empirical-based projections of LULC change for the state of California, for the period 2001–2100. Land use histories and demographic trends were used to project a “business-as-usual” (BAU) scenario and three population growth scenarios. For the BAU scenario, we projected developed lands would more than double by 2100. When combined with cultivated areas, we projected a 28% increase in anthropogenic land use by 2100. As a result, natural lands were projected to decline at a rate of 139 km2 yr−1; grasslands experienced the largest net decline, followed by shrublands and forests. The amount of cultivated land was projected to decline by approximately 10%; however, the relatively modest change masked large shifts between annual and perennial crop types. Under the three population scenarios, developed lands were projected to increase 40–90% by 2100. Our results suggest that when compared to the BAU projection, scenarios based on demographic trends may underestimate future changes in LULC. Furthermore, regardless of scenario, the spatial pattern of LULC change was likely to have the greatest negative impacts on rangeland ecosystems.

Future Scenarios of Land Change Based on Empirical Data and Demographic Trends

NASA Astrophysics Data System (ADS)

Sleeter, Benjamin M.; Wilson, Tamara S.; Sharygin, Ethan; Sherba, Jason T.

2017-11-01

Changes in land use and land cover (LULC) have important and fundamental interactions with the global climate system. Top-down global scale projections of land use change have been an important component of climate change research; however, their utility at local to regional scales is often limited. The goal of this study was to develop an approach for projecting changes in LULC based on land use histories and demographic trends. We developed a set of stochastic, empirical-based projections of LULC change for the state of California, for the period 2001-2100. Land use histories and demographic trends were used to project a "business-as-usual" (BAU) scenario and three population growth scenarios. For the BAU scenario, we projected developed lands would more than double by 2100. When combined with cultivated areas, we projected a 28% increase in anthropogenic land use by 2100. As a result, natural lands were projected to decline at a rate of 139 km2 yr-1; grasslands experienced the largest net decline, followed by shrublands and forests. The amount of cultivated land was projected to decline by approximately 10%; however, the relatively modest change masked large shifts between annual and perennial crop types. Under the three population scenarios, developed lands were projected to increase 40-90% by 2100. Our results suggest that when compared to the BAU projection, scenarios based on demographic trends may underestimate future changes in LULC. Furthermore, regardless of scenario, the spatial pattern of LULC change was likely to have the greatest negative impacts on rangeland ecosystems.

Implication of relationship between natural impacts and land use/land cover (LULC) changes of urban area in Mongolia

NASA Astrophysics Data System (ADS)

Gantumur, Byambakhuu; Wu, Falin; Zhao, Yan; Vandansambuu, Battsengel; Dalaibaatar, Enkhjargal; Itiritiphan, Fareda; Shaimurat, Dauryenbyek

2017-10-01

Urban growth can profoundly alter the urban landscape structure, ecosystem processes, and local climates. Timely and accurate information on the status and trends of urban ecosystems is critical to develop strategies for sustainable development and to improve the urban residential environment and living quality. Ulaanbaatar city was urbanized very rapidly caused by herders and farmers, many of them migrating from rural places, have played a big role in this urban expansion (sprawl). Today, 1.3 million residents for about 40% of total population are living in the Ulaanbaatar region. Those human activities influenced stronger to green environments. Therefore, the aim of this study is determined to change detection of land use/land cover (LULC) and estimating their areas for the trend of future by remote sensing and statistical methods. The implications of analysis were provided by change detection methods of LULC, remote sensing spectral indices including normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI). In addition, it can relate to urban heat island (UHI) provided by Land surface temperature (LST) with local climate issues. Statistical methods for image processing used to define relations between those spectral indices and change detection images and regression analysis for time series trend in future. Remote sensing data are used by Landsat (TM/ETM+/OLI) satellite images over the period between 1990 and 2016 by 5 years. The advantages of this study are very useful remote sensing approaches with statistical analysis and important to detecting changes of LULC. The experimental results show that the LULC changes can image on the present and after few years and determined relations between impacts of environmental conditions.

Modelling and analyzing the watershed dynamics using Cellular Automata (CA)-Markov model - A geo-information based approach

NASA Astrophysics Data System (ADS)

Behera, Mukunda D.; Borate, Santosh N.; Panda, Sudhindra N.; Behera, Priti R.; Roy, Partha S.

2012-08-01

Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)-Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socio-economic drivers including residential/industrial development, road-rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.

Land use and land cover classification for rural residential areas in China using soft-probability cascading of multifeatures

NASA Astrophysics Data System (ADS)

Zhang, Bin; Liu, Yueyan; Zhang, Zuyu; Shen, Yonglin

2017-10-01

A multifeature soft-probability cascading scheme to solve the problem of land use and land cover (LULC) classification using high-spatial-resolution images to map rural residential areas in China is proposed. The proposed method is used to build midlevel LULC features. Local features are frequently considered as low-level feature descriptors in a midlevel feature learning method. However, spectral and textural features, which are very effective low-level features, are neglected. The acquisition of the dictionary of sparse coding is unsupervised, and this phenomenon reduces the discriminative power of the midlevel feature. Thus, we propose to learn supervised features based on sparse coding, a support vector machine (SVM) classifier, and a conditional random field (CRF) model to utilize the different effective low-level features and improve the discriminability of midlevel feature descriptors. First, three kinds of typical low-level features, namely, dense scale-invariant feature transform, gray-level co-occurrence matrix, and spectral features, are extracted separately. Second, combined with sparse coding and the SVM classifier, the probabilities of the different LULC classes are inferred to build supervised feature descriptors. Finally, the CRF model, which consists of two parts: unary potential and pairwise potential, is employed to construct an LULC classification map. Experimental results show that the proposed classification scheme can achieve impressive performance when the total accuracy reached about 87%.

Land-use and Land-cover Change from 1974 to 2008 around Mobile Bay

NASA Technical Reports Server (NTRS)

Ellis, Jean; Spruce, Joseph; Smoot, James; Hilbert, Kent; Swann, Roberta

2008-01-01

This project is a Gulf of Mexico Application Pilot in which NASA Stennis Space Center (SSC) is working within a regional collaboration network of the Gulf of Mexico Alliance. NASA researchers, with support from the NASA SSC Applied Science Program Steering Committee, employed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL, between 1974 and 2008. A multi-decadal time-series, coastal LULC product unique to NASA SSC was produced. The geographic extent and nature of change was quantified for the open water, barren, upland herbaceous, non-woody wetland, upland forest, woody wetland, and urban landscapes. The National Oceanic and Atmospheric Administration (NOAA) National Coastal Development Data Center (NCDDC) will assist with the transition of the final product to the operational end user, which primarily is the Mobile Bay National Estuary Program (MBNEP). We found substantial LULC change over the 34-year study period, much more than is evident when the change occurring in the last years. Between 1974 and 2008, the upland forest landscape lost almost 6% of the total acreage, while urban land cover increased by slightly more than 3%. With exception to open water, upland forest is the dominant landscape, accounting for about 25-30% of the total area.

Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach

NASA Astrophysics Data System (ADS)

Bhattacharjee, S.; Ghosh, S. K.

2015-07-01

Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

Impact of Land Use/Land Cover Conditions on WRF Model Evaluation for Heat Island Assessment

NASA Astrophysics Data System (ADS)

Bhati, S.; Mohan, M.

2017-12-01

Urban heat island effect has been assessed using Weather Research and Forecasting model (WRF v3.5) focusing on air temperature and surface skin temperature in the sub-tropical urban Indian megacity of Delhi. Impact of urbanization related changes in land use/land cover (LULC) on model outputs has been analyzed. Four simulations have been carried out with different types of LULC data viz. (1) USGS , (2) MODIS, (3) user-modified USGS and (4) user modified land use data coupled with urban canopy model (UCM) for incorporation of canopy features. Heat island intensities have been estimated based on these simulations and subsequently compared with those derived from in-situ and satellite observations. There is a significant improvement in model performance with modification of LULC and inclusion of UCM. Overall, RMSEs for near surface temperature improved from 6.3°C to 3.9°C and index of agreement for mean urban heat island intensities (UHI) improved from 0.4 to 0.7 with modified land use coupled with UCM. In general, model is able to capture the magnitude of UHI as well as high UHI zones well. The study highlights the importance of appropriate and updated representation of landuse-landcover and urban canopies for improving predictive capabilities of the mesoscale models.

The spatio-temporal responses of the carbon cycle to climate and land use/land cover changes between 1981-2000 in China

NASA Astrophysics Data System (ADS)

Gao, Zhiqiang; Cao, Xiaoming; Gao, Wei

2013-03-01

This paper represents the first national effort of its kind to systematically investigate the impact of changes in climate and land use and land cover (LULC) on the carbon cycle with high-resolution dynamic LULC data at the decadal scale (1990s and 2000s). Based on simulations using well calibrated and validated Carbon Exchanges in the Vegetation-Soil-Atmosphere (CEVSA) model, temporal and spatial variations in carbon storage and fluxes in China may be generated empower us to relate these variations to climate variability and LULC with respect to net primary productivity (NPP), heterotrophic respiration (HR), net ecosystem productivity (NEP), storage and soil carbon (SOC), and vegetation carbon (VEGC) individually or collectively. Overall, the increases in NPP were greater than HR in most cases due to the effect of global warming with more precipitation in China from 1981 to 2000. With this trend, the NEP remained positive during that period, resulting in a net increase of total amount of carbon being stored by about 0.296 PgC within a 20-year time frame. Because the climate effect was much greater than that of changes of LULC, the total carbon storage in China actually increased by about 0.17 PgC within the 20-year time period. Such findings will contribute to the generation of carbon emissions control policies under global climate change impacts.

Differential Rate of Deforestation in Two Adjoining Indian River Basins: Does Resource Availability Matters?

NASA Astrophysics Data System (ADS)

Das, P.; Behera, M. D.

2017-12-01

Deforestation is one of the key factors of global climate change by altering the surface albedo reduces the evapotranspiration and surface roughness leads to warming in tropical regions. River basins are always subjected to LULC changes, especially decline in forest cover to give way for agricultural expansion, urbanisation, industrialisation etc. We generated LULC maps at three decadal intervals i.e., 1985, 1995 and 2005 in two major river basins of India using Landsat data employing on-screen visual image interpretation technique. In Rain-fed, Mahanadi river basin (MRB), 30.64% forest cover in 1985 was reduced to 30.13% in 2005, wherein glacier-fed, Brahmaputra river basin (BRB) this change was 63.44% to 62.32% during 1985 to 2005. Though conversion of forest land for agricultural activities was the major LULC changes in both the basins, the rate was more than two times higher in BRB than MRB. Scrub land in few zones acted as an intermediate class for mixed forest conversion to cropland land in both the basins. Analysing the drivers, in deforestation we observed the proximity zones around habitat and socio-economic drivers contributed higher compared to topographic, edaphic and climate. Using Dyna-CLUE modelling approach, we have predicted the LULC for 2025. For validation, comparing the predicted result with actual LULC of 2005, we obtained > 97% modeling accuracy; therefore it is expected that the Dyna-CLUE model has very well predicted the LULC for the year 2025. The predicted LULC of 2025 captured the similar trend of deforestation around 0.52% in MRB and 1.18% in BRB during 2005 to 2025. Acting as early warning, and with the past 2-decadal change analysis this study is believed to help the land use planners for improved regional planning to create balanced ecosystem, especially in a changing climate. On the basis of driver analysis, we believe that availability of more forest resources in Brahmaputra River basin provided extra liberty for higher deforestation for agriculture land conversion, followed by other developmental activities in comparison to Mahanadi River basin.

The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075

USGS Publications Warehouse

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be "suitable" for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.

The Relative Impacts of Climate and Land-Use Change on Conterminous United States Bird Species from 2001 to 2075

PubMed Central

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be “suitable” for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges. PMID:25372571

Land use/land cover mapping using multi-scale texture processing of high resolution data

NASA Astrophysics Data System (ADS)

Wong, S. N.; Sarker, M. L. R.

2014-02-01

Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road.

Monitoring urban growth by using segmentation-classification of multispectral Landsat images in Izmit, Turkey.

PubMed

Yildiz, Selin; Doker, Mehmet Fatih

2016-07-01

Assessing the spatial land use and land cover (LULC) information is essential for decision making and management of landscapes. In fact, LULC information has been changed dramatically in fast-growing cities. This results in wrong land use problems due to unplanned and uncontrolled urbanization. The planning and evaluating of limited natural resources under the pressure of a growing population can be possible when a precise land use management plan is established. Therefore, it is imperative to monitor continuous LULC changes for future planning. Remote sensing (RS) technique is used for determining changes in LULC in urban areas. In this study, we have focused on Izmit, which is one of a growing number of metropolitan cities where the impact of the spatial growing period on LULC has been assessed over the past 30 years by using RS data. We have utilized the segmentation process and supervised classification of Landsat satellite images for four different dates (1985, 1995, 2005, and 2015). The outcome of this research can be summarized by significant changes in the shares of urban areas and farmland LULC classes. The overall observed increase in urban area class is up to 2177 ha between 1985 and 2015 period and this dramatic change has resulted in the decline of 1211 ha of farmland. Another conclusion is that the new residential areas have been created to the north, south and east of Izmit during this period.

THE USE OF NTM DATA FOR THE ACCURACY ASSESSMENT OF LANDSAT DERIVED LAND USE/LAND COVER MAPS

EPA Science Inventory

National Technical Means (NTM) data were utilized to validate the accuracy of a series of LANDSAT derived Land Use / Land Cover (LU/LC) maps for the time frames mid- I 970s, early- I 990s and mid- I 990s. The area-of-interest for these maps is a 2000 square mile portion of the De...

Potential reciprocal effect between land use / land cover change and climate change

NASA Astrophysics Data System (ADS)

Daham, Afrah; Han, Dawei; Rico-Ramirez, Miguel

2016-04-01

Land use/land cover (LULC) activity influences climate change and one way to explore climate change is to analyse the change in LULC patterns. Modelling the Spatio-temporal pattern of LULC change requires the use of satellite remote sensing data and aerial photographs with different pre-processing steps. The aim of this research is to analyse the reciprocal effects of LUCC (Land Use and Cover Change) and the climate change on each other in the study area which covers part of Bristol, South Gloucestershire, Bath and Somerset in England for the period (1975-2015). LUCC is assessed using remote sensing data. Three sets of remotely sensed data, LanSAT-1 Multispectral Scanner (MSS) data obtained in (1975 and 1976), LanSAT-5 Thematic Mapper (TM) data obtained in (1984 and 1997), and LandSAT-7 Enhanced Thematic Mapper Plus (ETM+) acquired in (2003 and 2015), with a time span of forty years were used in the study. One of the most common problems in the satellite images is the presence of cloud covers. In this study, the cloud cover problem is handled using a novel algorithm, which is capable of reducing the cloud coverage in the classified images significantly. This study also examines a suite of possible photogrammetry techniques applicable to detect the change in LULC. At the moment photogrammertic techniques are used to derive the ground truth for supervised classification from the high resolution aerial photos which were provided by Ordnance Survey (contract number: 240215) and global mapper for the years in (2001 and 2014). After obtaining the classified images almost free of clouds, accuracy assessment is implemented with the derived classified images using confusion matrix at some ground truth points. Eight classes (Improved grassland, Built up areas and gardens, Arable and horticulture, Broad-leaved / mixed woodland, Coniferous woodland, Oceanic seas, Standing open water and reservoir, and Mountain; heath; bog) have been classified in the chosen study area. Also, CORINE Land Cover (CLC) maps are used to study the environmental changes and to validate the obtained maps from remote sensing and photogrammetry data. On climate change, different sources of climate data were used in this research. Three rainfall datasets from the Global Precipitation Climatology Centre (GPCC), the Climate Research Unit (CRU) and Gridded Estimates of daily Areal Rainfall (CEH-GEAR) in the study area were compared at a resolution of 0.5 degrees. The dataset were available for the operational period 1975-2015. The historically observed rainfall datasets for the study area were obtained from the Met Office Integrated Data Archive System (MIDAS) Land and Marine downloaded through the British Atmospheric Data Centre (BADC) website, which includes the rainfall and the temperature, are collected from all the weather stations in the UK in the last 40 years. Only four gauging stations were available to represent the spatial variability of rainfall within and around the study area. The monthly rainfall time series were evaluated against a dataset based on four rain gauges. These data are processed and analysed statistically to find the changes in climate of the study area in the last 40 years. The potential reciprocal effect between the LULC change and the climate change is done by finding the correlation between LUCC and the variables Rainfall and Temperature. In addition, The Soil and Water Assessment Tool (SWAT) model is used to study the impact of LULC change on the water system and climate.

Modelling Soil Erosion in the Densu River Basin Using RUSLE and GIS Tools.

PubMed

Ashiagbori, G; Forkuo, E K; Laari, P; Aabeyir, R

2014-07-01

Soil erosion involves detachment and transport of soil particles from top soil layers, degrading soil quality and reducing the productivity of affected lands. Soil eroded from the upland catchment causes depletion of fertile agricultural land and the resulting sediment deposited at the river networks creates river morphological change and reservoir sedimentation problems. However, land managers and policy makers are more interested in the spatial distribution of soil erosion risk than in absolute values of soil erosion loss. The aim of this paper is to model the spatial distribution of soil erosion in Densu River Basin of Ghana using RUSLE and GIS tools and to use the model to explore the relationship between erosion susceptibility, slope and land use/land cover (LULC) in the Basin. The rainfall map, digital elevation model, soil type map, and land cover map, were input data in the soil erosion model developed. This model was then categorized into four different erosion risk classes. The developed soil erosion map was then overlaid with the slope and LULC maps of the study area to explore their effects on erosion susceptibility of the soil in the Densu River Basin. The Model, predicted 88% of the basin as low erosion risk and 6% as moderate erosion risk, 3% as high erosion risk and 3% as severe risk. The high and severe erosion areas were distributed mainly within the areas of high slope gradient and also sections of the moderate forest LULC class. Also, the areas within the moderate forest LULC class found to have high erosion risk, had an intersecting high erodibility soil group.

Mapping urban impervious surface using object-based image analysis with WorldView-3 satellite imagery

NASA Astrophysics Data System (ADS)

Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

2017-10-01

Land use and land cover (LULC) data are important to monitor and assess environmental change. LULC classification using satellite images is a method widely used on a global and local scale. Especially, urban areas that have various LULC types are important components of the urban landscape and ecosystem. This study aims to classify urban LULC using WorldView-3 (WV-3) very high-spatial resolution satellite imagery and the object-based image analysis method. A decision rules set was applied to classify the WV-3 images in Kathu subdistrict, Phuket province, Thailand. The main steps were as follows: (1) the image was ortho-rectified with ground control points and using the digital elevation model, (2) multiscale image segmentation was applied to divide the image pixel level into image object level, (3) development of the decision ruleset for LULC classification using spectral bands, spectral indices, spatial and contextual information, and (4) accuracy assessment was computed using testing data, which sampled by statistical random sampling. The results show that seven LULC classes (water, vegetation, open space, road, residential, building, and bare soil) were successfully classified with overall classification accuracy of 94.14% and a kappa coefficient of 92.91%.

US GeoData Available Through the Internet

USGS Publications Warehouse

,

2000-01-01

The U.S. Geological Survey (USGS) offers certain US GeoData data sets through the Internet. They can be retrieved using the World Wide Web or anonymous File Transfer Protocol (FTP). The data bases and their directory paths are as follows: * 1:24,000-scale digital line graph data in SDTS format (/pub/data/DLG/24K) * 1:2,000,000-scale digital line graph data in SDTS format (/pub/data/DLG/2M) * 1:100,000-scale digital line graph data (/pub/data/DLG/100K) * 1:100,000-scale land use and land cover data (/pub/data/LULC/100K) * 1:250,000-scale land use and land cover data (/pub/data/LULC/250K) * 1:24,000-scale digital elevation data (/pub/data/DEM/7.5min) * 1-degree digital elevation model data (/pub/data/DEM/250)

Detection of land-use and land cover changes in Franklin, Gulf, and Liberty Counties, Florida, with multitemporal landsat thematic mapper images

Treesearch

Shufen Pan; Guiying Li

2007-01-01

Florida Panhandle region has been experiencing rapid land transformation in the recent decades. To quantify land use and land-cover (LULC) changes and other landscape changes in this area, three counties including Franklin, Liberty and Gulf were taken as a case study and an unsupervised classification approach implemented to Landsat TM images acquired from 1985 to 2005...

MULTI-TEMPORAL LAND USE GENERATION FOR THE OHIO RIVER BASIN

EPA Science Inventory

A set of backcast and forecast land use maps of the Ohio River Basin (ORB) was developed that could be used to assess the spatial-temporal patterns of land use/land cover (LULC) change in this important basin. This approach was taken to facilitate assessment of integrated sustain...

Decadal changes in the land use/land cover and shoreline along the coastal districts of southern Gujarat, India.

PubMed

Misra, A; Balaji, R

2015-07-01

The coastal zone along the districts of Surat, Navsari, and Valsad in southern Gujarat, India, is reported to be facing serious environmental challenges in the form of shoreline erosion, wetland loss, and man-made encroachments. This study assesses the decadal land use/ land cover (LULC) changes in these three districts for the years 1990, 2001, and 2014 using satellite datasets of Landsat TM, ETM, and OLI. The LULC changes are identified by using band ratios as a pre-classification step, followed by implementation of hybrid classification (a combination of supervised and unsupervised classification). An accuracy assessment is carried out for each dataset, and the overall accuracy ranges from 90 to 95%. It is observed that the spatial extents of aquaculture, urban built-up, and barren classes have appreciated over time, whereas the coverage of mudflats has depreciated due to rapid urbanization. The changes in the shoreline of these districts have also been analyzed for the same years, and significant changes are found in the form of shoreline erosion. The LULC maps prepared as well as the shoreline change analysis done for this study area will enable the local decision makers to adopt better land-use planning and shoreline protection measures, which will further aid in sustainable future developments in this region.

The interplay of climate and land use change affects the distribution of EU bumblebees.

PubMed

Marshall, Leon; Biesmeijer, Jacobus C; Rasmont, Pierre; Vereecken, Nicolas J; Dvorak, Libor; Fitzpatrick, Una; Francis, Frédéric; Neumayer, Johann; Ødegaard, Frode; Paukkunen, Juho P T; Pawlikowski, Tadeusz; Reemer, Menno; Roberts, Stuart P M; Straka, Jakub; Vray, Sarah; Dendoncker, Nicolas

2018-01-01

Bumblebees in Europe have been in steady decline since the 1900s. This decline is expected to continue with climate change as the main driver. However, at the local scale, land use and land cover (LULC) change strongly affects the occurrence of bumblebees. At present, LULC change is rarely included in models of future distributions of species. This study's objective is to compare the roles of dynamic LULC change and climate change on the projected distribution patterns of 48 European bumblebee species for three change scenarios until 2100 at the scales of Europe, and Belgium, Netherlands and Luxembourg (BENELUX). We compared three types of models: (1) only climate covariates, (2) climate and static LULC covariates and (3) climate and dynamic LULC covariates. The climate and LULC change scenarios used in the models include, extreme growth applied strategy (GRAS), business as might be usual and sustainable European development goals. We analysed model performance, range gain/loss and the shift in range limits for all bumblebees. Overall, model performance improved with the introduction of LULC covariates. Dynamic models projected less range loss and gain than climate-only projections, and greater range loss and gain than static models. Overall, there is considerable variation in species responses and effects were most pronounced at the BENELUX scale. The majority of species were predicted to lose considerable range, particularly under the extreme growth scenario (GRAS; overall mean: 64% ± 34). Model simulations project a number of local extinctions and considerable range loss at the BENELUX scale (overall mean: 56% ± 39). Therefore, we recommend species-specific modelling to understand how LULC and climate interact in future modelling. The efficacy of dynamic LULC change should improve with higher thematic and spatial resolution. Nevertheless, current broad scale representations of change in major land use classes impact modelled future distribution patterns. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Protected area effectiveness against land development in Spain.

PubMed

Rodríguez-Rodríguez, David; Martínez-Vega, Javier

2018-06-01

Land use-land cover (LULC) changes towards artificial covers are one of the main global threats to biodiversity conservation. In this comprehensive study, we tested a number of methodological and research hypotheses, and a new covariate control technique in order to address common protected area (PA) assessment issues and accurately assess whether different PA networks have had an effect at preventing development of artificial LULCs in Spain, a highly biodiverse country that has experienced massive socioeconomic transformations in the past two decades. We used digital census data for four PA networks designated between 1990 and 2000: Nature Reserves (NRs), Nature Parks (NPs), Sites of Community Importance (SCIs) and Special Protection Areas (SPAs). We analysed the effect of explanatory variables on the ecological effectiveness of protected polygons (PPs): Legislation stringency, cummulative legal designations, management, size, age and bio-physical characteristics. A multiple Before-After-Control-Impact (BACI) semi-experimental research design was used whereby artificial land cover increase (ALCI) and proportional artificial land cover increase (PALCI) results were compared inside and outside PAs, using 1 km and 5 km buffer areas surrounding PAs as controls. LULC data were retrieved from Corine Land Cover (CLC) 1990 and 2006 data. Results from three spatial-statistical models using progressively restrictive criteria to select control areas increasingly more accurate and similar to the assessed PPs were compared. PAs were a generally effective territorial policy to prevent land development in Spain. NRs were the most effective PA category, with no new artificial land covers in the assessed period, although exact causality could not be attributed due to legal overlaps. SPAs were the least effective category, with worse ALCI data than their control areas. Legal protection was effective against land development, which was influenced by most bio-physical variables. However, cumulative legal designations and PA management did not seem to influence land development. The spatial-statistical technique used to make cases and control environmentally similar did not produce consistent outcomes and should be refined. Copyright © 2018 Elsevier Ltd. All rights reserved.

Land Use/land Cover Changes in Semi-Arid Mountain Landscape in Southern India: a Geoinformatics Based Markov Chain Approach

NASA Astrophysics Data System (ADS)

Rahaman, S. A.; Aruchamy, S.; Balasubramani, K.; Jegankumar, R.

2017-05-01

Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly affected by severe soil erosion, landslide, frequent rainfall failures and associated drought. The foothill regions are mainly utilized for agriculture practices; due to water scarcity and meagre income, the productive agriculture lands are converted into settlement plots and wasteland. Hence, land use/land cover change deduction; a stochastic processed based method is indispensable for future prediction. For identification of land use/land cover, and vegetation changes, Landsat TM, ETM (1995, 2005) and IRS P6- LISS IV (2015) images were used. Through CAMarkov chain analysis, Lu/Lc changes in past three decades (1995, 2005, and 2015) were identified and projected for (2020 and 2025); Normalized Difference Vegetation Index (NDVI) were used to find the vegetation changes. The result shows that, maximum changes occur in the plantation and slight changes found in forest cover in the hilly terrain. In foothill areas, agriculture lands were decreased while wastelands and settlement plots were increased. The outcome of the results helps to farmer and policy makers to draw optimal lands use planning and better management strategies for sustainable development of natural resources.

Monitoring, analyzing and simulating of spatial-temporal changes of landscape pattern over mining area

NASA Astrophysics Data System (ADS)

Liu, Pei; Han, Ruimei; Wang, Shuangting

2014-11-01

According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

Improved vegetation parameterization for hydrological model and assessment of land cover change impacts on flow regime of the Upper Bhima basin, India

NASA Astrophysics Data System (ADS)

Mohaideen, M. M. Diwan; Varija, K.

2018-05-01

This study investigates the potential and applicability of variable infiltration capacity (VIC) hydrological model to simulate different hydrological components of the Upper Bhima basin under two different Land Use Land Cover (LULC) (the year 2000 and 2010) conditions. The total drainage area of the basin was discretized into 1694 grids of about 5.5 km by 5.5 km: accordingly the model parameters were calibrated at each grid level. Vegetation parameters for the model were prepared using temporal profile of Leaf Area Index (LAI) from Moderate-Resolution Imaging Spectroradiometer and LULC. This practice provides a methodological framework for the improved vegetation parameterization along with region-specific condition for the model simulation. The calibrated and validated model was run using the two LULC conditions separately with the same observed meteorological forcing (1996-2001) and soil data. The change in LULC has resulted to an increase in the average annual evapotranspiration over the basin by 7.8%, while the average annual surface runoff and baseflow decreased by 18.86 and 5.83%, respectively. The variability in hydrological components and the spatial variation of each component attributed to LULC were assessed at the basin grid level. It was observed that 80% of the basin grids showed an increase in evapotranspiration (ET) (maximum of 292 mm). While the majority of the grids showed a decrease in surface runoff and baseflow, some of the grids showed an increase (i.e. 21 and 15% of total grids—surface runoff and baseflow, respectively).

Investigating the Potential of Land Use Modifications to Mitigate the Respiratory Health Impacts of NO2: A Case Study in the Portland-Vancouver Metropolitan Area

NASA Astrophysics Data System (ADS)

Rao, Meenakshi

The health impacts of urban air pollution are a growing concern in our rapidly urbanizing world. Urban air pollutants show high intra-urban spatial variability linked to urban land use and land cover (LULC). This correlation of air pollutants with LULC is widely recognized; LULC data is an integral input into a wide range of models, especially land use regression models developed by epidemiologists to study the impact of air pollution on human health. Given the demonstrated links between LULC and urban air pollution, and between urban air pollution and health, an interesting question arises: what is the potential of LULC modifications to mitigate the health impacts of urban air pollution? In this dissertation we assess the potential of LULC modifications to mitigate the health impacts of NO2, a respiratory irritant and strong marker for combustion-related air pollution, in the Portland-Vancouver metropolitan area in northwestern USA. We begin by measuring summer and winter NO2 in the area using a spatially dense network of passive NO 2 samplers. We next develop an annual average model for NO2 based on the observational data, using random forest--for the first time in the realm of urban air pollution--to disentangle the effects of highly correlated LULC variables on ambient NO2 concentrations. We apply this random forest (LURF) model to a 200m spatial grid covering the study area, and use this 200m LURF model to quantify the effect of different urban land use categories on ambient concentrations of NO2. Using the changes in ambient NO2 concentrations resulting from land use modifications as input to BenMAP (a health benefits assessment tool form the US EPA), we assess the NO2-related health impact associated with each land use category and its modifications. We demonstrate how the LURF model can be used to assess the respiratory health benefits of competing land use modifications, including city-wide and local-scale mitigation strategies based on modifying tree canopy and vehicle miles traveled (VMT). Planting trees is a common land cover modification strategy undertaken by cities to reduce air pollution. Statistical models such as LUR and LURF demonstrate a correlation between tree cover and reduced air pollution, but they cannot demonstrate causation. Hence, we run the atmospheric chemistry and transport model CMAQ to examine to what extent the dry deposition mechanism can explain the reduction of NO2 which statistical models associate with tree canopy. Results from our research indicate that even though the Portland-Vancouver area is in compliance with the US EPA NO2 standards, ambient concentrations of NO2 still create an annual health burden of at least 40 million USD. Our model suggests that NO2 associated with high intensity development and VMT may be creating an annual health burden of 7 million and 3.3 million USD respectively. Existing tree canopy, on the other hand, is associated with an annual health benefit of 1.4 million USD. LULC modifications can mitigate some fraction of this health burden. A 2% increase in tree canopy across the study area may reduce incidence rates of asthma exacerbation by as much as 7%. We also find that increasing tree canopy is a more effective strategy than reducing VMT in terms of mitigating the health burden of NO 2. CMAQ indicates that the amount of NO2 removed by dry deposition is an order of magnitude smaller than that predicted by our statistical model. About one-third of the difference can be explained by the lower NO2 values predicted by CMAQ, and one-third may be attributable to parameterization of stomatal uptake.

Agricultural cropland mapping using black-and-white aerial photography, Object-Based Image Analysis and Random Forests

NASA Astrophysics Data System (ADS)

Vogels, M. F. A.; de Jong, S. M.; Sterk, G.; Addink, E. A.

2017-02-01

Land-use and land-cover (LULC) conversions have an important impact on land degradation, erosion and water availability. Information on historical land cover (change) is crucial for studying and modelling land- and ecosystem degradation. During the past decades major LULC conversions occurred in Africa, Southeast Asia and South America as a consequence of a growing population and economy. Most distinct is the conversion of natural vegetation into cropland. Historical LULC information can be derived from satellite imagery, but these only date back until approximately 1972. Before the emergence of satellite imagery, landscapes were monitored by black-and-white (B&W) aerial photography. This photography is often visually interpreted, which is a very time-consuming approach. This study presents an innovative, semi-automated method to map cropland acreage from B&W photography. Cropland acreage was mapped on two study sites in Ethiopia and in The Netherlands. For this purpose we used Geographic Object-Based Image Analysis (GEOBIA) and a Random Forest classification on a set of variables comprising texture, shape, slope, neighbour and spectral information. Overall mapping accuracies attained are 90% and 96% for the two study areas respectively. This mapping method increases the timeline at which historical cropland expansion can be mapped purely from brightness information in B&W photography up to the 1930s, which is beneficial for regions where historical land-use statistics are mostly absent.

Influence of riparian and watershed alterations on sandbars in a Great Plains river

USGS Publications Warehouse

Fischer, Jeffrey M.; Paukert, Craig P.; Daniels, M.L.

2014-01-01

Anthropogenic alterations have caused sandbar habitats in rivers and the biota dependent on them to decline. Restoring large river sandbars may be needed as these habitats are important components of river ecosystems and provide essential habitat to terrestrial and aquatic organisms. We quantified factors within the riparian zone of the Kansas River, USA, and within its tributaries that influenced sandbar size and density using aerial photographs and land use/land cover (LULC) data. We developed, a priori, 16 linear regression models focused on LULC at the local, adjacent upstream river bend, and the segment (18–44 km upstream) scales and used an information theoretic approach to determine what alterations best predicted the size and density of sandbars. Variation in sandbar density was best explained by the LULC within contributing tributaries at the segment scale, which indicated reduced sandbar density with increased forest cover within tributary watersheds. Similarly, LULC within contributing tributary watersheds at the segment scale best explained variation in sandbar size. These models indicated that sandbar size increased with agriculture and forest and decreased with urban cover within tributary watersheds. Our findings suggest that sediment supply and delivery from upstream tributary watersheds may be influential on sandbars within the Kansas River and that preserving natural grassland and reducing woody encroachment within tributary watersheds in Great Plains rivers may help improve sediment delivery to help restore natural river function.

Land use and land cover changes and spatiotemporal dynamics of anopheline larval habitats during a four-year period in a highland community of Africa.

PubMed

Munga, Stephen; Yakob, Laith; Mushinzimana, Emmanuel; Zhou, Guofa; Ouna, Tom; Minakawa, Noboru; Githeko, Andrew; Yan, Guiyun

2009-12-01

Spatial and temporal variations in the distribution of anopheline larval habitats and land use and land cover (LULC) changes can influence malaria transmission intensity. This information is important for understanding the environmental determinants of malaria transmission heterogeneity, and it is critical to the study of the effects of environmental changes on malaria transmission. In this study, we investigated the spatial and temporal variations in the distribution of anopheline larval habitats and LULC changes in western Kenya highlands over a 4-year period. Anopheles gambiae complex larvae were mainly confined to valley bottoms during both the dry and wet seasons. Although An. gambiae larvae were located in man-made habitats where riparian forests and natural swamps had been cleared, Anopheles funestus larvae were mainly found in permanent habitats in pastures. The association between land cover type and occurrence of anopheline larvae was statistically significant. The distribution of anopheline positive habitats varied significantly between months, during the survey. In 2004, the mean density of An. gambiae was significantly higher during the month of May, whereas the density of An. funestus peaked significantly in February. Over the study period, major LULC changes occurred mostly in the valley bottoms. Overall, farmland increased by 3.9%, whereas both pastures and natural swamps decreased by 8.9% and 20.9%, respectively. The area under forest cover was decreased by 5.8%. Land-use changes in the study area are favorable to An. gambiae larval development, thereby risking a more widespread distribution of malaria vector habitats and potentially increasing malaria transmission in western Kenya highlands.

Drivers of land use/land cover changes in Munessa-Shashemene landscape of the south-central highlands of Ethiopia.

PubMed

Kindu, Mengistie; Schneider, Thomas; Teketay, Demel; Knoke, Thomas

2015-07-01

Understanding drivers of changes in land use/land cover (LULC) is essential for modeling future dynamics or development of management strategies to ameliorate or prevent further decline of natural resources. In this study, an attempt has been made to identify the main drivers behind the LULC changes that had occurred in the past four decades in Munessa-Shashemene landscape of the south-central highlands of Ethiopia. The datasets required for the study were generated through both primary and secondary sources. Combination of techniques, including descriptive statistics, GIS-based processing, and regression analyses were employed for data analyses. Changes triggered by the interplay of more than 12 drivers were identified related to social, economic, environmental, policy/institutional, and technological factors. Specifically, population growth, expansion of cultivated lands and settlements, livestock ranching, cutting of woody species for fuelwood, and charcoal making were the top six important drivers of LULC change as viewed by the local people and confirmed by quantitative analyses. Differences in respondents' perceptions related to environmental (i.e., location specific) and socioeconomic determinants (e.g., age and literacy) about drivers were statically significant (P = 0.001). LULC changes were also determined by distances to major drivers (e.g., the further a pixel is from the road, the less likelihood of changes) as shown by the landscape level analyses. Further studies are suggested targeting these drivers to explore the consequences and future options and formulate intervention strategies for sustainable development in the studied landscape and elsewhere with similar geographic settings.

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to central plains stream conditions

USGS Publications Warehouse

Griffith, J.A.; Martinko, E.A.; Whistler, J.L.; Price, K.P.

2002-01-01

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to Central Plains stream conditions.

PubMed

Griffith, Jerry A; Martinko, Edward A; Whistler, Jerry L; Price, Kevin P

2002-01-01

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.

Sensitivity of WRF Regional Climate Simulations to Choice of Land Use Dataset

EPA Science Inventory

The goal of this study is to assess the sensitivity of regional climate simulations run with the Weather Research and Forecasting (WRF) model to the choice of datasets representing land use and land cover (LULC). Within a regional climate modeling application, an accurate repres...

Geospatial Method for Computing Supplemental Multi-Decadal U.S. Coastal Land-Use and Land-Cover Classification Products, Using Landsat Data and C-CAP Products

NASA Technical Reports Server (NTRS)

Spruce, J. P.; Smoot, James; Ellis, Jean; Hilbert, Kent; Swann, Roberta

2012-01-01

This paper discusses the development and implementation of a geospatial data processing method and multi-decadal Landsat time series for computing general coastal U.S. land-use and land-cover (LULC) classifications and change products consisting of seven classes (water, barren, upland herbaceous, non-woody wetland, woody upland, woody wetland, and urban). Use of this approach extends the observational period of the NOAA-generated Coastal Change and Analysis Program (C-CAP) products by almost two decades, assuming the availability of one cloud free Landsat scene from any season for each targeted year. The Mobile Bay region in Alabama was used as a study area to develop, demonstrate, and validate the method that was applied to derive LULC products for nine dates at approximate five year intervals across a 34-year time span, using single dates of data for each classification in which forests were either leaf-on, leaf-off, or mixed senescent conditions. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and C-CAP value-added products. Each classification's overall accuracy was assessed by comparing stratified random locations to available reference data, including higher spatial resolution satellite and aerial imagery, field survey data, and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall Kappa statistics ranging from 0.78 to 0.89. The accuracies are comparable to those from similar, generalized LULC products derived from C-CAP data. The Landsat MSS-based LULC product accuracies are similar to those from Landsat TM or ETM+ data. Accurate classifications were computed for all nine dates, yielding effective results regardless of season. This classification method yielded products that were used to compute LULC change products via additive GIS overlay techniques.

Assessing the Potential of Land Use Modification to Mitigate Ambient NO₂ and Its Consequences for Respiratory Health.

PubMed

Rao, Meenakshi; George, Linda A; Shandas, Vivek; Rosenstiel, Todd N

2017-07-10

Understanding how local land use and land cover (LULC) shapes intra-urban concentrations of atmospheric pollutants-and thus human health-is a key component in designing healthier cities. Here, NO₂ is modeled based on spatially dense summer and winter NO₂ observations in Portland-Hillsboro-Vancouver (USA), and the spatial variation of NO₂ with LULC investigated using random forest, an ensemble data learning technique. The NO 2 random forest model, together with BenMAP, is further used to develop a better understanding of the relationship among LULC, ambient NO₂ and respiratory health. The impact of land use modifications on ambient NO₂, and consequently on respiratory health, is also investigated using a sensitivity analysis. We find that NO₂ associated with roadways and tree-canopied areas may be affecting annual incidence rates of asthma exacerbation in 4-12 year olds by +3000 per 100,000 and -1400 per 100,000, respectively. Our model shows that increasing local tree canopy by 5% may reduce local incidences rates of asthma exacerbation by 6%, indicating that targeted local tree-planting efforts may have a substantial impact on reducing city-wide incidence of respiratory distress. Our findings demonstrate the utility of random forest modeling in evaluating LULC modifications for enhanced respiratory health.

Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979-2009) in China.

PubMed

Yin, Jie; Yin, Zhane; Zhong, Haidong; Xu, Shiyuan; Hu, Xiaomeng; Wang, Jun; Wu, Jianping

2011-06-01

This study explored the spatio-temporal dynamics and evolution of land use/cover changes and urban expansion in Shanghai metropolitan area, China, during the transitional economy period (1979-2009) using multi-temporal satellite images and geographic information systems (GIS). A maximum likelihood supervised classification algorithm was employed to extract information from four landsat images, with the post-classification change detection technique and GIS-based spatial analysis methods used to detect land-use and land-cover (LULC) changes. The overall Kappa indices of land use/cover change maps ranged from 0.79 to 0.89. Results indicated that urbanization has accelerated at an unprecedented scale and rate during the study period, leading to a considerable reduction in the area of farmland and green land. Findings further revealed that water bodies and bare land increased, obviously due to large-scale coastal development after 2000. The direction of urban expansion was along a north-south axis from 1979 to 2000, but after 2000 this growth changed to spread from both the existing urban area and along transport routes in all directions. Urban expansion and subsequent LULC changes in Shanghai have largely been driven by policy reform, population growth, and economic development. Rapid urban expansion through clearing of vegetation has led to a wide range of eco-environmental degradation.

Assessing LULC changes over Chilika Lake watershed in Eastern India using Driving Force Analysis

NASA Astrophysics Data System (ADS)

Jadav, S.; Syed, T. H.

2017-12-01

Rapid population growth and industrial development has brought about significant changes in Land Use Land Cover (LULC) of many developing countries in the world. This study investigates LULC changes in the Chilika Lake watershed of Eastern India for the period of 1988 to 2016. The methodology involves pre-processing and classification of Landsat satellite images using support vector machine (SVM) supervised classification algorithm. Results reveal that `Cropland', `Emergent Vegetation' and `Settlement' has expanded over the study period by 284.61 km², 106.83 km² and 98.83 km² respectively. Contemporaneously, `Lake Area', `Vegetation' and `Scrub Land' have decreased by 121.62 km², 96.05 km² and 80.29 km² respectively. This study also analyzes five major driving force variables of socio-economic and climatological factors triggering LULC changes through a bivariate logistic regression model. The outcome gives credible relative operating characteristics (ROC) value of 0.76 that indicate goodness fit of logistic regression model. In addition, independent variables like distance to drainage network and average annual rainfall have negative regression coefficient values that represent decreased rate of dependent variable (changed LULC) whereas independent variables (population density, distance to road and distance to railway) have positive regression coefficient indicates increased rate of changed LULC . Results from this study will be crucial for planning and restoration of this vital lake water body that has major implications over the society and environment at large.

Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA

USGS Publications Warehouse

Soulard, Christopher E.; Walker, Jessica; Griffith, Glenn E.

2017-01-01

Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the Cascade Mountains, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras of logging trends that align with prevailing regulations and economic conditions. We used multiple logistic regression to determine the biophysical and anthropogenic factors that influence fine-scale selection of harvest stands in each time period. Results show that private lands forest cover became significantly reduced and more fragmented from 1985 to 2014. Variables linked to parameters of site conditions, location, climate, and vegetation greenness consistently distinguished harvest selection for each distinct era. This study demonstrates the utility of annual LULC data for investigating the underlying factors that influence land cover change.

Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population.

PubMed

Alimi, Temitope O; Fuller, Douglas O; Qualls, Whitney A; Herrera, Socrates V; Arevalo-Herrera, Myriam; Quinones, Martha L; Lacerda, Marcus V G; Beier, John C

2015-08-20

Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts. Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent. Results from our land change modeling indicate that about 70,000 km(2) of forest land would be lost by 2050 and 78,000 km(2) by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution. As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination.

Integration of remote sensing (RS) and geographic information system (GIS) techniques for change detection of the land use and land cover (LULC) for soil management in the southern Port Said region, Egypt

NASA Astrophysics Data System (ADS)

Hassan, Mohamed Abd El Rehim Abd El Aziz

2014-11-01

The monitoring of land use/land cover (LULC) changes in southern Port Said region area is very important for the planner of managements, governmental and non-governmental organizations, decision makers and the scientific community. This information is essential for planning and implementing policies to optimize the use of natural resources and accommodate development whilst minimizing the impact on the environment. To monitor these changes in the study area, two sets of satellite images (Landsat TM-5 and ETM+7) data were used with Path/Row (175/38) in date 1986 and 2006, respectively. The Landsat TM and ETM data are useful for this type of study due to its high spatial resolution, spectral resolution and low repetitive acquisition (16 days). A postclassification technique is used in this study based on hybrid classification (Unsupervised and Supervised). Each method used was assessed, and checked in field. Eight to Twelve LULC classes are recognized and mapping produced. The soils in southern Port Said area were classification in two orders for soil taxonomic units, which are Entisols and Aridisols and four sub-orders classes. The study land was evaluated into five classes from non suitable (N) to very highly suitable (S1) for some crops in the southern region of Port Said studied soils, with assess the nature of future change following construction of the international coastal road which crosses near to the study area.

Land-Cover Trends of the Southern California Mountains Ecoregion

USGS Publications Warehouse

Soulard, Christopher E.; Raumann, Christian G.; Wilson, Tamara S.

2007-01-01

This report presents an assessment of land-use and land-cover (LU/LC) change in the Southern California Mountains ecoregion for the period 1973-2001. The Southern California Mountains is one of 84 Level-III ecoregions as defined by the U.S. Environmental Protection Agency (EPA). Ecoregions have served as a spatial framework for environmental resource management, denoting areas that contain a geographically distinct assemblage of biotic and abiotic phenomena including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The established Land Cover Trends methodology generates estimates of change for ecoregions using a probability sampling approach and change-detection analysis of thematic land-cover images derived from Landsat satellite imagery.

Impact of climate and land use/cover changes on the carbon cycle in China (1981-2000): a system-based assessment

NASA Astrophysics Data System (ADS)

Gao, Z.; Gao, W.; Chang, N.-B.

2010-07-01

In China, cumulative changes in climate and land use/land cover (LULC) from 1981 to 2000 had collectively affected the net productivity in the terrestrial ecosystem and thus the net carbon flux, both of which are intimately linked with the global carbon cycle. This paper represents the first national effort of its kind to systematically investigate the impact of changes of LULC on carbon cycle with high-resolution dynamic LULC data at the decadal scale (1990s and 2000s). The CEVSA was applied and driven by high resolution LULC data retrieved from remote sensing and climate data collected from two ground-based meteorological stations. In particular, it allowed us to simulate carbon fluxes (net primary productivity (NPP), vegetation carbon (VEGC) storage, soil carbon (SOC) storage, heterotrophic respiration (HR), and net ecosystem productivity (NEP)) and carbon storage from 1981 to 2000. Simulations generally agree with output from other models and results from bookkeeping approach. Based on these simulations, temporal and spatial variations in carbon storage and fluxes in China may be confirmed and we are able to relate these variations to climate variability during this period for detailed analyses to show influences of the LULC and environmental controls on NPP, NEP, HR, SOC, and VEGC. Overall, the increases in NPP were greater than HR in most of the time due to the effect of global warming with more precipitation in China from 1981 to 2000. With this trend, the NEP remained positive during that period, resulting in the net increase of total amount of carbon being stored by about 0.296 Pg C within the 20-years time frame. Because the climate effect was much greater than that of changes of LULC, the total carbon storage in China actually increased by about 0.17 Pg C within the 20 years. Such findings will contribute to the generation of control policies of carbon emissions under global climate change.

Attribution of local climate zones using a multitemporal land use/land cover classification scheme

NASA Astrophysics Data System (ADS)

Wicki, Andreas; Parlow, Eberhard

2017-04-01

Worldwide, the number of people living in an urban environment exceeds the rural population with increasing tendency. Especially in relation to global climate change, cities play a major role considering the impacts of extreme heat waves on the population. For urban planners, it is important to know which types of urban structures are beneficial for a comfortable urban climate and which actions can be taken to improve urban climate conditions. Therefore, it is essential to differ between not only urban and rural environments, but also between different levels of urban densification. To compare these built-up types within different cities worldwide, Stewart and Oke developed the concept of local climate zones (LCZ) defined by morphological characteristics. The original LCZ scheme often has considerable problems when adapted to European cities with historical city centers, including narrow streets and irregular patterns. In this study, a method to bridge the gap between a classical land use/land cover (LULC) classification and the LCZ scheme is presented. Multitemporal Landsat 8 data are used to create a high accuracy LULC map, which is linked to the LCZ by morphological parameters derived from a high-resolution digital surface model and cadastral data. A bijective combination of the different classification schemes could not be achieved completely due to overlapping threshold values and the spatially homogeneous distribution of morphological parameters, but the attribution of LCZ to the LULC classification was successful.

Assessing the Potential of Land Use Modification to Mitigate Ambient NO2 and Its Consequences for Respiratory Health

PubMed Central

Rao, Meenakshi; George, Linda A.; Shandas, Vivek; Rosenstiel, Todd N.

2017-01-01

Understanding how local land use and land cover (LULC) shapes intra-urban concentrations of atmospheric pollutants—and thus human health—is a key component in designing healthier cities. Here, NO2 is modeled based on spatially dense summer and winter NO2 observations in Portland-Hillsboro-Vancouver (USA), and the spatial variation of NO2 with LULC investigated using random forest, an ensemble data learning technique. The NO2 random forest model, together with BenMAP, is further used to develop a better understanding of the relationship among LULC, ambient NO2 and respiratory health. The impact of land use modifications on ambient NO2, and consequently on respiratory health, is also investigated using a sensitivity analysis. We find that NO2 associated with roadways and tree-canopied areas may be affecting annual incidence rates of asthma exacerbation in 4–12 year olds by +3000 per 100,000 and −1400 per 100,000, respectively. Our model shows that increasing local tree canopy by 5% may reduce local incidences rates of asthma exacerbation by 6%, indicating that targeted local tree-planting efforts may have a substantial impact on reducing city-wide incidence of respiratory distress. Our findings demonstrate the utility of random forest modeling in evaluating LULC modifications for enhanced respiratory health. PMID:28698523

Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

NASA Astrophysics Data System (ADS)

Karakacan Kuzucu, A.; Bektas Balcik, F.

2017-11-01

Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

Decadal Trend in Agricultural Abandonment and Woodland Expansion in an Agro-Pastoral Transition Band in Northern China.

PubMed

Wang, Chao; Gao, Qiong; Wang, Xian; Yu, Mei

2015-01-01

Land use land cover (LULC) changes frequently in ecotones due to the large climate and soil gradients, and complex landscape composition and configuration. Accurate mapping of LULC changes in ecotones is of great importance for assessment of ecosystem functions/services and policy-decision support. Decadal or sub-decadal mapping of LULC provides scenarios for modeling biogeochemical processes and their feedbacks to climate, and evaluating effectiveness of land-use policies, e.g. forest conversion. However, it remains a great challenge to produce reliable LULC maps in moderate resolution and to evaluate their uncertainties over large areas with complex landscapes. In this study we developed a robust LULC classification system using multiple classifiers based on MODIS (Moderate Resolution Imaging Spectroradiometer) data and posterior data fusion. Not only does the system create LULC maps with high statistical accuracy, but also it provides pixel-level uncertainties that are essential for subsequent analyses and applications. We applied the classification system to the Agro-pasture transition band in northern China (APTBNC) to detect the decadal changes in LULC during 2003-2013 and evaluated the effectiveness of the implementation of major Key Forestry Programs (KFPs). In our study, the random forest (RF), support vector machine (SVM), and weighted k-nearest neighbors (WKNN) classifiers outperformed the artificial neural networks (ANN) and naive Bayes (NB) in terms of high classification accuracy and low sensitivity to training sample size. The Bayesian-average data fusion based on the results of RF, SVM, and WKNN achieved the 87.5% Kappa statistics, higher than any individual classifiers and the majority-vote integration. The pixel-level uncertainty map agreed with the traditional accuracy assessment. However, it conveys spatial variation of uncertainty. Specifically, it pinpoints the southwestern area of APTBNC has higher uncertainty than other part of the region, and the open shrubland is likely to be misclassified to the bare ground in some locations. Forests, closed shrublands, and grasslands in APTBNC expanded by 23%, 50%, and 9%, respectively, during 2003-2013. The expansion of these land cover types is compensated with the shrinkages in croplands (20%), bare ground (15%), and open shrublands (30%). The significant decline in agricultural lands is primarily attributed to the KFPs implemented in the end of last century and the nationwide urbanization in recent decade. The increased coverage of grass and woody plants would largely reduce soil erosion, improve mitigation of climate change, and enhance carbon sequestration in this region.

LAND-USE CHANGE AND CARBON FLUX BETWEEN 1970S AND 1990S IN CENTRAL HIGHLANDS OF CHIAPAS, MEXICO

EPA Science Inventory

We present results of a study in an intensively impacted and highly fragmented landscape in which we apply field-measured carbon (C) density values to land-use/land-cover (LU/LC) statistics to estimate the flux of C between terrestrial ecosystems and the atmosphere from the 1970s...

Implications of sea level rise scenarios on land use /land cover classes of the coastal zones of Cochin, India.

PubMed

Mani Murali, R; Dinesh Kumar, P K

2015-01-15

Physical responses of the coastal zones in the vicinity of Cochin, India due to sea level rise are investigated based on analysis of inundation scenarios. Quantification of potential habitat loss was made by merging the Land use/Land cover (LU/LC) prepared from the satellite imagery with the digital elevation model. Scenarios were generated for two different rates of sea level rise and responses of changes occurred were made to ascertain the vulnerability and loss in extent. LU/LC classes overlaid on 1 m and 2 m elevation showed that it was mostly covered by vegetation areas followed by water and urban zones. For the sea level rise scenarios of 1 m and 2 m, the total inundation zones were estimated to be 169.11 km(2) and 598.83 km(2) respectively using Geographic Information System (GIS). The losses of urban areas were estimated at 43 km(2) and 187 km(2) for the 1 m and 2 m sea level rise respectively which is alarming information for the most densely populated state of India. Quantitative comparison of other LU/LC classes showed significant changes under each of the inundation scenarios. The results obtained conclusively point that sea level rise scenarios will bring profound effects on the land use and land cover classes as well as on coastal landforms in the study region. Coastal inundation would leave ocean front and inland properties vulnerable. Increase in these water levels would alter the coastal drainage gradients. Reduction in these gradients would increase flooding attributable to rainstorms which could promote salt water intrusion into coastal aquifers and force water tables to rise. Changes in the coastal landforms associated with inundation generate concern in the background that the coastal region may continue to remain vulnerable in the coming decades due to population growth and development pressures. Copyright © 2014 Elsevier Ltd. All rights reserved.

Impact of LULC change on the runoff, base flow and evapotranspiration dynamics in eastern Indian river basins during 1985-2005 using variable infiltration capacity approach

NASA Astrophysics Data System (ADS)

Das, Pulakesh; Behera, Mukunda Dev; Patidar, Nitesh; Sahoo, Bhabagrahi; Tripathi, Poonam; Behera, Priti Ranjan; Srivastava, S. K.; Roy, Partha Sarathi; Thakur, Praveen; Agrawal, S. P.; Krishnamurthy, Y. V. N.

2018-03-01

As a catchment phenomenon, land use and land cover change (LULCC) has a great role in influencing the hydrological cycle. In this study, decadal LULC maps of 1985, 1995, 2005 and predicted-2025 of the Subarnarekha, Brahmani, Baitarani, Mahanadi and Nagavali River basins of eastern India were analyzed in the framework of the variable infiltration capacity (VIC) macro scale hydrologic model to estimate their relative consequences. The model simulation showed a decrease in ET with 0.0276% during 1985-1995, but a slight increase with 0.0097% during 1995-2005. Conversely, runoff and base flow showed an overall increasing trend with 0.0319 and 0.0041% respectively during 1985-1995. In response to the predicted LULC in 2025, the VIC model simulation estimated reduction of ET with 0.0851% with an increase of runoff by 0.051%. Among the vegetation parameters, leaf area index (LAI) emerged as the most sensitive one to alter the simulated water balance. LULC alterations via deforestation, urbanization, cropland expansions led to reduced canopy cover for interception and transpiration that in turn contributed to overall decrease in ET and increase in runoff and base flow. This study reiterates changes in the hydrology due to LULCC, thereby providing useful inputs for integrated water resources management in the principle of sustained ecology.

Landscape composition and configuration in the central highlands of Ethiopia.

PubMed

Tolessa, Terefe; Senbeta, Feyera; Kidane, Moges

2016-10-01

Landscape dynamics are common phenomenon in the human-dominated environments whereby it can be observed that the composition and configuration between landscape elements change over time. This dynamism brings about habitat loss and fragmentation that can greatly alter ecosystem services at patch, class, and landscape levels. We conducted a study to examine composition and configuration of forested landscape in the central highlands of Ethiopia using satellite images of over a period of four decades, and FRAGSTAT raster dataset was used to analyze fragmentation. Our result showed five land use/land cover (LULC) types in the study area. Cultivated land and settlement land increased at the expense of forestland, shrubland, and grassland. Fragmentation analysis showed the number of patches increased for all LULC types, indicating the level of fragmentation and interspersion. Juxtaposition increased for shrubland, grassland, and cultivated lands and decreased for settlement and forestland resulting in the fragmentation and isolation of patches. The study of LULC along with fragmentation at the landscape level can help improve our understanding of the pace at which conversion of landscape elements is happening and the impacts on ecosystem services as studies of LULC are courser in nature and would not show how each land use is reducing in size, proximity and shape among other things that determine ecosystem services. Such type of studies in rural landscapes are very vital to consider appropriate land management policies for the landscape level by taking into account the interaction between each element for sustainable development. We recommend land managers, conservationists, and land owners for observing the roles of each patch in the matrix to maximize the benefits than focusing on a single element.

Simulating the impact of climate, land use and human water use on the hydrological system over the period 1850-2100 using PCR-GLOBWB

NASA Astrophysics Data System (ADS)

Bosmans, Joyce; van Beek, Rens; Bierkens, Marc

2015-04-01

In this study we investigate the impact of humans on the global hydrological system by separating the impacts of climate change, land use and land cover change, and human water use in a series of experiments with the PCR-GLOBWB hydrological model (e.g. van Beek et al., 2011; Sutanudjaja et al., 2014). We force PCR-GLOBWB with input from the EC-Earth and CESM GCMs, allowing us to extend our experiments from the pre-industrial (1850) to the end of the century (2099). Two greenhouse gas emission scenarios are used for the coming century: Representative Concentration Pathway 2.6 (RCP2.6), a low-end scenario, as well as the high-end RCP8.5 scenario. Precipitation, temperature and reference potential evapotranspiration are applied to PCR-GLOBWB, after bias-correction using the ISI-MIP method (Hempel et al., 2013). The reference potential evapotranspiration is computed using the Penman-Monteith equation with GCM wind, radiation, temperature, humidity and pressure as opposed to the Hamon method used as default in PCR-GLOBWB. To evaluate the impacts of climate change as well as land use and land cover (LULC) change, we apply a combination of fixed and transient LULC scenarios. First, LULC is kept fixed at 1850 values, so the hydrological model is only experiencing changes in precipitation, temperature and reference potential evapotranspiration. Then, LULC is allowed to vary according to historical reconstructions (HYDE) and future projections per RCP (Hurtt et al., 2011). In these experiments, anthropogenic effects are excluded. This is the first study to evaluate PCR-GLOBWB with pre-industrial or transient LULC in combination with present and future climate change. The next step is to investigate human impacts on the water system, by comparing the experiment with varying LULC to an experiment that additionally includes reservoir operations, human water abstractions including irrigation (paddy and non-paddy) and subsequent return flows. We aim to project future human impacts using information based on Shared Socioeconomic Pathways (SSPs). In previous studies, domestic, industrial and irrigation water demand were varied over the past decades in PCR-GLOBWB. Here we improve the analyses of human impacts on the hydrological system by looking further into the past and the future, as well as by comparing the impact of human water use to impacts of climate and LULC change. van Beek et al (2011), Global monthly water stress: 1. Water balance and water availability. Water Resources Research, Vol 47. Hempel et al (2013), A trend-preserving bias correction - the ISI-MIP approach. Earth System Dynamics, Vol 4. Hurtt et al (2011), Harmonization of land-use scenarios for the period 1500-2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Climatic Change, Vol 109. Sutanudjaja et al (2014), Development and validation of PCR-GLOBWB 2.0: a 5 arc min resolution global hydrology and water resources model. EGU General Assembly Conference Abstracts

Soil erosion and sediment delivery in a mountain catchment under scenarios of land use change using a spatially distributed numerical model

NASA Astrophysics Data System (ADS)

Alatorre, L. C.; Beguería, S.; Lana-Renault, N.; Navas, A.; García-Ruiz, J. M.

2012-05-01

Soil erosion and sediment yield are strongly affected by land use/land cover (LULC). Spatially distributed erosion models are of great interest to assess the expected effect of LULC changes on soil erosion and sediment yield. However, they can only be applied if spatially distributed data is available for their calibration. In this study the soil erosion and sediment delivery model WATEM/SEDEM was applied to a small (2.84 km2) experimental catchment in the Central Spanish Pyrenees. Model calibration was performed based on a dataset of soil redistribution rates derived from point 137Cs inventories, allowing capture differences per land use in the main model parameters. Model calibration showed a good convergence to a global optimum in the parameter space, which was not possible to attain if only external (not spatially distributed) sediment yield data were available. Validation of the model results against seven years of recorded sediment yield at the catchment outlet was satisfactory. Two LULC scenarios were then modeled to reproduce land use at the beginning of the twentieth century and a hypothetic future scenario, and to compare the simulation results to the current LULC situation. The results show a reduction of about one order of magnitude in gross erosion (3180 to 350 Mg yr-1) and sediment delivery (11.2 to 1.2 Mg yr-1 ha-1) during the last decades as a result of the abandonment of traditional land uses (mostly agriculture) and subsequent vegetation recolonization. The simulation also allowed assessing differences in the sediment sources and sinks within the catchment.

Land Use Land Cover Changes in Detection of Water Quality: A Study Based on Remote Sensing and Multivariate Statistics.

PubMed

Hua, Ang Kean

2017-01-01

Malacca River water quality is affected due to rapid urbanization development. The present study applied LULC changes towards water quality detection in Malacca River. The method uses LULC, PCA, CCA, HCA, NHCA, and ANOVA. PCA confirmed DS, EC, salinity, turbidity, TSS, DO, BOD, COD, As, Hg, Zn, Fe, E. coli , and total coliform. CCA confirmed 14 variables into two variates; first variate involves residential and industrial activities; and second variate involves agriculture, sewage treatment plant, and animal husbandry. HCA and NHCA emphasize that cluster 1 occurs in urban area with Hg, Fe, total coliform, and DO pollution; cluster 3 occurs in suburban area with salinity, EC, and DS; and cluster 2 occurs in rural area with salinity and EC. ANOVA between LULC and water quality data indicates that built-up area significantly polluted the water quality through E. coli , total coliform, EC, BOD, COD, TSS, Hg, Zn, and Fe, while agriculture activities cause EC, TSS, salinity, E. coli , total coliform, arsenic, and iron pollution; and open space causes contamination of turbidity, salinity, EC, and TSS. Research finding provided useful information in identifying pollution sources and understanding LULC with river water quality as references to policy maker for proper management of Land Use area.

Land Use Change and Land Degradation in Southeastern Mediterranean Spain

NASA Astrophysics Data System (ADS)

Symeonakis, Elias; Calvo-Cases, Adolfo; Arnau-Rosalen, Eva

2007-07-01

The magnitude of the environmental and social consequences of soil erosion and land degradation in semiarid areas of the Mediterranean region has long been recognized and studied. This paper investigates the interrelationship between land use/cover (LULC) changes and land degradation using remotely sensed and ancillary data for southeastern Spain. The area of study, the Xaló River catchment situated in the north of the Alicante Province, has been subjected to a number of LULC changes during the second half of the 20th century such as agricultural abandonment, forest fires, and tourist development. Aerial photographs dating back to 1956 were used for the delineation of historic LULC types; Landsat ETM+ data were used for the analysis and mapping of current conditions. Two important indicators of land degradation, namely, susceptibility to surface runoff and soil erosion, were estimated for the two dates using easily parametrizable models. The comparison of 1956 to 2000 conditions shows an overall “recuperating” trend over the catchment and increased susceptibility to soil erosion only in 3% of the catchment area. The results also identify potential degradation hot-spots where mitigation measures should be taken to prevent further degradation. The readily implemented methodology, based on modest data requirements demonstrated by this study, is a useful tool for catchment to regional scale land use change and land degradation studies and strategic planning for environmental management.

Land use change and land degradation in southeastern Mediterranean Spain.

PubMed

Symeonakis, Elias; Calvo-Cases, Adolfo; Arnau-Rosalen, Eva

2007-07-01

The magnitude of the environmental and social consequences of soil erosion and land degradation in semiarid areas of the Mediterranean region has long been recognized and studied. This paper investigates the interrelationship between land use/cover (LULC) changes and land degradation using remotely sensed and ancillary data for southeastern Spain. The area of study, the Xaló River catchment situated in the north of the Alicante Province, has been subjected to a number of LULC changes during the second half of the 20th century such as agricultural abandonment, forest fires, and tourist development. Aerial photographs dating back to 1956 were used for the delineation of historic LULC types; Landsat ETM+ data were used for the analysis and mapping of current conditions. Two important indicators of land degradation, namely, susceptibility to surface runoff and soil erosion, were estimated for the two dates using easily parametrizable models. The comparison of 1956 to 2000 conditions shows an overall "recuperating" trend over the catchment and increased susceptibility to soil erosion only in 3% of the catchment area. The results also identify potential degradation hot-spots where mitigation measures should be taken to prevent further degradation. The readily implemented methodology, based on modest data requirements demonstrated by this study, is a useful tool for catchment to regional scale land use change and land degradation studies and strategic planning for environmental management.

Ecosystem Service Valuation Assessments for Protected Area Management: A Case Study Comparing Methods Using Different Land Cover Classification and Valuation Approaches

PubMed Central

Whitham, Charlotte E. L.

2015-01-01

Accurate and spatially-appropriate ecosystem service valuations are vital for decision-makers and land managers. Many approaches for estimating ecosystem service value (ESV) exist, but their appropriateness under specific conditions or logistical limitations is not uniform. The most accurate techniques are therefore not always adopted. Six different assessment approaches were used to estimate ESV for a National Nature Reserve in southwest China, across different management zones. These approaches incorporated two different land-use land cover (LULC) maps and development of three economic valuation techniques, using globally or locally-derived data. The differences in ESV across management zones for the six approaches were largely influenced by the classifications of forest and farmland and how they corresponded with valuation coefficients. With realistic limits on access to time, data, skills and resources, and using acquired estimates from globally-relevant sources, the Buffer zone was estimated as the most valuable (2.494 million ± 1.371 million CNY yr-1 km-2) and the Non-protected zone as the least valuable (770,000 ± 4,600 CNY yr-1 km-2). However, for both LULC maps, when using the locally-based and more time and skill-intensive valuation approaches, this pattern was generally reversed. This paper provides a detailed practical example of how ESV can differ widely depending on the availability and appropriateness of LULC maps and valuation approaches used, highlighting pitfalls for the managers of protected areas. PMID:26086191

Agro-pastoral expansion and land use/land cover (LU/LC) change dynamics in Central-western Brazil

NASA Astrophysics Data System (ADS)

Sanga-Ngoie, K.; Yoshikawa, S.; Kanae, S.

2011-12-01

In Brazil, large-scale land cover changes following extensive deforestations are expected to generate big impacts onto the climate and the environment over this area, with eventually many negative feedbacks on the global scale. Mato Grosso State, located in the central western Brazil, is known to be the Brazilian state with the highest deforestation rate. Land use/land cover (LU/LC) changes have been reported to occur over large areas in this state due to the introduction of large-scale mechanized agriculture, extensive cattle ranching and uncontrolled slash-and-burn cultivation since the 1980s. In this study, we specifically aim at doing more detailed analysis for the causes of deforestation and savannization in this area, with special attention to agriculture and cattle ranching industry at the municipal district level in this state. Using GIS techniques and remotely-sensed NOAA/AVHRR data, we created 5-year Digital Vegetation Model Maps characterizing LU/LC features for every five years during the 1981-2001 periods using the PCA first components of the NOAA/AVHRR multi-spectral data. Our results make it clear that: (1) LU/LC changes among the phases are of the following 3 major types: degradation, recovery or transition; (2) The changes in LU/LC features are concomitant with the advance of cattle ranching and corn production activities toward the northern parts of the state, and with the expansion of soybean production in the central and western Mato Grosso; (3) Most of the agro-pastoral business are found in the southern Mato Grosso where about 46% of the state's deforestation during the 1981-2001 period occurred; (4) Rates of vegetation change are larger over non-inhabited areas (56%), especially in the north, than over the populated zones in the south (42%). Moreover, this work sheds some new light on the patterns of the changes in LU/LC features (deforestation and savannization) for each municipal district of Mato Grosso. In general, the following activities are shown to be the main contributors to the deforestation of tropical rainforests in Mato Grosso: cattle ranches or corn croplands in northwestern, and soybean fields in the central areas. On the other side, savannization due to soybean or corn cultivation is found mainly in the west and the southeast, respectively. It has to be noted that corn production seems to bring forth more savannization impacts than soybean cultivation over this Brazilian state. All these findings highlight the non-sustainable characteristics of resources development processes occurring not only in Mato Grosso State, but also over all the tropical rainforests in the Amazonian Basin subcontinent.

Comparing daily temperature averaging methods: the role of surface and atmosphere variables in determining spatial and seasonal variability

NASA Astrophysics Data System (ADS)

Bernhardt, Jase; Carleton, Andrew M.

2018-05-01

The two main methods for determining the average daily near-surface air temperature, twice-daily averaging (i.e., [Tmax+Tmin]/2) and hourly averaging (i.e., the average of 24 hourly temperature measurements), typically show differences associated with the asymmetry of the daily temperature curve. To quantify the relative influence of several land surface and atmosphere variables on the two temperature averaging methods, we correlate data for 215 weather stations across the Contiguous United States (CONUS) for the period 1981-2010 with the differences between the two temperature-averaging methods. The variables are land use-land cover (LULC) type, soil moisture, snow cover, cloud cover, atmospheric moisture (i.e., specific humidity, dew point temperature), and precipitation. Multiple linear regression models explain the spatial and monthly variations in the difference between the two temperature-averaging methods. We find statistically significant correlations between both the land surface and atmosphere variables studied with the difference between temperature-averaging methods, especially for the extreme (i.e., summer, winter) seasons (adjusted R2 > 0.50). Models considering stations with certain LULC types, particularly forest and developed land, have adjusted R2 values > 0.70, indicating that both surface and atmosphere variables control the daily temperature curve and its asymmetry. This study improves our understanding of the role of surface and near-surface conditions in modifying thermal climates of the CONUS for a wide range of environments, and their likely importance as anthropogenic forcings—notably LULC changes and greenhouse gas emissions—continues.

Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya.

PubMed

Richard, Kyalo; Abdel-Rahman, Elfatih M; Subramanian, Sevgan; Nyasani, Johnson O; Thiel, Michael; Jozani, Hosein; Borgemeister, Christian; Landmann, Tobias

2017-11-03

Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer's accuracy and UA: user's accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10-20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.

NUTRIENT SOUIRCES, TRANSPORT, AND FATE IN COUPLED WATERSHED-ESTUARINE SYSTEMS OF COASTAL ALABAMA

EPA Science Inventory

The processes regulating sources, transport, and fate of nutrients were studied in 3 coupled watershed-estuarine systems that varied mainly by differences in the dominant land use-land cover (LULC), i.e. Weeks Bay -- agriculture, Dog River -- urban, and Fowl River -- forest. Mea...

Land Use Change and Hydrologic Processes in High-Elevation Tropical Watersheds of the Northern Andes

NASA Astrophysics Data System (ADS)

Avery, W. A.; Riveros-Iregui, D. A.; Covino, T. P.; Peña, C.

2013-12-01

The humid tropics cover one-fifth of the Earth's land surface and generate the greatest amount of runoff of any biome globally, but remain poorly understood and understudied. Humid tropical regions of the northern and central Andes have experienced greater anthropogenic land-use/land-cover (LULC) change than nearly any other high mountain system in the world. Vast expanses of this region are currently undergoing rapid transformation to farmland for production of potatoes and pasture for cattle grazing. Although the humid tropics have some of the highest runoff ratios, precipitation, and largest river flows in the world, there is a lack of scientific literature that addresses hydrologic processes in these regions and very few field observations are available to inform management strategies to ensure the sustainability of water resources of present and future generations. We seek to improve understanding of hydrologic processes and feedbacks in the humid tropics using existing and new information from two high-elevation watersheds that span a LULC gradient in the Andes Mountains of Colombia. One site is located in the preserved Chingaza Natural National Park in Central Colombia (undisturbed). The second site is located ~60 km to the northwest and has experienced considerable LULC change over the last 40 years. Combined, these watersheds deliver over 80% of the water resources to Bogotá and neighboring communities. These watersheds have similar climatological characteristics (including annual precipitation), but have strong differences in LULC which result in substantial differences in hydrologic response and streamflow dynamics. We present an overview of many of the pressing issues and effects that land degradation and climate change are posing to the long-term sustainability of water resources in the northern Andes. Our overarching goal is to provide process-based knowledge that will be useful to prevent, mitigate, or respond to future water crises along the Andean-Amazon biome and more broadly throughout the understudied humid tropics.

Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan'an City, China.

PubMed

Zhang, Xinping; Wang, Dexiang; Hao, Hongke; Zhang, Fangfang; Hu, Youning

2017-07-26

In this study Yan'an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI) and land use/land cover (LULC) types, the landscape pattern metrics of LULC types and land surface temperature (LST) and remote sensing indexes were retrieved from Landsat data during 1990-2015, and to find factors contributed to the green space cool island intensity (GSCI) through field measurements of 34 green spaces. The results showed that during 1990-2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon's diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment.

Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan’an City, China

PubMed Central

Zhang, Xinping; Hao, Hongke; Zhang, Fangfang; Hu, Youning

2017-01-01

In this study Yan’an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI) and land use/land cover (LULC) types, the landscape pattern metrics of LULC types and land surface temperature (LST) and remote sensing indexes were retrieved from Landsat data during 1990–2015, and to find factors contributed to the green space cool island intensity (GSCI) through field measurements of 34 green spaces. The results showed that during 1990–2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon’s diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment. PMID:28933770

Predicting the impact of land management decisions on overland flow generation: Implications for cesium migration in forested Fukushima watersheds

NASA Astrophysics Data System (ADS)

Siirila-Woodburn, Erica R.; Steefel, Carl I.; Williams, Kenneth H.; Birkholzer, Jens T.

2018-03-01

The effects of land use and land cover (LULC) change on environmental systems across the land surface's "critical zone" are highly uncertain, often making prediction and risk management decision difficult. In a series of numerical experiments with an integrated hydrologic model, overland flow generation is quantified for both present day and forest thinning scenarios. A typhoon storm event in a watershed near the Fukushima Dai-ichi Nuclear Power Plant is used as an example application in which the interplay between LULC change and overland flow generation is important given that sediment-bound radionuclides may cause secondary contamination via surface water transport. Results illustrate the nonlinearity of the integrated system spanning from the deep groundwater to the atmosphere, and provide quantitative tools when determining the tradeoffs of different risk-mitigation strategies.

Land use change and effects on water quality and ecosystem health in the Lake Tahoe basin, Nevada and California: year-1 progress

USGS Publications Warehouse

Forney, William; Raumann, Christian G.; Minor, T.B.; Smith, J. LaRue; Vogel, John; Vitales, Robert

2002-01-01

As part of the requirements for the Geographic Research and Applications Prospectus grants, this Open-File Report is the second of two that resulted from the first year of the project. The first Open-File Report (OFR 01-418) introduced the project, reviewed the existing body of literature, and outlined the research approach. This document will present an update of the research approach and offer some preliminary results from multiple efforts, specifically, the production of historical digital orthophoto quadrangles, the development of the land use/land cover (LULC) classification system, the development of a temporal transportation layer, the classification of anthropogenic cover types from the IKONOS imagery, a preliminary evaluation of landscape ecology metrics (quantification of spatial and temporal patterns of ecosystem structure and function with appropriate indices) and their utility in comparing two LULC systems, and a new initiative in community-based science and facilitation.

Simulation of boreal Summer Monsoon Rainfall using CFSV2_SSiB model: sensitivity to Land Use Land Cover (LULC)

NASA Astrophysics Data System (ADS)

Chilukoti, N.; Xue, Y.

2016-12-01

The land surface play a vital role in determining the surface energy budget, accurate representation of land use and land cover (LULC) is necessary to improve forecast. In this study, we have investigated the influence of surface vegetation maps with different LULC on simulating the boreal summer monsoon rainfall. Using a National Centres for Environmental Prediction (NCEP) Coupled Forecast System version 2(CFSv2) model coupled with Simplified Simple Biosphere (SSiB) model, two experiments were conducted: one with old vegetation map and one with new vegetation map. The significant differences between new and old vegetation map were in semi-arid and arid areas. For example, in old map Tibetan plateau classified as desert, which is not appropriate, while in new map it was classified as grasslands or shrubs with bare soil. Old map classified the Sahara desert as a bare soil and shrubs with bare soil, whereas in new map it was classified as bare ground. In addition to central Asia and the Sahara desert, in new vegetation map, Europe had more cropped area and India's vegetation cover was changed from crops and forests to wooded grassland and small areas of grassland and shrubs. The simulated surface air temperature with new map shows a significant improvement over Asia, South Africa, and northern America by some 1 to 2ºC and 2 to 3ºC over north east China and these are consistent with the reduced rainfall biases over Africa, near Somali coast, north east India, Bangladesh, east China sea, eastern Pacific and northern USA. Over Indian continent and bay of Bengal dry rainfall anomalies that is the only area showing large dry rainfall bias, however, they were unchanged with new map simulation. Overall the CFSv2(coupled with SSiB) model with new vegetation map show a promising result in improving the monsoon forecast by improving the Land -Atmosphere interactions. To compare with the LULC forcing, experiment was conducted using the Global Forecast System (GFS) simulations forced with different observed Sea Surface Temperatures (SST) for the same period: one is from NCEP reanalysis and one from Hadley Center. They have substantial difference in Indian Ocean. Preliminary analysis shows that, the impact of these two SST data sets on Indian summer monsoon rainfall has no significant impact.

Effects of Land-use/Land-cover and Climate Changes on Water Quantity and Quality in Sub-basins near Major US Cities in the Great Lakes Region

NASA Astrophysics Data System (ADS)

Murphy, L.; Al-Hamdan, M. Z.; Crosson, W. L.; Barik, M.

2017-12-01

Land-cover change over time to urbanized, less permeable surfaces, leads to reduced water infiltration at the location of water input while simultaneously transporting sediments, nutrients and contaminants farther downstream. With an abundance of agricultural fields bordering the greater urban areas of Milwaukee, Detroit, and Chicago, water and nutrient transport is vital to the farming industry, wetlands, and communities that rely on water availability. Two USGS stream gages each located within a sub-basin near each of these Great Lakes Region cities were examined, one with primarily urban land-cover between 1992 and 2011, and one with primarily agriculture land-cover. ArcSWAT, a watershed model and soil and water assessment tool used in extension with ArcGIS, was used to develop hydrologic models that vary the land-covers to simulate surface runoff during a model run period from 2004 to 2008. Model inputs that include a digital elevation model (DEM), Landsat-derived land-use/land-cover (LULC) satellite images from 1992, 2001, and 2011, soil classification, and meteorological data were used to determine the effect of different land-covers on the water runoff, nutrients and sediments. The models were then calibrated and validated to USGS stream gage data measurements over time. Additionally, the watershed model was run based on meteorological data from an IPCC CMIP5 high emissions climate change scenario for 2050. Model outputs from the different LCLU scenarios were statistically evaluated and results showed that water runoff, nutrients and sediments were impacted by LULC change in four out of the six sub-basins. In the 2050 climate scenario, only one out of the six sub-basin's water quantity and quality was affected. These results contribute to the importance of developing hydrologic models as the dependence on the Great Lakes as a freshwater resource competes with the expansion of urbanization leading to the movement of runoff, nutrients, and sediments off the land.

Spatial relations between floodplain environments and land use - land cover of a large lowland tropical river valley: Pánuco basin, México.

PubMed

Hudson, Paul F; Colditz, René R; Aguilar-Robledo, Miguel

2006-09-01

Large lowland river valleys include a variety of floodplain environments that represent opportunities and constraints for human activities. This study integrates extensive field observations and geomorphic data with analysis of satellite remote sensing data to examine spatial relations between land use/land cover (LULC) and floodplain environments in the lower Pánuco basin of eastern Mexico. The floodplain of the lower Pánuco basin was delineated by combining a digital elevation model with a satellite image of a large flood event. The LULC was classified by combining a hybrid classification strategy with image stratification, applied to 15-m-resolution ASTER data. A geomorphic classification of floodplain environments was performed using a dry-stage image (ASTER data) and a 1993 Landsat image acquired during a large flood event. Accuracy assessment was based on aerial photographs (1:38,000), global positioning satellite ground-truthing, and a Landsat 7ETM(+) image from 2000, which resulted in an overall accuracy of 82.9% and a KHAT of 79.8% for the LULC classification. The geomorphic classification yielded 83.5% overall accuracy, whereas the KHAT was 81.5%. LULC analysis was performed for the entire floodplain and individually within four valley segments. The analysis indicates that the study area is primarily utilized for grazing and farming. Agriculture is primarily associated with coarse-grained (sandy/silty) natural levee and point bar units close to the river channel, whereas cattle grazing occurs in distal and lower-lying reaches dominated by cohesive fine-grained (clayey) deposits, such as backswamps. In the Pánuco valley, wetlands and lakes occur within backswamp environments, whereas in the Moctezuma segments, wetlands and lakes are associated with relict channels. This study reveals considerable variation in LULC related to spatial differences in floodplain environments and illustrates the importance of considering older anthropogenic influences on the landscape. The research design should be applicable for other large lowland coastal plain river valleys where agriculture is a major component of the floodplain landscape.

Effects of Green Space and Land Use/Land Cover on Urban Heat Island in a Subtropical Mega-city in China

NASA Astrophysics Data System (ADS)

Qiu, G. Y.; Li, X.; Li, H.; Guo, Q.

2014-12-01

With the quick expansion of urban in size and population, its urban heat island intensity (UHII, expressed as the temperature difference between urban and rural areas) increased rapidly. However, very few studies could quantitatively reveal the effects of green space and land use/land cover (LULC) on urban thermal environment because of lacking of the detailed measurement. This study focuses on quantifying the effects of green space and LULC on urban Heat Island (UHI) in Shenzhen, a mega subtropical city in China. Extensive measurements (air temperature and humidity) were made by mobile traverse method in a transect of 8 km in length, where a variety of LULC types were included. Measurements were carried out at 2 hours interval for 2 years (totally repeated for 7011 times). According to LULC types, we selected 5 different LULC types for studying, including water body, village in the city, shopping center (commercial area), urban green space (well-vegetated area) and suburb (forest). The main conclusions are obtained as follows: (1) The temperature difference between the 5 different urban landscapes is obvious, i.e. shopping center > village in the city > urban water body > urban green space > suburb; (2) Air temperature and UHII decreases linearly with the increase of green space in urban; (3) Green space and water body in urban have obvious effects to reduce the air temperature by evapotranspiration. Compared to the commercial areas, urban water body can relieve the IUHI by 0.9℃, while the urban green space can relieve the IUHI by 1.57℃. The cooling effect of the urban green space is better than that of the urban water body; (4) Periodic activity of human being has obvious effects on urban air temperature. The UHII on Saturday and Sunday are higher than that from Monday to Friday, respectively higher for 0.65, 0.57, 0.26 and 0.21℃. Thursday and Friday have the minimum air temperature and UHII. These results indicate that increase in urban evapotranspiration by increasing green space could be a useful way to improve urban thermal environment and mitigation of UHI.

Analysing land cover and land use change in the Ruma National Park and surroundings in Kenya

NASA Astrophysics Data System (ADS)

Scharsich, Valeska; Ochuodho Otieno, Dennis; Bogner, Christina

2017-04-01

The change of land use and land cover (LULC) is often driven by the growth of human population. In the Lambwe valley, Kenya, the most important reason for accelerated settlement in the last decades was the control of the tsetse fly, the biological vector of trypanosomes. Since the huge efforts of tsetse control in the 1970s, the population of the Lambwe valley in Kenya increased rapidly and therefore the cultivated area expanded. This amplified the pressure on the forested areas at higher elevations and the Ruma National Park which occupies one third of the Lambwe valley. Here, we investigate possible effects of this pressure on the land cover in the Lambwe valley and in particular in the Ruma National Park. To answer this question, we analysed the surface reflectance of three Landsat images of Ruma National Park and its surroundings from 1984, 2002 and 2014. To compensate for the lack of ground data we inferred past land use and land cover from recent observations combining Google Earth images and change detection. By supervised classification with Random Forests, we identified four land use and land cover types, namely the forest dominant at the high elevation; dense shrub land; savanna; and sparsely covered soil including bare light soils with little vegetation, fields and settlements. Subsequently, we compared the three classifications and identified LULC changes that occurred between 1984 and 2014. We observed an increase of agricultural area in the western part of the Lambwe valley, where high elevation vegetation was dominant. This goes hand in hand with farming on higher slopes and a decrease of forest. In the National Park itself the savanna increased by about 8% and the proportion of sparsely covered soil decreased by about 10%. This might be due to the fire management in the park and the recovering of burned areas.

Classification of High Spatial Resolution, Hyperspectral Remote Sensing Imagery of the Little Miami River Watershed in Southwest Ohio, USA (Final)

EPA Science Inventory

EPA announced the availability of the final report,. This report and associated land use/land cover (LULC) coverage is the result o...

Impacts of Urbanization on Flood and Soil Erosion Hazards in Istanbul, Turkey

ERIC Educational Resources Information Center

Ozacar, Biricik Gozde

2013-01-01

Due to the inappropriate planning and explosive population growth in urban areas, especially in developing countries, sustainable and disaster-safe urbanization has become the most important challenge for governments. Urbanization presents benefits in different ways but has led simultaneously to changes in land use/land cover (LULC), impacting…

Monitoring and predicting the fecal indicator bacteria concentrations from agricultural, mixed land use and urban stormwater runoff.

PubMed

Paule-Mercado, M A; Ventura, J S; Memon, S A; Jahng, D; Kang, J-H; Lee, C-H

2016-04-15

While the urban runoff are increasingly being studied as a source of fecal indicator bacteria (FIB), less is known about the occurrence of FIB in watershed with mixed land use and ongoing land use and land cover (LULC) change. In this study, Escherichia coli (EC) and fecal streptococcus (FS) were monitored from 2012 to 2013 in agricultural, mixed and urban LULC and analyzed according to the most probable number (MPN). Pearson correlation was used to determine the relationship between FIB and environmental parameters (physicochemical and hydrometeorological). Multiple linear regressions (MLR) were used to identify the significant parameters that affect the FIB concentrations and to predict the response of FIB in LULC change. Overall, the FIB concentrations were higher in urban LULC (EC=3.33-7.39; FS=3.30-7.36log10MPN/100mL) possibly because of runoff from commercial market and 100% impervious cover (IC). Also, during early-summer season; this reflects a greater persistence and growth rate of FIB in a warmer environment. During intra-event, however, the FIB concentrations varied according to site condition. Anthropogenic activities and IC influenced the correlation between the FIB concentrations and environmental parameters. Stormwater temperature (TEMP), turbidity, and TSS positively correlated with the FIB concentrations (p>0.01), since IC increased, implying an accumulation of bacterial sources in urban activities. TEMP, BOD5, turbidity, TSS, and antecedent dry days (ADD) were the most significant explanatory variables for FIB as determined in MLR, possibly because they promoted the FIB growth and survival. The model confirmed the FIB concentrations: EC (R(2)=0.71-0.85; NSE=0.72-0.86) and FS (R(2)=0.65-0.83; NSE=0.66-0.84) are predicted to increase due to urbanization. Therefore, these findings will help in stormwater monitoring strategies, designing the best management practice for FIB removal and as input data for stormwater models. Copyright © 2016 Elsevier B.V. All rights reserved.

Classification of forest land attributes using multi-source remotely sensed data

NASA Astrophysics Data System (ADS)

Pippuri, Inka; Suvanto, Aki; Maltamo, Matti; Korhonen, Kari T.; Pitkänen, Juho; Packalen, Petteri

2016-02-01

The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008-2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.

Use of multi-temporal SPOT-5 satellite images for land degradation assessment in Cameron Highlands, Malaysia using Geospatial techniques

NASA Astrophysics Data System (ADS)

Nampak, Haleh; Pradhan, Biswajeet

2016-07-01

Soil erosion is the common land degradation problem worldwide because of its economic and environmental impacts. Therefore, land-use change detection has become one of the major concern to geomorphologists, environmentalists, and land use planners due to its impact on natural ecosystems. The objective of this paper is to evaluate the relationship between land use/cover changes and land degradation in the Cameron highlands (Malaysia) through multi-temporal remotely sensed satellite images and ancillary data. Land clearing in the study area has resulted increased soil erosion due to rainfall events. Also unsustainable development and agriculture, mismanagement and lacking policies contribute to increasing soil erosion rates. The LULC distribution of the study area was mapped for 2005, 2010, and 2015 through SPOT-5 satellite imagery data which were classified based on object-based classification. A soil erosion model was also used within a GIS in order to study the susceptibility of the areas affected by changes to overland flow and rain splash erosion. The model consists of four parameters, namely soil erodibility, slope, vegetation cover and overland flow. The results of this research will be used in the selection of the areas that require mitigation processes which will reduce their degrading potential. Key words: Land degradation, Geospatial, LULC change, Soil erosion modelling, Cameron highlands.

Evaluating Impacts of Land Use/Land Cover Change on Water Resources in Semiarid Regions

NASA Astrophysics Data System (ADS)

Scanlon, B. R.; Faunt, C. C.; Pool, D. R.; Reedy, R. C.

2017-12-01

Land use/land cover (LU/LC) changes play an integral role in water resources by controlling the partitioning of water at the land surface. Here we evaluate impacts of changing LU/LC on water resources in response to climate variation and change and land use change related to agriculture using data from semiarid regions in the southwestern U.S. Land cover changes in response to climate can amplify or dampen climate impacts on water resources. Changes from wet Pleistocene to much drier Holocene climate resulted in expansion of perennial vegetation, amplifying climate change impacts on water resources by reducing groundwater recharge as shown in soil profiles in the southwestern U.S.. In contrast, vegetation response to climate extremes, including droughts and floods, dampen impacts of these extremes on water resources, as shown by water budget monitoring in the Mojave Desert. Agriculture often involves changes from native perennial vegetation to annual crops increasing groundwater recharge in many semiarid regions. Irrigation based on conjunctive use of surface water and groundwater increases water resource availability, as shown in the Central Valley of California and in southern Arizona. Surface water irrigation in these regions is enhanced by water transported from more humid settings through extensive pipelines. These projects have reversed long-term declining groundwater trends in some regions. While irrigation design has often focused on increased efficiency, "more crop per drop", optimal water resource management may benefit more from inefficient (e.g. flood irrigation) surface-water irrigation combined with efficient (e.g. subsurface drip) irrigation to maximize groundwater recharge, as seen in parts of the Central Valley. Flood irrigation of perennial crops, such as almonds and vineyards, during winter is being considered in the Central Valley to enhance groundwater recharge. Managed aquifer recharge can be considered a special case of conjunctive use of surface water and groundwater use where spreading basins focus recharge in southern California and Arizona. This overview highlights the importance of changes in LU/LC in controlling water budgets in semiarid regions. Understanding these controls should allow us to better manage water resources.

Development of a Land Use Mapping and Monitoring Protocol for the High Plains Region: A Multitemporal Remote Sensing Application

NASA Technical Reports Server (NTRS)

Price, Kevin P.; Nellis, M. Duane

1996-01-01

The purpose of this project was to develop a practical protocol that employs multitemporal remotely sensed imagery, integrated with environmental parameters to model and monitor agricultural and natural resources in the High Plains Region of the United States. The value of this project would be extended throughout the region via workshops targeted at carefully selected audiences and designed to transfer remote sensing technology and the methods and applications developed. Implementation of such a protocol using remotely sensed satellite imagery is critical for addressing many issues of regional importance, including: (1) Prediction of rural land use/land cover (LULC) categories within a region; (2) Use of rural LULC maps for successive years to monitor change; (3) Crop types derived from LULC maps as important inputs to water consumption models; (4) Early prediction of crop yields; (5) Multi-date maps of crop types to monitor patterns related to crop change; (6) Knowledge of crop types to monitor condition and improve prediction of crop yield; (7) More precise models of crop types and conditions to improve agricultural economic forecasts; (8;) Prediction of biomass for estimating vegetation production, soil protection from erosion forces, nonpoint source pollution, wildlife habitat quality and other related factors; (9) Crop type and condition information to more accurately predict production of biogeochemicals such as CO2, CH4, and other greenhouse gases that are inputs to global climate models; (10) Provide information regarding limiting factors (i.e., economic constraints of pumping, fertilizing, etc.) used in conjunction with other factors, such as changes in climate for predicting changes in rural LULC; (11) Accurate prediction of rural LULC used to assess the effectiveness of government programs such as the U.S. Soil Conservation Service (SCS) Conservation Reserve Program; and (12) Prediction of water demand based on rural LULC that can be related to rates of draw-down of underground water supplies.

Integrating global satellite-derived data products as a pre-analysis for hydrological modelling studies: a case study for the Red River Basin

USDA-ARS?s Scientific Manuscript database

With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P) and land use / land cover (LULC) is c...

Modelling regional land change scenarios to assess land abandonment and reforestation dynamics in the Pyrenees (France)

USGS Publications Warehouse

Vacquie, Laure; Houet, Thomas; Sohl, Terry L.; Reker, Ryan R.; Sayler, Kristi L.

2015-01-01

Over the last decades and centuries, European mountain landscapes have experienced substantial transformations. Natural and anthropogenic LULC changes (land use and land cover changes), especially agro-pastoral activities, have directly influenced the spatial organization and composition of European mountain landscapes. For the past sixty years, natural reforestation has been occurring due to a decline in both agricultural production activities and rural population. Stakeholders, to better anticipate future changes, need spatially and temporally explicit models to identify areas at risk of land change and possible abandonment. This paper presents an integrated approach combining forecasting scenarios and a LULC changes simulation model to assess where LULC changes may occur in the Pyrenees Mountains, based on historical LULC trends and a range of future socio-economic drivers. The proposed methodology considers local specificities of the Pyrenean valleys, sub-regional climate and topographical properties, and regional economic policies. Results indicate that some regions are projected to face strong abandonment, regardless of the scenario conditions. Overall, high rates of change are associated with administrative regions where land productivity is highly dependent on socio-economic drivers and climatic and environmental conditions limit intensive (agricultural and/or pastoral) production and profitability. The combination of the results for the four scenarios allows assessments of where encroachment (e.g. colonization by shrublands) and reforestation are the most probable. This assessment intends to provide insight into the potential future development of the Pyrenees to help identify areas that are the most sensitive to change and to guide decision makers to help their management decisions.

Landscape Based Modeling of Nonpoint Source Nitrogen Loading in the Neuse River Basin, North Carolina

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garten, C.T.

2001-01-11

The objective of this research was to arrive at a quantitative and qualitative assessment of nonpoint sources of potential excess N under different land use/land cover (LULC) categories in the Neuse River Basin on a seasonal time scale. This assessment is being supplied to EPA's Landscape Characterization Branch, National Exposure Research Laboratory, in Research Triangle Park, NC, for inclusion in a hydrologic model to predict seasonal fluxes of N from the terrestrial landscape to surface receiving waters and groundwater in the Neuse River Basin. The analysis was performed in the following five steps: (1) development of a conceptual model tomore » predict potential excess N on land, (2) a literature review to parameterize N fluxes under LULC categories found in the Neuse River Basin, (3) acquisition of high resolution (15-m pixel) LULC data from EPA's Landscape Characterization Branch, National Exposure Research Laboratory, in Research Triangle Park, NC, (4) acquisition of a soil N inventory map for the Neuse River Basin, (5) calculations of potential excess N on a seasonal basis for the entire Neuse River Basin.« less

Public participation GIS: a method for identifying ecosystems services

USGS Publications Warehouse

Brown, Greg; Montag, Jessica; Lyon, Katie

2012-01-01

This study evaluated the use of an Internet-based public participation geographic information system (PPGIS) to identify ecosystem services in Grand County, Colorado. Specific research objectives were to examine the distribution of ecosystem services, identify the characteristics of participants in the study, explore potential relationships between ecosystem services and land use and land cover (LULC) classifications, and assess the methodological strengths and weakness of the PPGIS approach for identifying ecosystem services. Key findings include: (1) Cultural ecosystem service opportunities were easiest to identify while supporting and regulatory services most challenging, (2) participants were highly educated, knowledgeable about nature and science, and have a strong connection to the outdoors, (3) some LULC classifications were logically and spatially associated with ecosystem services, and (4) despite limitations, the PPGIS method demonstrates potential for identifying ecosystem services to augment expert judgment and to inform public or environmental policy decisions regarding land use trade-offs.

Effects of land use and land cover changes on water quality in the uMngeni river catchment, South Africa

NASA Astrophysics Data System (ADS)

Namugize, Jean Nepomuscene; Jewitt, Graham; Graham, Mark

2018-06-01

Land use and land cover change are major drivers of water quality deterioration in watercourses and impoundments. However, understanding of the spatial and temporal variability of land use change characteristics and their link to water quality parameters in catchments is limited. As a contribution to address this limitation, the objective of this study is to assess the linkages between biophysico-chemical water quality parameters and land use and land cover (LULC) classes in the upper reaches of the uMngeni Catchment, a rapidly developing catchment in South Africa. These were assessed using Geographic Information Systems tools and statistical analyses for the years 1994, 2000, 2008 and 2011 based on changes over time of eight LULC classes and available water quality information. Natural vegetation, forest plantations and cultivated areas occupy 85% of the catchment. Cultivated, urban/built-up and degraded areas increased by 6%, 4.5% and 3%, respectively coinciding with a decrease in natural vegetation by 17%. Variability in the concentration of water quality parameters from 1994 to 2011 and an overall decline in water quality were observed. Escherichia coli (E. coli) levels exceeding the recommended guidelines for recreation and public health protection was noted as a major issue at seven of the nine sampling points. Overall, water supply reservoirs in the catchment retained over 20% of nutrients and over 85% of E. coli entering them. A relationship between land use types and water quality variables was found. However, the degree and magnitude of the associations varies between sub-catchments and is difficult to quantify. This highlights the complexity and the site-specific nature of relationships between land use types and water quality parameters in the catchment. Thus, this study provides useful findings on the general relationship between land use and land cover and water quality degradation, but highlights the risks of applying simple relationships or adding complex relationships in the management of the catchment.

Multi-scale 46-year remote sensing change detection of diamond mining and land cover in a conflict and post-conflict setting

USGS Publications Warehouse

Dewitt, Jessica D.; Chirico, Peter G.; Bergstresser, Sarah E.; Warner, Timothy A.

2017-01-01

The town of Tortiya was created in the rural northern region of Côte d′Ivoire in the late 1940s to house workers for a new diamond mine. Nearly three decades later, the closure of the industrial-scale diamond mine in 1975 did not diminish the importance of diamond profits to the region's economy, and resulted in the growth of artisanal and small-scale diamond mining (ASM) within the abandoned industrial-scale mining concession. In the early 2000s, the violent conflict that arose in Côte d′Ivoire highlighted the importance of ASM land use to the local economy, but also brought about international concerns that diamond profits were being used to fund the rebellion. In recent years, cashew plantations have expanded exponentially in the region, diversifying economic activity, but also creating the potential for conflict between diamond mining and agricultural land uses. As the government looks to address the future of Tortiya and this potential conflict, a detailed spatio-temporal understanding of the changes in these two land uses over time may assist in informing policymaking. Remotely sensed imagery presents an objective and detailed spatial record of land use/land cover (LULC), and change detection methods can provide quantitative insight regarding regional land cover trends. However, the vastly different scales of ASM and cashew orchards present a unique challenge to comprehensive understanding of land use change in the region. In this study, moderate-scale categories of LULC, including cashew orchards, uncultivated forest, urban space, mining/ bare, and mixed vegetation, were produced through supervised classification of Landsat multispectral imagery from 1984, 1991, 2000, 2007, and 2014. The fine-scale ASM land use was identified through manual interpretation of annually acquired high resolution satellite imagery. Corona imagery was also integrated into the study to extend the temporal duration of the remote sensing record back to the period of industrial-scale mining. These different-scale analyses were then integrated to create a record of 46 years of mining activity and land cover change in Tortiya. While similar in spatial extent, the mining/ bare class in the integrated analysis exhibits a substantially different spatial distribution than in the original classifications. This additional information regarding the locations of ASM activity in the Tortiya area is important from a policy and planning perspective. The results of this study also suggest that LULC classifications of Landsat imagery do not consistently capture areas of ASM in the Côte d′Ivoire landscape.

Land-use impacts on water resources and protected areas: applications of state-and-transition simulation modeling of future scenarios

USGS Publications Warehouse

Wilson, Tamara; Sleeter, Benjamin M.; Sherba, Jason T.; Dick Cameron,

2015-01-01

Human land use will increasingly contribute to habitat loss and water shortages in California, given future population projections and associated land-use demand. Understanding how land-use change may impact future water use and where existing protected areas may be threatened by land-use conversion will be important if effective, sustainable management approaches are to be implemented. We used a state-and-transition simulation modeling (STSM) framework to simulate spatially-explicit (1 km2) historical (1992-2010) and future (2011-2060) land-use change for 52 California counties within Mediterranean California ecoregions. Historical land use and land cover (LULC) change estimates were derived from the Farmland Mapping and Monitoring Program dataset and attributed with county-level agricultural water-use data from the California Department of Water Resources. Five future alternative land-use scenarios were developed and modeled using the historical land-use change estimates and land-use projections based on the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios A2 and B1 scenarios. Spatial land-use transition outputs across scenarios were combined to reveal scenario agreement and a land conversion threat index was developed to evaluate vulnerability of existing protected areas to proximal land conversion. By 2060, highest LULC conversion threats were projected to impact nearly 10,500 km2 of land area within 10 km of a protected area boundary and over 18,000 km2 of land area within essential habitat connectivity areas. Agricultural water use declined across all scenarios perpetuating historical drought-related land use from 2008-2010 and trends of annual cropland conversion into perennial woody crops. STSM is useful in analyzing land-use related impacts on water resource use as well as potential threats to existing protected land. Exploring a range of alternative, yet plausible, LULC change impacts will help to better inform resource management and mitigation strategies.

Analysis of Relationship Between Urban Heat Island Effect and Land Use/cover Type Using Landsat 7 ETM+ and Landsat 8 Oli Images

NASA Astrophysics Data System (ADS)

Aslan, N.; Koc-San, D.

2016-06-01

The main objectives of this study are (i) to calculate Land Surface Temperature (LST) from Landsat imageries, (ii) to determine the UHI effects from Landsat 7 ETM+ (June 5, 2001) and Landsat 8 OLI (June 17, 2014) imageries, (iii) to examine the relationship between LST and different Land Use/Land Cover (LU/LC) types for the years 2001 and 2014. The study is implemented in the central districts of Antalya. Initially, the brightness temperatures are retrieved and the LST values are calculated from Landsat thermal images. Then, the LU/LC maps are created from Landsat pan-sharpened images using Random Forest (RF) classifier. Normalized Difference Vegetation Index (NDVI) image, ASTER Global Digital Elevation Model (GDEM) and DMSP_OLS nighttime lights data are used as auxiliary data during the classification procedure. Finally, UHI effect is determined and the LST values are compared with LU/LC classes. The overall accuracies of RF classification results were computed higher than 88 % for both Landsat images. During 13-year time interval, it was observed that the urban and industrial areas were increased significantly. Maximum LST values were detected for dry agriculture, urban, and bareland classes, while minimum LST values were detected for vegetation and irrigated agriculture classes. The UHI effect was computed as 5.6 °C for 2001 and 6.8 °C for 2014. The validity of the study results were assessed using MODIS/Terra LST and Emissivity data and it was found that there are high correlation between Landsat LST and MODIS LST data (r2 = 0.7 and r2 = 0.9 for 2001 and 2014, respectively).

Woody encroachment and soil carbon stocks in subalpine areas in the Central Spanish Pyrenees.

PubMed

Nadal-Romero, E; Otal-Laín, I; Lasanta, T; Sánchez-Navarrete, P; Errea, P; Cammeraat, E

2018-05-01

Woody encroachment has been an ongoing process in the subalpine belt of Mediterranean mountains, after land abandonment, the disappearance of the transhumant system and the decrease of the livestock number. The main objectives of this study were: (i) to identify land use/land cover (LULC) changes from 1956 to 2015, and (ii) to investigate the effects of LULC changes in physical and chemical soil properties and soil organic carbon (SOC) and nitrogen (N) stocks. It is hypothesized that woody encroachment in the subalpine belt may lead to significant changes in soil properties, and will generate an increase in the SOC stocks. A land use gradient was identified in the subalpine belt of the Central Spanish Pyrenees: (i) subalpine grasslands, (ii) shrublands, (iii) young forests, and (iv) old forests. Mineral soil samples were collected every 10 cm, down to 40 cm, at three points per each LULC and a total of 48 samples were analyzed. The results showed that (i) woody encroachment has occurred from 1956 to 2015 due to the expansion of coniferous forests and shrublands (at the expense of grasslands), (ii) land cover and soil depth had significant effects on soil properties (except for pH), being larger in the uppermost 0-10 cm depth, (iii) SOC and N contents and stocks were higher in the grassland sites, and (iv) the woody encroachment process initially produced a decrease in the SOC stocks (shrublands), but no differences were observed considering the complete soil profile between grasslands and young and old forests. Further studies, describing SOC stabilization and quantifying above-ground carbon (shrub and tree biomass) are required. Copyright © 2018 Elsevier B.V. All rights reserved.

Riparian swallows as integrators of landscape change in a multiuse river system: implications for aquatic-to-terrestrial transfers of contaminants.

PubMed

Alberts, Jeremy M; Sullivan, S Mažeika P; Kautza, A

2013-10-01

Recent research has highlighted the transfer of contaminants from aquatic to terrestrial ecosystems via predation of aquatic emergent insects by riparian consumers. The influence of adjacent land use and land cover (LULC) on aquatic-to-terrestrial contaminant transfer, however, has received limited attention. From 2010 to 2012, at 11 river reaches in the Scioto River basin (OH, USA), we investigated the relationships between LULC and selenium (Se) and mercury (Hg) concentrations in four species of riparian swallows. Hg concentrations in swallows were significantly higher at rural reaches than at urban reaches (t=-3.58, P<0.001, df=30), whereas Se concentrations were positively associated with adjacent land cover characterized by mature tree cover (R(2)=0.49, P=0.006). To an extent, these relationships appear to be mediated by swallow reliance on aquatic emergent insects. For example, tree swallows (Tachycineta bicolor) at urban reaches exhibited a higher proportion of aquatic prey in their diet, fed at a higher trophic level, and exhibited elevated Se levels. We also found that both Se and Hg concentrations in adult swallows were significantly higher than those observed in nestlings at both urban and rural reaches (Se: t=-2.83, P=0.033, df=3; Hg: t=-3.22, P=0.024, df=3). Collectively, our results indicate that riparian swallows integrate contaminant exposure in linked aquatic-terrestrial systems and that LULC may strongly regulate aquatic contaminant flux to terrestrial consumers. Copyright © 2013 Elsevier B.V. All rights reserved.

Spatial variations in water quality of river Ganga with respect to land uses in Varanasi.

PubMed

Sharma, Shikha; Roy, Arijit; Agrawal, Madhoolika

2016-11-01

Water quality of a river is a function of surrounding environment and land use due to its connectivity with land, resulting in pollutants finding their way through land. This necessitates a spatially explicit study of river ecology. The paper presents a pioneer study to establish and explore the linkage between land use and water quality of river Ganga in Varanasi district. The land use land cover (LULC) map of 20 km of river stretch for buffer radii of 1000 m in Varanasi revealed that riparian vegetation is negligible in the district. The hierarchical cluster analysis of LULC data suggested that there are two major land use categories, viz., urban and agriculture. The land use wise principal component analysis (PCA) suggested that urbanized areas are major contributor of metals, whereas agricultural land contributes organic matter into the river. The Spearman correlation study revealed that with rising urbanization, the pollutant load into the river increased compared to that from agricultural land use. The statistical analysis of the data clearly concluded that water quality of river Ganga at Varanasi was a function of adjacent land use. The study provides an insight anticipating the Indian government to embrace the relationship of land use to river water quality while formulating policies for the upcoming River Regulation Zone.

Simulation of the hyperspectral data from multispectral data using Python programming language

NASA Astrophysics Data System (ADS)

Tiwari, Varun; Kumar, Vinay; Pandey, Kamal; Ranade, Rigved; Agarwal, Shefali

2016-04-01

Multispectral remote sensing (MRS) sensors have proved their potential in acquiring and retrieving information of Land Use Land (LULC) Cover features in the past few decades. These MRS sensor generally acquire data within limited broad spectral bands i.e. ranging from 3 to 10 number of bands. The limited number of bands and broad spectral bandwidth in MRS sensors becomes a limitation in detailed LULC studies as it is not capable of distinguishing spectrally similar LULC features. On the counterpart, fascinating detailed information available in hyperspectral (HRS) data is spectrally over determined and able to distinguish spectrally similar material of the earth surface. But presently the availability of HRS sensors is limited. This is because of the requirement of sensitive detectors and large storage capability, which makes the acquisition and processing cumbersome and exorbitant. So, there arises a need to utilize the available MRS data for detailed LULC studies. Spectral reconstruction approach is one of the technique used for simulating hyperspectral data from available multispectral data. In the present study, spectral reconstruction approach is utilized for the simulation of hyperspectral data using EO-1 ALI multispectral data. The technique is implemented using python programming language which is open source in nature and possess support for advanced imaging processing libraries and utilities. Over all 70 bands have been simulated and validated using visual interpretation, statistical and classification approach.

Mapping tsunami impacts on land cover and related ecosystem service supply in Phang Nga, Thailand

NASA Astrophysics Data System (ADS)

Kaiser, G.; Burkhard, B.; Römer, H.; Sangkaew, S.; Graterol, R.; Haitook, T.; Sterr, H.; Sakuna-Schwartz, D.

2013-12-01

The 2004 Indian Ocean tsunami caused damages to coastal ecosystems and thus affected the livelihoods of the coastal communities who depend on services provided by these ecosystems. The paper presents a case study on evaluating and mapping the spatial and temporal impacts of the tsunami on land use and land cover (LULC) and related ecosystem service supply in the Phang Nga province, Thailand. The method includes local stakeholder interviews, field investigations, remote-sensing techniques, and GIS. Results provide an ecosystem services matrix with capacity scores for 18 LULC classes and 17 ecosystem functions and services as well as pre-/post-tsunami and recovery maps indicating changes in the ecosystem service supply capacities in the study area. Local stakeholder interviews revealed that mangroves, casuarina forest, mixed beach forest, coral reefs, tidal inlets, as well as wetlands (peat swamp forest) have the highest capacity to supply ecosystem services, while e.g. plantations have a lower capacity. The remote-sensing based damage and recovery analysis showed a loss of the ecosystem service supply capacities in almost all LULC classes for most of the services due to the tsunami. A fast recovery of LULC and related ecosystem service supply capacities within one year could be observed for e.g. beaches, while mangroves or casuarina forest needed several years to recover. Applying multi-temporal mapping the spatial variations of recovery could be visualised. While some patches of coastal forest were fully recovered after 3 yr, other patches were still affected and thus had a reduced capacity to supply ecosystem services. The ecosystem services maps can be used to quantify ecological values and their spatial distribution in the framework of a tsunami risk assessment. Beyond that they are considered to be a useful tool for spatial analysis in coastal risk management in Phang Nga.

Examination of Land Use, Hydrology, and Perceptions of Use and Management of the Colombian Paramo with Implications for Water Quality and Availability Concerns for Affected Watersheds

NASA Astrophysics Data System (ADS)

Tyson, A. F.; Covino, T.; Riveros-Iregui, D. A.; Gonzalez-Pinzon, R.

2015-12-01

The Northern and Central Andes have experienced greater anthropogenic land use/land-cover (LULC) change than nearly any other high mountain system on Earth. In particular, páramo ecosystems, high elevation grasslands of the tropical Andes of Colombia, are undergoing rapid conversion to cropland and pasture. These systems have strong hydrologic buffering capacity and have historically provided consistent freshwater flows to downstream communities. Therefore, loss of these systems could threaten the viability of freshwater resources in the region. While this region has some of the highest runoff ratios, precipitation, and largest river flows in the world, the resiliency of these hydrologic systems and the influence LULC change may have on them remains poorly understood. Here we seek to develop a deeper understanding of these relationships through quantitative analyses of LULC change and impacts on the quantity and quality of water exported from páramo landscapes of Colombia. Our results indicate the intensity and spatial distribution of LULC change, build upon past remote sensing studies of the region, and aid in prioritizing areas of concern for hydrologic research on the ground. This information provides an initial framework for characterizing the degree of modification and impact to water quantity/quality, as well as the long-term sustainability of water resources in the region. We highlight the complexities of watershed management practices in the Colombian páramo and the need to account for the impact of human activity on changes in water quantity and quality in the region.

Geospatial assessment of tourism impact on land environment of Dehradun, Uttarakhand, India.

PubMed

Dey, Jaydip; Sakhre, Saurabh; Gupta, Vikash; Vijay, Ritesh; Pathak, Sunil; Biniwale, Rajesh; Kumar, Rakesh

2018-03-01

India's tourism industry has emerged as a leading industry with a potential to grow further in the next few decades. Dehradun, one of the famous tourist places in India located in the state of Uttarakhand, attracts tourist from all over the country and abroad. The surge in tourist number paved the way for new infrastructure projects like roads, buildings, and hotels, which in turn affects the topography of the mountainous region. In this study, remote sensing and GIS techniques have been used to assess the impact of tourism on the land environment of Dehradun. Satellite images of the years 1972, 2000, and 2016 were analyzed using object-based image analysis (OBIA) to derive land use and land cover (LULC) and ASTER-DEM (Digital Elevation Model) was used to determine the topography of the study area. LULC classification includes built-up, vegetation, forest, scrub, agriculture, plantation, and water body. The slope of the region was categorized as gentle, moderate, strong, extreme, steep, and very steep. To assess the sprawl of built-up on high terrain land, built-up class of LULC was overlaid on slope classes. The overlay analysis reveals that due to increase in tourism, the land use in terms of the built-up area has been extended from gentle slope to very steep slope. The haphazard construction on the extreme, steep, and very steep slope is prone to landslide and other natural disasters. For this, landslide susceptibility maps have also been generated using multicriteria evaluation (MCE) techniques to prevent haphazard construction and to assist in further planning of Dehradun City. This study suggests that a proper developmental plan of the city is essential which follows the principles of optimum use of land and sustainable tourism.

Identifying the fingerprints of the anthropogenic component of land use/land cover changes on regional climate of the USA high plains

NASA Astrophysics Data System (ADS)

Mutiibwa, D.; Irmak, S.

2011-12-01

The majority of recent climate change studies have largely focused on detection and attribution of anthropogenic forcings of greenhouse gases, aerosols, stratospheric and tropospheric ozone. However, there is growing evidence that land cover/land use (LULC) change can significantly impact atmospheric processes from local to regional weather and climate variability. Human activities such as conversion of natural ecosystem to croplands and urban-centers, deforestation and afforestation impact biophysical properties of the land surfaces including albedo, energy balance, moisture-holding capacity of soil, and surface roughness. Alterations in these properties affect the heat and moisture exchanges between the land surface and atmospheric boundary layer, and ultimately impact the climate system. The challenge is to demonstrate that LULC changes produce a signal that can be discerned from natural climate noise. In this study, we attempt to detect the signature of anthropogenic forcing of LULC change on climate on regional scale. The signal projector investigated for detecting the signature of LULC changes on regional climate of the High Plains of the USA is the Normalized Difference Vegetation Index (NDVI). NDVI is an indicator that captures short and long-term geographical distribution of vegetation surfaces. The study develops an enhanced signal processing procedure to maximize the signal to noise ratio by introducing a pre-filtering technique of ARMA processes on the investigated climate and signal variables, before applying the optimal fingerprinting technique to detect the signals of LULC changes on observed climate, temperature, in the High Plains. The intent is to filter out as much noise as possible while still retaining the essential features of the signal by making use of the known characteristics of the noise and the anticipated signal. The study discusses the approach of identifying and suppressing the autocorrelation in optimal fingerprint analysis by applying linear transformation of ARMA processes to the analysis variables. With the assumption that natural climate variability is a near stationary process, the pre-filters are developed to generate stationary residuals. The High Plains region although impacted by droughts over the last three decades has had an increase in agricultural lands, both irrigated and non-irrigated. The study shows that for the most part of the High Plains region there is significant influence of evaporative cooling on regional climate during the summer months. As the vegetation coverage increases coupled with increased in irrigation application, the regional daytime surface energy in summer is increasingly redistributed into latent heat flux which increases the effect of evaporative cooling on summer temperatures. We included the anthropogenic forcing of CO2 on regional climate with the main purpose of surpassing the radiative heating effect of greenhouse gases from natural climate noise, to enhance the LULC signal-to-noise ratio. The warming signal due to greenhouse gas forcing is observed to be weakest in the central part of the High Plains. The results showed that the CO2 signal in the region was weak or is being surpassed by the evaporative cooling effect.

Impact of land use and land cover change on groundwater recharge and quality in the southwestern US

USGS Publications Warehouse

Scanlon, Bridget R.; Reedy, Robert C.; Stonestrom, David A.; Prudic, David E.; Dennehy, Kevin F.

2005-01-01

Humans have exerted large‐scale changes on the terrestrial biosphere, primarily through agriculture; however, the impacts of such changes on the hydrologic cycle are poorly understood. The purpose of this study was to test the hypothesis that the conversion of natural rangeland ecosystems to agricultural ecosystems impacts the subsurface portion of the hydrologic cycle by changing groundwater recharge and flushing salts to underlying aquifers. The hypothesis was examined through point and areal studies investigating the effects of land use/land cover (LU/LC) changes on groundwater recharge and solute transport in the Amargosa Desert (AD) in Nevada and in the High Plains (HP) in Texas, US. Studies use the fact that matric (pore‐water‐pressure) potential and environmental‐tracer profiles in thick unsaturated zones archive past changes in recharging fluxes. Results show that recharge is related to LU/LC as follows: discharge through evapotranspiration (i.e., no recharge; upward fluxes <0.1 mm yr−1) in natural rangeland ecosystems (low matric potentials; high chloride and nitrate concentrations); moderate‐to‐high recharge in irrigated agricultural ecosystems (high matric potentials; low‐to‐moderate chloride and nitrate concentrations) (AD recharge: ∼130–640 mm yr−1); and moderate recharge in nonirrigated (dryland) agricultural ecosystems (high matric potentials; low chloride and nitrate concentrations, and increasing groundwater levels) (HP recharge: ∼9–32 mm yr−1). Replacement of rangeland with agriculture changed flow directions from upward (discharge) to downward (recharge). Recent replacement of rangeland with irrigated ecosystems was documented through downward displacement of chloride and nitrate fronts. Thick unsaturated zones contain a reservoir of salts that are readily mobilized under increased recharge related to LU/LC changes, potentially degrading groundwater quality. Sustainable land use requires quantitative knowledge of the linkages between ecosystem change, recharge, and groundwater quality.

Mapping Soil Organic Carbon Resources Across Agricultural Land Uses in Highland Lesotho Using High Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Knight, J.; Adam, E.

2015-12-01

Mapping spatial patterns of soil organic carbon (SOC) using high resolution satellite imagery is especially important in inaccessible or upland areas that have limited field measurements, where land use and land cover (LULC) are changing rapidly, or where the land surface is sensitive to overgrazing and high rates of soil erosion and thus sediment, nutrient and carbon export. Here we outline the methods and results of mapping soil organic carbon in highland areas (~2400 m) of eastern Lesotho, southern Africa, across different land uses. Bedrock summit areas with very thin soils are dominated by xeric alpine grassland; terrace agriculture with strip fields and thicker soils is found within river valleys. Multispectral Worldview 2 imagery was used to map LULC across the region. An overall accuracy of 88% and kappa value of 0.83 were achieved using a support vector machine model. Soils were examined in the field from different LULC areas for properties such as soil depth, maturity and structure. In situ soils in the field were also evaluated using a portable analytical spectral device (ASD) in order to ground truth spectral signatures from Worldview. Soil samples were examined in the lab for chemical properties including organic carbon. Regression modeling was used in order to establish a relationship between soil characteristics and soil spectral reflectance. We were thus able to map SOC across this diverse landscape. Results show that there are notable differences in SOC between upland and agricultural areas which reflect both soil thickness and maturity, and land use practices such as manuring of fields by cattle. Soil erosion and thus carbon (nutrient) export is significant issue in this region, which this project will now be examining.

Mediterranean Land Use and Land Cover Classification Assessment Using High Spatial Resolution Data

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Boteva, Silvena

2016-10-01

Landscape fragmentation is noticeably practiced in Mediterranean regions and imposes substantial complications in several satellite image classification methods. To some extent, high spatial resolution data were able to overcome such complications. For better classification performances in Land Use Land Cover (LULC) mapping, the current research adopts different classification methods comparison for LULC mapping using Sentinel-2 satellite as a source of high spatial resolution. Both of pixel-based and an object-based classification algorithms were assessed; the pixel-based approach employs Maximum Likelihood (ML), Artificial Neural Network (ANN) algorithms, Support Vector Machine (SVM), and, the object-based classification uses the Nearest Neighbour (NN) classifier. Stratified Masking Process (SMP) that integrates a ranking process within the classes based on spectral fluctuation of the sum of the training and testing sites was implemented. An analysis of the overall and individual accuracy of the classification results of all four methods reveals that the SVM classifier was the most efficient overall by distinguishing most of the classes with the highest accuracy. NN succeeded to deal with artificial surface classes in general while agriculture area classes, and forest and semi-natural area classes were segregated successfully with SVM. Furthermore, a comparative analysis indicates that the conventional classification method yielded better accuracy results than the SMP method overall with both classifiers used, ML and SVM.

Spatial-temporal eco-environmental vulnerability assessment and its influential factors based on Landsat data

NASA Astrophysics Data System (ADS)

Anh, N. K.; Liou, Y. A.; Ming-Hsu, L.

2016-12-01

Regional land use/land cover (LULC) changes lead to various changes in ecological processes and, in turn, alter regional micro-climate. To understand eco-environmental responses to LULC changes, eco-environmental evaluation is thus required with aims to identify vulnerable regions and influential factors, so that practical measures for environmental protection and management may be proposed. The Thua Thien - Hue Province has been experiencing urbanization at a rapid rate in both population and physical size. The urban land, agricultural land, and aquaculture activities have been invasively into natural space and caused eco-environment deterioration by land desertification, soil erosion, shrinking forest resources,…etc. In this study, an assessment framework that is composed by 11 variables with 9 of them constructed from Landsat time series is proposed to serve as basis to examine eco-environmental vulnerability in the Thua Thien - Hue Province in years 1989, 2003, and 2014. An eco-environmental vulnerability map is assorted into six vulnerability levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities. Result shows that there is an increasing trend in eco-environmental vulnerability in general with expected evolving distributions in heavy and very heavy vulnerability levels, which mainly lying on developed land, bare land, semi bare land, agricultural land, and poor and recovery forests. In contrast, there is a significant decline in potential vulnerability level. The contributing factors of an upward trend in medium, heavy, and very heavy levels include: (i) a large natural forest converted to plantation forest and agriculture land; and (ii) significant expansion of developed land leading to difference in thermal signatures in urban areas as compared with those of the surrounding areas. It is concluded that anthropogenic processes with transformation on LULC has amplified the vulnerability of eco-environment in the study area.

Using Landsat imagery to detect, monitor, and project net landscape change

USGS Publications Warehouse

Reker, Ryan R.; Sohl, Terry L.; Gallant, Alisa L.

2015-01-01

Detailed landscape information is a necessary component to bird habitat conservation planning. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has been providing information on the Earth’s surface for over 40 years via the continuous series of Landsat satellites. In addition to operating, processing, and disseminating satellite images, EROS is the home to nationwide and global landscape mapping, monitoring, and projection products, including:National Land Cover Database (NLCD) – the definitive land cover dataset for the U.S., with updates occurring at five-year intervals;Global Land Cover Monitoring – producing 30m resolution global land cover;LANDFIRE – Landscape Fire and Resource Management Planning Tools–EROS is a partner in this joint program between U.S. Department of Agriculture and Department of Interior that produces consistent, comprehensive, geospatial data and databases that describe vegetation, wildland fuel, and fire regimes across the U.S.;Land Cover Trends – a landscape monitoring and assessment effort to understand the rates, trends, causes, and consequences of contemporary U.S. land use and land cover change; andLand Use and Land Cover (LULC) Modeling – a project extending contemporary databases of landscape change forward and backward in time through moderate-resolution land cover projections.

Changes of ecosystem service values in response to land use/land cover dynamics in Munessa-Shashemene landscape of the Ethiopian highlands.

PubMed

Kindu, Mengistie; Schneider, Thomas; Teketay, Demel; Knoke, Thomas

2016-03-15

Land use/land cover (LULC) dynamics alter ecosystem services values (ESVs), yet quantitative evaluations of changes in ESVs are seldom attempted. Using Munessa-Shashemene landscape of the Ethiopian highlands as an example, we showed estimate of changes in ESVs in response to LULC dynamics over the past four decades (1973-2012). Estimation and change analyses of ESVs were conducted, mainly, by employing GIS using LULC datasets of the year 1973, 1986, 2000 and 2012 with their corresponding global value coefficients developed earlier and our own modified conservative value coefficients for the studied landscape. The results between periods revealed a decrease of total ESVs from US$ 130.5 million in 1973, to US$ 118.5, 114.8 and 111.1 million in 1986, 2000 and 2012, respectively. While using global value coefficients, the total ESVs declined from US$ 164.6 million in 1973, to US$ 135.8, 127.2 and 118.7 million in 1986, 2000 and 2012, respectively. The results from the analyses of changes in the four decades revealed a total loss of ESVs ranging from US$ 19.3 million when using our own modified value coefficients to US$ 45.9 million when employing global value coefficients. Changes have also occurred in values of individual ecosystem service functions, such as erosion control, nutrient cycling, climate regulation and water treatment, which were among the highest contributors of the total ESVs. However, the value of food production service function consistently increased during the study periods although not drastically. All in all, it must be considered a minimum estimate of ESV changes due to uncertainties in the value coefficients used in this study. We conclude that the decline of ESVs reflected the effects of ecological degradation in the studied landscape and suggest further studies to explore future options and formulate intervention strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

LandSense: A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring

NASA Astrophysics Data System (ADS)

Moorthy, Inian; Fritz, Steffen; See, Linda; McCallum, Ian

2017-04-01

Currently within the EU's Earth Observation (EO) monitoring framework, there is a need for low-cost methods for acquiring high quality in-situ data to create accurate and well-validated environmental monitoring products. To help address this need, a new four year Horizon 2020 project entitled LandSense will link remote sensing data with modern participatory data collection methods that involve citizen scientists. This paper will describe the citizen science activities within the LandSense Observatory that aim to deliver concrete, measurable and quality-assured ground-based data that will complement existing satellite monitoring systems. LandSense will deploy advanced tools, services and resources to mobilize and engage citizens to collect in-situ observations (i.e. ground-based data and visual interpretations of EO imagery). Integrating these citizen-driven in-situ data collections with established authoritative and open access data sources will help reduce costs, extend GEOSS and Copernicus capacities, and support comprehensive environmental monitoring systems. Policy-relevant campaigns will be implemented in close collaboration with multiple stakeholders to ensure that citizen observations address user requirements and contribute to EU-wide environmental governance and decision-making. Campaigns for addressing local and regional Land Use and Land Cover (LULC) issues are planned for select areas in Austria, France, Germany, Spain, Slovenia and Serbia. Novel LandSense services (LandSense Campaigner, FarmLand Support, Change Detector and Quality Assurance & Control) will be deployed and tested in these areas to address critical LULC issues (i.e. urbanization, agricultural land use and forest/habitat monitoring). For example, local residents in the cities of Vienna, Tulln, and Heidelberg will help cooperatively detect and map changes in land cover and green space to address key issues of urban sprawl, land take and flooding. Such campaigns are facilitated through numerous pathways of citizen empowerment via the LandSense Engagement Platform, i.e. tools for discussion, online voting collaborative mapping, as well as events linked to public consultation and cooperative planning. In addition to creating tools for data collection, quality assurance, and interaction with the public, the project aims to drive innovation through collaboration with the private sector. LandSense will build an innovation marketplace to attract a vast community of users across numerous disciplines and sectors and boost Europe's role in the business of ground-based monitoring. The anticipated outcomes of LandSense have considerable potential to lower expenditure costs on ground-based data collection and greatly extend the current sources of such data, thereby realizing citizen-powered innovations in the processing chain of LULC monitoring activities both within and beyond Europe.

Classification of High Spatial Resolution, Hyperspectral ...

EPA Pesticide Factsheets

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Assessing the influence of land use land cover pattern, socio economic factors and air quality status to predict morbidity on the basis of logistic based regression model

NASA Astrophysics Data System (ADS)

Dixit, A.; Singh, V. K.

2017-12-01

Recent studies conducted by World Health Organisation (WHO) estimated that 92 % of the total world population are living in places where the air quality level has exceeded the WHO standard limit for air quality. This is due to the change in Land Use Land Cover (LULC) pattern, socio economic drivers and anthropogenic heat emission caused by manmade activity. Thereby, many prevalent human respiratory diseases such as lung cancer, chronic obstructive pulmonary disease and emphysema have increased in recent times. In this study, a quantitative relationship is developed between land use (built-up land, water bodies, and vegetation), socio economic drivers and air quality parameters using logistic based regression model over 7 different cities of India for the winter season of 2012 to 2016. Different LULC, socio economic, industrial emission sources, meteorological condition and air quality level from the monitoring stations are taken to estimate the influence on morbidity of each city. Results of correlation are analyzed between land use variables and monthly concentration of pollutants. These values range from 0.63 to 0.76. Similarly, the correlation value between land use variable with socio economic and morbidity ranges from 0.57 to 0.73. The performance of model is improved from 67 % to 79 % in estimating morbidity for the year 2015 and 2016 due to the better availability of observed data.The study highlights the growing importance of incorporating socio-economic drivers with air quality data for evaluating morbidity rate for each city in comparison to just change in quantitative analysis of air quality.

Determining the importance of model calibration for forecasting absolute/relative changes in streamflow from LULC and climate changes

USGS Publications Warehouse

Niraula, Rewati; Meixner, Thomas; Norman, Laura M.

2015-01-01

Land use/land cover (LULC) and climate changes are important drivers of change in streamflow. Assessing the impact of LULC and climate changes on streamflow is typically done with a calibrated and validated watershed model. However, there is a debate on the degree of calibration required. The objective of this study was to quantify the variation in estimated relative and absolute changes in streamflow associated with LULC and climate changes with different calibration approaches. The Soil and Water Assessment Tool (SWAT) was applied in an uncalibrated (UC), single outlet calibrated (OC), and spatially-calibrated (SC) mode to compare the relative and absolute changes in streamflow at 14 gaging stations within the Santa Cruz River Watershed in southern Arizona, USA. For this purpose, the effect of 3 LULC, 3 precipitation (P), and 3 temperature (T) scenarios were tested individually. For the validation period, Percent Bias (PBIAS) values were >100% with the UC model for all gages, the values were between 0% and 100% with the OC model and within 20% with the SC model. Changes in streamflow predicted with the UC and OC models were compared with those of the SC model. This approach implicitly assumes that the SC model is “ideal”. Results indicated that the magnitude of both absolute and relative changes in streamflow due to LULC predicted with the UC and OC results were different than those of the SC model. The magnitude of absolute changes predicted with the UC and SC models due to climate change (both P and T) were also significantly different, but were not different for OC and SC models. Results clearly indicated that relative changes due to climate change predicted with the UC and OC were not significantly different than that predicted with the SC models. This result suggests that it is important to calibrate the model spatially to analyze the effect of LULC change but not as important for analyzing the relative change in streamflow due to climate change. This study also indicated that model calibration in not necessary to determine the direction of change in streamflow due to LULC and climate change.

Quantitative assessment of human-induced impacts based on net primary productivity in Guangzhou, China.

PubMed

Wu, Yanyan; Wu, Zhifeng

2018-04-01

Urban expansion and land cover change driven primarily by human activities have significant influences on the urban eco-environment, and together with climate change jointly alter net primary productivity (NPP). However, at the spatiotemporal scale, there has been limited quantitative analysis of the impacts of human activities independent of climate change on NPP. We chose Guangzhou city as a study area to analyze the impacts of human activities on NPP, as well as the spatiotemporal variations of those impacts within three segments, using a relative impact index (RII) based on potential NPP (NPP p ), actual NPP (NPP act ), and NPP appropriation due to land use/land cover change (NPP lulc ). The spatial patterns and dynamics of NPP act and NPP lulc were evaluated and the impacts of human activities on NPP during the process of urban sprawl were quantitatively analyzed and assessed using the RII. The results showed that NPP act and NPP lulc in the study area had clear spatial heterogeneity, between 2001 and 2013 there was a declining trend in NPP act while an increasing trend occurred in NPP lulc , and those trends were especially significant in the 10-40-km segment. The results also revealed that more than 91.0% of pixels in whole study region had positive RII values, while the lowest average RII values were found in the > 40-km segment (39.03%), indicating that human activities were not the main cause for the change in NPP there; meanwhile, the average RII was greater than 65.0% in the other two, suggesting that they were subjected to severe anthropogenic disturbances. The RII values in all three segments of the study area increased, indicating an increasing human interference. The 10-40-km buffer zone had the largest slope value (0.5665), suggesting that this segment was closely associated with growing human disturbances. Particularly noteworthy is the fact that the > 40-km segment had a large slope value (0.3323) and required more conservation efforts. Based on the above results, we suggest that continuous efforts may be necessary to improve the intensity of protection and management in the urban environment of Guangzhou.

Potential Relationships Between Urban Development and the Trophic Status of Tampa Bay Tributaries and Lake Thonotosassa, Further the Potential Effect on Public Health

NASA Technical Reports Server (NTRS)

MorenoMadrinan, Max J.; Allhamdan, Mohammad; Rickman, Douglas L.; Estes, Maury

2010-01-01

This slide presentation reviews the use of remote sensing to monitor the relationships between the urban development and water quality in Tampa Bay and the tributaries. It examines the changes in land cover/land use (LU/LC) and the affects that this change has on the water quality of Tampa Bay, Lake Thonotosassa and the tributaries, and that shows the ways that these changes can be estimated with remote sensing.

Spatio-temporal analysis on land transformation in a forested tropical landscape in Jambi Province, Sumatra

NASA Astrophysics Data System (ADS)

Melati, Dian N.; Nengah Surati Jaya, I.; Pérez-Cruzado, César; Zuhdi, Muhammad; Fehrmann, Lutz; Magdon, Paul; Kleinn, Christoph

2015-04-01

Land use/land cover (LULC) in forested tropical landscapes is very dynamically developing. In particular, the pace of forest conversion in the tropics is a global concern as it directly impacts the global carbon cycle and biodiversity conservation. Expansion of agriculture is known to be among the major drivers of forest loss especially in the tropics. This is also the case in Jambi Province, Sumatra, Indonesia where it is the mainly expansion of tree crops that triggers deforestation: oil palm and rubber trees. Another transformation system in Jambi is the one from natural forest into jungle rubber, which is an agroforestry system where a certain density of forest trees accompanies the rubber tree crop, also for production of wood and non-wood forest products. The spatial distribution and the dynamics of these transformation systems and of the remaining forests are essential information for example for further research on ecosystem services and on the drivers of land transformation. In order to study land transformation, maps from the years 1990, 2000, 2011, and 2013 were utilized, derived from visual interpretation of Landsat images. From these maps, we analyze the land use/land cover change (LULCC) in the study region. It is found that secondary dryland forest (on mineral soils) and secondary swamp forest have been transformed largely into (temporary) shrub land, plantation forests, mixed dryland agriculture, bare lands and estate crops where the latter include the oil palm and rubber plantations. In addition, we present some analyses of the spatial pattern of land transformation to better understand the process of LULC fragmentation within the studied periods. Furthermore, the driving forces are analyzed.

The spatial and temporal shifts of biofuel production in the ecosystem-level carbon and water dynamics in the central plains of US

NASA Astrophysics Data System (ADS)

Lin, P.; Brunsell, N. A.

2011-12-01

The grasslands of the central plains US are the leading producer of wheat, sorghum and a significant amount of corn and soybean. By linking the food production and energy cycles, increasing demand for ethanol, biodiesel, and food, not only regional ecosystems are altered by the influences of Land-Use Land-Cover (LULC), but it is also a challenge for us to gain more knowledge about the carbon balance on fuel and food. In order to ascertain the impacts of changing LULC on carbon and water dynamics, more specifically, to examine the impacts of altering current land cover to increase biofuel production in this region, we used Normalized Difference Vegetation Index (NDVI) data and precipitation record for the period from 1982 to 2003 to show the temporal dynamics associated with different landcover types as a function of location along the mean precipitation gradient; and then employed Biome-BGC model to estimate key carbon fluxes and storage pools associated with each of the different landcover classes, as well as the fluxes resulting from landcover changes. Results show an increasing trend of NDVI is from the west to the east, which agreed with the spatial distribution of precipitation, however due to some of LULC types are grown by irrigation, precipitation is not the main effect for vegetation development in west portion. However, overall within the study area, indicated by the temporal distributed plots of wavelet analysis for NDVI and precipitation, vegetation dynamics is obviously affected by long-term regional climatic factors, i.e. precipitation, not by short-term or individual local factors instead. On the other hand, by inputting actual land cover and interpolated meteorological data, as well as important ecosystem variables that govern carbon dynamics, we can better define the impacts of biofuel productions; moreover, this ecosystem carbon cycling simulation by Bio-BGC model illustrates that the extent of those landcover responses depend not only on the rate of changes in local environmental factors, but also on site-specific conditions such as regional climate and soil depth.

Biomass Change of the Landless Peasants' Settlements in Lower Amazon

NASA Astrophysics Data System (ADS)

Yoshikawa, S.; Ishimaru, K.

2014-12-01

Land use/land cover (LU/LC) changes have been reported to occur over large areas in Legal Amazon due to the introduction of large-scale mechanized agriculture, extensive cattle ranching and uncontrolled slash-and-burn cultivation since the 1980s. Around the same time, movements which poor peoples or landless peasants settle into abandoned land have been very active in Brazil. In many cases, these people lack agricultural experiences to yield sufficient production for livelihoods. Thus, it leads to abandon the land and repeat forest clearance. In recent year, education by NGOs to these people encourage spreading of agroforestry which is a land use management system in which trees are grown around or among crops or pasture land. In this study, we specifically aimed at clarifying changes in LULC and these biomass using ground observation data, remotely-sensed LANDSAT data and GIS techniques. We focus on four different settlements: old-established settlement (around 30 years), established settlement (around 20 years), productive settlement (7 year) and unproductive settlement (7 years). These four settelements were located at Santa Barbará province, about 40 km northeast from the center of Belém, the Pará state capital, in the northern part of Brazil. We clarify that the biomass change varied according to whether the settlement are productive or not.

Evaluating Crop Area Mapping from MODIS Time-Series as an Assessment Tool for Zimbabwe’s “Fast Track Land Reform Programme”

PubMed Central

2016-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) data forms the basis for numerous land use and land cover (LULC) mapping and analysis frameworks at regional scale. Compared to other satellite sensors, the spatial, temporal and spectral specifications of MODIS are considered as highly suitable for LULC classifications which support many different aspects of social, environmental and developmental research. The LULC mapping of this study was carried out in the context of the development of an evaluation approach for Zimbabwe’s land reform program. Within the discourse about the success of this program, a lack of spatially explicit methods to produce objective data, such as on the extent of agricultural area, is apparent. We therefore assessed the suitability of moderate spatial and high temporal resolution imagery and phenological parameters to retrieve regional figures about the extent of cropland area in former freehold tenure in a series of 13 years from 2001–2013. Time-series data was processed with TIMESAT and was stratified according to agro-ecological potential zoning of Zimbabwe. Random Forest (RF) classifications were used to produce annual binary crop/non crop maps which were evaluated with high spatial resolution data from other satellite sensors. We assessed the cropland products in former freehold tenure in terms of classification accuracy, inter-annual comparability and heterogeneity. Although general LULC patterns were depicted in classification results and an overall accuracy of over 80% was achieved, user accuracies for rainfed agriculture were limited to below 65%. We conclude that phenological analysis has to be treated with caution when rainfed agriculture and grassland in semi-humid tropical regions have to be separated based on MODIS spectral data and phenological parameters. Because classification results significantly underestimate redistributed commercial farmland in Zimbabwe, we argue that the method cannot be used to produce spatial information on land-use which could be linked to tenure change. Hence capabilities of moderate resolution data are limited to assess Zimbabwe’s land reform. To make use of the unquestionable potential of MODIS time-series analysis, we propose an analysis of plant productivity which allows to link annual growth and production of vegetation to ownership after Zimbabwe’s land reform. PMID:27253327

Multitemporal analysis of forest fragmentation in Hindu Kush Himalaya-a case study from Khangchendzonga Biosphere Reserve, Sikkim, India.

PubMed

Sharma, Mohit; Areendran, G; Raj, Krishna; Sharma, Ankita; Joshi, P K

2016-10-01

Forests in the mountains are a treasure trove; harbour a large biodiversity; and provide fodder, firewood, timber and non-timber forest products; all of these are essential for human survival in the highest mountains on earth. The present paper attempts a spatiotemporal assessment of forest fragmentation and changes in land use land cover (LULC) pattern using multitemporal satellite data over a time span of around a decade (2000-2009), within the third highest protected area (PA) in the world. The fragmentation analysis using Landscape Fragmentation Tool (LFT) depicts a decrease in large core, edge and patches areas by 5.93, 3.64 and 0.66 %, respectively, while an increase in non-forest and perforated areas by 6.59 and 4.01 %, respectively. The land cover dynamics shows a decrease in open forest, alpine scrub, alpine meadows, snow and hill shadow areas by 2.81, 0.39, 8.18, 3.46 and 0.60 %, respectively, and there is an increase in dense forest and glacier area by 4.79 and 10.65 %, respectively. The change analysis shows a major transformation in areas from open forest to dense forest and from alpine meadows to alpine scrub. In order to quantify changes induced by forest fragmentation and to characterize composition and configuration of LULC mosaics, fragmentation indices were computed using Fragstats at class level, showing the signs of accelerated fragmentation. The outcome of the analysis revealed the effectiveness of geospatial tools coupled with landscape ecology in characterization and quantification of forest fragmentation and land cover changes. The present study provides a baseline database for sustainable conservation planning that will benefit the subsistence livelihoods in the region. Recommendations made based on the present analysis will help to recover forest and halt the pessimistic effects of fragmentation and land cover changes on biodiversity and ecosystem services in the region.

Land Use and Land Cover (LULC) Change Detection in Islamabad and its Comparison with Capital Development Authority (CDA) 2006 Master Plan

NASA Astrophysics Data System (ADS)

Hasaan, Zahra

2016-07-01

Remote sensing is very useful for the production of land use and land cover statistics which can be beneficial to determine the distribution of land uses. Using remote sensing techniques to develop land use classification mapping is a convenient and detailed way to improve the selection of areas designed to agricultural, urban and/or industrial areas of a region. In Islamabad city and surrounding the land use has been changing, every day new developments (urban, industrial, commercial and agricultural) are emerging leading to decrease in vegetation cover. The purpose of this work was to develop the land use of Islamabad and its surrounding area that is an important natural resource. For this work the eCognition Developer 64 computer software was used to develop a land use classification using SPOT 5 image of year 2012. For image processing object-based classification technique was used and important land use features i.e. Vegetation cover, barren land, impervious surface, built up area and water bodies were extracted on the basis of object variation and compared the results with the CDA Master Plan. The great increase was found in built-up area and impervious surface area. On the other hand vegetation cover and barren area followed a declining trend. Accuracy assessment of classification yielded 92% accuracies of the final land cover land use maps. In addition these improved land cover/land use maps which are produced by remote sensing technique of class definition, meet the growing need of legend standardization.

Multi-scale, multi-model assessment of projected land allocation

NASA Astrophysics Data System (ADS)

Vernon, C. R.; Huang, M.; Chen, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.

2017-12-01

Effects of land use and land cover change (LULCC) on climate are generally classified into two scale-dependent processes: biophysical and biogeochemical. An extensive amount of research has been conducted related to the impact of each process under alternative climate change futures. However, these studies are generally focused on the impacts of a single process and fail to bridge the gap between sector-driven scale dependencies and any associated dynamics. Studies have been conducted to better understand the relationship of these processes but their respective scale has not adequately captured overall interdependencies between land surface changes and changes in other human-earth systems (e.g., energy, water, economic, etc.). There has also been considerable uncertainty surrounding land use land cover downscaling approaches due to scale dependencies. Demeter, a land use land cover downscaling and change detection model, was created to address this science gap. Demeter is an open-source model written in Python that downscales zonal land allocation projections to the gridded resolution of a user-selected spatial base layer (e.g., MODIS, NLCD, EIA CCI, etc.). Demeter was designed to be fully extensible to allow for module inheritance and replacement for custom research needs, such as flexible IO design to facilitate the coupling of Earth system models (e.g., the Accelerated Climate Modeling for Energy (ACME) and the Community Earth System Model (CESM)) to integrated assessment models (e.g., the Global Change Assessment Model (GCAM)). In this study, we first assessed the sensitivity of downscaled LULCC scenarios at multiple resolutions from Demeter to its parameters by comparing them to historical LULC change data. "Optimal" values of key parameters for each region were identified and used to downscale GCAM-based future scenarios consistent with those in the Land Use Model Intercomparison Project (LUMIP). Demeter-downscaled land use scenarios were then compared to the default LUMIP scenarios to illustrate the uncertainties in projected LULC as a result of difference in downscaling algorithms. Our results show that such uncertainties could propagate to other components in ACME and CESM and lead to significant differences in simulated water and biogeochemical cycles.

Woody plant communities along urban, suburban, and rural streams in Louisville, Kentucky, USA

Treesearch

R. Jonathan White; Margaret M. Carreiro; Wayne C. Zipperer

2014-01-01

Anthropogenic changes in land use and cover (LULC) in stream catchments can alter the composition of riparian plant communities, which can affect ecosystem functions of riparian areas and streams from local to landscape scales.We conducted a study to determine if woody plant species composition and abundance along headwater streams were correlated with categorical and...

Integrated assessment of the impact of climate and land use changes on groundwater quantity and quality in Mancha Oriental (Spain)

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Peña-Haro, S.; Garcia-Prats, A.; Mocholi-Almudever, A. F.; Henriquez-Dole, L.; Macian-Sorribes, H.; Lopez-Nicolas, A.

2014-09-01

Climate and land use change (global change) impacts on groundwater systems cannot be studied in isolation, as various and complex interactions in the hydrological cycle take part. Land-use and land-cover (LULC) changes have a great impact on the water cycle and contaminant production and transport. Groundwater flow and storage are changing in response not only to climatic changes but also to human impacts on land uses and demands (global change). Changes in future climate and land uses will alter the hydrologic cycles and subsequently impact the quantity and quality of regional water systems. Predicting the behavior of recharge and discharge conditions under future climatic and land use changes is essential for integrated water management and adaptation. In the Mancha Oriental system in Spain, in the last decades the transformation from dry to irrigated lands has led to a significant drop of the groundwater table in one of the largest groundwater bodies in Spain, with the consequent effect on stream-aquifer interaction in the connected Jucar River. Streamflow depletion is compromising the related ecosystems and the supply to the downstream demands, provoking a complex management issue. The intense use of fertilizer in agriculture is also leading to locally high groundwater nitrate concentrations. Understanding the spatial and temporal distribution of water availability and water quality is essential for a proper management of the system. In this paper we analyze the potential impact of climate and land use change in the system by using an integrated modelling framework consisting of the sequentially coupling of a watershed agriculturally-based hydrological model (SWAT) with the ground-water model MODFLOW and mass-transport model MT3D. SWAT model outputs (mainly groundwater recharge and pumping, considering new irrigation needs under changing ET and precipitation) are used as MODFLOW inputs to simulate changes in groundwater flow and storage and impacts on stream-aquifer interaction. SWAT and MODFLOW outputs (nitrate loads from SWAT, groundwater velocity field from MODFLOW) are used as MT3D inputs for assessing the fate and transport of nitrate leached from the topsoil. Results on river discharge, crop yields, groundwater levels and groundwater nitrate concentrations obtained from simulation fit well to the observed values. Three climate change scenarios have been considered, corresponding to 3 different GCMs for emission scenario A1B, covering the control period, and short, medium and long-term future periods. A multi-temporal analysis of LULC change was carried out, helped by the study of historical trends by remote sensing images and key driving forces to explain LULC transitions. Markov chains and European scenarios and projections have been used to quantify trends in the future. The cellular automata technique was applied for stochastic modeling future LULC maps. The results show the sensitivity of groundwater quantity and quality (nitrate pollution) to climate and land use changes, and the need to implement adaptation measures in order to prevent further groundwater level declines and increasing nitrate concentrations. The sequential modelling chain has been proved to be a valuable assessment and management tool for supporting the development of sustainable management strategies.

The use of cartographic modeling to assess the impacts of coastal flooding: a case study of Port Said Governorate, Egypt.

PubMed

Abou Samra, Rasha M

2017-09-01

Low-set coastal areas are expected to aggravate inundation on account of sea level rise (SLR). The present study is planned to appraise the impacts of coastal flooding in Port Said city, Egypt by using remote sensing, GIS, and cartographic modeling techniques. To accomplish this scope, Landsat 8-OLI image dated 2016 and SRTM 1Arc-Second Digital Elevation Model (DEM) data were used. Landsat image was classified into seven land use and land cover (LULC) classes by using remote sensing and GIS's software. Different inundation scenarios 1.0, 2.0, and 3.0-m coastal elevation were used to figure the influence of SLR on the study area. Estimation of potential losses under SLR was made by overlaying the expected scenarios on land use. The inundation areas under the expected SLR scenarios of 1.0, 2.0, and 3.0 m were estimated at 827.49, 1072.67, and 1179.41 km 2 , respectively. In conclusion, this study demonstrated that expected coastal flooding scenarios will lead up to serious impacts on LULC classes and coastal features in the study area.

Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

NASA Astrophysics Data System (ADS)

Yang, He; Ma, Ben; Du, Qian; Yang, Chenghai

2010-08-01

In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified class pairs, such as roof and trail, road and roof. These classes may be difficult to be separated because they may have similar spectral signatures and their spatial features are not distinct enough to help their discrimination. In addition, misclassification incurred from within-class trivial spectral variation can be corrected by using pixel connectivity information in a local window so that spectrally homogeneous regions can be well preserved. Our experimental results demonstrate the efficiency of the proposed approaches in classification accuracy improvement. The overall performance is competitive to the object-based SVM classification.

Integrated assessment of the impact of climate and land use changes on groundwater quantity and quality in the Mancha Oriental system (Spain)

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Peña-Haro, S.; García-Prats, A.; Mocholi-Almudever, A. F.; Henriquez-Dole, L.; Macian-Sorribes, H.; Lopez-Nicolas, A.

2015-04-01

Climate and land use change (global change) impacts on groundwater systems cannot be studied in isolation. Land use and land cover (LULC) changes have a great impact on the water cycle and contaminant production and transport. Groundwater flow and storage are changing in response not only to climatic changes but also to human impacts on land uses and demands, which will alter the hydrologic cycle and subsequently impact the quantity and quality of regional water systems. Predicting groundwater recharge and discharge conditions under future climate and land use changes is essential for integrated water management and adaptation. In the Mancha Oriental system (MOS), one of the largest groundwater bodies in Spain, the transformation from dry to irrigated lands during the last decades has led to a significant drop of the groundwater table, with the consequent effect on stream-aquifer interaction in the connected Jucar River. Understanding the spatial and temporal distribution of water quantity and water quality is essential for a proper management of the system. On the one hand, streamflow depletion is compromising the dependent ecosystems and the supply to the downstream demands, provoking a complex management issue. On the other hand, the intense use of fertilizer in agriculture is leading to locally high groundwater nitrate concentrations. In this paper we analyze the potential impacts of climate and land use change in the system by using an integrated modeling framework that consists in sequentially coupling a watershed agriculturally based hydrological model (Soil and Water Assessment Tool, SWAT) with a groundwater flow model developed in MODFLOW, and with a nitrate mass-transport model in MT3DMS. SWAT model outputs (mainly groundwater recharge and pumping, considering new irrigation needs under changing evapotranspiration (ET) and precipitation) are used as MODFLOW inputs to simulate changes in groundwater flow and storage and impacts on stream-aquifer interaction. SWAT and MODFLOW outputs (nitrate loads from SWAT, groundwater velocity field from MODFLOW) are used as MT3DMS inputs for assessing the fate and transport of nitrate leached from the topsoil. Three climate change scenarios have been considered, corresponding to three different general circulation models (GCMs) for emission scenario A1B that covers the control period, and short-, medium- and long-term future periods. A multi-temporal analysis of LULC change was carried out, helped by the study of historical trends (from remote-sensing images) and key driving forces to explain LULC transitions. Markov chains and European scenarios and projections were used to quantify trends in the future. The cellular automata technique was applied for stochastic modeling future LULC maps. Simulated values of river discharge, crop yields, groundwater levels and nitrate concentrations fit well to the observed ones. The results show the response of groundwater quantity and quality (nitrate pollution) to climate and land use changes, with decreasing groundwater recharge and an increase in nitrate concentrations. The sequential modeling chain has been proven to be a valuable assessment tool for supporting the development of sustainable management strategies.

Changes in the methodology used in the production of the Spanish CORINE: Uncertainty analysis of the new maps

NASA Astrophysics Data System (ADS)

García-Álvarez, David; Camacho Olmedo, María Teresa

2017-12-01

Since 2012 CORINE has been obtained in Spain from the generalization of a more detailed land cover map (SIOSE). This methodological change has meant the production of a new CORINE map, which is different from the existing ones. To analyze how different the new maps are from the previous ones, as well as the advantages and disadvantages of the new methodology, we carried out a comparison of the CORINE obtained from both methods (traditional and generalization) for the year 2006. The new CORINE is more detailed and it is more coherent with the rest of Spanish Land Use Land Cover (LULC) maps. However, problems have been encountered with regard to the meaning of its classes, the fragmentation of patches and the complexity of its perimeters.

Monitoring land use/land cover transformations from 1945 to 2007 in two peri-urban mountainous areas of Athens metropolitan area, Greece.

PubMed

Mallinis, Giorgos; Koutsias, Nikos; Arianoutsou, Margarita

2014-08-15

The aims of this study were to map and analyze land use/land cover transitions and landscape changes in the Parnitha and Penteli mountains, which surround the Athens metropolitan area of Attica, Greece over a period of 62 years. In order to quantify the changes between land categories through time, we computed the transition matrices for three distinct periods (1945-1960, 1960-1996, and 1996-2007), on the basis of available aerial photographs used to create multi-temporal maps. We identified systematic and stationary transitions with multi-level intensity analysis. Forest areas in Parnitha remained the dominant class of land cover throughout the 62 years studied, while transitional woodlands and shrublands were the main classes involved in LULC transitions. Conversely, in Penteli, transitional woodlands, along with shrublands, dominated the study site. The annual rate of change was faster in the first and third time intervals, compared to the second (1960-1996) time interval, in both study areas. The category level analysis results indicated that in both sites annual crops avoided to gain while discontinuous urban fabric avoided to lose areas. At the transition level of analysis, similarities as well as distinct differences existed between the two areas. In both sites the gaining pattern of permanent crops with respect to annual crops and the gain of forest with respect to transitional woodland/shrublands were stationary across the three time intervals. Overall, we identified more systematic transitions and stationary processes in Penteli. We discussed these LULC changes and associated them with human interference (activity) and other major socio-economic developments that were simultaneously occurring in the area. The different patterns of change of the areas, despite their geographical proximity, throughout the period of analysis imply that site-specific studies are needed in order to comprehensively assess the driving forces and develop models of landscape transformation in Mediterranean areas. Copyright © 2014 Elsevier B.V. All rights reserved.

Dem Local Accuracy Patterns in Land-Use/Land-Cover Classification

NASA Astrophysics Data System (ADS)

Katerji, Wassim; Farjas Abadia, Mercedes; Morillo Balsera, Maria del Carmen

2016-01-01

Global and nation-wide DEM do not preserve the same height accuracy throughout the area of study. Instead of assuming a single RMSE value for the whole area, this study proposes a vario-model that divides the area into sub-regions depending on the land-use / landcover (LULC) classification, and assigns a local accuracy per each zone, as these areas share similar terrain formation and roughness, and tend to have similar DEM accuracies. A pilot study over Lebanon using the SRTM and ASTER DEMs, combined with a set of 1,105 randomly distributed ground control points (GCPs) showed that even though the inputDEMs have different spatial and temporal resolution, and were collected using difierent techniques, their accuracy varied similarly when changing over difierent LULC classes. Furthermore, validating the generated vario-models proved that they provide a closer representation of the accuracy to the validating GCPs than the conventional RMSE, by 94% and 86% for the SRTMand ASTER respectively. Geostatistical analysis of the input and output datasets showed that the results have a normal distribution, which support the generalization of the proven hypothesis, making this finding applicable to other input datasets anywhere around the world.

Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia.

PubMed

Minale, Amare Sewnet; Alemu, Kalkidan

2018-05-07

The main objective of this study was to develop a malaria risk map for Bahir Dar City, Amhara, which is situated south of Lake Tana on the Ethiopian plateau. Rainfall, temperature, altitude, slope and land use/land cover (LULC), as well as proximity measures to lake, river and health facilities, were investigated using remote sensing and geographical information systems. The LULC variable was derived from a 2012 SPOT satellite image by supervised classification, while 30-m spatial resolution measurements of altitude and slope came from the Shuttle Radar Topography Mission. Metrological data were collected from the National Meteorological Agency, Bahir Dar branch. These separate datasets, represented as layers in the computer, were combined using weighted, multi-criteria evaluations. The outcome shows that rainfall, temperature, slope, elevation, distance from the lake and distance from the river influenced the malaria hazard the study area by 35%, 15%, 10%, 7%, 5% and 3%, respectively, resulting in a map showing five areas with different levels of malaria hazard: very high (11.2%); high (14.5%); moderate (63.3%); low (6%); and none (5%). The malaria risk map, based on this hazard map plus additional information on proximity to health facilities and current LULC conditions, shows that Bahir Dar City has areas with very high (15%); high (65%); moderate (8%); and low (5%) levels of malaria risk, with only 2% of the land completely riskfree. Such risk maps are essential for planning, implementing, monitoring and evaluating disease control as well as for contemplating prevention and elimination of epidemiological hazards from endemic areas.

Aerosol and Urban Land Use Effect on Rainfall Around Cities in Indo-Gangetic Basin From Observations and Cloud Resolving Model Simulations

NASA Astrophysics Data System (ADS)

Sarangi, Chandan; Tripathi, S. N.; Qian, Yun; Kumar, Shailendra; Ruby Leung, L.

2018-04-01

Coupling of urban land use land cover (LULC) and aerosol loading on rainfall around cities in the Gangetic Basin (GB) is examined here. Long-term observations illustrate more rainfall at urban core and climatological downwind regions compared to the upwind regions of Kanpur, a metropolitan area located in central GB. In addition, analysis of a 15 day cloud resolving simulation using the Weather Research and Forecasting model also illustrated similar rainfall pattern around other major cities in the GB. Interestingly, the enhancement of downwind rainfall was greater than that over urban regions, and it was positively associated with both the urban area of the city and ambient aerosol loading during the propagating storm. Further, to gain a process-level understanding, a typical storm that propagated northwestward across Kanpur was simulated using Weather Research and Forecasting under three different scenarios. Case 1 has realistic LULC representation of Kanpur, while the grids representing the Kanpur urban region were replaced by cropland LULC pattern in Case 2. Comparison illustrated that urban heat island effect caused convergence of winds and moisture in the lower troposphere, which enhances convection over urban region and induced more rainfall over the urban core compared to upwind regions. Case 3 is similar to Case 1 but lower aerosol concentration (by a factor of 100) over the storm region. Analysis shows that aerosol-induced microphysical changes delay the initiation of warm rain (over the upwind region) but enhance ice phase particle formation in latter stages (over the urban and downwind regions) resulting in increase in downwind rainfall.

Landscape changes in a neotropical forest-savanna ecotone zone in central Brazil: The role of protected areas in the maintenance of native vegetation.

PubMed

Garcia, Andrea S; Sawakuchi, Henrique O; Ferreira, Manuel Eduardo; Ballester, Maria Victoria R

2017-02-01

In the Amazon-savanna ecotone in northwest Brazil, the understudied Araguaia River Basin contains high biodiversity and seasonal wetlands. The region is representative of tropical humid-dry ecotone zones, which have experienced intense land use and land cover (LULC) conversions. Here we assessed the LULC changes for the last four decades in the central portion of the Araguaia River Basin to understand the temporal changes in the landscape composition and configuration outside and inside protected areas. We conducted these analyzes by LULC mapping and landscape metrics based on patch classes. During this period, native vegetation was reduced by 26%. Forests were the most threatened physiognomy, with significant areal reduction and fragmentation. Native vegetation cover was mainly replaced by croplands and pastures. Such replacement followed spatial and temporal trends related to the implementation of protected areas and increases in population cattle herds. The creation of most protected areas took place between 1996 and 2007, the same period during which the conversion of the landscape matrix from natural vegetation to agriculture occurred. We observed that protected areas mitigate fragmentation, but their roles differ according to their location and level of protection. Still, we argue that landscape characteristics, such as suitability for agriculture, also influence landscape conversions and should be considered when establishing protected areas. The information provided in this study can guide new research on species conservation and landscape planning, as well as improve the understanding of the impacts of landscape composition and configuration changes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes. Sensitivity study of the model indicated that southern and south-west part of the city have shown improvement and small patches of growth are also observed in the north western part of the city.The study highlights the growing importance of socio economic factors and geo-computational modeling approach on changing LULC of newly growing cities of modern India.

Cases of Coastal Zone Change and Land Use/Land Cover Change: a learning module that goes beyond the "how" of doing image processing and change detection to asking the "why" about what are the "driving forces" of global change.

NASA Astrophysics Data System (ADS)

Ford, R. E.

2006-12-01

In 2006 the Loma Linda University ESSE21 Mesoamerican Project (Earth System Science Education for the 21st Century) along with partners such as the University of Redlands and California State University, Pomona, produced an online learning module that is designed to help students learn critical remote sensing skills-- specifically: ecosystem characterization, i.e. doing a supervised or unsupervised classification of satellite imagery in a tropical coastal environment. And, it would teach how to measure land use / land cover change (LULC) over time and then encourage students to use that data to assess the Human Dimensions of Global Change (HDGC). Specific objectives include: 1. Learn where to find remote sensing data and practice downloading, pre-processing, and "cleaning" the data for image analysis. 2. Use Leica-Geosystems ERDAS Imagine or IDRISI Kilimanjaro to analyze and display the data. 3. Do an unsupervised classification of a LANDSAT image of a protected area in Honduras, i.e. Cuero y Salado, Pico Bonito, or Isla del Tigre. 4. Virtually participate in a ground-validation exercise that would allow one to re-classify the image into a supervised classification using the FAO Global Land Cover Network (GLCN) classification system. 5. Learn more about each protected area's landscape, history, livelihood patterns and "sustainability" issues via virtual online tours that provide ground and space photos of different sites. This will help students in identifying potential "training sites" for doing a supervised classification. 6. Study other global, US, Canadian, and European land use/land cover classification systems and compare their advantages and disadvantages over the FAO/GLCN system. 7. Learn to appreciate the advantages and disadvantages of existing LULC classification schemes and adapt them to local-level user needs. 8. Carry out a change detection exercise that shows how land use and/or land cover has changed over time for the protected area of your choice. The presenter will demonstrate the module, assess the collaborative process which created it, and describe how it has been used so far by users in the US as well as in Honduras and elsewhere via a series joint workshops held in Mesoamerica. Suggestions for improvement will be requested. See the module and related content resources at: http://resweb.llu.edu/rford/ESSE21/LUCCModule/

How do land management practices affect net ecosystem CO2 exchange of an invasive plant infestation?

NASA Astrophysics Data System (ADS)

Sonnentag, O.; Detto, M.; Runkle, B.; Kelly, M.; Baldocchi, D. D.

2009-12-01

Ecosystem gas and energy exchanges of invasive plant infestations under different land management practices have been subject of few studies and thus little is known. Our goal is to characterize seasonal changes in net ecosystem CO2 exchange (NEE) through the processes of photosynthesis (GEP) and ecosystem respiration (Reco) of a grassland used as pasture yet infested by perennial pepperweed (Lepidium latifolium) in California’s Sacramento-San Joaquin River Delta. We analyze eddy-covariance supported by environmental and canopy-scale hyperspectral reflectance measurements acquired in 2007-2009. Our study covers three summer drought periods with slightly different land management practices. Over the study period the site was subject to year-round grazing, and in 2008 the site was additionally mowed. Specific questions we address are a) how does pepperweed flowering affect GEP, b) does a mowing event affect NEE mainly through GEP or Reco, and c) can the combined effects of phenology and mowing on pepperweed NEE potentially be tracked using routinely applied remote sensing techniques? Preliminary results indicate that pepperweed flowering drastically decreases photosynthetic CO2 uptake due to shading by the dense arrangement of white flowers at the canopy top, causing the infestation to be almost CO2 neutral. In contrast, mowing causes the infestation to act as moderate net CO2 sink, mainly due to increased CO2 uptake during regrowth. We demonstrate that spectral regions other than commonly-used red and near-infrared might be more promising for pepperweed monitoring because of its spectral uniqueness during the flowering phase. Our results have important implications for land-use land-cover (LULC) change studies when biological invasions and their management alter ecosystem structure and functioning but not necessarily the respective LULC class.

An integrated and open source GIS environmental management system for a protected area in the south of Portugal

NASA Astrophysics Data System (ADS)

Teodoro, A.; Duarte, L.; Sillero, N.; Gonçalves, J. A.; Fonte, J.; Gonçalves-Seco, L.; Pinheiro da Luz, L. M.; dos Santos Beja, N. M. R.

2015-10-01

Herdade da Contenda (HC), located in Moura municipality, Beja district (Alentejo province) in the south of Portugal (southwestern Iberia Peninsula), is a national hunting area with 5270ha. The development of an integrated system that aims to make the management of the natural and cultural heritage resources will be very useful for an effective management of this area. This integrated system should include the physical characterization of the territory, natural conservation, land use and land management themes, as well the cultural heritage resources. This paper presents a new tool for an integrated environmental management system of the HC, which aims to produce maps under a GIS open source environment (QGIS). The application is composed by a single button which opens a window. The window is composed by twelve menus (File, DRASTIC, Forest Fire Risk, Revised Universal Soil Loss Equation (RUSLE), Bioclimatic Index, Cultural Heritage, Fauna and Flora, Ortofoto, Normalizes Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), Land Use Land Cover Cover (LULC) and Help. Several inputs are requires to generate these maps, e.g. DEM, geologic information, soil map, hydraulic conductivity information, LULC map, vulnerability and economic information, NDVI. Six buttons were added to the toolbar which allows to manipulate the information in the map canvas: Zoom in, Zoom out, Pan, Print/Layout and Clear. This integrated and open source GIS environment management system was developed for the HC area, but could be easily adapted to other natural or protected area. Despite the lack of data, the methodology presented fulfills the objectives.

Landuse/Landcover and Climate Change Interaction in the Derived Savannah Region of Nigeria

NASA Astrophysics Data System (ADS)

Akintuyi, A. O.; Fasona, M.; Soneye, A. S. O.

2016-12-01

The interaction of landuse/Landcover (LULC) and climate change, to a large extent, involves anthropogenic activities. This study was carried out in the derived savannah of Nigeria, a delicate ecological zone where the interaction of LULC and climate change could be well appreciated. The study evaluated coupled interaction between LULC and climate change and assessed the changes in the landuse/landcover patterns for the periods 1972, 1986, 2002 and 2010, evaluated the present (1941 - 2010) and future (2011 - 2050) variability in rainfall patterns and an attempt was made to predict the interaction between LULC and climate change during future climate. The study adopted remote sensing and GIS techniques, land change modeller and multivariate statistics The results suggest that the built up area, farmland, waterbody and woodland experienced a rapid increase of about 1,134.69%, 1,202.85%, 631.51% and 188.09%, respectively, while the forest cover, degraded surfaces and grassland lost about 19.32%, 72.76% and 0.05% respectively between 1972 and 2010. Furthermore, the study predicted 40.28% and 37.84% reduction in the forested area between 1986 and 2050 and 2010 and 2050 respectively. The study concludes that rainfall will be the major driver of LULC change within the study area under a future climate.

Analysis of spatial pattern Change of LU/LC over the upper Tarim River region since 1990 using remote sensing data

NASA Astrophysics Data System (ADS)

Bai, L. Y.; Feng, J. Z.; Ma, Y. X.; Ran, Q. Y.; Wang, K.; Zhao, Y.

2017-02-01

The upper reaches of Tarim River (URTR) is an important port of trade between China and central Asia. The development of the URTR is thus significant for the SREB initiative. The LU/LC data in the URTR from 1990 to 2015 were used to quantitatively explore the dynamics of LU/LC changes, and its driving force was discussed from two aspects of nature and human. Results showed that the unused land and grassland were the main land use types in this area, accounting for more than 79%. Compared with the data of 1990, the areas of woodland, water, farmland, and building land of 2015 increased with 3.24%, 6.53%, 10.57%, and 0.40%, respectively, and the areas of unused land and grassland decreased, which accounted for 53.25% and 26.01%, respectively. The increases of the woodland and farmland areas mainly is originated from grassland and unused land. The woodland increased sharply around 2000 due to the abundant water during the period between 1998 and 2000. Subsequently, part of the woodland was shifted into the farmland. The extension of building land wasn’t obvious, but showed a salient feature of population urbanization. It was essential that the LU/LC patterns of the URTR were deeply influenced by human farming and living activities.

Quantification and mapping of the supply of and demand for carbon storage and sequestration service in woody biomass and soil to mitigate climate change in the socio-ecological environment.

PubMed

Sahle, Mesfin; Saito, Osamu; Fürst, Christine; Yeshitela, Kumelachew

2018-05-15

In this study, the supply of and demand for carbon storage and sequestration of woody biomass in the socio-ecological environment of the Wabe River catchment in Gurage Mountains, Ethiopia, were estimated. This information was subsequently integrated into a map that showed the balance between supply capacities and demand in a spatially explicit manner to inform planners and decision makers on methods used to manage local climate change. Field data for wood biomass and soil were collected, satellite images for land use and land cover (LULC) were classified, and secondary data from statistics and studies for estimation were obtained. Carbon storage, the rate of carbon sequestration and the rate of greenhouse gas (GHG) emissions from diverse sources at different LULCs, was estimated accordingly by several methods. Even though a large amount of carbon was stored in the catchment, the current yearly sequestration was less than the CO 2 -eq. GHG emissions. Forest and Enset-based agroforestry emissions exhibited the highest amount of woody biomass, and cereal crop and wetland exhibited the highest decrease in soil carbon sequestration. CO 2 -eq. GHG emissions are mainly caused by livestock, nitrogenous fertilizer consumption, and urban activities. The net negative emissions were estimated for the LULC classes of cereal crop, grazing land, and urban areas. In conclusion, without any high-emission industries, GHG emissions can be greater than the regulatory capacity of ecosystems in the socio-ecological environment. This quantification approach can provide information to policy and decision makers to enable them to tackle climate change at the root level. Thus, measures to decrease emission levels and enhance the sequestration capacity are crucial to mitigate the globally delivered service in a specific area. Further studies on the effects of land use alternatives on net emissions are recommended to obtain in-depth knowledge on sustainable land use planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimizing classification performance in an object-based very-high-resolution land use-land cover urban application

NASA Astrophysics Data System (ADS)

Georganos, Stefanos; Grippa, Tais; Vanhuysse, Sabine; Lennert, Moritz; Shimoni, Michal; Wolff, Eléonore

2017-10-01

This study evaluates the impact of three Feature Selection (FS) algorithms in an Object Based Image Analysis (OBIA) framework for Very-High-Resolution (VHR) Land Use-Land Cover (LULC) classification. The three selected FS algorithms, Correlation Based Selection (CFS), Mean Decrease in Accuracy (MDA) and Random Forest (RF) based Recursive Feature Elimination (RFE), were tested on Support Vector Machine (SVM), K-Nearest Neighbor, and Random Forest (RF) classifiers. The results demonstrate that the accuracy of SVM and KNN classifiers are the most sensitive to FS. The RF appeared to be more robust to high dimensionality, although a significant increase in accuracy was found by using the RFE method. In terms of classification accuracy, SVM performed the best using FS, followed by RF and KNN. Finally, only a small number of features is needed to achieve the highest performance using each classifier. This study emphasizes the benefits of rigorous FS for maximizing performance, as well as for minimizing model complexity and interpretation.

Relationships between landscape pattern and land surface temperature and their applications to the study of West Nile Virus: As case studies in cities of Indianapolis and Chicago, United States

NASA Astrophysics Data System (ADS)

Liu, Hua

A new synthesis of remote sensing and landscape ecology approaches was developed to establish relationships between the landscape patterns and land surface temperatures (LST) in the city of Indianapolis, Indiana, United States. Land use and land cover (LULC) and LST images were derived from Terra Satellite's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns and land surface temperature zones. Detailed landscape pattern analyses at the landscape and class scales were conducted using landscape metrics in the City of Indianapolis. The effects of spatial resolution on the identification of the relationship were examined in the same city. The best level of equalization between the LULC and LST maps was determined based on minimum distance analysis in landscape metrics space. The analyses of relationships between the landscape patterns and land surface temperatures, and scaling effects were applied to the spread of West Nile Virus (WNV) in the City of Chicago, Illinois. Results show that urban, forest, and grassland were the main landscape components in Indianapolis. They possessed relatively higher fractal dimensions but lower spatial aggregation levels in April 5, 2004, June 16, 2001, and October 3, 2000, but not in February 6, 2006. Obvious seasonal differences existed with the most distinct landscape pattern detected on February 6, 2006. Urban was the dominant LULC type in high-temperature zones, while water and vegetation mainly fell in low-temperature zones. For each individual date, the metrics of LST zones apparently corresponded to the metrics of LULC types. In the study of scaling-up effect analysis, Patch Percentage, Patch Density, and Landscape Shape index were found to be able to effectively quantify the spatial changes of LULC types and temperature zones at different scales without contradiction. Urban, forest, and grassland in each season were more easily affected by the process in Patch Density and Landscape Shape index. Ninety meters was believed to be the optimal spatial resolution to examine relationships between landscape patterns and LSTs in the City of Indianapolis. In the study of the spread of West Nile Virus in the City of Chicago, WNV was found to have been spread throughout all of Cook County since 2001. Landscape factors, like landscape aggregation index and areas of urban, grass, and water showed a strong correlation with the number of WNV infections. Socioeconomic conditions, like population above 65 years old also showed a strong relationship with the spread of WNV in Cook County. Thermal conditions of water had a lower but still significant correlation to the spread of WNV. This research offers an opportunity to explore the mechanism of interaction between urban landscape patterns and land surface temperatures at different spatial scales, and show the effects of landscape pattern and land surface temperature on the spread of West Nile Virus. This study can be useful for urban planning and environmental management practices in the studied areas. It also contributes to public health management and protection.

Management of land use land cover through the application of remote sensing, geographic information systems and simulation

NASA Astrophysics Data System (ADS)

Jha, Praveen

Deforestation and degradation of forest areas, including those in the Protected Areas (PAs), are major concerns in India. There were 2 broad objectives of the study: the technological objective pertained to the development of state-of-art programs that could serve as Decision Support Systems while finalizing plans and policy interventions, while the other objective aimed at generating geo-spatial data in 2 PAs. A part of the Eastern Himalaya biodiversity hotspot, Manas Tiger Reserve (MTR), Assam, India having an area of 2837.12 sq km and an important part of Rajaji-Corbett Tiger Conservation Unit, Rajaji National Park (RNP), Uttarakhand, India, having an area of 820.42 sq km, were taken for the assessment of land use and land cover (LULC) change during 1990--2004. Simulation was undertaken in a smaller area of 1.2 km * 1.2 km right on the fringe of RNP. Three advanced geo-spatial programs---Multi-Algorithm Automation Program (MAAP), Data Automatic Modification Program (DAMP) and Multi-Stage Simulation Program (MUSSIP)---developed by the author were used extensively. Based on the satellite data, MAAP was used for the rapid assessments of LULC of 2004 and 1990; DAMP was used for the spectral modification of the satellite data of the adjacent scenes of 2004 and of 1990; and MUSSIP was used to simulate LULC maps for the future periods (till 2018). These programs produced very high accuracy levels: 91.12% in 2004 and 89.67% in 1990 were obtained for MTR; and 94.87% in 2004 and 94.10% in 1990 were obtained for RNP; 93.40% pixel-to-pixel accuracy and 0.7904 for kappa were achieved for simulation. The annual rate of loss of forests (0.41% in MTR and 1.20% in RNP) and loss of water (1.79% in MTR and 1.69% in RNP) during 1990-2004 is a matter of serious concern. The scenario analysis in the study area for simulation revealed that the deforestation rate of 1.27% per year during 2004--2018 would increase to 2.04% if the human population growth rate is enhanced by 10%. Hence these PAs need urgent restoration measures and effective conservation planning to address the problems of deforestation, severe degradation and immense loss of water.

Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

2016-12-01

State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

Land susceptibility to soil erosion in Orashi Catchment, Nnewi South, Anambra State, Nigeria

NASA Astrophysics Data System (ADS)

Odunuga, Shakirudeen; Ajijola, Abiodun; Igwetu, Nkechi; Adegun, Olubunmi

2018-02-01

Soil erosion is one of the most critical environmental hazards that causes land degradation and water quality challenges. Specifically, this phenomenon has been linked, among other problems, to river sedimentation, groundwater pollution and flooding. This paper assesses the susceptibility of Orashi River Basin (ORB) to soil erosion for the purpose of erosion control measures. Located in the South Eastern part of Nigeria, the ORB which covers approximately 413.61 km2 is currently experiencing one of the fastest population growth rate in the region. Analysis of the soil erosion susceptibility of the basin was based on four factors including; rainfall, Land use/Land cover change (LULC), slope and soil erodibility factor (k). The rainfall was assumed to be a constant and independent variable, slope and soil types were categorised into ten (10) classes each while the landuse was categorised into five classes. Weight was assigned to the classes based on the degree of susceptibility to erosion. An overlay of the four variables in a GIS environment was used to produce the basin susceptibility to soil erosion. This was based on the weight index of each factors. The LULC analysis revealed that built-up land use increased from 26.49 km2 (6.4 %) in year 1980 to 79.24 km2 (19.16 %) in 2015 at an average growth rate of 1.51 km2 per annum while the light forest decreased from 336.41 km2 (81.33 %) in 1980 to 280.82 km2 (67.89 %) in 2015 at an average rate 1.59 km2 per annum. The light forest was adjudged to have the highest land cover soil erosion susceptibility. The steepest slope ranges between 70 and 82° (14.34 % of the total land area) and was adjudged to have the highest soil susceptibility to erosion. The total area covered of the loamy soil is 112.37 km2 (27.07 %) with erodibility of 0.7. In all, the overlay of all the variables revealed that 106.66 km2 (25.70 %) and 164.80 km2 (39.7 %) of the basin has a high and very high susceptibility to soil erosion. The over 50 % high susceptibility of catchment has serious negative implications on the surface water in terms of water quality and downstream siltation with great consequences on biodiversity and ecosystem services including domestic and industrial usage.

Scrub typhus re-emergence in India: Contributing factors and way forward.

PubMed

Ranjan, Jai; Prakash, John Antony Jude

2018-06-01

Scrub typhus is a mite borne infectious disease which has re-emerged in India in the 3rd millennium after years of quiescence. In this review, the authors hypothesize the various factors responsible for resurgence of this disease. The main drivers that could have contributed to the upsurge in scrub typhus cases in past two decades are changes in land use land cover (LULC) and urbanisation which are; as a result of the population explosion, causing a strain on sanitation and also increased diversion of forest land for agricultural use. In addition, the availability of better tests, changes in antimicrobial use, climate change also could have impacted the epidemiology, which is showing an upward trend as is evidenced by increasing reports and concomitant publications from India on scrub typhus. Scrub typhus cases are supposed to increase in the coming years as factors like global warming, urbanisation, changes in LULC and rise in AMR (anti-microbial resistance) will be difficult or impossible to control. Therefore, increasing awareness of public and health care professionals regarding scrub typhus coupled with availability of rapid diagnostic assays and implementation of appropriate treatment protocols for control of AFI (acute febrile illness) especially at the community level will help mitigate the scenario in the long run. Copyright © 2018. Published by Elsevier Ltd.

Integrating vegetation index time series and meteorological data to understand the effect of the land use/land cover (LULC) in the climatic seasonality of the Brazilian Cerrado

NASA Astrophysics Data System (ADS)

Lins, D. B.; Zullo, J.; Friedel, M. J.

2013-12-01

The Cerrado (savanna ecosystem) of São Paulo state (Brazil) represent a complex mosaic of different typologies of uses, actors and biophysical and social restrictions. Originally, 14% of the state of São Paulo area was covered by the diversity of Cerrado phytophysiognomies. Currently, only 1% of this original composition remains fragmented into numerous relicts of biodiversity, mainly concentrated in the central-eastern of the state. A relevant part of the fragments are found in areas of intense coverage change by human activities, whereas the greatest pressure comes from sugar cane cultivation, either by direct replacement of Cerrado vegetation or occupying pasture areas in the fragments edges. As a result, new local level dynamics has been introduced, directly or indirectly, affecting the established of processes in climate systems. In this study, the main goal is analyzing the relationship between the Cerrado landscape changing and the climate dynamics in regional and local areas. The multi-temporal MODIS 250 m Vegetation Index (VI) datasets (period of 2000 to 2012) are integrated with precipitation data of the correspondent period (http://www.agritempo.gov.br/),one of the most important variable of the spatial phytophysiognomies distribution. The integration of meteorological data enable the development of an integrated approach to understand the relationship between climatic seasonality and the changes in the spatial patterns. A procedure to congregated diverse dynamics information is the Self Organizing Map (SOM, Kohonen, 2001), a technique that relies on unsupervised competitive learning (Kohonen and Somervuo 2002) to recognize patterns. In this approach, high-dimensional data are represented on two dimensions, making possible to obtain patterns that takes into account information from different natures. Observed advances will contribute to bring machine-learning techniques as a valid tool to provide improve in land use/land cover (LULC) analyzes at different hierarchical scales to support numerous science and policy applications.

Hydrological modeling of geophysical parameters of arboviral and protozoan disease vectors in Internally Displaced People camps in Gulu, Uganda.

PubMed

Jacob, Benjamin G; Muturi, Ephantus J; Caamano, Erick X; Gunter, James T; Mpanga, Enoch; Ayine, Robert; Okelloonen, Joseph; Nyeko, Jack Pen-Mogi; Shililu, Josephat I; Githure, John I; Regens, James L; Novak, Robert J; Kakoma, Ibulaimu

2008-03-14

The aim of this study was to determine if remotely sensed data and Digital Elevation Model (DEM) can test relationships between Culex quinquefasciatus and Anopheles gambiae s.l. larval habitats and environmental parameters within Internally Displaced People (IDP) campgrounds in Gulu, Uganda. A total of 65 georeferenced aquatic habitats in various IDP camps were studied to compare the larval abundance of Cx. quinquefasciatus and An. gambiae s.l. The aquatic habitat dataset were overlaid onto Land Use Land Cover (LULC) maps retrieved from Landsat imagery with 150 m x 150 m grid cells stratified by levels of drainage. The LULC change was estimated over a period of 14 years. Poisson regression analyses and Moran's I statistics were used to model relationships between larval abundance and environmental predictors. Individual larval habitat data were further evaluated in terms of their covariations with spatial autocorrelation by regressing them on candidate spatial filter eigenvectors. Multispectral QuickBird imagery classification and DEM-based GIS methods were generated to evaluate stream flow direction and accumulation for identification of immature Cx. quinquefasciatus and An. gambiae s.l. and abundance. The main LULC change in urban Gulu IDP camps was non-urban to urban, which included about 71.5 % of the land cover. The regression models indicate that counts of An. gambiae s.l. larvae were associated with shade while Cx. quinquefasciatus were associated with floating vegetation. Moran's I and the General G statistics for mosquito density by species and instars, identified significant clusters of high densities of Anopheles; larvae, however, Culex are not consistently clustered. A stepwise negative binomial regression decomposed the immature An. gambiae s.l. data into empirical orthogonal bases. The data suggest the presence of roughly 11% to 28 % redundant information in the larval count samples. The DEM suggest a positive correlation for Culex (0.24) while for Anopheles there was a negative correlation (-0.23) for a local model distance to stream. These data demonstrate that optical remote sensing; geostatistics and DEMs can be used to identify parameters associated with Culex and Anopheles aquatic habitats.

Hydrological modeling of geophysical parameters of arboviral and protozoan disease vectors in Internally Displaced People camps in Gulu, Uganda

PubMed Central

Jacob, Benjamin G; Muturi, Ephantus J; Caamano, Erick X; Gunter, James T; Mpanga, Enoch; Ayine, Robert; Okelloonen, Joseph; Nyeko, Jack Pen-Mogi; Shililu, Josephat I; Githure, John I; Regens, James L; Novak, Robert J; Kakoma, Ibulaimu

2008-01-01

Background The aim of this study was to determine if remotely sensed data and Digital Elevation Model (DEM) can test relationships between Culex quinquefasciatus and Anopheles gambiae s.l. larval habitats and environmental parameters within Internally Displaced People (IDP) campgrounds in Gulu, Uganda. A total of 65 georeferenced aquatic habitats in various IDP camps were studied to compare the larval abundance of Cx. quinquefasciatus and An. gambiae s.l. The aquatic habitat dataset were overlaid onto Land Use Land Cover (LULC) maps retrieved from Landsat imagery with 150 m × 150 m grid cells stratified by levels of drainage. The LULC change was estimated over a period of 14 years. Poisson regression analyses and Moran's I statistics were used to model relationships between larval abundance and environmental predictors. Individual larval habitat data were further evaluated in terms of their covariations with spatial autocorrelation by regressing them on candidate spatial filter eigenvectors. Multispectral QuickBird imagery classification and DEM-based GIS methods were generated to evaluate stream flow direction and accumulation for identification of immature Cx. quinquefasciatus and An. gambiae s.l. and abundance. Results The main LULC change in urban Gulu IDP camps was non-urban to urban, which included about 71.5 % of the land cover. The regression models indicate that counts of An. gambiae s.l. larvae were associated with shade while Cx. quinquefasciatus were associated with floating vegetation. Moran's I and the General G statistics for mosquito density by species and instars, identified significant clusters of high densities of Anopheles; larvae, however, Culex are not consistently clustered. A stepwise negative binomial regression decomposed the immature An. gambiae s.l. data into empirical orthogonal bases. The data suggest the presence of roughly 11% to 28 % redundant information in the larval count samples. The DEM suggest a positive correlation for Culex (0.24) while for Anopheles there was a negative correlation (-0.23) for a local model distance to stream. Conclusion These data demonstrate that optical remote sensing; geostatistics and DEMs can be used to identify parameters associated with Culex and Anopheles aquatic habitats. PMID:18341699

A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios

USGS Publications Warehouse

Bergamaschi, Brian A.; Bernknopf, Richard; Clow, David; Dye, Dennis; Faulkner, Stephen; Forney, William; Gleason, Robert; Hawbaker, Todd; Liu, Jinxun; Liu, Shu-Guang; Prisley, Stephen; Reed, Bradley; Reeves, Matthew; Rollins, Matthew; Sleeter, Benjamin; Sohl, Terry; Stackpoole, Sarah; Stehman, Stephen; Striegl, Robert G.; Wein, Anne; Zhu, Zhi-Liang; Zhu, Zhi-Liang

2010-01-01

he Energy Independence and Security Act of 2007 (EISA), Section 712, mandates the U.S. Department of the Interior to develop a methodology and conduct an assessment of the Nation’s ecosystems, focusing on carbon stocks, carbon sequestration, and emissions of three greenhouse gases (GHGs): carbon dioxide, methane, and nitrous oxide. The major requirements include (1) an assessment of all ecosystems (terrestrial systems, such as forests, croplands, wetlands, grasslands/shrublands; and aquatic ecosystems, such as rivers, lakes, and estuaries); (2) an estimate of the annual potential capacities of ecosystems to increase carbon sequestration and reduce net GHG emissions in the context of mitigation strategies (including management and restoration activities); and (3) an evaluation of the effects of controlling processes, such as climate change, land-use and land-cover change, and disturbances such as wildfires.The concepts of ecosystems, carbon pools, and GHG fluxes follow conventional definitions in use by major national and international assessment or inventory efforts. In order to estimate current ecosystem carbon stocks and GHG fluxes and to understand the potential capacity and effects of mitigation strategies, the method will use two time periods for the assessment: 2001 through 2010, which establishes a current ecosystem carbon and GHG baseline and will be used to validate the models; and 2011 through 2050, which will be used to assess potential capacities based on a set of scenarios. The scenario framework will be constructed using storylines of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES), along with both reference and enhanced land-use and land-cover (LULC) and land-management parameters. Additional LULC and land-management mitigation scenarios will be constructed for each storyline to increase carbon sequestration and reduce GHG fluxes in ecosystems. Input from regional experts and stakeholders will be solicited to construct these scenarios.The methods for mapping the current LULC and ecosystem disturbances will require the extensive use of both remote-sensing data and field-survey data (for example, forest inventories) to capture and characterize landscape-changing events. For potential LULC changes and ecosystem disturbances, key drivers such as socioeconomic and climate changes will be used in addition to the biophysical data. The result of these analyses will be a series of maps for each future year for each scenario. These annual maps will form the basis for estimating carbon storage and GHG emissions. For terrestrial ecosystems, carbon storage, carbon-sequestration capacities, and GHG emissions under the present conditions and future scenarios will be assessed using the LULC-change and ecosystem-disturbance estimates in map format with a spatially explicit biogeochemical ensemble modeling system that incorporates properties of management activities (such as tillage or harvesting) and properties of individual ecosystems (such as energy exchange, vegetation characteristics, hydrological cycling, and soil attributes). For aquatic ecosystems, carbon burial in sediments and fluxes of GHG are functions of the present and future potential stream flow and sediment transport and will be assessed using empirical hydrological modeling methods. Validation and uncertainty analysis methods described in the methodology will follow established guidelines to assess the quality of the assessment results.The U.S. Environmental Protection Agency’s Level II ecoregions map will be the practical instrument for developing and delivering assessment results. Consequently, the ecoregion (there are 22 modified ecoregions) will be the reporting unit of the assessment because the scenarios, assessment results, validation, and uncertainty analysis will be produced at that scale. The implementation of these methods will require collaborations among various Federal agencies, State agencies, nongovernmental organizations, and the science community. Using the method described in this document, the assessment can be completed in approximately 3 to 4 years. The primary deliverables will be assessment reports containing tables, charts, and maps that will present the estimated GHG parameters annually for 2001 through 2050 by ecosystem, pool, and scenario. The results will permit the evaluation of a range of policies, mitigation options, and research topics, such as the demographic, LULC-change, or climate-change effects on carbon stocks, carbon sequestration, and GHG fluxes in ecosystems.

Climate Change Studies over Bangalore using Multi-source Remote Sensing Data and GIS

NASA Astrophysics Data System (ADS)

B, S.; Gouda, K. C.; Laxmikantha, B. P.; Bhat, N.

2014-12-01

Urbanization is a form of metropolitan growth that is a response to often bewildering sets of economic, social, and political forces and to the physical geography of an area. Some of the causes of the sprawl include - population growth, economy, patterns of infrastructure initiatives like the construction of roads and the provision of infrastructure using public money encouraging development. The direct implication of such urban sprawl is the change in land use and land cover of the region. In this study the long term climate data from multiple sources like NCEP reanalysis, IMD observations and various satellite derived products from MAIRS, IMD, ERSL and TRMM are considered and analyzed using the developed algorithms for the better understanding of the variability in the climate parameters over Bangalore. These products are further mathematically analyzed to arrive at desired results by extracting land surface temperature (LST), Potential evapo-transmission (PET), Rainfall, Humidity etc. Various satellites products are derived from NASA (National Aeronautics Space Agency), Indian meteorological satellites and global satellites are helpful in massive study of urban issues at global and regional scale. Climate change analysis is well studied by using either single source data such as Temperature or Rainfall from IMD (Indian Meteorological Department) or combined data products available as in case of MAIRS (Monsoon Asia Integrated Regional Scale) program to get rainfall at regional scale. Finally all the above said parameters are normalized and analyzed with the help of various open source available software's for pre and post processing our requirements to obtain desired results. A sample of analysis i.e. the Inter annual variability of annual averaged Temperature over Bangalore is presented in figure 1, which clearly shows the rising trend of the temperature (0.06oC/year). Also the Land use and land cover (LULC) analysis over Bangalore, Day light hours from satellite derived products are analyzed and the correlation of climate parameters with LULC are presented.

The impacts of land use, radiative forcing, and biological changes on regional climate in Japan

NASA Astrophysics Data System (ADS)

Dairaku, K.; Pielke, R. A., Sr.

2013-12-01

Because regional responses of surface hydrological and biogeochemical changes are particularly complex, it is necessary to develop assessment tools for regional scale adaptation to climate. We developed a dynamical downscaling method using the regional climate model (NIED-RAMS) over Japan. The NIED-RAMS model includes a plant model that considers biological processes, the General Energy and Mass Transfer Model (GEMTM) which adds spatial resolution to accurately assess critical interactions within the regional climate system for vulnerability assessments to climate change. We digitalized a potential vegetation map that formerly existed only on paper into Geographic Information System data. It quantified information on the reduction of green spaces and the expansion of urban and agricultural areas in Japan. We conducted regional climate sensitivity experiments of land use and land cover (LULC) change, radiative forcing, and biological effects by using the NIED-RAMS with horizontal grid spacing of 20 km. We investigated regional climate responses in Japan for three experimental scenarios: 1. land use and land cover is changed from current to potential vegetation; 2. radiative forcing is changed from 1 x CO2 to 2 x CO2; and 3. biological CO2 partial pressures in plants are doubled. The experiments show good accuracy in reproducing the surface air temperature and precipitation. The experiments indicate the distinct change of hydrological cycles in various aspects due to anthropogenic LULC change, radiative forcing, and biological effects. The relative impacts of those changes are discussed and compared. Acknowledgments This study was conducted as part of the research subject "Vulnerability and Adaptation to Climate Change in Water Hazard Assessed Using Regional Climate Scenarios in the Tokyo Region' (National Research Institute for Earth Science and Disaster Prevention; PI: Koji Dairaku) of Research Program on Climate Change Adaptation (RECCA), and was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

Combined and synergistic effects of climate change and urbanization on water quality in the Wolf Bay watershed, southern Alabama.

PubMed

Wang, Ruoyu; Kalin, Latif

2018-02-01

This study investigated potential changes in flow, total suspended solid (TSS) and nutrient (nitrogen and phosphorous) loadings under future climate change, land use/cover (LULC) change and combined change scenarios in the Wolf Bay watershed, southern Alabama, USA. Four Global Circulation Models (GCMs) under three Special Report Emission Scenarios (SRES) of greenhouse gas were used to assess the future climate change (2016-2040). Three projected LULC maps (2030) were employed to reflect different extents of urbanization in future. The individual, combined and synergistic impacts of LULC and climate change on water quantity/quality were analyzed by the Soil and Water Assessment Tool (SWAT). Under the "climate change only" scenario, monthly distribution and projected variation of TSS are expected to follow a pattern similar to streamflow. Nutrients are influenced both by flow and management practices. The variation of Total Nitrogen (TN) and Total Phosphorous (TP) generally follow the flow trend as well. No evident difference in the N:P ratio was projected. Under the "LULC change only" scenario, TN was projected to decrease, mainly due to the shrinkage of croplands. TP will increase in fall and winter. The N:P ratio shows a strong decreasing potential. Under the "combined change" scenario, LULC and climate change effect were considered simultaneously. Results indicate that if future loadings are expected to increase/decrease under any individual scenario, then the combined change will intensify that trend. Conversely, if their effects are in opposite directions, an offsetting effect occurs. Science-based management practices are needed to reduce nutrient loadings to the Bay. Copyright © 2017. Published by Elsevier B.V.

Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios

USGS Publications Warehouse

Bergamaschi, Brian A.; Bernknopf, Richard; Clow, David; Dye, Dennis; Faulkner, Stephen; Forney, William; Gleason, Robert; Hawbaker, Todd; Liu, Jinxun; Liu, Shu-Guang; Prisley, Stephen; Reed, Bradley; Reeves, Matthew; Rollins, Matthew; Sleeter, Benjamin; Sohl, Terry; Stackpoole, Sarah; Stehman, Stephen; Striegl, Robert G.; Wein, Anne; Zhu, Zhi-Liang; Zhu, Zhi-Liang

2010-01-01

The Energy Independence and Security Act of 2007 (EISA), Section 712, authorizes the U.S. Department of the Interior to develop a methodology and conduct an assessment of the Nation's ecosystems focusing on carbon stocks, carbon sequestration, and emissions of three greenhouse gases (GHGs): carbon dioxide, methane, and nitrous oxide. The major requirements include (1) an assessment of all ecosystems (terrestrial systems, such as forests, croplands, wetlands, shrub and grasslands; and aquatic ecosystems, such as rivers, lakes, and estuaries), (2) an estimation of annual potential capacities of ecosystems to increase carbon sequestration and reduce net GHG emissions in the context of mitigation strategies (including management and restoration activities), and (3) an evaluation of the effects of controlling processes, such as climate change, land use and land cover, and wildlfires. The purpose of this draft methodology for public review is to propose a technical plan to conduct the assessment. Within the methodology, the concepts of ecosystems, carbon pools, and GHG fluxes used for the assessment follow conventional definitions in use by major national and international assessment or inventory efforts. In order to estimate current ecosystem carbon stocks and GHG fluxes and to understand the potential capacity and effects of mitigation strategies, the method will use two time periods for the assessment: 2001 through 2010, which establishes a current ecosystem GHG baseline and will be used to validate the models; and 2011 through 2050, which will be used to assess future potential conditions based on a set of projected scenarios. The scenario framework is constructed using storylines of the Intergovernmental Panel on Climate Change (IPCC) Special Report Emission Scenarios (SRES), along with initial reference land-use and land-cover (LULC) and land-management scenarios. An additional three LULC and land-management mitigation scenarios will be constructed for each storyline to enhance carbon sequestration and reduce GHG fluxes in ecosystems. Input from regional experts and stakeholders will be solicited to construct realistic and meaningful scenarios. The methods for mapping the current LULC and ecosystem disturbances will require the extensive use of both remote-sensing data and in-situ (for example, forest inventory data) to capture and characterize landscape-change events. For future potential LULC and ecosystem disturbances, key drivers such as socioeconomic, policy, and climate assumptions will be used in addition to biophysical data. The product of these analyses will be a series of maps for each future year for each scenario. These annual maps will form the basis for estimating carbon storage and GHG emissions. For terrestrial ecosystems, carbon storage, carbon-sequestration capacities, and GHG emissions under the current and projected future conditions will be assessed using the LULC and ecosystem-disturbance estimates in map format with a spatially explicit biogeochemical ensemble modeling system that incorporates properties of management activities (such as tillage or harvesting) and properties of individual ecosystems (such as elevation, vegetation characteristics, and soil attributes). For aquatic ecosystems, carbon burial in sediments and GHG fluxes are functions of the current and projected future stream flow and sediment transports, and therefore will be assessed using empirical modeling methods. Validation and uncertainty analysis methods described in the methodology will follow established guidelines to assess the quality of the assessment results. The U.S. Environmental Protection Agency's Level II ecoregions map (which delineates 24 ecoregions for the Nation) will be the practical instrument for developing and delivering assessment results. Consequently, the ecoregion will be the reporting unit of the assessment because the mitigation scenarios, assessment results, validation, and uncertainty analysis will be

Object-based land-use/land-cover change detection using Landsat imagery: a case study of Ardabil, Namin, and Nir counties in northwest Iran.

PubMed

Aslami, Farnoosh; Ghorbani, Ardavan

2018-06-03

In this study, land-use/land-cover (LULC) change in the Ardabil, Namin, and Nir counties, in the Ardabil province in the northwest of Iran, was detected using an object-based method. Landsat images including Thematic Mapper (TM), Landsat Enhanced Thematic Mapper Plus (ETM + ), and Operational Land Imager (OLI) were used. Preprocessing methods, including geometric and radiometric correction, and topographic normalization were performed. Image processing was conducted according to object-based image analysis using the nearest neighbor algorithm. An accuracy assessment was conducted using overall accuracy and Kappa statistics. Results show that maps obtained from images for 1987, 2002, and 2013 had an overall accuracy of 91.76, 91.06, and 93.00%, and a Kappa coefficient of 0.90, 0.83, and 0.91, respectively. Change detection between 1987 and 2013 shows that most of the rangelands (97,156.6 ha) have been converted to dry farming; moreover, residential and other urban land uses have also increased. The largest change in land use has occurred for irrigated farming, rangelands, and dry farming, of which approximately 3539.8, 3086.9, and 2271.9 ha, respectively, have given way to urban land use for each of the studied years.

Evaluating the Return in Ecosystem Services from Investment in Public Land Acquisitions

PubMed Central

Kovacs, Kent; Polasky, Stephen; Nelson, Erik; Keeler, Bonnie L.; Pennington, Derric; Plantinga, Andrew J.; Taff, Steven J.

2013-01-01

We evaluate the return on investment (ROI) from public land conservation in the state of Minnesota, USA. We use a spatially-explicit modeling tool, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), to estimate how changes in land use and land cover (LULC), including public land acquisitions for conservation, influence the joint provision and value of multiple ecosystem services. We calculate the ROI of a public conservation acquisition as the ratio of the present value of ecosystem services generated by the conservation to the cost of the conservation. For the land scenarios analyzed, carbon sequestration services generated the greatest benefits followed by water quality improvements and recreation opportunities. We found ROI values ranged from 0.21 to 5.28 depending on assumptions about future land use change, service values, and discount rate. Our study suggests conservation is a good investment as long as investments are targeted to areas with low land costs and high service values. PMID:23776429

Urban Thermal Environment Dynamics: A Case Study in Hangzhou During 2005-2015

NASA Astrophysics Data System (ADS)

Sun, W.; Li, F.; Yang, G.

2017-12-01

Hangzhou, as the Capital of Zhejiang Province in East China, has experienced the rapid urbanization process and associated urban heat island effect in the past twenty decades. In this study, we implemented Landsat satellite remote sensing images to investigate the relationship between landscape changes and thermal environment dynamics during 2005-2015 in Hangzhou City. A total of 48 Landsat TM/ETM+/OLR/TIRS images spanning four different seasons were downloaded from the USGS website and utilized in the study. Preprocessing works, i.e., radiometric correction and removing cloud- and fog -contaminated pixels, were conducted, and the land surface temperature (LST) was derived using the radiative transfer equation. Meanwhile, the land use and land cover (LULC) classification was accomplished by using the Support Vector Machine (SVM) classifier, and four main landscape indexes (i.e., Shannon Diversity Index, Landscape Division Index, Shannon Evenness Index, and Aggregation Index) were estimated from the LULC map. Our preliminary results show that: 1) the magnitude of urban thermal environment has obviously increased from 2005 to 2015, and the summer season shows more significant heat island effect than other three seasons; 2) the general landscape pattern of Hangzhou becomes more diversified and fragmentized from 2005 to 2015, and different landscape patterns bring that four different function zones (i.e., urban core zone, tourism function zone, industrial development zone and ecological reservation zone) of Hangzhou have different characteristics in urban thermal environment; 3) significant hot spots of LST point to the construction land while cold spots of LST coincides with the vegetation land.

Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery

NASA Astrophysics Data System (ADS)

Nguyen, Hoang Hai; Tran, Hien; Sunwoo, Wooyeon; Yi, Jong-hyuk; Kim, Dongkyun; Choi, Minha

2017-04-01

A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.

Sensitivity of Hurricane Storm Surge to Land Cover and Topography Under Various Sea Level Rise Scenarios Along the Mississippi Coast

NASA Astrophysics Data System (ADS)

Bilskie, M. V.; Hagen, S. C.; Medeiros, S. C.

2013-12-01

Major Gulf hurricanes have a high probability of impacting the northern Gulf of Mexico, especially coastal Mississippi (Resio, 2007). Due to the wide and flat continental shelf, this area provides near-perfect geometry for high water levels under tropical cyclone conditions. Literature suggests with 'very high confidence that global sea level will rise at least 0.2 m and no more than 2.0 m by 2011' (Donoghue, 2011; Parris et al., 2012). Further, it is recognized that the Mississippi barrier islands are highly susceptible to a westward migration and retreating shoreline. With predictions for less frequent, more intense tropical storms, rising sea levels, and a changing landscape, it is important to understand how these changes may affect inundation extent and flooding due to hurricane storm surge. A state-of-the-art SWAN+ADCIRC hydrodynamic model of coastal Mississippi was utilized to simulate Hurricane Katrina with present day sea level conditions. Using present day as a base scenario, past (1960) and future (2050) sea level changes were simulated. In addition to altering the initial sea state, land use land cover (LULC) was modified for 1960 and 2050 based on historic data and future projections. LULC datasets are used to derive surface roughness characteristics, such as Manning's n, and wind reduction factors. The topography along the barrier islands and near the Pascagoula River, MS was also altered to reflect the 1960 landscape. Storm surge sensitivity to topographic change were addressed by comparing model results between two 1960 storm surge simulations; one with current topography and a second with changes to the barrier islands. In addition, model responses to changes in LULC are compared. The results will be used to gain insight into adapting present day storm surge models for future conditions. References Donoghue, J. (2011). Sea level history of the northern Gulf of Mexico coast and sea level rise scenarios for the near future. Climatic Change, 107(1-2), 17-33. doi: 10.1007/s10584-011-0077-x Parris, A., Bromirski, P., Burkett, V., Cayan, D., Culver, M., Hall, J., . . . Weiss, J. (2012). Global Sea Level Rise Scenarios for the United States National Climate Assessment NOAA Tech Memo OAR CPO-1 (pp. 37). Resio, D. T. (2007). White paper on estimating hurricane inundation probabilities (pp. 125). Vicksburg, MS: U.S. Army Engineering Research and Development Center.

Estuarine Response to River Flow and Sea-Level Rise under Future Climate Change and Human Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Zhaoqing; Wang, Taiping; Voisin, Nathalie

Understanding the response of river flow and estuarine hydrodynamics to climate change, land-use/land-cover change (LULC), and sea-level rise is essential to managing water resources and stress on living organisms under these changing conditions. This paper presents a modeling study using a watershed hydrology model and an estuarine hydrodynamic model, in a one-way coupling, to investigate the estuarine hydrodynamic response to sea-level rise and change in river flow due to the effect of future climate and LULC changes in the Snohomish River estuary, Washington, USA. A set of hydrodynamic variables, including salinity intrusion points, average water depth, and salinity of themore » inundated area, were used to quantify the estuarine response to river flow and sea-level rise. Model results suggest that salinity intrusion points in the Snohomish River estuary and the average salinity of the inundated areas are a nonlinear function of river flow, although the average water depth in the inundated area is approximately linear with river flow. Future climate changes will shift salinity intrusion points further upstream under low flow conditions and further downstream under high flow conditions. In contrast, under the future LULC change scenario, the salinity intrusion point will shift downstream under both low and high flow conditions, compared to present conditions. The model results also suggest that the average water depth in the inundated areas increases linearly with sea-level rise but at a slower rate, and the average salinity in the inundated areas increases linearly with sea-level rise; however, the response of salinity intrusion points in the river to sea-level rise is strongly nonlinear.« less

Spatiotemporal response of the water cycle to land use conversions in a typical hilly-gully basin on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Qiu, Linjing; Wu, Yiping; Wang, Lijing; Lei, Xiaohui; Liao, Weihong; Hui, Ying; Meng, Xianyong

2017-12-01

The hydrological effects of the Grain for Green project (GFGP) on the Loess Plateau have been extensively debated due to the complexity of the water system and its multiple driving factors. The aim of this study was to investigate the response of the hydrological cycle to the GFGP measures based in a case study of the Yanhe Basin, a typical hilly-gully area on the Loess Plateau of China. First, we analyzed the land use and land cover (LULC) changes from 1990 to 2010. Then, we evaluated the effects of LULC changes and sloping land conversion on the main hydrological components in the basin using the Soil and Water Assessment Tool (SWAT). The results indicated that cropland exhibited a decreasing trend, declining from 40.2 % of the basin area in 1990 to 17.6 % in 2010, and that the woodland and grassland areas correspondingly increased. With the land use changes from 1990 to 2010, the water yield showed a decreasing trend which was mainly due to decrease in surface runoff. In contrast, evapotranspiration (ET) showed an increasing trend over the same period, resulting in a persistent decrease in soil water. The conversion of sloping cropland to grassland or woodland exerted negative effects on water yield and soil water. Compared with the land use condition in 2010, the negative effects were most evident where cropland with a slope ≥ 15° was converted to woodland, with decreases in surface runoff and soil water of 17.1 and 6.4 %, respectively. These results suggest that the expansive reforestation on sloping land in the loess hilly-gully region decreased water yield and increased ET, resulting in reduced soil water. The results of this study can be used to support sustainable land use planning and water resource management on the Loess Plateau in China.

Integrated assessment of future potential global change scenarios and their hydrological impacts in coastal aquifers - a new tool to analyse management alternatives in the Plana Oropesa-Torreblanca aquifer

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, David; Renau-Pruñonosa, Arianna; Llopis-Albert, Carlos; Morell, Ignacio; Collados-Lara, Antonio-Juan; Senent-Aparicio, Javier; Baena-Ruiz, Leticia

2018-05-01

Any change in the components of the water balance in a coastal aquifer, whether natural or anthropogenic, can alter the freshwater-salt water equilibrium. In this sense climate change (CC) and land use and land cover (LULC) change might significantly influence the availability of groundwater resources in the future. These coastal systems demand an integrated analysis of quantity and quality issues to obtain an appropriate assessment of hydrological impacts using density-dependent flow solutions. The aim of this work is to perform an integrated analysis of future potential global change (GC) scenarios and their hydrological impacts in a coastal aquifer, the Plana Oropesa-Torreblanca aquifer. It is a Mediterranean aquifer that extends over 75 km2 in which important historical LULC changes have been produced and are planned for the future. Future CC scenarios will be defined by using an equi-feasible and non-feasible ensemble of projections based on the results of a multi-criteria analysis of the series generated from several regional climatic models with different downscaling approaches. The hydrological impacts of these CC scenarios combined with future LULC scenarios will be assessed with a chain of models defined by a sequential coupling of rainfall-recharge models, crop irrigation requirements and irrigation return models (for the aquifer and its neighbours that feed it), and a density-dependent aquifer approach. This chain of models, calibrated using the available historical data, allow testing of the conceptual approximation of the aquifer behaviour. They are also fed with series representatives of potential global change scenarios in order to perform a sensitivity analysis regarding future scenarios of rainfall recharge, lateral flows coming from the hydraulically connected neighbouring aquifer, agricultural recharge (taking into account expected future LULC changes) and sea level rise (SLR). The proposed analysis is valuable for improving our knowledge about the aquifer, and so comprises a tool to design sustainable adaptation management strategies taking into account the uncertainty in future GC conditions and their impacts. The results show that GC scenarios produce significant increases in the variability of flow budget components and in the salinity.

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

NASA Astrophysics Data System (ADS)

Li, Xia; Mitra, Chandana; Dong, Li; Yang, Qichun

2018-02-01

To explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under the urbanization scenario, but expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. This study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region.

Recent landscape change in California's Central Valley

NASA Astrophysics Data System (ADS)

Soulard, C. E.; Wilson, T. S.

2012-12-01

Long term monitoring of land use and land cover in California's intensively farmed Central Valley reveals several key physical and socioeconomic factors driving landscape change. As part of the USGS Land Cover Trends Project, we analyzed modern land-use/land-cover change for the California Central Valley ecoregion between 2000 and 2010, monitoring annual change between 2005 and 2010, while creating two new change intervals (2000-2005 and 2005-2010) to update the existing 27-year, interval-based analysis. Between 2000 and 2010, agricultural lands fluctuated due to changes in water allocations and emerging drought conditions, or were lost permanently to development (240 square km). Land-use pressure from agriculture and development also led to a decline in grasslands and shrublands across the region (280 square km). Overall, 400 square km of new developed lands were added in the first decade of the 21st century. From 2007 to 2010, development only expanded by 50 square km, coinciding with defaults in the banking system, the onset of historic foreclosure crisis in California and the global economic downturn. Our annual LULC change estimates capture landscape-level change in response to regional policy changes, climate, and fluctuations (e.g., growth or decline) in the national and global economy. The resulting change data provide insights into the drivers of landscape change in the California Central Valley and the combination of two consistent mapping efforts represents the first continuous, 37-year endeavor of its kind.

NASA's Contributions to the Gulf of Mexico Alliance

NASA Technical Reports Server (NTRS)

Glorioso, Mark

2008-01-01

This viewgraph document reviews the contribution that NASA has made and the plans for future missions that will assist the mission of the Gulf of Mexico Alliance (GOMA). Specific reference to the work of the Stennis Space Center is reviewed. Some of the projects are: Coastal Online Assessment and Synthesis Tool (COAST), Regional Sediment Management, Coral Reef Early Warning System, Harmful Algal Bloom, Hypoxia, Land-Use and Land-Cover (LULC) Change from 1974-2008 around Mobile Bay, AL, Satellite Estimation of Suspended Particulate Loads in and around Mobile Bay, AL, Estimating Relative Nutrient Contributions of Agriculture and Forests Using MODIS Time Series, Coastal Marsh Monitoring for Persistent Saltwater Intrusion, Standardized Remote Sensing PRoduct for Water Clarity estimation within Gulf of Mexico Coastal Waters.

High resolution satellite image indexing and retrieval using SURF features and bag of visual words

NASA Astrophysics Data System (ADS)

Bouteldja, Samia; Kourgli, Assia

2017-03-01

In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

Supporting the Establishment of Climate-Resilient Rural Livelihoods in Mongolia with EO Services

NASA Astrophysics Data System (ADS)

Grosso, Nuno; Patinha, Carla; Sainkhuu, Tserendash; Bataa, Mendbayar; Doljinsuren, Nyamdorj

2016-08-01

The work presented here shows the results from the project "Climate-Resilient Rural Livelihoods in Mongolia", included in the EOTAP (Earth Observation for a Transforming Asia Pacific) initiative, a collaboration between the European Space Agency (ESA) and the Asian Development Bank (ADB), developed in cooperation with the Ministry of Food and Agriculture of Mongolia.The EO services developed within this EOTAP project primarily aimed at enriching the existing environmental database maintained by the National Remote Sensing Center (NRSC) in Mongolia and sustaining the collaborative pasture management practices introduced by the teams within the Ministry of Food and Agriculture of Mongolia. The geographic area covered by the EOTAP services is Bayankhongor province, in western Mongolia region, with two main services: drought monitoring at the provincial level for the year 2014 and Land Use/Land Cover (LULC) and changes mapping for three districts of this province (Buutsagaan, Dzag and Khureemaral) for the years 2013, 2014.

A conceptual model for quantifying connectivity using graph theory and cellular (per-pixel) approach

NASA Astrophysics Data System (ADS)

Singh, Manudeo; Sinha, Rajiv; Tandon, Sampat K.

2016-04-01

The concept of connectivity is being increasingly used for understanding hydro-geomorphic processes at all spatio-temporal scales. Connectivity is defined as the potential for energy and material flux (water, sediments, nutrients, heat, etc.) to navigate within or between the landscape systems and has two components, structural connectivity and dynamic connectivity. Structural connectivity is defined by the spatially connected features (physical linkages) through which energy and materials flow. Dynamic connectivity is a process defined connectivity component. These two connectivity components also interact with each other by forming a feedback system. This study attempts to explore a method to quantify structural and dynamic connectivity. In fluvial transport systems, sediment and water can flow in either a diffused manner or in a channelized way. At all the scales, hydrological and sediment fluxes can be tracked using a cellular (per-pixel) approach and can be quantified using graphical approach. The material flux, slope and LULC (Land Use Land Cover) weightage factors of a pixel together determine if it will contribute towards connectivity of the landscape/system. In a graphical approach, all the contributing pixels will form a node at their centroid and this node will be connected to the next 'down-node' via a directed edge with 'least cost path'. The length of the edge will depend on the desired spatial scale and its path direction will depend on the traversed pixel's slope and the LULC (weightage) factors. The weightage factors will lie in-between 0 to 1. This value approaches 1 for the LULC factors which promote connectivity. For example, in terms of sediment connectivity, the weightage could be RUSLE (Revised Universal Soil Loss Equation) C-factors with bare unconsolidated surfaces having values close to 1. This method is best suited for areas with low slopes, where LULC can be a deciding as well as dominating factor. The degree of connectivity and its pathways will show changes under different LULC conditions even if the slope remains the same. The graphical approach provides the statistics of connected and disconnected graph elements (edges, nodes) and graph components, thereby allowing the quantification of structural connectivity. This approach also quantifies the dynamic connectivity by allowing the measurement of the fluxes (e.g. via hydrographs or sedimentographs) at any node as well as at any system outlet. The contribution of any sub-system can be understood by removing the remaining sub-systems which can be conveniently achieved by masking associated graph elements.

The influence of bed friction variability due to land cover on storm-driven barrier island morphodynamics

USGS Publications Warehouse

Passeri, Davina L.; Long, Joseph W.; Plant, Nathaniel G.; Bilskie, Matthew V.; Hagen, Scott C.

2018-01-01

Variations in bed friction due to land cover type have the potential to influence morphologic change during storm events; the importance of these variations can be studied through numerical simulation and experimentation at locations with sufficient observational data to initialize realistic scenarios, evaluate model accuracy and guide interpretations. Two-dimensional in the horizontal plane (2DH) morphodynamic (XBeach) simulations were conducted to assess morphodynamic sensitivity to spatially varying bed friction at Dauphin Island, AL using hurricanes Ivan (2004) and Katrina (2005) as experimental test cases. For each storm, three bed friction scenarios were simulated: (1) a constant Chezy coefficient across land and water, (2) a constant Chezy coefficient across land and depth-dependent Chezy coefficients across water, and (3) spatially varying Chezy coefficients across land based on land use/land cover (LULC) data and depth-dependent Chezy coefficients across water. Modeled post-storm bed elevations were compared qualitatively and quantitatively with post-storm lidar data. Results showed that implementing spatially varying bed friction influenced the ability of XBeach to accurately simulate morphologic change during both storms. Accounting for frictional effects due to large-scale variations in vegetation and development reduced cross-barrier sediment transport and captured overwash and breaching more accurately. Model output from the spatially varying friction scenarios was used to examine the need for an existing sediment transport limiter, the influence of pre-storm topography and the effects of water level gradients on storm-driven morphodynamics.

Quantifying the Uncertainty in Streamflow Predictions Using Swat for Brazos-Colorado Coastal Watershed, Texas

NASA Astrophysics Data System (ADS)

Mandal, D.; Bhatia, N.; Srivastav, R. K.

2016-12-01

Soil Water Assessment Tool (SWAT) is one of the most comprehensive hydrologic models to simulate streamflow for a watershed. The two major inputs for a SWAT model are: (i) Digital Elevation Models (DEM), and (ii) Land Use and Land Cover Maps (LULC). This study aims to quantify the uncertainty in streamflow predictions using SWAT for San Bernard River in Brazos-Colorado coastal watershed, Texas, by incorporating the respective datasets from different sources: (i) DEM data will be obtained from ASTER GDEM V2, GMTED2010, NHD DEM, and SRTM DEM datasets with ranging resolution from 1/3 arc-second to 30 arc-second, and (ii) LULC data will be obtained from GLCC V2, MRLC NLCD2011, NOAA's C-CAP, USGS GAP, and TCEQ databases. Weather variables (Precipitation and Max-Min Temperature at daily scale) will be obtained from National Climatic Data Centre (NCDC) and SWAT in-built STASGO tool will be used to obtain the soil maps. The SWAT model will be calibrated using SWAT-CUP SUFI-2 approach and its performance will be evaluated using the statistical indices of Nash-Sutcliffe efficiency (NSE), ratio of Root-Mean-Square-Error to standard deviation of observed streamflow (RSR), and Percent-Bias Error (PBIAS). The study will help understand the performance of SWAT model with varying data sources and eventually aid the regional state water boards in planning, designing, and managing hydrologic systems.

Quantifying climate change mitigation potential in Great Plains wetlands for three greenhouse gas emission scenarios

USGS Publications Warehouse

Byrd, Kristin B.; Ratliff, Jamie L.; Wein, Anne; Bliss, Norman B.; Sleeter, Benjamin M.; Sohl, Terry L.; Li, Zhengpeng

2015-01-01

We examined opportunities for avoided loss of wetland carbon stocks in the Great Plains of the United States in the context of future agricultural expansion through analysis of land-use land-cover (LULC) change scenarios, baseline carbon datasets and biogeochemical model outputs. A wetland map that classifies wetlands according to carbon pools was created to describe future patterns of carbon loss and potential carbon savings. Wetland avoided loss scenarios, superimposed upon LULC change scenarios, quantified carbon stocks preserved under criteria of carbon densities or land value plus cropland suitability. Up to 3420 km2 of wetlands may be lost in the region by 2050, mainly due to conversion of herbaceous wetlands in the Temperate Prairies where soil organic carbon (SOC) is highest. SOC loss would be approximately 0.20 ± 0.15 megagrams of carbon per hectare per year (MgC ha−1 yr−1), depending upon tillage practices on converted wetlands, and total ecosystem carbon loss in woody wetlands would be approximately 0.81 ± 0.41 MgC ha−1 yr−1, based on biogeochemical model results. Among wetlands vulnerable to conversion, wetlands in the Northern Glaciated Plains and Lake Agassiz Plains ecoregions exhibit very high mean SOC and on average, relatively low land values, potentially creating economically competitive opportunities for avoided carbon loss. This mitigation scenarios approach may be adapted by managers using their own preferred criteria to select sites that best meet their objectives. Results can help prioritize field-based assessments, where site-level investigations of carbon stocks, land value, and consideration of local priorities for climate change mitigation programs are needed.

Comparison of k-means related clustering methods for nuclear medicine images segmentation

NASA Astrophysics Data System (ADS)

Borys, Damian; Bzowski, Pawel; Danch-Wierzchowska, Marta; Psiuk-Maksymowicz, Krzysztof

2017-03-01

In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

Temporal and spatial trends in nutrient and sediment loading to Lake Tahoe, California-Nevada, USA

USGS Publications Warehouse

Coats, Robert; Lewis, Jack; Alvarez, Nancy L.; Arneson, Patricia

2016-01-01

Since 1980, the Lake Tahoe Interagency Monitoring Program (LTIMP) has provided stream-discharge and water quality data—nitrogen (N), phosphorus (P), and suspended sediment—at more than 20 stations in Lake Tahoe Basin streams. To characterize the temporal and spatial patterns in nutrient and sediment loading to the lake, and improve the usefulness of the program and the existing database, we have (1) identified and corrected for sources of bias in the water quality database; (2) generated synthetic datasets for sediments and nutrients, and resampled to compare the accuracy and precision of different load calculation models; (3) using the best models, recalculated total annual loads over the period of record; (4) regressed total loads against total annual and annual maximum daily discharge, and tested for time trends in the residuals; (5) compared loads for different forms of N and P; and (6) tested constituent loads against land use-land cover (LULC) variables using multiple regression. The results show (1) N and P loads are dominated by organic N and particulate P; (2) there are significant long-term downward trends in some constituent loads of some streams; and (3) anthropogenic impervious surface is the most important LULC variable influencing water quality in basin streams. Many of our recommendations for changes in water quality monitoring and load calculation methods have been adopted by the LTIMP.

Is Nigeria losing its natural vegetation and landscape? Assessing the landuse-landcover change trajectories and effects in Onitsha using remote sensing and GIS

NASA Astrophysics Data System (ADS)

Nwaogu, Chukwudi; Okeke, Onyedikachi J.; Fadipe, Olusola O.; Bashiru, Kehinde A.; Pechanec, Vilém

2017-12-01

Onitsha is one of the largest commercial cities in Africa with its population growth rate increasing arithmetically for the past two decades. This situation has direct and indirect effects on the natural resources including vegetation and water. The study aimed at assessing land use-land cover (LULC) change and its effects on the vegetation and landscape from 1987 to 2015 using geoinformatics. Supervised and unsupervised classifications including maximum likelihood algorithm were performed using ENVI 4.7 and ArcGIS 10.1 versions. The LULC was classified into 7 classes: built-up areas (settlement), waterbody, thick vegetation, light vegetation, riparian vegetation, sand deposit (bare soil) and floodplain. The result revealed that all the three vegetation types decreased in areas throughout the study period while, settlement, sand deposit and floodplain areas have remarkable increase of about 100% in 2015 when compared with the total in 1987. Number of dominant plant species decreased continuously during the study. The overall classification accuracies in 1987, 2002 and 2015 was 90.7%, 92.9% and 95.5% respectively. The overall kappa coefficient of the image classification for 1987, 2002 and 2015 was 0.98, 0.93 and 0.96 respectively. In general, the average classification was above 90%, a proof that the classification was reliable and acceptable.

Application of Coupled Human-Natural Systems Model for Assessing Trade-Offs Between Watershed Ecosystem Services in Veracruz, Mexico

NASA Astrophysics Data System (ADS)

Mayer, A. S.; Jones, K.; Berry, Z. C.; Congalton, R.; Kolka, R. K.; López-Ramírez, S.; Manson, R.; Muñoz Villers, L.; Saenz, L.; Salcone, J.; Von Thaden Ugalde, J.; Asbjornsen, H.

2016-12-01

Trade-offs between ecosystem services (ES) occur due to management choices that impact the type, magnitude, and relative mix of services provided by ecosystems. Trade-offs arise when the provision of one ES is reduced as a consequence of increased use of another ES. Here, we assess ES tradeoffs with a coupled human-natural systems (CHNS) model, in response to payments for watershed services (PWS) programs in two watersheds in Veracruz, Mexico. An econometric component of the CHNS model is used to determine the effect of the PWS programs on a given land use-land cover (LULC). Eight LULC categories, corresponding to 95% of the watershed area, are used to force LULC feedbacks within the CHNS model. The LULC can transition from the present category to another, given the outcome of landowner participation in the PWS programs. Biophysical sub-models of watershed discharge and water quality, carbon storage, and biodiversity conservation are used to estimate values of ES indicators at the watershed scale. These biophysical models are derived from qualitative and quantitative observations in the study watersheds. Using these models, we gain first-approximation insights into ES tradeoffs and the sensitivity of estimated tradeoffs to model structure—serving as a critical platform for informing hypotheses about PWS program design and ES tradeoffs. With a CHNS model in place, and data collected collected from our field experiments, we explore first, baseline implications for ES of existing PWS programs in Xalapa, Veracruz; and second, we develop scenarios of potential PWS program pathways, with or without climate change projection forcings in order to improve our understanding of changes in ES distribution, magnitude and biophysical tradeoffs. Finally, the econometric component is parameterized with economic variables and indicators identified with local stakeholders in order to asses economic implications of ES tradeoffs. Outputs from the model provide important information to the local and national agencies involved in PWS program design in the study watersheds. This first tier model will be used to inform development of a more integrated process-based model using primary watershed socioeconomic and ecohydrological data, as well as household level data on participation in the PWS programs and spillover effects of PWS.

A method for the use of landscape metrics in freshwater research and management

USGS Publications Warehouse

Kearns, F.R.; Kelly, N.M.; Carter, J.L.; Resh, V.H.

2005-01-01

Freshwater research and management efforts could be greatly enhanced by a better understanding of the relationship between landscape-scale factors and water quality indicators. This is particularly true in urban areas, where land transformation impacts stream systems at a variety of scales. Despite advances in landscape quantification methods, several studies attempting to elucidate the relationship between land use/land cover (LULC) and water quality have resulted in mixed conclusions. However, these studies have largely relied on compositional landscape metrics. For urban and urbanizing watersheds in particular, the use of metrics that capture spatial pattern may further aid in distinguishing the effects of various urban growth patterns, as well as exploring the interplay between environmental and socioeconomic variables. However, to be truly useful for freshwater applications, pattern metrics must be optimized based on characteristic watershed properties and common water quality point sampling methods. Using a freely available LULC data set for the Santa Clara Basin, California, USA, we quantified landscape composition and configuration for subwatershed areas upstream of individual sampling sites, reducing the number of metrics based on: (1) sensitivity to changes in extent and (2) redundancy, as determined by a multivariate factor analysis. The first two factors, interpreted as (1) patch density and distribution and (2) patch shape and landscape subdivision, explained approximately 85% of the variation in the data set, and are highly reflective of the heterogeneous urban development pattern found in the study area. Although offering slightly less explanatory power, compositional metrics can provide important contextual information. ?? Springer 2005.

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

DOE PAGES

Li, Xia; Mitra, Chandana; Dong, Li; ...

2017-02-02

In order to explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Our results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under themore » urbanization scenario, but expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. Our study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region.« less

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xia; Mitra, Chandana; Dong, Li

In order to explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Our results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under themore » urbanization scenario, but expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. Our study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region.« less

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xia; Mitra, Chandana; Dong, Li

To explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under the urbanization scenario, butmore » expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. This study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region. (C) 2017 Elsevier Ltd. All rights reserved.« less

Assessing the Impact of Farmland Abandonment on Ecosystem Services of a Catchment in Southern Italy.

NASA Astrophysics Data System (ADS)

Romano, N.; Nasta, P.; Palladino, M.; Saracino, A.; Ursino, N.

2016-12-01

During the postwar period farming systems in hilly and mountainous areas of Mediterranean Europe have been subjected to progressive abandonment. The environmental impacts of land-use/land-cover (LULC) changes on the ecosystem services (ESs) have been investigated in the Upper Alento River Basin (UARB) located in Southern Italy. A chronosequence of LULC maps was built. In 1955 we document the human-driven landscape with dominance of pasture and crops (35% and 34%, respectively) over forested areas (20%); in 1998 forests doubled and crops roughly halved their surface (43% and 18%, respectively) as a result of decadal land abandonment. In 2015 we document a massive landscape shift in which secondary forests occupy 70% of the basin and orchards 20%, the latter favored by European Community incentives. The 1998 land-use scenario has been implemented in the SWAT model that was calibrated and validated using direct streamflow measurements recorded in the period 1995-2004 at the earth-dam located at the outlet of UARB. Numerical simulations offer "pseudo-realistic" scenarios that can help interpret differences in average annual and monthly water budget and sediment transport when the 1998 land-use scenario is compared to 1955 and 2015 ones, respectively. The dominance of forest in the last decades implies a reduction of runoff and water influx into the water reservoir, thereby limiting the water stocks for hydroelectric, irrigation and drinking purposes. Conversely, the reduction in runoff is compensated by a decrease in soil erosion that represents a beneficial ES. In a hypothetical land-use scenario, by returning to cropland dominance, as observed in 1955, the ESs will benefit of higher water influx into the reservoir, yet counterbalanced by higher sediment transport. Therefore, in order to mitigate soil erosion, it is necessary to plan soil-loss suitable support practices in view of the potential impact of future projected extreme rainfall events on the hydrological cycle in a Mediterranean patchy agro-forestry system.

The application of remote sensing for climate change adaptation in Sahel region

NASA Astrophysics Data System (ADS)

Deafalla, Taisser H. H.; Csaplovics, Elmar; El-Abbas, Mustafa M.

2014-10-01

In recent years, there is no doubt that global climate change (CC) has observable development impacts, which seriously threatens the ability of individuals and communities at all levels. During this process, the clear degradation in the situation of ecosystems has produced a global concern of the urgency to mitigate climate threats and related effects. Assessing the impacts and vulnerability of CC requires accurate, up-to-date and improved information. Coupled with the ready availability of historical remote sensing (RS) data, the reduction in data cost and increased resolution from satellite platforms, RS technology appears poised to make a great impact on planning agencies and providing better understanding the dynamics of the climate system, predict and mitigate the expected global changes and the effects on human civilization involved in mapping Land Use Land Cover (LU/LC) at a variety of spatial scales. This research was designed to study the impact of CC in conflict zones and potential flashpoints in Sudan namely Nuba Mountains, where the community in this area living in fragile and unstable conditions, which making them more vulnerable to the risk of violent conflict and CC effects. And to determine the factors that exacerbate vulnerability in the study area as well as to map and assess the LU/LC change during the period 1984 to 2011 covered the years (1999, 2002 and 2009). Multispectral satellite data (i.e. LANDSAT TM and TERRA ASTER) were used. Change detection techniques were applied to analyze the rate of changes, causal factors as well as the drivers of changes. Recent study showed the importance of spatial variables in tackling CC which promoted the use of maps made within a RS. In addition to provide an input for climate models; and thus plan adaptation strategies.

Estimating changes in carbon burial on the western US coastal shelf due to anthropogenic influences on river exports

NASA Astrophysics Data System (ADS)

Sauer, M.; Bergamaschi, B. A.; Smith, R. A.; Zhu, Z.; Shih, J.

2012-12-01

Flux of nutrients and sediments to the coastal zone varies in response to land-use modification, reservoir construction, management action and population change. It is anticipated that future changes in the flux of these components in response to climate and terrestrial processes will affect carbon (C) burial in the coastal ocean. Coastal oceans store appreciable amounts of C as a result of river inflows: coastal primary production is enhanced by inputs of terrestrially derived nutrients, and C burial is controlled by terrestrial sediment supply. Assessing the capacity and changes to coastal C preservation, therefore, requires estimation of (1) riverine nutrient and sediment delivery to the coastal ocean, and (2) the enhanced C production and sediment deposition in the coastal ocean. The United States Geological Survey (USGS) has embarked on a congressionally-mandated nationwide effort to assess the future effects of climate and land use and land cover change (LULC) on C storage. The USGS has developed alternative scenarios for changes in US LULC from 2006 to 2100 based on the Intergovernmental Panel on Climate Change (IPCC) climate, economic, and demographic scenarios (Sohl et al 2012). These spatially-detailed scenarios provide inputs to national-scale SPARROW watershed models of total nitrogen, total phosphorus, total organic C (TOC), and suspended sediment (Smith et al 1997; Schwarz et al, 2006). The watershed models, in turn, provide inputs of nutrients, TOC, and sediment to a coupled model of coastal transport, production, and sedimentation. This coastal modelling component includes particulate C sedimentation and burial estimated as functions of bathymetry and pycnocline depth (Armstrong, et al 2002; Dunne et al 2007). River borne fluxes of TOC to US Pacific coastal waters under baseline conditions (1992) were 1.59 TgC/yr. Projected future (2050) fluxes under a regionally-downscaled LULC scenario aligned with the IPCC A2 scenario were similar (1.61TgC/yr). C storage in coastal environments as influenced by terrestrial processes represents a significant sink for C in comparison to terrestrial biomass C sinks, and is significantly sensitive to changes in LULC and population. The estimated rate of storage in Pacific coastal waters was 2.0 TgC/yr under baseline conditions. Projection of land use and population changes through 2050 associated with the IPCC A2 scenario had a small effect on coastal C storage processes, reducing C storage by 4% over baseline conditions. Results of this modeling exercise indicate that the size of the C sink associated with terrestrial exports is substantial and sensitive to anthropogenic activity. Thus, future assessments of how terrestrial policy and management actions may alter C storage should include an evaluation of the effects prospective alterations in terrestrial processes have on coastal C storage.

Comparison of transect sampling and object-oriented image classification methods of urbanizing catchments

NASA Astrophysics Data System (ADS)

Yang, Y.; Tenenbaum, D. E.

2009-12-01

The process of urbanization has major effects on both human and natural systems. In order to monitor these changes and better understand how urban ecological systems work, urban spatial structure and the variation needs to be first quantified at a fine scale. Because the land-use and land-cover (LULC) in urbanizing areas is highly heterogeneous, the classification of urbanizing environments is the most challenging field in remote sensing. Although a pixel-based method is a common way to do classification, the results are not good enough for many research objectives which require more accurate classification data in fine scales. Transect sampling and object-oriented classification methods are more appropriate for urbanizing areas. Tenenbaum used a transect sampling method using a computer-based facility within a widely available commercial GIS in the Glyndon Catchment and the Upper Baismans Run Catchment, Baltimore, Maryland. It was a two-tiered classification system, including a primary level (which includes 7 classes) and a secondary level (which includes 37 categories). The statistical information of LULC was collected. W. Zhou applied an object-oriented method at the parcel level in Gwynn’s Falls Watershed which includes the two previously mentioned catchments and six classes were extracted. The two urbanizing catchments are located in greater Baltimore, Maryland and drain into Chesapeake Bay. In this research, the two different methods are compared for 6 classes (woody, herbaceous, water, ground, pavement and structure). The comparison method uses the segments in the transect method to extract LULC information from the results of the object-oriented method. Classification results were compared in order to evaluate the difference between the two methods. The overall proportions of LULC classes from the two studies show that there is overestimation of structures in the object-oriented method. For the other five classes, the results from the two methods are similar, except for a difference in the proportions of the woody class. The segment to segment comparison shows that the resolution of the light detection and ranging (LIDAR) data used in the object-oriented method does affect the accuracy of the classification. Shadows of trees and structures are still a big problem in the object-oriented method. For classes that make up a small proportion of the catchments, such as water, neither method was capable of detecting them.

GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed, Ethiopia.

PubMed

Nigatu Wondrade; Dick, Øystein B; Tveite, Havard

2014-03-01

Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km(2) in 1973 to 95.2 km(2) in 2011, while that of Lake Cheleleka whose area was 11.3 km(2) in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The "change and no change" analysis revealed that more than one third (548.0 km(2)) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.

Carbon sequestration associated to the land-use and land-cover changes in the forestry sector in Southern Brazil

NASA Astrophysics Data System (ADS)

Ronquim, Carlos C.; Silva, Ramon F. B.; de Figueiredo, Eduardo B.; Bordonal, Ricardo O.; de C. Teixeira, Antônio H.; Cochasrk, Thomas C. D.; Leivas, Janice F.

2016-10-01

We studied the Paraíba do Sul river watershed, São Paulo state (PSWSP), Southeastern Brazil, in order to assess the land use and cover (LULC) and their implications to the amount of carbon (C) stored in the forest cover between the years 1985 and 2015. The region covers an area of 1,395,975 ha. We used images made by the Operational Land Imager (OLI) sensor (OLI/Landsat-8) to produce mappings, and image segmentation techniques to produce vectors with homogeneous characteristics. The training samples and the samples used for classification and validation were collected from the segmented image. To quantify the C stocked in aboveground live biomass (AGLB), we used an indirect method and applied literature-based reference values. The recovery of 205,690 ha of a secondary Native Forest (NF) after 1985 sequestered 9.7 Tg (Teragram) of C. Considering the whole NF area (455,232 ha), the amount of C accumulated along the whole watershed was 35.5 Tg, and the whole Eucalyptus crop (EU) area (113,600 ha) sequestered 4.4 Tg of C. Thus, the total amount of C sequestered in the whole watershed (NF + EU) was 39.9 Tg of C or 145.6 Tg of CO2, and the NF areas were responsible for the largest C stock at the watershed (89%). Therefore, the increase of the NF cover contributes positively to the reduction of CO2 concentration in the atmosphere, and Reducing Emissions from Deforestation and Forest Degradation (REDD+) may become one of the most promising compensation mechanisms for the farmers who increased forest cover at their farms.

Does deforestation promote or inhibit malaria transmission in the Amazon? A systematic literature review and critical appraisal of current evidence

PubMed Central

Tucker Lima, Joanna M.; Vittor, Amy; Rifai, Sami

2017-01-01

Considerable interest in the relationship between biodiversity and disease has recently captured the attention of the research community, with important public policy implications. In particular, malaria in the Amazon region is often cited as an example of how forest conservation can improve public health outcomes. However, despite a growing body of literature and an increased understanding of the relationship between malaria and land use / land cover change (LULC) in Amazonia, contradictions have emerged. While some studies report that deforestation increases malaria risk, others claim the opposite. Assessing malaria risk requires examination of dynamic processes among three main components: (i) the environment (i.e. LULC and landscape transformations), (ii) vector biology (e.g. mosquito species distributions, vector activity and life cycle, plasmodium infection rates), and (iii) human populations (e.g. forest-related activity, host susceptibility, movement patterns). In this paper, we conduct a systematic literature review on malaria risk and deforestation in the Amazon focusing on these three components. We explore key features that are likely to generate these contrasting results using the reviewed articles and our own data from Brazil and Peru, and conclude with suggestions for productive avenues in future research. This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications'. PMID:28438914

Does deforestation promote or inhibit malaria transmission in the Amazon? A systematic literature review and critical appraisal of current evidence.

PubMed

Tucker Lima, Joanna M; Vittor, Amy; Rifai, Sami; Valle, Denis

2017-06-05

Considerable interest in the relationship between biodiversity and disease has recently captured the attention of the research community, with important public policy implications. In particular, malaria in the Amazon region is often cited as an example of how forest conservation can improve public health outcomes. However, despite a growing body of literature and an increased understanding of the relationship between malaria and land use / land cover change (LULC) in Amazonia, contradictions have emerged. While some studies report that deforestation increases malaria risk, others claim the opposite. Assessing malaria risk requires examination of dynamic processes among three main components: (i) the environment (i.e. LULC and landscape transformations), (ii) vector biology (e.g. mosquito species distributions, vector activity and life cycle, plasmodium infection rates), and (iii) human populations (e.g. forest-related activity, host susceptibility, movement patterns). In this paper, we conduct a systematic literature review on malaria risk and deforestation in the Amazon focusing on these three components. We explore key features that are likely to generate these contrasting results using the reviewed articles and our own data from Brazil and Peru, and conclude with suggestions for productive avenues in future research.This article is part of the themed issue 'Conservation, biodiversity and infectious disease: scientific evidence and policy implications'. © 2017 The Authors.

GIS and remote sensing techniques for the assessment of land use changes impact on flood hydrology: the case study of Yialias Basin in Cyprus

NASA Astrophysics Data System (ADS)

Alexakis, D. D.; Gryllakis, M. G.; Koutroulis, A. G.; Agapiou, A.; Themistocleous, K.; Tsanis, I. K.; Michaelides, S.; Pashiardis, S.; Demetriou, C.; Aristeidou, K.; Retalis, A.; Tymvios, F.; Hadjimitsis, D. G.

2013-09-01

Flooding is one of the most common natural disasters worldwide, leading to economic losses and loss of human lives. This paper highlights the hydrological effects of multi-temporal land use changes in flood hazard within the Yialias catchment area, located in central Cyprus. Calibrated hydrological and hydraulic models were used to describe the hydrological processes and internal basin dynamics of the three major sub-basins, in order to study the diachronic effects of land use changes. For the implementation of the hydrological model, land use, soil and hydrometeorological data were incorporated. The climatic and stream flow data were derived from rain and flow gauge stations located in the wider area of the watershed basin. In addition, the land use and soil data were extracted after the application of object oriented nearest neighbor algorithms of ASTER satellite images. Subsequently, the CA-Markov chain analysis was implemented to predict the 2020 Land use/Land cover (LULC) map and incorporate it to the hydrological impact assessment. The results denoted the increase of runoff in the catchment area due to the recorded extensive urban sprawl phenomenon of the last decade.

Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

NASA Astrophysics Data System (ADS)

Rußwurm, Marc; Körner, Marco

2018-03-01

Earth observation (EO) sensors deliver data with daily or weekly temporal resolution. Most land use and land cover (LULC) approaches, however, expect cloud-free and mono-temporal observations. The increasing temporal capabilities of today's sensors enables the use of temporal, along with spectral and spatial features. Domains, such as speech recognition or neural machine translation, work with inherently temporal data and, today, achieve impressive results using sequential encoder-decoder structures. Inspired by these sequence-to-sequence models, we adapt an encoder structure with convolutional recurrent layers in order to approximate a phenological model for vegetation classes based on a temporal sequence of Sentinel 2 (S2) images. In our experiments, we visualize internal activations over a sequence of cloudy and non-cloudy images and find several recurrent cells, which reduce the input activity for cloudy observations. Hence, we assume that our network has learned cloud-filtering schemes solely from input data, which could alleviate the need for tedious cloud-filtering as a preprocessing step for many EO approaches. Moreover, using unfiltered temporal series of top-of-atmosphere (TOA) reflectance data, we achieved in our experiments state-of-the-art classification accuracies on a large number of crop classes with minimal preprocessing compared to other classification approaches.

Assessment of Spatio-temporal Barren-lands Expansion and Agricultural Adaptation due to Climate Change and Anthropogenic Activity: A Geospatial Approach in Hot Semi-arid Region of Maharashtra State, India

NASA Astrophysics Data System (ADS)

Roy, A.; Inamdar, A. B.

2017-12-01

Major parts of Upper Godavari River Basin are intensely drought prone and climate vulnerable in Maharashtra State, India. The economy of the state depends on the agronomic productivity of this region. So, it is necessary to monitor and regulate the effects of climate change and anthropogenic activity on agricultural land in that region. This study investigates and maps the barren-lands and alteration of agricultural lands, their decadal deviations with the multi-temporal LANDSAT satellite images; and finally quantifies the agricultural adaptations. This work involves the utilization of remote sensing and GIS tools and modeling. First, climatic trend analysis is carried out with dataset obtained from India Meteorological Department. Then, multi-temporal LANDSAT images are classified (Level I, hybrid classification technique are followed) to determine the decadal Land Use Land Cover (LULC) changes and correlated with the agricultural water demand. Finally, various LANDSAT band analysis is conducted to determine irrigated and non-irrigated cropping area estimation and identifying the agricultural adaptations. The analysis of LANDSAT images shows that barren-lands are most increased class during the study period. The overall spatial extent of barren-lands are increased drastically during the study period. The geospatial study (class-to-class conversion study) shows that, most of the conversion of the barren-lands are from the agricultural land and reserve or open forests. The barren-lands are constantly increasing and the agricultural land is linearly decreasing. Hence, there is an inverse correlation between barren-lands and agricultural land. Moreover, there is a shift to non-irrigated and less water demanding crops, from more water demanding crops, which is a noticeable adaptation. The surface-water availability is highly dependent on rainfall and/or climatic conditions. It is changing either way in a random fashion based upon the quantity of rainfall occurred in near preceding years. The agricultural lands are densely replenished around the dams and natural water bodies which serve as the water supply stations for the irrigation purposes. Hence, the study shows there are alteration in LULC, agricultural practices and surface-water availability and expansion of barren-lands.

Quantifying the Influence of Urbanization on a Coastal Floodplain

NASA Astrophysics Data System (ADS)

Sebastian, A.; Juan, A.; Bedient, P. B.

2016-12-01

The U.S. Gulf Coast is the fastest growing region in the United States; between 1960 and 2010, the number of housing units along the Gulf of Mexico increased by 246%, vastly outpacing growth in other parts of the country (NOAA 2013). Numerous studies have shown that increases in impervious surface associated with urbanization reduce infiltration and increase surface runoff. While empirical evidence suggests that changes in land use are leading to increased flood damage in overland areas, earlier studies have largely focused on the impacts of urbanization on surface runoff and watershed hydrology, rather than quantifying its influence on the spatial extent of flooding. In this study, we conduct a longitudinal assessment of the evolution of flood risk since 1970 in an urbanizing coastal watershed. Utilizing the distributed hydrologic model, Vflo®, in combination with the hydraulic model, HEC-RAS, we quantify the impact of localized land use/land cover (LULC) change on the spatial extent of flooding in the watershed and the underlying flood hazard structure. The results demonstrate that increases in impervious cover between 1970 and 2010 (34%) and 2010 and 2040 (18%) increase the size of the floodplain by 26 and 17%, respectively. Furthermore, the results indicate that the depth and frequency of flooding in neighborhoods within the 1% floodplain have increased substantially (see attached figure). Finally, this analysis provides evidence that outdated FEMA floodplain maps could be underestimating the extent of the floodplain by upwards of 25%, depending on the rate of urbanization in the watershed; and, that by incorporating physics-based distributed hydrologic models into floodplain studies, floodplain maps can be easily updated to reflect the most recent LULC information available. The methods presented in this study have important implications for the development of mitigation strategies in coastal areas, such as deterring future development in flood prone areas and directing flood mitigation efforts in already flood prone communities. ReferencesNational Oceanic and Atmospheric Administration (NOAA). (2013). National Coastal Population Report: Population Trends from 1970 to 2020.

GIS and remote sensing techniques for the assessment of land use change impact on flood hydrology: the case study of Yialias basin in Cyprus

NASA Astrophysics Data System (ADS)

Alexakis, D. D.; Grillakis, M. G.; Koutroulis, A. G.; Agapiou, A.; Themistocleous, K.; Tsanis, I. K.; Michaelides, S.; Pashiardis, S.; Demetriou, C.; Aristeidou, K.; Retalis, A.; Tymvios, F.; Hadjimitsis, D. G.

2014-02-01

Floods are one of the most common natural disasters worldwide, leading to economic losses and loss of human lives. This paper highlights the hydrological effects of multi-temporal land use changes in flood hazard within the Yialias catchment area, located in central Cyprus. A calibrated hydrological model was firstly developed to describe the hydrological processes and internal basin dynamics of the three major subbasins, in order to study the diachronic effects of land use changes. For the implementation of the hydrological model, land use, soil and hydrometeorological data were incorporated. The climatic and stream flow data were derived from rain and flow gauge stations located in the wider area of the watershed basin. In addition, the land use and soil data were extracted after the application of object-oriented nearest neighbor algorithms of ASTER satellite images. Subsequently, the cellular automata (CA)-Markov chain analysis was implemented to predict the 2020 land use/land cover (LULC) map and incorporate it to the hydrological impact assessment. The results denoted the increase of runoff in the catchment area due to the recorded extensive urban sprawl phenomenon of the last decade.

Characterizing the fabric of the urban environment: A case study of Greater Houston, Texas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rose, Leanna Shea; Akbari, Hashem; Taha, Haider

2003-01-15

In this report, the materials and various surface types that comprise a city are referred to as the ''urban fabric.'' Urban fabric data are needed in order to estimate the impact of light-colored surfaces (roofs and pavements) and urban vegetation (trees, grass, shrubs) on the meteorology and air quality of a city, and to design effective urban environmental implementation programs. We discuss the results of a semi-automatic Monte-Carlo statistical approach used to develop data on surface-type distribution and city-fabric makeup (percentage of various surface-types) using aerial color orthophotography. The digital aerial photographs for Houston covered a total of about 52more » km2 (20 mi2). At 0.30-m resolution, there were approximately 5.8 x 108 pixels of data. Four major land-use types were examined: (1) commercial, (2) industrial, (3) educational, and (4) residential. On average, for the regions studied, vegetation covers about 39 percent of the area, roofs cover about 21 percent, and paved surfaces cover about 29 percent. For the most part, trees shade streets, parking lots, grass, and sidewalks. At ground level, i.e., view from below the vegetation canopies, paved surfaces cover about 32 percent of the study area. GLOBEIS model data from University of Texas and land-use/land-cover (LULC) information from the United States Geological Survey (USGS) were used to extrapolate these results from neighborhood scales to Greater Houston. It was found that in an area of roughly 3,430 km2, defining most of Greater Houston, over 56 percent is residential. The total roof area is about 740 km2, and the total paved surface area (roads, parking areas, sidewalks) covers about 1000 km2. Vegetation covers about 1,320 km2.« less

Characterizing the fabric of the urban environment: A case study of Salt Lake City, Utah

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akbari, Hashem; Rose, L. Shea

2001-02-28

Urban fabric data are needed in order to estimate the impact of light-colored surfaces (roofs and pavements) and urban vegetation (trees, grass, shrubs) on the meteorology and air quality of a city, and to design effective implementation programs. In this report, we discuss the result of a semi-automatic Monte-Carlo statistical approach used to develop data on surface-type distribution and city-fabric makeup (percentage of various surface-types) using aerial color orthophotography. The digital aerial photographs for Salt Lake City covered a total of about 34 km2 (13 mi2). At 0.50-m resolution, there were approximately 1.4 x 108 pixels of data. Four majormore » land-use types were examined: (1) commercial, (2) industrial, (3) educational, and (4) residential. On average, for the areas studied, vegetation covers about 46 percent of the area (ranging 44-51 percent), roofs cover about 21 percent (ranging 15-24 percent), and paved surfaces about 26 percent (ranging 21-28 percent). For the most part, trees shade streets, parking lots, grass, and sidewalks. In most non-residential areas, paved surfaces cover 46-66 percent of the area. In residential areas, on average, paved surfaces cover about 32 percent of the area. Land-use/land-cover (LU/LC) data from the United States Geological Survey were used to extrapolate these results from neighborhood scales to metropolitan Salt Lake City. In an area of roughly 560 km2, defining most of metropolitan Salt Lake City, over 60 percent is residential. The total roof area is about 110 km2, and the total paved surface area (roads, parking areas, sidewalks) covers about 170 km2. The total vegetated area covers about 230 km2.« less

Data on spatiotemporal urban sprawl of Dire Dawa City, Eastern Ethiopia.

PubMed

Taffa, Chaltu; Mekonen, Teferi; Mulugeta, Messay; Tesfaye, Bechaye

2017-06-01

The data presented in this paper shows the spatiotemporal expansion of Dire Dawa City (eastern Ethiopia) and the ensuing land use land cover changes in its peri-urban areas between 1985 and 2015. The data were generated from satellite images of Thematic Mapper (TM), Enhanced Thematic Mapper-Plus (ETM+) and OLI (Operational Land Image) with path/raw value of 166/053 by using Arc GIS 10.1 software. The precision of the images was verified by geolocation data collected from ground control points by using Geographic Positioning System (GPS) receiver. Four LULC classes (built up area, vegetation, barren land and farmland) with their respective spatiotemporal dimensions were clearly identified in the analysis. Built up area had shown an overall annual increment of 15.8% (82 ha per year) from 517 ha in 1985 to 2976 ha in 2015. Expansion took place in all directions but it was more pronounced along the main road towards other nearby towns, recently established business/service areas and the Industrial Park. Barren land, farmland and vegetation areas showed speedy decline over the years.

Synergetic Use of Crowdsourcing for Environmental Science Research, Applications and Education

NASA Astrophysics Data System (ADS)

Nair, U. S.; Thau, D.

2015-12-01

Environmental science research and applications often utilize information that is not readily available or routinely collected by government agencies. Whereas, the quality and quantity of environmental monitoring data is continually improving (e. g., spectral and spatial resolution of satellite imagery) contextual information needed to effectively utilize the data is sparse. Examples of such contextual information include ground truth data for land cover classification, presence/absence of species, prevalence of mosquito breeding sites and characteristics of urban land cover. Often, there are no agencies tasked with routine collection of such contextual information, which could be effectively collected through crowdsourcing. Crowdsourcing of such information, that is useful for environmental science research and applications, also provide opportunities for experiential learning at all levels of education. Appropriately designed crowdsourcing activity can be transform students from passive recipients of information to generators of knowledge. Multiple examples of synergistic use of crowdsourcing, developed by the Public Environmental Education and Research Apps (PEERA) group, at the University of Alabama in Huntsville will be presented. One example is crowdsourcing of land use and land cover (LULC) data using Open Data Kit (ODK) and associated analysis of satellite imagery using Google Earth Engine (GEE). Implementation of this activity as inquiry based learning exercise, for both middle school and for pre-service teachers will be discussed. Another example will detail the synergy between crowdsourcing for biodiversity mapping in southern India and environmental education. Other crowdsourcing activities that offer potential for synergy between research and public education will also be discussed.

Impacts of land use and land cover on surface and air temperature in urban landscapes

NASA Astrophysics Data System (ADS)

Crum, S.; Jenerette, D.

2015-12-01

Accelerating urbanization affects regional climate as the result of changing land cover and land use (LCLU). Urban land cover composition may provide valuable insight into relationships among urbanization, air, and land-surface temperature (Ta and LST, respectively). Climate may alter these relationships, where hotter climates experience larger LULC effects. To address these hypotheses we examined links between Ta, LST, LCLU, and vegetation across an urban coastal to desert climate gradient in southern California, USA. Using surface temperature radiometers, continuously measuring LST on standardized asphalt, concrete, and turf grass surfaces across the climate gradient, we found a 7.2°C and 4.6°C temperature decrease from asphalt to vegetated cover in the coast and desert, respectively. There is 131% more temporal variation in asphalt than turf grass surfaces, but 37% less temporal variation in concrete than turf grass. For concrete and turf grass surfaces, temporal variation in temperature increased from coast to desert. Using ground-based thermal imagery, measuring LST for 24 h sequences over citrus orchard and industrial use locations, we found a 14.5°C temperature decrease from industrial to orchard land use types (38.4°C and 23.9°C, respectively). Additionally, industrial land use types have 209% more spatial variation than orchard (CV=0.20 and 0.09, respectively). Using a network of 300 Ta (iButton) sensors mounted in city street trees throughout the region and hyperspectral imagery data we found urban vegetation greenness, measured using the normalized difference vegetation index (NDVI), was negatively correlated to Ta at night across the climate gradient. Contrasting previous findings, the closest coupling between NDVI and Ta is at the coast from 0000 h to 0800 h (highest r2 = 0.6, P < 0.05) while relationships at the desert are weaker (highest r2 = 0.38, P < 0.05). These findings indicate that vegetation cover in urbanized regions of southern California, USA decrease Ta and LST and spatial variation in LST, while built surfaces and land uses have the opposite effect. Furthermore these relationships are regulated by regional climate patterns, with decreases in Ta and LST being strongest in the coastal sub-region.

State-and-transition simulation models: a framework for forecasting landscape change

USGS Publications Warehouse

Daniel, Colin; Frid, Leonardo; Sleeter, Benjamin M.; Fortin, Marie-Josée

2016-01-01

SummaryA wide range of spatially explicit simulation models have been developed to forecast landscape dynamics, including models for projecting changes in both vegetation and land use. While these models have generally been developed as separate applications, each with a separate purpose and audience, they share many common features.We present a general framework, called a state-and-transition simulation model (STSM), which captures a number of these common features, accompanied by a software product, called ST-Sim, to build and run such models. The STSM method divides a landscape into a set of discrete spatial units and simulates the discrete state of each cell forward as a discrete-time-inhomogeneous stochastic process. The method differs from a spatially interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state variables, to specify one-step transition rates as either probabilities or target areas, and to represent multiple types of transitions between pairs of states.We demonstrate the STSM method using a model of land-use/land-cover (LULC) change for the state of Hawai'i, USA. Processes represented in this example include expansion/contraction of agricultural lands, urbanization, wildfire, shrub encroachment into grassland and harvest of tree plantations; the model also projects shifts in moisture zones due to climate change. Key model output includes projections of the future spatial and temporal distribution of LULC classes and moisture zones across the landscape over the next 50 years.State-and-transition simulation models can be applied to a wide range of landscapes, including questions of both land-use change and vegetation dynamics. Because the method is inherently stochastic, it is well suited for characterizing uncertainty in model projections. When combined with the ST-Sim software, STSMs offer a simple yet powerful means for developing a wide range of models of landscape dynamics.

From soilscapes to landscapes: A landscape-oriented approach to simulate soil organic carbon dynamics in intensively managed landscapes

NASA Astrophysics Data System (ADS)

Papanicolaou, A. N. (Thanos); Wacha, Kenneth M.; Abban, Benjamin K.; Wilson, Christopher G.; Hatfield, Jerry L.; Stanier, Charles O.; Filley, Timothy R.

2015-11-01

Most available biogeochemical models focus within a soil profile and cannot adequately resolve contributions of the lighter size fractions of organic rich soils for enrichment ratio (ER) estimates, thereby causing unintended errors in soil organic carbon (SOC) storage predictions. These models set ER as constant, usually equal to unity. The goal of this study is to provide spatiotemporal predictions of SOC stocks at the hillslope scale that account for the selective entrainment and deposition of lighter size fractions. It is hypothesized herein that ER values may vary depending on hillslope location, Land Use/Land Cover (LULC) conditions, and magnitude of the hydrologic event. An ER module interlinked with two established models, CENTURY and Watershed Erosion Prediction Project, is developed that considers the effects of changing runoff coefficients, bare soil coverage, tillage depth, fertilization, and soil roughness on SOC redistribution and storage. In this study, a representative hillslope is partitioned into two control volumes (CVs): a net erosional upslope zone and a net depositional downslope zone. We first estimate ER values for both CVs I and II for different hydrologic and LULC conditions. Second, using the improved ER estimates for the two CVs, we evaluate the effects that management practices have on SOC redistribution during different crop rotations. Overall, LULC promoting less runoff generally yielded higher ER values, which ranged between 0.97 and 3.25. Eroded soils in the upland CV were up to 4% more enriched in SOC than eroded soils in the downslope CV due to larger interrill contributions, which were found to be of equal importance to rill contributions. The chronosequence in SOC storage for the erosional zone revealed that conservation tillage and enhanced crop yields begun in the 1980s reversed the downward trend in SOC losses, causing nearly 26% of the lost SOC to be regained.

Assessing Land Management Changes and Population Dynamics in Central Burkina Faso in Response to Climate Change.

NASA Astrophysics Data System (ADS)

Kabore Bontogho, P. E.; Boubacar, I.; Afouda, A.; Joerg, H.

2015-12-01

Assessing landscape and population's dynamics at watershed level contribute to address anthropogenic aspect of climate change issue owing to the close link between LULC and climate changes. The objective of this study is to explore the dependencies of population to land management changes in Massili basin (2612 km²) located in central Burkina Faso. A set of three satellite scenes was acquired for the years 1990 (Landsat 7 ETM), 2002 (Landsat 7 ETM+) and 2013 (Landsat 8 OLI/TIRS) from the Global Land Cover Facility's (GLCF) website. Census data were provided by the National institute of statistics and demographic (INSD). The satellites images were classified using object-oriented classification method which was supported by historic maps and field data. Those were collected in order to allow for class definition, verification and accuracy assessments. Based on the developed land use maps, change analysis was carried out using post classification comparison in GIS. Finally, derived land use changes were compared with census data in order to explore links between population dynamics and the land use changes. It was found in 1990 that Massili watershed LULC was dominated by Tree/shrub savannah (69%, 1802.28 km2 ), Farm/Fallow was representing 22%, Gallery forest (4%), Settlement (3%), Barre soil (1%), Water bodies (1%). In 2002, the major landscape was Farm (54%). Tree/Shrub savannas were reduced to 36% while the Gallery Forest was decreased to1% of the basin area. The situation has also slightly changed in 2013 with an increase of the area devoted to farm/fallow and settlement at a rate of 3% and Gallery forest has increased to 4%. The changes in land use are in agreement with a notable increase in population. The analysis of census data showed that the number of inhabitants increased from 338 inhabitants per km2 in 1990 to 1150 inhabitants per km2 in 2013. As shown by statistical analysis (Kendall correlation tau=0.9), there is a close relation between both dynamics.

Integrating continuous stocks and flows into state-and-transition simulation models of landscape change

USGS Publications Warehouse

Daniel, Colin J.; Sleeter, Benjamin M.; Frid, Leonardo; Fortin, Marie-Josée

2018-01-01

State-and-transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land-use/land-cover (LULC) change. The STSM method divides a landscape into spatially-referenced cells and then simulates the state of each cell forward in time, as a discrete-time stochastic process using a Monte Carlo approach, in response to any number of possible transitions. A current limitation of the STSM method, however, is that all of the state variables must be discrete.Here we present a new approach for extending a STSM, in order to account for continuous state variables, called a state-and-transition simulation model with stocks and flows (STSM-SF). The STSM-SF method allows for any number of continuous stocks to be defined for every spatial cell in the STSM, along with a suite of continuous flows specifying the rates at which stock levels change over time. The change in the level of each stock is then simulated forward in time, for each spatial cell, as a discrete-time stochastic process. The method differs from the traditional systems dynamics approach to stock-flow modelling in that the stocks and flows can be spatially-explicit, and the flows can be expressed as a function of the STSM states and transitions.We demonstrate the STSM-SF method by integrating a spatially-explicit carbon (C) budget model with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, while the flows are the possible fluxes of C between these pools. Importantly, several of these C fluxes are triggered by corresponding LULC transitions in the STSM. Model outputs include changes in the spatial and temporal distribution of C pools and fluxes across the landscape in response to projected future changes in LULC over the next 50 years.The new STSM-SF method allows both discrete and continuous state variables to be integrated into a STSM, including interactions between them. With the addition of stocks and flows, STSMs provide a conceptually simple yet powerful approach for characterizing uncertainties in projections of a wide range of questions regarding landscape change.

Characterizing the fabric of the urban environment: A case studyof Metropolitan Chicago, Illinois and Executive Summary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akbari, Hashem; Rose, Leanna Shea

2001-10-30

Urban fabric data are needed in order to estimate the impactof light-colored surfaces (roofs and pavements) and urban vegetation(trees, grass, shrubs) on the meteorology and air quality of a city, andto design effective implementation programs. In this report, we discussthe result of a semi-automatic Monte-Carlo statistical approach used todevelop data on surface-type distribution and city-fabric makeup(percentage of various surface-types) using aerial colororthophotography. The digital aerial photographs for metropolitan Chicagocovered a total of about 36 km2 (14 mi2). At 0.3m resolution, there wereapproximately 3.9 x 108 pixels of data. Four major land-use types wereexamined: commercial, industrial, residential, andtransportation/communication. On average, formore » the areas studied, atground level vegetation covers about 29 percent of the area (ranging 4 80percent); roofs cover about 25 percent (ranging 8 41 percent), and pavedsurfaces about 33 percent (ranging 12 59 percent). For the most part,trees shade streets, parking lots, grass, and side-walks. In commercialareas, paved surfaces cover 50 60 percent of the area. In residentialareas, on average, paved surfaces cover about 27percent of the area.Land-use/land-cover (LULC) data from the United States Geological Surveywas used to extrapolate these results from neighborhood scales tometropolitan Chicago. In an area of roughly 2500 km2, defining most ofmetropolitan Chicago, over 53 percent is residential. The total roof areais about 680 km2, and the total paved surfaces (roads, parking areas,sidewalks) are about 880 km2. The total vegetated area is about 680km2.« less

Fusion of optical and SAR remote sensing images for tropical forests monitoring

NASA Astrophysics Data System (ADS)

Wang, C.; Yu, M.; Gao, Q.; Wang, X.

2016-12-01

Although tropical deforestation prevails in South America and Southeast Asia, reforestation appeared in some tropical regions due to economic changes. After the economic shift from agriculture to industry, the tropical island of Puerto Rico has experienced rapid reforestation as well as urban expansion since the late 1940s. Continued urban growth without the guide of sustainable planning might prevent further forest regrowth. Accurate and timely mapping of LULC is of great importance for evaluating the consequences of reforestation and urban expansion on the coupled human and nature systems. However, owning to persistent cloud cover in tropics, it remains a challenge to produce reliable LULC maps in fine spatial resolution. Here, we retrieved cloud-free Landsat surface reflectance composite data by removing clouds and shades from the USGS Landsat Surface Reflectance (SR) product for each scene using the CFmask and Fmask algorithms in Google Earth Engine. We then produced high accuracy land cover classification maps using SR optical data for the year of 2000 and fused optical and ALOS SAR data for 2010 and 2015, with an overall accuracy of 92.0%, 92.5%, and 91.6%, respectively. The classification result indicated that a successive forest gain of 6.52% and 1.03% occurred between the first (2000-2010) and second (2010-2015) study periods, respectively. We also conducted a comparative spatial analysis of patterns of deforestation and reforestation based on a series of forest cover zones (50 × 50 pixels, 150 ha). The annual rates of deforestation and reforestation against forest cover presented the similar trends during two periods: decreasing with the forest cover increasing. However, the annual net forest change rate was different in the zones with forest cover less than 30%, presenting significant gain (2.2-8.4% yr-1) for the first period and significant loss (2.3-6.4% yr-1) for the second period. It indicated that both deforestation and reforestation mostly occurred near the forest edges and low density secondary forests.

Dynamics of carbon, water and energy cycles in a heterogeneous landscape and a changing climate

NASA Astrophysics Data System (ADS)

Schmidt, A.; Law, B. E.; Still, C. J.; Hilker, T.

2016-12-01

The combined effects of changes in land-use and land cover (LULC) and climate on carbon and water cycling need to be assessed at regional scales. LULC changes over time have many drivers such as expanding urban areas, exploration of new agricultural areas due to overused natural resources of current agricultural areas (e.g. degraded soil), economical reasons, or policy changes that encourage the use of alternative energy resources. Our study assesses the effects of conversion of semi-arid sagebrush and agricultural crops to bioenergy production on carbon, water and energy cycling, and resulting heating or cooling effects. Our project focusses on Oregon, where agricultural crops, significant forest area, and urban expansion are coupled with a strong spatial climate gradient that allows us to examine influences on carbon sequestration by the terrestrial biosphere. Our inverse modeling results showed that the prior fluxes modelled with CLM4.5 underestimated NEE in the highly productive western Douglas fir forests by more than 50%. Based on the results of our Bayesian inversion, we optimized ecosystem fluxes and changed CLM model parameters accordingly. By integrating remote sensing LULC data, eddy covariance data from flux sites, tall tower CO2 observations, biomass estimates from field samples, and CLM4.5, we predict current and future statewide carbon sequestration with unprecedented accuracy. Using inventories and tower flux data, we determined the effect of conversion of hay and grass seed cropland (323,200 ha) to hybrid poplar and found the state NEP increased from 4 TgCO2 per year to 13 TgCO2 per year for that area. The last coal power plant in the state (Boardman) is in the process of switching from coal combustion to biofuel burning to meet the state's goal for the reduction of greenhouse gas emissions. Our results show that the 7816 tons of biomass per day to keep the 518 MW power plant running at base load would amount to 35,000 hectares of hybrid poplar per year under current climate conditions. The improved CLM4.5 model will be used to evaluate the impacts of this land use change on the net ecosystem carbon balance under future climate conditions.

Effects of Land Use Land Cover (LULC) and Climate on Simulation of Phosphorus loading in the Southeast United States Region

NASA Astrophysics Data System (ADS)

Jima, T. G.; Roberts, A.

2013-12-01

Quality of coastal and freshwater resources in the Southeastern United States is threatened due to Eutrophication as a result of excessive nutrients, and phosphorus is acknowledged as one of the major limiting nutrients. In areas with much non-point source (NPS) pollution, land use land cover and climate have been found to have significant impact on water quality. Landscape metrics applied in catchment and riparian stream based nutrient export models are known to significantly improve nutrient prediction. The regional SPARROW (Spatially Referenced Regression On Watershed attributes), which predicts Total Phosphorus has been developed by the Southeastern United States regions USGS, as part of the National Water Quality Assessment (NAWQA) program and the model accuracy was found to be 67%. However, landscape composition and configuration metrics which play a significant role in the source, transport and delivery of the nutrient have not been incorporated in the model. Including these matrices in the models parameterization will improve the models accuracy and improve decision making process for mitigating and managing NPS phosphorus in the region. The National Land Cover Data 2001 raster data will be used (since the base line is 2002) for the region (with 8321 watersheds ) with fragstats 4.1 and ArcGIS Desktop 10.1 for the analysis of landscape matrices, buffers and creating map layers. The result will be imported to the Southeast SPARROW model and will be analyzed. Resulting statistical significance and model accuracy will be assessed and predictions for those areas with no water quality monitoring station will be made.

Reduction of Topographic Effect for Curve Number Estimated from Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Zhang, Wen-Yan; Lin, Chao-Yuan

2016-04-01

The Soil Conservation Service Curve Number (SCS-CN) method is commonly used in hydrology to estimate direct runoff volume. The CN is the empirical parameter which corresponding to land use/land cover, hydrologic soil group and antecedent soil moisture condition. In large watersheds with complex topography, satellite remote sensing is the appropriate approach to acquire the land use change information. However, the topographic effect have been usually found in the remotely sensed imageries and resulted in land use classification. This research selected summer and winter scenes of Landsat-5 TM during 2008 to classified land use in Chen-You-Lan Watershed, Taiwan. The b-correction, the empirical topographic correction method, was applied to Landsat-5 TM data. Land use were categorized using K-mean classification into 4 groups i.e. forest, grassland, agriculture and river. Accuracy assessment of image classification was performed with national land use map. The results showed that after topographic correction, the overall accuracy of classification was increased from 68.0% to 74.5%. The average CN estimated from remotely sensed imagery decreased from 48.69 to 45.35 where the average CN estimated from national LULC map was 44.11. Therefore, the topographic correction method was recommended to normalize the topographic effect from the satellite remote sensing data before estimating the CN.

GIS Based Multi-Criteria Decision Analysis For Cement Plant Site Selection For Cuddalore District

NASA Astrophysics Data System (ADS)

Chhabra, A.

2015-12-01

India's cement industry is a vital part of its economy, providing employment to more than a million people. On the back of growing demands, due to increased construction and infrastructural activities cement market in India is expected to grow at a compound annual growth rate (CAGR) of 8.96 percent during the period 2014-2019. In this study, GIS-based spatial Multi Criteria Decision Analysis (MCDA) is used to determine the optimum and alternative sites to setup a cement plant. This technique contains a set of evaluation criteria which are quantifiable indicators of the extent to which decision objectives are realized. In intersection with available GIS (Geographical Information System) and local ancillary data, the outputs of image analysis serves as input for the multi-criteria decision making system. Moreover, the following steps were performed so as to represent the criteria in GIS layers, which underwent the GIS analysis in order to get several potential sites. Satellite imagery from LANDSAT 8 and ASTER DEM were used for the analysis. Cuddalore District in Tamil Nadu was selected as the study site as limestone mining is already being carried out in that region which meets the criteria of raw material for cement production. Several other criteria considered were land use land cover (LULC) classification (built-up area, river, forest cover, wet land, barren land, harvest land and agriculture land), slope, proximity to road, railway and drainage networks.

Meta-Analysis of Land Use / Land Cover Change Factors in the Conterminous US and Prediction of Potential Working Timberlands in the US South from FIA Inventory Plots and NLCD Cover Maps

NASA Astrophysics Data System (ADS)

Jeuck, James A.

This dissertation consists of research projects related to forest land use / land cover (LULC): (1) factors predicting LULC change and (2) methodology to predict particular forest use, or "potential working timberland" (PWT), from current forms of land data. The first project resulted in a published paper, a meta-analysis of 64 econometric models from 47 studies predicting forest land use changes. The response variables, representing some form of forest land change, were organized into four groups: forest conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified, from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratio estimates were developed based on (1) proportion of times independent variables successfully achieved statistical significance (p ≤0.10), and (2) proportion of times independent variables successfully met the original researchers'expectations. In F2D models, popular independent variables such as population, income, and urban proximity often achieved statistical significance. In F2A models, popular independent variables such as forest and agricultural rents and costs, governmental programs, and site quality often achieved statistical significance. In U2D models, successful independent variables included urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. F2NF models high success variables were found to be agricultural rents, site quality, population, and income. This meta-analysis provides insight into the general success of econometric independent variables for future forest use or cover change research. The second part of this dissertation developed a method for predicting area estimates and spatial distribution of PWT in the US South. This technique determined land use from USFS Forest Inventory and Analysis (FIA) and land cover from the National Land Cover Database (NLCD). Three dependent variable forms (DV Forms) were derived from the FIA data: DV Form 1, timberland, other; DV Form 2, short timberland, tall timberland, agriculture, other; and DV Form 3, short hardwood (HW) timberland, tall HW timberland, short softwood (SW) timberland, tall SW timberland, agriculture, other. The prediction accuracy of each DV Form was investigated using both random forest model and logistic regression model specifications and data optimization techniques. Model verification employing a "leave-group-out" Monte Carlo simulation determined the selection of a stratified version of the random forest model using one-year NLCD observations with an overall accuracy of 0.53-0.94. The lower accuracy side of the range was when predictions were made from an aggregated NLCD land cover class "grass_shrub". The selected model specification was run using 2011 NLCD and the other predictor variables to produce three levels of timberland prediction and probability maps for the US South. Spatial masks removed areas unlikely to be working forests (protected and urbanized lands) resulting in PWT maps. The area of the resulting maps compared well with USFS area estimates and masked PWT maps and had an 8-11% reduction of the USFS timberland estimate for the US South compared to the DV Form. Change analysis of the 2011 NLCD to PWT showed (1) the majority of the short timberland came from NLCD grass_shrub; (2) the majority of NLCD grass_shrub predicted into tall timberland, and (3) NLCD grass_shrub was more strongly associated with timberland in the Coastal Plain. Resulting map products provide practical analytical tools for those interested in studying the area and distribution of PWT in the US South.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Developing scenarios to assess future landslide risks: a model-based approach applied to mountainous regions

NASA Astrophysics Data System (ADS)

Vacquie, Laure; Houet, Thomas

2016-04-01

In the last century, European mountain landscapes have experienced significant transformations. Natural and anthropogenic changes, climate changes, touristic and industrial development, socio-economic interactions, and their implications in terms of LUCC (land use and land cover changes) have directly influenced the spatial organization and vulnerability of mountain landscapes. This study is conducted as part of the SAMCO project founded by the French National Science Agency (ANR). It aims at developing a methodological approach, combining various tools, modelling platforms and methods, to identify vulnerable regions to landslide hazards accounting for futures LUCC. It presents an integrated approach combining participative scenarios and a LULC changes simulation models to assess the combined effects of LUCC and climate change on landslide risks in the Cauterets valley (French Pyrenees Mountains) up to 2100. Through vulnerability and risk mapping, the objective is to gather information to support landscape planning and implement land use strategies with local stakeholders for risk management. Four contrasting scenarios are developed and exhibit contrasting trajectories of socio-economic development. Prospective scenarios are based on national and international socio-economic contexts relying on existing assessment reports. The methodological approach integrates knowledge from local stakeholders to refine each scenario during their construction and to reinforce their plausibility and relevance by accounting for local specificities, e.g. logging and pastoral activities, touristic development, urban planning, etc. A process-based model, the Forecasting Scenarios for Mountains (ForeSceM) model, developed on the Dinamica Ego modelling platform is used to spatially allocate futures LUCC for each prospective scenario. Concurrently, a spatial decision support tool, i.e. the SYLVACCESS model, is used to identify accessible areas for forestry in scenario projecting logging activities. The method results in the development of LULC maps providing insights into a range of alternative futures using a scope of socio-economic and environmental conditions. A landslides assessment model, the ALICE model is then used as a final tool to analyze the potential impacts of simulated LUCC on landslide risks and the consequences in terms of vulnerability, e.g. changes in disaster risk allocation or characterization, degree of perturbation. This assessment intends to provide insights onto the potential future development of the valley to help identify areas at stake and to guide decision makers to help the risk management. Preliminary results show strong differences of futures land use and land cover maps that have significant influence on landslides hazards.

Integrated approach for prioritizing watersheds for management: a study of lidder catchment of kashmir himalayas.

PubMed

Malik, Mohammad Imran; Bhat, M Sultan

2014-12-01

The Himalayan watersheds are susceptible to various forms of degradation due to their sensitive and fragile ecological disposition coupled with increasing anthropogenic disturbances. Owing to the paucity of appropriate technology and financial resources, the prioritization of watersheds has become an inevitable process for effective planning and management of natural resources. Lidder catchment constitutes a segment of the western Himalayas with an area of 1,159.38 km(2). The study is based on integrated analysis of remote sensing, geographic information system, field study, and socioeconomic data. Multicriteria evaluation of geophysical, land-use and land-cover (LULC) change, and socioeconomic indicators is carried out to prioritize watersheds for natural resource conservation and management. Knowledge-based weights and ranks are normalized, and weighted linear combination technique is adopted to determine final priority value. The watersheds are classified into four priority zones (very high priority, high priority, medium priority, and low priority) on the basis of quartiles of the priority value, thus indicating their ecological status in terms of degradation caused by anthropogenic disturbances. The correlation between priority ranks of individual indicators and integrated indicators is drawn. The results reveal that socioeconomic indicators are the most important drivers of LULC change and environmental degradation in the catchment. Moreover, the magnitude and intensity of anthropogenic impact is not uniform in different watersheds of Lidder catchment. Therefore, any conservation and management strategy must be formulated on the basis of watershed prioritization.

Integrated Approach for Prioritizing Watersheds for Management: A Study of Lidder Catchment of Kashmir Himalayas

NASA Astrophysics Data System (ADS)

Malik, Mohammad Imran; Bhat, M. Sultan

2014-12-01

The Himalayan watersheds are susceptible to various forms of degradation due to their sensitive and fragile ecological disposition coupled with increasing anthropogenic disturbances. Owing to the paucity of appropriate technology and financial resources, the prioritization of watersheds has become an inevitable process for effective planning and management of natural resources. Lidder catchment constitutes a segment of the western Himalayas with an area of 1,159.38 km2. The study is based on integrated analysis of remote sensing, geographic information system, field study, and socioeconomic data. Multicriteria evaluation of geophysical, land-use and land-cover (LULC) change, and socioeconomic indicators is carried out to prioritize watersheds for natural resource conservation and management. Knowledge-based weights and ranks are normalized, and weighted linear combination technique is adopted to determine final priority value. The watersheds are classified into four priority zones (very high priority, high priority, medium priority, and low priority) on the basis of quartiles of the priority value, thus indicating their ecological status in terms of degradation caused by anthropogenic disturbances. The correlation between priority ranks of individual indicators and integrated indicators is drawn. The results reveal that socioeconomic indicators are the most important drivers of LULC change and environmental degradation in the catchment. Moreover, the magnitude and intensity of anthropogenic impact is not uniform in different watersheds of Lidder catchment. Therefore, any conservation and management strategy must be formulated on the basis of watershed prioritization.

Handling Input and Output for COAMPS

NASA Technical Reports Server (NTRS)

Fitzpatrick, Patrick; Tran, Nam; Li, Yongzuo; Anantharaj, Valentine

2007-01-01

Two suites of software have been developed to handle the input and output of the Coupled Ocean Atmosphere Prediction System (COAMPS), which is a regional atmospheric model developed by the Navy for simulating and predicting weather. Typically, the initial and boundary conditions for COAMPS are provided by a flat-file representation of the Navy s global model. Additional algorithms are needed for running the COAMPS software using global models. One of the present suites satisfies this need for running COAMPS using the Global Forecast System (GFS) model of the National Oceanic and Atmospheric Administration. The first step in running COAMPS downloading of GFS data from an Internet file-transfer-protocol (FTP) server computer of the National Centers for Environmental Prediction (NCEP) is performed by one of the programs (SSC-00273) in this suite. The GFS data, which are in gridded binary (GRIB) format, are then changed to a COAMPS-compatible format by another program in the suite (SSC-00278). Once a forecast is complete, still another program in the suite (SSC-00274) sends the output data to a different server computer. The second suite of software (SSC- 00275) addresses the need to ingest up-to-date land-use-and-land-cover (LULC) data into COAMPS for use in specifying typical climatological values of such surface parameters as albedo, aerodynamic roughness, and ground wetness. This suite includes (1) a program to process LULC data derived from observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Terra and Aqua satellites, (2) programs to derive new climatological parameters for the 17-land-use-category MODIS data; and (3) a modified version of a FORTRAN subroutine to be used by COAMPS. The MODIS data files are processed to reformat them into a compressed American Standard Code for Information Interchange (ASCII) format used by COAMPS for efficient processing.

Assessing and monitoring the risk of land degradation in Baragan Plain, Romania, using spectral mixture analysis and Landsat imagery.

PubMed

Vorovencii, Iosif

2016-07-01

The fall of the communist regime in Romania at the end of 1989 and the ensuing transition to the market economy brought about many changes in the use of agricultural land. These changes combined with the action of climatic factors led, in most cases, to negative effects increasing the risk of degradation of agricultural land. This study aims to assess and monitor the risk of land degradation in Baragan Plain, Romania, for the period 1988-2011 using Landsat Thematic Mapper (TM) and Spectral Mixture Analysis (SMA). Each satellite image was classified through the Decision Tree Classifier (DTC) method; then, on the basis of certain threshold values, we obtained maps of land degradation and maps showing the passage from various classes of land use/land cover (LULC) to land degradation. The results indicate that during the intermediary periods there was an ascending and descending trend in the risk of land degradation determined by the interaction of climatic factors with the social-economic ones. For the entire period, the overall trend was ascending, the risk of land degradation increasing by around 4.60 % of the studied surface. Out of the climatic factors, high temperatures and, implicitly, drought were the most significant. The social-economic factors are the result of the changes which occurred after the fall of the communist regime, the most important being the fragmentation of agricultural land and the destruction of the irrigation system.

Remote Sensing and GIS for Landuse/Landcover Classification and Water Quality in the Northern Ireland

NASA Astrophysics Data System (ADS)

Amer, R.; Ofterdinger, U.; Ruffell, A.; Donald, A.

2012-04-01

This study presents landuse/landcover (LULC) classifications of Northern Ireland in order to quantify land-use types driving chemical loading in the surface water bodies. The major LULC classes are agricultural land, bare land (mountainous areas), forest, urban areas, and water bodies. Three ENVISAT ASAR multi-look precision images acquired in 2011 and two Enhanced Thematic Mapper Plus (ETM+) acquired in 2003 were used for classification. The ASAR digital numbers were converted to backscattering coefficient (sigma nought) and enhanced using adaptive Gamma filter and Gaussian stretch. Supervised classifications of Maximum Likelihood, Mahalanobils Distance, Minimum Distance, Spectral Angel Mapper, Parallelepiped, and Winner Tercat were applied on ETM+ and ASAR images. A confusion matrix was used to evaluate the classification accuracy; the best results of ETM+ and ASAR were given by the winner classification (82.9 and 73.6 %), and maximum likelihood (81.7 and 72.5 %), respectively. Change detection was applied to identify the areas of significant changes in landuse/landcover over the last eight years. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model was processed to extract the drainage systems and watersheds. Water quality data of the first and second order streams were extracted from 2005 survey by Geological Survey of Northern Ireland. GIS spatially distributed modelling generated maps showing the distribution of phosphorus (P), nitrate (NO3), dissolved organic carbon (DOC), and some of the trace elements including fluoride (F), calcium (Ca), aluminium (Al), iron (Fe), copper (Cu), lead (Pb), zinc (Zn), and arsenic (As) across the watersheds of the Northern Ireland were generated. The distribution of these elements was evaluated against the LULC classes and bed rock geology. Concentration of these elements was classified into normal (safe level), moderate, high, and very high based on the World Health Organization (WHO, 2011) water quality standards. The results show that P concentration is generally high across all the watersheds. NO3 is within normal range in all watersheds. DOC is within normal range in urban areas, moderate to high in agricultural lands, and high in the forest areas and bare lands. F and Fe are within safe level in all watersheds. Al, Cu, and As are high in all watersheds around the bare land LULC class which are underlain by psammite and semipelite metamorphic rocks. Ca is within normal range in most of watersheds but it is high in the south western part of the study area because of the presence of limestone bedrock. Pb and Zn are within normal range in the urban and most of the agricultural land, and high in the mountainous areas underlain by psammite and semipelite metamorphic bed rock.

Response of evapotranspiration to changes in land use and land cover and climate in China during 2001-2013.

PubMed

Li, Gen; Zhang, Fangmin; Jing, Yuanshu; Liu, Yibo; Sun, Ge

2017-10-15

Land surface evapotranspiration (ET) is a central component of the Earth's global energy balance and water cycle. Understanding ET is important in quantifying the impacts of human influences on the hydrological cycle and thus helps improving water use efficiency and strengthening water use planning and watershed management. China has experienced tremendous land use and land cover changes (LUCC) as a result of urbanization and ecological restoration under a broad background of climate change. This study used MODIS data products to analyze how LUCC and climate change affected ET in China in the period 2001-2013. We examined the separate contribution to the estimated ET changes by combining LUCC and climate data. Results showed that the average annual ET in China decreased at a rate of -0.6mm/yr from 2001 to 2013. Areas in which ET decreased significantly were mainly distributed in the northwest China, the central of southwest China, and most regions of south central and east China. The trends of four climatic factors including air temperature, wind speed, sunshine duration, and relative humidity were determined, while the contributions of these four factors to ET were quantified by combining the ET and climate datasets. Among the four climatic factors, sunshine duration and wind speed had the greatest influence on ET. LUCC data from 2001 to 2013 showed that forests, grasslands and croplands in China mutually replaced each other. The reduction of forests had much greater effects on ET than change by other land cover types. Finally, through quantitative separation of the distinct effects of climate change and LUCC on ET, we conclude that climate change was the more significant than LULC change in influencing ET in China during the period 2001-2013. Effective water resource management and vegetation-based ecological restoration efforts in China must consider the effects of climate change on ET and water availability. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterizing Satellite Rainfall Errors based on Land Use and Land Cover and Tracing Error Source in Hydrologic Model Simulation

NASA Astrophysics Data System (ADS)

Gebregiorgis, A. S.; Peters-Lidard, C. D.; Tian, Y.; Hossain, F.

2011-12-01

Hydrologic modeling has benefited from operational production of high resolution satellite rainfall products. The global coverage, near-real time availability, spatial and temporal sampling resolutions have advanced the application of physically based semi-distributed and distributed hydrologic models for wide range of environmental decision making processes. Despite these successes, the existence of uncertainties due to indirect way of satellite rainfall estimates and hydrologic models themselves remain a challenge in making meaningful and more evocative predictions. This study comprises breaking down of total satellite rainfall error into three independent components (hit bias, missed precipitation and false alarm), characterizing them as function of land use and land cover (LULC), and tracing back the source of simulated soil moisture and runoff error in physically based distributed hydrologic model. Here, we asked "on what way the three independent total bias components, hit bias, missed, and false precipitation, affect the estimation of soil moisture and runoff in physically based hydrologic models?" To understand the clear picture of the outlined question above, we implemented a systematic approach by characterizing and decomposing the total satellite rainfall error as a function of land use and land cover in Mississippi basin. This will help us to understand the major source of soil moisture and runoff errors in hydrologic model simulation and trace back the information to algorithm development and sensor type which ultimately helps to improve algorithms better and will improve application and data assimilation in future for GPM. For forest and woodland and human land use system, the soil moisture was mainly dictated by the total bias for 3B42-RT, CMORPH, and PERSIANN products. On the other side, runoff error was largely dominated by hit bias than the total bias. This difference occurred due to the presence of missed precipitation which is a major contributor to the total bias both during the summer and winter seasons. Missed precipitation, most likely light rain and rain over snow cover, has significant effect on soil moisture and are less capable of producing runoff that results runoff dependency on the hit bias only.

Pairing Coral Geochemical Analyses with an Ecosystem Services Model to Assess Drivers and Impacts of Sediment Delivery within Micronesia's Largest Estuary, Ngeremeduu Bay

NASA Astrophysics Data System (ADS)

Lewis, S.; Dunbar, R. B.; Mucciarone, D.; Barkdull, M.

2017-12-01

Scientific tools assessing impacts to watershed and coastal ecosystem services, like those from land-use land conversion (LULC), are critical for sustainable land management strategies. Small island nations are particularly vulnerable to LULC threats, especially sediment delivery, given their small spatial size and reliance on natural resources. In the Republic of Palau, a small Pacific island country, three major land-use activities—construction, fires, and agriculture— have increased sediment delivery to important estuarine and coastal habitats (i.e., rivers, mangroves, coral reefs) over the past 30 years. This project examines the predictive capacity of an ecosystem services model, Natural Capital Project's InVEST, for sediment delivery using historic land-use and coral geochemical analysis. These refined model projections are used to assess ecosystem services tradeoffs under different future land development and management scenarios. Coral cores (20-41cm in length) were sampled along a high-to-low sedimentation gradient (i.e., near major rivers (high-impact) and ocean (low-impact)) in Micronesia's largest estuary, Ngeremeduu Bay. Isotopic indicators of seasonality (δ18O and δ13C values (% VPDB)) were used to construct the age model for each core. Barium, Manganese, and Yttrium were used as trace metal proxies for sedimentation and measured in each core using a laser ablation ICP-MS. Finally, the Natural Capital Project's InVEST sediment delivery model was paired with Geospatial data to examine the drivers of sediment delivery (i.e., construction, farms and fires) within these two watersheds. A thirty-year record of trace metal to calcium ratios in coral skeletons show a peak in sedimentation during 2006 and 2007, and in 2012. These results suggest historic peaks in sediment delivery correlating to large-scale road construction and support previous findings that Ngeremeduu Bay has reached a tipping point of retaining sediment. Natural Capital's project InVEST sediment delivery model results suggest fires increases sediment exportation by an order of magnitude compared with the other major land-use activities. A refined measure of LULC from a novel database (earth-moving permits) will be used to develop a more accurate depiction of sediment delivery to estuarine and coastal habitats.

Practical approaches for assessing local land use change and conservation priorities in the tropics

NASA Astrophysics Data System (ADS)

Rivas, Cassandra J.

Tropical areas typically support high biological diversity; however, many are experiencing rapid land-use change. The resulting loss, fragmentation, and degradation of habitats place biodiversity at risk. For these reasons, the tropics are frequently identified as global conservation hotspots. Safeguarding tropical biodiversity necessitates successful and efficient conservation planning and implementation at local scales, where land use decisions are made and enforced. Yet, despite considerable agreement on the need for improved practices, planning may be difficult due to limited resources, such as funding, data, and expertise, especially for small conservation organizations in tropical developing countries. My thesis aims to assist small, non-governmental organizations (NGOs), operating in tropical developing countries, in overcoming resource limitations by providing recommendations for improved conservation planning. Following a brief introduction in Chapter 1, I present a literature review of systematic conservation planning (SCP) projects in the developing tropics. Although SCP is considered an efficient, effective approach, it requires substantial data and expertise to conduct the analysis and may present challenges for implementation. I reviewed and synthesized the methods and results of 14 case studies to identify practical ways to implement and overcome limitations for employing SCP. I found that SCP studies in the peer-reviewed literature were primarily implemented by researchers in large organizations or institutions, as opposed to on-the-ground conservation planners. A variety of data types were used in the SCP analyses, many of which data are freely available. Few case studies involved stakeholders and intended to implement the assessment; instead, the case studies were carried out in the context of research and development, limiting local involvement and implementation. Nonetheless, the studies provided valuable strategies for employing each step of the SCP assessment and ways to overcome limitations. These included obtaining and using publicly available data resources, collaborating with institutions or organizations with resources, and using expertise to employ the analytical process. In conclusion, the local conservation organization should ultimately decide whether or not to use the SCP approach using reviews such as this one and the feasibility assessment model provided in this chapter. In Chapter 3, to support locally based conservation planning efforts in southwestern Nicaragua, I collaborated with a small NGO and produced valuable data products for conservation planning. I produced a land-use and land cover change (LULC) classification and identified hot and cold spots (i.e., high and low concentration) of land cover change between the years of 2000 - 2009. I used SPOT satellite imagery from 2009, ground referenced data, and manual training points to classify 10 LULC types using a regression tree algorithm. I employed a post-classification change detection analysis to compare my classification to one from the year of 2000, applied a cluster analysis to delineate hot and cold spots of change, and used the resulting data products to identify preliminary conservation and restoration priorities. The LULC classification accuracy was 87.9% and deforestation rates were approximately 5.6% per year. I observed that pasture was the most converted-to class, plantation was a proliferating class, and some regrowth succeeded into secondary forest. Hotspots and cold spots of change for conservation concern included areas converted from forest into pasture, which often occurred in areas of rugged terrain. Hotspots from forest to plantation occurred in the northern isthmus, while cold spots occurred in the south. These two trends revealed the vulnerability of remaining secondary forests, which are of primary importance to regional conservation efforts. Conservation priorities included remaining old secondary forest patches and succeeding forests occurring near them and should factor into future conservation planning.

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands

PubMed Central

Miller, Brian W.; Breckheimer, Ian; McCleary, Amy L.; Guzmán-Ramirez, Liza; Caplow, Susan C.; Jones-Smith, Jessica C.; Walsh, Stephen J.

2010-01-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands – tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps. PMID:20539752

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands.

PubMed

Miller, Brian W; Breckheimer, Ian; McCleary, Amy L; Guzmán-Ramirez, Liza; Caplow, Susan C; Jones-Smith, Jessica C; Walsh, Stephen J

2010-05-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands - tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps.

Global synthesis of groundwater recharge in semiarid and arid regions

NASA Astrophysics Data System (ADS)

Scanlon, Bridget R.; Keese, Kelley E.; Flint, Alan L.; Flint, Lorraine E.; Gaye, Cheikh B.; Edmunds, W. Michael; Simmers, Ian

2006-10-01

Global synthesis of the findings from 140 recharge study areas in semiarid and arid regions provides important information on recharge rates, controls, and processes, which are critical for sustainable water development. Water resource evaluation, dryland salinity assessment (Australia), and radioactive waste disposal (US) are among the primary goals of many of these recharge studies. The chloride mass balance (CMB) technique is widely used to estimate recharge. Average recharge rates estimated over large areas (40-374 000 km2) range from 0.2 to 35 mm year-1, representing 0.1-5% of long-term average annual precipitation. Extreme local variability in recharge, with rates up to 720 m year-1, results from focussed recharge beneath ephemeral streams and lakes and preferential flow mostly in fractured systems. System response to climate variability and land use/land cover (LU/LC) changes is archived in unsaturated zone tracer profiles and in groundwater level fluctuations. Inter-annual climate variability related to El Niño Southern Oscillation (ENSO) results in up to three times higher recharge in regions within the SW US during periods of frequent El Niños (1977-1998) relative to periods dominated by La Niñas (1941-1957). Enhanced recharge related to ENSO is also documented in Argentina. Climate variability at decadal to century scales recorded in chloride profiles in Africa results in recharge rates of 30 mm year-1 during the Sahel drought (1970-1986) to 150 mm year-1 during non-drought periods. Variations in climate at millennial scales in the SW US changed systems from recharge during the Pleistocene glacial period (10 000 years ago) to discharge during the Holocene semiarid period. LU/LC changes such as deforestation in Australia increased recharge up to about 2 orders of magnitude. Changes from natural grassland and shrublands to dryland (rain-fed) agriculture altered systems from discharge (evapotranspiration, ET) to recharge in the SW US. The impact of LU change was much greater than climate variability in Niger (Africa), where replacement of savanna by crops increased recharge by about an order of magnitude even during severe droughts. Sensitivity of recharge to LU/LC changes suggests that recharge may be controlled through management of LU. In irrigated areas, recharge varies from 10 to 485 mm year-1, representing 1-25% of irrigation plus precipitation. However, irrigation pumpage in groundwater-fed irrigated areas greatly exceeds recharge rates, resulting in groundwater mining. Increased recharge related to cultivation has mobilized salts that accumulated in the unsaturated zone over millennia, resulting in widespread groundwater and surface water contamination, particularly in Australia. The synthesis of recharge rates provided in this study contains valuable information for developing sustainable groundwater resource programmes within the context of climate variability and LU/LC change.

Impact of Flooding on Land Use/ Land Cover Transformation in Wular Lake and its Environs, Kashmir Valley, India Using Geoinformatics

NASA Astrophysics Data System (ADS)

Ahmad, T.; Pandey, A. C.; Kumar, A.

2017-11-01

Wular lake, located at an elevation of 1520 m above sea level in Kashmir valley, India. In the present study, the immediate and long term impact of flood (2014) over the Wular lake environs was analyzed by using satellite images and employing supervised classification technique in GIS environment. The LULC classification was performed on the images of 25th August 2014 (pre flood) and 13th September 2015 (post flood) and was compared, which indicated marked decrease in terrestrial vegetation (23.7 %), agriculture (43.7 %) and water bodies (39.9 %). Overlaying analysis was performed with pre and post flood classified images with reference to the satellite image of 10th September 2014(during flood) which indicated total area inundated during flood was 88.77 km2. With the pre-flood situation, the aquatic vegetation of 34.06 km2, 13.89 km2 of agriculture land and terrestrial vegetation of 3.13 km2 was inundated. In the post flood situation, it was also came into focus that more than the half of the area under water bodies was converted into sand deposits (22.76 km2) due to anomalous increase in siltation. The overlay analysis on post flood classified image indicated that aquatic vegetation followed by agriculture and sand deposits lie within the flood inundated area. Further spatial analysis was performed within the flood inundated area (88.77 km2) with pre and post classified image to understand the situation before and after the flood and to calculate the changes. These land use-land cover transformations signifies the ill effect of flooding on the biodiversity of Wular Lake.

Dynamic analysis and ecological evaluation of urban heat islands in Raipur city, India

NASA Astrophysics Data System (ADS)

Guha, Subhanil; Govil, Himanshu; Mukherjee, Sandip

2017-07-01

Spatial-temporal distribution of the urban heat islands (UHI) and their changes over Raipur city have been analyzed using multitemporal Landsat satellite data from 1995 to 2016. Land surface temperature (LST) was retrieved through a mono-window algorithm. Some selected land use/land cover (LU-LC) indices were analyzed with LST using linear regression. The urban thermal field variance index (UTFVI) was applied to measure the thermal comfort level of the city. Results show that during the observed period, the study area experienced a gradual increasing rate in mean LST (>1% per annum). The UHI developed especially along the north-western industrial area and south-eastern bare land of the city. A difference in mean LST between UHI and non-UHI for different time periods (2.6°C in 1995, 2.85°C in 2006, 3.42°C in 2009, and 3.63°C in 2016) reflects the continuous warming status of the city. The LST map also shows the existence of a few urban hot spots near the industrial areas, metal roofs, and high density transport parking lots, which are more abundant in the north-western part of the city. The UTFVI map associated with UHI indicates that the inner parts of the city are ecologically more comfortable than the outer peripheries.

Assessment of the intensity and spatial variability of urban heat islands over the Indian cities for Regional Climate Analysis

NASA Astrophysics Data System (ADS)

Sultana, S.; Satyanarayana, A. N. V.

2016-12-01

The Urban heat island (UHI) in general developed over cities, due to the drastic changes in land use and land cover (LULC), has profound impact on the atmospheric circulation patterns due to the changes in the energy transport mechanism which in turn affect the regional climate. In this study, an attempt has been made to quantify the intensity of UHI, and to identify the pockets of UHI over cities during last decade over fast developing cosmopolitan Indian cities such as New Delhi, Mumbai and Kolkata. For this purpose, Landsat TM and ETM+ images during winter period, in about 5 year intervals from 2002 to 2013, has been selected to retrieve the brightness temperatures and land use/cover, from which Land Surface Temperature (LST) has been estimated using Normalized Difference Vegetation Index (NDVI). Normalized Difference Build-up Index (NDBI) and Normalized Difference Bareness Index (NDBaI) are estimated to extract build-up areas and bare land from the satellite images to identify the UHI pockets over the study area. For this purpose image processing and GIS tools were employed. Results reveal a significant increase in the intensity of UHI and increase in its area of influence over all the three cities. An increase of 2 to 2.5 oC of UHI intensity over the study regions has been noticed. The range of increase in UHI intensity is found to be more over New Delhi compared to Mumbai and Kolkata which is more or less same. The number of hotspot pockets of UHI has also been increased as seen from the spatial distribution of LST, NDVI and NDBI. This result signifies the impact of rapid urbanization and infrastructural developments has a direct consequence in modulating the regional climate over the Indian cities.

Toward a 30m resolution time series of historical global urban expansion: exploring variation in North American cities

NASA Astrophysics Data System (ADS)

Stuhlmacher, M.; Wang, C.; Georgescu, M.; Tellman, B.; Balling, R.; Clinton, N. E.; Collins, L.; Goldblatt, R.; Hanson, G.

2016-12-01

Global representations of modern day urban land use and land cover (LULC) extent are becoming increasingly prevalent. Yet considerable uncertainties in the representation of built environment extent (i.e. global classifications generated from 250m resolution MODIS imagery or the United States' National Land Cover Database) remain because of the lack of a systematic, globally consistent methodological approach. We aim to increase resolution, accuracy, and improve upon past efforts by establishing a data-driven definition of the urban landscape, based on Landsat 5, 7 & 8 imagery and ancillary data sets. Continuous and discrete machine learning classification algorithms have been developed in Google Earth Engine (GEE), a powerful online cloud-based geospatial storage and parallel-computing platform. Additionally, thousands of ground truth points have been selected from high resolution imagery to fill in the previous lack of accurate data to be used for training and validation. We will present preliminary classification and accuracy assessments for select cities in the United States and Mexico. Our approach has direct implications for development of projected urban growth that is grounded on realistic identification of urbanizing hot-spots, with consequences for local to regional scale climate change, energy demand, water stress, human health, urban-ecological interactions, and efforts used to prioritize adaptation and mitigation strategies to offset large-scale climate change. Future work to apply the built-up detection algorithm globally and yearly is underway in a partnership between GEE, University of California in San Diego, and Arizona State University.

Effectiveness of SWAT in characterizing the watershed hydrology in the snowy-mountainous Lower Bear Malad River (LBMR) watershed in Box Elder County, Utah

NASA Astrophysics Data System (ADS)

Salha, A. A.; Stevens, D. K.

2015-12-01

Distributed watershed models are essential for quantifying sediment and nutrient loads that originate from point and nonpoint sources. Such models are primary means towards generating pollutant estimates in ungaged watersheds and respond well at watershed scales by capturing the variability in soils, climatic conditions, land uses/covers and management conditions over extended periods of time. This effort evaluates the performance of the Soil and Water Assessment Tool (SWAT) model as a watershed level tool to investigate, manage, and characterize the transport and fate of nutrients in Lower Bear Malad River (LBMR) watershed (Subbasin HUC 16010204) in Utah. Water quality concerns have been documented and are primarily attributed to high phosphorus and total suspended sediment concentrations caused by agricultural and farming practices along with identified point sources (WWTPs). Input data such as Digital Elevation Model (DEM), land use/Land cover (LULC), soils, and climate data for 10 years (2000-2010) is utilized to quantify the LBMR streamflow. Such modeling is useful in developing the required water quality regulations such as Total Maximum Daily Loads (TMDL). Measured concentrations of nutrients were closely captured by simulated monthly nutrient concentrations based on the R2 and Nash- Sutcliffe fitness criteria. The model is expected to be able to identify contaminant non-point sources, identify areas of high pollution risk, locate optimal monitoring sites, and evaluate best management practices to cost-effectively reduce pollution and improve water quality as required by the LBMR watershed's TMDL.

Analysing Relationships Between Urban Land Use Fragmentation Metrics and Socio-Economic Variables

NASA Astrophysics Data System (ADS)

Sapena, M.; Ruiz, L. A.; Goerlich, F. J.

2016-06-01

Analysing urban regions is essential for their correct monitoring and planning. This is mainly accounted for the sharp increase of people living in urban areas, and consequently, the need to manage them. At the same time there has been a rise in the use of spatial and statistical datasets, such as the Urban Atlas, which offers high-resolution urban land use maps obtained from satellite imagery, and the Urban Audit, which provides statistics of European cities and their surroundings. In this study, we analyse the relations between urban fragmentation metrics derived from Land Use and Land Cover (LULC) data from the Urban Atlas dataset, and socio-economic data from the Urban Audit for the reference years 2006 and 2012. We conducted the analysis on a sample of sixty-eight Functional Urban Areas (FUAs). One-date and two-date based fragmentation indices were computed for each FUA, land use class and date. Correlation tests and principal component analysis were then applied to select the most representative indices. Finally, multiple regression models were tested to explore the prediction of socio-economic variables, using different combinations of land use metrics as explanatory variables, both at a given date and in a dynamic context. The outcomes show that demography, living conditions, labour, and transportation variables have a clear relation with the morphology of the FUAs. This methodology allows us to compare European FUAs in terms of the spatial distribution of the land use classes, their complexity, and their structural changes, as well as to preview and model different growth patterns and socio-economic indicators.

Assessment of NASA's Physiographic and Meteorological Datasets as Input to HSPF and SWAT Hydrological Models

NASA Technical Reports Server (NTRS)

Alacron, Vladimir J.; Nigro, Joseph D.; McAnally, William H.; OHara, Charles G.; Engman, Edwin Ted; Toll, David

2011-01-01

This paper documents the use of simulated Moderate Resolution Imaging Spectroradiometer land use/land cover (MODIS-LULC), NASA-LIS generated precipitation and evapo-transpiration (ET), and Shuttle Radar Topography Mission (SRTM) datasets (in conjunction with standard land use, topographical and meteorological datasets) as input to hydrological models routinely used by the watershed hydrology modeling community. The study is focused in coastal watersheds in the Mississippi Gulf Coast although one of the test cases focuses in an inland watershed located in northeastern State of Mississippi, USA. The decision support tools (DSTs) into which the NASA datasets were assimilated were the Soil Water & Assessment Tool (SWAT) and the Hydrological Simulation Program FORTRAN (HSPF). These DSTs are endorsed by several US government agencies (EPA, FEMA, USGS) for water resources management strategies. These models use physiographic and meteorological data extensively. Precipitation gages and USGS gage stations in the region were used to calibrate several HSPF and SWAT model applications. Land use and topographical datasets were swapped to assess model output sensitivities. NASA-LIS meteorological data were introduced in the calibrated model applications for simulation of watershed hydrology for a time period in which no weather data were available (1997-2006). The performance of the NASA datasets in the context of hydrological modeling was assessed through comparison of measured and model-simulated hydrographs. Overall, NASA datasets were as useful as standard land use, topographical , and meteorological datasets. Moreover, NASA datasets were used for performing analyses that the standard datasets could not made possible, e.g., introduction of land use dynamics into hydrological simulations

Projecting the impact of regional land-use change and water management policies on lake water quality: an application to periurban lakes and reservoirs.

PubMed

Catherine, Arnaud; Mouillot, David; Maloufi, Selma; Troussellier, Marc; Bernard, Cécile

2013-01-01

As the human population grows, the demand for living space and supplies of resources also increases, which may induce rapid change in land-use/land-cover (LULC) and associated pressures exerted on aquatic habitats. We propose a new approach to forecast the impact of regional land cover change and water management policies (i.e., targets in nutrient loads reduction) on lake and reservoir water eutrophication status using a model that requires minimal parameterisation compared with alternative methods. This approach was applied to a set of 48 periurban lakes located in the Ile de France region (IDF, France) to simulate catchment-scale management scenarios. Model outputs were subsequently compared to governmental agencies' 2030 forecasts. Our model indicated that the efforts made to reduce pressure in the catchment of seepage lakes might be expected to be proportional to the gain that might be obtained, whereas drainage lakes will display little improvement until a critical level of pressure reduction is reached. The model also indicated that remediation measures, as currently planned by governmental agencies, might only have a marginal impact on improving the eutrophication status of lakes and reservoirs within the IDF region. Despite the commitment to appropriately managing the water resources in many countries, prospective tools to evaluate the potential impacts of global change on freshwater ecosystems integrity at medium to large spatial scales are lacking. This study proposes a new approach to investigate the impact of region-scale human-driven changes on lake and reservoir ecological status and could be implemented elsewhere with limited parameterisation. Issues are discussed that relate to model uncertainty and to its relevance as a tool applied to decision-making.

Projecting the Impact of Regional Land-Use Change and Water Management Policies on Lake Water Quality: An Application to Periurban Lakes and Reservoirs

PubMed Central

Catherine, Arnaud; Mouillot, David; Maloufi, Selma; Troussellier, Marc; Bernard, Cécile

2013-01-01

As the human population grows, the demand for living space and supplies of resources also increases, which may induce rapid change in land-use/land-cover (LULC) and associated pressures exerted on aquatic habitats. We propose a new approach to forecast the impact of regional land cover change and water management policies (i.e., targets in nutrient loads reduction) on lake and reservoir water eutrophication status using a model that requires minimal parameterisation compared with alternative methods. This approach was applied to a set of 48 periurban lakes located in the Ile de France region (IDF, France) to simulate catchment-scale management scenarios. Model outputs were subsequently compared to governmental agencies’ 2030 forecasts. Our model indicated that the efforts made to reduce pressure in the catchment of seepage lakes might be expected to be proportional to the gain that might be obtained, whereas drainage lakes will display little improvement until a critical level of pressure reduction is reached. The model also indicated that remediation measures, as currently planned by governmental agencies, might only have a marginal impact on improving the eutrophication status of lakes and reservoirs within the IDF region. Despite the commitment to appropriately managing the water resources in many countries, prospective tools to evaluate the potential impacts of global change on freshwater ecosystems integrity at medium to large spatial scales are lacking. This study proposes a new approach to investigate the impact of region-scale human-driven changes on lake and reservoir ecological status and could be implemented elsewhere with limited parameterisation. Issues are discussed that relate to model uncertainty and to its relevance as a tool applied to decision-making. PMID:23991066

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping

PubMed Central

Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

2016-01-01

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply. PMID:27128915

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping.

PubMed

Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

2016-04-26

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply.

Global synthesis of groundwater recharge in semiarid and arid regions

USGS Publications Warehouse

Scanlon, Bridget R.; Keese, K.E.; Flint, A.L.; Flint, L.E.; Gaye, C.B.; Edmunds, W.M.; Simmers, I.

2006-01-01

Global synthesis of the findings from ∼140 recharge study areas in semiarid and arid regions provides important information on recharge rates, controls, and processes, which are critical for sustainable water development. Water resource evaluation, dryland salinity assessment (Australia), and radioactive waste disposal (US) are among the primary goals of many of these recharge studies. The chloride mass balance (CMB) technique is widely used to estimate recharge. Average recharge rates estimated over large areas (40–374 000 km2) range from 0·2 to 35 mm year−1, representing 0·1–5% of long-term average annual precipitation. Extreme local variability in recharge, with rates up to ∼720 m year−1, results from focussed recharge beneath ephemeral streams and lakes and preferential flow mostly in fractured systems. System response to climate variability and land use/land cover (LU/LC) changes is archived in unsaturated zone tracer profiles and in groundwater level fluctuations. Inter-annual climate variability related to El Niño Southern Oscillation (ENSO) results in up to three times higher recharge in regions within the SW US during periods of frequent El Niños (1977–1998) relative to periods dominated by La Niñas (1941–1957). Enhanced recharge related to ENSO is also documented in Argentina. Climate variability at decadal to century scales recorded in chloride profiles in Africa results in recharge rates of 30 mm year−1 during the Sahel drought (1970–1986) to 150 mm year−1 during non-drought periods. Variations in climate at millennial scales in the SW US changed systems from recharge during the Pleistocene glacial period (≥10 000 years ago) to discharge during the Holocene semiarid period. LU/LC changes such as deforestation in Australia increased recharge up to about 2 orders of magnitude. Changes from natural grassland and shrublands to dryland (rain-fed) agriculture altered systems from discharge (evapotranspiration, ET) to recharge in the SW US. The impact of LU change was much greater than climate variability in Niger (Africa), where replacement of savanna by crops increased recharge by about an order of magnitude even during severe droughts. Sensitivity of recharge to LU/LC changes suggests that recharge may be controlled through management of LU. In irrigated areas, recharge varies from 10 to 485 mm year−1, representing 1–25% of irrigation plus precipitation. However, irrigation pumpage in groundwater-fed irrigated areas greatly exceeds recharge rates, resulting in groundwater mining. Increased recharge related to cultivation has mobilized salts that accumulated in the unsaturated zone over millennia, resulting in widespread groundwater and surface water contamination, particularly in Australia. The synthesis of recharge rates provided in this study contains valuable information for developing sustainable groundwater resource programmes within the context of climate variability and LU/LC change. 

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

NASA Astrophysics Data System (ADS)

Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

2008-08-01

SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig

2008-01-01

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

Effects of River Discharge and Land Use and Land Cover (LULC) on Water Quality Dynamics in Migina Catchment, Rwanda

NASA Astrophysics Data System (ADS)

Uwimana, Abias; van Dam, Anne; Gettel, Gretchen; Bigirimana, Bonfils; Irvine, Kenneth

2017-09-01

Agricultural intensification may accelerate the loss of wetlands, increasing the concentrations of nutrients and sediments in downstream water bodies. The objective of this study was to assess the effects of land use and land cover and river discharge on water quality in the Migina catchment, southern Rwanda. Rainfall, discharge and water quality (total nitrogen, total phosphorus, total suspended solids, dissolved oxygen, conductivity, pH, and temperature) were measured in different periods from May 2009 to June 2013. In 2011, measurements were done at the outlets of 3 sub-catchments (Munyazi, Mukura and Akagera). Between May 2012 and May 2013 the measurements were done in 16 reaches of Munyazi dominated by rice, vegetables, grass/forest or ponds/reservoirs. Water quality was also measured during two rainfall events. Results showed seasonal trends in water quality associated with high water flows and farming activities. Across all sites, the total suspended solids related positively to discharge, increasing 2-8 times during high flow periods. Conductivity, temperature, dissolved oxygen, and pH decreased with increasing discharge, while total nitrogen and total phosphorus did not show a clear pattern. The total suspended solids concentrations were consistently higher downstream of reaches dominated by rice and vegetable farming. For total nitrogen and total phosphorus results were mixed, but suggesting higher concentration of total nitrogen and total phosphorus during the dry and early rainy (and farming) season, and then wash out during the rainy season, with subsequent dilution at the end of the rains. Rice and vegetable farming generate the transport of sediment as opposed to ponds/reservoir and grass/forest.

Analysis of Urban Expansion of the Resort City of Al Ain Using Remote Sensing and GIS

NASA Astrophysics Data System (ADS)

Issa, S.; Al Shuwaihi, A.

2009-12-01

The urban growth of AL Ain city has been investigated using remote sensing data for three different dates, 1972, 1990 and 2000. We used three Landsat images together with socio-economic data in a post-classification analysis to map the spatial dynamics of land use/cover changes and identify the urbanization process in Al Ain resort city, United Arab Emirates. Land use/cover statistics, extracted from Landsat Multi-spectral Scanner (MSS). Thematic Mapper (TM) and Enhanced Thematic Mapper plus (ETM +) images for 1972. 1990 and 2000 respectively, revealed that the built-up area has expanded by about 170.53km2. The city was found to have a tendency for major expansion in four different directions: along the Abu Dhabi highway, along Dubai highway, Myziad direction and Hafeet recreational area. Expansion in any direction was found to be governed by the availability of road network, suitability for construction, utilities, economic activities, geographical constraints, and legal factors (boundary with Sultanate of Oman). The road network in particular has influenced the spatial patterns and structure of urban development, so that the expansion of the built-up areas has assumed an accretive as well as linear growth along the major roads. The research concludes that the development is based on conservation of agricultural areas (oases) and reclamation of the desert for farming and agricultural activities. The integration of remote sensing and GIS was found to be effective in monitoring LULC changes and providing valuable information necessary for planning and research.

Analysis of MODIS 250 m Time Series Product for LULC Classification and Retrieval of Crop Biophysical Parameter

NASA Astrophysics Data System (ADS)

Verma, A. K.; Garg, P. K.; Prasad, K. S. H.; Dadhwal, V. K.

2016-12-01

Agriculture is a backbone of Indian economy, providing livelihood to about 70% of the population. The primary objective of this research is to investigate the general applicability of time-series MODIS 250m Normalized difference vegetation index (NDVI) and Enhanced vegetation index (EVI) data for various Land use/Land cover (LULC) classification. The other objective is the retrieval of crop biophysical parameter using MODIS 250m resolution data. The Uttar Pradesh state of India is selected for this research work. A field study of 38 farms was conducted during entire crop season of the year 2015 to evaluate the applicability of MODIS 8-day, 250m resolution composite images for assessment of crop condition. The spectroradiometer is used for ground reflectance and the AccuPAR LP-80 Ceptometer is used to measure the agricultural crops Leaf Area Index (LAI). The AccuPAR measures Photosynthetically Active Radiation (PAR) and can invert these readings to give LAI for plant canopy. Ground-based canopy reflectance and LAI were used to calibrate a radiative transfer model to create look-up table (LUT) that was used to simulate LAI. The seasonal trend of MODIS-derived LAI was used to find crop parameter by adjusting the LAI simulated from climate-based crop yield model. Cloud free MODIS images of 250m resolution (16 day composite period) were downloaded using LP-DAAC website over a period of 12 months (Jan to Dec 2015). MODIS both the VI products were found to have sufficient spectral, spatial and temporal resolution to detect unique signatures for each class (water, fallow land, urban, dense vegetation, orchard, sugarcane and other crops). Ground truth data were collected using JUNO GPS. Multi-temporal VI signatures for vegetation classes were consistent with its general phenological characteristic and were spectrally separable at some point during the growing season. The MODIS NDVI and EVI multi-temporal images tracked similar seasonal responses for all croplands and were highly correlated across the growing season. The confusion matrix method is used for accuracy assessment and reference data which has been taken during the field visit. Total 520 pixels have been selected for various classes to determine the accuracy. The classification accuracy and kappa coefficient is found to be 79.76% and 0.78 respectively.

A Landscape-based model for predicting Mycobacterium ulcerans infection (Buruli Ulcer disease) presence in Benin, West Africa.

PubMed

Wagner, Tyler; Benbow, M Eric; Burns, Meghan; Johnson, R Christian; Merritt, Richard W; Qi, Jiaguo; Small, Pamela L C

2008-03-01

Mycobacterium ulcerans infection (Buruli ulcer [BU] disease) is an emerging tropical disease that causes severe morbidity in many communities, especially those in close proximity to aquatic environments. Research and control efforts are severely hampered by the paucity of data regarding the ecology of this disease; for example, the vectors and modes of transmission remain unknown. It is hypothesized that BU presence is associated with altered landscapes that perturb aquatic ecosystems; however, this has yet to be quantified over large spatial scales. We quantified relationships between land use/land cover (LULC) characteristics surrounding individual villages and BU presence in Benin, West Africa. We also examined the effects of other village-level characteristics which we hypothesized to affect BU presence, such as village distance to the nearest river. We found that as the percent urban land use in a 50-km buffer surrounding a village increased, the probability of BU presence decreased. Conversely, as the percent agricultural land use in a 20-km buffer surrounding a village increased, the probability of BU presence increased. Landscape-based models had predictive ability when predicting BU presence using validation data sets from Benin and Ghana, West Africa. Our analyses suggest that relatively small amounts of urbanization are associated with a decrease in the probability of BU presence, and we hypothesize that this is due to the increased availability of pumped water in urban environments. Our models provide an initial approach to predicting the probability of BU presence over large spatial scales in Benin and Ghana, using readily available land use data.

Land Use Dynamics of the Fast-Growing Shanghai Metropolis, China (1979–2008) and its Implications for Land Use and Urban Planning Policy

PubMed Central

Zhang, Hao; Zhou, Li-Guo; Chen, Ming-Nan; Ma, Wei-Chun

2011-01-01

Through the integrated approach of remote sensing and geographic information system (GIS) techniques, four Landsat TM/ETM+ imagery acquired during 1979 and 2008 were used to quantitatively characterize the patterns of land use and land cover change (LULC) and urban sprawl in the fast-growing Shanghai Metropolis, China. Results showed that, the urban/built-up area grew on average by 4,242.06 ha yr−1. Bare land grew by 1,594.66 ha yr−1 on average. In contrast, cropland decreased by 3,286.26 ha yr−1 on average, followed by forest and shrub, water, and tidal land, which decreased by 1,331.33 ha yr−1, 903.43 ha yr−1, and 315.72 ha yr−1 on average, respectively. As a result, during 1979 and 2008 approximately 83.83% of the newly urban/built-up land was converted from cropland (67.35%), forest and shrub (9.12%), water (4.80%), and tidal land (2.19%). Another significant change was the continuous increase in regular residents, which played a very important role in contributing to local population growth and increase in urban/built-up land. This can be explained with this city’s huge demand for investment and qualified labor since the latest industrial transformation. Moreover, with a decrease in cropland, the proportion of population engaged in farming decreased 13.84%. Therefore, significant socio-economic transformation occurred, and this would lead to new demand for land resources. However, due to very scarce land resources and overload of population in Shanghai, the drive to achieve economic goals at the loss of cropland, water, and the other lands is not sustainable. Future urban planning policy aiming at ensuring a win-win balance between sustainable land use and economic growth is urgently needed. PMID:22319382

Integrated climate/land use/hydrological change scenarios for assessing threats to ecosystem services on California rangelands

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Flint, L. E.; Casey, C. F.; Alvarez, P.; Sleeter, B. M.; Sohl, T.

2013-12-01

In California there are over 18 million acres of rangelands in the Central Valley and the interior Coast Range, most of which are privately owned and managed for livestock production. Ranches provide extensive wildlife habitat and generate multiple ecosystem services that carry considerable market and non-market values. These rangelands are under pressure from urbanization and conversion to intensive agriculture, as well as from climate change that can alter the flow of these services. To understand the coupled and isolated impacts of land use and climate change on rangeland ecosystem services, we developed six spatially explicit (250 m) coupled climate/land use/hydrological change scenarios for the Central Valley and oak woodland regions of California consistent with three IPCC emission scenarios - A2, A1B and B1. Three land use land cover (LULC) change scenarios were each integrated with two downscaled global climate models (GCMs) (a warm, wet future and a hot, dry future) and related hydrologic data. We used these scenarios to quantify wildlife habitat, water supply (recharge potential and streamflow) and carbon sequestration on rangelands and to conduct an economic analysis associated with changes in these benefits. The USGS FOREcasting SCEnarios of land-use change model (FORE-SCE), which runs dynamically with downscaled GCM outputs, was used to generate maps of yearly LULC change for each scenario from 2006 to 2100. We used the USGS Basin Characterization Model (BCM), a regional water balance model, to generate change in runoff, recharge, and stream discharge based on land use change and climate change. Metrics derived from model outputs were generated at the landscape scale and for six case-study watersheds. At the landscape scale, over a quarter of the million acres set aside for conservation in the B1 scenario would otherwise be converted to agriculture in the A2 scenario, where temperatures increase by up to 4.5 °C compared to 1.3 °C in the B1 scenario. A comparison of two watersheds - Alameda Creek, an urbanized watershed, and Upper Stony Creek, impacted by intensified agriculture, demonstrates the relative contribution of urbanization and climate change to water supply. In Upper Stony Creek, where 24% of grassland is converted to agriculture in the A1B scenario, a hotter, dryer 4-year time period could lead to a 40% reduction in streamflow compared to present day. In Alameda Creek, for the same scenario, 47% of grassland is converted to urbanized lands and streamflow may increase by 11%, resulting in a recharge:runoff ratio of 0.26; though if urbanization does not take place, streamflow could decrease by 64% and the recharge:runoff ratio would be 1.2. Model outputs quantify the impact of urbanization on water supply and show the importance of soil storage capacity. Scenarios have applications for climate-smart conservation and land use planning by identifying outcomes associated with coupled future land use scenarios and more variable and extreme potential future climates.

Utility of Mobile phones to support In-situ data collection for Land Cover Mapping

NASA Astrophysics Data System (ADS)

Oduor, P.; Omondi, S.; Wahome, A.; Mugo, R. M.; Flores, A.

2017-12-01

With the compelling need to create better monitoring tools for our landscapes to enhance better decision making processes, it becomes imperative to do so in much more sophisticated yet simple ways. Making it possible to leverage untapped potential of our "lay men" at the same time enabling us to respond to the complexity of the information we have to get out. SERVIR Eastern and Southern Africa has developed a mobile app that can be utilized with very little prior knowledge or no knowledge at all to collect spatial information on land cover. This set of in-situ data can be collected by masses because the tools is very simple to use, and have this information fed in classification algorithms than can then be used to map out our ever changing landscape. The LULC Mapper is a subset of JiMap system and is able to pull the google earth imagery and open street maps to enable user familiarize with their location. It uses phone GPS, phone network information to map location coordinates and at the same time gives the user sample picture of what to categorize their landscape. The system is able to work offline and when user gets access to internet they can push the information into an amazon database as bulk data. The location details including geotagged photos allows the data to be used in development of a lot of spatial information including land cover data. The app is currently available in Google Play Store and will soon be uploaded on Appstore for utilization by a wider community. We foresee a lot of potential in this tool in terms of making data collection cheaper and affordable. Taking advantage of the advances made in phone technology. We envisage to do a data collection campaign where we can have the tool used for crowdsourcing.

Projecting global land-use change and its effect on ecosystem service provision and biodiversity with simple models.

PubMed

Nelson, Erik; Sander, Heather; Hawthorne, Peter; Conte, Marc; Ennaanay, Driss; Wolny, Stacie; Manson, Steven; Polasky, Stephen

2010-12-15

As the global human population grows and its consumption patterns change, additional land will be needed for living space and agricultural production. A critical question facing global society is how to meet growing human demands for living space, food, fuel, and other materials while sustaining ecosystem services and biodiversity [1]. We spatially allocate two scenarios of 2000 to 2015 global areal change in urban land and cropland at the grid cell-level and measure the impact of this change on the provision of ecosystem services and biodiversity. The models and techniques used to spatially allocate land-use/land-cover (LULC) change and evaluate its impact on ecosystems are relatively simple and transparent [2]. The difference in the magnitude and pattern of cropland expansion across the two scenarios engenders different tradeoffs among crop production, provision of species habitat, and other important ecosystem services such as biomass carbon storage. For example, in one scenario, 5.2 grams of carbon stored in biomass is released for every additional calorie of crop produced across the globe; under the other scenario this tradeoff rate is 13.7. By comparing scenarios and their impacts we can begin to identify the global pattern of cropland and irrigation development that is significant enough to meet future food needs but has less of an impact on ecosystem service and habitat provision. Urban area and croplands will expand in the future to meet human needs for living space, livelihoods, and food. In order to jointly provide desired levels of urban land, food production, and ecosystem service and species habitat provision the global society will have to become much more strategic in its allocation of intensively managed land uses. Here we illustrate a method for quickly and transparently evaluating the performance of potential global futures.

Classification of urban features using airborne hyperspectral data

NASA Astrophysics Data System (ADS)

Ganesh Babu, Bharath

Accurate mapping and modeling of urban environments are critical for their efficient and successful management. Superior understanding of complex urban environments is made possible by using modern geospatial technologies. This research focuses on thematic classification of urban land use and land cover (LULC) using 248 bands of 2.0 meter resolution hyperspectral data acquired from an airborne imaging spectrometer (AISA+) on 24th July 2006 in and near Terre Haute, Indiana. Three distinct study areas including two commercial classes, two residential classes, and two urban parks/recreational classes were selected for classification and analysis. Four commonly used classification methods -- maximum likelihood (ML), extraction and classification of homogeneous objects (ECHO), spectral angle mapper (SAM), and iterative self organizing data analysis (ISODATA) - were applied to each data set. Accuracy assessment was conducted and overall accuracies were compared between the twenty four resulting thematic maps. With the exception of SAM and ISODATA in a complex commercial area, all methods employed classified the designated urban features with more than 80% accuracy. The thematic classification from ECHO showed the best agreement with ground reference samples. The residential area with relatively homogeneous composition was classified consistently with highest accuracy by all four of the classification methods used. The average accuracy amongst the classifiers was 93.60% for this area. When individually observed, the complex recreational area (Deming Park) was classified with the highest accuracy by ECHO, with an accuracy of 96.80% and 96.10% Kappa. The average accuracy amongst all the classifiers was 92.07%. The commercial area with relatively high complexity was classified with the least accuracy by all classifiers. The lowest accuracy was achieved by SAM at 63.90% with 59.20% Kappa. This was also the lowest accuracy in the entire analysis. This study demonstrates the potential for using the visible and near infrared (VNIR) bands from AISA+ hyperspectral data in urban LULC classification. Based on their performance, the need for further research using ECHO and SAM is underscored. The importance incorporating imaging spectrometer data in high resolution urban feature mapping is emphasized.

Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

NASA Astrophysics Data System (ADS)

Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

2016-05-01

Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

Characterizing commercial oil palm expansion in Latin America: land use change and trade

NASA Astrophysics Data System (ADS)

Furumo, Paul Richard; Aide, T. Mitchell

2017-02-01

Commodity crop expansion has increased with the globalization of production systems and consumer demand, linking distant socio-ecological systems. Oil palm plantations are expanding in the tropics to satisfy growing oilseed and biofuel markets, and much of this expansion has caused extensive deforestation, especially in Asia. In Latin America, palm oil output has doubled since 2001, and the majority of expansion seems to be occurring on non-forested lands. We used MODIS satellite imagery (250 m resolution) to map current oil palm plantations in Latin America and determined prior land use and land cover (LULC) using high-resolution images in Google Earth. In addition, we compiled trade data to determine where Latin American palm oil flows, in order to better understand the underlying drivers of expansion in the region. Based on a sample of 342 032 ha of oil palm plantations across Latin America, we found that 79% replaced previously intervened lands (e.g. pastures, croplands, bananas), primarily cattle pastures (56%). The remaining 21% came from areas that were classified as woody vegetation (e.g. forests), most notably in the Amazon and the Petén region in northern Guatemala. Latin America is a net exporter of palm oil but the majority of palm oil exports (70%) stayed within the region, with Mexico importing about half. Growth of the oil palm sector may be driven by global factors, but environmental and economic outcomes vary between regions (i.e. Asia and Latin America), within regions (i.e. Colombia and Peru), and within single countries (i.e. Guatemala), suggesting that local conditions are influential. The present trend of oil palm expanding onto previously cleared lands, guided by roundtable certifications programs, provides an opportunity for more sustainable development of the oil palm sector in Latin America.

The Human Appropriation of Ecosystem Service Values (HAESV) in the Sundarban Biosphere Region Using Biophysical Quantification Approach

NASA Astrophysics Data System (ADS)

Sannigrahi, S.; Paul, S. K.; Sen, S.

2017-12-01

Human appropriation, especially unusual changes in land-use and land cover, significantly affects ecosystem services and functions. Driven by the growth of the population and the economy, human demands on earth's land surface have increased dramatically in the past 50 - 100 years. The area studied was divided into six major categories; cropland, mangrove forest, sparse vegetation, built-up urban area, water bodies and sandy coast, and the land coverage was calculated for the years 1973, 1988, 2002 and 2013. The spatial explicit value of the primary regulatory and supporting ecosystem services (climate regulation, raw material production, water regulation) were quantified through the indirect market valuation approach. A light use efficiency based ecosystem model, i.e. Carnegie- Ames-Stanford-Approach (CASA) was employed to estimate the carbon sequestration and oxygen production services of the ecosystem. The ArcGIS matrix transform approach calculated LULC dynamics among the classes. Investigation revealed that the built-up urban area increased from 42.9 km2 in 1973 to 308 km2 in 2013 with a 6.6 km2 yr-1 expansion rate. Similarly, water bodies (especially inland water bodies increased dramatically in the north central region) increased from 3392.1 sq.km in 1973 to 5420 sq.km in 2013 at the expense of semi-natural and natural land resulting in significant changes of ecological and ecosystem services. However, the area occupied by dense mangrove forest decreased substantially during the 40 years (1973 -2013); it was recorded to cover 2294 km2 in 1973 and 1820 km2 in 2013. The results showed that the estimated regulatory and supporting ecosystem services respond quite differently to human appropriation across the regions in both the economic and ecological dimensions. While evaluating the trade-of between human appropriation and ecosystem service changes, it has been estimated that the ecosystem service value of organic matter provision services decreased from 755 US ha-1 in 2000 to 608 US ha-1 in 2013. Therefore, the rigorous and centralised policy for sustainable and regionally balanced land-use planning has been essential in the recent era for economic viability, and ecosystem preservation, to prevent undesirable outcomes.

Spatialization of instantaneous and daily average net radiation and soil heat flux in the territory of Itaparica, Northeast Brazil

NASA Astrophysics Data System (ADS)

Lopes, Helio L.; Silva, Bernardo B.; Teixeira, Antônio H. C.; Accioly, Luciano J. O.

2012-09-01

This work has as aim to quantify the energy changes between atmosphere and surface by modeling both net radiation and soil heat flux related to land use and cover. The methodology took into account modeling and mapping of physical and biophysical parameters using MODIS images and SEBAL algorithm in an area of native vegetation and irrigated crops. The results showed that there are variations in the values of the estimated parameters for different land cover types and mainly in caatinga cover. The dense caatinga presents mean values of soil heat flux (Go) of 124.9 Wm-2 while sparse caatinga with incidence of erosion, present average value of 132.6 Wm-2. For irrigated plots cultivated with banana, coconut, and papaya the mean Go values were 103.8, 98.6, 113.9 Wm-2, respectively. With regard to the instantaneous net radiation (Rn), dense caatinga presented mean value of 626.1 Wm-2, while sparse caatinga a mean value of 575.2 Wm-2. Irrigated areas cultivated with banana, coconut, and papaya presented Rn of 658.1, 647.4 and 617.9 W m-2 respectively. Applying daily mean net radiation (RnDAve) it was found that dense caatinga had a mean value of 417.1 W m-2, while sparse caatinga had a mean value of 379.9 W m-2. For the irrigated crops of banana, coconut and papaya the RnDAve values were 430.9, 431.3 and 411.6 W m-2, respectively. Sinusoidal model can be applied to determine the maximum and RnDAve considering the diverse classes of LULC; however, there is a need to compare the results with field data for validation of this model.

Assessment of sea water inundation along Daboo creek area in Indus Delta Region, Pakistan

NASA Astrophysics Data System (ADS)

Zia, Ibrahim; Zafar, Hina; Shahzad, Muhammad I.; Meraj, Mohsin; Kazmi, Jamil H.

2017-12-01

Indus Deltaic Region (IDR) in Pakistan is an erosion vulnerable coast due to the high deep water wave energy. Livelihood of millions of people depends on the fisheries and mangrove forests in IDR. IDR consists of many creeks where Daboo is a major creek located at southeast of the largest city of Pakistan, Karachi. Unfortunately, there has been no detailed study to analyze the damages of sea water intrusion at a large temporal and spatial scale. Therefore, this study is designed to estimate the effects of sea water inundation based on changing sea water surface salinity and sea surface temperature (SST). Sea surface salinity and SST data from two different surveys in Daboo creek during 1986 and 2010 are analyzed to estimate the damages and extent of sea water intrusion. Mean salinity has increased 33.33% whereas mean SST decreased 13.79% from 1987 to 2010. Spatio-temporal analysis of creek area using LANDSAT 5 Thematic mapper (TM) data for the years 1987 and 2010 shows significant amount of erosion at macro scale. Creek area has increased approximately 9.93% (260.86 m2 per year) which is roughly equal to 60 extensive sized shrimp farms. Further Land Use Land Cover (LULC) analyses for years 2001 and 2014 using LANDSAT 7 Enhanced Thematic Mapper Plus (ETM+) has indicated 42.3% decrease in cultivated land. Wet mud flats have spread out at the inner mouth of creek with enormous increase of 123.3%. Significant sea water intrusion has increased the area of barren land by 37.9%. This also resulted in overall decrease of 6.7% in area covered by mangroves. Therefore, this study recorded a significant evidence of sea water intrusion in IDR that has caused serious damages to community living in the area, economical losses. Additionally, it has also changed the environment by reducing creek biological productivity as reported by earlier studies over other regions of the world.

Integration of Satellite, Global Reanalysis Data and Macroscale Hydrological Model for Drought Assessment in Sub-Tropical Region of India

NASA Astrophysics Data System (ADS)

Pandey, V.; Srivastava, P. K.

2018-04-01

Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI). A macroscale hydrological model Variable Infiltration Capacity (VIC) was used to simulate the hydro-climatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC) and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP) and ESA's Climate Change Initiative soil moisture (CCI-SM) data respectively. The analysis of results demonstrates that most of the study regions (> 80 %) especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model.

Spatio-Temporal Distribution of Vector-Host Contact (VHC) Ratios and Ecological Niche Modeling of the West Nile Virus Mosquito Vector, Culex quinquefasciatus, in the City of New Orleans, LA, USA

PubMed Central

Michaels, Sarah R.; Riegel, Claudia; Pereira, Roberto M.; Zipperer, Wayne; Lockaby, B. Graeme; Koehler, Philip G.

2017-01-01

The consistent sporadic transmission of West Nile Virus (WNV) in the city of New Orleans justifies the need for distribution risk maps highlighting human risk of mosquito bites. We modeled the influence of biophysical and socioeconomic metrics on the spatio-temporal distributions of presence/vector-host contact (VHC) ratios of WNV vector, Culex quinquefasciatus, within their flight range. Biophysical and socioeconomic data were extracted within 5-km buffer radii around sampling localities of gravid female Culex quinquefasciatus. The spatio-temporal correlations between VHC data and 33 variables, including climate, land use-land cover (LULC), socioeconomic, and land surface terrain were analyzed using stepwise linear regression models (RM). Using MaxEnt, we developed a distribution model using the correlated predicting variables. Only 12 factors showed significant correlations with spatial distribution of VHC ratios (R2 = 81.62, p < 0.01). Non-forested wetland (NFWL), tree density (TD) and residential-urban (RU) settings demonstrated the strongest relationship. The VHC ratios showed monthly environmental resilience in terms of number and type of influential factors. The highest prediction power of RU and other urban and built up land (OUBL), was demonstrated during May–August. This association was positively correlated with the onset of the mosquito WNV infection rate during June. These findings were confirmed by the Jackknife analysis in MaxEnt and independently collected field validation points. The spatial and temporal correlations of VHC ratios and their response to the predicting variables are discussed. PMID:28786934

Spatio-Temporal Distribution of Vector-Host Contact (VHC) Ratios and Ecological Niche Modeling of the West Nile Virus Mosquito Vector, Culex quinquefasciatus, in the City of New Orleans, LA, USA.

PubMed

Sallam, Mohamed F; Michaels, Sarah R; Riegel, Claudia; Pereira, Roberto M; Zipperer, Wayne; Lockaby, B Graeme; Koehler, Philip G

2017-08-08

The consistent sporadic transmission of West Nile Virus (WNV) in the city of New Orleans justifies the need for distribution risk maps highlighting human risk of mosquito bites. We modeled the influence of biophysical and socioeconomic metrics on the spatio-temporal distributions of presence/vector-host contact (VHC) ratios of WNV vector, Culex quinquefasciatus , within their flight range . Biophysical and socioeconomic data were extracted within 5-km buffer radii around sampling localities of gravid female Culex quinquefasciatus . The spatio-temporal correlations between VHC data and 33 variables, including climate, land use-land cover (LULC), socioeconomic, and land surface terrain were analyzed using stepwise linear regression models (RM). Using MaxEnt, we developed a distribution model using the correlated predicting variables. Only 12 factors showed significant correlations with spatial distribution of VHC ratios ( R ² = 81.62, p < 0.01). Non-forested wetland (NFWL), tree density (TD) and residential-urban (RU) settings demonstrated the strongest relationship. The VHC ratios showed monthly environmental resilience in terms of number and type of influential factors. The highest prediction power of RU and other urban and built up land (OUBL), was demonstrated during May-August. This association was positively correlated with the onset of the mosquito WNV infection rate during June. These findings were confirmed by the Jackknife analysis in MaxEnt and independently collected field validation points. The spatial and temporal correlations of VHC ratios and their response to the predicting variables are discussed.

Probabilistic Assessment of Soil Moisture using C-band Quad-polarized Remote Sensing Data from RISAT1

NASA Astrophysics Data System (ADS)

Pal, Manali; Suman, Mayank; Das, Sarit Kumar; Maity, Rajib

2017-04-01

Information on spatio-temporal distribution of surface Soil Moisture Content (SMC) is essential in several hydrological, meteorological and agricultural applications. There has been increasing importance of microwave active remote sensing data for large-scale estimation of surface SMC because of its ability to monitor spatial and temporal variation of surface SMC at regional, continental and global scale at a reasonably fine spatial and temporal resolution. The use of Synthetic Aperture Radar (SAR) is highly potential for catchment-scale applications due to high spatial resolution (˜10-20 m) both for vegetated and bare soil surface as well as because of its all-weather and day and night characteristics. However, one prime disadvantage of SAR is that their signal is subjective to SMC along with Land Use Land Cover (LULC) and surface roughness conditions, making the retrieval of SMC from SAR data an "ill-posed" problem. Moreover, the quantification of uncertainty due to inappropriate surface roughness characterization, soil texture, inversion techniques etc. even in the latest established retrieval methods, is little explored. This paper reports a recently developed method to estimate the surface SMC with probabilistic assessment of uncertainty associated with the estimation (Pal et al., 2016). Quad-polarized SAR data from Radar Imaging Satellite1 (RISAT1), launched in 2012 by Indian Space Research Organization (ISRO) and information on LULC regarding bareland and vegetated land (<30 cm height) are used in estimation using the potential of multivariate probabilistic assessment through copulas. The salient features of the study are: 1) development of a combined index to understand the role of all the quad-polarized backscattering coefficients and soil texture information in SMC estimation; 2) applicability of the model for different incidence angles using normalized incidence angle theory proposed by Zibri et al. (2005); and 3) assessment of uncertainty range of the estimated SMC. Supervised Principal Component Analysis (SPCA) is used for development of combined index and Frank copula is found to be the best-fit copula. The developed model is validated with the field soil moisture values over 334 monitoring points within the study area and used for development of a soil moisture map. While the performance is promising, the model is applicable only for bare and vegetated land. References: Pal, M., Maity, R., Suman, M., Das, S.K., Patel, P., and Srivastava, H.S., (2016). "Satellite-Based Probabilistic Assessment of Soil Moisture Using C-Band Quad-Polarized RISAT1 Data." IEEE Transactions on Geoscience and Remote Sensing, In Press, doi:10.1109/TGRS.2016.2623378. Zribi, M., Baghdadi, N., Holah, N., and Fafin, O., (2005)."New methodology for soil surface moisture estimation and its application to ENVISAT-ASAR multi-incidence data inversion." Remote Sensing of Environment, vol. 96, nos. 3-4, pp. 485-496.

Spatial and temporal analysis of land cover change, sedimentation and water quality in the Lake Issaqueena watershed, South Carolina

NASA Astrophysics Data System (ADS)

Pilgrim, Cassie Mechele

Soil erosion and increased sediment yields within a watershed lead to impaired water quality, decreased availability of wildlife habitat and reduced recreational opportunities. While some sedimentation occurs naturally within a water system, most erosion processes are the result of anthropogenic activities across a landscape, namely changes in land use and land cover (LULC). This study was conducted to determine temporal and spatial sedimentation trends in the Lake Issaquena watershed using sonar logging equipment, geographic information systems (GIS) and limited hydrologic data from the Soil Conservation Service (1941 and 1949). Sediment deposition was analyzed in relation to several key factors that influence erosion and sediment yields; these being dominant land cover, topography and slopes, soils and geology, rainfall and climatological aspects. Significant sedimentation has occurred in the Sixmile Creek delta, located at the northern end of Lake Issaqueena. Sedimentation rates inferred from an analysis of afore mentioned factors show considerable changes in erosion potential that correspond with substantial changes in riparian vegetation, extreme variations in rainfall events, conversion of land from agricultural to forestland and application of management practices. Water quality data, including sampling depth, water temperature, dissolved oxygen content, Fecal coliform levels, inorganic nitrogen concentrations and turbidity, were obtained from the South Carolina Department of Environmental Health and Safety (SCDHEC) for two stations and analyzed for trends as they related to land cover change. Data was available for the Sixmile Creek site for dates ranging from 1962 to 2005 and from 1999 to 2005 for the Lake Issaqueena site. From 1951 to 2009, the watershed experienced an increase of tree cover and bare ground (+17.4% evergreen, +62.3% deciduous, +9.8% bare ground) and a decrease of pasture/ grassland and cultivated (-42.6% pasture/ grassland, -57.1% cultivated). From 2005 to 2009, there was an increase of 21.5% in residential/ other development. Sampling depth ranged from 0.1 meters to 0.3 meters. Water temperature fluctuated corresponding to changing air temperatures, and dissolved oxygen content fluctuated as a factor of water temperature. Inorganic nitrogen content was higher from December to April possibly due to application of fertilizers prior to the growing season. Fecal coliform levels stayed relatively the same, there was however, a slight decrease overall, likely due to the decrease in pasture/ grassland. Turbidity remained relatively the same from 1962 to 2005, but a slight decrease in pH can be observed at both stations. Sedimentation analysis has shown that overall the lake surface area has decreased by 11.333 hectares and lake volume has decreased by 320,800 m3, while catchment area increased by 6.99 hectares. Average annual precipitation rates were shown to have no direct correlation with these bathymetric measurements, and it is hypothesized that changes in land cover, slope and extreme precipitation events are largely responsible for sedimentation in Lake Issaqueena.

Continental-Scale Estimates of Runoff Using Future Climate ...

EPA Pesticide Factsheets

Recent runoff events have had serious repercussions to both natural ecosystems and human infrastructure. Understanding how shifts in storm event intensities are expected to change runoff responses are valuable for local, regional, and landscape planning. To address this challenge, relative changes in runoff using predicted future climate conditions were estimated over different biophysical areas for the CONterminous U.S. (CONUS). Runoff was estimated using the Curve Number (CN) developed by the USDA Soil Conservation Service (USDA, 1986). A seamless gridded dataset representing a CN for existing land use/land cover (LULC) across the CONUS was used along with two different storm event grids created specifically for this effort. The two storm event grids represent a 2- and a 100-year, 24-hour storm event under current climate conditions. The storm event grids were generated using a compilation of county-scale Texas USGS Intensity-Duration-Frequency (IDF) data (provided by William Asquith, USGS, Lubbock, Texas), and NOAA Atlas-2 and NOAA Atlas-14 gridded data sets. Future CN runoff was predicted using extreme storm events grids created using a method based on Kao and Ganguly (2011) where precipitation extremes reflect changes in saturated water vapor pressure of the atmosphere in response to temperature changes. The Clausius-Clapeyron relationship establishes that the total water vapor mass of fully saturated air increases with increasing temperature, leading to

Change Detection Processing Chain Dedicated to Sentinel Data Time Series. Application to Forest and Water Bodies Monitoring

NASA Astrophysics Data System (ADS)

Perez Saavedra, L.-M.; Mercier, G.; Yesou, H.; Liege, F.; Pasero, G.

2016-08-01

The Copernicus program of ESA and European commission (6 Sentinels Missions, among them Sentinel-1 with Synthetic Aperture Radar sensor and Sentinel-2 with 13-band 10 to 60 meter resolution optical sensors), offers a new opportunity to Earth Observation with high temporal acquisition capability ( 12 days repetitiveness and 5 days in some geographic areas of the world) with high spatial resolution.Due to these high temporal and spatial resolutions, it opens new challenges in several fields such as image processing, new algorithms for Time Series and big data analysis. In addition, these missions will be able to analyze several topics of earth temporal evolution such as crop vegetation, water bodies, Land use and Land Cover (LULC), sea and ice information, etc. This is particularly useful for end users and policy makers to detect early signs of damages, vegetation illness, flooding areas, etc.From the state of the art, one can find algorithms and methods that use a bi-date comparison for change detection [1-3] or time series analysis. Actually, these methods are essentially used for target detection or for abrupt change detection that requires 2 observations only.A Hölder means-based change detection technique has been proposed in [2,3] for high resolution radar images. This so-called MIMOSA technique has been mainly dedicated to man-made change detection in urban areas and CARABAS - II project by using a couple of SAR images. An extension to multitemporal change detection technique has been investigated but its application to land use and cover changes still has to be validated.The Hölder Hp is a Time Series pixel by pixel feature extraction and is defined by:H𝑝[X]=[1/n∑ⁿᵢ₌1 Xᴾᵢ]1/p p∈R Hp[X] : N images * S Bandes * t datesn is the number of images in the time series. N > 2Hp (X) is continuous and monotonic increasing in p for - ∞ < p < ∞

Mapping irrigated areas of Ghana using fusion of 30 m and 250 m resolution remote-sensing data

USGS Publications Warehouse

Gumma, M.K.; Thenkabail, P.S.; Hideto, F.; Nelson, A.; Dheeravath, V.; Busia, D.; Rala, A.

2011-01-01

Maps of irrigated areas are essential for Ghana's agricultural development. The goal of this research was to map irrigated agricultural areas and explain methods and protocols using remote sensing. Landsat Enhanced Thematic Mapper (ETM+) data and time-series Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to map irrigated agricultural areas as well as other land use/land cover (LULC) classes, for Ghana. Temporal variations in the normalized difference vegetation index (NDVI) pattern obtained in the LULC class were used to identify irrigated and non-irrigated areas. First, the temporal variations in NDVI pattern were found to be more consistent in long-duration irrigated crops than with short-duration rainfed crops due to more assured water supply for irrigated areas. Second, surface water availability for irrigated areas is dependent on shallow dug-wells (on river banks) and dug-outs (in river bottoms) that affect the timing of crop sowing and growth stages, which was in turn reflected in the seasonal NDVI pattern. A decision tree approach using Landsat 30 m one time data fusion with MODIS 250 m time-series data was adopted to classify, group, and label classes. Finally, classes were tested and verified using ground truth data and national statistics. Fuzzy classification accuracy assessment for the irrigated classes varied between 67 and 93%. An irrigated area derived from remote sensing (32,421 ha) was 20-57% higher than irrigated areas reported by Ghana's Irrigation Development Authority (GIDA). This was because of the uncertainties involved in factors such as: (a) absence of shallow irrigated area statistics in GIDA statistics, (b) non-clarity in the irrigated areas in its use, under-development, and potential for development in GIDA statistics, (c) errors of omissions and commissions in the remote sensing approach, and (d) comparison involving widely varying data types, methods, and approaches used in determining irrigated area statistics using GIDA and remote sensing. Extensive field campaigns to help in better classification and validation of irrigated areas using high (30 m ) to very high (<5 m) resolution remote sensing data that are fused with multi temporal data like MODIS are the way forward. This is especially true in accounting for small yet contiguous patches of irrigated areas from dug-wells and dug-outs. ?? 2011 by the authors.

Evaluation of groundwater potential using geospatial techniques

NASA Astrophysics Data System (ADS)

Hussein, Abdul-Aziz; Govindu, Vanum; Nigusse, Amare Gebre Medhin

2017-09-01

The issue of unsustainable groundwater utilization is becoming increasingly an evident problem and the key concern for many developing countries. One of the problems is the absence of updated spatial information on the quantity and distribution of groundwater resource. Like the other developing countries, groundwater evaluation in Ethiopia has been usually conducted using field survey which is not feasible in terms of time and resource. This study was conducted in Northern Ethiopia, Wollo Zone, in Gerardo River Catchment district to spatially delineate the groundwater potential areas using geospatial and MCDA tools. To do so, eight major biophysical and environmental factors like geomorphology, lithology, slope, rainfall, land use land cover (LULC), soil, lineament density and drainage density were considered. The sources of these data were satellite image, digital elevation model (DEM), existing thematic maps and metrological station data. Landsat image was used in ERDAS Imagine to drive the LULC of the area, while the geomorphology, soil, and lithology of the area were identified and classified through field survey and digitized from existing maps using the ArcGIS software. The slope, lineament and drainage density of the area were derived from DEM using spatial analysis tools. The rainfall surface map was generated using the thissen polygon interpolation. Finally, after all these thematic maps were organized, weighted value determination for each factor and its field value was computed using IDRSI software. At last, all the factors were integrated together and computed the model using the weighted overlay so that potential groundwater areas were mapped. The findings depicted that the most potential groundwater areas are found in the central and eastern parts of the study area, while the northern and western parts of the Gerado River Catchment have poor potential of groundwater availability. This is mainly due to the cumulative effect of steep topographic and high drainage density. At last, once the potential groundwater areas were identified, cross validation of the resultant model was carefully carried out using existing data of dung wells and bore holes. The point data of dung wells and bore holes were overlaid on groundwater potential suitability map and coincide with the expected values. Generally, from this study, it can be concluded that RS and GIS with the help of MCDA are important tools in monitoring and evaluation of groundwater resource potential areas.

Assessment of underground water potential zones using modern geomatics technologies in Jhansi district, Uttar Pradesh, India.

NASA Astrophysics Data System (ADS)

Pandey, N. K.; Shukla, A. K.; Shukla, S.; Pandey, M.

2014-11-01

Ground water is a distinguished component of the hydrologic cycle. Surface water storage and ground water withdrawal are traditional engineering approaches which will continue to be followed in the future. The uncertainty about the occurrence, distribution and quality aspect of the ground water and the energy requirement for its withdrawal impose restriction on exploitation of ground water. The main objective of the study is assessment of underground water potential zones of Jhansi city and surrounding area, by preparing underground water potential zone map using Geographical Information System (GIS), remote sensing, and validation by underground water inventory mapping using GPS field survey done along the parts of National Highway 25 and 26 and some state highway passing through the study area. Study area covers an area of 1401 km2 and its perimeter is approximate 425 km. For this study Landsat TM (0.76-0.90 um) band data were acquired from GLCF website. Sensor spatial resolution is 30 m. Satellite image has become a standard tool aiding in the study of underground water. Extraction of different thematic layers like Land Use Land Cover (LULC), settlement, etc. can be done through unsupervised classification. The modern geometics technologies viz. remote sensing and GIS are used to produce the map that classifies the groundwater potential zone to a number of qualitative zone such as very high, high, moderate, low or very low. Thematic maps are prepared by visual interpretation of Survey of India topo-sheets and linearly enhanced Landsat TM satellite image on 1 : 50,000 scale using AutoCAD, ArcGIS 10.1 and ERDAS 11 software packages.

Spatial changes of estuary in Ernakulam district, Southern India for last seven decades, using multi-temporal satellite data.

PubMed

Dipson, P T; Chithra, S V; Amarnath, A; Smitha, S V; Harindranathan Nair, M V; Shahin, Adhem

2015-01-15

The study area, located in the western side of Kerala State, South India, is a part of Vembanad-Kol wetlands - the largest estuary in India's western coastal wetland system and one of the Ramsar Sites of Kerala. Major portion of this estuary comes under the Ernakulam district which includes the Cochin City - the business and Industrial hub of Kerala, which has seen fast urbanization since independence (1947). Recently, this region is subjected to a characteristic fast urban sprawl, whereas, the estuarine zone is subjected to tremendous land use/land cover changes (LULC). Periodic monitoring of the estuary is essential for the formulation of viable management options for the sustainable utilization of this vital environmental resource. Remote sensing coupled with GIS applications has proved to be a useful tool in monitoring wetland changes. In the present study, the changes this estuarine region have undergone from 1944 to 2009 have been monitored with the help of multi-temporal satellite data. Estuarine areas were mapped with the help of Landsat MSS (1973), Landsat ETM (1990) and IRS LISS-III (1998 and 2009) using visual interpretation and digitization techniques in ArcGIS 9.3 Environment. The study shows a progressive decrease in the estuarine area, the reasons of which are identified chronologically. Copyright © 2014 Elsevier Ltd. All rights reserved.

The South Florida Ecosystem Portfolio Model - A Map-Based Multicriteria Ecological, Economic, and Community Land-Use Planning Tool

USGS Publications Warehouse

Labiosa, William B.; Bernknopf, Richard; Hearn, Paul; Hogan, Dianna; Strong, David; Pearlstine, Leonard; Mathie, Amy M.; Wein, Anne M.; Gillen, Kevin; Wachter, Susan

2009-01-01

The South Florida Ecosystem Portfolio Model (EPM) prototype is a regional land-use planning Web tool that integrates ecological, economic, and social information and values of relevance to decision-makers and stakeholders. The EPM uses a multicriteria evaluation framework that builds on geographic information system-based (GIS) analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to regional land-use/land-cover (LULC) change. The EPM uses both economics (monetized) and multiattribute utility (nonmonetized) approaches to valuing these endpoints and consequences. This hybrid approach represents a methodological middle ground between rigorous economic and ecological/ environmental scientific approaches. The EPM sacrifices some degree of economic- and ecological-forecasting precision to gain methodological transparency, spatial explicitness, and transferability, while maintaining credibility. After all, even small steps in the direction of including ecosystem services evaluation are an improvement over current land-use planning practice (Boyd and Wainger, 2003). There are many participants involved in land-use decision-making in South Florida, including local, regional, State, and Federal agencies, developers, environmental groups, agricultural groups, and other stakeholders (South Florida Regional Planning Council, 2003, 2004). The EPM's multicriteria evaluation framework is designed to cut across the objectives and knowledge bases of all of these participants. This approach places fundamental importance on social equity and stakeholder participation in land-use decision-making, but makes no attempt to determine normative socially 'optimal' land-use plans. The EPM is thus a map-based set of evaluation tools for planners and stakeholders to use in their deliberations of what is 'best', considering a balancing of disparate interests within a regional perspective. Although issues of regional ecological sustainability can be explored with the EPM (for example, changes in biodiversity potential and regional habitat fragmentation), it does not attempt to define or evaluate long-term ecological sustainability as such. Instead, the EPM is intended to provide transparent first-order indications of the direction of ecological, economic, and community change, not to make detailed predictions of ecological, economic, and social outcomes. In short, the EPM is an attempt to widen the perspectives of its users by integrating natural and social scientific information in a framework that recognizes the diversity of values at stake in South Florida land-use planning. For terrestrial ecosystems, land-cover change is one of the most important direct drivers of changes in ecosystem services (Hassan and others, 2005). More specifically, the fragmentation of habitat from expanding low-density development across landscapes appears to be a major driver of terrestrial species decline and the impairment of terrestrial ecosystem integrity, in some cases causing irreversible impairment from a land-use planning perspective (Brody, 2008; Peck, 1998). Many resource managers and land-use planners have come to realize that evaluating land-use conversions on a parcel-by-parcel basis leads to a fragmented and narrow view of the regional effects of natural land-cover loss to development (Marsh and Lallas, 1995). The EPM is an attempt to integrate important aspects of the coupled natural-system/human-system view from a regional planning perspective. The EPM evaluates proposed land-use changes, both conversion and intensification, in terms of relevant ecological, economic, and social criteria that combine information about probable land-use outcomes, based on ecological and environmental models, as well as value judgments, as expressed in user-modifiable preference models. Based on on-going meetings and interviews with stakeholders and potential tool users we foc

Extraction and Analysis of Mega Cities’ Impervious Surface on Pixel-based and Object-oriented Support Vector Machine Classification Technology: A case of Bombay

NASA Astrophysics Data System (ADS)

Yu, S. S.; Sun, Z. C.; Sun, L.; Wu, M. F.

2017-02-01

The object of this paper is to study the impervious surface extraction method using remote sensing imagery and monitor the spatiotemporal changing patterns of mega cities. Megacity Bombay was selected as the interesting area. Firstly, the pixel-based and object-oriented support vector machine (SVM) classification methods were used to acquire the land use/land cover (LULC) products of Bombay in 2010. Consequently, the overall accuracy (OA) and overall Kappa (OK) of the pixel-based method were 94.97% and 0.96 with a running time of 78 minutes, the OA and OK of the object-oriented method were 93.72% and 0.94 with a running time of only 17s. Additionally, OA and OK of the object-oriented method after a post-classification were improved up to 95.8% and 0.94. Then, the dynamic impervious surfaces of Bombay in the period 1973-2015 were extracted and the urbanization pattern of Bombay was analysed. Results told that both the two SVM classification methods could accomplish the impervious surface extraction, but the object-oriented method should be a better choice. Urbanization of Bombay experienced a fast extending during the past 42 years, implying a dramatically urban sprawl of mega cities in the developing countries along the One Belt and One Road (OBOR).

Understanding The Individual Impacts Of Human Interventions And Climate Change On Hydrologic Variables In India

NASA Astrophysics Data System (ADS)

Sharma, T.; Chhabra, S., Jr.; Karmakar, S.; Ghosh, S.

2015-12-01

We have quantified the historical climate change and Land Use Land Cover (LULC) change impacts on the hydrologic variables of Indian subcontinent by using Variable Infiltration Capacity (VIC) mesoscale model at 0.5° spatial resolution and daily temporal resolution. The results indicate that the climate change in India has predominating effects on the basic water balance components such as water yield, evapotranspiration and soil moisture. This analysis is with the assumption of naturalised hydrologic cycle, i.e., the impacts of human interventions like construction of controlled (primarily dams, diversions and reservoirs) and water withdrawals structures are not taken into account. The assumption is unrealistic since there are numerous anthropogenic disturbances which result in large changes on vegetation composition and distribution patterns. These activities can directly or indirectly influence the dynamics of water cycle; subsequently affecting the hydrologic processes like plant transpiration, infiltration, evaporation, runoff and sublimation. Here, we have quantified the human interventions by using the reservoir and irrigation module of VIC model which incorporates the irrigation schemes, reservoir characteristics and water withdrawals. The impact of human interventions on hydrologic variables in many grids are found more predominant than climate change and might be detrimental to water resources at regional level. This spatial pattern of impacts will facilitate water manager and planners to design and station hydrologic structures for a sustainable water resources management.

Comparison of Random Forest and Support Vector Machine classifiers using UAV remote sensing imagery

NASA Astrophysics Data System (ADS)

Piragnolo, Marco; Masiero, Andrea; Pirotti, Francesco

2017-04-01

Since recent years surveying with unmanned aerial vehicles (UAV) is getting a great amount of attention due to decreasing costs, higher precision and flexibility of usage. UAVs have been applied for geomorphological investigations, forestry, precision agriculture, cultural heritage assessment and for archaeological purposes. It can be used for land use and land cover classification (LULC). In literature, there are two main types of approaches for classification of remote sensing imagery: pixel-based and object-based. On one hand, pixel-based approach mostly uses training areas to define classes and respective spectral signatures. On the other hand, object-based classification considers pixels, scale, spatial information and texture information for creating homogeneous objects. Machine learning methods have been applied successfully for classification, and their use is increasing due to the availability of faster computing capabilities. The methods learn and train the model from previous computation. Two machine learning methods which have given good results in previous investigations are Random Forest (RF) and Support Vector Machine (SVM). The goal of this work is to compare RF and SVM methods for classifying LULC using images collected with a fixed wing UAV. The processing chain regarding classification uses packages in R, an open source scripting language for data analysis, which provides all necessary algorithms. The imagery was acquired and processed in November 2015 with cameras providing information over the red, blue, green and near infrared wavelength reflectivity over a testing area in the campus of Agripolis, in Italy. Images were elaborated and ortho-rectified through Agisoft Photoscan. The ortho-rectified image is the full data set, and the test set is derived from partial sub-setting of the full data set. Different tests have been carried out, using a percentage from 2 % to 20 % of the total. Ten training sets and ten validation sets are obtained from each test set. The control dataset consist of an independent visual classification done by an expert over the whole area. The classes are (i) broadleaf, (ii) building, (iii) grass, (iv) headland access path, (v) road, (vi) sowed land, (vii) vegetable. The RF and SVM are applied to the test set. The performances of the methods are evaluated using the three following accuracy metrics: Kappa index, Classification accuracy and Classification Error. All three are calculated in three different ways: with K-fold cross validation, using the validation test set and using the full test set. The analysis indicates that SVM gets better results in terms of good scores using K-fold cross or validation test set. Using the full test set, RF achieves a better result in comparison to SVM. It also seems that SVM performs better with smaller training sets, whereas RF performs better as training sets get larger.

Hydrological impacts of forest decline and regrowth: a retrospective analysis of the past 60 years in Saxony, Germany

NASA Astrophysics Data System (ADS)

Renner, Maik; Kristina, Brust; Christian, Bernhofer

2013-04-01

It is generally believed that both, climate and land use land cover (LULC) changes impact evapotranspiration and runoff; yet there is some difficulty to separate the effects of these different impacts. Here, we condense meteorological and hydrological data from the long and well established observation network over Saxony covering the period 1950-2009. The region can be considered as a typical Central European landscape with considerable anthropogenically related impacts. Certainly, one of the most severe impacts have been the air pollution driven tree dieback along the top mountain ranges peaking in the 1970s and 1980s. To address the role of environmental factors on the long term annual average and the potential role of regional scale environmental pollution we conduct a hydro-climatic data analysis of 71 small to medium range river basins covering the greatest part of Saxony. Plotting the 1950-2009 annual averages in a Budyko diagram reveals a significant linear relation of the evaporative fraction (ET/P) to the aridity index (E0-P ). It appears that topographically controlled gradients of precipitation, land use and basin water retention exist. While most basins are found to follow the Budyko curve, two groups of basins deviate. Agriculturally dominated basins at lower altitudes exceed the Budyko curve while a set of high altitude, forested basins fall well below. The latter group is characterized by significant temporal dynamics, which are consistent in space and time with tree damage data. We visualize the decadal dynamics on the relative partitioning of water and energy at the catchment scale and show that the pollution driven tree damage affected head water catchments leading to a decline of ET (P-Q) of up to 200 mm/yr in the 1980s. The apparent regrowth since effective measures on industrial pollution have been established in the 1990s, shows a significant increase of ET. This increase is visible from space and we found good coherence with increasing trends in summer-time GIMMS derived NDVI allowing to disentangle apparent NDVI increases over Central Europe.

Hydrological inferences through morphometric analysis of lower Kosi river basin of India for water resource management based on remote sensing data

NASA Astrophysics Data System (ADS)

Rai, Praveen Kumar; Chandel, Rajeev Singh; Mishra, Varun Narayan; Singh, Prafull

2018-03-01

Satellite based remote sensing technology has proven to be an effectual tool in analysis of drainage networks, study of surface morphological features and their correlation with groundwater management prospect at basin level. The present study highlights the effectiveness and advantage of remote sensing and GIS-based analysis for quantitative and qualitative assessment of flood plain region of lower Kosi river basin based on morphometric analysis. In this study, ASTER DEM is used to extract the vital hydrological parameters of lower Kosi river basin in ARC GIS software. Morphometric parameters, e.g., stream order, stream length, bifurcation ratio, drainage density, drainage frequency, drainage texture, form factor, circularity ratio, elongation ratio, etc., have been calculated for the Kosi basin and their hydrological inferences were discussed. Most of the morphometric parameters such as bifurcation ratio, drainage density, drainage frequency, drainage texture concluded that basin has good prospect for water management program for various purposes and also generated data base that can provide scientific information for site selection of water-harvesting structures and flood management activities in the basin. Land use land cover (LULC) of the basin were also prepared from Landsat data of 2005, 2010 and 2015 to assess the change in dynamic of the basin and these layers are very noteworthy for further watershed prioritization.

Quantification of BMPs Selection and Spatial Placement Impact on Water Quality Controlling Plans in Lower Bear River Watershed, Utah

NASA Astrophysics Data System (ADS)

Salha, A. A.; Stevens, D. K.

2016-12-01

The aim of the watershed-management program in Box Elder County, Utah set by Utah Division of Water Quality (UDEQ) is to evaluate the effectiveness and spatial placement of the implemented best-management practices (BMP) for controlling nonpoint-source contamination at watershed scale. The need to evaluate the performance of BMPs would help future policy and program decisions making as desired end results. The environmental and costs benefits of BMPs in Lower Bear River watershed have seldom been measured beyond field experiments. Yet, implemented practices have rarely been evaluated at the watershed scale where the combined effects of variable soils, climatic conditions, topography and land use/covers and management conditions may significantly change anticipated results and reductions loads. Such evaluation requires distributed watershed models that are necessary for quantifying and reproducing the movement of water, sediments and nutrients. Soil and Water Assessment Tool (SWAT) model is selected as a watershed level tool to identify contaminant nonpoint sources (critical zones) and areas of high pollution risks. Water quality concerns have been documented and are primarily attributed to high phosphorus and total suspended sediment concentrations caused by agricultural and farming practices (required load is 460 kg/day of total phosphorus based on 0.075 mg/l and an average of total suspended solids of 90 mg/l). Input data such as digital elevation model (DEM), land use/Land cover (LULC), soils, and climate data for 10 years (2000-2010) is utilized along with observed water quality at the watershed outlet (USGS) and some discrete monitoring points within the watershed. Statistical and spatial analysis of scenarios of management practices (BMP's) are not implemented (before implementation), during implementation, and after BMP's have been studied to determine whether water quality of the two main water bodies has improved as required by the LBMR watershed's TMDL and if the BMPs are cost-effectively targeting the critical zones.

Climatic effects of 30 years of landscape change over the Greater Phoenix, Arizona, region: 1. Surface energy budget changes

USGS Publications Warehouse

Georgescu, M.; Miguez-Macho, G.; Steyaert, L.T.; Weaver, C.P.

2009-01-01

This paper is part 1 of a two-part study that evaluates the climatic effects of recent landscape change for one of the nation's most rapidly expanding metropolitan complexes, the Greater Phoenix, Arizona, region. The region's landscape evolution over an approximate 30-year period since the early 1970s is documented on the basis of analyses of Landsat images and land use/land cover (LULC) data sets derived from aerial photography (1973) and Landsat (1992 and 2001). High-resolution, Regional Atmospheric Modeling System (RAMS), simulations (2-km grid spacing) are used in conjunction with consistently defined land cover data sets and associated biophysical parameters for the circa 1973, circa 1992, and circa 2001 time periods to quantify the impacts of intensive land use changes on the July surface temperatures and the surface radiation and energy budgets for the Greater Phoenix region. The main findings are as follows: since the early 1970s the region's landscape has been altered by a significant increase in urban/suburban land area, primarily at the expense of decreasing plots of irrigated agriculture and secondarily by the conversion of seminatural shrubland. Mean regional temperatures for the circa 2001 landscape were 0.12??C warmer than the circa 1973 landscape, with maximum temperature differences, located over regions of greatest urbanization, in excess of 1??C. The significant reduction in irrigated agriculture, for the circa 2001 relative to the circa 1973 landscape, resulted in dew point temperature decreases in excess of 1??C. The effect of distinct land use conversion themes (e.g., conversion from irrigated agriculture to urban land) was also examined to evaluate how the most important conversion themes have each contributed to the region's changing climate. The two urbanization themes studied (from an initial landscape of irrigated agriculture and seminatural shrubland) have the greatest positive effect on near-surface temperature, increasing maximum daily temperatures by 1??C. Overall, sensible heat flux differences between the circa 2001 and circa 1973 landscapes result in a 1 W m-2 increase in domain-wide sensible heating, and a similar order of magnitude decrease in latent heating, highlighting the importance of surface repartitioning in establishing near-surface temperature trends. In part 2 of this study, we address the role of the surface budget changes on the mesoscale dynamics/thermodynamics, in context of the large-scale environment. Copyright 2009 by the American Geophysical Union.

Mapping of Temporal Surface-water Resources Availability and Agricultural Adaptability due to Climate Change and Anthropogenic Activity in a Hot Semi-arid Region of Maharashtra State, India

NASA Astrophysics Data System (ADS)

Roy, A.; Inamdar, A. B.

2016-12-01

Major part of Godavari River Basin is intensely drought prone and climate vulnerable in the Western Maharashtra State, India. The economy of the state depends on the agronomic productivity of this region. So, it is necessary to regulate the effects of existing and upcoming hydro-meteorological advances in various strata. This study investigates and maps the surface water resources availability and vegetation, their decadal deviations with multi-temporal LANDSAT images; and finally quantifies the agricultural adaptations. This work involves the utilization of Remote Sensing and GIS with Hydrological modeling. First, climatic trend analysis is carried out with NCEP dataset. Then, multi-temporal LANDSAT images are classified to determine the decadal LULC changes and correlated to the community level hydrological demand. Finally, NDVI, NDWI and SWAT model analysis are accomplished to determine irrigated and non-irrigated cropping area for identifying the agricultural adaptations. The analysis shows that the mean value of annual and monsoon rainfall is significantly decreasing, whereas the mean value of annual and summer temperature is increasing significantly and the winter temperature is decreasing. The analysis of LANDSAT images shows that the surface water availability is highly dependent on climatic conditions. Barren-lands are most dynamic during the study period followed by, vegetation, and water bodies. The spatial extent of barren-lands is increased drastically during the climate vulnerable years replacing the vegetation and surface water bodies. Hence, the barren lands are constantly increasing and the vegetation cover is linearly decreasing, whereas the water extent is changing either way in a random fashion. There appears a positive correlation between surface water and vegetation occurrence; as they are fluctuating in a similar fashion in all the years. The vegetation cover is densely replenished around the dams and natural water bodies which serve as the water supply stations for the irrigation purposes. Moreover, there is a shift to non-irrigated and less water demanding crops, from more water demanding crops, which is a conspicuous adaptation. Hence, the study shows there are alteration in meteorological predictors, land cover, agricultural practices and surface water availability.

Prediction of land use changes based on land change modeler and attribution of changes in the water balance of Ganga basin to land use change using the SWAT model

NASA Astrophysics Data System (ADS)

Anand, J.; Gosain, A. K.; Khosa, R.

2017-12-01

Conflicts between increasing irrigated agricultural area, commercial crops, shifting cultivation and ever increasing domestic and industrial demand has already been a cause of tension in the society over water in the Ganga River Basin, India. For the development of sustainable water resource strategies, it is essential to establish interaction between landuse changes and local hydrology through proper assessment. Precisely, seeing how change in each LULC affects hydrologic regimes, or conversely evaluating which LULC shall be appropriate for the local hydrological regime can help decision makers to incorporate in the policy instruments. In this study, we assess hydrologic regimes of the Ganga River basin with landuse change. Catchment hydrologic responses were simulated using Soil and Water Assessment Tool (SWAT). Meteorological data from IMD of 0.25°×0.25° spatial resolution were taken as the climate inputs. Simulated stream flow was compared at different gauge stations distributed across the Gang basin and its tributaries. Urbanization was the topmost contributor to the increase in surface runoff and water yield. While, increased irrigation demands was the dominant contributor to the water consumption and also added to the increased evapotranspiration. In addition scenarios have been generated to study the impact of landuse change on various components of hydrology including groundwater recharge, with different cropping patterns and increased irrigation efficiency to determine various mitigation strategies that can be adopted. This study can be important tool in quantifying the changes in hydrological components in response to changes made in landuse in especially basins undergoing rapid commercialization. This shall provide substantive information to the decision makers required to develop ameliorative strategies. Keywords: Landuse and Landcover change, Hydrologic model, Soil Water Assessment Tool (SWAT), Urbanization, Ganga River, Watershed hydrology.

Vulnerability assessment of Glacial Lake Outburst Floods using Remote Sensing and GIS in North Sikkim (India), Eastern Himalaya

NASA Astrophysics Data System (ADS)

Aggarwal, Suruchi; Probha Devi, Juna; Thakur, Praveen Kumar; Rai, Suresh Chand

2016-04-01

Glacial lake outburst floods (GLOFs) occur when glacier melt water dammed by a moraine is released in short time. Such floods may lead to disastrous events posing, therefore, a huge threat to human lives and infrastructure. A devastating GLOF in Uttarakhand, India, on 17 July 2013 has led to the loss of all villages in a stretch of 18 km downstream the lake and the loss of more than 5000 lives. The present study evaluates all 16 glacial lakes (with an area >0.1 km²) in the Thangu valley, northern Sikkim (India), eastern Himalaya, with respect to potential threats for the downstream areas. The hazard criteria for the study include slope, aspect and distance of the respective parent glacier, change in the lake area, dam characteristics and lake depth. For the most hazardous lakes, the socio-economic conditions in the downstream areas (settlements and infrastructure) are analysed regarding the impact of potential GLOFs. For the vulnerability analysis, we used various satellite products including LANDSAT, RESOUCESAT-1 and 2, RISAT-1 imageries and ASTER GDEM covering the period from 1977 to 2014. For lake mapping, we applied the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Snow Index (NDSI). A Land Use Land Cover (LULC) map of the study area showing in-situ observations is serving as driving factor for the vulnerability analysis. The results of the study show that almost all evaluated glacial lakes were expanding during the study period (1977-2014). Combining the hazard criteria for the lakes, 5 of the 16 studied glacial lakes are identified as highly hazardous. In the downstream area, there are two villages with 200 inhabitants and an army camp within the zone of highest vulnerability. The identified vulnerability zones may be used by the local authorities to take caution of the threatened villages and infrastructure and for risk analysis for planned future hydropower plants.

Geographic Information System Software to Remodel Population Data Using Dasymetric Mapping Methods

USGS Publications Warehouse

Sleeter, Rachel; Gould, Michael

2007-01-01

The U.S. Census Bureau provides decadal demographic data collected at the household level and aggregated to larger enumeration units for anonymity purposes. Although this system is appropriate for the dissemination of large amounts of national demographic data, often the boundaries of the enumeration units do not reflect the distribution of the underlying statistical phenomena. Conventional mapping methods such as choropleth mapping, are primarily employed due to their ease of use. However, the analytical drawbacks of choropleth methods are well known ranging from (1) the artificial transition of population at the boundaries of mapping units to (2) the assumption that the phenomena is evenly distributed across the enumeration unit (when in actuality there can be significant variation). Many methods to map population distribution have been practiced in geographic information systems (GIS) and remote sensing fields. Many cartographers prefer dasymetric mapping to map population because of its ability to more accurately distribute data over geographic space. Similar to ?choropleth maps?, a dasymetric map utilizes standardized data (for example, census data). However, rather than using arbitrary enumeration zones to symbolize population distribution, a dasymetric approach introduces ancillary information to redistribute the standardized data into zones relative to land use and land cover (LULC), taking into consideration actual changing densities within the boundaries of the enumeration unit. Thus, new zones are created that correlate to the function of the map, capturing spatial variations in population density. The transfer of data from census enumeration units to ancillary-driven homogenous zones is performed by a process called areal interpolation.

Impacts of soil sealing on potential agriculture in Egypt using remote sensing and GIS techniques

NASA Astrophysics Data System (ADS)

Mohamed, Elsayed Said; Belal, Abdelaziz; Shalaby, Adel

2015-10-01

This paper highlights the impacts of soil sealing on the agricultural soils in Nile Delta using remote sensing and GIS. The current work focuses on two aims. The first aim is to evaluate soil productivity lost to urban sprawl, which is a significant cause of soil sealing in Nile Delta. The second aim is to evaluate the Land Use and Land Cover Changes (LU LC) from 2001 to 2013 in El-Gharbia governorate as a case study. Three temporal data sets of images from two different sensors: Landsat 7 Enhanced Thematic Mapper (ETM+) with 30 m resolution acquired in 2001 and Landsat 8 acquired in 2013 with 30 m resolution, and Egypt sat acquired in 2010 with 7.8 m resolution, consequently were used. Four different supervised classification techniques (Maximum Likelihood (ML), Minimum Distance, Neural Networks (NN); and Support Vector Machine (SVM) were applied to monitor the changes of LULC in the investigated area. The results showed that the agricultural soils of the investigated area are characterized by high soil productivity depending on its chemical and physical properties. During 2010-2013, soil sealing took place on 1397 ha from the study area which characterized by soil productivity classes ranging between I and II. It is expected that the urban sprawl will be increased to 12.4% by 2020 from the study area, which means that additional 3400 ha of productive soils will be lost from agriculture. However, population growth is the most significant factor effecting urban sprawl in Nile Delta.

Potential future land use threats to California's protected areas

USGS Publications Warehouse

Wilson, Tamara Sue; Sleeter, Benjamin Michael; Davis, Adam Wilkinson

2015-01-01

Increasing pressures from land use coupled with future changes in climate will present unique challenges for California’s protected areas. We assessed the potential for future land use conversion on land surrounding existing protected areas in California’s twelve ecoregions, utilizing annual, spatially explicit (250 m) scenario projections of land use for 2006–2100 based on the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios to examine future changes in development, agriculture, and logging. We calculated a conversion threat index (CTI) for each unprotected pixel, combining land use conversion potential with proximity to protected area boundaries, in order to identify ecoregions and protected areas at greatest potential risk of proximal land conversion. Our results indicate that California’s Coast Range ecoregion had the highest CTI with competition for extractive logging placing the greatest demand on land in close proximity to existing protected areas. For more permanent land use conversions into agriculture and developed uses, our CTI results indicate that protected areas in the Central California Valley and Oak Woodlands are most vulnerable. Overall, the Eastern Cascades, Central California Valley, and Oak Woodlands ecoregions had the lowest areal percent of protected lands and highest conversion threat values. With limited resources and time, rapid, landscape-level analysis of potential land use threats can help quickly identify areas with higher conversion probability of future land use and potential changes to both habitat and potential ecosystem reserves. Given the broad range of future uncertainties, LULC projections are a useful tool allowing land managers to visualize alternative landscape futures, improve planning, and optimize management practices.

Hydrologic Simulation in Mediterranean flood prone Watersheds using high-resolution quality data

NASA Astrophysics Data System (ADS)

Eirini Vozinaki, Anthi; Alexakis, Dimitrios; Pappa, Polixeni; Tsanis, Ioannis

2015-04-01

Flooding is a significant threat causing lots of inconveniencies in several societies, worldwide. The fact that the climatic change is already happening, increases the flooding risk, which is no longer a substantial menace to several societies and their economies. The improvement of spatial-resolution and accuracy of the topography and land use data due to remote sensing techniques could provide integrated flood inundation simulations. In this work hydrological analysis of several historic flood events in Mediterranean flood prone watersheds (island of Crete/Greece) takes place. Satellite images of high resolution are elaborated. A very high resolution (VHR) digital elevation model (DEM) is produced from a GeoEye-1 0.5-m-resolution satellite stereo pair and is used for floodplain management and mapping applications such as watershed delineation and river cross-section extraction. Sophisticated classification algorithms are implemented for improving Land Use/ Land Cover maps accuracy. In addition, soil maps are updated with means of Radar satellite images. The above high-resolution data are innovatively used to simulate and validate several historical flood events in Mediterranean watersheds, which have experienced severe flooding in the past. The hydrologic/hydraulic models used for flood inundation simulation in this work are HEC-HMS and HEC-RAS. The Natural Resource Conservation Service (NRCS) curve number (CN) approach is implemented to account for the effect of LULC and soil on the hydrologic response of the catchment. The use of high resolution data provides detailed validation results and results of high precision, accordingly. Furthermore, the meteorological forecasting data, which are also combined to the simulation model results, manage the development of an integrated flood forecasting and early warning system tool, which is capable of confronting or even preventing this imminent risk. The research reported in this paper was fully supported by the "ARISTEIA II" Action ("REINFORCE" program) of the "Operational Education and Life Long Learning programme" and is co-funded by the European Social Fund (ESF) and National Resources.

The impact of urban morphology and land cover on the sensible heat flux retrieved by satellite and in-situ observations

NASA Astrophysics Data System (ADS)

Gawuc, L.; Łobocki, L.; Kaminski, J. W.

2017-12-01

Land surface temperature (LST) is a key parameter in various applications for urban environments research. However, remotely-sensed radiative surface temperature is not equivalent to kinetic nor aerodynamic surface temperature (Becker and Li, 1995; Norman and Becker, 1995). Thermal satellite observations of urban areas are also prone to angular anisotropy which is directly connected with the urban structure and relative sun-satellite position (Hu et al., 2016). Sensible heat flux (Qh) is the main component of surface energy balance in urban areas. Retrieval of Qh, requires observations of, among others, a temperature gradient. The lower level of temperature measurement is commonly replaced by remotely-sensed radiative surface temperature (Chrysoulakis, 2003; Voogt and Grimmond, 2000; Xu et al., 2008). However, such replacement requires accounting for the differences between aerodynamic and radiative surface temperature (Chehbouni et al., 1996; Sun and Mahrt, 1995). Moreover, it is important to avoid micro-scale processes, which play a major role in the roughness sublayer. This is due to the fact that Monin-Obukhov similarity theory is valid only in dynamic sublayer. We will present results of the analyses of the impact of urban morphology and land cover on the seasonal changes of sensible heat flux (Qh). Qh will be retrieved by two approaches. First will be based on satellite observations of radiative surface temperature and second will be based on in-situ observations of kinetic road temperature. Both approaches will utilize wind velocity, and air temperature observed in-situ. We will utilize time series of MODIS LST observations for the period of 2005-2014 as well as simultaneous in-situ observations collected by road weather network (9 stations). Ground stations are located across the city of Warsaw, outside the city centre in low-rise urban structure. We will account for differences in urban morphology and land cover in the proximity of ground stations. We will utilize DEM and Urban Atlas LULC database and freely available visible aerial and satellite imagery. All the analyses will be conducted for single pixels, which will be closest to the locations of the ground stations (nearest neighbour approach). Appropriate figures showing the seasonal variability of Qh will be presented.

Derivation of a GIS-based watershed-scale conceptual model for the St. Jones River Delaware from habitat-scale conceptual models.

PubMed

Reiter, Michael A; Saintil, Max; Yang, Ziming; Pokrajac, Dragoljub

2009-08-01

Conceptual modeling is a useful tool for identifying pathways between drivers, stressors, Valued Ecosystem Components (VECs), and services that are central to understanding how an ecosystem operates. The St. Jones River watershed, DE is a complex ecosystem, and because management decisions must include ecological, social, political, and economic considerations, a conceptual model is a good tool for accommodating the full range of inputs. In 2002, a Four-Component, Level 1 conceptual model was formed for the key habitats of the St. Jones River watershed, but since the habitat level of resolution is too fine for some important watershed-scale issues we developed a functional watershed-scale model using the existing narrowed habitat-scale models. The narrowed habitat-scale conceptual models and associated matrices developed by Reiter et al. (2006) were combined with data from the 2002 land use/land cover (LULC) GIS-based maps of Kent County in Delaware to assemble a diagrammatic and numerical watershed-scale conceptual model incorporating the calculated weight of each habitat within the watershed. The numerical component of the assembled watershed model was subsequently subjected to the same Monte Carlo narrowing methodology used for the habitat versions to refine the diagrammatic component of the watershed-scale model. The narrowed numerical representation of the model was used to generate forecasts for changes in the parameters "Agriculture" and "Forest", showing that land use changes in these habitats propagated through the results of the model by the weighting factor. Also, the narrowed watershed-scale conceptual model identified some key parameters upon which to focus research attention and management decisions at the watershed scale. The forecast and simulation results seemed to indicate that the watershed-scale conceptual model does lead to different conclusions than the habitat-scale conceptual models for some issues at the larger watershed scale.

Historical Maps Potential on the Assessment of the Hydromorphological Changes in Large Rivers: Towards Sustainable Rivers Management under Altered Flows

NASA Astrophysics Data System (ADS)

Kuriqi, Alban; Rosário Fernandes, M.; Santos, Artur; Ferreira, M. Teresa

2017-04-01

Hydromorphological patterns changes in large rivers, result from a long history of human interventions. In this study, we evaluate the causes and effects of hydromorphological alterations in the Iberian Minho River using a planform change analysis. We performed a temporal comparison using historical maps (nineteen century) and contemporaneous maps. The studied river was divided in 2.5 km long river stretches in a total of 25 sampling units. The historical maps were initially georeferenced for the WGS84 coordinate system. We used Geographic Information System (GIS) to extract the hydromorphological features and to store and organised the spatial data. The hydromorphological features (sinuosity index, braiding intensity, river corridor and active channel width, lotic and lentic habitats) were mapped by visual interpretation of the historical and the contemporaneous maps on a scale 1:2500 by applying the same methodology. Also, we analysed certain Indicators of Hydrological Alteration (IHA) based on pre- and post-dam daily streamflow data obtained from the Spanish Water Information System (SIA). The results revealed a significant reduction in the active channel width and all sinuosity indexes representing an overall degradation of river conditions. We also noticed a drastic diminution in the number and total area of lentic habitats causing fish habitat shifts. Changes were less evident in upstream sampling units due to diverse Land Use/Land Cover (LULC) changes combine with some geological constraints. These responses were consistent with reductions in mean annual discharge, flood disturbance decrease and minimum flow increase during the summer season. This work allows to understand the evolutionary trajectory of large fluvial system over more than 100 years and to implement concrete measures for sustainable river management. Keywords: historical maps, large rivers, flow alteration, sinuosity index, lotic and lentic habitats, regulated rivers, river restoration.

Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams

NASA Astrophysics Data System (ADS)

Strode, Georgianna; Mesev, Victor; Thornton, Benjamin; Jerez, Marjorie; Tricarico, Thomas; McAlear, Tyler

2018-05-01

The terms `land use' and `land cover' typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

The FORE-SCE model: a practical approach for projecting land cover change using scenario-based modeling

USGS Publications Warehouse

Sohl, Terry L.; Sayler, Kristi L.; Drummond, Mark A.; Loveland, Thomas R.

2007-01-01

A wide variety of ecological applications require spatially explicit, historic, current, and projected land use and land cover data. The U.S. Land Cover Trends project is analyzing contemporary (1973–2000) land-cover change in the conterminous United States. The newly developed FORE-SCE model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land cover change through 2020 for multiple plausible scenarios. Projected proportions of future land use were initially developed, and then sited on the lands with the highest potential for supporting that land use and land cover using a statistically based stochastic allocation procedure. Three scenarios of 2020 land cover were mapped for the western Great Plains in the US. The model provided realistic, high-resolution, scenario-based land-cover products suitable for multiple applications, including studies of climate and weather variability, carbon dynamics, and regional hydrology.

Interaction between Cities and Climate Change: Modelling Urban Morphology and Local Urban Planning Scenarios from Open Datasets across European Cities

NASA Astrophysics Data System (ADS)

Thomas, Bart; Stevens, Catherine; Grommen, Mart

2015-04-01

Cities are characterised by a large spatiotemporal diversity of local climates induced by a superposition of various factors and processes interacting at global and regional scales but also at the micro level such as the urban heat island effect. As urban areas are known as 'hot spots' prone to climate and its variability over time leading to changes in the severity and occurrence of extreme events such as heat waves, it is of crucial importance to capture the spatial heterogeneity resulting from variations in land use land cover (LULC) and urban morphology in an effective way to drive local urban climate simulations. The first part of the study conducted in the framework of the NACLIM FP7 project funded by the European Commission focusses on the extraction of land surface parameters linked to urban morphology characteristics from detailed 3D city models and their relationship with openly accessible European datasets such as the degree of soil sealing and disaggregated population densities from the European Environment Agency (EEA) and the Joint Research Centre (JRC). While it has been demonstrated that good correlations can be found between those datasets and the planar and frontal area indices, the present work has expanded the research to other urban morphology parameters including the average and variation of the building height and the sky view factor. Correlations up to 80% have been achieved depending on the considered parameter and the specific urban area including the cities of Antwerp (Belgium), Berlin (Germany) and Almada (Portugal) represented by different climate and urban characteristics. Moreover, the transferability of the established relations has been investigated across the various cities. Secondly, a flexible and scalable approach as a function of the required the level of detail has been elaborated to update the various morphology parameters in case of integration with urban planning data to analyse the local impact of future land use scenarios, climate adaptation strategies and mitigation measures in an effective way by comparing the future occupation of the soil against metrics derived from existing soil sealing data from the EEA.

Mapping Water Resources, Allocation and Consumption in the Mills River Basin

NASA Astrophysics Data System (ADS)

Hodes, J.; Jeuland, M. A.; Barros, A. P.

2014-12-01

Mountain basins and the headwaters of river basins along the foothills of major mountain ranges are undergoing rapid environmental change due to urban development, land acquisition by investors, population increase, and climate change. Classical water infrastructure in these regions is primarily designed to meet human water demand associated with agriculture, tourism, and economic development. Often overlooked and ignored is the fundamental interdependence of human water demand, ecosystem water demand, water rights and allocation, and water supply. A truly sustainable system for water resources takes into account ecosystem demand along with human infrastructure and economic demand, as well as the feedbacks that exist between them. Allocation policies need to take into account basin resilience that is the amount of stress the system can handle under varying future scenarios. Changes in stress on the system can be anthropogenic in the form of population increase, land use change, economic development, or may be natural in the form of climate change and decrease in water supply due to changes in precipitation. Mapping the water rights, supply, and demands within the basin can help determine the resiliency and sustainability of the basin. Here, we present a coupled natural human system project based in the French Broad River Basin, in the Southern Appalachians. In the first phase of the project, we are developing and implementing a coupled hydro-economics modeling framework in the Mills River Basin (MRB), a tributary of the French Broad. The Mills River Basin was selected as the core basin for implementing a sustainable system of water allocation that is adaptive and reflects the interdependence of water dependent sectors. The headwaters of the Mills River are in the foothills of the Appalachians, and are currently under substantial land use land cover (LULC) change pressure for agricultural purposes. In this regard, the MRB is representative of similar headwater basins in regions of complex terrain undergoing similar pressures such as the Andes and Himalayas. First results of the project including a quantitative organigram mapping water availability, water consumption, and the relationships among water stakeholders within the basin will be presented.

Earth observation for regional scale environmental and natural resources management

NASA Astrophysics Data System (ADS)

Bernknopf, R.; Brookshire, D.; Faulkner, S.; Chivoiu, B.; Bridge, B.; Broadbent, C.

2013-12-01

Earth observations (EO) provide critical information to natural resource assessment. Three examples are presented: conserving potable groundwater in intense agricultural regions, maximizing ecosystem service benefits at regional scales from afforestation investment and management, and enabling integrated natural and behavioral sciences for resource management and policy analysis. In each of these cases EO of different resolutions are used in different ways to help in the classification, characterization, and availability of natural resources and ecosystem services. To inform decisions, each example includes a spatiotemporal economic model to optimize the net societal benefits of resource development and exploitation. 1) EO is used for monitoring land use in intensively cultivated agricultural regions. Archival imagery is coupled to a hydrogeological process model to evaluate the tradeoff between agrochemical use and retention of potable groundwater. EO is used to couple individual producers and regional resource managers using information from markets and natural systems to aid in the objective of maximizing agricultural production and maintaining groundwater quality. The contribution of EO is input to a nitrate loading and transport model to estimate the cumulative impact on groundwater at specified distances from specific sites (wells) for 35 Iowa counties and two aquifers. 2) Land use/land cover (LULC) derived from EO is used to compare biological carbon sequestration alternatives and their provisioning of ecosystem services. EO is used to target land attributes that are more or less desirable for enhancing ecosystem services in two parishes in Louisiana. Ecological production functions are coupled with value data to maximize the expected return on investment in carbon sequestration and other ancillary ecosystem services while minimizing the risk. 3) Environmental and natural resources management decisions employ probabilistic estimates of yet-to-find or yet-to-develop volumes of natural and environmental resources and ecosystem services. The potential quantities of resources available are of great societal relevance, as are the resources that are necessarily disturbed in the development of economic reserves. EO is input to a multidimensional decision framework for natural resources and ecosystem services. Imagery supports a spatiotemporal model of regional resource extraction and the associated impacts on ecosystem services. The framework is used to assess societal tradeoffs by evaluating the benefits and costs of future development or preservation in a comparison of regional development options.

Spatiotemporal impacts of LULC changes on hydrology from the perspective of runoff generation mechanism using SWAT model with evolving parameters

NASA Astrophysics Data System (ADS)

Li, Y.; Chang, J.; Luo, L.

2017-12-01

It is of great importance for water resources management to model the truly hydrological process under changing environment, especially under significant changes of underlying surfaces like the Wei River Bain (WRB) where the subsurface hydrology is highly influenced by human activities, and to systematically investigate the interactions among LULC change, streamflow variation and changes in runoff generation process. Therefore, we proposed the idea of evolving parameters in hydrological model (SWAT) to reflect the changes in physical environment with different LULC conditions. Then with these evolving parameters, the spatiotemporal impacts of LULC changes on streamflow were quantified, and qualitative analysis was conducted to further explore how LULC changes affect the streamflow from the perspective of runoff generation mechanism. Results indicate the following: 1) evolving parameter calibration is not only effective but necessary to ensure the validity of the model when dealing with significant changes in underlying surfaces due to human activities. 2) compared to the baseline period, the streamflow in wet seasons increased in the 1990s but decreased in the 2000s. While at yearly and dry seasonal scales, the streamflow decreased in both two decades; 3) the expansion of cropland is the major contributor to the reduction of surface water component, thus causing the decline in streamflow at yearly and dry seasonal scales. While compared to the 1990s, the expansions of woodland in the middle stream and grassland in the downstream are the main stressors that increased the soil water component, thus leading to the more decline of the streamflow in the 2000s.

Developing an Ecosystem Services Online Decision Support Tool to Assess the Impacts of Climate Change and Urban Growth in the Santa Cruz Watershed: Where We Live, Work, and Play

USGS Publications Warehouse

Norman, Laura; Tallent-Halsell, Nita; Labiosa, William; Weber, Matt; McCoy, Amy; Hirschboeck, Katie; Callegary, James; van Riper, Charles; Gray, Floyd

2010-01-01

Using respective strengths of the biological, physical, and social sciences, we are developing an online decision support tool, the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM), to help promote the use of information relevant to water allocation and land management in a binational watershed along the U.S.-Mexico border. The SCWEPM will include an ES valuation system within a suite of linked regional driver-response models and will use a multicriteria scenario-evaluation framework that builds on GIS analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to climate patterns, regional water budgets, and regional LULC change in the SCW.

Consequences of land use and land cover change

USGS Publications Warehouse

Slonecker, E. Terrence; Barnes, Christopher; Karstensen, Krista; Milheim, Lesley E.; Roig-Silva, Coral M.

2013-01-01

The U.S. Geological Survey (USGS) Climate and Land Use Change Mission Area is one of seven USGS mission areas that focuses on making substantial scientific "...contributions to understanding how Earth systems interact, respond to, and cause global change". Using satellite and other remotely sensed data, USGS scientists monitor patterns of land cover change over space and time at regional, national, and global scales. These data are analyzed to understand the causes and consequences of changing land cover, such as economic impacts, effects on water quality and availability, the spread of invasive species, habitats and biodiversity, carbon fluctuations, and climate variability. USGS scientists are among the leaders in the study of land cover, which is a term that generally refers to the vegetation and artificial structures that cover the land surface. Examples of land cover include forests, grasslands, wetlands, water, crops, and buildings. Land use involves human activities that take place on the land. For example, "grass" is a land cover, whereas pasture and recreational parks are land uses that produce a cover of grass.

Yangon River Geomorphology Identification and its Enviromental Imapacts Analsysi by Optical and Radar Sensing Techniques

NASA Astrophysics Data System (ADS)

Lwin, A.; Khaing, M. M.

2012-07-01

The Yangon river, also known as the Rangoon river, is about 40 km long (25miles), and flows from southern Myanmar as an outlet of the Irrawaddy (Ayeyarwady) river into the Ayeyarwady delta. The Yangon river drains the Pegu Mountains; both the Yangon and the Pathein rivers enter the Ayeyarwady at the delta. Fluvial geomorphology is based primarily on rivers of manageable dimensions. The emphasis is on geomorphology, sedimentology of Yangon river and techniques for their identification and management. Present techniques such as remote sensing have made it easier to investigate and interpret in details analysis of river geomorphology. In this paper, attempt has been made the complicated issues of geomorphology, sedimentation patterns and management of river system and evolution studied. The analysis was carried out for the impact of land use/ land cover (LULC) changes on stream flow patterns. The hydrologic response to intense, flood producing rainfall events bears the signatures of the geomorphic structure of the channel network and of the characteristic slope lengths defining the drainage density of the basin. The interpretation of the hydrologic response as the travel time distribution of a water particle randomly injected in a distributed manner across the landscape inspired many geomorphic insights. In 2008, Cyclone Nargis was seriously damaged to mangrove area and its biodiversity system in and around of Yangon river terraces. A combination of digital image processing techniques was employed for enhancement and classification process. It is observed from the study that middle infra red band (0.77mm - 0.86mm) is highly suitable for mapping mangroves. Two major classes of mangroves, dense and open mangroves were delineated from the digital data.

Land cover characterization and mapping of South America for the year 2010 using Landsat 30 m satellite data

USGS Publications Warehouse

Giri, Chandra; Long, Jordan

2014-01-01

Detailed and accurate land cover and land cover change information is needed for South America because the continent is in constant flux, experiencing some of the highest rates of land cover change and forest loss in the world. The land cover data available for the entire continent are too coarse (250 m to 1 km) for resource managers, government and non-government organizations, and Earth scientists to develop conservation strategies, formulate resource management options, and monitor land cover dynamics. We used Landsat 30 m satellite data of 2010 and prepared the land cover database of South America using state-of-the-science remote sensing techniques. We produced regionally consistent and locally relevant land cover information by processing a large volume of data covering the entire continent. Our analysis revealed that in 2010, 50% of South America was covered by forests, 2.5% was covered by water, and 0.02% was covered by snow and ice. The percent forest area of South America varies from 9.5% in Uruguay to 96.5% in French Guiana. We used very high resolution (<5 m) satellite data to validate the land cover product. The overall accuracy of the 2010 South American 30-m land cover map is 89% with a Kappa coefficient of 79%. Accuracy of barren areas needs to improve possibly using multi-temporal Landsat data. An update of land cover and change database of South America with additional land cover classes is needed. The results from this study are useful for developing resource management strategies, formulating biodiversity conservation strategies, and regular land cover monitoring and forecasting.

Ecoregional differences in late-20th-century land-use and land-cover change in the U.S. northern great plains

USGS Publications Warehouse

Auch, Roger F.; Sayler, K. L.; Napton, D.E.; Taylor, Janis L.; Brooks, M.S.

2011-01-01

Land-cover and land-use change usually results from a combination of anthropogenic drivers and biophysical conditions found across multiple scales, ranging from parcel to regional levels. A group of four Level 111 ecoregions located in the U.S. northern Great Plains is used to demonstrate the similarities and differences in land change during nearly a 30-year period (1973-2000) using results from the U.S. Geological Survey's Land Cover Trends project. There were changes to major suites of land-cover; the transitions between agriculture and grassland/shrubland and the transitions among wetland, water, agriculture, and grassland/ shrubland were affected by different factors. Anthropogenic drivers affected the land-use tension (or land-use competition) between agriculture and grassland/shrubland land-covers, whereas changes between wetland and water land-covers, and their relationship to agriculture and grassland/shrubland land-covers, were mostly affected by regional weather cycles. More land-use tension between agriculture and grassland/shrubland landcovers occurred in ecoregions with greater amounts of economically marginal cropland. Land-cover change associated with weather variability occurred in ecoregions that had large concentrations of wetlands and water impoundments, such as the Missouri River reservoirs. The Northwestern Glaciated Plains ecoregion had the highest overall estimated percentage of change because it had both land-use tension between agriculture and grassland/shrubland land-covers and wetland-water changes. 

Land cover trends dataset, 1973-2000

USGS Publications Warehouse

Soulard, Christopher E.; Acevedo, William; Auch, Roger F.; Sohl, Terry L.; Drummond, Mark A.; Sleeter, Benjamin M.; Sorenson, Daniel G.; Kambly, Steven; Wilson, Tamara S.; Taylor, Janis L.; Sayler, Kristi L.; Stier, Michael P.; Barnes, Christopher A.; Methven, Steven C.; Loveland, Thomas R.; Headley, Rachel; Brooks, Mark S.

2014-01-01

The U.S. Geological Survey Land Cover Trends Project is releasing a 1973–2000 time-series land-use/land-cover dataset for the conterminous United States. The dataset contains 5 dates of land-use/land-cover data for 2,688 sample blocks randomly selected within 84 ecological regions. The nominal dates of the land-use/land-cover maps are 1973, 1980, 1986, 1992, and 2000. The land-use/land-cover maps were classified manually from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery using a modified Anderson Level I classification scheme. The resulting land-use/land-cover data has a 60-meter resolution and the projection is set to Albers Equal-Area Conic, North American Datum of 1983. The files are labeled using a standard file naming convention that contains the number of the ecoregion, sample block, and Landsat year. The downloadable files are organized by ecoregion, and are available in the ERDAS IMAGINETM (.img) raster file format.

Using the FORE-SCE model to project land-cover change in the southeastern United States

USGS Publications Warehouse

Sohl, Terry; Sayler, Kristi L.

2008-01-01

A wide variety of ecological applications require spatially explicit current and projected land-use and land-cover data. The southeastern United States has experienced massive land-use change since European settlement and continues to experience extremely high rates of forest cutting, significant urban development, and changes in agricultural land use. Forest-cover patterns and structure are projected to change dramatically in the southeastern United States in the next 50 years due to population growth and demand for wood products [Wear, D.N., Greis, J.G. (Eds.), 2002. Southern Forest Resource Assessment. General Technical Report SRS-53. U.S. Department of Agriculture, Forest Service, Southern Research Station, Asheville, NC, 635 pp]. Along with our climate partners, we are examining the potential effects of southeastern U.S. land-cover change on regional climate. The U.S. Geological Survey (USGS) Land Cover Trends project is analyzing contemporary (1973-2000) land-cover change in the conterminous United States, providing ecoregion-by-ecoregion estimates of the rates of change, descriptive transition matrices, and changes in landscape metrics. The FORecasting SCEnarios of future land-cover (FORE-SCE) model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land-cover change through 2050 for the southeastern United States. Prescriptions for future proportions of land cover for this application were provided by ecoregion-based extrapolations of historical change. Logistic regression was used to develop relationships between suspected drivers of land-cover change and land cover, resulting in the development of probability-of-occurrence surfaces for each unique land-cover type. Forest stand age was initially established with Forest Inventory and Analysis (FIA) data and tracked through model iterations. The spatial allocation procedure placed patches of new land cover on the landscape until the scenario prescriptions were met, using measured Land Cover Trends data to guide patch characteristics and the probability surfaces to guide placement. The approach provides an efficient method for extrapolating historical land-cover trends and is amenable to the incorporation of more detailed and focused studies for the establishment of scenario prescriptions.

Land-cover change and avian diversity in the conterminous United States

Treesearch

Chadwick D. Rittenhouse; Anna M. Pidgeon; Thomas P. Albright; Patrick D. Culbert; Murray K. Clayton; Curtis H. Flather; Jeffrey G. Masek; Volker C. Radeloff

2012-01-01

Changes in land use and land cover have affected and will continue to affect biological diversity worldwide. Yet, understanding the spatially extensive effects of land-cover change has been challenging because data that are consistent over space and time are lacking. We used the U.S. National Land Cover Dataset Land Cover Change Retrofit Product and North American...

Consequences of land-cover misclassification in models of impervious surface

USGS Publications Warehouse

McMahon, G.

2007-01-01

Model estimates of impervious area as a function of landcover area may be biased and imprecise because of errors in the land-cover classification. This investigation of the effects of land-cover misclassification on impervious surface models that use National Land Cover Data (NLCD) evaluates the consequences of adjusting land-cover within a watershed to reflect uncertainty assessment information. Model validation results indicate that using error-matrix information to adjust land-cover values used in impervious surface models does not substantially improve impervious surface predictions. Validation results indicate that the resolution of the landcover data (Level I and Level II) is more important in predicting impervious surface accurately than whether the land-cover data have been adjusted using information in the error matrix. Level I NLCD, adjusted for land-cover misclassification, is preferable to the other land-cover options for use in models of impervious surface. This result is tied to the lower classification error rates for the Level I NLCD. ?? 2007 American Society for Photogrammetry and Remote Sensing.

A global dataset of crowdsourced land cover and land use reference data.

PubMed

Fritz, Steffen; See, Linda; Perger, Christoph; McCallum, Ian; Schill, Christian; Schepaschenko, Dmitry; Duerauer, Martina; Karner, Mathias; Dresel, Christopher; Laso-Bayas, Juan-Carlos; Lesiv, Myroslava; Moorthy, Inian; Salk, Carl F; Danylo, Olha; Sturn, Tobias; Albrecht, Franziska; You, Liangzhi; Kraxner, Florian; Obersteiner, Michael

2017-06-13

Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general.

A global dataset of crowdsourced land cover and land use reference data

PubMed Central

Fritz, Steffen; See, Linda; Perger, Christoph; McCallum, Ian; Schill, Christian; Schepaschenko, Dmitry; Duerauer, Martina; Karner, Mathias; Dresel, Christopher; Laso-Bayas, Juan-Carlos; Lesiv, Myroslava; Moorthy, Inian; Salk, Carl F.; Danylo, Olha; Sturn, Tobias; Albrecht, Franziska; You, Liangzhi; Kraxner, Florian; Obersteiner, Michael

2017-01-01

Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general. PMID:28608851

Model of land cover change prediction in West Java using cellular automata-Markov chain (CA-MC)

NASA Astrophysics Data System (ADS)

Virtriana, Riantini; Sumarto, Irawan; Deliar, Albertus; Pasaribu, Udjianna S.; Taufik, Moh.

2015-04-01

Land is a fundamental factor that closely related to economic growth and supports the needs of human life. Land-use activity is a major issue and challenge for country planners. The cause of change in land use type activity may be due to socio economic development or due to changes in the environment or may be due to both. In an effort to understand the phenomenon of land cover changes, can be approached through land cover change modelling. Based on the facts and data contained, West Java has a high economic activity that will have an impact on land cover change. CA-MC is a model that used to determine the statistical change probabilistic for each of land cover type from land cover data at different time periods. CA-MC is able to provide the output of land cover type that should occurred. Results from a CA-MC modelling in predicting land cover changes showed an accuracy rate of 95.42%.

Regional Climate Effects of Aerosols Over South Asia: a Synthesis of Hybrid-Synergistic Analysis

NASA Astrophysics Data System (ADS)

Subba, T.; Gogoi, M. M.; Pathak, B.; Bhuyan, P. K.

2017-12-01

The south-Asian region faces formidable challenges in the accurate estimation of the aerosol-climate forcing due to the increasing demographic pressure and the rapid socio-economic growth which intensify the anthropogenic emissions causing degradation of regional air quality and climate. In this context, the present study employs a hybrid-method synergizing the aerosol data from ground-based measurements, satellite retrievals and radiative transfer simulations over the south-Asian region. The ground based aerosol and solar radiation data (2010-2015) are considered for nine selected locations of India as well as the adjoining Bay of Bengal representing distinct aerosol environment. The land use land cover (LULC) data from Indian remote sensing satellite (IRS-P6) is used to understand the association of aerosol environment with the change in the land surface pattern.The results indicate that the northern part, pre-dominantly the Indo-Gangetic plains (IGP) experiences the highest aerosol optical depth throughout the year. While the presence of dust plays a significant role in modifying the radiation balance over the west Asian region, extending to IGP; the highest Fire Radiative Power is observed over Eastern India ( 30 MW), the hotspot of biomass burning sources, followed by Central, South/West and Northern India. Considering the distinct source processes, incoming ground reaching fluxes are simulated using radiative transfer model, which showed a good correlation with the measured values (R2 0.97) with the mean bias errors between -40 to +7 Wm-2 (an overestimation of 2-4%). Estimated aerosol direct radiative forcing efficiency (DRFE) is highest over the eastern IGP due to heavy loading of long range transported aerosols from the arid region in the west, followed by the Himalayan foothills and west-Asian regions which are mostly dominated by agro-industrial and dust activities. However, a pristine high altitude location in the Western Ghats showed lower DRFE compared to north, with the values still higher than that over a marine location in the Andaman and Nicobar Island. The quantitative information of the dominating influence of anthropogenic aerosol sources over distinct regions of south Asia are useful for the improvement and validation of climate-model simulations over the region.

Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

NASA Astrophysics Data System (ADS)

Di Vittorio, A. V.; Mao, J.; Shi, X.; Chini, L.; Hurtt, G.; Collins, W. D.

2018-01-01

Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. Here we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO2 in 2004, and generates carbon uncertainty that is equivalent to 80% of the net effects of CO2 and climate and 124% of the effects of nitrogen deposition during 1850-2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. We conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.

Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

DOE PAGES

Di Vittorio, A. V.; Mao, J.; Shi, X.; ...

2018-01-03

Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. In this paper, we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO 2 in 2004, and generates carbon uncertainty that is equivalentmore » to 80% of the net effects of CO 2 and climate and 124% of the effects of nitrogen deposition during 1850–2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. Finally, we conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.« less

Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Di Vittorio, A. V.; Mao, J.; Shi, X.

Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. In this paper, we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO 2 in 2004, and generates carbon uncertainty that is equivalentmore » to 80% of the net effects of CO 2 and climate and 124% of the effects of nitrogen deposition during 1850–2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. Finally, we conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.« less

Simulating urban land cover changes at sub-pixel level in a coastal city

NASA Astrophysics Data System (ADS)

Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang

2014-10-01

The simulation of urban expansion or land cover changes is a major theme in both geographic information science and landscape ecology. Yet till now, almost all of previous studies were based on grid computations at pixel level. With the prevalence of spectral mixture analysis in urban land cover research, the simulation of urban land cover at sub-pixel level is being put into agenda. This study provided a new approach of land cover simulation at sub-pixel level. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover data through supervised classification. Then the two classified land cover data were utilized to extract the transformation rule between 2002 and 2007 using logistic regression. The transformation possibility of each land cover type in a certain pixel was taken as its percent in the same pixel after normalization. And cellular automata (CA) based grid computation was carried out to acquire simulated land cover on 2007. The simulated 2007 sub-pixel land cover was testified with a validated sub-pixel land cover achieved by spectral mixture analysis in our previous studies on the same date. And finally the sub-pixel land cover of 2017 was simulated for urban planning and management. The results showed that our method is useful in land cover simulation at sub-pixel level. Although the simulation accuracy is not quite satisfactory for all the land cover types, it provides an important idea and a good start in the CA-based urban land cover simulation.

Specifications for updating USGS land use and land cover maps

USGS Publications Warehouse

Milazzo, Valerie A.

1983-01-01

To meet the increasing demands for up-to-date land use and land cover information, a primary goal of the U.S. Geological Survey's (USGS) national land use and land cover mapping program is to provide for periodic updating of maps and data in a timely and uniform manner. The technical specifications for updating existing USGS land use and land cover maps that are presented here cover both the interpretive aspects of detecting and identifying land use and land cover changes and the cartographic aspects of mapping and presenting the change data in conventional map format. They provide the map compiler with the procedures and techniques necessary to then use these change data to update existing land use and land cover maps in a manner that is both standardized and repeatable. Included are specifications for the acquisition of remotely sensed source materials, selection of compilation map bases, handling of data base corrections, editing and quality control operations, generation of map update products for USGS open file, and the reproduction and distribution of open file materials. These specifications are planned to become part of the National Mapping Division's Technical Instructions.

Land use and land cover data changes in Indian Ocean Islands: Case study of Unguja in Zanzibar Island.

PubMed

Mwalusepo, Sizah; Muli, Eliud; Faki, Asha; Raina, Suresh

2017-04-01

Land use and land cover changes will continue to affect resilient human communities and ecosystems as a result of climate change. However, an assessment of land use and land cover changes over time in Indian Ocean Islands is less documented. The land use/cover data changes over 10 years at smaller geographical scale across Unguja Island in Zanzibar were analyzed. Downscaling of the data was obtained from SERVIR through partnership with Kenya-based Regional Centre for Mapping of Resources for Development (RCMRD) database (http://www.servirglobal.net), and clipped down in ArcMap (Version 10.1) to Unguja Island. SERVIR and RCMRD Land Cover Dataset are mainly 30 m multispectral images include Landsat TM and ETM+Multispectral Images. Landscape ecology Statistics tool (LecoS) was used to analysis the land use and land cover changes. The data provide information on the status of the land use and land cover changes along the Unguja Island in Zanzibar. The data is of great significance to the future research on global change.

West Africa land use and land cover time series

USGS Publications Warehouse

Cotillon, Suzanne E.

2017-02-16

Started in 1999, the West Africa Land Use Dynamics project represents an effort to map land use and land cover, characterize the trends in time and space, and understand their effects on the environment across West Africa. The outcome of the West Africa Land Use Dynamics project is the production of a three-time period (1975, 2000, and 2013) land use and land cover dataset for the Sub-Saharan region of West Africa, including the Cabo Verde archipelago. The West Africa Land Use Land Cover Time Series dataset offers a unique basis for characterizing and analyzing land changes across the region, systematically and at an unprecedented level of detail.

Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual

USGS Publications Warehouse

Cotillon, Suzanne E.; Mathis, Melissa L.

2017-02-15

The Rapid Land Cover Mapper is an Esri ArcGIS® Desktop add-in, which was created as an alternative to automated or semiautomated mapping methods. Based on a manual photo interpretation technique, the tool facilitates mapping over large areas and through time, and produces time-series raster maps and associated statistics that characterize the changing landscapes. The Rapid Land Cover Mapper add-in can be used with any imagery source to map various themes (for instance, land cover, soils, or forest) at any chosen mapping resolution. The user manual contains all essential information for the user to make full use of the Rapid Land Cover Mapper add-in. This manual includes a description of the add-in functions and capabilities, and step-by-step procedures for using the add-in. The Rapid Land Cover Mapper add-in was successfully used by the U.S. Geological Survey West Africa Land Use Dynamics team to accurately map land use and land cover in 17 West African countries through time (1975, 2000, and 2013).

Comparison of two Classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia

NASA Astrophysics Data System (ADS)

Rokni Deilmai, B.; Ahmad, B. Bin; Zabihi, H.

2014-06-01

Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification.

Assessing the predictability of fire occurrence and area burned across phytoclimatic regions in Spain

NASA Astrophysics Data System (ADS)

Bedia, J.; Herrera, S.; Gutiérrez, J. M.

2014-01-01

Most fire protection agencies throughout the world have developed forest fire risk forecast systems, usually building upon existing fire danger indices and meteorological forecast data. In this context, the daily predictability of wildfires is of utmost importance in order to allow the fire protection agencies to issue timely fire hazard alerts. In this study, we address the predictability of daily fire occurrence using the components of the Canadian Fire Weather Index (FWI) System and related variables calculated from the latest ECMWF (European Centre for Medium Range Weather Forecasts) reanalysis, ERA-Interim. We develop daily fire occurrence models in peninsular Spain for the period 1990-2008 and, considering different minimum burned area thresholds for fire definition, assess their ability to reproduce the inter-annual fire frequency variability. We based the analysis on a phytoclimatic classification aiming the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climate/fuel conditions. We then extend the analysis in order to assess the predictability of monthly burned areas. The sensitivity of the models to the level of spatial aggregation of the data is also evaluated. Additionally, we investigate the gain in model performance with the inclusion of socioeconomic and land use/land cover (LULC) covariates in model formulation. Fire occurrence models have attained good performance in most of the phytoclimatic zones considered, being able to faithfully reproduce the inter-annual variability of fire frequency. Total area burned has exhibited some dependence on the meteorological drivers, although model performance was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, highlighting the adequacy of the FWI system for fire occurrence prediction in the study area. The results were improved when using aggregated data across regions compared to when data were sampled at the grid-box level. The inclusion of socioeconomic and LULC covariates contributed marginally to the improvement of the models, and in most cases attained no relevant contribution to total explained variance - excepting northern Spain, where anthropogenic factors are known to be the major driver of fires. Models of monthly fire counts performed better in the case of fires larger than 0.1 ha, and for the rest of the thresholds (1, 10 and 100 ha) the daily occurrence models improved the predicted inter-annual variability, indicating the added value of daily models. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as a response variable. Our results leave the door open to the development a more complex modelling framework based on daily data from numerical climate model outputs based on the FWI system.

LAND COVER ASSESSMENT OF INDIGENOUS COMMUNITIES IN THE BOSAWAS REGION OF NICARAGUA

EPA Science Inventory

Data derived from remotely sensed images were utilized to conduct land cover assessments of three indigenous communities in northern Nicaragua. Historical land use, present land cover and land cover change processes were all identified through the use of a geographic informat...

Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis

USGS Publications Warehouse

Sharpe, Jennifer B.; Soong, David T.

2015-01-01

This study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.

Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

NASA Astrophysics Data System (ADS)

Ban, Yifang; Gong, Peng; Giri, Chandra

2015-05-01

Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.

Regional land cover characterization using Landsat thematic mapper data and ancillary data sources

USGS Publications Warehouse

Vogelmann, James E.; Sohl, Terry L.; Campbell, P.V.; Shaw, D.M.; ,

1998-01-01

As part of the activities of the Multi-Resolution Land Characteristics (MRLC) Interagency Consortium, an intermediate-scale land cover data set is being generated for the conterminous United States. This effort is being conducted on a region-by-region basis using U.S. Standard Federal Regions. To date, land cover data sets have been generated for Federal Regions 3 (Pennsylvania, West Virginia, Virginia, Maryland, and Delaware) and 2 (New York and New Jersey). Classification work is currently under way in Federal Region 4 (the southeastern United States), and land cover mapping activities have been started in Federal Regions 5 (the Great Lakes region) and 1 (New England). It is anticipated that a land cover data set for the conterminous United States will be completed by the end of 1999. A standard land cover classification legend is used, which is analogous to and compatible with other classification schemes. The primary MRLC regional classification scheme contains 23 land cover classes.The primary source of data for the project is the Landsat thematic mapper (TM) sensor. For each region, TM scenes representing both leaf-on and leaf-off conditions are acquired, preprocessed, and georeferenced to MRLC specifications. Mosaicked data are clustered using unsupervised classification, and individual clusters are labeled using aerial photographs. Individual clusters that represent more than one land cover unit are split using spatial modeling with multiple ancillary spatial data layers (most notably, digital elevation model, population, land use and land cover, and wetlands information). This approach yields regional land cover information suitable for a wide array of applications, including landscape metric analyses, land management, land cover change studies, and nutrient and pesticide runoff modeling.

Research priorities in land use and land-cover change for the Earth system and integrated assessment modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hibbard, Kathleen A.; Janetos, Anthony C.; Van Vuuren, Detlef

2010-11-15

This special issue has highlighted recent and innovative methods and results that integrate observations and AQ3 modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated Assessment modeling communities recognize the importance of an accurate representation of land use and land-cover change to understand and quantify the interactions and feedbacks with the climate and socio-economic systems, respectively. To date, cooperation between these communities has been limited. Based on common interests, this work discusses research priorities in representing land use and land-cover change for improvedmore » collaboration across modelling, observing and measurement communities. Major research topics in land use and land-cover change are those that help us better understand (1) the interaction of land use and land cover with the climate system (e.g. carbon cycle feedbacks), (2) the provision of goods and ecosystem services by terrestrial (natural and anthropogenic) land-cover types (e.g. food production), (3) land use and management decisions and (4) opportunities and limitations for managing climate change (for both mitigation and adaptation strategies).« less

Commentary: A cautionary tale regarding use of the National Land Cover Dataset 1992

USGS Publications Warehouse

Thogmartin, Wayne E.; Gallant, Alisa L.; Knutson, Melinda G.; Fox, Timothy J.; Suarez, Manuel J.

2004-01-01

Digital land-cover data are among the most popular data sources used in ecological research and natural resource management. However, processes for accurate land-cover classification over large regions are still evolving. We identified inconsistencies in the National Land Cover Dataset 1992, the most current and available representation of land cover for the conterminous United States. We also report means to address these inconsistencies in a bird-habitat model. We used a Geographic Information System (GIS) to position a regular grid (or lattice) over the upper midwestern United States and summarized the proportion of individual land covers in each cell within the lattice. These proportions were then mapped back onto the lattice, and the resultant lattice was compared to satellite paths, state borders, and regional map classification units. We observed mapping inconsistencies at the borders between mapping regions, states, and Thematic Mapper (TM) mapping paths in the upper midwestern United States, particularly related to grass I and-herbaceous, emergent-herbaceous wetland, and small-grain land covers. We attributed these discrepancies to differences in image dates between mapping regions, suboptimal image dates for distinguishing certain land-cover types, lack of suitable ancillary data for improving discrimination for rare land covers, and possibly differences among image interpreters. To overcome these inconsistencies for the purpose of modeling regional populations of birds, we combined grassland-herbaceous and pasture-hay land-cover classes and excluded the use of emergent-herbaceous and small-grain land covers. We recommend that users of digital land-cover data conduct similar assessments for other regions before using these data for habitat evaluation. Further, caution is advised in using these data in the analysis of regional land-cover change because it is not likely that future digital land-cover maps will repeat the same problems, thus resulting in biased estimates of change.

Comparing Minnesota land cover/use area estimates using NRI and FIA data

Treesearch

Veronica C. Lessard; Mark H. Hansen; Mark D. Nelson

2002-01-01

Areas for land cover/use categories on non-Federal land in Minnesota were estimated from Forest Inventory and Analysis (FIA) data and National Resources Inventory (NRI) data. Six common land cover/use categories were defined, and the NRI and FIA land cover/use categories were assigned to them. Area estimates for these categories were calculated from the FIA and NRI...

Reconstructed Historical Land Cover and Biophysical Parameters for Studies of Land-Atmosphere Interactions within the Eastern United States

NASA Technical Reports Server (NTRS)

Steyaert, Louis T.; Knox, Robert G.

2007-01-01

The local environment where we live within the Earth's biosphere is often taken for granted. This environment can vary depending on whether the land cover is a forest, grassland, wetland, water body, bare soil, pastureland, agricultural field, village, residential suburb, or an urban complex with concrete, asphalt, and large buildings. In general, the type and characteristics of land cover influence surface temperatures, sunlight exposure and duration, relative humidity, wind speed and direction, soil moisture amount, plant life, birds, and other wildlife in our backyards. The physical and biological properties (biophysical characteristics) of land cover help to determine our surface environment because they directly affect surface radiation, heat, and soil moisture processes, and also feedback to regional weather and climate. Depending on the spatial scale and land use intensity, land cover changes can have profound impacts on our local and regional environment. Over the past 350 years, the eastern half of the United States, an area extending from the grassland prairies of the Great Plains to the Gulf and Atlantic coasts, has experienced extensive land cover and land use changes that began with land clearing in the 1600s, led to extensive deforestation and intensive land use practices by 1920, and then evolved to the present-day landscape. Determining the consequences of such land cover changes on regional and global climate is a major research issue. Such research requires detailed historical land cover data and modeling experiments simulating historical climates. Given the need to understand the effects of historical land cover changes in the eastern United States, some questions include: - What were the most important land cover transformations and how did they alter biophysical characteristics of the land cover at key points in time since the mid-1600s? - How have land cover and land use changes over the past 350 years affected the land surface environment including surface weather, hydrologic, and climatic variability? - How do the potential effects of regional human-induced land cover change on the environment compare to similar changes that are caused by the natural variations of the Earth's climate system? To help answer these questions, we reconstructed a fractional land cover and biophysical parameter dataset for the eastern United States at 1650, 1850, 1920, and 1992 time-slices. Each land cover fraction is associated with a biophysical parameter class, a suite of parameters defining the biophysical characteristics of that kind of land cover. This new dataset is designed for use in computer models of land-atmosphere interactions, to understand and quantify the effects of historical land cover changes on the water, energy, and carbon cycles

Comprehensive data set of global land cover change for land surface model applications

NASA Astrophysics Data System (ADS)

Sterling, Shannon; Ducharne, AgnèS.

2008-09-01

To increase our understanding of how humans have altered the Earth's surface and to facilitate land surface modeling experiments aimed to elucidate the direct impact of land cover change on the Earth system, we create and analyze a database of global land use/cover change (LUCC). From a combination of sources including satellite imagery and other remote sensing, ecological modeling, and country surveys, we adapt and synthesize existing maps of potential land cover and layers of the major anthropogenic land covers, including a layer of wetland loss, that are then tailored for land surface modeling studies. Our map database shows that anthropogenic land cover totals to approximately 40% of the Earth's surface, consistent with literature estimates. Almost all (92%) of the natural grassland on the Earth has been converted to human use, mostly grazing land, and the natural temperate savanna with mixed C3/C4 is almost completely lost (˜90%), due mostly to conversion to cropland. Yet the resultant change in functioning, in terms of plant functional types, of the Earth system from land cover change is dominated by a loss of tree cover. Finally, we identify need for standardization of percent bare soil for global land covers and for a global map of tree plantations. Estimates of land cover change are inherently uncertain, and these uncertainties propagate into modeling studies of the impact of land cover change on the Earth system; to begin to address this problem, modelers need to document fully areas of land cover change used in their studies.

Seasonal land-cover regions of the United States

USGS Publications Warehouse

Loveland, Thomas R.; Merchant, James W.; Brown, Jesslyn F.; Ohlen, Donald O.; Reed, Bradley C.; Olson, Paul; Hutchinson, John

1995-01-01

Global-change investigations have been hindered by deficiencies in the availability and quality of land-cover data. The U.S. Geological Survey and the University of Nebraska-Lincoln have collaborated on the development of a new approach to land-cover characterization that attempts to address requirements of the global-change research community and others interested in regional patterns of land cover. An experimental 1 -kilometer-resolution database of land-cover characteristics for the coterminous U.S. has been prepared to test and evaluate the approach. Using multidate Advanced Very High Resolution Radiometer (AVHRR) satellite data complemented by elevation, climate, ecoregions, and other digital spatial datasets, the authors define 152, seasonal land-cover regions. The regionalization is based on a taxonomy of areas with respect to data on land cover, seasonality or phenology, and relative levels of primary production. The resulting database consists of descriptions of the vegetation, land cover, and seasonal, spectral, and site characteristics for each region. These data are used in the construction of an illustrative 1:7,500,000-scaIe map of the seasonal land-cover regions as well as of smaller-scale maps portraying general land cover and seasonality. The seasonal land-cover characteristics database can also be tailored to provide a broad range of other landscape parameters useful in national and global-scale environmental modeling and assessment.

Spatiotemporal dynamics of LUCC from 2001 to 2010 in Yunnan Province, China

NASA Astrophysics Data System (ADS)

Li, Z. J.; Yu, J. S.; Yao, X. L.; Chen, X.; Li, Z. L.

2016-08-01

LUCC (Land use and land cover change) is increasingly regarded as an important component of global environmental change and sustainable development. In this study, regional land cover type maps were drawn using the MODIS products from 2001 and 2010 based on the modified classification scheme embodied by the characteristics of land cover in Yunnan. Dynamic change in each type of land cover was investigated by classification statistics, dynamic transfer matrices, and landscape pattern metrics. In addition, the driving factors of LUCC were discussed. The results showed that the land cover types of the Yunnan province, especially woodland (WL), cropland (CL) and grassland (GL), had experienced noticeable changes with an area of about 30% of land during the study period. And there was an obvious vertical distribution pattern for land cover types. The average altitude of different land cover types from the highest to the lowest were unused land (UUT), WL, GL, water (WT), urban and built-up areas (UB) and CL. The average slope for most of the land-cover types did not vary over the past 10 years. Stabilization and homogenization will be the direction of land cover in the future according to landscape metrics analysis. The regional differences of land use structure in the area are strongly influenced by such factors as the geographical position, level of economic development and land use policy. The new policy of land use, Construction of Mountainous Town, would be provided to achieve the economical and intensive utilization of land resources during the rapid development of urbanization and industrialization in Yunnan.

Relationships between aerodynamic roughness and land use and land cover in Baltimore, Maryland

USGS Publications Warehouse

Nicholas, F.W.; Lewis, J.E.

1980-01-01

Urbanization changes the radiative, thermal, hydrologic, and aerodynamic properties of the Earth's surface. Knowledge of these surface characteristics, therefore, is essential to urban climate analysis. Aerodynamic or surface roughness of urban areas is not well documented, however, because of practical constraints in measuring the wind profile in the presence of large buildings. Using an empirical method designed by Lettau, and an analysis of variance of surface roughness values calculated for 324 samples averaging 0.8 hectare (ha) of land use and land cover sample in Baltimore, Md., a strong statistical relation was found between aerodynamic roughness and urban land use and land cover types. Assessment of three land use and land cover systems indicates that some of these types have significantly different surface roughness characteristics. The tests further indicate that statistically significant differences exist in estimated surface roughness values when categories (classes) from different land use and land cover classification systems are used as surrogates. A Level III extension of the U.S. Geological Survey Level II land use and land cover classification system provided the most reliable results. An evaluation of the physical association between the aerodynamic properties of land use and land cover and the surface climate by numerical simulation of the surface energy balance indicates that changes in surface roughness within the range of values typical of the Level III categories induce important changes in the surface climate.

Land cover mapping of Greater Mesoamerica using MODIS data

USGS Publications Warehouse

Giri, Chandra; Jenkins, Clinton N.

2005-01-01

A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed

USGS Publications Warehouse

2011-01-01

Trends derived from multitemporal land-cover data can be used to make informed land management decisions and to help managers model future change scenarios. We developed a multitemporal land-use/land-cover dataset for the binational Santa Cruz watershed of southern Arizona, United States, and northern Sonora, Mexico by creating a series of land-cover maps at decadal intervals (1979, 1989, 1999, and 2009) using Landsat Multispectral Scanner and Thematic Mapper data and a classification and regression tree classifier. The classification model exploited phenological changes of different land-cover spectral signatures through the use of biseasonal imagery collected during the (dry) early summer and (wet) late summer following rains from the North American monsoon. Landsat images were corrected to remove atmospheric influences, and the data were converted from raw digital numbers to surface reflectance values. The 14-class land-cover classification scheme is based on the 2001 National Land Cover Database with a focus on "Developed" land-use classes and riverine "Forest" and "Wetlands" cover classes required for specific watershed models. The classification procedure included the creation of several image-derived and topographic variables, including digital elevation model derivatives, image variance, and multitemporal Kauth-Thomas transformations. The accuracy of the land-cover maps was assessed using a random-stratified sampling design, reference aerial photography, and digital imagery. This showed high accuracy results, with kappa values (the statistical measure of agreement between map and reference data) ranging from 0.80 to 0.85.

A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011

USGS Publications Warehouse

Jin, Suming; Yang, Limin; Zhu, Zhe; Homer, Collin G.

2017-01-01

Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD from 2001 to 2011 and provide a 10-year cyclical update of the state's land cover and land cover changes. Our method is designed to characterize the main land cover changes associated with different drivers, including the conversion of forests to shrub and grassland primarily as a result of wildland fire and forest harvest, the vegetation successional processes after disturbance, and changes of surface water extent and glacier ice/snow associated with weather and climate changes. For natural vegetated areas, a component named AKUP11-VEG was developed for updating the land cover that involves four major steps: 1) identify the disturbed and successional areas using Landsat images and ancillary datasets; 2) update the land cover status for these areas using a SKILL model (System of Knowledge-based Integrated-trajectory Land cover Labeling); 3) perform decision tree classification; and 4) develop a final land cover and land cover change product through the postprocessing modeling. For water and ice/snow areas, another component named AKUP11-WIS was developed for initial land cover change detection, removal of the terrain shadow effects, and exclusion of ephemeral snow changes using a 3-year MODIS snow extent dataset from 2010 to 2012. The overall approach was tested in three pilot study areas in Alaska, with each area consisting of four Landsat image footprints. The results from the pilot study show that the overall accuracy in detecting change and no-change is 90% and the overall accuracy of the updated land cover label for 2011 is 86%. The method provided a robust, consistent, and efficient means for capturing major disturbance events and updating land cover for Alaska. The method has subsequently been applied to generate the land cover and land cover change products for the entire state of Alaska.

Land-Cover Change in the East Central Texas Plains, 1973-2000

USGS Publications Warehouse

Karstensen, Krista A.

2009-01-01

Project Background: The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-use and land-cover change. The objectives of the study are to: (1) develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) data for measuring regional land-cover change across the United States, (2) characterize the types, rates and temporal variability of change for a 30-year period, (3) document regional driving forces and consequences of change, and (4) prepare a national synthesis of land-cover change (Loveland and others, 1999). Using the 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) as the geographic framework, geospatial data collected between 1973 and 2000 were processed and analyzed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000. General land-cover classes such as water, developed, grassland/shrubland, and agriculture for these periods were interpreted from Landsat MSS, TM, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land-Use Land-Cover Classification System for image interpretation. The interpretation of these land-cover classes complement the program objective of looking at land-use change with cover serving as a surrogate for land use. The land-cover change rates are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. For example, the scalar statistics can show the spatial extent of change per cover type with time, as well as the land-cover transformations from one land-cover type to another type occurring with time. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional observations of the character and condition of the landscape, assistance in sample block interpretation, ground truthing of Landsat imagery, and helps determine the driving forces of change identified in an ecoregion. Management and maintenance of field data, beyond initial use for training and validation of image classifications, is important as improved methods for image classification are developed, and as present-day data become part of the historical legacy for which studies of land-cover change in the future will depend (Loveland and others, 2002). The results illustrate that there is no single profile of land-cover change; instead, there is significant geographic variability that results from land uses within ecoregions continuously adapting to the resource potential created by various environmental, technological, and socioeconomic factors.

Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS

NASA Astrophysics Data System (ADS)

Tehrany, Mahyat Shafapour; Pradhan, Biswajeet; Jebur, Mustafa Neamah

2014-05-01

Flood is one of the most devastating natural disasters that occur frequently in Terengganu, Malaysia. Recently, ensemble based techniques are getting extremely popular in flood modeling. In this paper, weights-of-evidence (WoE) model was utilized first, to assess the impact of classes of each conditioning factor on flooding through bivariate statistical analysis (BSA). Then, these factors were reclassified using the acquired weights and entered into the support vector machine (SVM) model to evaluate the correlation between flood occurrence and each conditioning factor. Through this integration, the weak point of WoE can be solved and the performance of the SVM will be enhanced. The spatial database included flood inventory, slope, stream power index (SPI), topographic wetness index (TWI), altitude, curvature, distance from the river, geology, rainfall, land use/cover (LULC), and soil type. Four kernel types of SVM (linear kernel (LN), polynomial kernel (PL), radial basis function kernel (RBF), and sigmoid kernel (SIG)) were used to investigate the performance of each kernel type. The efficiency of the new ensemble WoE and SVM method was tested using area under curve (AUC) which measured the prediction and success rates. The validation results proved the strength and efficiency of the ensemble method over the individual methods. The best results were obtained from RBF kernel when compared with the other kernel types. Success rate and prediction rate for ensemble WoE and RBF-SVM method were 96.48% and 95.67% respectively. The proposed ensemble flood susceptibility mapping method could assist researchers and local governments in flood mitigation strategies.

Change detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm

Treesearch

Kathleen M. Bergen; Daniel G. Brown; James F. Rutherford; Eric J. Gustafson

2005-01-01

A ca. 1980 national-scale land-cover classification based on aerial photo interpretation was combined with 2000 AVHRR satellite imagery to derive land cover and land-cover change information for forest, urban, and agriculture categories over a seven-state region in the U.S. To derive useful land-cover change data using a heterogeneous dataset and to validate our...

The effects of changing land cover on streamflow simulation in Puerto Rico

USGS Publications Warehouse

Van Beusekom, Ashley E.; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad

2014-01-01

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

Beyond Impervious: Urban Land-Cover Pattern Variation and Implications for Watershed Management

NASA Astrophysics Data System (ADS)

Beck, Scott M.; McHale, Melissa R.; Hess, George R.

2016-07-01

Impervious surfaces degrade urban water quality, but their over-coverage has not explained the persistent water quality variation observed among catchments with similar rates of imperviousness. Land-cover patterns likely explain much of this variation, although little is known about how they vary among watersheds. Our goal was to analyze a series of urban catchments within a range of impervious cover to evaluate how land-cover varies among them. We then highlight examples from the literature to explore the potential effects of land-cover pattern variability for urban watershed management. High-resolution (1 m2) land-cover data were used to quantify 23 land-cover pattern and stormwater infrastructure metrics within 32 catchments across the Triangle Region of North Carolina. These metrics were used to analyze variability in land-cover patterns among the study catchments. We used hierarchical clustering to organize the catchments into four groups, each with a distinct landscape pattern. Among these groups, the connectivity of combined land-cover patches accounted for 40 %, and the size and shape of lawns and buildings accounted for 20 %, of the overall variation in land-cover patterns among catchments. Storm water infrastructure metrics accounted for 8 % of the remaining variation. Our analysis demonstrates that land-cover patterns do vary among urban catchments, and that trees and grass (lawns) are divergent cover types in urban systems. The complex interactions among land-covers have several direct implications for the ongoing management of urban watersheds.

Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watershed

NASA Astrophysics Data System (ADS)

Saran, Sameer; Sterk, Geert; Kumar, Suresh

2009-10-01

Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into HRU's requires good-quality spatial data on land use/land cover. This paper presents different approaches to attain an optimal land use/land cover map based on remote sensing imagery for a Himalayan watershed in northern India. First digital classifications using maximum likelihood classifier (MLC) and a decision tree classifier were applied. The results obtained from the decision tree were better and even improved after post classification sorting. But the obtained land use/land cover map was not sufficient for the delineation of HRUs, since the agricultural land use/land cover class did not discriminate between the two major crops in the area i.e. paddy and maize. Subsequently the digital classification on fused data (ASAR and ASTER) were attempted to map land use/land cover classes with emphasis to delineate the paddy and maize crops but the supervised classification over fused datasets did not provide the desired accuracy and proper delineation of paddy and maize crops. Eventually, we adopted a visual classification approach on fused data. This second step with detailed classification system resulted into better classification accuracy within the 'agricultural land' class which will be further combined with topography and soil type to derive HRU's for physically-based hydrological modeling.

A higher order conditional random field model for simultaneous classification of land cover and land use

NASA Astrophysics Data System (ADS)

Albert, Lena; Rottensteiner, Franz; Heipke, Christian

2017-08-01

We propose a new approach for the simultaneous classification of land cover and land use considering spatial as well as semantic context. We apply a Conditional Random Fields (CRF) consisting of a land cover and a land use layer. In the land cover layer of the CRF, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Intra-layer edges of the CRF model spatial dependencies between neighbouring image sites. All spatially overlapping sites in both layers are connected by inter-layer edges, which leads to higher order cliques modelling the semantic relation between all land cover and land use sites in the clique. A generic formulation of the higher order potential is proposed. In order to enable efficient inference in the two-layer higher order CRF, we propose an iterative inference procedure in which the two classification tasks mutually influence each other. We integrate contextual relations between land cover and land use in the classification process by using contextual features describing the complex dependencies of all nodes in a higher order clique. These features are incorporated in a discriminative classifier, which approximates the higher order potentials during the inference procedure. The approach is designed for input data based on aerial images. Experiments are carried out on two test sites to evaluate the performance of the proposed method. The experiments show that the classification results are improved compared to the results of a non-contextual classifier. For land cover classification, the result is much more homogeneous and the delineation of land cover segments is improved. For the land use classification, an improvement is mainly achieved for land use objects showing non-typical characteristics or similarities to other land use classes. Furthermore, we have shown that the size of the super-pixels has an influence on the level of detail of the classification result, but also on the degree of smoothing induced by the segmentation method, which is especially beneficial for land cover classes covering large, homogeneous areas.

Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods

USGS Publications Warehouse

Xian, George; Homer, Collin G.; Fry, Joyce

2009-01-01

The recent release of the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001, which represents the nation's land cover status based on a nominal date of 2001, is widely used as a baseline for national land cover conditions. To enable the updating of this land cover information in a consistent and continuous manner, a prototype method was developed to update land cover by an individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season in 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, land cover classifications at the full NLCD resolution for 2006 areas of change were completed by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain several metropolitan areas including Seattle, Washington; San Diego, California; Sioux Falls, South Dakota; Jackson, Mississippi; and Manchester, New Hampshire. Results from the five study areas show that the vast majority of land cover change was captured and updated with overall land cover classification accuracies of 78.32%, 87.5%, 88.57%, 78.36%, and 83.33% for these areas. The method optimizes mapping efficiency and has the potential to provide users a flexible method to generate updated land cover at national and regional scales by using NLCD 2001 as the baseline.

An Iterative Inference Procedure Applying Conditional Random Fields for Simultaneous Classification of Land Cover and Land Use

NASA Astrophysics Data System (ADS)

Albert, L.; Rottensteiner, F.; Heipke, C.

2015-08-01

Land cover and land use exhibit strong contextual dependencies. We propose a novel approach for the simultaneous classification of land cover and land use, where semantic and spatial context is considered. The image sites for land cover and land use classification form a hierarchy consisting of two layers: a land cover layer and a land use layer. We apply Conditional Random Fields (CRF) at both layers. The layers differ with respect to the image entities corresponding to the nodes, the employed features and the classes to be distinguished. In the land cover layer, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Both CRFs model spatial dependencies between neighbouring image sites. The complex semantic relations between land cover and land use are integrated in the classification process by using contextual features. We propose a new iterative inference procedure for the simultaneous classification of land cover and land use, in which the two classification tasks mutually influence each other. This helps to improve the classification accuracy for certain classes. The main idea of this approach is that semantic context helps to refine the class predictions, which, in turn, leads to more expressive context information. Thus, potentially wrong decisions can be reversed at later stages. The approach is designed for input data based on aerial images. Experiments are carried out on a test site to evaluate the performance of the proposed method. We show the effectiveness of the iterative inference procedure and demonstrate that a smaller size of the super-pixels has a positive influence on the classification result.

U.S. landowner behavior, land use and land cover changes, and climate change mitigation.

Treesearch

Ralph J. Alig

2003-01-01

Landowner behavior is a major determinant of land use and land cover changes. an important consideration for policy analysts concerned with global change. Study of landowner behavior aids in designing more effective incentives for inducing land use and land cover changes to help mitigate climate change by reducing net greenhouse gas emissions. Afforestation,...

Assessing uncertainties in land cover projections.

PubMed

Alexander, Peter; Prestele, Reinhard; Verburg, Peter H; Arneth, Almut; Baranzelli, Claudia; Batista E Silva, Filipe; Brown, Calum; Butler, Adam; Calvin, Katherine; Dendoncker, Nicolas; Doelman, Jonathan C; Dunford, Robert; Engström, Kerstin; Eitelberg, David; Fujimori, Shinichiro; Harrison, Paula A; Hasegawa, Tomoko; Havlik, Petr; Holzhauer, Sascha; Humpenöder, Florian; Jacobs-Crisioni, Chris; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Lavalle, Carlo; Lenton, Tim; Liu, Jiayi; Meiyappan, Prasanth; Popp, Alexander; Powell, Tom; Sands, Ronald D; Schaldach, Rüdiger; Stehfest, Elke; Steinbuks, Jevgenijs; Tabeau, Andrzej; van Meijl, Hans; Wise, Marshall A; Rounsevell, Mark D A

2017-02-01

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover. © 2016 John Wiley & Sons Ltd.

Vegetation and terrain mapping in Alaska using Landsat MSS and digital terrain data

USGS Publications Warehouse

Shasby, Mark; Carneggie, David M.

1986-01-01

During the past 5 years, the U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center Field Office in Anchorage, Alaska has worked cooperatively with Federal and State resource management agencies to produce land-cover and terrain maps for 245 million acres of Alaska. The need for current land-cover information in Alaska comes principally from the mandates of the Alaska National Interest Lands Conservation Act (ANILCA), December 1980, which requires major land management agencies to prepare comprehensive management plans. The land-cover mapping projects integrate digital Landsat data, terrain data, aerial photographs, and field data. The resultant land-cover and terrain maps and associated data bases are used for resource assessment, management, and planning by many Alaskan agencies including the U.S. Fish and Wildlife Service, U.S. Forest Service, Bureau of Land Management, and Alaska Department of Natural Resources. Applications addressed through use of the digital land-cover and terrain data bases range from comprehensive refuge planning to multiphased sampling procedures designed to inventory vegetation statewide. The land-cover mapping programs in Alaska demonstrate the operational utility of digital Landsat data and have resulted in a new land-cover mapping program by the USGS National Mapping Division to compile 1:250,000-scale land-cover maps in Alaska using a common statewide land-cover map legend.

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

NASA Astrophysics Data System (ADS)

Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

2017-12-01

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

Assessing the effects of land use/cover change on carbon dioxide fluxes in a semiarid shrubland

NASA Astrophysics Data System (ADS)

Gong, Tingting; Lei, Huimin; Yang, Dawen; Jiao, Yang; Yang, Hanbo

2017-04-01

Land use/cover change has been generally considered a local environmental issue. Our study focuses on the effects of land use/cover change on the carbon cycle using long-term continuous field observation data, which is measured by the eddy covariance (EC) technique. The study site is at Yulin (38.45N, 109.47E), which is a desert shrubland ecosystem in Mu Us sandland, China. Before June 2012, the vegetation in this site was covered with mixed vegetation: typical desert shrubs (e.g., Salix psammophila and Artemisia ordosica) and grass. After July 2012, a part of the land use/cover condition within the footprint was changed by the local farmers, which converted the land use/cover condition changed first from mixed vegetation to bare soil and then from bare soil to grassland resulting from the re-growing grass. Four-year carbon fluxes are selected and separated into three periods: Period I is from July 1 2011 to June 30 2012 when land use/cover condition did not change; Period II is from July 1 2012 to June 30 2014 when land use/cover condition changed from mixed vegetation (shrubs and grass) to the mix of bare soil and desert shrubs; Period III is from July 1 2014 to June 30 2015 when land use/cover condition changed from the mix of desert shrubs and bare soil to the mix of desert shrubs and re-growing grass. A linear statistical model will be used to evaluate and quantify the effects of land use/cover change on the uptake or release of carbon fluxes (net ecosystem exchange (NEE), ecosystem respiration (Reco) and gross primary production (GPP)). Moreover, this study is expected to get insights into how agricultural cultivation influences on the local carbon balance (e.g., how NEE, Reco and GPP respond to the land use/cover change; Is the annual carbon balance changed during the land use/cover change process; and the contribution of land use/cover change on these changes of carbon fluxes).

Using land-cover data to understand effects of agricultural and urban development on regional water quality

USGS Publications Warehouse

Karstensen, Krista A.; Warner, Kelly L.

2010-01-01

The Land-Cover Trends project is a collaborative effort between the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS), the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA) to understand the rates, trends, causes, and consequences of contemporary land-use and land-cover change in the United States. The data produced from this research can lead to an enriched understanding of the drivers of future landuse change, effects on environmental systems, and any associated feedbacks. USGS scientists are using the EPA Level III ecoregions as the geographic framework to process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land-Use/Land-Cover Classification System for image interpretation.

Land-cover change research at the U.S. Geological Survey-assessing our nation's dynamic land surface

USGS Publications Warehouse

Wilson, Tamara S.

2011-01-01

The U.S. Geological Survey (USGS) recently completed an unprecedented, 27-year assessment of land-use and land-cover change for the conterminous United States. For the period 1973 to 2000, scientists generated estimates of change in major types of land use and land cover, such as development, mining, agriculture, forest, grasslands, and wetlands. To help provide the insight that our Nation will need to make land-use decisions in coming decades, the historical trends data is now being used by the USGS to help model potential future land use/land cover under different scenarios, including climate, environmental, economic, population, public policy, and technological change.

Land-Cover Change in the Central Irregular Plains, 1973-2000

USGS Publications Warehouse

Karstensen, Krista A.

2009-01-01

Spearheaded by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA), the Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000 and 1973-2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land Use Land Cover Classification System for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion. The results illustrate that there is no single profile of land-cover change but instead point to geographic variability that results from land uses within ecoregions continuously adapting to various factors including environmental, technological, and socioeconomic.

The challenges associated with applying global models in heterogeneous landscapes: A case study using MOD17 GPP estimates in Hawaii

NASA Astrophysics Data System (ADS)

Kimball, H.; Selmants, P. C.; Running, S. W.; Moreno, A.; Giardina, C. P.

2016-12-01

In this study we evaluate the influence of spatial data product accuracy and resolution on the application of global models for smaller scale heterogeneous landscapes. In particular, we assess the influence of locally specific land cover and high-resolution climate data products on estimates of Gross Primary Production (GPP) for the Hawaiian Islands using the MOD17 model. The MOD17 GPP algorithm uses a measure of the fraction of absorbed photosynthetically active radiation from the National Aeronautics and Space Administration's Earth Observation System. This direct measurement is combined with global land cover (500-m resolution) and climate models ( 1/2-degree resolution) to estimate GPP. We first compared the alignment between the global land cover model used in MOD17 with a Hawaii specific land cover data product. We found that there was a 51.6% overall agreement between the two land cover products. We then compared four MOD17 GPP models: A global model that used the global land cover and low-resolution global climate data products, a model produced using the Hawaii specific land cover and low-resolution global climate data products, a model with global land cover and high-resolution climate data products, and finally, a model using both Hawaii specific land cover and high-resolution climate data products. We found that including either the Hawaii specific land cover or the high-resolution Hawaii climate data products with MOD17 reduced overall estimates of GPP by 8%. When both were used, GPP estimates were reduced by 16%. The reduction associated with land cover is explained by a reduction of the total area designated as evergreen broad leaf forest and an increase in the area designated as barren or sparsely vegetated in the Hawaii land cover product as compared to the global product. The climate based reduction is explained primarily by the spatial resolution and distribution of solar radiation in the Hawaiian Islands. This study highlights the importance of accuracy and resolution when applying global models to highly variable landscapes and provides an estimate of the influence of land cover and climate data products on estimates of GPP using MOD17.

Modeling tropical land-use and land-cover change related to sugarcane crops using remote sensing and soft computing techniques

NASA Astrophysics Data System (ADS)

Vicente, L. E.; Koga-Vicente, A.; Friedel, M. J.; Zullo, J.; Victoria, D.; Gomes, D.; Bayma, G.

2013-12-01

Agriculture is closely related to land-use/cover changes (LUCC). The increase in demand for ethanol necessitates the expansion of areas occupied by corn and sugar cane. In São Paulo state, the conversion of this land raises concern for impacts on food security, such as the decrease in traditional food crop production areas. We used remote sensing data to train and evaluate future land-cover scenarios using a machine-learning algorithm. The land cover classification procedure was based on Landsat 5 TM images, obtained from the Global Land Survey, covering three time periods over twenty years (1990 - 2010). Landsat images were segmented into homogeneous objects, which represent areas on the ground with similar spatial and spectral characteristics. These objects are related to the distinct land cover types that occur in each municipality. Based on the object shape, texture and spectral characteristics, land use/cover was visually identified, considering the following classes: sugarcane plantations, pasture lands, natural cover, forest plantation, permanent crop, short cycle crop, water bodies and urban areas. Results for the western regions of São Paulo state indicate that sugarcane crop area advanced mostly upon pasture areas with few areas of food crops being replaced by sugarcane.

Classification of Land Cover and Land Use Based on Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Yang, Chun; Rottensteiner, Franz; Heipke, Christian

2018-04-01

Land cover describes the physical material of the earth's surface, whereas land use describes the socio-economic function of a piece of land. Land use information is typically collected in geospatial databases. As such databases become outdated quickly, an automatic update process is required. This paper presents a new approach to determine land cover and to classify land use objects based on convolutional neural networks (CNN). The input data are aerial images and derived data such as digital surface models. Firstly, we apply a CNN to determine the land cover for each pixel of the input image. We compare different CNN structures, all of them based on an encoder-decoder structure for obtaining dense class predictions. Secondly, we propose a new CNN-based methodology for the prediction of the land use label of objects from a geospatial database. In this context, we present a strategy for generating image patches of identical size from the input data, which are classified by a CNN. Again, we compare different CNN architectures. Our experiments show that an overall accuracy of up to 85.7 % and 77.4 % can be achieved for land cover and land use, respectively. The classification of land cover has a positive contribution to the classification of the land use classification.

Land use, population dynamics, and land-cover change in eastern Puerto Rico: Chapter B in Water quality and landscape processes of four watersheds in eastern Puerto Rico

USGS Publications Warehouse

Gould, William A.; Martinuzzi, Sebastián; Pares-Ramos, Isabel K.; Murphy, Sheila F.; Stallard, Robert F.; Murphy, Sheila F.; Stallard, Robert F.

2012-01-01

We assessed current and historic land use and land cover in the Luquillo Mountains and surrounding area in eastern Puerto Rico, including four small subwatersheds that are study watersheds of the U.S. Geological Survey's Water, Energy, and Biogeochemical Budgets (WEBB) program. This region occupies an area of 1,616 square kilometers, about 18 percent of the total land in Puerto Rico. Closed forests occupy about 37 percent of the area, woodlands and shrublands 7 percent, nonforest vegetation 43 percent, urban development 10 percent, and water and natural barrens total less than 2 percent. The area has been classified into three main land-use categories by integrating recent census information (population density per barrio in the year 2000) with satellite image analyses (degree of developed area versus natural land cover). Urban land use (in this analysis, land with more than 20 percent developed cover within a 1-square-kilometer area and population density greater than 500 people per square kilometer) covered 16 percent of eastern Puerto Rico. Suburban land use (more than 80 percent natural land cover, more than 500 people per square kilometer, and primarily residential) covers 50 percent of the area. Rural land use (more than 80 percent natural land cover, less than 500 people per square kilometer, and primarily active or abandoned agricultural, wetland, steep slope, or protected conservation areas) covered 34 percent of the area. Our analysis of land-cover change indicates that in the 1990s, forest cover increased at the expense of woodlands and grasslands. Urban development increased by 16 percent during that time. The most pronounced change in the last seven decades has been the shift from a nonforested to a forested landscape and the intensification of the ring of urbanization that surrounds the long-protected Luquillo Experimental Forest.

Land-cover change in the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative, 1973 to 2000

USGS Publications Warehouse

Drummond, Mark A.; Stier, Michael P.; Coffin, Alisa W.

2015-01-01

This report summarizes baseline land-cover change information for four time intervals from between 1973 and 2000 for the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (LCC). The study used sample data from the USGS Land Cover Trends dataset to develop estimates of change for 10 land-cover classes in the LCC. The results show that an estimated 17.7 percent of the LCC land cover had a change during the 27-year period. Cyclic forest dynamics—of timber harvest and regrowth—are the most extensive types of land conversion. Agricultural land had an estimated net decline of 3.5 percent as cropland and pasture were urbanized and developed and converted to forest use. Urban and other developed land covers expanded from 2.0 percent of the LCC in 1973 to 3.1 percent in 2000. The report also highlights causes and challenges of land-cover change.

Alaska Interim Land Cover Mapping Program; final report

USGS Publications Warehouse

Fitzpatrick-Lins, Katherine; Doughty, E.F.; Shasby, Mark; Benjamin, Susan

1989-01-01

In 1985, the U.S. Geological Survey initiated a research project to develop an interim land cover data base for Alaska as an alternative to the nationwide Land Use and Land Cover Mapping Program. The Alaska Interim Land Cover Mapping Program was subsequently created to develop methods for producing a series of land cover maps that utilized the existing Landsat digital land cover classifications produced by and for the major land management agencies for mapping the vegetation of Alaska. The program was successful in producing digital land cover classifications and statistical summaries using a common statewide classification and in reformatting these data to produce l:250,000-scale quadrangle-based maps directly from the Scitex laser plotter. A Federal and State agency review of these products found considerable user support for the maps. Presently the Geological Survey is committed to digital processing of six to eight quadrangles each year.

A Tool for Creating Regionally Calibrated High-Resolution Land Cover Data Sets for the West African Sahel: Using Machine Learning to Scale Up Hand-Classified Maps in a Data-Sparse Environment

NASA Astrophysics Data System (ADS)

Van Gordon, M.; Van Gordon, S.; Min, A.; Sullivan, J.; Weiner, Z.; Tappan, G. G.

2017-12-01

Using support vector machine (SVM) learning and high-accuracy hand-classified maps, we have developed a publicly available land cover classification tool for the West African Sahel. Our classifier produces high-resolution and regionally calibrated land cover maps for the Sahel, representing a significant contribution to the data available for this region. Global land cover products are unreliable for the Sahel, and accurate land cover data for the region are sparse. To address this gap, the U.S. Geological Survey and the Regional Center for Agriculture, Hydrology and Meteorology (AGRHYMET) in Niger produced high-quality land cover maps for the region via hand-classification of Landsat images. This method produces highly accurate maps, but the time and labor required constrain the spatial and temporal resolution of the data products. By using these hand-classified maps alongside SVM techniques, we successfully increase the resolution of the land cover maps by 1-2 orders of magnitude, from 2km-decadal resolution to 30m-annual resolution. These high-resolution regionally calibrated land cover datasets, along with the classifier we developed to produce them, lay the foundation for major advances in studies of land surface processes in the region. These datasets will provide more accurate inputs for food security modeling, hydrologic modeling, analyses of land cover change and climate change adaptation efforts. The land cover classification tool we have developed will be publicly available for use in creating additional West Africa land cover datasets with future remote sensing data and can be adapted for use in other parts of the world.

Modeling Land Use/Cover Changes in an African Rural Landscape

NASA Astrophysics Data System (ADS)

Kamusoko, C.; Aniya, M.

2006-12-01

Land use/cover changes are analyzed in the Bindura district of Zimbabwe, Africa through the integration of data from a time series of Landsat imagery (1973, 1989 and 2000), a household survey and GIS coverages. We employed a hybrid supervised/unsupervised classification approach to generate land use/cover maps from which landscape metrics were calculated. Population and other household variables were derived from a sample of surveyed villages, while road accessibility and slope were obtained from topographic maps and digital elevation model, respectively. Markov-cellular automata modeling approach that incorporates Markov chain analysis, cellular automata and multi-criteria evaluation (MCE) / multi-objective allocation (MOLA) procedures was used to simulate land use/cover changes. A GIS-based MCE technique computed transition potential maps, whereas transition areas were derived from the 1973-2000 land use/cover maps using the Markov chain analysis. A 5 x 5 cellular automata filter was used to develop a spatially explicit contiguity- weighting factor to change the cells based on its previous state and those of its neighbors, while MOLA resolved land use/cover class allocation conflicts. The kappa index of agreement was used for model validation. Observed trends in land use/cover changes indicate that deforestation and the encroachment of cultivation in woodland areas is a continuous trend in the study area. This suggests that economic activities driven by agricultural expansion were the main causes of landscape fragmentation, leading to landscape degradation. Rigorous calibration of transition potential maps done by a MCE algorithm and Markovian transition probabilities produced accurate inputs for the simulation of land use/cover changes. Overall standard kappa index of agreement ranged from 0.73 to 0.83, which is sufficient for simulating land use/cover changes in the study area. Land use/cover simulations under the 1989 and 2000 scenario indicated further landscape degradation in the rural areas of the Bindura district. Keywords: Zimbabwe, land use/cover changes, landscape fragmentation, GIS, land use/cover change modeling, multi-criteria evaluation/multi-objective allocation procedures, Markov-cellular automata

Land cover characterization and mapping of continental southeast Asia using multi-resolution satellite sensor data

USGS Publications Warehouse

Giri, Chandra; Defourny, Pierre; Shrestha, Surendra

2003-01-01

Land use/land cover change, particularly that of tropical deforestation and forest degradation, has been occurring at an unprecedented rate and scale in Southeast Asia. The rapid rate of economic development, demographics and poverty are believed to be the underlying forces responsible for the change. Accurate and up-to-date information to support the above statement is, however, not available. The available data, if any, are outdated and are not comparable for various technical reasons. Time series analysis of land cover change and the identification of the driving forces responsible for these changes are needed for the sustainable management of natural resources and also for projecting future land cover trajectories. We analysed the multi-temporal and multi-seasonal NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite data of 1985/86 and 1992 to (1) prepare historical land cover maps and (2) to identify areas undergoing major land cover transformations (called ‘hot spots’). The identified ‘hot spot’ areas were investigated in detail using high-resolution satellite sensor data such as Landsat and SPOT supplemented by intensive field surveys. Shifting cultivation, intensification of agricultural activities and change of cropping patterns, and conversion of forest to agricultural land were found to be the principal reasons for land use/land cover change in the Oudomxay province of Lao PDR, the Mekong Delta of Vietnam and the Loei province of Thailand, respectively. Moreover, typical land use/land cover change patterns of the ‘hot spot’ areas were also examined. In addition, we developed an operational methodology for land use/land cover change analysis at the national level with the help of national remote sensing institutions.

Hydrological Responses of Climate and Land Use/Cover Changes in Tao'er River Basin Based on the SWAT Model

NASA Astrophysics Data System (ADS)

Liu, J.; Kou, L.

2015-12-01

Abstract: The changes of both climate and land use/cover have some impact on the water resources. For Tao'er River Basin, these changes have a direct impact on the land use pattern adjustment, wetland protection, connection project between rivers and reservoirs, local social and economic development, etc. Therefore, studying the impact of climate and land use/cover changes is of great practical significance. The Soil and Water Assessment Tool (SWAT) is used as the research method. With historical actual measured runoff data and the yearly land use classification caught by satellite remote sensing maps, analyze the impact of climate change on the runoff of Tao'er River. And according to the land use/cover classification of 1990, 2000 and 2010, analyze the land use/cover change in the recent 30 years, the impact of the land use/cover change on the river runoff and the contribution coefficient of farmland, woodland, grassland and other major land-use types to the runoff. These studies can provide some references to the rational allocation of water resource and adjustment of land use structure in this area.

Land-Cover Trends of the Sierra Nevada Ecoregion, 1973-2000

USGS Publications Warehouse

Raumann, Christian G.; Soulard, Christopher E.

2007-01-01

The U.S. Geological Survey has developed and is implementing the Land Cover Trends project to estimate and describe the temporal and spatial distribution and variability of contemporary land-use and land-cover change in the United States. As part of the Land Cover Trends project, the purpose of this study was to assess land-use/land-cover change in the Sierra Nevada ecoregion for the period 1973 to 2000 using a probability sampling technique and satellite imagery. We randomly selected 36 100-km2 sample blocks to derive thematic images of land-use/land-cover for five dates of Landsat imagery (1973, 1980, 1986, 1992, 2000). We visually interpreted as many as 11 land-use/land-cover classes using a 60-meter minimum mapping unit from the five dates of imagery yielding four periods for analysis. Change-detection results from post-classification comparison of our mapped data showed that landscape disturbance from fire was the dominant change from 1973-2000. The second most-common change was forest disturbance resulting from harvest of timber resources by way of clear-cutting. The rates of forest regeneration from temporary fire and harvest disturbances coincided with the rates of disturbance from the previous period. Relatively minor landscape changes were caused by new development and reservoir drawdown. Multiple linear regression analysis suggests that land ownership and the proportion of forest and developed cover types were significant determinants of the likelihood of direct human-induced change occurring in sampling units. Driving forces of change include land ownership, land management such as fire suppression policy, and demand for natural resources.

Land Cover Indicators for U.S. National Climate Assessments

NASA Astrophysics Data System (ADS)

Channan, S.; Thomson, A. M.; Collins, K. M.; Sexton, J. O.; Torrens, P.; Emanuel, W. R.

2014-12-01

Land is a critical resource for human habitat and for the vast majority of human activities. Many natural resources are derived from terrestrial ecosystems or otherwise extracted from the landscape. Terrestrial biodiversity depends on land attributes as do people's perceptions of the value of land, including its value for recreation or tourism. Furthermore, land surface properties and processes affect weather and climate, and land cover change and land management affect emissions of greenhouse gases. Thus, land cover with its close association with climate is so pervasive that a land cover indicator is of fundamental importance to U.S. national climate assessments and related research. Moderate resolution remote sensing products (MODIS) were used to provide systematic data on annual distributions of land cover over the period 2001-2012. Selected Landsat observations and data products further characterize land cover at higher resolution. Here we will present the prototype for a suite of land cover indicators including land cover maps as well as charts depicting attributes such as composition by land cover class, statistical indicators of landscape characteristics, and tabular data summaries indispensable for communicating the status and trends of U.S. land cover at national, regional and state levels.

Impact factors on expansion of built-up areas in Zhejiang Province, China

NASA Astrophysics Data System (ADS)

Liu, Dong; Zhu, Qiankun; Li, Yan; Gong, Fang

2017-10-01

Built-up areas are the results of human activities. Not only are they the real reflection of human and society activities, but also one of the most important input parameters for the simulation of biogeochemical cycle. Therefore, it is very necessary to map the distribution of built-up areas and monitor their changes by using new technologies and methods at high spatiotemporal resolution. By combining technologies of GIS (Geographic Information System) and RS (Remote Sensing), this study mainly explored the expansion and driving factors of built-up areas at the beginning of the 21st century in Zhejiang Province, China. Firstly, it introduced the mapping processes of LULC (Land Use and Land Cover) based on the method which combined object-oriented method and binary decision tree. Then, it analyzed the expansion features of built-up areas in Zhejiang from 2000 to 2005 and 2005 to 2010. In addition to these, potential driving factors on the expansion of built-up areas were also explored, which contained physical geographical factors, railways, highways, rivers, urban centers, elevation, and slop. Results revealed that the expansions of built-up areas in Zhejiang from 2000 to 2005 and from 2005 to 2010 were very obvious and they showed high levels of variation in spatial heterogeneity. Except those, increased built-up areas with distance to railways, highways, rivers, and urban centers could be fitted with power function (y = a*xb ), with minimum R2 of 0.9507 for urban centers from 2000 to 2005; the increased permillages of built-up areas to mean elevation and mean slop could be fitted with exponential functions (y = a*ebx), with minimum R2 of 0.6657 for mean slop from 2005 to 2010. Besides, government policy could also impact expansion of built-up areas. In a nutshell, a series of conclusions were obtained through this study about the spatial features and driving factors of evolution of built-up areas in Zhejiang from 2000 to 2010.

Modeling the Land Use/Cover Change in an Arid Region Oasis City Constrained by Water Resource and Environmental Policy Change using Cellular Automata Model

NASA Astrophysics Data System (ADS)

Hu, X.; Li, X.; Lu, L.

2017-12-01

Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.

Soil chemical and physical properties that differentiate urban land-use and cover types

Treesearch

R.V. Pouyat; I.D. Yesilonis; J. Russell-Anelli; N.K. Neerchal

2007-01-01

We investigated the effects of land use and cover and surface geology on soil properties in Baltimore, MD, with the objectives to: (i) measure the physical and chemical properties of surface soils (0?10 cm) by land use and cover; and (ii) ascertain whether land use and cover explain differences in these properties relative to surface geology. Mean and median values of...

[Effects of sub-watershed landscape patterns at the upper reaches of Minjiang River on soil erosion].

PubMed

Yang, Meng; Li, Xiu-zhen; Yang, Zhao-ping; Hu, Yuan-man; Wen, Qing-chun

2007-11-01

Based on GIS, the spatial distribution of soil loss and sediment yield in Heishui and Zhenjiangguan sub-watersheds at the upper reaches of Minjiang River was simulated by using sediment delivery-distribution (SEDD) model, and the effects of land use/cover types on soil erosion and sediment yield were discussed, based on the simulated results and related land use maps. A landscape index named location-weighted landscape contrast index (LCI) was calculated to evaluate the effects of landscape components' spatial distribution, weight, and structure of land use/cover on soil erosion. The results showed the soil erosion modulus varied with land use pattern, and decreased in the order of bare rock > urban/village > rangeland > farmland > shrub > forest. There were no significant differences in sediment yield modules among different land use/covers. In the two sub-watersheds, the spatial distribution of land use/covers on slope tended to decrease the final sediment load at watershed outlet, hut as related to relative elevation, relative distance, and flow length, the spatial distribution tended to increase sediment yield. The two sub-watersheds had different advantages as related to landscape components' spatial distribution, but, when the land use/cover weight was considered, the advantages of Zhenjiangguan sub-watershed increased. If the land use/cover structure was considered in addition, the landscape pattern of Zhenjiangguan subwatershed was better. Therefore, only the three elements, i.e., landscape components' spatial distribution, land use/cover weight, and land use/cover structure, were considered comprehensively, can we get an overall evaluation on the effects of landscape pattern on soil erosion. The calculation of LCI related to slope suggested that this index couldn' t accurately reflect the effects of land use/cover weight and structure on soil erosion, and thus, needed to be modified.

Scenarios of land use and land cover change in the conterminous United States: Utilizing the special report on emission scenarios at ecoregional scales

USGS Publications Warehouse

Sleeter, Benjamin M.; Sohl, Terry L.; Bouchard, Michelle A.; Reker, Ryan R.; Soulard, Christopher E.; Acevedo, William; Griffith, Glenn E.; Sleeter, Rachel R.; Auch, Roger F.; Sayler, Kristi L.; Prisley, Stephen; Zhu, Zhi-Liang

2012-01-01

Global environmental change scenarios have typically provided projections of land use and land cover for a relatively small number of regions or using a relatively coarse resolution spatial grid, and for only a few major sectors. The coarseness of global projections, in both spatial and thematic dimensions, often limits their direct utility at scales useful for environmental management. This paper describes methods to downscale projections of land-use and land-cover change from the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios to ecological regions of the conterminous United States, using an integrated assessment model, land-use histories, and expert knowledge. Downscaled projections span a wide range of future potential conditions across sixteen land use/land cover sectors and 84 ecological regions, and are logically consistent with both historical measurements and SRES characteristics. Results appear to provide a credible solution for connecting regionalized projections of land use and land cover with existing downscaled climate scenarios, under a common set of scenario-based socioeconomic assumptions.

Towards realistic Holocene land cover scenarios: integration of archaeological, palynological and geomorphological records and comparison to global land cover scenarios.

NASA Astrophysics Data System (ADS)

De Brue, Hanne; Verstraeten, Gert; Broothaerts, Nils; Notebaert, Bastiaan

2016-04-01

Accurate and spatially explicit landscape reconstructions for distinct time periods in human history are essential for the quantification of the effect of anthropogenic land cover changes on, e.g., global biogeochemical cycles, ecology, and geomorphic processes, and to improve our understanding of interaction between humans and the environment in general. A long-term perspective covering Mid and Late Holocene land use changes is recommended in this context, as it provides a baseline to evaluate human impact in more recent periods. Previous efforts to assess the evolution and intensity of agricultural land cover in past centuries or millennia have predominantly focused on palynological records. An increasing number of quantitative techniques has been developed during the last two decades to transfer palynological data to land cover estimates. However, these techniques have to deal with equifinality issues and, furthermore, do not sufficiently allow to reconstruct spatial patterns of past land cover. On the other hand, several continental and global databases of historical anthropogenic land cover changes based on estimates of global population and the required agricultural land per capita have been developed in the past decennium. However, at such long temporal and spatial scales, reconstruction of past anthropogenic land cover intensities and spatial patterns necessarily involves many uncertainties and assumptions as well. Here, we present a novel approach that combines archaeological, palynological and geomorphological data for the Dijle catchment in the central Belgium Loess Belt in order to arrive at more realistic Holocene land cover histories. Multiple land cover scenarios (> 60.000) are constructed using probabilistic rules and used as input into a sediment delivery model (WaTEM/SEDEM). Model outcomes are confronted with a detailed geomorphic dataset on Holocene sediment fluxes and with REVEALS based estimates of vegetation cover using palynological data from six alluvial sites. This comparison drastically reduces the number of realistic land cover scenarios for various cultural periods. REVEALS based land cover histories provide more accurate estimates of Holocene sediment fluxes compared to global land cover scenarios (KK10 and HYDE 3.1). Both global land cover scenarios produce erroneous results when applied at their original coarse scale resolution. However, spatially allocating KK10 land cover data to a finer spatial resolution increases its performance, whereas this is not the case for HYDE 3.1. Results suggest that KK10 also offers a more realistic history of human impact than HYDE 3.1 although it overestimates human impact in the Belgian Loess Belt prior to the Roman Age, whereas it underestimates human impact from the Medieval Period onwards.

Quantifying Urban Watershed Stressor Gradients and Evaluating How Different Land Cover Datasets Affect Stream Management.

PubMed

Smucker, Nathan J; Kuhn, Anne; Charpentier, Michael A; Cruz-Quinones, Carlos J; Elonen, Colleen M; Whorley, Sarah B; Jicha, Terri M; Serbst, Jonathan R; Hill, Brian H; Wehr, John D

2016-03-01

Watershed management and policies affecting downstream ecosystems benefit from identifying relationships between land cover and water quality. However, different data sources can create dissimilarities in land cover estimates and models that characterize ecosystem responses. We used a spatially balanced stream study (1) to effectively sample development and urban stressor gradients while representing the extent of a large coastal watershed (>4400 km(2)), (2) to document differences between estimates of watershed land cover using 30-m resolution national land cover database (NLCD) and <1-m resolution land cover data, and (3) to determine if predictive models and relationships between water quality and land cover differed when using these two land cover datasets. Increased concentrations of nutrients, anions, and cations had similarly significant correlations with increased watershed percent impervious cover (IC), regardless of data resolution. The NLCD underestimated percent forest for 71/76 sites by a mean of 11 % and overestimated percent wetlands for 71/76 sites by a mean of 8 %. The NLCD almost always underestimated IC at low development intensities and overestimated IC at high development intensities. As a result of underestimated IC, regression models using NLCD data predicted mean background concentrations of NO3 (-) and Cl(-) that were 475 and 177 %, respectively, of those predicted when using finer resolution land cover data. Our sampling design could help states and other agencies seeking to create monitoring programs and indicators responsive to anthropogenic impacts. Differences between land cover datasets could affect resource protection due to misguided management targets, watershed development and conservation practices, or water quality criteria.

Land-cover change in the Lower Mississippi Valley, 1973-2000

USGS Publications Warehouse

Karstensen, Krista A.; Sayler, Kristi L.

2009-01-01

The Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. The project is coordinated by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in conjunction with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 were processed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into four temporal periods: 1973 to1980, 1980 to 1986, 1986 to 1992, 1992 to 2000 and overall from 1973 to 2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation.The rates of land-cover change were estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images were used to interpret land-cover change. The sample block data then were incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion.

Using land-cover change as dynamic variables in surface-water and water-quality models

USGS Publications Warehouse

Karstensen, Krista A.; Warner, Kelly L.; Kuhn, Anne

2010-01-01

Land-cover data are typically used in hydrologic modeling to establish or describe land surface dynamics. This project is designed to demonstrate the use of land-cover change data in surface-water and water-quality models by incorporating land-cover as a variable condition. The project incorporates three different scenarios that vary hydrologically and geographically: 1) Agriculture in the Plains, 2) Loon habitat in New England, and 3) Forestry in the Ozarks.

Land-use poverty traps identified in shifting cultivation systems shape long-term tropical forest cover

PubMed Central

Coomes, Oliver T.; Takasaki, Yoshito; Rhemtulla, Jeanine M.

2011-01-01

In this article we illustrate how fine-grained longitudinal analyses of land holding and land use among forest peasant households in an Amazonian village can enrich our understanding of the poverty/land cover nexus. We examine the dynamic links in shifting cultivation systems among asset poverty, land use, and land cover in a community where poverty is persistent and primary forests have been replaced over time—with community enclosure—by secondary forests (i.e., fallows), orchards, and crop land. Land cover change is assessed using aerial photographs/satellite imagery from 1965 to 2007. Household and plot level data are used to track land holding, portfolios, and use as well as land cover over the past 30 y, with particular attention to forest status (type and age). Our analyses find evidence for two important types of “land-use” poverty traps—a “subsistence crop” trap and a “short fallow” trap—and indicate that the initial conditions of land holding by forest peasants have long-term effects on future forest cover and household welfare. These findings suggest a new mechanism driving poverty traps: insufficient initial land holdings induce land use patterns that trap households in low agricultural productivity. Path dependency in the evolution of household land portfolios and land use strategies strongly influences not only the wellbeing of forest people but also the dynamics of tropical deforestation and secondary forest regrowth. PMID:21873179

Land Use and Land Cover Change Modeling Using Remote Sensing and Soft Computing Approach to Assess Sugarcane Expansion Impacts in Tropical Agriculture

NASA Astrophysics Data System (ADS)

Vicente, L. E.; Koga-Vicente, A.; Friedel, M. J.; Victoria, D.; Zullo, J., Jr.; Gomes, D.; Bayma-Silva, G.

2014-12-01

Agriculture is related with land-use/cover changes (LUCC) over large areas and, in recent years, increase in demand of ethanol fuel has been influence in expansion of areas occupied with corn and sugar cane, raw material for ethanol production. Nevertheless, there´s a concern regarding the impacts on food security, such as, decrease in areas planted with food crops. Considering that the LUCC is highly dynamic, the use of Remote Sensing is a tool for monitoring changes quickly and precisely in order to provide information for agricultural planning. In this work, Remote Sensing techniques were used to monitor the LUCC occurred in municipalities of São Paulo state- Brazil related with sugarcane crops expansion in order to (i) evaluate and quantify the previous land cover in areas of sugarcane crop expansion, and (ii) provide information to elaborate a future land cover scenario based on Self Organizing Map (SOM) approach. The land cover classification procedure was based on Landsat 5 TM images, obtained from the Global Land Survey. The Landsat images were then segmented into homogeneous objects, with represent areas on the ground with similar spatial and spectral characteristics. These objects are related to the distinct land cover types that occur in each municipality. The segmentation procedure resulted in polygons over the three time periods along twenty years (1990-2010). The land cover for each object was visually identified, based on its shape, texture and spectral characteristics. Land cover types considered were: sugarcane plantations, pasture lands, natural cover, forest plantation, permanent crop, short cycle crop, water bodies and urban areas. SOM technique was used to estimate the values for the future land cover scenarios for the selected municipalities, using the information of land change provided by the remote sensing and data from official sources.

Discrimination and Biophysical Characterization of Land Cover Types and Land Conversions in the Brazilian Cerrado Using EO-1 Hyperion Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Miura, T.; Huete, A. R.; Ferreira, L.

2002-12-01

The savanna, typically found in the sub-tropics and seasonal tropics, are the dominant vegetation biome type in the southern hemisphere, covering approximately 45 % of the South America. In Brazil, the savanna, locally known as "cerrado", is the most intensely stressed biome with rapid and aggressive land use conversions. Better characterization and discrimination of cerrado land cover types are needed in order to improve assessments of the impact of these land cover conversions on carbon storage, nutrient dynamics, and the prospect for sustainable land use in the Amazon region. In this study, we explored the utility of hyperspectral remote sensing in improving discrimination and biophysical/biochemical characterization of the cerrado land cover types by taking advantage of a newly available satellite-based, hyperspectral imaging sensor, "EO-1 Hyperion". A Hyperion image was acquired over the Brasilia National Park (BNP) and surrounding areas in Brasilia on July 20, 2001. Two commonly-used techniques, spectral derivatives and spectral mixture modeling, were applied to the atmospherically-corrected Hyperion scene. Derivative spectroscopy was useful in analyzing variations in spectral signatures and absorption depths, while spectral mixture modeling provided a means to simultaneously analyze variations in component fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil brightness. Data sets were extracted over a range of land cover types typically found in the Brazilian Cerrado. These included cerrado grassland, shrub cerrado, wooded cerrado, and cerrado woodland as undisturbed cerrado land cover types, and gallery forest as an undisturbed forest cover type in the Cerrado domain, and cultivated pasture as a converted land cover. In the derivative spectra analysis, both the position and magnitude of the red edge peak, and the ligno-cellulose absorptions at 2090nm and around 2300nm wavelengths showed large differences among the land cover types with the absorption depth of the latter correlating well with ground-measured % NPV cover. The multi-component fractional estimates successfully discriminated pasture and gallery forest from other cerrado land cover types. Likewise, PV and NPV fractional estimates for cerrado land cover types correlated well with ground-measured % green and NPV covers, respectively. These preliminary analyses showed a great potential of hyperspectral data in biophysical/biochemical characterization as well as discrimination of the land cover types in the Brazilian cerrado.

Land Use and Land Cover Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Daniel; Polsky, Colin; Bolstad, Paul V.

2014-05-01

A contribution to the 3rd National Climate Assessment report, discussing the following key messages: 1. Choices about land-use and land-cover patterns have affected and will continue to affect how vulnerable or resilient human communities and ecosystems are to the effects of climate change. 2. Land-use and land-cover changes affect local, regional, and global climate processes. 3. Individuals, organizations, and governments have the capacity to make land-use decisions to adapt to the effects of climate change. 4. Choices about land use and land management provide a means of reducing atmospheric greenhouse gas levels.

Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques

NASA Astrophysics Data System (ADS)

Kumar, Lalit; Ghosh, Manoj Kumer

2012-01-01

Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.

Late twentieth century land-cover change in the basin and range ecoregions of the United States

USGS Publications Warehouse

Soulard, Christopher E.; Sleeter, Benjamin M.

2012-01-01

As part of the US Geological Survey's Land Cover Trends project, land-use/land-cover change estimates between 1973 and 2000 are presented for the basin and range ecoregions, including Northern, Central, Mojave, and Sonoran. Landsat data were employed to estimate and characterize land-cover change from 1973, 1980, 1986, 1992, and 2000 using a post-classification comparison. Overall, spatial change was 2.5% (17,830 km2). Change increased steadily between 1973 and 1986 but decreased slightly between 1992 and 2000. The grassland/shrubland class, frequently used for livestock grazing, constituted the majority of the study area and had a net decrease from an estimated 83.8% (587,024 km2) in 1973 to 82.6% (578,242 km2) in 2000. The most common land-use/land-cover conversions across the basin and range ecoregions were indicative of the changes associated with natural, nonmechanical disturbances (i.e., fire), and grassland/shrubland loss to development, agriculture, and mining. This comprehensive look at contemporary land-use/land-cover change provides critical insight into how the deserts of the United States have changed and can be used to inform adaptive management practices of public lands.

Simulation of Land-Cover Change in Taipei Metropolitan Area under Climate Change Impact

NASA Astrophysics Data System (ADS)

Huang, Kuo-Ching; Huang, Thomas C. C.

2014-02-01

Climate change causes environment change and shows up on land covers. Through observing the change of land use, researchers can find out the trend and potential mechanism of the land cover change. Effective adaptation policies can affect pattern of land cover change and may decrease the risks of climate change impacts. By simulating land use dynamics with scenario settings, this paper attempts to explore the relationship between climate change and land-cover change through efficient adaptation polices. It involves spatial statistical model in estimating possibility of land-cover change, cellular automata model in modeling land-cover dynamics, and scenario analysis in response to adaptation polices. The results show that, without any control, the critical eco-areas, such as estuarine areas, will be destroyed and people may move to the vulnerable and important economic development areas. In the other hand, under the limited development condition for adaptation, people migration to peri-urban and critical eco-areas may be deterred.

Impacts of land use/cover classification accuracy on regional climate simulations

NASA Astrophysics Data System (ADS)

Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

2007-03-01

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

Measuring land-use and land-cover change using the U.S. department of agriculture's cropland data layer: Cautions and recommendations

NASA Astrophysics Data System (ADS)

Lark, Tyler J.; Mueller, Richard M.; Johnson, David M.; Gibbs, Holly K.

2017-10-01

Monitoring agricultural land is important for understanding and managing food production, environmental conservation efforts, and climate change. The United States Department of Agriculture's Cropland Data Layer (CDL), an annual satellite imagery-derived land cover map, has been increasingly used for this application since complete coverage of the conterminous United States became available in 2008. However, the CDL is designed and produced with the intent of mapping annual land cover rather than tracking changes over time, and as a result certain precautions are needed in multi-year change analyses to minimize error and misapplication. We highlight scenarios that require special considerations, suggest solutions to key challenges, and propose a set of recommended good practices and general guidelines for CDL-based land change estimation. We also characterize a problematic issue of crop area underestimation bias within the CDL that needs to be accounted for and corrected when calculating changes to crop and cropland areas. When used appropriately and in conjunction with related information, the CDL is a valuable and effective tool for detecting diverse trends in agriculture. By explicitly discussing the methods and techniques for post-classification measurement of land-cover and land-use change using the CDL, we aim to further stimulate the discourse and continued development of suitable methodologies. Recommendations generated here are intended specifically for the CDL but may be broadly applicable to additional remotely-sensed land cover datasets including the National Land Cover Database (NLCD), Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover products, and other regional, national, and global land cover classification maps.

[Study of the microwave emissivity characteristics over different land cover types].

PubMed

Zhang, Yong-Pan; Jiang, Ling-Mei; Qiu, Yu-Bao; Wu, Sheng-Li; Shi, Jian-Cheng; Zhang, Li-Xin

2010-06-01

The microwave emissivity over land is very important for describing the characteristics of the lands, and it is also a key factor for retrieving the parameters of land and atmosphere. Different land covers have their emission behavior as a function of structure, water content, and surface roughness. In the present study the global land surface emissivities were calculated using six month (June, 2003-August, 2003, Dec, 2003-Feb, 2004) AMSR-E L2A brightness temperature, MODIS land surface temperature and the layered atmosphere temperature, and humidity and pressure profiles data retrieved from MODIS/Aqua under clear sky conditions. With the information of IGBP land cover types, "pure" pixels were used, which are defined when the fraction cover of each land type is larger than 85%. Then, the emissivity of sixteen land covers at different frequencies, polarization and their seasonal variation were analyzed respectively. The results show that the emissivity of vegetation including forests, grasslands and croplands is higher than that over bare soil, and the polarization difference of vegetation is smaller than that of bare soil. In summer, the emissivity of vegetation is relatively stable because it is in bloom, therefore the authors can use it as its emissivity in our microwave emissivity database over different land cover types. Furthermore, snow cover can heavily impact the change in land cover emissivity, especially in winter.

Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

USGS Publications Warehouse

Loveland, Thomas R.; Reed, B.C.; Brown, Jesslyn F.; Ohlen, D.O.; Zhu, Z.; Yang, L.; Merchant, J.W.

2000-01-01

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

Reconstructed historical land cover and biophysical parameters for studies of land-atmosphere interactions within the eastern United States

USGS Publications Warehouse

Steyaert, Louis T.; Knox, R.G.

2008-01-01

Over the past 350 years, the eastern half of the United States experienced extensive land cover changes. These began with land clearing in the 1600s, continued with widespread deforestation, wetland drainage, and intensive land use by 1920, and then evolved to the present-day landscape of forest regrowth, intensive agriculture, urban expansion, and landscape fragmentation. Such changes alter biophysical properties that are key determinants of land-atmosphere interactions (water, energy, and carbon exchanges). To understand the potential implications of these land use transformations, we developed and analyzed 20-km land cover and biophysical parameter data sets for the eastern United States at 1650, 1850, 1920, and 1992 time slices. Our approach combined potential vegetation, county-level census data, soils data, resource statistics, a Landsat-derived land cover classification, and published historical information on land cover and land use. We reconstructed land use intensity maps for each time slice and characterized the land cover condition. We combined these land use data with a mutually consistent set of biophysical parameter classes, to characterize the historical diversity and distribution of land surface properties. Time series maps of land surface albedo, leaf area index, a deciduousness index, canopy height, surface roughness, and potential saturated soils in 1650, 1850, 1920, and 1992 illustrate the profound effects of land use change on biophysical properties of the land surface. Although much of the eastern forest has returned, the average biophysical parameters for recent landscapes remain markedly different from those of earlier periods. Understanding the consequences of these historical changes will require land-atmosphere interactions modeling experiments.

Status and trends of land change in the United States--1973 to 2000

USGS Publications Warehouse

,

2012-01-01

U.S. Geological Survey (USGS) Professional Paper 1794 is a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the United States between 1973 and 2000. Volumes A, B, C, and D provide analyses for the Western United States, the Great Plains, the Midwest–South Central United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation. This report is only one of the products produced by USGS on land-use and land-cover change in the United States. Other reports and land-cover statistics are available online at http://landcovertrends.usgs.gov.

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

NASA Technical Reports Server (NTRS)

Steyaert, Lou; Hall, Forrest G.; Newcomer, Jeffrey A. (Editor); Knapp, David E. (Editor); Loveland, Thomas R.; Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Simulation of urban land surface temperature based on sub-pixel land cover in a coastal city

NASA Astrophysics Data System (ADS)

Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang

2014-11-01

The sub-pixel urban land cover has been proved to have obvious correlations with land surface temperature (LST). Yet these relationships have seldom been used to simulate LST. In this study we provided a new approach of urban LST simulation based on sub-pixel land cover modeling. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover and then extract the transformation rule using logistic regression. The transformation possibility was taken as its percent in the same pixel after normalization. And cellular automata were used to acquire simulated sub-pixel land cover on 2007 and 2017. On the other hand, the correlations between retrieved LST and sub-pixel land cover achieved by spectral mixture analysis in 2002 were examined and a regression model was built. Then the regression model was used on simulated 2007 land cover to model the LST of 2007. Finally the LST of 2017 was simulated for urban planning and management. The results showed that our method is useful in LST simulation. Although the simulation accuracy is not quite satisfactory, it provides an important idea and a good start in the modeling of urban LST.

Impact of land cover change on the environmental hydrology characteristics in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Saadatkhah, Nader; Mansor, Shattri; Khuzaimah, Zailani; Asmat, Arnis; Adnan, Noraizam; Adam, Siti Noradzah

2016-09-01

Changing the land cover/ land use has serious environmental impacts affecting the ecosystem in Malaysia. The impact of land cover changes on the environmental functions such as surface water, loss water, and soil moisture is considered in this paper on the Kelantan river basin. The study area at the east coast of the peninsular Malaysia has suffered significant land cover changes in the recent years. The current research tried to assess the impact of land cover changes in the study area focused on the surface water, loss water, and soil moisture from different land use classes and the potential impact of land cover changes on the ecosystem of Kelantan river basin. To simulate the impact of land cover changes on the environmental hydrology characteristics, a deterministic regional modeling were employed in this study based on five approaches, i.e. (1) Land cover classification based on Landsat images; (2) assessment of land cover changes during last three decades; (3) Calculation the rate of water Loss/ Infiltration; (4) Assessment of hydrological and mechanical effects of the land cover changes on the surface water; and (5) evaluation the impact of land cover changes on the ecosystem of the study area. Assessment of land cover impact on the environmental hydrology was computed with the improved transient rainfall infiltration and grid based regional model (Improved-TRIGRS) based on the transient infiltration, and subsequently changes in the surface water, due to precipitation events. The results showed the direct increased in surface water from development area, agricultural area, and grassland regions compared with surface water from other land covered areas in the study area. The urban areas or lower planting density areas tend to increase for surface water during the monsoon seasons, whereas the inter flow from forested and secondary jungle areas contributes to the normal surface water.

Land cover change of watersheds in Southern Guam from 1973 to 2001.

PubMed

Wen, Yuming; Khosrowpanah, Shahram; Heitz, Leroy

2011-08-01

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

PubMed Central

Moran, Emilio Federico.

2010-01-01

High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

Completion of the National Land Cover Database (NLCD) 1992–2001 Land Cover Change Retrofit product

USGS Publications Warehouse

Fry, J.A.; Coan, Michael; Homer, Collin G.; Meyer, Debra K.; Wickham, J.D.

2009-01-01

The Multi-Resolution Land Characteristics Consortium has supported the development of two national digital land cover products: the National Land Cover Dataset (NLCD) 1992 and National Land Cover Database (NLCD) 2001. Substantial differences in imagery, legends, and methods between these two land cover products must be overcome in order to support direct comparison. The NLCD 1992-2001 Land Cover Change Retrofit product was developed to provide more accurate and useful land cover change data than would be possible by direct comparison of NLCD 1992 and NLCD 2001. For the change analysis method to be both national in scale and timely, implementation required production across many Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) path/rows simultaneously. To meet these requirements, a hybrid change analysis process was developed to incorporate both post-classification comparison and specialized ratio differencing change analysis techniques. At a resolution of 30 meters, the completed NLCD 1992-2001 Land Cover Change Retrofit product contains unchanged pixels from the NLCD 2001 land cover dataset that have been cross-walked to a modified Anderson Level I class code, and changed pixels labeled with a 'from-to' class code. Analysis of the results for the conterminous United States indicated that about 3 percent of the land cover dataset changed between 1992 and 2001.

VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013

PubMed Central

Morse-McNabb, Elizabeth; Sheffield, Kathryn; Clark, Rob; Lewis, Hayden; Robson, Susan; Cherry, Don; Williams, Steve

2015-01-01

Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engagement to establish product requirements such as format, classification, frequency and spatial resolution. Its genesis is significantly different to traditional methods, incorporating data from a range of jurisdictions to develop land use information designed for regular on-going creation and consistency. Covering the entire landmass of Victoria, the dataset separately describes land tenure, land use and land cover. These variables are co-registered to a common spatial base (cadastral parcels) across the state for the period 2006 to 2013; biennially for land tenure and land use, and annually for land cover. Data is produced as a spatial GIS feature class. PMID:26602150

VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013.

PubMed

Morse-McNabb, Elizabeth; Sheffield, Kathryn; Clark, Rob; Lewis, Hayden; Robson, Susan; Cherry, Don; Williams, Steve

2015-11-24

Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engagement to establish product requirements such as format, classification, frequency and spatial resolution. Its genesis is significantly different to traditional methods, incorporating data from a range of jurisdictions to develop land use information designed for regular on-going creation and consistency. Covering the entire landmass of Victoria, the dataset separately describes land tenure, land use and land cover. These variables are co-registered to a common spatial base (cadastral parcels) across the state for the period 2006 to 2013; biennially for land tenure and land use, and annually for land cover. Data is produced as a spatial GIS feature class.

A watershed model to integrate EO data

NASA Astrophysics Data System (ADS)

Jauch, Eduardo; Chambel-Leitao, Pedro; Carina, Almeida; Brito, David; Cherif, Ines; Alexandridis, Thomas; Neves, Ramiro

2013-04-01

MOHID LAND is a open source watershed model developed by MARETEC and is part of the MOHID Framework. It integrates four mediums (or compartments): porous media, surface, rivers and atmosphere. The movement of water between these mediums are based on mass and momentum balance equations. The atmosphere medium is not explicity simulated. Instead, it's used as boundary condition to the model through meteorological properties: precipitation, solar radiation, wind speed/direction, relative humidity and air temperature. The surface medium includes the overland runoff and vegetation growth processes and is simulated using a 2D grid. The porous media includes both the unsaturated (soil) and saturated zones (aquifer) and is simulated using a 3D grid. The river flow is simulated through a 1D drainage network. All these mediums are linked through evapotranspiration and flow exchanges (infiltration, river-soil growndwater flow, surface-river overland flow). Besides the water movement, it is also possible to simulate water quality processes and solute/sediment transport. Model setup include the definition of the geometry and the properties of each one of its compartments. After the setup of the model, the only continuous input data that MOHID LAND requires are the atmosphere properties (boundary conditions) that can be provided as timeseries or spacial data. MOHID LAND has been adapted the last 4 years under FP7 and ESA projects to integrate Earth Observation (EO) data, both variable in time and in space. EO data can be used to calibrate/validate or as input/assimilation data to the model. The currently EO data used include LULC (Land Use Land Cover) maps, LAI (Leaf Area Index) maps, EVTP (Evapotranspiration) maps and SWC (Soil Water Content) maps. Model results are improved by the EO data, but the advantage of this integration is that the model can still run without the EO data. This means that model do not stop due to unavailability of EO data and can run on a forecast mode. The LCLU maps are coupled with a database that transforms land use into model properties through lookup tables. The LAI maps, usually based on NDVI satellite images, can be used directly as input to the model. When the vegetation growth is being simulated, the use of a LAI distributed in space improve the model results, by improving, for example, the estimated evapotranspiration, the estimated values of biomass, the nutrient uptake, etc. MOHID LAND calculates a Reference Evapotranspiration (rEVTP), based on the meteorological properties. The Actual Evapotranspiration (aEVTP) is then computed based on vegetation transpiration, soil evaporation and the available water in soil. Alternatively, EO derived maps of EVTP can be used as input to the model, in the place of the rEVTP, or even in the place of the aEVTP, both being provided as boundary condition. The same can be done with SWC maps, that can be used to initialize the model soil water content. The integration of EO data with MOHID LAND was tested and is being continuously developed and applied for support farmers and to help water managers to improve the water management.

Spatially quantifying and attributing 17 years of land cover change to examine post-agricultural forest transition in Hawai`i

NASA Astrophysics Data System (ADS)

Lucas, M.; Trauernicht, C.; Carlson, K. M.; Miura, T.; Giambelluca, T. W.; Chen, Q.

2017-12-01

The past decades in Hawaii have seen large scale land use change and land cover shifts. However, much these dynamics are only described anecdotally or studied at a single locale, with little information on the extent, rate, or direction of change. This lack of data hinders any effort to assess, plan, and prioritize land management. To improve assessments of statewide vegetation and land cover change, this project developed high resolution, sub-pixel, percent cover maps of forest, grassland and bare earth at annual time steps from 1999 to 2016. Vegetation cover was quantified using archived LANDSAT imagery and a custom remote-sensing algorithm developed in the Google Earth Engine platform. A statistical trend analysis of annual maps of the these three proportional land covers were then used to detect land cover transitions across the archipelago. The aim of this work focused on quantifying the total area of change, annual rates of change and final vegetation cover outcomes statewide. Additionally these findings were attributed to past and current land uses and management history by compiling spatial datasets of development, agriculture, forest restoration sites and burned areas statewide. Results indicated that nearly 10% of the state's land surfaces are suspected to have transitioned between the three cover classes during the study period. Total statewide net change resulted in a gain in forest cover with largest areas of change occurring in unmanaged areas, current and past pastoral land, commercial forestry and abandoned cultivated land. The fastest annual rates of change were forest increases that occurred in restoration areas and commercial forestry. These findings indicate that Hawaii is going through a forest transition, primarily driven by agricultural abandonment with likely feedbacks from invasive species, but also influenced by the establishment of forestry production on former agricultural lands that show potential for native forest restoration. These results directly link land management history to land cover outcomes using an innovative approach to quantify change. It is also the first study to quantify forest transition dynamics in Hawaii and points to the need for similar assessments in post-agricultural landscapes on other oceanic islands.

Estimation of evapotranspiration across the conterminous United States using a regression with climate and land-cover data

USGS Publications Warehouse

Sanford, Ward E.; Selnick, David L.

2013-01-01

Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water-balance method was combined with a climate and land-cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971-2000 across the U.S. to obtain long-term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land-cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land-cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land-cover data can also improve those predictions. Using the climate and land-cover data at an 800-m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land-cover data are plentiful.

High Resolution Land Use Land Cover Classification using Landsat Earth Observation Data for the Continental Africa

NASA Astrophysics Data System (ADS)

Midekisa, A.; Bennet, A.; Gething, P. W.; Holl, F.; Andrade-Pacheco, R.; Savory, D. J.; Hugh, S. J.

2016-12-01

Spatially detailed and temporally dynamic land use land cover data is necessary to monitor the state of the land surface for various applications. Yet, such data at a continental to global scale is lacking. Here, we developed high resolution (30 meter) annual land use land cover layers for the continental Africa using Google Earth Engine. To capture ground truth training data, high resolution satellite imageries were visually inspected and used to identify 7, 212 sample Landsat pixels that were comprised entirely of one of seven land use land cover classes (water, man-made impervious surface, high biomass, low biomass, rock, sand and bare soil). For model validation purposes, 80% of points from each class were used as training data, with 20% withheld as a validation dataset. Cloud free Landsat 7 annual composites for 2000 to 2015 were generated and spectral bands from the Landsat images were then extracted for each of the training and validation sample points. In addition to the Landsat spectral bands, spectral indices such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used as covariates in the model. Additionally, calibrated night time light imageries from the National Oceanic and Atmospheric Administration (NOAA) were included as a covariate. A decision tree classification algorithm was applied to predict the 7 land cover classes for the periods 2000 to 2015 using the training dataset. Using the validation dataset, classification accuracy including omission error and commission error were computed for each land cover class. Model results showed that overall accuracy of classification was high (88%). This high resolution land cover product developed for the continental Africa will be available for public use and can potentially enhance the ability of monitoring and studying the state of the Earth's surface.

Built-Up Area and Land Cover Extraction Using High Resolution Pleiades Satellite Imagery for Midrand, in Gauteng Province, South Africa

NASA Astrophysics Data System (ADS)

Fundisi, E.; Musakwa, W.

2017-09-01

Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.

Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

NASA Astrophysics Data System (ADS)

Zhu, Z.; Woodcock, C. E.

2012-12-01

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

Land cover characterization and land surface parameterization research

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Parton, William J.

1997-01-01

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Developed land cover of Puerto Rico

Treesearch

William A. Gould; Sebastian Martinuzzi; Olga M. Ramos Gonzalez

2008-01-01

This map shows the distribution of developed land cover in Puerto Rico (Martinuzzi et al. 2007). Developed land cover refers to urban, built-up and non-vegetated areas that result from human activity. These typically include built structures, concrete, asphalt, and other infrastructure. The developed land cover was estimated using Landsat 7 ETM+ satellite images pan...

Land cover changes in central Sonora Mexico

Treesearch

Diego Valdez-Zamudio; Alejandro Castellanos-Villegas; Stuart Marsh

2000-01-01

Remote sensing techniques have been demonstrated to be very effective tools to help detect, analyze, and evaluate land cover changes in natural areas of the world. Changes in land cover can generally be attributed to either natural or anthropogenic forces. Multitemporal satellite imagery and airborne videography were used to detect, analyze, and evaluate land cover...

The national land use data program of the US Geological Survey

NASA Technical Reports Server (NTRS)

Anderson, J. R.; Witmer, R. E.

1975-01-01

The Land Use Data and Analysis (LUDA) Program which provides a systematic and comprehensive collection and analysis of land use and land cover data on a nationwide basis is described. Maps are compiled at about 1:125,000 scale showing present land use/cover at Level II of a land use/cover classification system developed by the U.S. Geological Survey in conjunction with other Federal and state agencies and other users. For each of the land use/cover maps produced at 1:125,000 scale, overlays are also compiled showing Federal land ownership, river basins and subbasins, counties, and census county subdivisions. The program utilizes the advanced technology of the Special Mapping Center of the U.S. Geological Survey, high altitude NASA photographs, aerial photographs acquired for the USGS Topographic Division's mapping program, and LANDSAT data in complementary ways.

Extraction of land cover change information from ENVISAT-ASAR data in Chengdu Plain

NASA Astrophysics Data System (ADS)

Xu, Wenbo; Fan, Jinlong; Huang, Jianxi; Tian, Yichen; Zhang, Yong

2006-10-01

Land cover data are essential to most global change research objectives, including the assessment of current environmental conditions and the simulation of future environmental scenarios that ultimately lead to public policy development. Chinese Academy of Sciences generated a nationwide land cover database in order to carry out the quantification and spatial characterization of land use/cover changes (LUCC) in 1990s. In order to improve the reliability of the database, we will update the database anytime. But it is difficult to obtain remote sensing data to extract land cover change information in large-scale. It is hard to acquire optical remote sensing data in Chengdu plain, so the objective of this research was to evaluate multitemporal ENVISAT advanced synthetic aperture radar (ASAR) data for extracting land cover change information. Based on the fieldwork and the nationwide 1:100000 land cover database, the paper assesses several land cover changes in Chengdu plain, for example: crop to buildings, forest to buildings, and forest to bare land. The results show that ENVISAT ASAR data have great potential for the applications of extracting land cover change information.

Linking land use changes to surface water quality variability in Lake Victoria: some insights from remote sensing

NASA Astrophysics Data System (ADS)

Mugo, R. M.; Limaye, A. S.; Nyaga, J. W.; Farah, H.; Wahome, A.; Flores, A.

2016-12-01

The water quality of inland lakes is largely influenced by land use and land cover changes within the lake's catchment. In Africa, some of the major land use changes are driven by a number of factors, which include urbanization, intensification of agricultural practices, unsustainable farm management practices, deforestation, land fragmentation and degradation. Often, the impacts of these factors are observable on changes in the land cover, and eventually in the hydrological systems. When the natural vegetation cover is reduced or changed, the surface water flow patterns, water and nutrient retention capacities are also changed. This can lead to high nutrient inputs into lakes, leading to eutrophication, siltation and infestation of floating aquatic vegetation. To assess the relationship between land use and land cover changes in part of the Lake Victoria Basin, a series of land cover maps were derived from Landsat imagery. Changes in land cover were identified through change maps and statistics. Further, the surface water chlorophyll-a concentration and turbidity were derived from MODIS-Aqua data for Lake Victoria. Chlrophyll-a and turbidity are good proxy indicators of nutrient inputs and siltation respectively. The trends in chlorophyll-a and turbidity concentrations were analyzed and compared to the land cover changes over time. Certain land cover changes related to agriculture and urban development were clearly identifiable. While these changes might not be solely responsible for variability in chlrophyll-a and turbidity concentrations in the lake, they are potentially contributing factors to this problem. This work illustrates the importance of addressing watershed degradation while seeking to solve water quality related problems.

GlobCorine- A Joint EEA-ESA Project for Operational Land Cover and Land Use Mapping at Pan-European Scale

NASA Astrophysics Data System (ADS)

Bontemps, S.; Defourny, P.; Van Bogaert, E.; Weber, J. L.; Arino, O.

2010-12-01

Regular and global land cover mapping contributes to evaluating the impact of human activities on the environment. Jointly supported by the European Space Agency and the European Environmental Agency, the GlobCorine project builds on the GlobCover findings and aims at making the full use of the MERIS time series for frequent land cover monitoring. The GlobCover automated classification approach has been tuned to the pan-European continent and adjusted towards a classification compatible with the Corine typology. The GlobCorine 2005 land cover map has been achieved, validated and made available to a broad- level stakeholder community from the ESA website. A first version of the GlobCorine 2009 map has also been produced, demonstrating the possibility for an operational production of frequent and updated global land cover maps.

Development of 2010 national land cover database for the Nepal.

PubMed

Uddin, Kabir; Shrestha, Him Lal; Murthy, M S R; Bajracharya, Birendra; Shrestha, Basanta; Gilani, Hammad; Pradhan, Sudip; Dangol, Bikash

2015-01-15

Land cover and its change analysis across the Hindu Kush Himalayan (HKH) region is realized as an urgent need to support diverse issues of environmental conservation. This study presents the first and most complete national land cover database of Nepal prepared using public domain Landsat TM data of 2010 and replicable methodology. The study estimated that 39.1% of Nepal is covered by forests and 29.83% by agriculture. Patch and edge forests constituting 23.4% of national forest cover revealed proximate biotic interferences over the forests. Core forests constituted 79.3% of forests of Protected areas where as 63% of area was under core forests in the outside protected area. Physiographic regions wise forest fragmentation analysis revealed specific conservation requirements for productive hill and mid mountain regions. Comparative analysis with Landsat TM based global land cover product showed difference of the order of 30-60% among different land cover classes stressing the need for significant improvements for national level adoption. The online web based land cover validation tool is developed for continual improvement of land cover product. The potential use of the data set for national and regional level sustainable land use planning strategies and meeting several global commitments also highlighted. Copyright © 2014 Elsevier Ltd. All rights reserved.

Application of spectrometer cropscan MSR 16R and Landsat imagery for identification the spectral characteristics of land cover

NASA Astrophysics Data System (ADS)

Tampubolon, Togi; Abdullah, Khiruddin bin; San, Lim Hwee

2013-09-01

The spectral characteristics of land cover are basic references in classifying satellite image for geophysics analysis. It can be obtained from the measurements using spectrometer and satellite image processing. The aims of this study to investigate the spectral characteristics of land cover based on the results of measurement using Spectrometer Cropscan MSR 16R and Landsat satellite imagery. The area of study in this research is in Medan, (Deli Serdang, North Sumatera) Indonesia. The scope of this study is the basic survey from the measurements of spectral land cover which is covered several type of land such as a cultivated and managed terrestrial areas, natural and semi-natural, cultivated aquatic or regularly flooded areas, natural and semi-natural aquatic, artificial surfaces and associated areas, bare areas, artificial waterbodies and natural waterbodies. The measurement and verification were conducted using a spectrometer provided their spectral characteristics and Landsat imagery, respectively. The results of the spectral characteristics of land cover shows that each type of land cover have a unique characteristic. The correlation of spectral land cover based on spectrometer Cropscan MSR 16R and Landsat satellite image are above 90 %. However, the land cover of artificial waterbodiese have a correlation under 40 %. That is because the measurement of spectrometer Cropscan MSR 16R and acquisition of Landsat satellite imagery has a time different.

Coupling of Markov chains and cellular automata spatial models to predict land cover changes (case study: upper Ci Leungsi catchment area)

NASA Astrophysics Data System (ADS)

Marko, K.; Zulkarnain, F.; Kusratmoko, E.

2016-11-01

Land cover changes particular in urban catchment area has been rapidly occur. Land cover changes occur as a result of increasing demand for built-up area. Various kinds of environmental and hydrological problems e.g. floods and urban heat island can happen if the changes are uncontrolled. This study aims to predict land cover changes using coupling of Markov chains and cellular automata. One of the most rapid land cover changes is occurs at upper Ci Leungsi catchment area that located near Bekasi City and Jakarta Metropolitan Area. Markov chains has a good ability to predict the probability of change statistically while cellular automata believed as a powerful method in reading the spatial patterns of change. Temporal land cover data was obtained by remote sensing satellite imageries. In addition, this study also used multi-criteria analysis to determine which driving factor that could stimulate the changes such as proximity, elevation, and slope. Coupling of these two methods could give better prediction model rather than just using it separately. The prediction model was validated using existing 2015 land cover data and shown a satisfactory kappa coefficient. The most significant increasing land cover is built-up area from 24% to 53%.

MODIS Vegetative Cover Conversion and Vegetation Continuous Fields

NASA Astrophysics Data System (ADS)

Carroll, Mark; Townshend, John; Hansen, Matthew; DiMiceli, Charlene; Sohlberg, Robert; Wurster, Karl

Land cover change occurs at various spatial and temporal scales. For example, large-scale mechanical removal of forests for agro-industrial activities contrasts with the small-scale clearing of subsistence farmers. Such dynamics vary in spatial extent and rate of land conversion. Such changes are attributable to both natural and anthropogenic factors. For example, lightning- or human-ignited fires burn millions of acres of land surface each year. Further, land cover conversion requires ­contrasting with the land cover modification. In the first instance, the dynamic represents extensive categorical change between two land cover types. Land cover modification mechanisms such as selective logging and woody encroachment depict changes within a given land cover type rather than a conversion from one land cover type to another. This chapter describes the production of two standard MODIS land products used to document changes in global land cover. The Vegetative Cover Conversion (VCC) product is designed primarily to serve as a global alarm for areas where land cover change occurs rapidly (Zhan et al. 2000). The Vegetation Continuous Fields (VCF) product is designed to continuously ­represent ground cover as a proportion of basic vegetation traits. Terra's launch in December 1999 afforded a new opportunity to observe the entire Earth every 1.2 days at 250-m spatial resolution. The MODIS instrument's appropriate spatial and ­temporal resolutions provide the opportunity to substantially improve the characterization of the land surface and changes occurring thereupon (Townshend et al. 1991).

GLCF: Help me

Science.gov Websites

ONLY Deforestation data -- displays changes in land cover MODIS (2001-2005) available globally Forest (1981-2000) available globally Land Cover Classification -- useful for identifying changes in land cover

Producing Information for Corine Database by Using Classification Method: a Case Study of Sazlidere Basin, Istanbul

NASA Astrophysics Data System (ADS)

Sarıyılmaz, F. B.; Musaoğlu, N.; Uluğtekin, N.

2017-11-01

The Sazlidere Basin is located on the European side of Istanbul within the borders of Arnavutkoy and Basaksehir districts. The total area of the basin, which is largely located within the province of Arnavutkoy, is approximately 177 km2. The Sazlidere Basin is faced with intense urbanization pressures and land use / cover change due to the Northern Marmara Motorway, 3rd airport and Channel Istanbul Projects, which are planned to be realized in the Arnavutkoy region. Due to the mentioned projects, intense land use /cover changes occur in the basin. In this study, 2000 and 2012 dated LANDSAT images were supervised classified based on CORINE Land Cover first level to determine the land use/cover classes. As a result, four information classes were identified. These classes are water bodies, forest and semi-natural areas, agricultural areas and artificial surfaces. Accuracy analysis of the images were performed following the classification process. The supervised classified images that have the smallest mapping units 0.09 ha and 0.64 ha were generalized to be compatible with the CORINE Land Cover data. The image pixels have been rearranged by using the thematic pixel aggregation method as the smallest mapping unit is 25 ha. These results were compared with CORINE Land Cover 2000 and CORINE Land Cover 2012, which were obtained by digitizing land cover and land use classes on satellite images. It has been determined that the compared results are compatible with each other in terms of quality and quantity.

Land Cover Characterization Program

USGS Publications Warehouse

,

1997-01-01

(2) identify sources, develop procedures, and organize partners to deliver data and information to meet user requirements. The LCCP builds on the heritage and success of previous USGS land use and land cover programs and projects. It will be compatible with current concepts of government operations, the changing needs of the land use and land cover data users, and the technological tools with which the data are applied.

How well do route survey areas represent landscapes at larger spatial extents? An analysis of land cover composition along Breeding Bird Survey routes

USGS Publications Warehouse

Veech, Joseph A.; Pardieck, Keith L.; Ziolkowski, David

2017-01-01

The occurrence of birds in a survey unit is partly determined by the habitat present. Moreover, some bird species preferentially avoid some land cover types and are attracted to others. As such, land cover composition within the 400 m survey areas along a Breeding Bird Survey (BBS) route clearly influences the species available to be detected. Ideally, to extend survey results to the larger landscape, land cover composition within the survey area should be similar to that at larger spatial extents defining the landscape. Such representativeness helps minimize possible roadside effects (bias), here defined as differences in bird species composition and abundance along a roadside as compared to a larger surrounding landscape. We used land cover data from the 2011 National Land Cover Database to examine representativeness of land cover composition along routes. Using ArcGIS, the percentages of each of 15 land cover types within 400 m buffers along 2,696 U.S. BBS routes were calculated and compared to percentages in 2 km, 5 km, and 10 km buffers surrounding each route. This assessment revealed that aquatic cover types and highly urbanized land tend to be slightly underrepresented in the survey areas. Two anthropogenic cover types (pasture/hay and cropland) may be slightly overrepresented in the survey areas. Over all cover types, 92% of the 2,696 routes exhibited “good” representativeness, with <5 percentage points per cover type difference in proportional cover between the 400 m and 10 km buffers. This assessment further supports previous research indicating that any land-cover-based roadside bias in the bird data of the BBS is likely minimal.

Hydrogeomorphic features mediate the effects of land use/cover on reservoir productivity and food webs

USGS Publications Warehouse

Bremigan, M.T.; Soranno, P.A.; Gonzalez, M.J.; Bunnell, D.B.; Arend, K.K.; Renwick, W.H.; Stein, R.A.; Vanni, M.J.

2008-01-01

Although effects of land use/cover on nutrient concentrations in aquatic systems are well known, half or more of the variation in nutrient concentration remains unexplained by land use/cover alone. Hydrogeomorphic (HGM) landscape features can explain much remaining variation and influence food web interactions. To explore complex linkages among land use/cover, HGM features, reservoir productivity, and food webs, we sampled 11 Ohio reservoirs, ranging broadly in agricultural catchment land use/cover, for 3 years. We hypothesized that HGM features mediate the bottom-up effects of land use/cover on reservoir productivity, chlorophyll a, zooplankton, and recruitment of gizzard shad, an omnivorous fish species common throughout southeastern U.S. reservoirs and capable of exerting strong effects on food web and nutrient dynamics. We tested specific hypotheses using a model selection approach. Percent variation explained was highest for total nitrogen (R2 = 0.92), moderately high for total phosphorus, chlorophyll a, and rotifer biomass (R2 = 0.57 to 0.67), relatively low for crustacean zooplankton biomass and larval gizzard shad hatch abundance (R2 = 0.43 and 0.42), and high for larval gizzard shad survivor abundance (R2 = 0.79). The trophic status models included agricultural land use/cover and an HGM predictor, whereas the zooplankton models had few HGM predictors. The larval gizzard shad models had the highest complexity, including more than one HGM feature and food web components. We demonstrate the importance of integrating land use/cover, HGM features, and food web interactions to investigate critical interactions and feedbacks among physical, chemical, and biological components of linked land-water ecosystems.

Impacts of land cover transitions on surface temperature in China based on satellite observations

NASA Astrophysics Data System (ADS)

Zhang, Yuzhen; Liang, Shunlin

2018-02-01

China has experienced intense land use and land cover changes during the past several decades, which have exerted significant influences on climate change. Previous studies exploring related climatic effects have focused mainly on one or two specific land use changes, or have considered all land use and land cover change types together without distinguishing their individual impacts, and few have examined the physical processes of the mechanism through which land use changes affect surface temperature. However, in this study, we considered satellite-derived data of multiple land cover changes and transitions in China. The objective was to obtain observational evidence of the climatic effects of land cover transitions in China by exploring how they affect surface temperature and to what degree they influence it through the modification of biophysical processes, with an emphasis on changes in surface albedo and evapotranspiration (ET). To achieve this goal, we quantified the changes in albedo, ET, and surface temperature in the transition areas, examined their correlations with temperature change, and calculated the contributions of different land use transitions to surface temperature change via changes in albedo and ET. Results suggested that land cover transitions from cropland to urban land increased land surface temperature (LST) during both daytime and nighttime by 0.18 and 0.01 K, respectively. Conversely, the transition of forest to cropland tended to decrease surface temperature by 0.53 K during the day and by 0.07 K at night, mainly through changes in surface albedo. Decreases in both daytime and nighttime LST were observed over regions of grassland to forest transition, corresponding to average values of 0.44 and 0.20 K, respectively, predominantly controlled by changes in ET. These results highlight the necessity to consider the individual climatic effects of different land cover transitions or conversions in climate research studies. This short-term analysis of land cover transitions in China means our estimates should represent local temperature effects. Changes in ET and albedo explained <60% of the variation in LST change caused by land cover transitions; thus, additional factors that affect surface climate need consideration in future studies.

Effect of landslides on the structural characteristics of land-cover based on complex networks

NASA Astrophysics Data System (ADS)

He, Jing; Tang, Chuan; Liu, Gang; Li, Weile

2017-09-01

Landslides have been widely studied by geologists. However, previous studies mainly focused on the formation of landslides and never considered the effect of landslides on the structural characteristics of land-cover. Here we define the modeling of the graph topology for the land-cover, using the satellite images of the earth’s surface before and after the earthquake. We find that the land-cover network satisfies the power-law distribution, whether the land-cover contains landslides or not. However, landslides may change some parameters or measures of the structural characteristics of land-cover. The results show that the linear coefficient, modularity and area distribution are all changed after the occurence of landslides, which means the structural characteristics of the land-cover are changed.

Hydrologic impacts of land cover variability and change at seasonal to decadal time scales over North America, 1992-2016

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.

2017-12-01

Land cover variability and change have been shown to influence the terrestrial hydrologic cycle by altering the partitioning of moisture and energy fluxes. However, the magnitude and directionality of the relationship between land cover and surface hydrology has been shown to vary substantially across regions. Here, we provide an assessment of the impacts of land cover change on hydrologic processes at seasonal (vegetation phenology) to decadal scales (land cover conversion) in the United States and Mexico. To this end, we combine time series of remotely-sensed land surface characteristics with land cover maps for different decades as input to the Variable Infiltration Capacity hydrologic model. Land surface characteristics (leaf area index, surface albedo, and canopy fraction derived from normalized difference vegetation index) were obtained from the Moderate Resolution Imaging Spectrometer (MODIS) at 8-day intervals over the period 2000-2016. Land cover maps representing conditions in 1992, 2001, and 2011 were derived by homogenizing the National Land Cover Database over the US and the INEGI Series I through V maps over Mexico. An additional map covering all of North America was derived from the most frequent land cover class observed in each pixel of the MODIS MOD12Q1 product during 2001-2013. Land surface characteristics were summarized over land cover fractions at 1/16 degree (6 km) resolution. For each land cover map, hydrologic simulations were conducted that covered the period 1980-2013, using the best-available, hourly meteorological forcings at a similar spatial resolution. Based on these simulations, we present a comparison of the contributions of land cover change and climate variability at seasonal to decadal scales on the hydrologic and energy budgets, identifying the dominant components through time and space. This work also offers a valuable dataset on land cover variability and its hydrologic response for continental-scale assessments and modeling.

Monitoring land use on military installations

USGS Publications Warehouse

Karstensen, K.A.; Loveland, Thomas R.

2009-01-01

The US Geological Survey's Land Cover Trends is a research projects aimed to understand the rates, trends, causes, and consequences of contemporary US land use and land-cover change. The project is using the EPA Level III eco-regions as a geographic framework to process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. The results are expected to be used for collaborative environmental change consequences research with various partners including the National Science Foundation, the National Oceanic and Atmospheric Administration, and the US Fish and Wildlife Service. The Land Cover project can provide geographic understanding of the state of the nation's ecosystems. The project is scheduled to be completed by 2010 and expected to provide an unbiased, national synthesis of land-cover changes.

Regional Climate Modeling over the Marmara Region, Turkey, with Improved Land Cover Data

NASA Astrophysics Data System (ADS)

Sertel, E.; Robock, A.

2007-12-01

Land surface controls the partitioning of available energy at the surface between sensible and latent heat,and controls partitioning of available water between evaporation and runoff. Current land cover data available within the regional climate models such as Regional Atmospheric Modeling System (RAMS), the Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) and Weather Research and Forecasting (WRF) was obtained from 1- km Advanced Very High Resolution Radiometer satellite images spanning April 1992 through March 1993 with an unsupervised classification technique. These data are not up-to-date and are not accurate for all regions and some land cover types such as urban areas. Here we introduce new, up-to-date and accurate land cover data for the Marmara Region, Turkey derived from Landsat Enhanced Thematic Mapper images into the WRF regional climate model. We used several image processing techniques to create accurate land cover data from Landsat images obtained between 2001 and 2005. First, all images were atmospherically and radiometrically corrected to minimize contamination effects of atmospheric particles and systematic errors. Then, geometric correction was performed for each image to eliminate geometric distortions and define images in a common coordinate system. Finally, unsupervised and supervised classification techniques were utilized to form the most accurate land cover data yet for the study area. Accuracy assessments of the classifications were performed using error matrix and kappa statistics to find the best classification results. Maximum likelihood classification method gave the most accurate results over the study area. We compared the new land cover data with the default WRF land cover data. WRF land cover data cannot represent urban areas in the cities of Istanbul, Izmit, and Bursa. As an example, both original satellite images and new land cover data showed the expansion of urban areas into the Istanbul metropolitan area, but in the WRF land cover data only a limited area along the Bosporus is shown as urban. In addition, the new land cover data indicate that the northern part of Istanbul is covered by evergreen and deciduous forest (verified by ground truth data), but the WRF data indicate that most of this region is croplands. In the northern part of the Marmara Region, there is bare ground as a result of open mining activities and this class can be identified in our land cover data, whereas the WRF data indicated this region as woodland. We then used this new data set to conduct WRF simulations for one main and two nested domains, where the inner-most domain represents the Marmara Region with 3 km horizontal resolution. The vertical domain of both main and nested domains extends over 28 vertical levels. Initial and boundary conditions were obtained from National Centers for Environmental Prediction-Department of Energy Reanalysis II and the Noah model was selected as the land surface model. Two model simulations were conducted; one with available land cover data and one with the newly created land cover data. Using detailed meteorological station data within the study area, we find that the simulation with the new land cover data set produces better temperature and precipitation simulations for the region, showing the value of accurate land cover data and that changing land cover data can be an important influence on local climate change.

Photo interpretation key to Michigan land cover/use

NASA Technical Reports Server (NTRS)

Enslin, W. R.; Hudson, W. D.; Lusch, D. P.

1983-01-01

A set of photo interpretation keys is presented to provide a structured approach to the identification of land cover/use categories as specified in the Michigan Resource Inventory Act. The designated categories are urban and; built up lands; agricultural lands; forest land; nonforested land; water bodies; wetlands; and barren land. The keys were developed for use with medium scale (1:20,000 to 1:24,000) color infrared aerial photography. Although each key is generalized in that it relies only upon the most distinguishing photo characteristics in separating the various land cover/use categories, additional interpretation characteristics, distinguishing features and background material are given.