Natural and anthropogenic land cover change and its impact on the regional climate and hydrological extremes over Sanjiangyuan region

NASA Astrophysics Data System (ADS)

Ji, P.; Yuan, X.

2017-12-01

Located in the northern Tibetan Plateau, Sanjiangyuan is the headwater region of the Yellow River, Yangtze River and Mekong River. Besides climate change, natural and human-induced land cover change (e.g., Graze for Grass Project) is also influencing the regional hydro-climate and hydrological extremes significantly. To quantify their impacts, a land surface model (LSM) with consideration of soil moisture-lateral surface flow interaction and quasi-three-dimensional subsurface flow, is used to conduct long-term high resolution simulations driven by China Meteorological Administration Land Data Assimilation System forcing data and different land cover scenarios. In particular, the role of surface and subsurface lateral flows is also analyzed by comparing with typical one-dimensional models. Lateral flows help to simulate soil moisture variability caused by topography at hyper-resolution (e.g., 100m), which is also essential for simulating hydrological extremes including soil moisture dryness/wetness and high/low flows. The LSM will also be coupled with a regional climate model to simulate the effect of natural and anthropogenic land cover change on regional climate, with particular focus on the land-atmosphere coupling at different resolutions with different configurations in modeling land surface hydrology.

Simulation of regional temperature change effect of land cover change in agroforestry ecotone of Nenjiang River Basin in China

NASA Astrophysics Data System (ADS)

Liu, Tingxiang; Zhang, Shuwen; Yu, Lingxue; Bu, Kun; Yang, Jiuchun; Chang, Liping

2017-05-01

The Northeast China is one of typical regions experiencing intensive human activities within short time worldwide. Particularly, as the significant changes of agriculture land and forest, typical characteristics of pattern and process of agroforestry ecotone change formed in recent decades. The intensive land use change of agroforestry ecotone has made significant change for regional land cover, which had significant impact on the regional climate system elements and the interactions among them. This paper took agroforestry ecotone of Nenjiang River Basin in China as study region and simulated temperature change based on land cover change from 1950s to 1978 and from 1978 to 2010. The analysis of temperature difference sensitivity to land cover change based on Weather Research and Forecasting (WRF) model showed that the land cover change from 1950s to 1978 induced warming effect over all the study area, including the change of grassland to agriculture land, grassland to deciduous broad-leaved forest, and deciduous broad-leaved forest to shrub land. The land cover change from 1978 to 2010 induced cooling effect over all the study area, including the change of deciduous broad-leaved forest to agriculture land, grassland to agriculture land, shrub land to agriculture land, and deciduous broad-leaved forest to grassland. In addition, the warming and cooling effect of land cover change was more significant in the region scale than specific land cover change area.

Impacts of Land Cover and Land Use Change on the Hydrology of the US-Mexico Border Region, 1992-2011

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.; Mascaro, G.; White, D. D.

2016-12-01

The semi-arid US-Mexico border region has been experiencing rapid urbanization and agricultural expansion over the last several decades, due in part to the lifting of trade barriers of the 1994 North American Free Trade Agreement (NAFTA), placing additional pressures on the region's already strained water resources. Here we examine the effects of changes in land cover/use over the period 1992-2011 on the region's hydrology and water resources, using the Variable Infiltration Capacity (VIC) model with an irrigation module to estimate both natural and anthropogenic water fluxes. Land cover has been taken from the National Land Cover Database (NLCD) over the US, and from the Instituto Nacional de Estadística y Geografía (INEGI) database over Mexico, for three snapshots: 1992/3, 2001/2, and 2011. We have performed 3 simulations, one per land cover snapshot, at 6 km resolution, driven by a gridded observed meteorology dataset and a climatology of land surface characteristics derived from remote sensing products. Urban water withdrawal rates were estimated from literature. The primary changes in the region's water budget over the period 1992-2011 consisted of: (1) a shift in agricultural irrigation water withdrawals from the US to Mexico, accompanied by similar shifts in runoff (via agricultural return flow) and evapotranspiration; and (2) a 50% increase in urban water withdrawals, concentrated in the US. Because groundwater supplied most of the additional agricultural withdrawals, and occurred over already over-exploited aquifers, these changes call into question the sustainability of the region's land and water management. By synthesizing the implications of these hydrologic changes, we present a novel view of how NAFTA has altered the US-Mexico border region, possibly in unintended ways.

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

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.

Sensitivity of summer climate to anthropogenic land-cover change over the Greater Phoenix, AZ, region

USGS Publications Warehouse

Georgescu, M.; Miguez-Macho, G.; Steyaert, L.T.; Weaver, C.P.

2008-01-01

This work evaluates the first-order effect of land-use/land-cover change (LULCC) on the summer climate of one of the nation's most rapidly expanding metropolitan complexes, the Greater Phoenix, AZ, region. High-resolution-2-km grid spacing-Regional Atmospheric Modeling System (RAMS) simulations of three "wet" and three "dry" summers were carried out for two different land-cover reconstructions for the region: a circa 1992 representation based on satellite observations, and a hypothetical land-cover scenario where the anthropogenic landscape of irrigated agriculture and urban pixels was replaced with current semi-natural vegetation. Model output is evaluated with respect to observed air temperature, dew point, and precipitation. Our results suggest that development of extensive irrigated agriculture adjacent to the urban area has dampened any regional-mean warming due to urbanization. Consistent with previous observationally based work, LULCC produces a systematic increase in precipitation to the north and east of the city, though only under dry conditions. This is due to a change in background atmospheric stability resulting from the advection of both warmth from the urban core and moisture from the irrigated area. ?? 2008 Elsevier Ltd. All rights reserved.

REGIONAL AND GLOBAL PATTERNS OF POPULATION, LAND USE AND LAND COVER CHANGE: AN OVERVIEW OF STRESSORS AND IMPACTS

EPA Science Inventory

This paper provides an overview of land use and land cover (LULC) change and regional to global patterns of that change and responses. Human activities now dominate the Earth's global ecosystem and LULC change is one of the most pervasive and influential activities. LULC change a...

Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China

NASA Astrophysics Data System (ADS)

Maimaitiaili, Ayisulitan; Aji, xiaokaiti; Kondoh, Akihiko

2016-04-01

Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China Ayisulitan Maimaitiaili1, Xiaokaiti Aji2 Akihiko Kondoh2 1Graduate School of Science, Chiba University, Japan 2Center for Environmental Remote Sensing, Chiba University The spatio-temporal changes of Land Use/Cover (LUCC) and its driving forces in Kashgar region, Xinjiang Province, China, are investigated by using satellite remote sensing and a geographical information system (GIS). Main goal of this paper is to quantify the drivers of LUCC. First, considering lack of the Land Cover (LC) map in whole study area, we produced LC map by using Landsat images. Land use information from Landsat data was collected using maximum likelihood classification method. Land use change was studied based on the change detection method of land use types. Second, because the snow provides a key water resources for stream flow, agricultural production and drinking water for sustaining large population in Kashgar region, snow cover are estimated by Spot Vegetation data. Normalized Difference Snow Index (NDSI) algorithm are applied to make snow cover map, which is used to screen the LUCC and climate change. The best agreement is found with threshold value of NDSI≥0.2 to generate multi-temporal snow cover and snowmelt maps. Third, driving forces are systematically identified by LC maps and statistical data such as climate and socio-economic data, regarding to i) the climate changes and ii) socioeconomic development that the spatial correlation among LUCC, snow cover change, climate and socioeconomic changes are quantified by using liner regression model and negative / positive trend analysis. Our results showed that water bodies, bare land and grass land have decreasing notably. By contrast, crop land and urban area have continually increasing significantly, which are dominated in study area. The area of snow/ice have fluctuated and has strong seasonal trends, total annual snow cover

CARETS: A prototype regional environmental information system. Volume 9: Shore zone land use and land cover; Central Atlantic Regional Ecological Test Site

NASA Technical Reports Server (NTRS)

Alexander, R. H. (Principal Investigator); Dolan, R.; Hayden, B. P.; Vincent, C. L.

1975-01-01

The author has identified the following significant results. Analysis of the land use and land cover maps provides a stratification of the CARETS shore area into regions which have a similar environmental organization. Different elements of the landscape are altered less frequently moving inland. Near the beach, higher frequency of monitoring is needed than is needed in the inland areas, including the marsh and estuarine areas.

AN APPROACH FOR DETERMINING REGIONAL LAND COVER AND SPECIES HABITAT DISTRIBUTIONS IN THE AMERICAN SOUTHWEST: THE SOUTHWEST REGIONAL GAP ANALYSIS PROJECT

EPA Science Inventory

The Southwest Regional Gap Analysis Project (SWReGAP) is developing seamless digital coverages for land cover, vertebrate animal habitat, and land management status for the 5-state region of Nevada, Arizona, Utah, New Mexico, and Colorado. The project is a second generation effor...

[Land cover classification of Four Lakes Region in Hubei Province based on MODIS and ENVISAT data].

PubMed

Xue, Lian; Jin, Wei-Bin; Xiong, Qin-Xue; Liu, Zhang-Yong

2010-03-01

Based on the differences of back scattering coefficient in ENVISAT ASAR data, a classification was made on the towns, waters, and vegetation-covered areas in the Four Lakes Region of Hubei Province. According to the local cropping systems and phenological characteristics in the region, and by using the discrepancies of the MODIS-NDVI index from late April to early May, the vegetation-covered areas were classified into croplands and non-croplands. The classification results based on the above-mentioned procedure was verified by the classification results based on the ETM data with high spatial resolution. Based on the DEM data, the non-croplands were categorized into forest land and bottomland; and based on the discrepancies of mean NDVI index per month, the crops were identified as mid rice, late rice, and cotton, and the croplands were identified as paddy field and upland field. The land cover classification based on the MODIS data with low spatial resolution was basically consistent with that based on the ETM data with high spatial resolution, and the total error rate was about 13.15% when the classification results based on ETM data were taken as the standard. The utilization of the above-mentioned procedures for large scale land cover classification and mapping could make the fast tracking of regional land cover classification.

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...

Evaluating relationships between urban land cover composition and evapotranspiration in semi-arid regions

NASA Astrophysics Data System (ADS)

Manago, K. F.; Hogue, T. S.; Litvak, E.; Pataki, D. E.

2016-12-01

California experienced its most severe drought on record in 2013 and 2014, forcing the governor to call for the first statewide reductions in urban water use. This led to numerous water conservation efforts including turf removal and restrictions on outdoor irrigation. The decrease in irrigation across the city of Los Angeles has had major effects on regional hydrologic fluxes. Previous studies have found that conservation efforts have decreased streamflow but little work has been done on the impact of reduced irrigation on Evapotranspiration (ET). ET is one of the most difficult variables to measure as a result of its heterogeneity both spatially and temporally; yet, it is imperative in characterizing energy and hydrologic processes and in aiding water management decisions. Estimating ET is further complicated in urban regions where land cover composition is extremely variable, even at small scales. Irrigated landscape and impervious surfaces are two of the most common land cover types associated with urbanization, but they have opposite effects on ET. While numerous studies have evaluated changes in ET caused by urbanization, they have all produced varying results. This is expected as changes to ET are highly dependent on land cover composition. In this study, we modeled the relationship between ET and urban land cover change in Los Angeles. We utilized empirical equations derived from in situ measurements to calculate tree and irrigated turfgrass ET and compared the results to estimates based on remote-sensing and California Irrigation Management Information System (CIMIS) network of weather stations. We found that unshaded turfgrass largely increased ET compared to impervious surfaces, which reveals lavish irrigation practices. Trees also increased ET, but they provided shade that decreased ET from turf grass. With much of the western United States facing drought and water supply uncertainty due to climate change, understanding and predicting how land cover

Downscaling global land-use/land-cover projections for use in region-level state-and-transition simulation modeling

USGS Publications Warehouse

Sherba, Jason T.; Sleeter, Benjamin M.; Davis, Adam W.; Parker, Owen P.

2015-01-01

Global land-use/land-cover (LULC) change projections and historical datasets are typically available at coarse grid resolutions and are often incompatible with modeling applications at local to regional scales. The difficulty of downscaling and reapportioning global gridded LULC change projections to regional boundaries is a barrier to the use of these datasets in a state-and-transition simulation model (STSM) framework. Here we compare three downscaling techniques to transform gridded LULC transitions into spatial scales and thematic LULC classes appropriate for use in a regional STSM. For each downscaling approach, Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) LULC projections, at the 0.5 × 0.5 cell resolution, were downscaled to seven Level III ecoregions in the Pacific Northwest, United States. RCP transition values at each cell were downscaled based on the proportional distribution between ecoregions of (1) cell area, (2) land-cover composition derived from remotely-sensed imagery, and (3) historic LULC transition values from a LULC history database. Resulting downscaled LULC transition values were aggregated according to their bounding ecoregion and “cross-walked” to relevant LULC classes. Ecoregion-level LULC transition values were applied in a STSM projecting LULC change between 2005 and 2100. While each downscaling methods had advantages and disadvantages, downscaling using the historical land-use history dataset consistently apportioned RCP LULC transitions in agreement with historical observations. Regardless of the downscaling method, some LULC projections remain improbable and require further investigation.

Land Use and Land Cover Changes 1977 to 2000 in the Steppe Region of Ukraine, and Preliminary Results of Evaluating its Ecological and Land Form Implications

NASA Astrophysics Data System (ADS)

White, G. J.; Prydatko, V.; Luhmann, E. P.

2001-05-01

Ukraine's history as agro-economic region dates back hundreds of years, being the most productive portion of the "black earth region" for the now defunct Soviet Union. This incredible level of agricultural production brought tremendous changes to the landscape matrix, largely eliminating forests and prairie systems from the southern steppe regions of Ukraine. The age of industrialization has had far less significant impacts to the land use patterns as large farms were operated and managed under Soviet Era cooperatives. The recent, 1992, independence of Ukraine has brought new pressures to the landscape. These pressures are initiated by economic needs of Ukraine seeking to be resolved through increased farm production and rapid land and industrial privatization. This study examines land cover changes between 1977, 1988 and 2000 within a representative region of southern Ukraine and northern Crimea. The region covers prototypical landscapes of the steppe region of agriculture at various scales and crops. The study area also allows an examination of changes along coastal areas in the Azov and Black Seas, specifically barrier systems. Additionally, areas of rapid privatization of industries and introduction of western industries exist within this region. The years selected for documentation were chosen as being one near the height of Soviet autonomy, near separation of the Soviet Union and independence of Ukraine and current times. The study looks at ways of documenting land cover change using satellite imagery with ancillary ground based information. The study evaluates effects of these land cover changes through associated losses of hydrologic characteristics in the landscape such as stream, as well as landform changes especially in coastal barrier systems. These changes are correlated to landscape changes and ecological parameters recorded during this nearly 30 year period. Preliminary conclusions are presented as to alternative land use practices and actions for

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

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.

The impact of anthropogenic land use and land cover change on regional climate extremes.

PubMed

Findell, Kirsten L; Berg, Alexis; Gentine, Pierre; Krasting, John P; Lintner, Benjamin R; Malyshev, Sergey; Santanello, Joseph A; Shevliakova, Elena

2017-10-20

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

Modelling land cover change in the Ganga basin

NASA Astrophysics Data System (ADS)

Moulds, S.; Tsarouchi, G.; Mijic, A.; Buytaert, W.

2013-12-01

Over recent decades the green revolution in India has driven substantial environmental change. Modelling experiments have identified northern India as a 'hot spot' of land-atmosphere coupling strength during the boreal summer. However, there is a wide range of sensitivity of atmospheric variables to soil moisture between individual climate models. The lack of a comprehensive land cover change dataset to force climate models has been identified as a major contributor to model uncertainty. In this work a time series dataset of land cover change between 1970 and 2010 is constructed for northern India to improve the quantification of regional hydrometeorological feedbacks. The MODIS instrument on board the Aqua and Terra satellites provides near-continuous remotely sensed datasets from 2000 to the present day. However, the quality of satellite products before 2000 is poor. To complete the dataset MODIS images are extrapolated back in time using the Conversion of Land Use and its Effects at small regional extent (CLUE-s) modelling framework. Non-spatial estimates of land cover area from national agriculture and forest statistics, available on a state-wise, annual basis, are used as a direct model input. Land cover change is allocated spatially as a function of biophysical and socioeconomic drivers identified using logistic regression. This dataset will provide an essential input to a high resolution, physically based land surface model to generate the lower boundary condition to assess the impact of land cover change on regional climate.

Hydrological Response to Land Cover Changes and Human Activities in Arid Regions Using a Geographic Information System and Remote Sensing

PubMed Central

Mahmoud, Shereif H.; Alazba, A. A.

2015-01-01

The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km2 area, whereas the increase in such depth reached only 10 mm/year in a 243-km2 area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km2 of land area by 2030, a significant decrease from the 747 km2 they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities. PMID:25923712

Ecoregions and land cover trends in Senegal

USGS Publications Warehouse

Tappan, G. Gray; Sall, M.; Wood, E.C.; Cushing, Matthew

2004-01-01

This study examines long-term changes in Senegal's natural resources. We monitor and quantify land use and land cover changes occurring across Senegal using nearly 40 years of satellite imagery, aerial surveys, and fieldwork. We stratify Senegal into ecological regions and present land use and land cover trends for each region, followed by a national summary. Results aggregated to the national level show moderate change, with a modest decrease in savannas from 74 to 70 percent from 1965 to 2000, and an expansion of cropland from 17 to 21 percent. However, at the ecoregion scale, we observed rapid change in some and relative stability in others. One particular concern is the decline in Senegal's biodiverse forests. However, in the year 2000, Senegal's savannas, woodlands, and forests still cover more than two-thirds of the country, and the rate of agricultural expansion has slowed.

Validation of national land-cover characteristics data for regional water-quality assessment

USGS Publications Warehouse

Zelt, Ronald B.; Brown, Jesslyn F.; Kelley, M.S.

1995-01-01

Land-cover information is used routinely to support the interpretation of water-quality data. The Prototype 1990 Conterminous US Land Cover Characteristics Data Set, developed primarily from Advanced Very High Resolution Radiometer (AVHRR) data, was made available to the US Geological Survey's National Water-Quality Assessment (NAWQA) Program. The study described in this paper explored the utility of the 1990 national data set for developing quantitative estimates of the areal extent of principal land-cover types within large areal units. Land-cover data were collected in 1993 at 210 sites in the Central Nebraska Basins, one of the NAWQA study units. Median percentage-corn estimates for each sampling stratum wre used to produce areally weighted estimates of the percentage-corn cover for hydrologic units. Comparison of those areal estimates with an independent source of 1992 land-cover data showed good agreement. -Authors

Land Use and Land Cover Change in the Qinghai Lake Region of the Tibetan Plateau and Its Impact on Ecosystem Services

PubMed Central

Gong, Jian; Yang, Jianxin; Tang, Wenwu

2017-01-01

Exploration of land use and land cover change (LULCC) and its impacts on ecosystem services in Tibetan plateau is valuable for landscape and environmental conservation. In this study, we conduct spatial analysis on empirical land use and land cover data in the Qinghai Lake region for 1990, 2000, and 2010 and simulate land cover patterns for 2020. We then evaluate the impacts of LULCC on ecosystem service value (ESV), and analyze the sensitivity of ESV to LULCC to identify the ecologically sensitive area. Our results indicate that, from 1990 to 2010, the area of forest and grassland increased while the area of unused land decreased. Simulation results suggest that the area of grassland and forest will continue to increase and the area of cropland and unused land will decrease for 2010–2020. The ESV in the study area increased from 694.50 billion Yuan in 1990 to 714.28 billion Yuan in 2000, and to 696.72 billion Yuan in 2020. Hydrology regulation and waste treatment are the top two ecosystem services in this region. The towns surrounding the Qinghai Lake have high ESVs, especially in the north of the Qinghai Lake. The towns with high ESV sensitivity to LULCC are located in the northwest, while the towns in the north of the Qinghai Lake experienced substantial increase in sensitivity index from 2000–2010 to 2010–2020, especially for three regulation services and aesthetic landscape provision services. PMID:28754029

Land Use and Land Cover Change in the Qinghai Lake Region of the Tibetan Plateau and Its Impact on Ecosystem Services.

PubMed

Gong, Jian; Li, Jingye; Yang, Jianxin; Li, Shicheng; Tang, Wenwu

2017-07-21

Exploration of land use and land cover change (LULCC) and its impacts on ecosystem services in Tibetan plateau is valuable for landscape and environmental conservation. In this study, we conduct spatial analysis on empirical land use and land cover data in the Qinghai Lake region for 1990, 2000, and 2010 and simulate land cover patterns for 2020. We then evaluate the impacts of LULCC on ecosystem service value (ESV), and analyze the sensitivity of ESV to LULCC to identify the ecologically sensitive area. Our results indicate that, from 1990 to 2010, the area of forest and grassland increased while the area of unused land decreased. Simulation results suggest that the area of grassland and forest will continue to increase and the area of cropland and unused land will decrease for 2010-2020. The ESV in the study area increased from 694.50 billion Yuan in 1990 to 714.28 billion Yuan in 2000, and to 696.72 billion Yuan in 2020. Hydrology regulation and waste treatment are the top two ecosystem services in this region. The towns surrounding the Qinghai Lake have high ESVs, especially in the north of the Qinghai Lake. The towns with high ESV sensitivity to LULCC are located in the northwest, while the towns in the north of the Qinghai Lake experienced substantial increase in sensitivity index from 2000-2010 to 2010-2020, especially for three regulation services and aesthetic landscape provision services.

Recent land cover changes and sensitivity of the model simulations to various land cover datasets for China

NASA Astrophysics Data System (ADS)

Chen, Liang; Ma, Zhuguo; Mahmood, Rezaul; Zhao, Tianbao; Li, Zhenhua; Li, Yanping

2017-08-01

Reliable land cover data are important for improving numerical simulation by regional climate model, because the land surface properties directly affect climate simulation by partitioning of energy, water and momentum fluxes and by determining temperature and moisture at the interface between the land surface and atmosphere. China has experienced significant land cover change in recent decades and accurate representation of these changes is, hence, essential. In this study, we used a climate model to examine the changes experienced in the regional climate because of the different land cover data in recent decades. Three sets of experiments are performed using the same settings, except for the land use/cover (LC) data for the years 1990, 2000, 2009, and the model default LC data. Three warm season periods are selected, which represented a wet (1998), normal (2000) and a dry year (2011) for China in each set of experiment. The results show that all three sets of land cover experiments simulate a warm bias relative to the control with default LC data for near-surface temperature in summertime in most parts of China. It is especially noticeable in the southwest China and south of the Yangtze River, where significant changes of LC occurred. Deforestation in southwest China and to the south of Yangtze River in the experiment cases may have contributed to the negative precipitation bias relative to the control cases. Large LC changes in northwestern Tibetan Plateau for 2000 and 2009 datasets are also associated with changes in surface temperature, precipitation, and heat fluxes. Wind anomalies and energy budget changes are consistent with the precipitation and temperature changes.

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

A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets

USGS Publications Warehouse

Giri, C.; Zhu, Z.; Reed, B.

2005-01-01

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced

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.

Modeled impact of anthropogenic land cover change on climate

USGS Publications Warehouse

Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.

2007-01-01

Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

Regional differences of urbanization in the conterminous U.S. on upland forest land cover, 1973-2011

USGS Publications Warehouse

Auch, Roger F.; Drummond, Mark A.; Xian, George Z.; Sayler, Kristi L.; Acevedo, William; Taylor, Janis

2016-01-01

In this U.S. Geological Survey study of forest land cover across the conterminous U.S. (CONUS), specific proportions and rates of forest conversion to developed (urban) land were assessed on an ecoregional basis. The study period was divided into six time intervals between 1973 and 2011. Forest land cover was the source of 40% or more of the new urban land in 35 of the 84 ecoregions located within the CONUS. In 11 of these ecoregions this threshold exceeded in every time interval. When the percent of change, forest to urban, was compared to the percent of forest in each ecoregion, 58 ecoregions had a greater percent of change and, in six of those, change occurred in every time interval. Annual rates of forest to urban land cover change of 0.2% or higher occurred in 12 ecoregions at least once and in one ecoregion in all intervals. There were three ecoregions where the above conditions were met for nearly every time interval. Even though only a small number of the ecoregions were heavily impacted by forest loss to urban development within the CONUS, the ecosystem services provided by undeveloped forest land cover need to be quantified more completely to better inform future regional land management.

Analysis of historical forest fire regime in Madrid region (1984-2010) and its relation with land-use/land-cover changes

NASA Astrophysics Data System (ADS)

Gómez-Nieto, Israel; Martín, María del Pilar; Salas, Francisco Javier; Gallardo, Marta

2013-04-01

Understanding the interaction between natural and socio-economic factors that determine fire regime is essential to make accurate projections and impact assessments. However, this requires having accurate historical, systematic, homogeneous and spatially explicit information on fire occurrence. Fire databases usually have serious limitations in this regard; therefore other sources of information, such as remote sensing, have emerged as alternatives to generate optimal fire maps on various spatial and temporal scales. Several national and international projects work in order to generate information to study the factors that determine the current fire regime and its future evolution. This work is included in the framework of the project "Forest fires under climate, social and economic Changes in Europe, the Mediterranean and other fire-affected areas of the World" (FUME http://www.fumeproject.eu), which aims to study the changes and factors related to fire regimes through time to determine the potential impacts on vegetation in Mediterranean regions and concrete steps to address future risk scenarios. We analyzed the changes in the fire regime in Madrid region (Spain) in the past three decades (1984-2010) and its relation to land use changes. We identified and mapped fires that have occurred in the region during those years using Landsat satellite images by combining digital techniques and visual analysis. The results show a clear cyclical behaviour of the fire, with years of high incidence (as 1985, 2000 and 2003, highlighted by the number of fires and the area concerned, over 2000 ha) followed by another with a clear occurrence decrease. At the same time, we analyzed the land use changes that have occurred in Madrid region between the early 80s and mid-2000s using as reference the CORINE Land-cover maps (1990, 2000 and 2006) and the Vegetation and Land Use map of the Community of Madrid, 1982. We studied the relationship between fire regimes and observed land

Impacts of Land Cover Changes on Climate over China

NASA Astrophysics Data System (ADS)

Chen, L.; Frauenfeld, O. W.

2014-12-01

Land cover changes can influence regional climate through modifying the surface energy balance and water fluxes, and can also affect climate at large scales via changes in atmospheric general circulation. With rapid population growth and economic development, China has experienced significant land cover changes, such as deforestation, grassland degradation, and farmland expansion. In this study, the Community Earth System Model (CESM) is used to investigate the climate impacts of anthropogenic land cover changes over China. To isolate the climatic effects of land cover change, we focus on the CAM and CLM models, with prescribed climatological sea surface temperature and sea ice cover. Two experiments were performed, one with current vegetation and the other with potential vegetation. Current vegetation conditions were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations, and potential vegetation over China was obtained from Ramankutty and Foley's global potential vegetation dataset. Impacts of land cover changes on surface air temperature and precipitation are assessed based on the difference of the two experiments. Results suggest that land cover changes have a cold-season cooling effect in a large region of China, but a warming effect in summer. These temperature changes can be reconciled with albedo forcing and evapotranspiration. Moreover, impacts on atmospheric circulation and the Asian Monsoon is also discussed.

Effect of land cover and green space on land surface temperature of a fast growing economic region in Malaysia

NASA Astrophysics Data System (ADS)

Sheikhi, A.; Kanniah, K. D.; Ho, C. H.

2015-10-01

Green space must be increased in the development of new cities as green space can moderate temperature in the cities. In this study we estimated the land surface temperature (LST) and established relationships between LST and land cover and various vegetation and urban surface indices in the Iskandar Malaysia (IM) region. IM is one of the emerging economic gateways of Malaysia, and is envisaged to transform into a metropolis by 2025. This change may cause increased temperature in IM and therefore we conducted a study by using Landsat 5 image covering the study region (2,217 km2) to estimate LST, classify different land covers and calculate spectral indices. Results show that urban surface had highest LST (24.49 °C) and the lowest temperature was recorded in, forest, rubber and water bodies ( 20.69 to 21.02°C). Oil palm plantations showed intermediate mean LST values with 21.65 °C. We further investigated the relationship between vegetation and build up densities with temperature. We extracted 1000 collocated pure pixels of Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Built-up Index (NDBI), Urban Index (UI) and LST in the study area. Results show a strong and significant negative correlation with (R2= -0.74 and -0.79) respectively between NDVI, NDWI and LST . Meanwhile a strong positive correlation (R2=0.8 and 0.86) exists between NDBI, UI and LST. These results show the importance of increasing green cover in urban environment to combat any adverse effects of climate change.

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.

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

Accuracy assessment for the U.S. Geological Survey Regional Land-Cover Mapping Program: New York and New Jersey Region

Treesearch

Zhiliang Zhu; Limin Yang; Stephen V. Stehman; Raymond L. Czaplewski

2000-01-01

The U.S. Geological Survey, in cooperation with other government and private organizations, is producing a conterminous U.S. land-cover map using Landsat Thematic Mapper 30-meter data for the Federal regions designated by the U.S. Environmental Protection Agency. Accuracy assessment is to be conducted for each Federal region to estimate overall and class-specific...

The Impact of Land Use and Land Cover Change on Water Yield in the Jing- Jin-Ji Region in China

NASA Astrophysics Data System (ADS)

Li, Suxiao; Yang, Hong

2017-04-01

Water yield is one of the key ecosystem services sustaining both people's life and economic development. However, the water yield function is sensitive to anthropogenic activity especially the land use and land cover change (LUCC). Assessment of historical LUCC and its impact on water yield could benefit designing and implementing appropriate land use strategy that enhance the water yield capacity. Beijing (Jing) and its surrounding areas of Tianjin (Jin) and Hebei (Ji) is the political, cultural and economic center of China. The region is facing increasingly water crisis. Taking the Jing-Jin-Ji region as a study area, this study analyzed the historical LUCC and its impact on water yield by using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to spatially map and quantify the changes of water yield from 1995 to 2010. The results showed there was main decline in area of wetland and forest and increase in area of crop land and built up land. An abrupt decline in water yield was found for year 2000. The water yield was influenced to a great extent by precipitation and evapotranspiration, but the land use played an important role in the water yield capacity (water yield per unit area) through plant cover that affected evapotranspiration, soil water permeability and the capacity of holding the moisture content. By general ranking, the water yield capacity of different land use type was as follows: built-up>bare land>cropland> grassland>forest >wetland, which illustrated that the built-up and bare land had higher run off rate while the vegetation area had higher capacity to control surface run off to increase the groundwater. A good understanding of temporal-spatial allocation of historical LUCC and Water yield of the Jing-Jin-Ji region could help guide land use policy decisions that take into consideration of tradeoffs with respect to spatial distribution of ecosystem services amongst the three administrative entities (Jing-Jin-Ji) and

Survey methods for assessing land cover map accuracy

USGS Publications Warehouse

Nusser, S.M.; Klaas, E.E.

2003-01-01

The increasing availability of digital photographic materials has fueled efforts by agencies and organizations to generate land cover maps for states, regions, and the United States as a whole. Regardless of the information sources and classification methods used, land cover maps are subject to numerous sources of error. In order to understand the quality of the information contained in these maps, it is desirable to generate statistically valid estimates of accuracy rates describing misclassification errors. We explored a full sample survey framework for creating accuracy assessment study designs that balance statistical and operational considerations in relation to study objectives for a regional assessment of GAP land cover maps. We focused not only on appropriate sample designs and estimation approaches, but on aspects of the data collection process, such as gaining cooperation of land owners and using pixel clusters as an observation unit. The approach was tested in a pilot study to assess the accuracy of Iowa GAP land cover maps. A stratified two-stage cluster sampling design addressed sample size requirements for land covers and the need for geographic spread while minimizing operational effort. Recruitment methods used for private land owners yielded high response rates, minimizing a source of nonresponse error. Collecting data for a 9-pixel cluster centered on the sampled pixel was simple to implement, and provided better information on rarer vegetation classes as well as substantial gains in precision relative to observing data at a single-pixel.

Review of Land Use and Land Cover Change research progress

NASA Astrophysics Data System (ADS)

Chang, Yue; Hou, Kang; Li, Xuxiang; Zhang, Yunwei; Chen, Pei

2018-02-01

Land Use and Land Cover Change (LUCC) can reflect the pattern of human land use in a region, and plays an important role in space soil and water conservation. The study on the change of land use patterns in the world is of great significance to cope with global climate change and sustainable development. This paper reviews the main research progress of LUCC at home and abroad, and suggests that land use change has been shifted from land use planning and management to land use change impact and driving factors. The development of remote sensing technology provides the basis and data for LUCC with dynamic monitoring and quantitative analysis. However, there is no uniform standard for land use classification at present, which brings a lot of inconvenience to the collection and analysis of land cover data. Globeland30 is an important milestone contribution to the study of international LUCC system. More attention should be paid to the accuracy and results contrasting test of land use classification obtained by remote sensing technology.

A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data

USGS Publications Warehouse

Stibig, H.-J.; Belward, A.S.; Roy, P.S.; Rosalina-Wasrin, U.; Agrawal, S.; Joshi, P.K.; ,; Beuchle, R.; Fritz, S.; Mubareka, S.; Giri, C.

2007-01-01

Aim  Our aim was to produce a uniform ‘regional’ land-cover map of South and Southeast Asia based on ‘sub-regional’ mapping results generated in the context of the Global Land Cover 2000 project.Location  The ‘region’ of tropical and sub-tropical South and Southeast Asia stretches from the Himalayas and the southern border of China in the north, to Sri Lanka and Indonesia in the south, and from Pakistan in the west to the islands of New Guinea in the far east.Methods  The regional land-cover map is based on sub-regional digital mapping results derived from SPOT-VEGETATION satellite data for the years 1998–2000. Image processing, digital classification and thematic mapping were performed separately for the three sub-regions of South Asia, continental Southeast Asia, and insular Southeast Asia. Landsat TM images, field data and existing national maps served as references. We used the FAO (Food and Agriculture Organization) Land Cover Classification System (LCCS) for coding the sub-regional land-cover classes and for aggregating the latter to a uniform regional legend. A validation was performed based on a systematic grid of sample points, referring to visual interpretation from high-resolution Landsat imagery. Regional land-cover area estimates were obtained and compared with FAO statistics for the categories ‘forest’ and ‘cropland’.Results  The regional map displays 26 land-cover classes. The LCCS coding provided a standardized class description, independent from local class names; it also allowed us to maintain the link to the detailed sub-regional land-cover classes. The validation of the map displayed a mapping accuracy of 72% for the dominant classes of ‘forest’ and ‘cropland’; regional area estimates for these classes correspond reasonably well to existing regional statistics.Main conclusions  The land-cover map of South and Southeast Asia provides a synoptic view of the distribution of land cover of tropical and sub

Modeling vulnerability to thermokarst disturbance and its consequences on regional land cover dynamic in boreal Alaska

NASA Astrophysics Data System (ADS)

Genet, H.; Lara, M. J.; Bolton, W. R.; McGuire, A. D.

2016-12-01

Estimation of the magnitude and consequences of permafrost degradation in high latitude is one of the most urgent research challenges related to contemporary and future climate change. In addition to widespread vertical degradation, ice-rich permafrost can thaw laterally, often triggering abrupt subsidence of the ground surface called thermokart. In this depression, permafrost plateau vegetation will transition to wetlands or lakes, while surface water of the surrounding landscape may drain towards it. These abrupt changes in land cover and hydrology can have dramatic consequences from wildlife habitat and biogeochemical cycles. Although recent studies have documented an acceleration of the rates of thermokarst formation in boreal and arctic peatlands, the importance of thermokarst at the regional level is still poorly understood. To better understand the vulnerability of the landscape to thermokarst disturbance in Alaska, we developed the Alaska Thermokarst Model (ATM), a state-and-transition model designed to simulate land cover change associated with thermokarst disturbance. In boreal regions, the model simulates transitions from permafrost plateau forest to thermokarst lake, bog or fen, as a function of climate and fire dynamics, permafrost characteristics and physiographic information. This model is designed and parameterized based on existing literature and a new repeated imagery analysis we conducted in a major wetland complex in boreal Alaska. We will present simulation and validation of thermokarst dynamic and associated land cover change in two wetland complexes in boreal Alaska, from 2000 to 2100 for six climate scenarios associating three AR5 emission scenarios and two global circulation model simulations. By 2100, ATM is predicting decrease between 3.5 and 9.1 % in the extent of permafrost plateau forest, mostly to the benefit of thermokarst fen, and lake. This analysis allowed us to assess the importance of thermokarst dynamics and landscape evolution

Land cover in Upper Egypt assessed using regional and global land cover products derived from MODIS imagery.

PubMed

Fuller, Douglas O; Parenti, Michael S; Gad, Adel M; Beier, John C

2012-01-01

Irrigation along the Nile River has resulted in dramatic changes in the biophysical environment of Upper Egypt. In this study we used a combination of MODIS 250 m NDVI data and Landsat imagery to identify areas that changed from 2001-2008 as a result of irrigation and water-level fluctuations in the Nile River and nearby water bodies. We used two different methods of time series analysis -- principal components (PCA) and harmonic decomposition (HD), applied to the MODIS 250 m NDVI images to derive simple three-class land cover maps and then assessed their accuracy using a set of reference polygons derived from 30 m Landsat 5 and 7 imagery. We analyzed our MODIS 250 m maps against a new MODIS global land cover product (MOD12Q1 collection 5) to assess whether regionally specific mapping approaches are superior to a standard global product. Results showed that the accuracy of the PCA-based product was greater than the accuracy of either the HD or MOD12Q1 products for the years 2001, 2003, and 2008. However, the accuracy of the PCA product was only slightly better than the MOD12Q1 for 2001 and 2003. Overall, the results suggest that our PCA-based approach produces a high level of user and producer accuracies, although the MOD12Q1 product also showed consistently high accuracy. Overlay of 2001-2008 PCA-based maps showed a net increase of 12 129 ha of irrigated vegetation, with the largest increase found from 2006-2008 around the Districts of Edfu and Kom Ombo. This result was unexpected in light of ambitious government plans to develop 336 000 ha of irrigated agriculture around the Toshka Lakes.

Land-cover change in the Ozark Highlands, 1973-2000

USGS Publications Warehouse

Karstensen, Krista A.

2010-01-01

Led 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 Project was initiated in 1999 and aims to document the types, geographic distributions, and rates of land-cover change on a region by region basis for the conterminous United States, and to determine some of the key drivers and consequences of the change (Loveland and others, 2002). For 1973, 1980, 1986, 1992, and 2000 land-cover maps derived from the Landsat series are classified by visual interpretation, inspection of historical aerial photography and ground survey, into 11 land-cover classes. The classes are defined to capture land cover that is discernable in Landsat data. A stratified probability-based sampling methodology undertaken within the 84 Omernik Level III Ecoregions (Omernik, 1987) was used to locate the blocks, with 9 to 48 blocks per ecoregion. The sampling was designed to enable a statistically robust 'scaling up' of the sample-classification data to estimate areal land-cover change within each ecoregion (Loveland and others, 2002; Stehman and others, 2005). At the time of writing, approximately 90 percent of the 84 conterminous United States ecoregions have been processed by the Land-Cover Trends Project. Results from these completed ecoregions illustrate that across the conterminous United States there is no single profile of land-cover/land-use change, rather, there are varying pulses affected by clusters of change agents (Loveland and others, 2002). Land-Cover Trends Project results for the conterminous United States to-date are being used for collaborative environmental change research with partners such as; the National Science Foundation, the National Oceanic and Atmospheric Administration, and the U.S. Fish and Wildlife Service. The strategy has also been adapted for use in a NASA global

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.

Land-cover change detection

USGS Publications Warehouse

Chen, Xuexia; Giri, Chandra; Vogelmann, James

2012-01-01

Land cover is the biophysical material on the surface of the earth. Land-cover types include grass, shrubs, trees, barren, water, and man-made features. Land cover changes continuously.  The rate of change can be either dramatic and abrupt, such as the changes caused by logging, hurricanes and fire, or subtle and gradual, such as regeneration of forests and damage caused by insects (Verbesselt et al., 2001).  Previous studies have shown that land cover has changed dramatically during the past sevearal centuries and that these changes have severely affected our ecosystems (Foody, 2010; Lambin et al., 2001). Lambin and Strahlers (1994b) summarized five types of cause for land-cover changes: (1) long-term natural changes in climate conditions, (2) geomorphological and ecological processes, (3) human-induced alterations of vegetation cover and landscapes, (4) interannual climate variability, and (5) human-induced greenhouse effect.  Tools and techniques are needed to detect, describe, and predict these changes to facilitate sustainable management of natural resources.

Development of a land-cover characteristics database for the conterminous U.S.

USGS Publications Warehouse

Loveland, Thomas R.; Merchant, J.W.; Ohlen, D.O.; Brown, Jesslyn F.

1991-01-01

Information regarding the characteristics and spatial distribution of the Earth's land cover is critical to global environmental research. A prototype land-cover database for the conterminous United States designed for use in a variety of global modelling, monitoring, mapping, and analytical endeavors has been created. The resultant database contains multiple layers, including the source AVHRR data, the ancillary data layers, the land-cover regions defined by the research, and translation tables linking the regions to other land classification schema (for example, UNESCO, USGS Anderson System). The land-cover characteristics database can be analyzed, transformed, or aggregated by users to meet a broad spectrum of requirements. -from Authors

Thematic accuracy of the National Land Cover Database (NLCD) 2001 land cover for Alaska

USGS Publications Warehouse

Selkowitz, D.J.; Stehman, S.V.

2011-01-01

The National Land Cover Database (NLCD) 2001 Alaska land cover classification is the first 30-m resolution land cover product available covering the entire state of Alaska. The accuracy assessment of the NLCD 2001 Alaska land cover classification employed a geographically stratified three-stage sampling design to select the reference sample of pixels. Reference land cover class labels were determined via fixed wing aircraft, as the high resolution imagery used for determining the reference land cover classification in the conterminous U.S. was not available for most of Alaska. Overall thematic accuracy for the Alaska NLCD was 76.2% (s.e. 2.8%) at Level II (12 classes evaluated) and 83.9% (s.e. 2.1%) at Level I (6 classes evaluated) when agreement was defined as a match between the map class and either the primary or alternate reference class label. When agreement was defined as a match between the map class and primary reference label only, overall accuracy was 59.4% at Level II and 69.3% at Level I. The majority of classification errors occurred at Level I of the classification hierarchy (i.e., misclassifications were generally to a different Level I class, not to a Level II class within the same Level I class). Classification accuracy was higher for more abundant land cover classes and for pixels located in the interior of homogeneous land cover patches. ?? 2011.

Revealing Land Cover Change in California With Satellite Data

NASA Astrophysics Data System (ADS)

Potter, Christopher; Genovese, Vanessa; Gross, Peggy; Boriah, Shyam; Steinbach, Michael; Kumar, Vipin

2007-06-01

The conversion of natural land cover into human-dominated cover types continues to be a change of global proportions with many unknown environmental consequences. Noteworthy conversions of this type include tree stand harvests in forested regions, urbanization, and agricultural intensification in former woodland and natural grassland areas. Determining where, when, and why natural ecosystem conversions occur is a crucial scientific concern [Foley et al., 2005]. Characteristics of the land cover can have important impacts on local climate, radiation balance, biogeochemistry, hydrology and the diversity and abundance of terrestrial species [Randerson et al., 2006]. Consequently, understanding trends in land cover conversion at local scales is a requirement for making useful numerical predictions about other regional and global changes. It is urgent that accurate, timely, and economical tools be made available to document these conversions and aid in the management of their impacts.

Completion of the National Land Cover Database (NLCD) 1992-2001 Land Cover Change Retrofit Product

EPA Science Inventory

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 betwe...

Globally scalable generation of high-resolution land cover from multispectral imagery

NASA Astrophysics Data System (ADS)

Stutts, S. Craig; Raskob, Benjamin L.; Wenger, Eric J.

2017-05-01

We present an automated method of generating high resolution ( 2 meter) land cover using a pattern recognition neural network trained on spatial and spectral features obtained from over 9000 WorldView multispectral images (MSI) in six distinct world regions. At this resolution, the network can classify small-scale objects such as individual buildings, roads, and irrigation ponds. This paper focuses on three key areas. First, we describe our land cover generation process, which involves the co-registration and aggregation of multiple spatially overlapping MSI, post-aggregation processing, and the registration of land cover to OpenStreetMap (OSM) road vectors using feature correspondence. Second, we discuss the generation of land cover derivative products and their impact in the areas of region reduction and object detection. Finally, we discuss the process of globally scaling land cover generation using cloud computing via Amazon Web Services (AWS).

THE RELATIONSHIP BETWEEN STREAM CHEMISTRY AND WATERSHED LAND COVER DATA IN THE MID-ATLANTIC REGION, U.S.

EPA Science Inventory

In order to investigate the relationship between stream chemistry and watershed land cover at the regional scale, we analyzed data from 368 wadeable streams sampled in the mid-Atlantic region of the U.S. during spring 1993-1994. Study sites were selected using a probability sampl...

Estimating Landscape Pattern Metrics from a Sample of Land Cover

EPA Science Inventory

Although landscape pattern metrics can be computed directly from wall-to-wall land-cover maps, statistical sampling offers a practical alternative when complete coverage land-cover information is unavailable. Partitioning a region into spatial units (“blocks”) to create a samplin...

Monitoring urban land cover change by updating the national land cover database impervious surface products

USGS Publications Warehouse

Xian, George Z.; Homer, Collin G.

2009-01-01

The U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001 is widely used as a baseline for national land cover and impervious conditions. To ensure timely and relevant data, it is important to update this base to a more recent time period. A prototype method was developed to update the land cover and impervious surface by 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 from both 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, impervious surface was estimated for areas of change by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain a variety of metropolitan areas. Results from the five study areas show that the vast majority of impervious surface changes associated with urban developments were accurately captured and updated. The approach optimizes mapping efficiency and can provide users a flexible method to generate updated impervious surface at national and regional scales.

Land Cover Change in the Boston Mountains, 1973-2000

USGS Publications Warehouse

Karstensen, Krista A.

2009-01-01

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-cover change. The objectives of the study are to: (1) to develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data to measure regional land-cover change across the United States; (2) to characterize the types, rates, and temporal variability of change for a 30-year period; (3) to document regional driving forces and consequences of change; and (4) to prepare a national synthesis of land-cover change (Loveland and others, 1999). The 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) provide the geographic framework for the geospatial data collected between 1973 and 2000. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000, and the data are evaluated using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) 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 for the five time periods previously mentioned. Additionally, historic aerial photographs from similar time frames 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. 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

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.

Evaluating the effects of historical land cover change on summertime weather and climate in New Jersey: Land cover and surface energy budget changes

USGS Publications Warehouse

Wichansky, P.S.; Steyaert, L.T.; Walko, R.L.; Waever, C.P.

2008-01-01

The 19th-century agrarian landscape of New Jersey (NJ) and the surrounding region has been extensively transformed to the present-day land cover by urbanization, reforestation, and localized areas of deforestation. This study used a mesoscale atmospheric numerical model to investigate the sensitivity of the warm season climate of NJ to these land cover changes. Reconstructed 1880s-era and present-day land cover data sets were used as surface boundary conditions for a set of simulations performed with the Regional Atmospheric Modeling System (RAMS). Three-member ensembles with historical and present-day land cover were compared to examine the sensitivity of surface air and dew point temperatures, rainfall, and the individual components of the surface energy budget to these land cover changes. Mean temperatures for the present-day landscape were 0.3-0.6??C warmer than for the historical landscape over a considerable portion of NJ and the surrounding region, with daily maximum temperatures at least 1.0??C warmer over some of the highly urbanized locations. Reforested regions, however, were slightly cooler. Dew point temperatures decreased by 0.3-0.6??C, suggesting drier, less humid near-surface air for the present-day landscape. Surface warming was generally associated with repartitioning of net radiation from latent to sensible heat flux, and conversely for cooling. While urbanization was accompanied by strong surface albedo decreases and increases in net shortwave radiation, reforestation and potential changes in forest composition have generally increased albedos and also enhanced landscape heterogeneity. The increased deciduousness of forests may have further reduced net downward longwave radiation. Copyright 2008 by the American Geophysical Union.

Land use, population dynamics, and land-cover change in Eastern Puerto Rico

Treesearch

W.A. Gould; S. Martinuzzi; I.K. Páres-Ramos

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...

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

The Land Cover Dynamics and Conversion of Agricultural Land in Northwestern Bangladesh, 1973-2003.

NASA Astrophysics Data System (ADS)

Pervez, M.; Seelan, S. K.; Rundquist, B. C.

2006-05-01

The importance of land cover information describing the nature and extent of land resources and changes over time is increasing; this is especially true in Bangladesh, where land cover is changing rapidly. This paper presents research into the land cover dynamics of northwestern Bangladesh for the period 1973-2003 using Landsat satellite images in combination with field survey data collected in January and February 2005. Land cover maps were produced for eight different years during the study period with an average 73 percent overall classification accuracy. The classification results and post-classification change analysis showed that agriculture is the dominant land cover (occupying 74.5 percent of the study area) and is being reduced at a rate of about 3,000 ha per year. In addition, 6.7 percent of the agricultural land is vulnerable to temporary water logging annually. Despite this loss of agricultural land, irrigated agriculture increased substantially until 2000, but has since declined because of diminishing water availability and uncontrolled extraction of groundwater driven by population pressures and the extended need for food. A good agreement (r = 0.73) was found between increases in irrigated land and the depletion of the shallow groundwater table, a factor affecting widely practiced small-scale irrigation in northwestern Bangladesh. Results quantified the land cover change patterns and the stresses placed on natural resources; additionally, they demonstrated an accurate and economical means to map and analyze changes in land cover over time at a regional scale, which can assist decision makers in land and natural resources management decisions.

Land cover classification for Puget Sound, 1974-1979

NASA Technical Reports Server (NTRS)

Eby, J. R.

1981-01-01

Digital analysis of LANDSAT data for land cover classification projects in the Puget Sound region is surveyed. Two early rural and urban land use classifications and their application are described. After acquisition of VICAR/IBIs software, another land use classification of the area was performed, and is described in more detail. Future applications are considered.

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.

Estimating Accuracy of Land-Cover Composition From Two-Stage Clustering Sampling

EPA Science Inventory

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), ...

Pre- and Post-Columbian Land Cover Changes and Associated Climate Impacts

NASA Astrophysics Data System (ADS)

Cook, B. I.; Puma, M. J.; Kaplan, J. O.; Anchukaitis, K. J.

2011-12-01

Central America experienced extensive expansion of agricultural land during development of the major Central American societies, followed by widespread abandonment and regrowth of natural vegetation after the European conquest. Here we use a high resolution climate model, in combination with a new land cover reconstruction, to investigate the impact of pre- (1490 C.E.) and post- (1650 C.E.) Columbian land cover change on climate in this region. Pre-Columbian land cover causes significant precipitation reductions over coastal Mexico, the Yucatan, and southern Mexico during the wet season, as replacement of forests with agricultural land reduces evapotranspiration fluxes to the atmosphere. Conversely, precipitation over the Yucatan increases during the dry season, as increased surface warming moves additional moisture into this region from the surrounding oceans. With the post-Columbian period, during which major population declines led to large scale agricultural abandonment, the forest recovery results in a partial, though not complete, return to wetter conditions. Our study finds support for previous work speculating that land cover change associated with the Mayan civilizations may have amplified major droughts in the region, and points to the possibility of a direct biogeophysical response to the forest recovery following the arrival of Europeans.

Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China.

PubMed

Gong, Jian; Yang, Jianxin; Tang, Wenwu

2015-11-09

Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution-severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems.

Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China

PubMed Central

Gong, Jian; Yang, Jianxin; Tang, Wenwu

2015-01-01

Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution—severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems. PMID:26569270

Global land-cover and land-use change of the last 6000 years for climate modelling studies: the PAGES LandCover6k initiative and its first achievements

NASA Astrophysics Data System (ADS)

Gaillard, Marie-Jose; Morrison, Kathleen; Madella, Marco; Whitehouse, Nicki J.; Pages Landcover6k Sub-Coordinators

2016-04-01

as such (i and ii above), and/or the revised HYDE and KK ALCCs. The LandCover6k working group focuses on regions of the world where humans have had a significant impact on land cover during the last 6000 (6k) calendar years (in some regions earlier than 6k ago) through deforestation and diverse agricultural practices, i.e. the Americas, Western and Eastern Africa, Europe, and Asia. In Asia, the emphasis has been placed so far on China, India and Japan. References: Kaplan JO et al. (2009) Quaternary Science Reviews 28(27-28): 3016-3034. doi: 10.1016/j.quascirev. 2009.09.028; Klein Goldewijk K et al. (2011) Global Ecology and Biogeography 20: 73-86. doi: 10.1111/j.1466-8238.2010.00587.x; Pirzamanbein B et al. (2014) Ecol Complex 20:127-141; Trondman A-K et al. (2015) Glob Chang Biol 21:676-697. doi:10.1111/gcb.12737.

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).

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.

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. 

Challenges in Global Land Use/Land Cover Change Modeling

NASA Astrophysics Data System (ADS)

Clarke, K. C.

2011-12-01

For the purposes of projecting and anticipating human-induced land use change at the global scale, much work remains in the systematic mapping and modeling of world-wide land uses and their related dynamics. In particular, research has focused on tropical deforestation, loss of prime agricultural land, loss of wild land and open space, and the spread of urbanization. Fifteen years of experience in modeling land use and land cover change at the regional and city level with the cellular automata model SLEUTH, including cross city and regional comparisons, has led to an ability to comment on the challenges and constraints that apply to global level land use change modeling. Some issues are common to other modeling domains, such as scaling, earth geometry, and model coupling. Others relate to geographical scaling of human activity, while some are issues of data fusion and international interoperability. Grid computing now offers the prospect of global land use change simulation. This presentation summarizes what barriers face global scale land use modeling, but also highlights the benefits of such modeling activity on global change research. An approach to converting land use maps and forecasts into environmental impact measurements is proposed. Using such an approach means that multitemporal mapping, often using remotely sensed sources, and forecasting can also yield results showing the overall and disaggregated status of the environment.

Land cover and land use changes in the oil and gas regions of Northwestern Siberia under changing climatic conditions

NASA Astrophysics Data System (ADS)

Yu, Qin; Epstein, Howard E.; Engstrom, Ryan; Shiklomanov, Nikolay; Strelestskiy, Dmitry

2015-12-01

Northwestern Siberia has been undergoing a range of land cover and land use changes associated with climate change, animal husbandry and development of mineral resources, particularly oil and gas. The changes caused by climate and oil/gas development Southeast of the city of Nadym were investigated using multi-temporal and multi-spatial remotely sensed images. Comparison between high spatial resolution imagery acquired in 1968 and 2006 indicates that 8.9% of the study area experienced an increase in vegetation cover (e.g. establishment of new saplings, extent of vegetated cover) in response to climate warming while 10.8% of the area showed a decrease in vegetation cover due to oil and gas development and logging activities. Waterlogging along linear structures and vehicle tracks was found near the oil and gas development site, while in natural landscapes the drying of thermokarst lakes is evident due to warming caused permafrost degradation. A Landsat time series dataset was used to document the spatial and temporal dynamics of these ecosystems in response to climate change and disturbances. The impacts of land use on surface vegetation, radiative, and hydrological properties were evaluated using Landsat image-derived biophysical indices. The spatial and temporal analyses suggest that the direct impacts associated with infrastructure development were mostly within 100 m distance from the disturbance source. While these impacts are rather localized they persist for decades despite partial recovery of vegetation after the initial disturbance and can have significant implications for changes in permafrost dynamics and surface energy budgets at landscape and regional scales.

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.

Estimation of late twentieth century land-cover change in California

USGS Publications Warehouse

Sleeter, Benjamin M.; Wilson, Tamara S.; Soulard, Christopher E.; Liu, Jinxun

2011-01-01

We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973–2000. Results indicate anthropogenic and natural disturbances, such as forest cutting and fire, were the dominant changes, followed by large fluctuations between agriculture and rangelands. Contrary to common perception, agriculture remained relatively stable over the 27-year period with an estimated loss of 1.0% of agricultural land. The largest net declines occurred in the grasslands/shrubs class at 5,131 km2 and forest class at 4,722 km2. Developed lands increased by 37.6%, composing an estimated 4.2% of the state’s land cover by 2000.

Land cover

USGS Publications Warehouse

Jorgenson, Janet C.; Joria, Peter C.; Douglas, David C.; Douglas, David C.; Reynolds, Patricia E.; Rhode, E.B.

2002-01-01

Documenting the distribution of land-cover types on the Arctic National Wildlife Refuge coastal plain is the foundation for impact assessment and mitigation of potential oil exploration and development. Vegetation maps facilitate wildlife studies by allowing biologists to quantify the availability of important wildlife habitats, investigate the relationships between animal locations and the distribution or juxtaposition of habitat types, and assess or extrapolate habitat characteristics across regional areas.To meet the needs of refuge managers and biologists, satellite imagery was chosen as the most cost-effective method for mapping the large, remote landscape of the 1002 Area.Objectives of our study were the following: 1) evaluate a vegetation classification scheme for use in mapping. 2) determine optimal methods for producing a satellite-based vegetation map that adequately met the needs of the wildlife research and management objectives; 3) produce a digital vegetation map for the Arctic Refuge coastal plain using Lands at-Thematic Mapper(TM) satellite imagery, existing geobotanical classifications, ground data, and aerial photographs, and 4) perform an accuracy assessment of the map.

Applications of VIC for Climate Land Cover Change Imapacts

NASA Technical Reports Server (NTRS)

Markert, Kel

2017-01-01

Study focuses on the Lower Mekong Basin (LMB), the LMB is an economically and ecologically important region: (1) One of the largest exporters of rice and fish products, (2) Within top three most biodiverse river basins in the world. Natural climate variability plays an important role in water supply within the region: (1) Short-term climate variability (ENSO, MJO), (2) Long-term climate variability (climate change). Projections of climate change show there will be a decrease in water availability world wide which has implications for food security and ecology. Additional studies show there may be socioeconomic turmoil due to water wars and food security in developing regions such as the Mekong Basin. Southeast Asia has experienced major changes in land use and land cover from 1980 – 2000. Major economic reforms resulting in shift from subsistence farming to market-based agricultural production. Changes in land cover continue to occur which have an important role within the land surface aspect of hydrology.

Theorizing Land Cover and Land Use Changes: The Case of Tropical Deforestation

NASA Technical Reports Server (NTRS)

Walker, Robert

2004-01-01

This article addresses land-cover and land-use dynamics from the perspective of regional science and economic geography. It first provides an account of the so-called spatially explicit model, which has emerged in recent years as a key empirical approach to the issue. The article uses this discussion as a springboard to evaluate the potential utility of von Thuenen to the discourse on land-cover and land-use change. After identifying shortcomings of current theoretical approaches to land use in mainly urban models, the article filters a discussion of deforestation through the lens of bid-rent and assesses its effectiveness in helping us comprehend the destruction of tropical forest in the Amazon basin. The article considers the adjustments that would have to be made to existing theory to make it more useful to the empirical issues.

Strong dependence of CO 2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization

DOE PAGES

Goll, Daniel S.; Brovkin, Victor; Liski, Jari; ...

2015-08-12

The quantification of sources and sinks of carbon from land use and land cover changes (LULCC) is uncertain. We investigated how the parametrization of LULCC and of organic matter decomposition, as well as initial land cover, affects the historical and future carbon fluxes in an Earth System Model (ESM). Using the land component of the Max Planck Institute ESM, we found that the historical (1750–2010) LULCC flux varied up to 25% depending on the fraction of biomass which enters the atmosphere directly due to burning or is used in short-lived products. The uncertainty in the decadal LULCC fluxes of themore » recent past due to the parametrization of decomposition and direct emissions was 0.6 Pg C yr $-$1, which is 3 times larger than the uncertainty previously attributed to model and method in general. Preindustrial natural land cover had a larger effect on decadal LULCC fluxes than the aforementioned parameter sensitivity (1.0 Pg C yr $-$1). Regional differences between reconstructed and dynamically computed land covers, in particular, at low latitudes, led to differences in historical LULCC emissions of 84–114 Pg C, globally. This effect is larger than the effects of forest regrowth, shifting cultivation, or climate feedbacks and comparable to the effect of differences among studies in the terminology of LULCC. Finally, in general, we find that the practice of calibrating the net land carbon balance to provide realistic boundary conditions for the climate component of an ESM hampers the applicability of the land component outside its primary field of application.« less

Strong dependence of CO 2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization

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

Goll, Daniel S.; Brovkin, Victor; Liski, Jari

The quantification of sources and sinks of carbon from land use and land cover changes (LULCC) is uncertain. We investigated how the parametrization of LULCC and of organic matter decomposition, as well as initial land cover, affects the historical and future carbon fluxes in an Earth System Model (ESM). Using the land component of the Max Planck Institute ESM, we found that the historical (1750–2010) LULCC flux varied up to 25% depending on the fraction of biomass which enters the atmosphere directly due to burning or is used in short-lived products. The uncertainty in the decadal LULCC fluxes of themore » recent past due to the parametrization of decomposition and direct emissions was 0.6 Pg C yr $-$1, which is 3 times larger than the uncertainty previously attributed to model and method in general. Preindustrial natural land cover had a larger effect on decadal LULCC fluxes than the aforementioned parameter sensitivity (1.0 Pg C yr $-$1). Regional differences between reconstructed and dynamically computed land covers, in particular, at low latitudes, led to differences in historical LULCC emissions of 84–114 Pg C, globally. This effect is larger than the effects of forest regrowth, shifting cultivation, or climate feedbacks and comparable to the effect of differences among studies in the terminology of LULCC. Finally, in general, we find that the practice of calibrating the net land carbon balance to provide realistic boundary conditions for the climate component of an ESM hampers the applicability of the land component outside its primary field of application.« less

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.

Operationalizing land cover/land use data products to support decision making in the forestry sector of Hindu Kush Himalaya region

NASA Astrophysics Data System (ADS)

Qamer, F. M.; Gilani, H.; Uddin, K.; Pradhan, S.; Murthy, M.; Bajracharya, B.

2014-12-01

The Himalayan mountain ecosystem is under severe stress due to population pressure and overexploitation, which is now being further compounded by climate change. Particularly the Himalayan mountain forests has been degrading since the 1850s, in the early years of British administration. Consistent country-wide and local level data are needed to show the patterns and processes of degradation as a basis for developing management strategies to halt degradation and ensure long-term sustainability. Realizing the need for developing consistent national and regional databases in the Hindu Kush-Himalayan region, with adequate spatial and temporal resolutions to be used by resource managers for informed decision making, time series land cover maps were developed for 1990, 2000, and 2010 based on the Landsat images. Considering forest sector as a primary user, a special attention was given to forest cover interpretation and relevant professional from national forestry institutions of Bangladesh, Bhutan, Myanmar, Nepal and Pakistan were closely engaged in developing standardized data products. With the use of consistent datasets and interpretation methods, this study provides first systematic assessment on forest cover distribution and change patterns during last two decades in these countries. At the same time, the results compiled at sub-district administrative unit, may facilitate institutions in developing appropriate forest conservation strategies, ecosystem vulnerability assessment and ecosystem services valuation at local level. To promote such usages, national forestry institutions are being closely engaged in a number of capacity building activities at national and regional level. In context of Reducing emissions from deforestation and forest degradation (REDD) initiatives, these datasets are also being evaluated to be considered as baseline for deforestation and degradation rates in the respective countries. To promote easy and open access, a web system was

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.

Sensitivity of selected landscape pattern metrics to land-cover misclassification and differences in land-cover composition

Treesearch

James D. Wickham; Robert V. O' Neill; Kurt H. Riitters; Timothy G. Wade; K. Bruce Jones

1997-01-01

Calculation of landscape metrics from land-cover data is becoming increasingly common. Some studies have shown that these measurements are sensitive to differences in land-cover composition, but none are known to have tested also their a sensitivity to land-cover misclassification. An error simulation model was written to test the sensitivity of selected land-scape...

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

Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP)

USGS Publications Warehouse

Lowry, J.; Ramsey, R.D.; Thomas, K.; Schrupp, D.; Sajwaj, T.; Kirby, J.; Waller, E.; Schrader, S.; Falzarano, S.; Langs, L.; Manis, G.; Wallace, C.; Schulz, K.; Comer, P.; Pohs, K.; Rieth, W.; Velasquez, C.; Wolk, B.; Kepner, W.; Boykin, K.; O'Brien, L.; Bradford, D.; Thompson, B.; Prior-Magee, J.

2007-01-01

Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwestern states of Arizona, Colorado, Nevada, New Mexico, and Utah. The land-cover map/dataset was generated using regionally consistent geospatial data (Landsat ETM+ imagery (1999-2001) and DEM derivatives), similar field data collection protocols, a standardized land-cover legend, and a common modeling approach (decision tree classifier). Partitioning of mapping responsibilities amongst the five collaborating states was organized around ecoregion-based "mapping zones". Over the course of 21/2 field seasons approximately 93,000 reference samples were collected directly, or obtained from other contemporary projects, for the land-cover modeling effort. The final map was made public in 2004 and contains 125 land-cover classes. An internal validation of 85 of the classes, representing 91% of the land area was performed. Agreement between withheld samples and the validated dataset was 61% (KHAT = .60, n = 17,030). This paper presents an overview of the methodologies used to create the regional land-cover dataset and highlights issues associated with large-area mapping within a coordinated, multi-institutional management framework. ?? 2006 Elsevier Inc. All rights reserved.

Land cover changes and their biogeophysical effects on climate

Treesearch

Rezaul Mahmood; Roger A. Pielke; Kenneth G. Hubbard; Dev Niyogi; Paul A. Dirmeyer; Clive McAlpine; Andrew M. Carleton; Robert Hale; Samuel Gameda; Adriana Beltrán-Przekurat; Bruce Baker; Richard McNider; David R. Legates; Marshall Shepherd; Jinyang Du; Peter D. Blanken; Oliver W. Frauenfeld; U.S. Nair; Souleymane Fall

2013-01-01

Land cover changes (LCCs) play an important role in the climate system. Research over recent decades highlights the impacts of these changes on atmospheric temperature, humidity, cloud cover, circulation, and precipitation. These impacts range from the local- and regional-scale to sub-continental and global-scale. It has been found that the impacts of regional-scale...

A design for a sustained assessment of climate forcings and feedbacks on land use land cover change

USGS Publications Warehouse

Loveland, Thomas; Mahmood, Rezaul

2014-01-01

Land use and land cover change (LULCC) significantly influences the climate system. Hence, to prepare the nation for future climate change and variability, a sustained assessment of LULCC and its climatic impacts needs to be undertaken. To address this objective, not only do we need to determine contemporary trends in land use and land cover that affect, or are affected by, weather and climate but also identify sectors and regions that are most affected by weather and climate variability. Moreover, it is critical that we recognize land cover and regions that are most vulnerable to climate change and how end-use practices are adapting to climate change. This paper identifies a series of steps that need to be undertaken to address these key items. In addition, national-scale institutional capabilities are identified and discussed. Included in the discussions are challenges and opportunities for collaboration among these institutions for a sustained assessment.

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.

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.

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.

The effect of land cover change to the biomass value in the forest region of West Java province

NASA Astrophysics Data System (ADS)

Rahayu, M. I.; Waryono, T.; Rokhmatullah; Shidiq, I. P. A.

2018-05-01

Due to the issue of climate change as a public concern, information of carbon stock availability play an important role to describe the condition of forest ecosystems in the context of sustainable forest management. This study has the objective to identify land cover change during 2 decades (1996 – 2016) in the forest region and estimate the value of forest carbon stocks in west Java Province using remote sensing imagery. The land cover change information was obtained by visually interpreting the Landsat image, while the estimation of the carbon stock value was performed using the transformation of the NDVI (Normalized Difference Vegetation Index) which extracted from Landsat image. Biomass value is calculated by existing allometric equations. The results of this study shows that the forest area in the forest region of West Java Province have decreased from year to year, and the estimation value of forest carbon stock in the forest region of West Java Province also decreased from year to year.

Development of the USGS national land-cover database over two decades

USGS Publications Warehouse

Xian, George Z.; Homer, Collin G.; Yang, Limin; Weng, Qihao

2011-01-01

Land-cover composition and change have profound impacts on terrestrial ecosystems. Land-cover and land-use (LCLU) conditions and their changes can affect social and physical environments by altering ecosystem conditions and services. Information about LCLU change is often used to produce landscape-based metrics and evaluate landscape conditions to monitor LCLU status and trends over a specific time interval (Loveland et al. 2002; Coppin et al. 2004; Lunetta et al. 2006). Continuous, accurate, and up-to-date land-cover data are important for natural resource and ecosystem management and are needed to support consistent monitoring of landscape attributes over time. Large-area land-cover information at regional, national, and global scales is critical for monitoring landscape variations over large areas.

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

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.

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.

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.

Estimating accuracy of land-cover composition from two-stage cluster sampling

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

2009-01-01

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

Land cover change or land-use intensification: simulating land system change with a global-scale land change model.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2013-12-01

Land-use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land-use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land systems that are characterized by their land cover mosaic, the agricultural management intensity, and livestock. Land system changes are simulated by the model, driven by regional demand for goods and influenced by local factors that either constrain or promote land system conversion. A characteristic of the new model is the endogenous simulation of intensification of agricultural management versus expansion of arable land, and urban versus rural settlements expansion based on land availability in the neighborhood of the location. Model results for the OECD Environmental Outlook scenario show that allocation of increased agricultural production by either management intensification or area expansion varies both among and within world regions, providing useful insight into the land sparing versus land sharing debate. The land system approach allows the inclusion of different types of demand for goods and services from the land system as a driving factor of land system change. Simulation results are compared to observed changes over the 1970-2000 period and projections of other global and regional land change models. © 2013 John Wiley & Sons Ltd.

GOFC-GOLD :: Global Observation of Forest and Land Cover Dynamics

Science.gov Websites

GTOS HOME OVERVIEW CALENDAR ORGANIZATION LAND TEAM FIRE TEAM NETWORKS WORKING GROUPS PARTNERS DATA availability of observations of forests and land cover at regional and global scales and to produce useful

Influence of Land Cover Heterogeneity, Land-Use Change and Management on the Regional Carbon Cycle in the Upper Midwest USA as Evaluated by High-Density Observations and a Dynamic Ecosystem Model

NASA Astrophysics Data System (ADS)

Desai, A. R.; Bolstad, P. V.; Moorcroft, P. R.; Davis, K. J.

2005-12-01

The interplay between land use change, forest management and land cover variability complicates the ability to characterize regional scale (10-1000 km) exchange of carbon dioxide between the land surface and atmosphere in heterogeneous landscapes. An attempt was made to observe and model these factors and their influence on the regional carbon cycle across the upper Midwest USA. A high density of eddy-covariance carbon flux, micrometeorology, carbon dioxide mixing ratio, stand-scale biometry and canopy component flux observations have been occurring in this area as part of the Chequamegon Ecosystem-Atmosphere Study. Observations limited to sampling only dominant stands and coarse-resolution biogeochemical models limited to biome-scale parameterization neither accurately capture the variability of carbon fluxes measured by the network of eddy covariance towers nor match the regional-scale carbon flux inferred from very tall tower eddy covariance measurements and multi-site upscaling. Analysis of plot level biometric data, U.S. Forest Service Forest Inventory Analysis data and high-resolution land cover data around the tall tower revealed significant variations in vegetation type, stand age, canopy stocking and structure. Wetlands, clearcuts and recent natural disturbances occur in characteristic small non-uniformly distributed patches that aggregate to form more than 30% of the landscape. The Ecosystem Demography model, a dynamic ecosystem model that incorporates vegetation heterogeneity, canopy structure, stand age, disturbance, land use change and forest management, was parameterized with regional biometric data and meteorology, historical records of land management and high-resolution satellite land cover maps. The model will be used to examine the significance of past land use change, natural disturbance history and current forest management in explaining landscape structure and regional carbon fluxes observed in the region today.

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

A stochastic Forest Fire Model for future land cover scenarios assessment

NASA Astrophysics Data System (ADS)

Fiorucci, P.; Holmes, T.; Gaetani, F.; D'Andrea, M.

2009-04-01

Land cover change and forest fire interaction under climate and socio-economics changes, is one of the main issues of the 21th century. The capability of defining future scenarios of land cover and fire regime allow forest managers to better understand the best actions to be carried out and their long term effects. In this paper a new methodology for land cover change simulations under climate change and fire disturbance is presented and discussed. The methodology is based on the assumption that forest fires exhibits power law frequency-area distribution. The well known Forest Fire Model (FFM), which is an example of self organized criticality, is able to reproduce this behavior. Starting from this observation, a modified version of the FFM has been developed. The new model, called Modified Forest Fire Model (MFFM) introduces several new features. A stochastic model for vegetation growth and regrowth after fire occurrence has been implemented for different kind of vegetations. In addition, a stochastic fire propagation model taking into account topography and vegetation cover has been introduced. The MFFM has been developed with the purpose of estimating vegetation cover changes and fire regimes over a time windows of many years for a given spatial region. Two different case studies have been carried out. The first case study is related with Liguria (Italy), a region of 5400 km2 lying between the Cote d'Azur, France, and Tuscany, Italy, on the northwest coast of the Tyrrhenian Sea. This region is characterized by Mediterranean fire regime. The second case study has been carried out in California (Florida) on a region having similar area and characterized by similar climate conditions. In both cases the model well represents the actual fire regime in terms of power law parameters proving interesting results about future land cover scenarios under climate, land use and socio-economics change.

The influence of land cover change in the Asian monsoon region on present-day and mid-Holocene climate

NASA Astrophysics Data System (ADS)

Dallmeyer, A.; Claussen, M.

2011-02-01

Using the general circulation model ECHAM5/JSBACH, we investigate the biogeophysical effect of large-scale afforestation and deforestation in the Asian monsoon domain on present-day and mid-Holocene climate. We demonstrate that the applied land cover change does not only modify the local climate but also change the climate in North Africa and the Middle East via teleconnections. Deforestation in the Asian monsoon domain enhances the rainfall in North Africa. In parts of the Sahara summer precipitation is more than doubled. In contrast, afforestation strongly decreases summer rainfall in the Middle East and even leads to the cessation of the rainfall-activity in some parts of this region. Regarding the local climate, deforestation results in a reduction of precipitation and a cooler climate as grass mostly has a higher albedo than forests. However, in the core region of the Asian monsoon the decrease of evaporative cooling in the monsoon season overcompensates this signal and results in a net warming. Afforestation has mainly the opposite effect, although the pattern of change is less clear. It leads to more precipitation in most parts of the Asian monsoon domain and a warmer climate except for the southern regions where a stronger evaporation decreases near-surface temperatures in the monsoon season. When prescribing mid-Holocene insolation, the pattern of local precipitation change differs. Afforestation particularly increases monsoon rainfall in the region along the Yellow River which was the settlement area of major prehistoric cultures. In this region, the effect of land cover change on precipitation is half as large as the orbitally-induced precipitation change. Thus, our model results reveal that mid- to late-Holocene land cover change could strongly have contributed to the decreasing Asian monsoon precipitation during the Holocene known from reconstructions.

The influence of land cover change in the Asian monsoon region on present-day and mid-Holocene climate

NASA Astrophysics Data System (ADS)

Dallmeyer, A.; Claussen, M.

2011-06-01

Using the general circulation model ECHAM5/JSBACH, we investigate the biogeophysical effect of large-scale afforestation and deforestation in the Asian monsoon domain on present-day and mid-Holocene climate. We demonstrate that the applied land cover change does not only modify the local climate but also change the climate in North Africa and the Middle East via teleconnections. Deforestation in the Asian monsoon domain enhances the rainfall in North Africa. In parts of the Sahara summer precipitation is more than doubled. In contrast, afforestation strongly decreases summer rainfall in the Middle East and even leads to the cessation of the rainfall-activity in some parts of this region. Regarding the local climate, deforestation results in a reduction of precipitation and a cooler climate as grass mostly has a higher albedo than forests. However, in the core region of the Asian monsoon the decrease in evaporative cooling in the monsoon season overcompensates this signal and results in a net warming. Afforestation has mainly the opposite effect, although the pattern of change is less clear. It leads to more precipitation in most parts of the Asian monsoon domain and a warmer climate except for the southern regions where a stronger evaporation decreases near-surface temperatures in the monsoon season. When prescribing mid-Holocene insolation, the pattern of local precipitation change differs. Afforestation particularly increases monsoon rainfall in the region along the Yellow River which was the settlement area of major prehistoric cultures. In this region, the effect of land cover change on precipitation is half as large as the orbitally-induced precipitation change. Thus, our model results reveal that mid- to late-Holocene land cover change could strongly have contributed to the decreasing Asian monsoon precipitation during the Holocene known from reconstructions.

Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region

USGS Publications Warehouse

Li, Zhengpeng; Liu, Shuguang; Zhang, Xuesong; West, Tristram O.; Ogle, Stephen M.; Zhou, Naijun

2016-01-01

Quantifying spatial and temporal patterns of carbon sources and sinks and their uncertainties across agriculture-dominated areas remains challenging for understanding regional carbon cycles. Characteristics of local land cover inputs could impact the regional carbon estimates but the effect has not been fully evaluated in the past. Within the North American Carbon Program Mid-Continent Intensive (MCI) Campaign, three models were developed to estimate carbon fluxes on croplands: an inventory-based model, the Environmental Policy Integrated Climate (EPIC) model, and the General Ensemble biogeochemical Modeling System (GEMS) model. They all provided estimates of three major carbon fluxes on cropland: net primary production (NPP), net ecosystem production (NEP), and soil organic carbon (SOC) change. Using data mining and spatial statistics, we studied the spatial distribution of the carbon fluxes uncertainties and the relationships between the uncertainties and the land cover characteristics. Results indicated that uncertainties for all three carbon fluxes were not randomly distributed, but instead formed multiple clusters within the MCI region. We investigated the impacts of three land cover characteristics on the fluxes uncertainties: cropland percentage, cropland richness and cropland diversity. The results indicated that cropland percentage significantly influenced the uncertainties of NPP and NEP, but not on the uncertainties of SOC change. Greater uncertainties of NPP and NEP were found in counties with small cropland percentage than the counties with large cropland percentage. Cropland species richness and diversity also showed negative correlations with the model uncertainties. Our study demonstrated that the land cover characteristics contributed to the uncertainties of regional carbon fluxes estimates. The approaches we used in this study can be applied to other ecosystem models to identify the areas with high uncertainties and where models can be improved to

How Scientists Differentiate Between Land Cover Types

NASA Technical Reports Server (NTRS)

2002-01-01

land cover and their attributes, researchers manipulate the colors recorded by the satellite to get the combination of wavelengths that best distinguishes the spectral signature of the land cover they wish to identify. After an area of forest or water or grass is identified, they can outline the category on an easy-to-analyze, color-coded map. To verify their results, the scientists will often travel to the regions of interest and compare the results of the map with test sites on the ground. next: The Basic Vegetation Map back: Mapping Earth's Diverse Landscapes

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.

The Impact of Land Use/Land Cover Changes on Land Degradation Dynamics: A Mediterranean Case Study

NASA Astrophysics Data System (ADS)

Bajocco, S.; De Angelis, A.; Perini, L.; Ferrara, A.; Salvati, L.

2012-05-01

In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas.

The impact of land use/land cover changes on land degradation dynamics: a Mediterranean case study.

PubMed

Bajocco, S; De Angelis, A; Perini, L; Ferrara, A; Salvati, L

2012-05-01

In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas.

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.

Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery

NASA Technical Reports Server (NTRS)

Estes, John E.; Gebelein, Jennifer

1999-01-01

This report is produced in accordance with the requirements outlined in the NASA Research Grant NAG9-1032 titled "Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery". This grant funds the Remote Sensing Research Unit of the University of California, Santa Barbara. This document summarizes the research progress and accomplishments to date and describes current on-going research activities. Even though this grant has technically expired, in a contractual sense, work continues on this project. Therefore, this summary will include all work done through and 5 May 1999. The principal goal of this effort is to test the accuracy of a sub-regional portion of an AVHRR-based land cover product. Land cover mapped to three different classification systems, in the southwestern United States, have been subjected to two specific accuracy assessments. One assessment utilizing astronaut acquired photography, and a second assessment employing Landsat Thematic Mapper imagery, augmented in some cases, high aerial photography. Validation of these three land cover products has proceeded using a stratified sampling methodology. We believe this research will provide an important initial test of the potential use of imagery acquired from Shuttle and ultimately the International Space Station (ISS) for the operational validation of the Moderate Resolution Imaging Spectrometer (MODIS) land cover products.

Metropolitan land cover inventory using multiseasonal Landsat data

USGS Publications Warehouse

Todd, William J.; Hill, R.N.; Henry, C.C.; Lake, B.L.

1978-01-01

As a part of the Pacific Northwest Land Resources Inventory Demonstration Project (PNLRIDP), planners from State, regional, and local agencies in Oregon are working with scientists from the EROS Data Center (USGS), Ames Research Center (NASA), and the Jet Propulsion Laboratory (California Institute of Technology) to obtain practical training and experience in the analysis of remotely sensed data collected from air and spacecraft. A 4,000 km2 area centered on metropolitan Portland was chosen as the demonstration site, and a four-date Landsat temporal overlay was created which contained January, April, July, and October data collected in 1973. Digital multispectral analysis of single dates and two-date combinations revealed that the spring-summer and summer-fall combinations were the most satisfactory for land cover inventory. Residential, commercial and industrial, improved open space, water, forested, and agriculture land cover categories were obtained consistently in the majority of classification iterations. Census tract and traffic zone boundaries were digitized and registered with the Landsat data to facilitate integration of the land cover information with socioeconomic and environmental data already available to Oregon planners.

Land cover maps, BVOC emissions, and SOA burden in a global aerosol-climate model

NASA Astrophysics Data System (ADS)

Stanelle, Tanja; Henrot, Alexandra; Bey, Isaelle

2015-04-01

It has been reported that different land cover representations influence the emission of biogenic volatile organic compounds (BVOC) (e.g. Guenther et al., 2006). But the land cover forcing used in model simulations is quite uncertain (e.g. Jung et al., 2006). As a consequence the simulated emission of BVOCs depends on the applied land cover map. To test the sensitivity of global and regional estimates of BVOC emissions on the applied land cover map we applied 3 different land cover maps into our global aerosol-climate model ECHAM6-HAM2.2. We found a high sensitivity for tropical regions. BVOCs are a very prominent precursor for the production of Secondary Organic Aerosols (SOA). Therefore the sensitivity of BVOC emissions on land cover maps impacts the SOA burden in the atmosphere. With our model system we are able to quantify that impact. References: Guenther et al. (2006), Estimates of global terrestrial isoprene emissions using MEGAN, Atmos. Chem. Phys., 6, 3181-3210, doi:10.5194/acp-6-3181-2006. Jung et al. (2006), Exploiting synergies of global land cover products for carbon cycle modeling, Rem. Sens. Environm., 101, 534-553, doi:10.1016/j.rse.2006.01.020.

Alternative method to validate the seasonal land cover regions of the conterminous United States

Treesearch

Zhiliang Zhu; Donald O. Ohlen; Raymond L. Czaplewski; Robert E. Burgan

1996-01-01

An accuracy assessment method involving double sampling and the multivariate composite estimator has been used to validate the prototype seasonal land cover characteristics database of the conterminous United States. The database consists of 159 land cover classes, classified using time series of 1990 1-km satellite data and augmented with ancillary data including...

Land use and land cover change in the Greater Yellowstone Ecosystem: 1975-1995

USGS Publications Warehouse

Parmenter, A.W.; Hansen, A.; Kennedy, R.E.; Cohen, W.; Langner, U.; Lawrence, R.; Maxwell, B.; Gallant, Alisa; Aspinall, R.

2003-01-01

Shifts in the demographic and economic character of the Greater Yellowstone Ecosystem (GYE) are driving patterns of land cover and land use change in the region. Such changes may have important consequences for ecosystem functioning. The objective of this paper is to quantify the trajectories and rates of change in land cover and use across the GYE for the period 1975-1995 using satellite imagery. Spectral and geographic variables were used as inputs to classification tree regression analysis (CART) to find "rules" which defined land use and land cover classes on the landscape. The resulting CART functions were used to map land cover and land use across seven Landsat TM scenes for 1995. We then used a thresholding technique to identify locations that differed in spectral properties between the 1995 and 1985 time periods. These "changed" locations were classified using CART functions derived from spectral and geographic data from 1985. This was similarly done for the year 1975 based on Landsat MSS data. Differences between the 1975, 1985, and 1995 maps were considered change in land cover and use. We calibrated and tested the accuracy of our models using data acquired through manual interpretation of aerial photos. Elevation and vegetative indices derived from the remotely sensed satellite imagery explained the most variance in the land use and land cover classes (-i.e., defined the "rules" most often). Overall accuracies from our study were good, ranging from 94% at the coarsest level of detail to 74% at the finest. The largest changes over the study period were the increases in burned, urban, and mixed conifer-herbaceous classes and decreases in woody deciduous, mixed woody deciduous-herbaceous, and conifer habitats. These changes have important implications for ecological function and biodiversity. The expansion of mixed conifer classes may increase fuel loads and enhance risk to the growing number of rural homes. The reduction of woody deciduous cover types is

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.

Assessment of land use/land cover dynamics of Tso Moriri Lake, a Ramsar site in India.

PubMed

Gupta, Sharad Kumar; Shukla, Dericks Praise

2016-12-01

Wetlands accounts for 6% area of the Earth's land cover and nearly 17% of the Hindu Kush Himalayan region. They are of utmost importance to climate dynamics and are critical links between terrestrial and aquatic ecosystems. Despite the need of high attention towards conserving and managing wetland resources, mapping them is a least practiced activity. This study shows the temporal change in land use and land cover pattern of Tso Moriri Lake, the highest altitude lake in India and designated as Ramsar site in year 2002, using multi-sensor and multi-date imagery. Due to change in hydro-meteorological conditions of the region, this lake area has been reduced. Since the lake recharge is dependent on snowmelt, hence change in climatic conditions (less snowfall in winters), to a certain extent, is also responsible for the decrease in water level and water spread of the lake. The result shows that the lake area has reduced approximately 2 km 2 in the last 15 years, and also, agriculture, grasslands, and vegetation cover have increased to a significant extent. Agricultural land and grasslands have doubled while the vegetation cover has increased more than six times, showing the coupled effect of climate change and anthropogenic activities. Trend of temperature and precipitation corroborates the effects of climate change in this region.

Land Cover Mapping for the Development of Green House Gas (GHG) Inventories in the Eastern and Southern Africa Region

NASA Astrophysics Data System (ADS)

Wakhayanga, J. A.; Oduor, P.; Korme, T.; Farah, H.; Limaye, A. S.; Irwin, D.; Artis, G.

2014-12-01

Anthropogenic activities are responsible for the largest share of green house gas (GHG) emissions. Research has shown that greenhouse gases cause radioactive forcing in the stratosphere, leading to ozone depletion. Different land cover types act as sources or sinks of carbon dioxide (CO2), the most dominant GHG.Under the oversight of the United Nations Framework Convention on Climate Change (UNFCCC) the Eastern and Southern Africa (ESA) region countries are developing Sustainable National GHG Inventory Management Systems. While the countries in the ESA region are making substantial progress in setting up GHG inventories, there remains significant constraints in the development of quality and sustainable National GHG Inventory Systems. For instance, there are fundamental challenges in capacity building and technology transfer, which can affect timely and consistent reporting on the land use, land-use change and forestry (LULUCF) component of the GHG inventory development. SERVIR Eastern and Southern Africa is a partnership project between the National Aeronautics and Space Administration (NASA) and the Regional Center for Mapping of Resources for Development (RCMRD), an intergovernmental organization in Africa, with 21 member states in the ESA region. With support from the United States Agency for International Development (USAID), SERVIR ESA is implementing the GHG Project in 9 countries. The main deliverables of the project are land cover maps for the years 2000 and 2010 (also 1990 for Malawi and Rwanda), and related technical reports, as well as technical training in land cover mapping using replicable methodologies. Landsat imagery which is freely available forms the main component of earth observation input data, in addition to ancillary data collected from each country. Supervised classification using maximum likelihood algorithm is applied to the Landsat images. The work is completed for the initial 6 countries (Malawi, Zambia, Rwanda, Tanzania, Botswana, and

The National Land Cover Database

USGS Publications Warehouse

Homer, Collin G.; Fry, Joyce A.; Barnes, Christopher A.

2012-01-01

The National Land Cover Database (NLCD) serves as the definitive Landsat-based, 30-meter resolution, land cover database for the Nation. NLCD provides spatial reference and descriptive data for characteristics of the land surface such as thematic class (for example, urban, agriculture, and forest), percent impervious surface, and percent tree canopy cover. NLCD supports a wide variety of Federal, State, local, and nongovernmental applications that seek to assess ecosystem status and health, understand the spatial patterns of biodiversity, predict effects of climate change, and develop land management policy. NLCD products are created by the Multi-Resolution Land Characteristics (MRLC) Consortium, a partnership of Federal agencies led by the U.S. Geological Survey. All NLCD data products are available for download at no charge to the public from the MRLC Web site: http://www.mrlc.gov.

Building a Continental Scale Land Cover Monitoring Framework for Australia

NASA Astrophysics Data System (ADS)

Thankappan, Medhavy; Lymburner, Leo; Tan, Peter; McIntyre, Alexis; Curnow, Steven; Lewis, Adam

2012-04-01

Land cover information is critical for national reporting and decision making in Australia. A review of information requirements for reporting on national environmental indicators identified the need for consistent land cover information to be compared against a baseline. A Dynamic Land Cover Dataset (DLCD) for Australia has been developed by Geoscience Australia and the Australian Bureau of Agriculture and Resource Economics and Sciences (ABARES) recently, to provide a comprehensive and consistent land cover information baseline to enable monitoring and reporting for sustainable farming practices, water resource management, soil erosion, and forests at national and regional scales. The DLCD was produced from the analysis of Enhanced Vegetation Index (EVI) data at 250-metre resolution derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the period from 2000 to 2008. The EVI time series data for each pixel was modelled as 12 coefficients based on the statistical, phenological and seasonal characteristics. The time series were then clustered in coefficients spaces and labelled using ancillary information on vegetation and land use at the catchment scale. The accuracy of the DLCD was assessed using field survey data over 25,000 locations provided by vegetation and land management agencies in State and Territory jurisdictions, and by ABARES. The DLCD is seen as the first in a series of steps to build a framework for national land cover monitoring in Australia. A robust methodology to provide annual updates to the DLCD is currently being developed at Geoscience Australia. There is also a growing demand from the user community for land cover information at better spatial resolution than currently available through the DLCD. Global land cover mapping initiatives that rely on Earth observation data offer many opportunities for national and international programs to work in concert and deliver better outcomes by streamlining efforts on development and

NASA Land Cover and Land Use Change (LCLUC): an interdisciplinary research program.

PubMed

Justice, Chris; Gutman, Garik; Vadrevu, Krishna Prasad

2015-01-15

Understanding Land Cover/Land Use Change (LCLUC) in diverse regions of the world and at varied spatial scales is one of the important challenges in global change research. In this article, we provide a brief overview of the NASA LCLUC program, its focus areas, and the importance of satellite remote sensing observations in LCLUC research including future directions. The LCLUC Program was designed to be a cross-cutting theme within NASA's Earth Science program. The program aims to develop and use remote sensing technologies to improve understanding of human interactions with the environment. Since 1997, the NASA LCLUC program has supported nearly 280 research projects on diverse topics such as forest loss and carbon, urban expansion, land abandonment, wetland loss, agricultural land use change and land use change in mountain systems. The NASA LCLUC program emphasizes studies where land-use changes are rapid or where there are significant regional or global LCLUC implications. Over a period of years, the LCLUC program has contributed to large regional science programs such as Land Biosphere-Atmosphere (LBA), the Northern Eurasia Earth Science Partnership Initiative (NEESPI), and the Monsoon Area Integrated Regional Study (MAIRS). The primary emphasis of the program will remain on using remote sensing datasets for LCLUC research. The program will continue to emphasize integration of physical and social sciences to address regional to global scale issues of LCLUC for the benefit of society. Copyright © 2014. Published by Elsevier Ltd.

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...

Understanding the Effect of Land Cover Classification on Model Estimates of Regional Carbon Cycling in the Boreal Forest Biome

NASA Technical Reports Server (NTRS)

Kimball, John; Kang, Sinkyu

2003-01-01

The original objectives of this proposed 3-year project were to: 1) quantify the respective contributions of land cover and disturbance (i.e., wild fire) to uncertainty associated with regional carbon source/sink estimates produced by a variety of boreal ecosystem models; 2) identify the model processes responsible for differences in simulated carbon source/sink patterns for the boreal forest; 3) validate model outputs using tower and field- based estimates of NEP and NPP; and 4) recommend/prioritize improvements to boreal ecosystem carbon models, which will better constrain regional source/sink estimates for atmospheric C02. These original objectives were subsequently distilled to fit within the constraints of a 1 -year study. This revised study involved a regional model intercomparison over the BOREAS study region involving Biome-BGC, and TEM (A.D. McGuire, UAF) ecosystem models. The major focus of these revised activities involved quantifying the sensitivity of regional model predictions associated with land cover classification uncertainties. We also evaluated the individual and combined effects of historical fire activity, historical atmospheric CO2 concentrations, and climate change on carbon and water flux simulations within the BOREAS study region.

Land-use and land-cover scenarios and spatial modeling at the regional scale

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.

2012-01-01

Land-use and land-cover (LULC) change has altered a large part of the earth's surface. Scenarios of potential future LULC change are required in order to better manage potential impacts on biodiversity, carbon fluxes, climate change, hydrology, and many other ecological processes. The U.S. Geological Survey is analyzing potential future LULC change in the United States, using an approach based on scenario construction and spatially explicit modeling. Similar modeling techniques are being used to produce historical LULC maps from 1940 to present. With the combination of backcast and forecast LULC data, the USGS is providing consistent LULC data for historical, current, and future time frames to support a variety of research applications.

Albedo and its Relationship to Land Cover and the Urban Heat Island in the Boston Metropolitan Region

NASA Astrophysics Data System (ADS)

Trlica, A.; Hutyra, L.; Wang, J.; Schaaf, C.; Erb, A.

2016-12-01

The urban built environment creates key changes in the biophysical character of the landscape, including the creation of Urban Heat Islands (UHIs) with increased near-surface temperatures in and around cities. Alteration in surface albedo is believed to partially drive UHIs through greater absorption of solar energy, but few empirical studies have specifically quantified albedo across a heterogeneous urban landscape, or investigated linkages between albedo, the UHI, and other surface socio-biophysical characteristics at a high enough spatial resolution to discern urban-scale features. This study used data derived from observations by Landsat and other remote sensing platforms to measure albedo across a varied urban landscape centered on Boston, Massachusetts, and examined the relationship between albedo, several key indicators of urban surface character (canopy cover, impervious fraction, and population density) and land surface temperature at resolutions of both 30 and 500 m. Albedo tended to be lower in areas with highest urbanization intensity indicators compared to rural undeveloped areas, and areas with lower albedo tended also to have higher median daytime summer surface temperatures. A k-means classification utilizing all the data available for each pixel revealed several distinct patterns of urban land cover corresponding mainly to the density of population and constructed surfaces and their impact on tree canopy cover. Mean 30-m summer surface temperatures ranged from 40.0 °C (SD = 2.6) in urban core areas to 26.2 °C (SD = 1.1) in nearby forest, but we only observed correspondingly large albedo decreases in the highest density urban core, with mean albedo of 0.116 (SD = 0.015) compared with 0.155 (SD = 0.015) in forest. Observations show that lower albedo in the Boston metropolitan region may be an important component of the local UHI in the most densely built-up urban core regions, while the UHI temperature effect in less densely settled peripheral

Land-use and land-cover change in montane mainland southeast Asia.

PubMed

Fox, Jefferson; Vogler, John B

2005-09-01

This paper summarizes land-cover and land-use change at eight sites in Thailand, Yunnan (China), Vietnam, Cambodia, and Laos over the last 50 years. Project methodology included incorporating information collected from a combination of semiformal, key informant, and formal household interviews with the development of spatial databases based on aerial photographs, satellite images, topographic maps, and GPS data. Results suggest that land use (e.g. swidden cultivation) and land cover (e.g. secondary vegetation) have remained stable and the minor amount of land-use change that has occurred has been a change from swidden to monocultural cash crops. Results suggest that two forces will increasingly determine land-use systems in this region. First, national land tenure policies-the nationalization of forest lands and efforts to increase control over upland resources by central governments-will provide a push factor making it increasingly difficult for farmers to maintain their traditional swidden land-use practices. Second, market pressures-the commercialization of subsistence resources and the substitution of commercial crops for subsistence crops-will provide a pull factor encouraging farmers to engage in new and different forms of commercial agriculture. These results appear to be robust as they come from eight studies conducted over the last decade. But important questions remain in terms of what research protocols are needed, if any, when linking social science data with remotely sensed data for understanding human-environment interactions.

A stochastic Forest Fire Model for future land cover scenarios assessment

NASA Astrophysics Data System (ADS)

D'Andrea, M.; Fiorucci, P.; Holmes, T. P.

2010-10-01

Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and climatic change. In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency. The method is based on the observation that many forest fire regimes, in different forest types and regions, exhibit power law frequency-area distributions. The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM) produces simulations which reproduce this observed pattern. However, the standard model is simplistic in that it considers land cover to be binary - each cell either contains a tree or it is empty - and the model overestimates the frequency of large fires relative to actual landscapes. Our new model, the Modified Forest Fire Model (MFFM), addresses this limitation by incorporating information on actual land use and differentiating among various types of flammable vegetation. The MFFM simulation model was tested on forest types with Mediterranean and sub-tropical fire regimes. The results showed that the MFFM was able to reproduce structural fire regime parameters for these two regions. Further, the model was used to forecast future land cover. Future research will extend this model to refine the forecasts of future land cover and fire regime scenarios under climate, land use and socio-economic change.

Development of an Independent Global Land Cover Validation Dataset

NASA Astrophysics Data System (ADS)

Sulla-Menashe, D. J.; Olofsson, P.; Woodcock, C. E.; Holden, C.; Metcalfe, M.; Friedl, M. A.; Stehman, S. V.; Herold, M.; Giri, C.

2012-12-01

Accurate information related to the global distribution and dynamics in global land cover is critical for a large number of global change science questions. A growing number of land cover products have been produced at regional to global scales, but the uncertainty in these products and the relative strengths and weaknesses among available products are poorly characterized. To address this limitation we are compiling a database of high spatial resolution imagery to support international land cover validation studies. Validation sites were selected based on a probability sample, and may therefore be used to estimate statistically defensible accuracy statistics and associated standard errors. Validation site locations were identified using a stratified random design based on 21 strata derived from an intersection of Koppen climate classes and a population density layer. In this way, the two major sources of global variation in land cover (climate and human activity) are explicitly included in the stratification scheme. At each site we are acquiring high spatial resolution (< 1-m) satellite imagery for 5-km x 5-km blocks. The response design uses an object-oriented hierarchical legend that is compatible with the UN FAO Land Cover Classification System. Using this response design, we are classifying each site using a semi-automated algorithm that blends image segmentation with a supervised RandomForest classification algorithm. In the long run, the validation site database is designed to support international efforts to validate land cover products. To illustrate, we use the site database to validate the MODIS Collection 4 Land Cover product, providing a prototype for validating the VIIRS Surface Type Intermediate Product scheduled to start operational production early in 2013. As part of our analysis we evaluate sources of error in coarse resolution products including semantic issues related to the class definitions, mixed pixels, and poor spectral separation between

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

Pattern-based, multi-scale segmentation and regionalization of EOSD land cover

NASA Astrophysics Data System (ADS)

Niesterowicz, Jacek; Stepinski, Tomasz F.

2017-10-01

The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.

Land-cover change in the conterminous United States from 1973 to 2000

USGS Publications Warehouse

Sleeter, Benjamin M.; Sohl, Terry L.; Loveland, Thomas R.; Auch, Roger F.; Acevedo, William; Drummond, Mark A.; Sayler, Kristi L.; Stehman, Stephen V.

2013-01-01

Land-cover change in the conterminous United States was quantified by interpreting change from satellite imagery for a sample stratified by 84 ecoregions. Gross and net changes between 11 land-cover classes were estimated for 5 dates of Landsat imagery (1973, 1980, 1986, 1992, and 2000). An estimated 673,000 km2(8.6%) of the United States’ land area experienced a change in land cover at least one time during the study period. Forest cover experienced the largest net decline of any class with 97,000 km2 lost between 1973 and 2000. The large decline in forest cover was prominent in the two regions with the highest percent of overall change, the Marine West Coast Forests (24.5% of the region experienced a change in at least one time period) and the Eastern Temperate Forests (11.4% of the region with at least one change). Agriculture declined by approximately 90,000 km2 with the largest annual net loss of 12,000 km2 yr−1 occurring between 1986 and 1992. Developed area increased by 33% and with the rate of conversion to developed accelerating rate over time. The time interval with the highest annual rate of change of 47,000 km2 yr−1 (0.6% per year) was 1986–1992. This national synthesis documents a spatially and temporally dynamic era of land change between 1973 and 2000. These results quantify land change based on a nationally consistent monitoring protocol and contribute fundamental estimates critical to developing understanding of the causes and consequences of land change in the conterminous United States.

The consequences of land-cover changes on soil erosion distribution in Slovakia

NASA Astrophysics Data System (ADS)

Cebecauer, Tomáš; Hofierka, Jaroslav

2008-06-01

Soil erosion is a complex process determined by mutual interaction of numerous factors. The aim of erosion research at regional scales is a general evaluation of the landscape susceptibility to soil erosion by water, taking into account the main factors influencing this process. One of the key factors influencing the susceptibility of a region to soil erosion is land cover. Natural as well as human-induced changes of landscape may result in both the diminishment and acceleration of soil erosion. Recent studies of land-cover changes indicate that during the last decade more than 4.11% of Slovak territory has changed. The objective of this study is to assess the influence of land-cover and crop rotation changes over the 1990-2000 period on the intensity and spatial pattern of soil erosion in Slovakia. The assessment is based on principles defined in the Universal Soil Loss Equation (USLE) modified for application at regional scale and the use of the CORINE land cover (CLC) databases for 1990 and 2000. The C factor for arable land has been refined using statistical data on the mean crop rotation and the acreage of particular agricultural crops in the districts of Slovakia. The L factor has been calculated using sample areas with parcels identified by LANDSAT TM data. The results indicate that the land-cover and crop rotation changes had a significant influence on soil erosion pattern predominately in the hilly and mountainous parts of Slovakia. The pattern of soil erosion changes exhibits high spatial variation with overall slightly decreased soil erosion risks. These changes are associated with ongoing land ownership changes, changing structure of crops, deforestation and afforestation.

Regional forest land cover characterisation using medium spatial resolution satellite data

USGS Publications Warehouse

Huang, Chengquan; Homer, Collin G.; Yang, Limin; Wulder, Michael A.; Franklin, Steven E.

2003-01-01

Increasing demands on forest resources require comprehensive, consistent and up-to-date information on those resources at spatial scales appropriate for management decision-making and for scientific analysis. While such information can be derived using coarse spatial resolution satellite data (e.g. Tucker et al. 1984; Zhu and Evans 1994; Cihlar et al. 1996; Cihlar et al., Chapter 12), many regional applications require more spatial and thematic details than can be derived by using coarse resolution imagery. High spatial resolution satellite data such as IKONOS and Quick Bird images (Aplin et al. 1997), though usable for deriving detailed forest information (Culvenor, Chapter 9), are currently not feasible for wall-to-wall regional applications because of extremely high data cost, huge data volume, and lack of contiguous coverage over large areas. Forest studies over large areas have often been accomplished using data acquired by intermediate spatial resolution sensor systems, including the Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and the Enhanced Thematic Mapper Plus (ETM+) of Landsat, the High Resolution Visible (HRV) of the Systeme Pour l'Observation de la Terre (SPOT), and the Linear Image Self-Scanner (LISS) of the Indian Remote Sensing satellite. These sensor systems are more appropriate for regional applications because they can routinely produce spatially contiguous data over large areas at relatively low cost, and can be used to derive a host of forest attributes (e.g. Cohen et al. 1995; Kimes et al. 1999; Cohen et al. 2001; Huang et al. 2001; Sugumaran 2001). Of the above intermediate spatial resolution satellites, Landsat is perhaps the most widely used in various types of land remote sensing applications, in part because it has provided more extensive spatial and temporal coverage of the globe than any other intermediate resolution satellite. Spatially contiguous Landsat data have been developed for many regions of the globe (e.g. Lunetta and

The impact of CO2 fertilization and historical land use/land cover change on regional climate extremes

NASA Astrophysics Data System (ADS)

Findell, Kirsten; Berg, Alexis; Gentine, Pierre; Krasting, John; Lintner, Benjamin; Malyshev, Sergey; Santanello, Joseph; Shevliakova, Elena

2017-04-01

Recent research highlights the role of land surface processes in heat waves, droughts, and other extreme events. Here we use an earth system model (ESM) from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the regional impacts of historical anthropogenic land use/land cover change (LULCC) and the vegetative response to changes in atmospheric CO2 on combined extremes of temperature and humidity. A bivariate assessment allows us to consider aridity and moist enthalpy extremes, quantities central to human experience of near-surface climate conditions. We show that according to this model, conversion of forests to cropland has contributed to much of the upper central US and central Europe experiencing extreme hot, dry summers every 2-3 years instead of every 10 years. In the tropics, historical patterns of wood harvesting, shifting cultivation and regrowth of secondary vegetation have enhanced near surface moist enthalpy, leading to extensive increases in the occurrence of humid conditions throughout the tropics year round. These critical land use processes and practices are not included in many current generation land models, yet these results identify them as critical factors in the energy and water cycles of the midlatitudes and tropics. Current work is targeted at understanding how CO2 fertilization of plant growth impacts water use efficiency and surface flux partitioning, and how these changes influence temperature and humidity extremes. We use this modeling work to explore how remote sensing can be used to determine how different forest ecosystems in different climatological regimes are responding to enhanced CO2 and a warming world.

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

Thematic accuracy of the 1992 National Land-Cover Data for the western United States

USGS Publications Warehouse

Wickham, J.D.; Stehman, S.V.; Smith, J.H.; Yang, L.

2004-01-01

The MultiResolution Land Characteristics (MRLC) consortium sponsored production of the National Land Cover Data (NLCD) for the conterminous United States, using Landsat imagery collected on a target year of 1992 (1992 NLCD). Here we report the thematic accuracy of the 1992 NLCD for the six western mapping regions. Reference data were collected in each region for a probability sample of pixels stratified by map land-cover class. Results are reported for each of the six mapping regions with agreement defined as a match between the primary or alternate reference land-cover label and a mode class of the mapped 3×3 block of pixels centered on the sample pixel. Overall accuracy at Anderson Level II was low and variable across the regions, ranging from 38% for the Midwest to 70% for the Southwest. Overall accuracy at Anderson Level I was higher and more consistent across the regions, ranging from 82% to 85% for five of the six regions, but only 74% for the South-central region.

Historical land cover changes in the Great Lakes Region

USGS Publications Warehouse

Cole, K.L.; Davis, M.B.; Stearns, F.; Guntenspergen, G.; Walker, K.; Sisk, Thomas D.

1999-01-01

Two different methods of reconstructing historical vegetation change, drawing on General Land Office (GLO) surveys and fossil pollen deposits, are demonstrated by using data from the Great Lakes region. Both types of data are incorporated into landscape-scale analyses and presented through geographic information systems. Results from the two methods reinforce each other and allow reconstructions of past landscapes at different time scales. Changes to forests of the Great Lakes region during the last 150 years were far greater than the changes recorded over the preceding 1,000 years. Over the last 150 years, the total amount of forested land in the Great Lakes region declined by over 40%, and much of the remaining forest was converted to early successional forest types as a result of extensive logging. These results demonstrate the utility of using GLO survey data in conjunction with other data sources to reconstruct a generalized 'presettlement' condition and assess changes in landcover.

Global land cover mapping and characterization: present situation and future research priorities

USGS Publications Warehouse

Giri, Chandra

2005-01-01

The availability and accessibility of global land cover data sets plays an important role in many global change studies. The importance of such science‐based information is also reflected in a number of international, regional, and national projects and programs. Recent developments in earth observing satellite technology, information technology, computer hardware and software, and infrastructure development have helped developed better quality land cover data sets. As a result, such data sets are increasingly becoming available, the user‐base is ever widening, application areas have been expanding, and the potential of many other applications are enormous. Yet, we are far from producing high quality global land cover data sets. This paper examines the progress in the development of digital global land cover data, their availability, and current applications. Problems and opportunities are also explained. The overview sets the stage for identifying future research priorities needed for operational land cover assessment and monitoring.

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.

Correlations between land covers and honey bee colony losses in a country with industrialized and rural regions.

PubMed

Clermont, Antoine; Eickermann, Michael; Kraus, François; Hoffmann, Lucien; Beyer, Marco

2015-11-01

High levels of honey bee colony losses were recently reported from Canada, China, Europe, Israel, Turkey and the United States, raising concerns of a global pollinator decline and questioning current land use practices, in particular intense agricultural cropping systems. Sixty-seven crops (data from the years 2010-2012) and 66 mid-term stable land cover classes (data from 2007) were analysed for statistical relationships with the honey bee colony losses experienced over the winters 2010/11-2012/13 in Luxembourg (Western Europe). The area covered by each land cover class, the shortest distance between each land cover class and the respective apiary, the number of plots covered by each land use class and the size of the biggest plot of each land cover class within radii of 2 km and 5 km around 166 apiaries (2010), 184 apiaries (2011) and 188 apiaries (2012) were tested for correlations with honey bee colony losses (% per apiary) experienced in the winter following the season when the crops were grown. Artificial water bodies, open urban areas, large industrial facilities including heavy industry, railways and associated installations, buildings and installations with socio-cultural purpose, camping-, sports-, playgrounds, golf courts, oilseed crops other than oilseed rape like sunflower or linseed, some spring cereals and former forest clearcuts or windthrows were the land cover classes most frequently associated with high honey bee colony losses. Grain maize, mixed forest and mixed coniferous forest were the land cover classes most frequently associated with low honey bee colony losses. The present data suggest that land covers related to transport, industry and leisure may have made a more substantial contribution to winter honey bee colony losses in developed countries than anticipated so far. Recommendations for the positioning of apiaries are discussed. Copyright © 2015. Published by Elsevier B.V.

Evaluation of historical land cover, land use, and land-use change emissions in the GCAM integrated assessment model

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Wise, M.; Kyle, P.; Janetos, A. C.; Zhou, Y.

2012-12-01

Integrated Assessment Models (IAMs) are often used as science-based decision-support tools for evaluating the consequences of climate and energy policies, and their use in this framework is likely to increase in the future. However, quantitative evaluation of these models has been somewhat limited for a variety of reasons, including data availability, data quality, and the inherent challenges in projections of societal values and decision-making. In this analysis, we identify and confront methodological challenges involved in evaluating the agriculture and land use component of the Global Change Assessment Model (GCAM). GCAM is a global integrated assessment model, linking submodules of the regionally disaggregated global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate. GCAM simulates supply, demand, and prices for energy and agricultural goods from 2005 to 2100 in 5-year increments. In each time period, the model computes the allocation of land across a variety of land cover types in 151 different regions, assuming that farmers maximize profits and that food demand is relatively inelastic. GCAM then calculates both emissions from land-use practices, and long-term changes in carbon stocks in different land uses, thus providing simulation information that can be compared to observed historical data. In this work, we compare GCAM results, both in recent historic and future time periods, to historical data sets. We focus on land use, land cover, land-use change emissions, and albedo.

High dimensional land cover inference using remotely sensed modis data

NASA Astrophysics Data System (ADS)

Glanz, Hunter S.

to validate our models and methods, and conduct an extensive continental scale case study using MODIS data. The results show that we successfully classify land cover and recover the spatial patterns present in large scale data. Application of our change point method to an area in the Amazon successfully identifies the progression of deforestation through portions of the region.

Spatially explicit land-use and land-cover scenarios for the Great Plains of the United States

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.; Sayler, Kristi L.; Bouchard, Michelle A.; Reker, Ryan R.; Bennett, Stacie L.; Sleeter, Rachel R.; Kanengieter, Ronald L.; Zhu, Zhi-Liang

2012-01-01

The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively fine spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by significant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey's Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire United States.

Soil cover patterns and SOC dynamics impacts on the soil processes, land management and ecosystem services in Central Region of Russia

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Chernikov, Vladimir; Yashin, Ivan; Geraskin, Mikhail; Morev, Dmitriy

2014-05-01

In the Central Region of Russia (CRR) the soil cover patterns usually play the very important role in the soil forming and degradation processes (SFP & SDP) potential and current rates, soil organic carbon (SOC) dynamics and pools, greenhouse gases (GHG) emissions and soluble SOC fluxes that we need take into attention for better assessment of the natural and especially man-changed ecosystems' services and for best land-use practices development. Central Region of Russia is the biggest one in RF according to its population and role in the economy. CRR is characterized by high spatial variability of soil cover due to as original landscape heterogeneity as complicated history of land-use practices during last 700 years. Our long-term researches include the wide zonal-provincial set of representative ecosystems and soil cover patterns with different types and history of land-use (forest, meadow-steppe and agricultural ones) from middle-taiga to steppe zones with different level of continentality. The carried out more than 30-years region- and local-scale researches of representative natural and rural landscapes in Tver', Yaroslavl', Kaluga, Moscow, Vladimir, Saransk (Mordovia), Kursk, Orel, Tambov, Voronezh and Saratov oblasts give us the interregional multi-factorial matrix of elementary soil cover patterns (ESCP) with different soil forming and degradation processes rates and soil organic carbon dynamics due to regionally specific soil-geomorphologic features, environmental and dominated microclimate conditions, land-use current practices and history. The validation and ranging of the limiting factors of SFP and SDP develop¬ment, soil carbon dynamics and sequestration potential, ecosystem (agroecosystem) principal services, land functional qualities and agroecological state have been done for dominating and most dynamical components of ESCP regional-typological forms - with application of SOC structure analysis, regional and local GIS, soil spatial patterns detail

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

National land cover monitoring using large, permanent photo plots

Treesearch

Raymond L. Czaplewski; Glenn P. Catts; Paul W. Snook

1987-01-01

A study in the State of North Carplina, U.S.A. demonstrated that large, permanent photo plots (400 hectares) can be used to monitor large regions of land by using remote sensing techniques. Estimates of area in a variety of land cover categories were made by photointerpretation of medium-scale aerial photography from a single month using 111 photo plots. Many of these...

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.

Polarization in the land distribution, land use and land cover change in the Amazon

PubMed Central

D'ANTONA, Alvaro; VANWEY, Leah; LUDEWIGS, Thomas

2013-01-01

The objective of this article is to present Polarization of Agrarian Structure as a single, more complete representation than models emphasizing rural exodus and consolidation of land into large agropastoral enterprises of the dynamics of changing land distribution, land use / cover, and thus the rural milieu of Amazonia. Data were collected in 2003 using social surveys on a sample of 587 lots randomly selected from among 5,086 lots on a cadastral map produced in the 1970s. Georeferencing of current property boundaries in the location of these previously demarcated lots allows us to relate sociodemographic and biophysical variables of the surveyed properties to the changes in boundaries that have occurred since the 1970s. As have other authors in other Amazonian regions, we found concentration of land ownership into larger properties. The approach we took, however, showed that changes in the distribution of land ownership is not limited to the appearance of larger properties, those with 200 ha or more; there also exists substantial division of earlier lots into properties with fewer than five hectares, many without any agropastoral use. These two trends are juxtaposed against the decline in establishments with between five and 200 ha. The variation across groups in land use / land cover and population distribution shows the necessity of developing conceptual models, whether from socioeconomic, demographic or environmental perspectives, look beyond a single group of people or properties. PMID:24639597

Continental land cover classification using meteorological satellite data

NASA Technical Reports Server (NTRS)

Tucker, C. J.; Townshend, J. R. G.; Goff, T. E.

1983-01-01

The use of the National Oceanic and Atmospheric Administration's advanced very high resolution radiometer satellite data for classifying land cover and monitoring of vegetation dynamics over an extremely large area is demonstrated for the continent of Africa. Data from 17 imaging periods of 21 consecutive days each were composited by a technique sensitive to the in situ green-leaf biomass to provide cloud-free imagery for the whole continent. Virtually cloud-free images were obtainable even for equatorial areas. Seasonal variation in the density and extent of green leaf vegetation corresponded to the patterns of rainfall associated with the inter-tropical convergence zone. Regional variations, such as the 1982 drought in east Africa, were also observed. Integration of the weekly satellite data with respect to time produced a remotely sensed assessment of biological activity based upon density and duration of green-leaf biomass. Two of the 21-day composited data sets were used to produce a general land cover classification. The resultant land cover distributions correspond well to those of existing maps.

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.

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.

Border Lakes land-cover classification

Treesearch

Marvin Bauer; Brian Loeffelholz; Doug Shinneman

2009-01-01

This document contains metadata and description of land-cover classification of approximately 5.1 million acres of land bordering Minnesota, U.S.A. and Ontario, Canada. The classification focused on the separation and identification of specific forest-cover types. Some separation of the nonforest classes also was performed. The classification was derived from multi-...

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.

Impact of land cover and land use change on runoff characteristics.

PubMed

Sajikumar, N; Remya, R S

2015-09-15

Change in Land Cover and Land Use (LCLU) influences the runoff characteristics of a drainage basin to a large extent, which in turn, affects the surface and groundwater availability of the area, and hence leads to further change in LCLU. This forms a vicious circle. Hence it becomes essential to assess the effect of change in LCLU on the runoff characteristics of a region in general and of small watershed levels (sub-basin levels) in particular. Such an analysis can effectively be carried out by using watershed simulation models with integrated GIS frame work. SWAT (Soil and Water Analysis Tool) model, being one of the versatile watershed simulation models, is found to be suitable for this purpose as many GIS integration modules are available for this model (e.g. ArcSWAT, MWSWAT). Watershed simulation using SWAT requires the land use and land cover data, soil data and many other features. With the availability of repository of satellite imageries, both from Indian and foreign sources, it becomes possible to use the concurrent local land use and land cover data, thereby enabling more accurate modelling of small watersheds. Such availability will also enable us to assess the effect of LCLU on runoff characteristics and their reverse impact. The current study assesses the effect of land use and land cover on the runoff characteristics of two watersheds in Kerala, India. It also assesses how the change in land use and land cover in the last few decades affected the runoff characteristics of these watersheds. It is seen that the reduction in the forest area amounts to 60% and 32% in the analysed watersheds. However, the changes in the surface runoff for these watersheds are not comparable with the changes in the forest area but are within 20%. Similarly the maximum (peak) value of runoff has increased by an amount of 15% only. The lesser (aforementioned) effect than expected might be due to the fact that forest has been converted to agricultural purpose with major

Monitoring the effects of land cover change on the supply of ecosystem services in an urban region: A study of Santiago-Valparaíso, Chile

PubMed Central

de la Barrera, Francisco; Salazar, Alejandro; Inostroza, Luis

2017-01-01

Mankind’s quest for well-being results in continuous pressure to transform landscapes, with said transformation driven by land use changes, urbanization, production activity, and protective measures in addition to climate variability and other environmental drivers. The relationship between anthropogenic landscape changes and the provision of ecosystem services (ES) is a topic of increasing interest in Latin America. In Chile, land cover changes due to increased urbanization and forestry, and expansion of agricultural land, in addition to conservation initiatives as a part of land planning, have been intensive in the last few decades. In this study, the effects of anthropogenic landscape changes on the supply of ES were analyzed for the urban region of Santiago-Valparaiso (Chile) using a method based on expert consultation and land cover change assessment. A pool of experts scored the potential of specific land covers to provide certain ES. The results enabled calculation and mapping of changes in the potential of the landscape to supply ES. The aforementioned changes over a period of 15 years were evaluated. The results indicate a tenuous balance between positive and negative changes to the supply of ES derived from land cover changes. Understanding and reporting how these processes occur in urban regions contributes to the conservation of valuable landscapes through spatial planning tools, especially in areas close to housing developments and sensitive ecosystems. PMID:29136016

Monitoring the effects of land cover change on the supply of ecosystem services in an urban region: A study of Santiago-Valparaíso, Chile.

PubMed

Montoya-Tangarife, Claudia; de la Barrera, Francisco; Salazar, Alejandro; Inostroza, Luis

2017-01-01

Mankind's quest for well-being results in continuous pressure to transform landscapes, with said transformation driven by land use changes, urbanization, production activity, and protective measures in addition to climate variability and other environmental drivers. The relationship between anthropogenic landscape changes and the provision of ecosystem services (ES) is a topic of increasing interest in Latin America. In Chile, land cover changes due to increased urbanization and forestry, and expansion of agricultural land, in addition to conservation initiatives as a part of land planning, have been intensive in the last few decades. In this study, the effects of anthropogenic landscape changes on the supply of ES were analyzed for the urban region of Santiago-Valparaiso (Chile) using a method based on expert consultation and land cover change assessment. A pool of experts scored the potential of specific land covers to provide certain ES. The results enabled calculation and mapping of changes in the potential of the landscape to supply ES. The aforementioned changes over a period of 15 years were evaluated. The results indicate a tenuous balance between positive and negative changes to the supply of ES derived from land cover changes. Understanding and reporting how these processes occur in urban regions contributes to the conservation of valuable landscapes through spatial planning tools, especially in areas close to housing developments and sensitive ecosystems.

The Trajectories and Impacts of Land Use and Land Cover Change: A Global Synthesis

NASA Astrophysics Data System (ADS)

Mustard, J. F.; Fisher, T. R.; Prince, S. D.; Soja, A. J.; Elmore, A. J.

2001-12-01

We have summarized the trajectories of land cover and land use change (LCLUC) and the resulting impacts through a synthesis of results from studies encompassing a wide range of environments. While the specific changes and impacts are in some ways unique to each environment, we have nevertheless identified some general principles that seem to apply across all regions. The LCLUC trajectory of a particular landscape under influence by human actions begins with the transition from conditions dominated by natural vegetation to a frontier state. Land use activities in a frontier state are centered primarily around resource extraction and development of infrastructure such as roads or ports. Under the proper conditions (e.g. soils, climate), the frontier state gives way to an agricultural landscape by further conversion of natural vegetation to agriculture and management of cleared land for agriculture. The maximum extent of this conversion is a function of local biophysical and socio-economic factors. For example conversion of arid lands may be limited by water availability, access to capital for development of water resources and access to markets for the products. Given the appropriate conditions (e.g. economic and social policy, generation of wealth), LCLUC evolves as large settlements and industrialization develop in concert with high land prices and agricultural intensification. In some cases (e.g., New England, Appalachia), economic conditions (e.g., better land for agriculture elsewhere) may result in reversion of agriculture to natural vegetation. The last stage in LCLUC is conversion of agriculture to residential and suburban environments (e.g., Baltimore/Washington corridor). Examination of global land cover indicates that every stage is currently present, with areas like the Eastern United States and Western Europe as examples of regions having experienced all stages, while parts of the Amazon basin, Siberia, and Africa are moving through the frontier

"Land-Cover Conversion in Amazonia, The Role of ENV" Ironment and Substrate composition in Modifying SOI

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Chadwick, Oliver A.; Batista, Getulio T.

2003-01-01

LBA research from the first phase of LBA focused on three broad categories: 1) mapping land cover and quantifying rates of change, persistence of pasture, and area of recovering forest; 2) evaluating the role of environmental factors and land-use history on soil biogeochemistry; and 3) quantifying the natural and human controls on stream nutrient concentrations. The focus of the research was regional, concentrating primarily in the state of RondBnia, but also included land-cover mapping in the vicinity of Maraba, Para, and Manaus, Amazonas. Remote sensing analysis utilized Landsat Thematic Mapper (TM) and Multispectral Scanner (MS S) data to map historical patterns of land-cover change. Specific questions addressed by the remote sensing component of the research included: 1) what is the areal extent of dominant land-cover classes? 2) what are the rates of change of dominant land cover through processes of deforestation, disturbance and regeneration? and 3) what are the dynamic properties of each class that characterize temporal variability, duration, and frequency of repeat disturbance? Biogeochemical analysis focused on natural variability and impacts of land-use/land-cover changes on soil and stream biogeochemical properties at the regional scale. An emphasis was given to specific soil properties considered to be primary limiting factors regionally, including phosphorus, nitrogen, base cations and cation-exchange properties. Stream sampling emphasized the relative effects of the rates and timing of land-cover change on stream nutrients, demonstrating that vegetation conversion alone does not impact nutrients as much as subsequent land use and urbanization.

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

Fine resolution probabilistic land cover classification of landscapes in the southeastern United States

Treesearch

Joseph St. Peter; John Hogland; Nathaniel Anderson; Jason Drake; Paul Medley

2018-01-01

Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a...

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...

Impacts of conflict on land use and land cover in the Imatong Mountain region of South Sudan and northern Uganda

NASA Astrophysics Data System (ADS)

Gorsevski, Virginia B.

The Imatong Mountain region of South Sudan makes up the northern most part of the Afromontane conservation 'biodiversity hotspot' due to the numerous species of plants and animals found here, some of which are endemic. At the same time, this area (including the nearby Dongotana Hills and the Agoro-Agu region of northern Uganda) has witnessed decades of armed conflict resulting from the Sudan Civil War and the presence of the Ugandan Lord's Resistance Army (LRA). The objective of my research was to investigate the impact of war on land use and land cover using a combination of satellite remote sensing data and semi-structured interviews with local informants. Specifically, I sought to (1) assess and compare changes in forest cover and location during both war and peace; (2) compare trends in fire activity with human population patterns; and (3) investigate the underlying causes influencing land use patterns related to war. I did this by using a Disturbance Index (DI), which isolates un-vegetated spectral signatures associated with deforestation, on Landsat TM and ETM+ data in order to compare changes in forest cover during conflict and post-conflict years, mapping the location and frequency of fires in subsets of the greater study area using MODIS active fire data, and by analyzing and summarizing information derived from interviews with key informants. I found that the rate of forest recovery was significantly higher than the rate of disturbance both during and after wartime in and around the Imatong Central Forest Reserve (ICFR) and that change in net forest cover remained largely unchanged for the two time periods. In contrast, the nearby Dongotana Hills experienced relatively high rates of disturbance during both periods; however, post war period losses were largely offset by gains in forest cover, potentially indicating opposing patterns in human population movements and land use activities within these two areas. For the Agoro-Agu Forest Reserve (AFR) region

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.

Land use/cover classification in the Brazilian Amazon using satellite images.

PubMed

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant'anna, Sidnei João Siqueira

2012-09-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Land use/cover classification in the Brazilian Amazon using satellite images

PubMed Central

Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant’Anna, Sidnei João Siqueira

2013-01-01

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data. PMID:24353353

Tsunami exposure estimation with land-cover data: Oregon and the Cascadia subduction zone

USGS Publications Warehouse

Wood, N.

2009-01-01

A Cascadia subduction-zone earthquake has the potential to generate tsunami waves which would impact more than 1000 km of coastline on the west coast of the United States and Canada. Although the predictable extent of tsunami inundation is similar for low-lying land throughout the region, human use of tsunami-prone land varies, creating variations in community exposure and potential impacts. To better understand such variations, land-cover information derived from midresolution remotely-sensed imagery (e.g., 30-m-resolution Landsat Thematic Mapper imagery) was coupled with tsunami-hazard information to describe tsunami-prone land along the Oregon coast. Land-cover data suggest that 95% of the tsunami-prone land in Oregon is undeveloped and is primarily wetlands and unconsolidated shores. Based on Spearman rank correlation coefficients (rs), correlative relationships are strong and statistically significant (p < 0.05) between city-level estimates of the amount of land-cover pixels classified as developed (impervious cover greater than 20%) and the amount of various societal assets, including residential and employee populations, homes, businesses, and tax-parcel values. Community exposure to tsunami hazards, described here by the amount and relative percentage of developed land in tsunami-prone areas, varies considerably among the 26 communities of the study area, and these variations relate to city size. Correlative relationships are strong and significant (p < 0.05) for community exposure rankings based on land-cover data and those based on aggregated socioeconomic data. In the absence of socioeconomic data or community-based knowledge, the integration of hazards information and land-cover information derived from midresolution remotely-sensed imagery to estimate community exposure may be a useful first step in understanding variations in community vulnerability to regional hazards.

A landscape indicator approach to the identification and articulation of the consequences of land-cover change in the Mid-Atlantic Region, 1973-2001

USGS Publications Warehouse

Slonecker, E. Terrence; Milheim, Lesley E.; Claggett, Peter

2009-01-01

Landscape indicators, derived from land-use and land-cover data, hydrology, nitrate deposition, and elevation data, were used by Jones and others (2001a) to calculate the ecological consequences of land-cover change. Nitrate loading and physical bird habitat were modeled from 1973 and 1992 land-cover and other spatial data for the Mid-Atlantic region. Utilizing the same methods, this study extends the analysis another decade with the use of the 2001 National Land Cover Dataset. Land-cover statistics and trends are calculated for three time periods: 1973-1992, 1992-2001 and 1973-2001. In addition, high-resolution aerial photographs (1 meter or better ground-sample distance) were acquired and analyzed for thirteen pairs of adjacent USGS 7.5 minute quadrangle maps in areas where distinct positive or negative changes to nitrogen loading and bird habitat were previously calculated. During the entire 30 year period, the data show that there was extensive loss of agriculture and forest area and a major increase in urban land-cover classes. However, the majority of the conversion of other classes to urban occurred during the 1992-2001 period. During the 1973-1992 period, there was only moderate increase in urban area, while there was an inverse relationship between agricultural change and forest change. In general, forest gain and agricultural loss was found in areas of improving landscape indicators, and forest loss and agricultural gain was found to occur in areas of declining indicators related to habitat and nitrogen loadings, which was generally confirmed by the aerial photographic analysis. In terms of the specific model results, bird habitat, which is mainly related to the extent of forest cover, declined overall with forest extent, but was also affected more in the decline of habitat quality. Nitrate loading, which is mainly related to agricultural land cover actually improved from 1992-2001, and in the overall study, mainly due to the conversion of agriculture to

Do we need to account for scenarios of land use/land cover changes in regional climate modeling and impact studies?

NASA Astrophysics Data System (ADS)

Strada, Susanna; de Noblet-Ducoudré, Nathalie; Perrin, Mathieu; Stefanon, Marc

2016-04-01

By modifying the Earth's natural landscapes, humans have introduced an imbalance in the Earth System's energy, water and emission fluxes via land-use and land-cover changes (LULCCs). Through land-atmosphere interactions, LULCCs influence weather, air quality and climate at different scales, from regional/local (a few ten kilometres) (Pielke et al., 2011) to global (a few hundred kilometres) (Mahmood et al., 2014). Therefore, in the context of climate change, LULCCs will play a role locally/regionally in altering weather/atmospheric conditions. In addition to the global climate change impacts, LULCCs will possibly induce further changes in the functioning of terrestrial ecosystems and thereby affect adaptation strategies. If LULCCs influence weather/atmospheric conditions, could land use planning alter climate conditions and ease the impact of climate change by wisely shaping urban and rural landscapes? Nowadays, numerical land-atmosphere modelling allows to assess LULCC impacts at different scales (e.g., Marshall et al., 2003; de Noblet-Ducoudré et al., 2011). However, most scenarios of climate changes used to force impact models result from downscaling procedures that do not account for LULCCs (e.g., Jacob et al., 2014). Therefore, if numerical modelling may help in tackling the discussion about LULCCs, do existing LULCC scenarios encompass realistic changes in terms of land use planning? In the present study, we apply a surface model to compare projected LULCC scenarios over France and to assess their impacts on surface fluxes (i.e., water, heat and carbon dioxide fluxes) and on water and carbon storage in soils. To depict future LULCCs in France, we use RCP scenarios from the IPCC AR5 report (Moss et al., 2011). LULCCs encompassed in RCPs are discussed in terms of: (a) their impacts on water and energy balance over France, and (b) their feasibility in the framework of land use planning in France. This study is the first step to quantify the sensitivity of land

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

Estimating The Effect of Biofuel on Land Cover Change Using Multi-Year Modis Land Cover Data

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

Singh, Nagendra; Bhaduri, Budhendra L

2010-01-01

There has been a growing debate on the effects of the increase in demands of biofuels on land use land cover (LULC) change with apprehension in some quarters that the growing demand for bioenergy as a clean fuel will result in widespread direct and indirect LULC change. However estimating both direct and indirect LULC change is challenging and will require development of accurate high frequency, high resolution (temporal and spatial) land use land cover data as well as new LULC models which can be used to locate, quantify and predict these changes. To assess whether the demand for biofuel hasmore » caused significant LULC we used MODIS land cover data (MCD12Q1) from 2001 to 2008 along with cropland data layer (CDL) to estimate cropland and grassland changes in United States for the years 2002-2008 as well as its correlation with biofuel growth.« less

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.

The land-cover cascade: relationships coupling land and water

Treesearch

C.L. Burcher; H.M. Valett; E.F. Benfield

2007-01-01

We introduce the land-cover cascade (LCC) as a conceptual framework to quantify the transfer of land-cover-disturbance effects to stream biota. We hypothesize that disturbance is propagated through multivariate systems through key variables that transform a disturbance and pass a reorganized disturbance effect to the next hierarchical level where the process repeats...

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.

Completion of the 2011 National Land Cover Database for the Conterminous United States – Representing a Decade of Land Cover Change Information

EPA Science Inventory

The National Land Cover Database (NLCD) provides nationwide data on land cover and land cover change at the native 30-m spatial resolution of the Landsat Thematic Mapper (TM). The database is designed to provide five-year cyclical updating of United States land cover and associat...

Response of net primary production to land use and land cover change in mainland China since the late 1980s.

PubMed

Li, Jun; Wang, Zhaoli; Lai, Chengguang; Wu, Xiaoqing; Zeng, Zhaoyang; Chen, Xiaohong; Lian, Yanqing

2018-05-19

Land use and land cover patterns in mainland China have substantially changed in the recent decades under the economic reform policies of the government. The terrestrial carbon cycle, particularly the net primary productivity (NPP), has been substantially changed on both local and national scales. With the growing concern over the effects of the terrestrial carbon cycle on global climate changes, the impacts of land use and cover change (LUCC) on NPP need to be understood. In this study, variations in NPP caused by LUCC (e.g., urbanization and conversion of other land use to forest and grassland) in mainland China from the late 1980s to 2015 were evaluated based on land cover datasets and NPPs simulated from the Carnegie-Ames-Stanford Approach model. The results indicate that the national total losses in NPP attributed to urbanization reached 1.695 TgC between the late 1980s and 2015. A large proportion (63.02%) of the total losses was due to the transformation from cropland to urban land. Urban expansion decreased the monthly and total NPPs over southern China, which includes the South China Region, Southwest China Region, and the middle and lower regions of the Yangtze River. However, the total NPP increased in the majority of urbanized areas in Northern China, including the Huang-Huai-Hai Region, Inner Mongolia Region (MGR), Gan-Xin Region (GXR), and Northeast China Region; monthly NPP in GXR and MGR increased throughout the year. By contrast, the conversion to grassland or forestland increased the monthly and total NPPs of Northern China, suggesting that returning to forestland and grassland could increase the carbon sequestration capacity of terrestrial ecosystems in mainland China. Among the sub-regions, the Loess Plateau Region contributed the largest increase in NPP, which was prompted by the conversion to grassland and forestland. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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.

High-resolution land cover classification using low resolution global data

NASA Astrophysics Data System (ADS)

Carlotto, Mark J.

2013-05-01

A fusion approach is described that combines texture features from high-resolution panchromatic imagery with land cover statistics derived from co-registered low-resolution global databases to obtain high-resolution land cover maps. The method does not require training data or any human intervention. We use an MxN Gabor filter bank consisting of M=16 oriented bandpass filters (0-180°) at N resolutions (3-24 meters/pixel). The size range of these spatial filters is consistent with the typical scale of manmade objects and patterns of cultural activity in imagery. Clustering reduces the complexity of the data by combining pixels that have similar texture into clusters (regions). Texture classification assigns a vector of class likelihoods to each cluster based on its textural properties. Classification is unsupervised and accomplished using a bank of texture anomaly detectors. Class likelihoods are modulated by land cover statistics derived from lower resolution global data over the scene. Preliminary results from a number of Quickbird scenes show our approach is able to classify general land cover features such as roads, built up area, forests, open areas, and bodies of water over a wide range of scenes.

Land use/ land cover and ecosystem functions change in the grassland restoration program areas in China from 2000 to 2010

NASA Astrophysics Data System (ADS)

Zhang, H.; Fan, J.

2015-12-01

The grassland restoration areas in China, most of which was located in arid and semi-arid areas, are affected by climate change and anthropogenic activities. Using the 3S (RS, GIS, GPS) technologies, quantitative analysis method of landscape patterns and ecological simulation, this study examines the spatiotemporal characteristics of land use/ land cover and ecosystem functions change in the grassland restoration areas in China from 2000 to 2010. We apply two parameters land use transfer matrix and land use dynamic degree to explore the speed and regional differentiation of land use change. We propose vegetation coverage, net primary production (NPP), soil and water conservation capacity to assess the ecosystem functions. This study analyzes the characteristics of landscape patterns at the class and landscape levels and explores the ecological effect of land use pattern and regional ecological processes. The results show that: (1) Grassland and others were the main landscape types in the study area in the past decade. The ecosystem structure was stable. About 0.37% of the total grassland area in 2000 experienced change in land use / land cover types. The area of woodlands, wetlands, farmlands, and built-up areas expanded. The area of others has declined. (2) The dynamic degree of regional land use was less than one percent in the recent ten years. The speed of land use and land cover change was low, and regional differentiation of change between the provinces was small. (3) The matrix of the landscape did not change in the study area. Landscape fragmentation index values decreased progressively; landscape diversity rose continuously; landscape aggregation and continuity decreased slightly; the landscape maintained relative integrity. (4) Ecosystem functions has increased as a whole. The vegetation coverages with significant increase (with a 1.99% yr-1 slope of regression) in the total study area; NPP has a fluctuating and increasing tendency, ranging from 218.23 g

Exploring dust emission responses to land cover change using an ecological land classification

NASA Astrophysics Data System (ADS)

Galloza, Magda S.; Webb, Nicholas P.; Bleiweiss, Max P.; Winters, Craig; Herrick, Jeffrey E.; Ayers, Eldon

2018-06-01

Despite efforts to quantify the impacts of land cover change on wind erosion, assessment uncertainty remains large. We address this uncertainty by evaluating the application of ecological site concepts and state-and-transition models (STMs) for detecting and quantitatively describing the impacts of land cover change on wind erosion. We apply a dust emission model over a rangeland study area in the northern Chihuahuan Desert, New Mexico, USA, and evaluate spatiotemporal patterns of modelled horizontal sediment mass flux and dust emission in the context of ecological sites and their vegetation states; representing a diversity of land cover types. Our results demonstrate how the impacts of land cover change on dust emission can be quantified, compared across land cover classes, and interpreted in the context of an ecological model that encapsulates land management intensity and change. Results also reveal the importance of established weaknesses in the dust model soil characterisation and drag partition scheme, which appeared generally insensitive to the impacts of land cover change. New models that address these weaknesses, coupled with ecological site concepts and field measurements across land cover types, could significantly reduce assessment uncertainties and provide opportunities for identifying land management options.

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.

EFFECTS OF LANDSCAPE CHARACTERISTICS ON LAND-COVER CLASS ACCURACY

EPA Science Inventory

Utilizing land-cover data gathered as part of the National Land-Cover Data (NLCD) set accuracy assessment, several logistic regression models were formulated to analyze the effects of patch size and land-cover heterogeneity on classification accuracy. Specific land-cover ...

Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

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

Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.

Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over centralmore » India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important

Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model

DOE PAGES

Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.; ...

2016-05-10

Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over centralmore » India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important

Linking remote sensing, land cover and disease.

PubMed

Curran, P J; Atkinson, P M; Foody, G M; Milton, E J

2000-01-01

Land cover is a critical variable in epidemiology and can be characterized remotely. A framework is used to describe both the links between land cover and radiation recorded in a remotely sensed image, and the links between land cover and the disease carried by vectors. The framework is then used to explore the issues involved when moving from remotely sensed imagery to land cover and then to vector density/disease risk. This exploration highlights the role of land cover; the need to develop a sound knowledge of each link in the predictive sequence; the problematic mismatch between the spatial units of the remotely sensed and epidemiological data and the challenges and opportunities posed by adding a temporal mismatch between the remotely sensed and epidemiological data. The paper concludes with a call for both greater understanding of the physical components of the proposed framework and the utilization of optimized statistical tools as prerequisites to progress in this field.

Thematic accuracy of the 1992 National Land-Cover Data for the eastern United States: Statistical methodology and regional results

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Smith, J.H.; Yang, L.

2003-01-01

The accuracy of the 1992 National Land-Cover Data (NLCD) map is assessed via a probability sampling design incorporating three levels of stratification and two stages of selection. Agreement between the map and reference land-cover labels is defined as a match between the primary or alternate reference label determined for a sample pixel and a mode class of the mapped 3×3 block of pixels centered on the sample pixel. Results are reported for each of the four regions comprising the eastern United States for both Anderson Level I and II classifications. Overall accuracies for Levels I and II are 80% and 46% for New England, 82% and 62% for New York/New Jersey (NY/NJ), 70% and 43% for the Mid-Atlantic, and 83% and 66% for the Southeast.

A land use and land cover classification system for use with remote sensor data

USGS Publications Warehouse

Anderson, James R.; Hardy, Ernest E.; Roach, John T.; Witmer, Richard E.

1976-01-01

The framework of a national land use and land cover classification system is presented for use with remote sensor data. The classification system has been developed to meet the needs of Federal and State agencies for an up-to-date overview of land use and land cover throughout the country on a basis that is uniform in categorization at the more generalized first and second levels and that will be receptive to data from satellite and aircraft remote sensors. The proposed system uses the features of existing widely used classification systems that are amenable to data derived from remote sensing sources. It is intentionally left open-ended so that Federal, regional, State, and local agencies can have flexibility in developing more detailed land use classifications at the third and fourth levels in order to meet their particular needs and at the same time remain compatible with each other and the national system. Revision of the land use classification system as presented in U.S. Geological Survey Circular 671 was undertaken in order to incorporate the results of extensive testing and review of the categorization and definitions.

Land Cover Change in the Vicinity of MT. Qomolangma (everest), Central High Himalayas Since 1976

NASA Astrophysics Data System (ADS)

Zhang, Y.; Nie, Y.; Liu, L.; Wang, Z.; Ding, M.; Zhang, J.

2010-12-01

Under the background of global environmental change, the Mt. Qomolangma (Everest) region becomes the ideal place for the research of earth-atmosphere system, water and energy change, ecosystem patterns and processes change due to its sensitive and fragile natural environment. Land change science has emerged as a fundamental component of global environmental change and sustainability research. In this paper, geography, spatial information, climate science and other related theories and methods were applied, with the help of remote sensing, GIS, GPS, combining with a large number of RS data, field survey data and meteorological observation data to build 3 periods (1976, 1988 and 2006) of land cover, 30 periods (1970-2009) of major lakes data and long time-series NDVI change data from 1982 to 2009 in the Mt. Qomolangma region. The main results are as follows: 1. The land cover types in Mt. Qomolangma region are rich and with distinctive alpine features. The main land cover types include: closed to open grassland, alpine sparse vegetation, bare rock, closed grassland, forbs and glaciers (each percentage larger than 7%) with the area of 8274.27 km2, 7515.15 km2, 5450.82 km2, 5215.85 km2, 2782.66 km2 and 2710.17 km2 respectively in 2006. 2. The distribution of the main cover types are of obvious vertical zonallity. The transition of land cover types is forest→shrubland→grassland→meadow→sparse grassland→bare rock →glacier in order as the altitude arises with basically Gaussian distribution and assending peak in each elevation zone of types. The dominant natural zones distributed from bottom to top are: forest dominated zone (1500 ~ 3900 m), shrubland dominated zone (3900 ~ 4100 m), grassland dominated zone (4100 ~ 5000 m), sparse vegetation dominated zone (5000 ~ 5600 m), bare land dominated zone (5600 ~ 5900 m) and glacier (>5900 m). The altitude distribution of forest, shrubland and grassland in north and south slope are generally consistent. The range of

Development of a 30 m Spatial Resolution Land Cover of Canada: Contribution to the Harmonized North America Land Cover Dataset

NASA Astrophysics Data System (ADS)

Pouliot, D.; Latifovic, R.; Olthof, I.

2017-12-01

Land cover is needed for a large range of environmental applications regarding climate impacts and adaption, emergency response, wildlife habitat, air quality, water yield, etc. In Canada a 2008 user survey revealed that the most practical scale for provision of land cover data is 30 m, nationwide, with an update frequency of five years (Ball, 2008). In response to this need the Canada Centre for Remote Sensing has generated a 30 m land cover of Canada for the base year 2010 as part of a planned series of maps at the recommended five year update frequency. This land cover is the Canadian contribution to the North American Land Change Monitoring System initiative, which seeks to provide harmonized land cover across Canada, the United States, and Mexico. The methodology developed in this research utilized a combination of unsupervised and machine learning techniques to map land cover, blend results between mapping units, locally optimize results, and process some thematic attributes with specific features sets. Accuracy assessment with available field data shows it was on average 75% for the five study areas assessed. In this presentation an overview of the unique processing aspects, example results, and initial accuracy assessment will be discussed.

Estimation of evapotranspiration for different land covers in a Brazilian semi-arid region: A case study of the Brígida River basin, Brazil

NASA Astrophysics Data System (ADS)

Santos, Celso Augusto Guimarães; Silva, Richarde Marques da; Silva, Alexandro Medeiros; Brasil Neto, Reginaldo Moura

2017-03-01

In this study, the Surface Energy Balance Algorithm for Land (SEBAL) was used to compute the surface albedo, vegetation indices (NDVI, SAVI and LAI), surface temperature, soil heat flux and evapotranspiration (ET) over two contrasting years (dry and wet) in the Brígida River basin, a semi-arid region of north-eastern Brazil. The actual ET was computed during satellite overpass and was integrated for 24 h on a pixel-by-pixel basis for the daily ET distribution. Due to the topographic effects, an attempt was also made to incorporate DEM information to estimate the net radiation. The land cover types identified in the watershed are cropland, bare land, dense canopy, grassland, and caatinga vegetation. In order to study the variation among the biophysical parameters and ET, two-way analysis of variance (ANOVA) was used. The ET calculated by SEBAL ranged between 2.46 and 6.87 mm/day for the dry year (1990) and 1.31 and 6.84 mm/day for the wet year (2009) for the river basin. The results showed that a reduction in vegetation cover is evident in the temporal and spatial analysis over the studied periods in the region and that these facts influence the values of the energy balance and ET. The results showed significant differences in the variables of land cover type and year at the probability level of 0.05 for all land cover types.

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.

Assessing the impact of future land use and land cover changes on climate over Brazilian semiarid

NASA Astrophysics Data System (ADS)

Cunha, A. M.; Alvalá, R. S.; Kubota, P. Y.; Vieira, R.

2013-12-01

The continental surface vegetal cover has been considerably changed by human activities, mainly through natural vegetation conversion in grasslands. Such changes in surface cover may impact the regional and global climates, through of the changes in biophysical processes and CO2 exchanges between vegetation and atmosphere. In recent decades, most of the Brazilian territory has been presenting transformation in the land use/cover spatial patterns. The typical vegetation of the Brazilian semiarid, known as caatinga (closed shrubland) had been replaced by pasture lands. Based on that, the main objective of this work was to investigate the impacts of future land cover and land use changes (LCLUC) on surface processes and on the climate of Brazilian semiarid region. Numerical experiments using the AGCM/CPTEC/IBIS were performed in order to investigate the impacts of LCLUC on the climate of Brazilian semiarid due to the replacement of natural vegetation by pasture and degraded areas. The climate impacts of LUCC were assessed using climate simulations considering two scenarios of vegetation distribution: i) Potential Vegetation (Control) and ii) Future scenario of the vegetation: maximum pasture limited by areas of desert and semidesert. These degraded areas were obtained from the future projection of the biome distribution in South America developed by Salazar Velasquez (2009) using CPTEC PVMReg and emission scenarios A2 of the Intergovernmental Panel on Climate Change (IPCC). In general, the simulation results showed that the LCLUC, due to the changes in relevant surface variables, has caused alterations in local and neighborhood regions climate. The LCLUC leads to a decrease in mean rainfall during dry season at study area. A meridional dipole pattern with near surface temperature increase (reduction) in the northern (southern) areas of semiarid was found. The results also highlight that LUCC led to changes in the components of the surface energy and carbon balance

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.

Impact of Land Use Land Cover Change on East Asian monsoon

NASA Astrophysics Data System (ADS)

Chilukoti, N.; Xue, Y.; Liu, Y.; Lee, J.

2017-12-01

Humans modify the Earth's terrestrial surface on a continental scale by removing natural vegetation for crops/grazing. The current rates, extents and intensities of Land Use and Land Cover Change (LULCC) are greater than ever in history. The earlier studies of Land-atmosphere interactions used specified land surface conditions without interannual variations. In this study using NCEP CFSv2 coupled with Simplified Simple Biosphere (SSiB) model, biogeophysical impacts of LULCC on climate variability, anomaly, and changes are investigated by using the LULCC map from the Hurtt et al. (2006, 2011), which covered 66 years from 1950-2015 with annual variability. We combined the changes in crop and pasture fractions and consider as LULCC. A methodology had been developed to convert the Hurtt LULCC change map with 1° resolution to the GCM grid points. Since the GCM has only one dominant type, when the crop and pasture frction value at one point was larger than the critical value, that grid was assigned as degraded. Comprehensive evaluation was conducted to ensure the consistence of the trend of land degradation in the Hurtt's map and in the GCM LULCC map. In the degraded point, trees were changed to low vegetation or grasses, and low vegetation to bare soil. A set of surface parameters such as leaf area index, vegetation height, roughness length, and soil parameters, associated with vegetation are changed to show the degradation effects. We integrated the model with the potential vegetation map and the map with LULCC from 1950 to 2015, and the results indicate the LULCC causes precipitation reduction globally, with the strongest signals over monsoon regions. For instance, the degradation in Mexico, West Africa, south and East Asia and South America produced significant precipitation anomalies, some of which are consistent with observed regional precipitation anomalies. Meanwhile, it has also found that the LULCC enhances the surface warming during the summer in monsoon

Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

NASA Astrophysics Data System (ADS)

Clark, M. L.; Kilham, N. E.

2015-12-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

Evaluating effects of land pattern with regional characteristic curves: Land cover indicators and estimating building energy use from thermal image data

NASA Astrophysics Data System (ADS)

Lewis, Geoffrey Mcdowell

Sustainability is a word that represents a wide spectrum of complex and interrelated topics, but it is fundamentally a concept that describes a balanced relationship with the physical environment. There is a need for timely feedback on that relationship in order for individuals and societies to make informed decisions. Investigating the relationship between the physical form of our cities and regions and the impacts that these regions have on their supporting ecological environment requires both a method for categorizing form and a method for quantifying impact. The latter was addressed through the development of the regional characteristic curve method. This method collects, summarizes, analyzes, and displays spatial data in a graphical form that is intuitive, informative, and has advantages over existing tabular methods. Regional characteristic curves are calculated using concentric rings as the basis for evaluating impact metrics from any kind of areal data. The method was investigated in an examination of spatial change over time in the Ann Arbor region and in a comparison between Ann Arbor and Detroit. Curves for several types of metrics were used, based on land-cover and demographic data. The lack of a suitable energy use data set was highlighted, as well as great impact that energy use causes. One aspect of energy use, energy use in buildings, was singled out for further investigation. The possible link between building energy use and thermal image data collected by satellite was explored. Satellite thermal image data has been shown to be primarily related to variation in land-cover, but remaining variability in satellite data may be related to energy use in buildings. This link was investigated in both summer and winter case studies, revealing no significant relationship in summer and a weak relationship in winter. The winter relationship was also in a counterintuitive direction, in that higher building energy use was associated with cooler thermal image

Monitoring land use/land cover changes using CORINE land cover data: a case study of Silivri coastal zone in Metropolitan Istanbul.

PubMed

Yilmaz, Rüya

2010-06-01

The objective of the present study was to assess changes in land use/land cover patterns in the coastal town of Silivri, a part of greater Istanbul administratively. In the assessment, remotely sensed data, in the form of satellite images, and geographic information systems were used. Types of land use/land cover were designated as the percentage of the total area studied. Results calculated from the satellite data for land cover classification were compared successfully with the database Coordination of Information on the Environment (CORINE). This served as a reference to appraise the reliability of the study presented here. The CORINE Program was established by the European Commission to create a harmonized Geographical Information System on the state of the environment in the European Community. Unplanned urbanization is causing land use changes mainly in developing countries such as Turkey. This situation in Turkey is frequently observed in the city of Istanbul. There are only a few studies of land use-land cover changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Istanbul. The research area comprised greater Silivri Town which is situated by the coast of Marmara Sea, and it is located approximately 60 km west of Istanbul. The city of Istanbul is one of the largest metropolises in Europe with ca. 15 million inhabitants. Additionally, greater Silivri is located near the terminal point of the state highway connecting Istanbul with Europe. Measuring of changes occurring in land use would help control future planning of settlements; hence, it is of importance for the Greater Silivri and Silivri Town. Following our evaluations, coastal zone of Silivri was classified into the land use groups of artificial surfaces agricultural areas and forests and seminatural areas with 47.1%, 12.66%, and 22.62%, respectively.

Recent land-use/land-cover change in the Central California Valley

USGS Publications Warehouse

Soulard, Christopher E.; Wilson, Tamara S.

2013-01-01

Open access to Landsat satellite data has enabled annual analyses of modern land-use and land-cover change (LULCC) for the Central California Valley ecoregion between 2005 and 2010. Our annual LULCC estimates capture landscape-level responses to water policy changes, climate, and economic instability. From 2005 to 2010, agriculture in the region fluctuated along with regulatory-driven changes in water allocation as well as persistent drought conditions. Grasslands and shrublands declined, while developed lands increased in former agricultural and grassland/shrublands. Development rates stagnated in 2007, coinciding with the onset of the historic foreclosure crisis in California and the global economic downturn. We utilized annual LULCC estimates to generate interval-based LULCC estimates (2000–2005 and 2005–2010) and extend existing 27 year interval-based land change monitoring through 2010. Resulting change data provides insights into the drivers of landscape change in the Central California Valley ecoregion and represents the first, continuous, 37 year mapping effort of its kind.

Time series change detection: Algorithms for land cover change

NASA Astrophysics Data System (ADS)

Boriah, Shyam

The climate and earth sciences have recently undergone a rapid transformation from a data-poor to a data-rich environment. In particular, climate and ecosystem related observations from remote sensors on satellites, as well as outputs of climate or earth system models from large-scale computational platforms, provide terabytes of temporal, spatial and spatio-temporal data. These massive and information-rich datasets offer huge potential for advancing the science of land cover change, climate change and anthropogenic impacts. One important area where remote sensing data can play a key role is in the study of land cover change. Specifically, the conversion of natural land cover into humandominated cover types continues to be a change of global proportions with many unknown environmental consequences. In addition, being able to assess the carbon risk of changes in forest cover is of critical importance for both economic and scientific reasons. In fact, changes in forests account for as much as 20% of the greenhouse gas emissions in the atmosphere, an amount second only to fossil fuel emissions. Thus, there is a need in the earth science domain to systematically study land cover change in order to understand its impact on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. Land cover conversions include tree harvests in forested regions, urbanization, and agricultural intensification in former woodland and natural grassland areas. These types of conversions also have significant public policy implications due to issues such as water supply management and atmospheric CO2 output. In spite of the importance of this problem and the considerable advances made over the last few years in high-resolution satellite data, data mining, and online mapping tools and services, end users still lack practical tools to help them manage and transform this data into actionable knowledge of changes in forest ecosystems that

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.

Monitoring land cover dynamics in the Aral Sea region by remote sensing

NASA Astrophysics Data System (ADS)

Kozhoridze, Giorgi; Orlovsky, Leah; Orlovsky, Nikolai

2012-10-01

The Aral Sea ecological crisis resulted from the USSR government decision in 1960s to deploy agricultural project for cotton production in Central Asia. Consequently water flow in the Aral Sea decreased drastically due to the regulation of Amydarya and Syrdarya Rivers for irrigation purposes from 55-60 km3 in 1950s to 43 km3 in 1970s, 4 km3 in 1980s and 9-10 km3 in 2000s. Expert land cover classification approach gives the opportunity to use the unlimited variable for classification purposes. The band algebra (band5/band4 and Band4/Band3) and remote sensing indices (Normalized differential Salinity Index (NDSI), Salt Pan Index (SPI), Salt Index (SI), Normalized difference Vegetation Index (NDVI), Albedo, Crust Index) utilized for the land cover classification has shown satisfactory result with classification overall accuracy 86.9 % and kappa coefficient 0.85. Developed research algorithm and obtained results can support monitoring system, contingency planning development, and improvement of natural resources rational management.

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.

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

High-Resolution Land Use and Land Cover Mapping

USGS Publications Warehouse

,

1999-01-01

As the Nation?s population grows, quantifying, monitoring, and managing land use becomes increasingly important. The U.S. Geological Survey (USGS) has a long heritage of leadership and innovation in land use and land cover (LULC) mapping that has been the model both nationally and internationally for over 20 years. At present, the USGS is producing high-resolution LULC data for several watershed and urban areas within the United States. This high-resolution LULC mapping is part of an ongoing USGS Land Cover Characterization Program (LCCP). The four components of the LCCP are global (1:2,000,000-scale), national (1:100,000-scale), urban (1:24,000-scale), and special projects (various scales and time periods). Within the urban and special project components, the USGS Rocky Mountain Mapping Center (RMMC) is collecting historical as well as contemporary high-resolution LULC data. RMMC?s high-resolution LULC mapping builds on the heritage and success of previous USGS LULC programs and provides LULC information to meet user requirements.

Towards Seamless Validation of Land Cover Data

NASA Astrophysics Data System (ADS)

Chuprikova, Ekaterina; Liebel, Lukas; Meng, Liqiu

2018-05-01

This article demonstrates the ability of the Bayesian Network analysis for the recognition of uncertainty patterns associated with the fusion of various land cover data sets including GlobeLand30, CORINE (CLC2006, Germany) and land cover data derived from Volunteered Geographic Information (VGI) such as Open Street Map (OSM). The results of recognition are expressed as probability and uncertainty maps which can be regarded as a by-product of the GlobeLand30 data. The uncertainty information may guide the quality improvement of GlobeLand30 by involving the ground truth data, information with superior quality, the know-how of experts and the crowd intelligence. Such an endeavor aims to pave a way towards a seamless validation of global land cover data on the one hand and a targeted knowledge discovery in areas with higher uncertainty values on the other hand.

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

Analysing land cover and land use change in the Matobo National Park and surroundings in Zimbabwe

NASA Astrophysics Data System (ADS)

Scharsich, Valeska; Mtata, Kupakwashe; Hauhs, Michael; Lange, Holger; Bogner, Christina

2016-04-01

Natural forests are threatened worldwide, therefore their protection in National Parks is essential. Here, we investigate how this protection status affects the land cover. To answer this question, we analyse the surface reflectance of three Landsat images of Matobo National Park and surrounding in Zimbabwe from 1989, 1998 and 2014 to detect changes in land cover in this region. To account for the rolling countryside and the resulting prominent shadows, a topographical correction of the surface reflectance was required. To infer land cover changes it is not only necessary to have some ground data for the current satellite images but also for the old ones. In particular for the older images no recent field study could help to reconstruct these data reliably. In our study we follow the idea that land cover classes of pixels in current images can be transferred to the equivalent pixels of older ones if no changes occurred meanwhile. Therefore we combine unsupervised clustering with supervised classification as follows. At first, we produce a land cover map for 2014. Secondly, we cluster the images with clara, which is similar to k-means, but suitable for large data sets. Whereby the best number of classes were determined to be 4. Thirdly, we locate unchanged pixels with change vector analysis in the images of 1989 and 1998. For these pixels we transfer the corresponding cluster label from 2014 to 1989 and 1998. Subsequently, the classified pixels serve as training data for supervised classification with random forest, which is carried out for each image separately. Finally, we derive land cover classes from the Landsat image in 2014, photographs and Google Earth and transfer them to the other two images. The resulting classes are shrub land; forest/shallow waters; bare soils/fields with some trees/shrubs; and bare light soils/rocks, fields and settlements. Subsequently the three different classifications are compared and land changes are mapped. The main changes are

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.

Impacts of land use/cover change on ecosystem services for Xiamen

NASA Astrophysics Data System (ADS)

Shi, L.; Cui, S.

2009-12-01

Based on remote sensing images of Xiamen in 1987, 1997 and 2007, the process of ecosystem service alteration resulting from land use/cover change was quantitatively analyzed through RS and GIS techniques. Consulting relative researches, an integrated assessment model was built to evaluating regional ecosystem services of Xiamen. The results showed that the total ecosystem service value of Xiamen was increased by 14.67%, from 3271.5 million to 3751.39 RMB. The relative change rate of supplying service, regulation service, cultural service and supporting service were 97.8%, -25.1%, 165.0% and -44.7% respectively, which indicated that land use/ cover change had positive effects on supplying and cultural service, whereas it had negatively affected both regulation service and supporting service. Land use/cover types of Xiamen in 1987, 1997 and 2007 Ecosystem values of Xiamen in 1987, 1997 and 2007 10 thousand RMB

SOUTHWEST REGIONAL GAP LAND COVER

EPA Science Inventory

The Gap Analysis Program is a national inter-agency program that maps the distribution

of plant communities and selected animal species and compares these distributions with land

stewardship to identify gaps in biodiversity protection. GAP uses remote satellite imag...

Developing a New North American Land Cover Product at 30m Resolution: Methods, Results and Future Plans

NASA Astrophysics Data System (ADS)

Homer, C.; Colditz, R. R.; Latifovic, R.; Llamas, R. M.; Pouliot, D.; Danielson, P.; Meneses, C.; Victoria, A.; Ressl, R.; Richardson, K.; Vulpescu, M.

2017-12-01

Land cover and land cover change information at regional and continental scales has become fundamental for studying and understanding the terrestrial environment. With recent advances in computer science and freely available image archives, continental land cover mapping has been advancing to higher spatial resolution products. The North American Land Change Monitoring System (NALCMS) remains the principal provider of seamless land cover maps of North America. Founded in 2006, this collaboration among the governments of Canada, Mexico and the United States has released two previous products based on 250m MODIS images, including a 2005 land cover and a 2005-2010 land cover change product. NALCMS has recently completed the next generation North America land cover product, based upon 30m Landsat images. This product now provides the first ever 30m land cover produced for the North American continent, providing 19 classes of seamless land cover. This presentation provides an overview of country-specific image classification processes, describes the continental map production process, provides results for the North American continent and discusses future plans. NALCMS is coordinated by the Commission for Environmental Cooperation (CEC) and all products can be obtained at their website - www.cec.org.

Retrieval of land cover information under thin fog in Landsat TM image

NASA Astrophysics Data System (ADS)

Wei, Yuchun

2008-04-01

Thin fog, which often appears in remote sensing image of subtropical climate region, has resulted in the low image quantity and bad image mapping. Therefore, it is necessary to develop the image processing method to retrieve land cover information under thin fog. In this paper, the Landsat TM image near the Taihu Lake that is in the subtropical climate zone of China was used as an example, and the workflow and method used to retrieve the land cover information under thin fog have been built based on ENVI software and a single TM image. The basic step covers three parts: 1) isolating the thin fog area in image according to the spectral difference of different bands; 2) retrieving the visible band information of different land cover types under thin fog from the near-infrared bands according to the relationships between near-infrared bands and visible bands of different land cover types in the area without fog; 3) image post-process. The result showed that the method in the paper is easy and suitable, and can be used to improve the quantity of TM image mapping more effectively.

Pairing FLUXNET sites to validate model representations of land-use/land-cover change

NASA Astrophysics Data System (ADS)

Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

2018-01-01

Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

Assessing the Impact of Land Use and Land Cover Change on Global Water Resources

NASA Astrophysics Data System (ADS)

Batra, N.; Yang, Y. E.; Choi, H. I.; Islam, A.; Charlotte, D. F.; Cai, X.; Kumar, P.

2007-12-01

Land use and land cover changes (LULCC) significantly modify the hydrological regime of the watersheds, affecting water resources and environment from regional to global scale. This study seeks to advance and integrate water and energy cycle observation, scientific understanding, and human impacts to assess future water availability. To achieve the research objective, we integrate and interpret past and current space based and in situ observations into a global hydrologic model (GHM). GHM is developed with enhanced spatial and temporal resolution, physical complexity, hydrologic theory and processes to quantify the impact of LULCC on physical variables: surface runoff, subsurface flow, groundwater, infiltration, ET, soil moisture, etc. Coupled with the common land model (CLM), a 3-dimensional volume averaged soil-moisture transport (VAST) model is expanded to incorporate the lateral flow and subgrid heterogeneity. The model consists of 11 soil-hydrology layers to predict lateral as well as vertical moisture flux transport based on Richard's equations. The primary surface boundary conditions (SBCs) include surface elevation and its derivatives, land cover category, sand and clay fraction profiles, bedrock depth and fractional vegetation cover. A consistent global GIS-based dataset is constructed for the SBCs of the model from existing observational datasets comprising of various resolutions, map projections and data formats. Global ECMWF data at 6-hour time steps for the period 1971 through 2000 is processed to get the forcing data which includes incoming longwave and shortwave radiation, precipitation, air temperature, pressure, wind components, boundary layer height and specific humidity. Land use land cover data, generated using IPCC scenarios for every 10 years from 2000 to 2100 is used for future assessment on water resources. Alterations due to LULCC on surface water balance components: ET, groundwater recharge and runoff are then addressed in the study. Land

Land use/land cover change geo-informative Tupu of Nujiang River in Northwest Yunnan Province

NASA Astrophysics Data System (ADS)

Wang, Jin-liang; Yang, Yue-yuan; Huang, You-ju; Fu, Lei; Rao, Qing

2008-10-01

Land Use/Land Cover Change (LUCC) is the core components of global change researches. It is significant for understanding regional ecological environment and LUCC mechanism of large scale to develop the study of LUCC of regional level. Nujiang River is the upper reaches of a big river in the South Asia--Salween River. Nujiang River is a typical mountainous river which is 3200 kilometer long and its basin area is 32.5 × 105 square kilometer. It locates in the core of "Three Parallel Rivers" World Natural Heritage. It is one of international biodiversity conservation center of the world, the ecological fragile zone and key ecological construction area, as well as a remote undeveloped area with high diversity ethnic. With the rapidly development of society and economy, the land use and land cover changed in a great degree. The function of ecosystem has being degraded in some areas which will not only impact on the ecological construction of local area, but also on the ecological safety of lower reaches -- Salween River. Therefore it is necessary to carry out the research of LUCC of Nujiang River. Based on the theory and methods of geo-information Tupu, the "Spatial Pattern" and "Change Process" of land use of middle reach in Nujiang River from 1974 to 2004 had been studied in quantification and integration, so as to provide a case study in local area and mesoscale in time. Supported by the remote sensing and GIS technology, LUCC Tupu of 1974-2004 had been built and the characteristics of LUCC have been analyzed quantificationally. The results showed that the built-up land (Included in this category are cities, towns, villages, strip developments along highways, transportation, power, and communications facilities, and areas such as those occupied by mills, shopping centers, industrial and commercial complexes, and institutions that may, in some instances, be isolated from urban areas), agriculture land, shrubbery land, meadow & grassland, difficultly/unused land

Completion of the 2011 National Land Cover Database for the conterminous United States – Representing a decade of land cover change information

USGS Publications Warehouse

Homer, Collin G.; Dewitz, Jon; Yang, Limin; Jin, Suming; Danielson, Patrick; Xian, George Z.; Coulston, John; Herold, Nathaniel; Wickham, James; Megown, Kevin

2015-01-01

The National Land Cover Database (NLCD) provides nationwide data on land cover and land cover change at the native 30-m spatial resolution of the Landsat Thematic Mapper (TM). The database is designed to provide five-year cyclical updating of United States land cover and associated changes. The recent release of NLCD 2011 products now represents a decade of consistently produced land cover and impervious surface for the Nation across three periods: 2001, 2006, and 2011 (Homer et al., 2007; Fry et al., 2011). Tree canopy cover has also been produced for 2011 (Coluston et al., 2012; Coluston et al., 2013). With the release of NLCD 2011, the database provides the ability to move beyond simple change detection to monitoring and trend assessments. NLCD 2011 represents the latest evolution of NLCD products, continuing its focus on consistency, production, efficiency, and product accuracy. NLCD products are designed for widespread application in biology, climate, education, land management, hydrology, environmental planning, risk and disease analysis, telecommunications and visualization, and are available for no cost at http://www.mrlc.gov. NLCD is produced by a Federal agency consortium called the Multi-Resolution Land Characteristics Consortium (MRLC) (Wickham et al., 2014). In the consortium arrangement, the U.S. Geological Survey (USGS) leads NLCD land cover and imperviousness production for the bulk of the Nation; the National Oceanic and Atmospheric Administration (NOAA) completes NLCD land cover for the conterminous U.S. (CONUS) coastal zones; and the U.S. Forest Service (USFS) designs and produces the NLCD tree canopy cover product. Other MRLC partners collaborate through resource or data contribution to ensure NLCD products meet their respective program needs (Wickham et al., 2014).

A spatial econometric analysis of land-use change with land cover trends data: an application to the Pacific Northwest

Treesearch

David J. Lewis; Ralph J. Alig

2014-01-01

This paper develops a plot-level spatial econometric land-use model and estimates it with U.S. Geological Survey Land Cover Trends (LCT) geographic information system panel data for the western halves of the states of Oregon and Washington. The discrete-choice framework we use models plot-scale choices of the three dominant land uses in this region: forest, agriculture...

Land use and land cover digital data

USGS Publications Warehouse

Fegeas, Robin G.; Claire, Robert W.; Guptill, Stephen C.; Anderson, K. Eric; Hallam, Cheryl A.

1983-01-01

The discipline of cartography is undergoing a number of profound changesthat center on the emerging influence ofdigital manipulation and analysis ofdata for the preparation of cartographic materials and for use in geographic information systems. Operational requirements have led to the development by the USGS National Mapping Division of several documents that establish in-house digital cartographic standards. In an effort to fulfill lead agency requirements for promulgation of Federal standards in the earth sciences, the documents have been edited and assembled with explanatory text into a USGS Circular. This Circular describes some of the pertinent issues relative to digital cartographic data standards, documents the digital cartographic data standards currently in use within the USGS, and details the efforts of the USGS related to the definition of national digital cartographic data standards. It consists of several chapters; the first is a general overview, and each succeeding chapter is made up from documents that establish in-house standards for one of the various types of digital cartographic data currently produced. This chapter 895-E, describes the Geographic Information Retrieval and Analysis System that is used in conjunction with the USGS land use and land cover classification system to encode, edit, manipuate, and analyze land use and land cover digital data.

Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

PubMed

Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

PubMed Central

Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241

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

Land Cover Changes between 1974 and 2008 in Ulaanbaatar, Mongolia

NASA Astrophysics Data System (ADS)

Bagan, H.; Kinoshita, T.; Yamagata, Y.

2009-12-01

In the past 35 years, a combination of human actions and natural causes has led to a significant decline in land quality in Ulaanbaatar, the capital city of Mongolia. Human causes include changes in conventional livestock husbandry, overgrazing, and exploitation for traditional uses. Natural causes include a harsh, dry climate, short growing seasons, and thin soils. Since 1995, many herders left the countryside to come to the city in search of new opportunities, the Ger areas (wooden houses and Ger) have expended, resulting in urban sprawl. Since urbanization usually advance in an uncontrolled or unorganized way in Mongolia, they have destructive effects on the environment, particularly on basic ecosystems, wildlife habitat, and pollution of natural resources (e.g. air and water). Land use and land cover changes occurred in the region are investigated using satellite images acquired in 1974 (Landsat MSS), 1990 (Landsat TM), 2000 (ASTER), 2006 (IKONOS), and 2008 (ALOS). Pre-processing of all data included orthorectification and registration to precisely geolocated imagery. In the detection of changes, classification approaches were employed using a self-organizing map (SOM) neural network classifier (Fig. 1a) and new developed subspace classification method (Fig. 1b). From the time-series classified remote sensing images, we extract the land cover and land cover temporal changes from 1974 to 2008. The results show some important findings regarding the size and nature of the change occurred in the study area. A significant amount of steppe and forest lands have been destroyed or replaced by residential areas; as a result, the total area of urban region doubled in the 35-year period with a higher urbanization rate between 2000 and 2008. Key words: Environment; Land Cover; Urban; Change detection; Classification. References Chinbat,B., Bayantur,M., & Amarsaikhan.D. (2006). Investigation of the internal structure changes of ulaanbaatar city using RS and GIS. ISPRS

Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005

USGS Publications Warehouse

Gutman, G.; Byrnes, Raymond A.; Masek, J.; Covington, S.; Justice, C.; Franks, S.; Headley, Rachel

2008-01-01

Land cover is a critical component of the Earth system, infl uencing land-atmosphere interactions, greenhouse gas fl uxes, ecosystem health, and availability of food, fi ber, and energy for human populations. The recent Integrated Global Observations of Land (IGOL) report calls for the generation of maps documenting global land cover at resolutions between 10m and 30m at least every fi ve years (Townshend et al., in press). Moreover, despite 35 years of Landsat observations, there has not been a unifi ed global analysis of land-cover trends nor has there been a global assessment of land-cover change at Landsat-like resolution. Since the 1990s, the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) have supported development of data sets based on global Landsat observations (Tucker et al., 2004). These land survey data sets, usually referred to as GeoCover ™, provide global, orthorectifi ed, typically cloud-free Landsat imagery centered on the years 1975, 1990, and 2000, with a preference for leaf-on conditions. Collectively, these data sets provided a consistent set of observations to assess land-cover changes at a decadal scale. These data are freely available via the Internet from the USGS Center for Earth Resources Observation and Science (EROS) (see http://earthexplorer.usgs.gov or http://glovis.usgs.gov). This has resulted in unprecedented downloads of data, which are widely used in scientifi c studies of land-cover change (e.g., Boone et al., 2007; Harris et al., 2005; Hilbert, 2006; Huang et al. 2007; Jantz et al., 2005, Kim et al., 2007; Leimgruber, 2005; Masek et al., 2006). NASA and USGS are continuing to support land-cover change research through the development of GLS2005 - an additional global Landsat assessment circa 20051 . Going beyond the earlier initiatives, this data set will establish a baseline for monitoring changes on a 5-year interval and will pave the way toward continuous global land-cover

Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

NASA Astrophysics Data System (ADS)

Steyaert, L. T.; Hall, F. G.; Loveland, T. R.

1997-12-01

A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach 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. The land cover classification was developed 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). Quantitative areal proportions of the major boreal forest components were determined for a 821 km × 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within

Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

USGS Publications Warehouse

Steyaert, L.T.; Hall, F.G.; Loveland, Thomas R.

1997-01-01

A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach 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. The land cover classification was developed 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). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within

Spatial analysis of land cover determinants of malaria incidence in the Ashanti Region, Ghana.

PubMed

Krefis, Anne Caroline; Schwarz, Norbert Georg; Nkrumah, Bernard; Acquah, Samuel; Loag, Wibke; Oldeland, Jens; Sarpong, Nimako; Adu-Sarkodie, Yaw; Ranft, Ulrich; May, Jürgen

2011-03-23

Malaria belongs to the infectious diseases with the highest morbidity and mortality worldwide. As a vector-borne disease malaria distribution is strongly influenced by environmental factors. The aim of this study was to investigate the association between malaria risk and different land cover classes by using high-resolution multispectral Ikonos images and Poisson regression analyses. The association of malaria incidence with land cover around 12 villages in the Ashanti Region, Ghana, was assessed in 1,988 children <15 years of age. The median malaria incidence was 85.7 per 1,000 inhabitants and year (range 28.4-272.7). Swampy areas and banana/plantain production in the proximity of villages were strong predictors of a high malaria incidence. An increase of 10% of swampy area coverage in the 2 km radius around a village led to a 43% higher incidence (relative risk [RR] = 1.43, p<0.001). Each 10% increase of area with banana/plantain production around a village tripled the risk for malaria (RR = 3.25, p<0.001). An increase in forested area of 10% was associated with a 47% decrease of malaria incidence (RR = 0.53, p = 0.029). Distinct cultivation in the proximity of homesteads was associated with childhood malaria in a rural area in Ghana. The analyses demonstrate the usefulness of satellite images for the prediction of malaria endemicity. Thus, planning and monitoring of malaria control measures should be assisted by models based on geographic information systems.

Integrated modelling of anthropogenic land-use and land-cover change on the global scale

NASA Astrophysics Data System (ADS)

Schaldach, R.; Koch, J.; Alcamo, J.

2009-04-01

In many cases land-use activities go hand in hand with substantial modifications of the physical and biological cover of the Earth's surface, resulting in direct effects on energy and matter fluxes between terrestrial ecosystems and the atmosphere. For instance, the conversion of forest to cropland is changing climate relevant surface parameters (e.g. albedo) as well as evapotranspiration processes and carbon flows. In turn, human land-use decisions are also influenced by environmental processes. Changing temperature and precipitation patterns for example are important determinants for location and intensity of agriculture. Due to these close linkages, processes of land-use and related land-cover change should be considered as important components in the construction of Earth System models. A major challenge in modelling land-use change on the global scale is the integration of socio-economic aspects and human decision making with environmental processes. One of the few global approaches that integrates functional components to represent both anthropogenic and environmental aspects of land-use change, is the LandSHIFT model. It simulates the spatial and temporal dynamics of the human land-use activities settlement, cultivation of food crops and grazing management, which compete for the available land resources. The rational of the model is to regionalize the demands for area intensive commodities (e.g. crop production) and services (e.g. space for housing) from the country-level to a global grid with the spatial resolution of 5 arc-minutes. The modelled land-use decisions within the agricultural sector are influenced by changing climate and the resulting effects on biomass productivity. Currently, this causal chain is modelled by integrating results from the process-based vegetation model LPJmL model for changing crop yields and net primary productivity of grazing land. Model output of LandSHIFT is a time series of grid maps with land-use/land-cover information

The Effects of Anthropogenic Land Cover Change on Global and Regional Climate in the Preindustrial Holocene: A Review

NASA Astrophysics Data System (ADS)

Kaplan, J. O.

2014-12-01

The recent development of anthropogenic land cover change (ALCC) scenarios that cover all or part of the preindustrial Holocene (11,700 BP to ~AD 1850) has led to a number of modelling studies on the impacts of land cover change on climate, using both GCMs and regional climate models. Because most ALCC scenarios arrive at similar estimates of anthropogenic deforestation by the late preindustrial, most models agree that the net biogeophysical effect of ALCC by AD 1850 is regional cooling at mid- to high-latitudes and warming and drying over the tropics and subtropics. In particular, tropical deforestation appears to lead to local amplification of externally forced drought cycles, e.g., from ENSO. The spatial extent of these climate changes varies between models because the choice of ALCC scenario leads to large differences in the initial forcing. Those model studies that considered biogeochemical feedbacks show that the importance of preindustrial CO2 emissions ranges from being insignificant to larger than the global biogeophysical feedback, depending on assumptions made about potential natural atmospheric CO2 at the beginning of the Industrial Revolution. While the net magnitude of deforestation is similar among ALCC scenarios at AD 1850, the timing of deforestation varies widely, which, in addition to affecting the inferred importance of biogeochemical feedbacks, leads to large differences in the estimated importance of ALCC on climate earlier in the Holocene. For example, modelling experiments performed on Europe and the Mediterranean representing conditions at the peak of the Roman Empire or in Mesoamerica for the Classic Maya period show large differences in the estimated importance of the biogeophysical feedback to regional climate depending on the ALCC scenario used. The wide variety of results gained so far from ALCC and climate modelling experiments shows that the question of "how much did humans influence the state of the Earth System before the

High-resolution Land Cover Datasets, Composite Curve Numbers, and Storm Water Retention in the Tampa Bay, FL region

EPA Science Inventory

Policy makers need to understand how land cover change alters storm water regimes, yet existing methods do not fully utilize newly available datasets to quantify storm water changes at a landscape-scale. Here, we use high-resolution, remotely-sensed land cover, imperviousness, an...

Studies of land-cover, land-use, and biophysical properties of vegetation in the Large Scale Biosphere Atmosphere experiment in Amazonia.

Treesearch

Dar A. Robertsa; Michael Keller; Joao Vianei Soares

2003-01-01

We summarize early research on land-cover, land-use, and biophysical properties of vegetation from the Large Scale Biosphere Atmosphere (LBA) experiment in Amazoˆnia. LBA is an international research program developed to evaluate regional function and to determine how land-use and climate modify biological, chemical and physical processes there. Remote sensing has...

Chesapeake bay watershed land cover data series

USGS Publications Warehouse

Irani, Frederick M.; Claggett, Peter

2010-01-01

To better understand how the land is changing and to relate those changes to water quality trends, the USGS EGSC funded the production of a Chesapeake Bay Watershed Land Cover Data Series (CBLCD) representing four dates: 1984, 1992, 2001, and 2006. EGSC will publish land change forecasts based on observed trends in the CBLCD over the coming year. They are in the process of interpreting and publishing statistics on the extent, type and patterns of land cover change for 1984-2006 in the Bay watershed, major tributaries and counties.

Shore zone land use and land cover: Central Atlantic Regional Ecological Test Site

USGS Publications Warehouse

Dolan, R.; Hayden, B.P.; Vincent, C.L.

1974-01-01

Anderson's 1972 United States Geological Survey classification in modified form was applied to the barrier-island coastline within the CARETS region. High-altitude, color-infrared photography of December, 1972, and January, 1973, served as the primary data base in this study. The CARETS shore zone studied was divided into six distinct geographical regions; area percentages for each class in the modified Anderson classification are presented. Similarities and differences between regions are discussed within the framework of man's modification of these landscapes. The results of this study are presented as a series of 19 maps of land-use categories. Recommendations are made for a remote-sensing system for monitoring the CARETS shore zone within the context of the dynamics of the landscapes studied.

Connectivity and distant drivers of land change: A case study of land use, land cover, and livelihood changes in Quang Tri, Vietnam

NASA Astrophysics Data System (ADS)

Rounds, Eric

The urban lowland areas of Vietnam have been at the forefront of economic liberalization over the last 30 years, while the more remote mountainous areas of the country have lagged behind. Upland areas in the Northern and Central portions of Vietnam in particular remain largely impoverished and disconnected from broader national and regional markets. To address this economic inequality in the uplands, recent economic development efforts such as the East-West Economic Corridor (EWEC) have aimed at expanding road infrastructure to remote areas in Central Vietnam. This study examines the impact of road expansion in the EWEC on a single village in Quang Tri, Vietnam. It draws from social economic data gathered during fieldwork and a historical land cover analysis to address how land use, land cover, and livelihoods have changed in recent decades. Moreover, the paper discusses the distal and proximate drivers of these changes. Findings show that the improved road connectivity provided by new roads has facilitated the transmission of distant market-related drivers into the study area, and that these drivers have fostered significant changes in land use, land cover, and livelihoods.

Soil cover patterns influence on the land environmental functions, agroecological quality, land-use and monitoring efficiency in the Central Russia

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Yashin, Ivan; Lukin, Sergey; Valentini, Riccardo

2015-04-01

First decades of XXI century actualized for soil researches the principal methodical problem of most modern geosciences: what spatial and temporal scale would be optimal for land quality evaluation and land-use practice optimizing? It is becoming obvious that this question cannot have one solution and have to be solved with especial attention on the features of concrete region and landscape, land-use history and practical issues, land current state and environmental functions, soil cover patterns and variability, governmental requirements and local society needs, best available technologies and their potential profitability. Central Russia is one of the most dynamical economic regions with naturally high and man-made complicated landscape and soil cover variability, long-term land-use history and self-contradictory issues, high potential of profitable farming and increased risks of land degradation. Global climate and technological changes essentially complicate the originally high and sharply increased in XX century farming land heterogeneity in the Central Russia that actualizes system analysis of its zonal, intra-zonal and azonal soil cover patterns according to their influence on land environmental functions, agroecological quality, and land-use and monitoring efficiency variability. Developed by the Laboratory of agroecological monitoring, ecosystem modeling & prediction (LAMP / RTSAU with support of RF Governmental projects #11.G34.31.0079 and #14.120.14.4266) regional systems of greenhouse gases environmental monitoring RusFluxNet (6 fixed & 1 mobile eddy covariance stations with zonal functional sets of key plots with chamber investigations in 5 Russian regions) and of agroecological monitoring (in representative key plots with different farming practice in 9 RF regions) allow to do this analysis in frame of enough representative regional multi-factorial matrix of soil cover patterns, bioclimatic conditions, landscape features, and land-use history and

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.

Temporal changes in land cover types and the incidence of malaria in Mangalore, India.

PubMed

Mohan, Venkata Raghava; Naumova, Elena N

2014-01-01

Malaria contributes to 881000 deaths worldwide annually and India is a major contributor in the region. This study aimed at detecting land cover changes and assesses their relationship with the burden of malaria in Mangalore taluk of southern India. Landsat TM images were obtained from the U.S. Geological Survey data repository. The statistics for the malaria incidences in the region were obtained from the National Vector Borne Diseases Control Program division of the State of Karnataka. The images were preprocessed, classified and change detection statistics were employed for major land cover types. An increase in the urban land cover by 20% with a reduction in the mountainous terrain by 34.7% and vegetation by 38.7% was noted between the years 2003 and 2005. The annual incidence of malaria increased five-fold from 203 to 1035/100000 population during the period. This study demonstrates the application of publicly available remote sensed data as a cost effective approach to study the agent, host and environment relationships in resource scarce settings which would provide valuable information planning and policy making at regional levels.

Open Land-Use Map: A Regional Land-Use Mapping Strategy for Incorporating OpenStreetMap with Earth Observations

NASA Astrophysics Data System (ADS)

Yang, D.; Fu, C. S.; Binford, M. W.

2017-12-01

The southeastern United States has high landscape heterogeneity, withheavily managed forestlands, highly developed agriculture lands, and multiple metropolitan areas. Human activities are transforming and altering land patterns and structures in both negative and positive manners. A land-use map for at the greater scale is a heavy computation task but is critical to most landowners, researchers, and decision makers, enabling them to make informed decisions for varying objectives. There are two major difficulties in generating the classification maps at the regional scale: the necessity of large training point sets and the expensive computation cost-in terms of both money and time-in classifier modeling. Volunteered Geographic Information (VGI) opens a new era in mapping and visualizing our world, where the platform is open for collecting valuable georeferenced information by volunteer citizens, and the data is freely available to the public. As one of the most well-known VGI initiatives, OpenStreetMap (OSM) contributes not only road network distribution, but also the potential for using this data to justify land cover and land use classifications. Google Earth Engine (GEE) is a platform designed for cloud-based mapping with a robust and fast computing power. Most large scale and national mapping approaches confuse "land cover" and "land-use", or build up the land-use database based on modeled land cover datasets. Unlike most other large-scale approaches, we distinguish and differentiate land-use from land cover. By focusing our prime objective of mapping land-use and management practices, a robust regional land-use mapping approach is developed by incorporating the OpenstreepMap dataset into Earth observation remote sensing imageries instead of the often-used land cover base maps.

Four decades of land-cover, land-use and hydroclimatology changes in the Itacaiúnas River watershed, southeastern Amazon.

PubMed

Souza-Filho, Pedro Walfir M; de Souza, Everaldo B; Silva Júnior, Renato O; Nascimento, Wilson R; Versiani de Mendonça, Breno R; Guimarães, José Tasso F; Dall'Agnol, Roberto; Siqueira, José Oswaldo

2016-02-01

Long-term human-induced impacts have significantly changed the Amazonian landscape. The most dramatic land cover and land use (LCLU) changes began in the early 1970s with the establishment of the Trans-Amazon Highway and large government projects associated with the expansion of agricultural settlement and cattle ranching, which cleared significant tropical forest cover in the areas of new and accelerated human development. Taking the changes in the LCLU over the past four decades as a basis, this study aims to determine the consequences of land cover (forest and savanna) and land use (pasturelands, mining and urban) changes on the hydroclimatology of the Itacaiúnas River watershed area of the located in the southeastern Amazon region. We analyzed a multi-decadal Landsat dataset from 1973, 1984, 1994, 2004 and 2013 and a 40-yr time series of water discharge from the Itacaiúnas River, as well as air temperature and relative humidity data over this drainage area for the same period. We employed standard Landsat image processing techniques in conjunction with a geographic object-based image analysis and multi-resolution classification approach. With the goal of detecting possible long-term trends, non-parametric Mann-Kendall test was applied, based on a Sen slope estimator on a 40-yr annual PREC, TMED and RH time series, considering the spatial average of the entire watershed. In the 1970s, the region was entirely covered by forest (99%) and savanna (∼0.3%). Four decades later, only ∼48% of the tropical forest remains, while pasturelands occupy approximately 50% of the watershed area. Moreover, in protected areas, nearly 97% of the tropical forest remains conserved, while the forest cover of non-protected areas is quite fragmented and, consequently, unevenly distributed, covering an area of only 30%. Based on observational data analysis, there is evidence that the conversion of forest cover to extensive and homogeneous pasturelands was accompanied by systematic

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

Land cover and topography affect the land transformation caused by wind facilities

USGS Publications Warehouse

Diffendorfer, Jay E.; Compton, Roger W.

2014-01-01

Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.

Land Cover and Topography Affect the Land Transformation Caused by Wind Facilities

PubMed Central

Diffendorfer, Jay E.; Compton, Roger W.

2014-01-01

Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here. PMID:24558449

Biophysical effects on temperature and precipitation due to land cover change

NASA Astrophysics Data System (ADS)

Perugini, Lucia; Caporaso, Luca; Marconi, Sergio; Cescatti, Alessandro; Quesada, Benjamin; de Noblet-Ducoudré, Nathalie; House, Johanna I.; Arneth, Almut

2017-05-01

Anthropogenic land cover changes (LCC) affect regional and global climate through biophysical variations of the surface energy budget mediated by albedo, evapotranspiration, and roughness. This change in surface energy budget may exacerbate or counteract biogeochemical greenhouse gas effects of LCC, with a large body of emerging assessments being produced, sometimes apparently contradictory. We reviewed the existing scientific literature with the objective to provide an overview of the state-of-the-knowledge of the biophysical LCC climate effects, in support of the assessment of mitigation/adaptation land policies. Out of the published studies that were analyzed, 28 papers fulfilled the eligibility criteria, providing surface air temperature and/or precipitation change with respect to LCC regionally and/or globally. We provide a synthesis of the signal, magnitude and uncertainty of temperature and precipitation changes in response to LCC biophysical effects by climate region (boreal/temperate/tropical) and by key land cover transitions. Model results indicate that a modification of biophysical processes at the land surface has a strong regional climate effect, and non-negligible global impact on temperature. Simulations experiments of large-scale (i.e. complete) regional deforestation lead to a mean reduction in precipitation in all regions, while air surface temperature increases in the tropics and decreases in boreal regions. The net global climate effects of regional deforestation are less certain. There is an overall consensus in the model experiments that the average global biophysical climate response to complete global deforestation is atmospheric cooling and drying. Observed estimates of temperature change following deforestation indicate a smaller effect than model-based regional estimates in boreal regions, comparable results in the tropics, and contrasting results in temperate regions. Regional/local biophysical effects following LCC are important for

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.

Monthly fractional green vegetation cover associated with land cover classes of the conterminous USA

USGS Publications Warehouse

Gallo, Kevin P.; Tarpley, Dan; Mitchell, Ken; Csiszar, Ivan; Owen, Timothy W.; Reed, Bradley C.

2001-01-01

The land cover classes developed under the coordination of the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) have been analyzed for a study area that includes the Conterminous United States and portions of Mexico and Canada. The 1-km resolution data have been analyzed to produce a gridded data set that includes within each 20-km grid cell: 1) the three most dominant land cover classes, 2) the fractional area associated with each of the three dominant classes, and 3) the fractional area covered by water. Additionally, the monthly fraction of green vegetation cover (fgreen) associated with each of the three dominant land cover classes per grid cell was derived from a 5-year climatology of 1-km resolution NOAA-AVHRR data. The variables derived in this study provide a potential improvement over the use of monthly fgreen linked to a single land cover class per model grid cell.

Land use and land cover mapping: City of Palm Bay, Florida

NASA Technical Reports Server (NTRS)

Barile, D. D.; Pierce, R.

1977-01-01

Two different computer systems were compared for use in making land use and land cover maps. The Honeywell 635 with the LANDSAT signature development program (LSDP) produced a map depicting general patterns, but themes were difficult to classify as specific land use. Urban areas were unclassified. The General Electric Image 100 produced a map depicting eight land cover categories classifying 68 percent of the total area. Ground truth, LSDP, and Image 100 maps were all made to the same scale for comparison. LSDP agreed with the ground truth 60 percent and 64 percent within the two test areas compared and Image 100 was in agreement 70 percent and 80 percent.

Analysing the Effects of Different Land Cover Types on Land Surface Temperature Using Satellite Data

NASA Astrophysics Data System (ADS)

Şekertekin, A.; Kutoglu, Ş. H.; Kaya, S.; Marangoz, A. M.

2015-12-01

Monitoring Land Surface Temperature (LST) via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES) Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

Towards a Remote Sensing Based Assessment of Land Susceptibility to Degradation: Examining Seasonal Variation in Land Use-Land Cover for Modelling Land Degradation in a Semi-Arid Context

NASA Astrophysics Data System (ADS)

Mashame, Gofamodimo; Akinyemi, Felicia

2016-06-01

Land degradation (LD) is among the major environmental and anthropogenic problems driven by land use-land cover (LULC) and climate change worldwide. For example, poor LULC practises such as deforestation, livestock overstocking, overgrazing and arable land use intensification on steep slopes disturbs the soil structure leaving the land susceptible to water erosion, a type of physical land degradation. Land degradation related problems exist in Sub-Saharan African countries such as Botswana which is semi-arid in nature. LULC and LD linkage information is still missing in many semi-arid regions worldwide.Mapping seasonal LULC is therefore very important in understanding LULC and LD linkages. This study assesses the impact of seasonal LULC variation on LD utilizing Remote Sensing (RS) techniques for Palapye region in Central District, Botswana. LULC classes for the dry and rainy seasons were classified using LANDSAT 8 images at Level I according to the Food and Agriculture Organization (FAO) International Organization of Standardization (ISO) code 19144. Level I consists of 10 LULC classes. The seasonal variations in LULC are further related to LD susceptibility in the semi-arid context. The results suggest that about 985 km² (22%) of the study area is susceptible to LD by water, major LULC types affected include: cropland, paved/rocky material, bare land, built-up area, mining area, and water body. Land degradation by water susceptibility due to seasonal land use-land cover variations is highest in the east of the study area where there is high cropland to bare land conversion.

A tool to evaluate local biophysical effects on temperature due to land cover change transitions

NASA Astrophysics Data System (ADS)

Perugini, Lucia; Caporaso, Luca; Duveiller, Gregory; Cescatti, Alessandro; Abad-Viñas, Raul; Grassi, Giacomo; Quesada, Benjamin

2017-04-01

Land Cover Changes (LCC) affect local, regional and global climate through biophysical variations of the surface energy budget mediated by albedo, evapotranspiration, and roughness. Assessment of the full climate impacts of anthropogenic LCC are incomplete without considering biophysical effects, but the high level of uncertainties in quantifying their impacts to date have made it impractical to offer clear advice on which policy makers could act. To overcome this barrier, we provide a tool to evaluate the biophysical impact of a matrix of land cover transitions, following a tiered methodological approach similar to the one provided by the IPCC to estimate the biogeochemical effects, i.e. through three levels of methodological complexity, from Tier 1 (i.e. default method and factors) to Tier 3 (i.e. specific methods and factors). In particular, the tool provides guidance for quantitative assessment of changes in temperature following a land cover transition. The tool focuses on temperature for two main reasons (i) it is the main variable of interest for policy makers at local and regional level, and (ii) temperature is able to summarize the impact of radiative and non-radiative processes following LULCC. The potential changes in annual air temperature that can be expected from various land cover transitions are derived from a dedicated dataset constructed by the JRC in the framework of the LUC4C FP7 project. The inputs for the dataset are air temperature values derived from satellite Earth Observation data (MODIS) and land cover characterization from the ESA Climate Change Initiative product reclassified into their IPCC land use category equivalent. This data, originally at 0.05 degree of spatial resolution, is aggregated and analysed at regional level to provide guidance on the expected temperature impact following specific LCC transitions.

Land-cover observations as part of a Global Earth Observation System of Systems (GEOSS): Progress, activities, and prospects

USGS Publications Warehouse

Herold, M.; Woodcock, C.E.; Loveland, Thomas R.; Townshend, J.; Brady, M.; Steenmans, C.; Schmullius, C. C.

2008-01-01

The international land-cover community has been working with GEO since 2005 to build the foundations for land-cover observations as an integral part of a Global Earth Observation System of Systems (GEOSS). The Group on Earth Observation (GEO) has provided the platform to elevate the societal relevance of land cover monitoring and helped to link a diverse set of global, regional, and national activities. A dedicated 2007-2009 GEO work plan task has resulted in achievements on the strategic and implementation levels. Integrated Global Observations of the Land (IGOL), the land theme of the Integrated Global Observation Strategy (IGOS), has been approved and is now in the process of transition into GEO implementation. New global land-cover maps at moderate spatial resolutions (i.e., GLOBCOVER) are being produced using guidelines and standards of the international community. The Middecadal Global Landsat Survey for 2005-2006 is extending previous 1990 and 2000 efforts for global, high-quality Landsat data. Despite this progress, essential challenges for building a sustained global land-cover-observing system remain, including: international cooperation on the continuity of global observations; ensuring consistency in land monitoring approaches; community engagement and country participation in mapping activities; commitment to ongoing quality assurance and validation; and regional networking and capacity building.

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.

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...

Ecosystem services from converted land: the importance of tree cover in Amazonian pastures

USGS Publications Warehouse

Barrett, Kirsten; Valentim, Judson; Turner, B. L.

2013-01-01

Deforestation is responsible for a substantial fraction of global carbon emissions and changes in surface energy budgets that affect climate. Deforestation losses include wildlife and human habitat, and myriad forest products on which rural and urban societies depend for food, fiber, fuel, fresh water, medicine, and recreation. Ecosystem services gained in the transition from forests to pasture and croplands, however, are often ignored in assessments of the impact of land cover change. The role of converted lands in tropical areas in terms of carbon uptake and storage is largely unknown. Pastures represent the fastest-growing form of converted land use in the tropics, even in some areas of rapid urban expansion. Tree biomass stored in these areas spans a broad range, depending on tree cover. Trees in pasture increase carbon storage, provide shade for cattle, and increase productivity of forage material. As a result, increasing fractional tree cover can provide benefits land managers as well as important ecosystem services such as reducing conversion pressure on forests adjacent to pastures. This study presents an estimation of fractional tree cover in pasture in a dynamic region on the verge of large-scale land use change. An appropriate sampling interval is established for similar studies, one that balances the need for independent samples of sufficient number to characterize a pasture in terms of fractional tree cover. This information represents a useful policy tool for government organizations and NGOs interested in encouraging ecosystem services on converted lands. Using high spatial resolution remotely sensed imagery, fractional tree cover in pasture is quantified for the municipality of Rio Branco, Brazil. A semivariogram and devolving spatial resolution are employed to determine the coarsest sampling interval that may be used, minimizing effects of spatial autocorrelation. The coarsest sampling interval that minimizes spatial dependence was about 22 m. The

Climate Risk and Vulnerability in the Caribbean and Gulf of Mexico Region: Interactions with Spatial Population and Land Cover Change

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M.; Baptista, S.; Adamo, S.

2010-12-01

Vulnerability to climate variability and change will depend on dynamic interactions between different aspects of climate, land-use change, and socioeconomic trends. Measurements and projections of these changes are difficult at the local scale but necessary for effective planning. New data sources and methods make it possible to assess land-use and socioeconomic changes that may affect future patterns of climate vulnerability. In this paper we report on new time series data sets that reveal trends in the spatial patterns of climate vulnerability in the Caribbean/Gulf of Mexico Region. Specifically, we examine spatial time series data for human population over the period 1990-2000, time series data on land use and land cover over 2000-2009, and infant mortality rates as a proxy for poverty for 2000-2008. We compare the spatial trends for these measures to the distribution of climate-related natural disaster risk hotspots (cyclones, floods, landslides, and droughts) in terms of frequency, mortality, and economic losses. We use these data to identify areas where climate vulnerability appears to be increasing and where it may be decreasing. Regions where trends and patterns are especially worrisome include coastal areas of Guatemala and Honduras.

LAND COVER TRENDS: RATES, CAUSES, AND CONSEQUENCES OF LATE TWENTIETH CENTURY U.S LAND COVER CHANGE

EPA Science Inventory

Information on the rates, driving forces, and consequences of land use and land cover change is important in studies addressing issues ranging from the health of aquatic resources to climate change. This four-year research project between the U.S. Geological Survey and the U.S. ...

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,...

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...

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

Land Cover Analysis of Temperate Asia

NASA Technical Reports Server (NTRS)

Justice, Chris

1998-01-01

Satellite data from the advanced very high resolution radiometer (AVHRR) instrument were used to produce a general land cover distribution of temperate Asia (referred to hence as Central Asia) from 1982, starting with the NOAA-7 satellite, and continuing through 1991, ending with the NOAA-11 satellite. Emphasis was placed upon delineating the and and semi-arid zones of Central Asia (largely Mongolia and adjacent areas), mapping broad categories of aggregated land cover, and upon studying photosynthetic capacity increases in Central Asia from 1982 to 1991.

Impacts of historic and projected land-cover, land-use, and land-management change on carbon and water fluxes: The Land Use Model Intercomparison Project (LUMIP)

NASA Astrophysics Data System (ADS)

Lawrence, D. M.; Lombardozzi, D. L.; Lawrence, P.; Hurtt, G. C.

2017-12-01

Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. In the future, land-use activities are likely to intensify to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the broad question of impacts of land-use and land-cover change (LULCC) as well as more detailed science questions to get at process-level attribution, uncertainty, and data requirements in more depth and sophistication than possible in a multi-model context to date. LUMIP is multi-faceted and aims to advance our understanding of land-use change from several perspectives. In particular, LUMIP includes a factorial set of land-only simulations that differ from each other with respect to the specific treatment of land use or land management (e.g., irrigation active or not, crop fertilization active or not, wood harvest on or not), or in terms of prescribed climate. This factorial series of experiments serves several purposes and is designed to provide a detailed assessment of how the specification of land-cover change and land management affects the carbon, water, and energy cycle response to land-use change. The potential analyses that are possible through this set of experiments are vast. For example, comparing a control experiment with all land management active to an experiment with no irrigation allows a multi-model assessment of whether or not the increasing use of irrigation during the 20th century is likely to have significantly altered trends of regional water and energy fluxes (and therefore climate) and/or crop yield and carbon fluxes in agricultural regions. Here, we will present preliminary results from the factorial set of experiments utilizing the Community Land Model (CLM5). The analyses presented here will help guide multi-model analyses once the full set of LUMIP simulations are available.

Land change monitoring, assessment, and projection (LCMAP) revolutionizes land cover and land change research

USGS Publications Warehouse

Young, Steven

2017-05-02

When nature and humanity change Earth’s landscapes - through flood or fire, public policy, natural resources management, or economic development - the results are often dramatic and lasting.Wildfires can reshape ecosystems. Hurricanes with names like Sandy or Katrina will howl for days while altering the landscape for years. One growing season in the evolution of drought-resistant genetics can transform semiarid landscapes into farm fields.In the past, valuable land cover maps created for understanding the effects of those events - whether changes in wildlife habitat, water-quality impacts, or the role land use and land cover play in affecting weather and climate - came out at best every 5 to 7 years. Those high quality, high resolution maps were good, but users always craved more: even higher quality data, additional land cover and land change variables, more detailed legends, and most importantly, more frequent land change information.Now a bold new initiative called Land Change Monitoring, Assessment, and Projection (LCMAP) promises to fulfill that demand.Developed at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, LCMAP provides definitive, timely information on how, why, and where the planet is changing. LCMAP’s continuous monitoring process can detect changes as they happen every day that Landsat satellites acquire clear observations. The result will be to place near real-time information in the hands of land and resource managers who need to understand the effects these changes have on landscapes.

Three Global Land Cover and Use Stage considering Environmental Condition and Economic Development

NASA Astrophysics Data System (ADS)

Lee, W. K.; Song, C.; Moon, J.; Ryu, D.

2016-12-01

The Mid-Latitude zone can be broadly defined as part of the hemisphere between around 30° - 60° latitude. This zone is a home to over more than 50% of the world population and encompasses about 36 countries throughout the principal regions which host most of the global problems related to development and poverty. Mid-Latitude region and its ecotone demands in-depth analysis, however, latitudinal approach has not been widely recognized, considering that many of natural resources and environment indicators, as well as social and economic indicators are based on administrative basis or by country and regional boundaries. This study sets the land cover change and use stage based on environmental condition and economic development. Because various land cover and use among the regions, form vegetated parts of East Asia and Mediterranean to deserted parts of Central Asia, the forest area was varied between countries. In addition, some nations such as North Korea, Afghanistan, Pakistan showed decreasing trends in forest area whereas some nations showed increasing trends in forest area. The economic capacity for environmental activities and policies for restoration were different among countries. By adopting the standard from IMF or World Bank, developing and developed counties were classified. Based on the classification, this study suggested the land cover and use stages as degradation, restoration, and sustainability. As the degradation stage, the nations which had decreasing forest area with less environmental restoration capacity based on economic size were selected. As the restoration stage, the nation which had increasing forest area or restoration capacity were selected. In the case of the sustainability, the nation which had enough restoration capacity with increasing forest area or small ratio in forest area decreasing were selected. In reviewing some of the past and current major environmental challenges that regions of Mid-Latitudes are facing, grouping by

The importance of land cover change across urban-rural typologies for climate modeling.

PubMed

Vargo, Jason; Habeeb, Dana; Stone, Brian

2013-01-15

Land cover changes affect local surface energy balances by changing the amount of solar energy reflected, the magnitude and duration over which absorbed energy is released as heat, and the amount of energy that is diverted to non-heating fluxes through evaporation. However, such local influences often are only crudely included in climate modeling exercises, if at all. A better understanding of local land conversion dynamics can serve to inform inputs for climate models and increase the role for land use planning in climate management policy. Here we present a new approach for projecting and incorporating metropolitan land cover change into mesoscale climate and other environmental assessment models. Our results demonstrate the relative contributions of different land development patterns to land cover change and conversion and suggest that regional growth management strategies serving to increase settlement densities over time can have a significant influence on the rate of deforestation per unit of population growth. Employing the approach presented herein, the impacts of land conversion on climate change and on parallel environmental systems and services, such as ground water recharge, habitat provision, and food production, may all be investigated more closely and managed through land use planning. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Land use pattern and its dynamic changes in Amur tiger distribution region].

PubMed

Li, Zhong-wen; Wu, Jian-guo; Kou, Xiao-jun; Tian, Yu; Wang, Tian-ming; Mu, Pu; Ge, Jian-ping

2009-03-01

Land use and land cover change has been the primary cause for the habitat loss and fragmentation in the distribution region of Amur tiger (Panthera tigris altaica). Based on the spatiotemporal changes of land use and land cover in the distribution region, as well as their effects on the population dynamics of Amur tiger, this paper analyzed the development process and its characteristics of the main land use types (agricultural land, forest land, and construction land) in this region, with the land use change history being divided chronically into three distinctive periods, i.e., ancient times (prior to 1860), modern times (1860-1949), and contemporary times (after 1949). The results showed that the sporadic land use in ancient times had no significant effects on the survival of Amur tiger, while the extensive and intensive land use after the 1860s was mainly responsible for the decrease of Amur tiger population and its living space. Since 1949, the Amur tiger distribution region has been divided into two parts, i.e., Northeast China and Russia Far East. The differences in land use pattern, policy, and intensity between these two parts led to different survival status of Amur tiger. The key driving forces for the land use change in Amur tiger distribution region were human population increase, policy change, and increased productivity.

Quantifying outdoor water consumption of urban land use/land cover: sensitivity to drought.

PubMed

Kaplan, Shai; Myint, Soe W; Fan, Chao; Brazel, Anthony J

2014-04-01

Outdoor water use is a key component in arid city water systems for achieving sustainable water use and ensuring water security. Using evapotranspiration (ET) calculations as a proxy for outdoor water consumption, the objectives of this research are to quantify outdoor water consumption of different land use and land cover types, and compare the spatio-temporal variation in water consumption between drought and wet years. An energy balance model was applied to Landsat 5 TM time series images to estimate daily and seasonal ET for the Central Arizona Phoenix Long-Term Ecological Research region (CAP-LTER). Modeled ET estimations were correlated with water use data in 49 parks within CAP-LTER and showed good agreement (r² = 0.77), indicating model effectiveness to capture the variations across park water consumption. Seasonally, active agriculture shows high ET (>500 mm) for both wet and dry conditions, while the desert and urban land cover types experienced lower ET during drought (<300 mm). Within urban locales of CAP-LTER, xeric neighborhoods show significant differences from year to year, while mesic neighborhoods retain their ET values (400-500 mm) during drought, implying considerable use of irrigation to sustain their greenness. Considering the potentially limiting water availability of this region in the future due to large population increases and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life.

Assessing the impact of urban land cover composition on CO2 flux

NASA Astrophysics Data System (ADS)

Becker, K.; Hinkle, C.

2013-12-01

Urbanization is an ever increasing trend in global land use change, and has been identified as a key driver of CO2 emissions. Therefore, understanding how urbanization affects CO2 flux across a range of climatic zones and development patterns is critical to projecting the impact of future land use on CO2 flux dynamics. A growing number of studies are applying the eddy covariance method to urban areas to quantify the CO2 flux dynamics of these systems. However, interpretation of eddy covariance data in these urban systems presents a challenge, particularly in areas with high heterogeneity due to a mixing of built and green space. Here we present a study aimed at establishing a relationship between land cover composition and CO2 flux for a heterogeneous urban area of Orlando, FL. CO2 flux has been measured at this site for > 4 years using an open path eddy covariance system. Land cover at this site was classified into built and green space, and relative weight of both land covers were calculated for each 30 min CO2 flux measurement using the Schuepp model and a source area based on +/- one standard deviation of wind direction. The results of this analysis established a relationship between built land cover and CO2 flux within the measured footprint of this urban area. These results, in combination with future projected land use data, will be a valuable resource for providing insight into the impact of future urbanization on CO2 flux dynamics in this region.

MRLC-LAND COVER MAPPING, ACCURACY ASSESSMENT AND APPLICATION RESEARCH

EPA Science Inventory

The National Land Cover Database (NLCD), produced by the Multi-Resolution Land Characteristics (MRLC) provides consistently classified land-cover and ancillary data for the United States. These data support many of the modeling and monitoring efforts related to GPRA goals of Cle...

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

Stratifying Tropical Fires by Land Cover: Insights into Amazonian Fires, Aerosol Loading, and Regional Deforestation

NASA Technical Reports Server (NTRS)

TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

2010-01-01

This study analyzes changes in the number of fires detected on forest, grass, and transition lands during the 2002-2009 biomass burning seasons using fire detection data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the total number of detected fires correlates well with MODIS mean aerosol optical depth (AOD) from year to year, in accord with other studies. However, we also show that the ratio of forest to savanna fires varies substantially from year to year. Forest fires have trended downward, on average, since the beginning of 2006 despite a modest increase in 2007. Our study suggests that high particulate matter loading detected in 2007 was likely due to a large number of savanna/agricultural fires that year. Finally, we illustrate that the correlation between annual Brazilian deforestation estimates and MODIS fires is considerably higher when fires are stratified by MODIS-derived land cover classifications.

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

AVHRR channel selection for land cover classification

USGS Publications Warehouse

Maxwell, S.K.; Hoffer, R.M.; Chapman, P.L.

2002-01-01

Mapping land cover of large regions often requires processing of satellite images collected from several time periods at many spectral wavelength channels. However, manipulating and processing large amounts of image data increases the complexity and time, and hence the cost, that it takes to produce a land cover map. Very few studies have evaluated the importance of individual Advanced Very High Resolution Radiometer (AVHRR) channels for discriminating cover types, especially the thermal channels (channels 3, 4 and 5). Studies rarely perform a multi-year analysis to determine the impact of inter-annual variability on the classification results. We evaluated 5 years of AVHRR data using combinations of the original AVHRR spectral channels (1-5) to determine which channels are most important for cover type discrimination, yet stabilize inter-annual variability. Particular attention was placed on the channels in the thermal portion of the spectrum. Fourteen cover types over the entire state of Colorado were evaluated using a supervised classification approach on all two-, three-, four- and five-channel combinations for seven AVHRR biweekly composite datasets covering the entire growing season for each of 5 years. Results show that all three of the major portions of the electromagnetic spectrum represented by the AVHRR sensor are required to discriminate cover types effectively and stabilize inter-annual variability. Of the two-channel combinations, channels 1 (red visible) and 2 (near-infrared) had, by far, the highest average overall accuracy (72.2%), yet the inter-annual classification accuracies were highly variable. Including a thermal channel (channel 4) significantly increased the average overall classification accuracy by 5.5% and stabilized interannual variability. Each of the thermal channels gave similar classification accuracies; however, because of the problems in consistently interpreting channel 3 data, either channel 4 or 5 was found to be a more

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.

Monitoring land/forest cover using the Kalman filter: A proposal

Treesearch

Raymond L. Czaplewski; Ralph J. Alig; Noel D. Cost

1988-01-01

Although growth and yield models have been used to update forest inventories for large regions, such models poorly predict cover changes from land use conversions, regeneration, and harvest. These changes could be monitored directly for large areas using remote sensing, which can be expensive, or estimates made by agricultural agencies, which are not detailed for...

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.

Effects of Microclimate Condition Changes Due to Land Use and Land Cover Changes on the Survivorship of Malaria Vectors in China-Myanmar Border Region.

PubMed

Zhong, Daibin; Wang, Xiaoming; Xu, Tielong; Zhou, Guofa; Wang, Ying; Lee, Ming-Chieh; Hartsel, Joshua A; Cui, Liwang; Zheng, Bin; Yan, Guiyun

2016-01-01

In the past decade, developing countries have been experiencing rapid land use and land cover changes, including deforestation and cultivation of previously forested land. However, little is known about the impact of deforestation and land-use changes on the life history of malaria vectors and their effects on malaria transmission. This study examined the effects of deforestation and crop cultivation on the adult survivorship of major malaria mosquitoes, Anopheles sinensis and An. minimus in the China-Myanmar border region. We examined three conditions: indoor, forested, and banana plantation. Mean survival time of An. sinensis in banana plantation environment was significantly longer than those in forested environment, and mosquitoes exhibited the longest longevity in the indoor environment. This pattern held for both males and females, and also for An. minimus. To further test the effect of temperature on mosquito survival, we used two study sites with different elevation and ambient temperatures. Significantly higher survivorship of both species was found in sites with lower elevation and higher ambient temperature. Increased vector survival in the deforested area could have an important impact on malaria transmission in Southeast Asia. Understanding how deforestation impacts vector survivorship can help combat malaria transmission.

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.

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.

Spatial Relationships between Biomass Burning and Land Use / Land Cover Dynamics in Northern Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Ellison, L.; Ichoku, C. M.

2016-12-01

Biomass burning (BB) is an extensive and persistent phenomenon across the world, and is a result of either natural (via lightning strikes) or anthropogenic processes, depending on the location. In Northern Sub-Saharan Africa (NSSA), where access to affordable modern farming equipment is extremely limited, agricultural practices dominate and BB is completely anthropogenic for all practical purposes, resulting in NSSA consistently contributing 15-20% of the total global annual emission of particulate matter from fires, according to estimates from version 1.0 of the Fire Energetics and Emissions Research BB emissions inventory (FEERv1.0, http://feer.gsfc.nasa.gov/data/emissions/). The FEERv1.0 algorithm uses a land cover type (LCT) product at either 0.5° or 0.1° resolutions for the conversion of total particulate matter estimates to various other smoke constituents. Due to the fact that fires are closely associated with land cover types, it became apparent that a fire-prone land cover type product at those spatial resolutions were needed, resulting in the FEERv1 BB-LCT product (http://feer.gsfc.nasa.gov/data/landcover/). In version 2 of the product, it was found that 6% of all grid cells with partial or full land cover in the original 0.5° LCT product is reclassified when considering BB practices. In NSSA, we see that the differences fall mainly along the borders between major regions of different LCT. Roughly speaking, fires along the cropland/savanna and savanna/forest borders in NSSA are mostly from from savanna burning. An in-depth analysis of the spatial extent and variability of fires and land cover in NSSA reveals that within the last one-and-a-half decades, the maximum fire activity occurred in the 2006/07 fire season and has been decreasing ever since. Interestingly, despite this decrease in fire activity, we observe a continuing increase in land cover conversion to cropland over the same time period at a rate of 0.3%/yr, which is equal to ≈37,500 km2/yr

Forest service contributions to the national land cover database (NLCD): Tree Canopy Cover Production

Treesearch

Bonnie Ruefenacht; Robert Benton; Vicky Johnson; Tanushree Biswas; Craig Baker; Mark Finco; Kevin Megown; John Coulston; Ken Winterberger; Mark Riley

2015-01-01

A tree canopy cover (TCC) layer is one of three elements in the National Land Cover Database (NLCD) 2011 suite of nationwide geospatial data layers. In 2010, the USDA Forest Service (USFS) committed to creating the TCC layer as a member of the Multi-Resolution Land Cover (MRLC) consortium. A general methodology for creating the TCC layer was reported at the 2012 FIA...

Monitoring Urban Land Cover/land Use Change in Algiers City Using Landsat Images (1987-2016)

NASA Astrophysics Data System (ADS)

Bouchachi, B.; Zhong, Y.

2017-09-01

Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.

A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi

USGS Publications Warehouse

Smith, Kathryn E.L.; Nayegandhi, Amar; Brock, John C.

2010-01-01

-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.

Implication of Agricultural Land Use Change on Regional Climate Projection

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Agricultural land use plays an important role in land-atmosphere interaction. Agricultural activity is one of the most important processes driving human-induced land use land cover change (LULCC) in a region. In addition to future socioeconomic changes, climate-induced changes in crop yield represent another important factor shaping agricultural land use. In feedback, the resulting LULCC influences the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. Therefore, assessment of climate change impact on future agricultural land use and its feedback is of great importance in climate change study. In this study, to evaluate the feedback of projected land use changes to the regional climate in West Africa, we employed an asynchronous coupling between a regional climate model (RegCM) and a prototype land use projection model (LandPro). The LandPro model, which was developed to project the future change in agricultural land use and the resulting shift in natural vegetation in West Africa, is a spatially explicit model that can account for both climate and socioeconomic changes in projecting future land use changes. In the asynchronously coupled modeling framework, LandPro was run for every five years during the period of 2005-2050 accounting for climate-induced change in crop yield and socioeconomic changes to project the land use pattern by the mid-21st century. Climate data at 0.5˚ was derived from RegCM to drive the crop model DSSAT for each of the five-year periods to simulate crop yields, which was then provided as input data to LandPro. Subsequently, the land use land cover map required to run RegCM was updated every five years using the outputs from the LandPro simulations. Results from the coupled model simulations improve the understanding of climate change impact on future land use and the resulting feedback to regional climate.

Wildfire Selectivity for Land Cover Type: Does Size Matter?

PubMed Central

Barros, Ana M. G.; Pereira, José M. C.

2014-01-01

Previous research has shown that fires burn certain land cover types disproportionally to their abundance. We used quantile regression to study land cover proneness to fire as a function of fire size, under the hypothesis that they are inversely related, for all land cover types. Using five years of fire perimeters, we estimated conditional quantile functions for lower (avoidance) and upper (preference) quantiles of fire selectivity for five land cover types - annual crops, evergreen oak woodlands, eucalypt forests, pine forests and shrublands. The slope of significant regression quantiles describes the rate of change in fire selectivity (avoidance or preference) as a function of fire size. We used Monte-Carlo methods to randomly permutate fires in order to obtain a distribution of fire selectivity due to chance. This distribution was used to test the null hypotheses that 1) mean fire selectivity does not differ from that obtained by randomly relocating observed fire perimeters; 2) that land cover proneness to fire does not vary with fire size. Our results show that land cover proneness to fire is higher for shrublands and pine forests than for annual crops and evergreen oak woodlands. As fire size increases, selectivity decreases for all land cover types tested. Moreover, the rate of change in selectivity with fire size is higher for preference than for avoidance. Comparison between observed and randomized data led us to reject both null hypotheses tested ( = 0.05) and to conclude it is very unlikely the observed values of fire selectivity and change in selectivity with fire size are due to chance. PMID:24454747

Regional Climate Change Impact on Agricultural Land Use in West Africa

NASA Astrophysics Data System (ADS)

Ahmed, K. F.; Wang, G.; You, L.

2014-12-01

Agriculture is a key element of the human-induced land use land cover change (LULCC) that is influenced by climate and can potentially influence regional climate. Temperature and precipitation directly impact the crop yield (by controlling photosynthesis, respiration and other physiological processes) that then affects agricultural land use pattern. In feedback, the resulting changes in land use and land cover play an important role to determine the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. The assessment of future agricultural land use is, therefore, of great importance in climate change study. In this study, we develop a prototype land use projection model and, using this model, project the changes to land use pattern and future land cover map accounting for climate-induced yield changes for major crops in West Africa. Among the inputs to the land use projection model are crop yield changes simulated by the crop model DSSAT, driven with the climate forcing data from the regional climate model RegCM4.3.4-CLM4.5, which features a projected decrease of future mean crop yield and increase of inter-annual variability. Another input to the land use projection model is the projected changes of food demand in the future. In a so-called "dumb-farmer scenario" without any adaptation, the combined effect of decrease in crop yield and increase in food demand will lead to a significant increase in agricultural land use in future years accompanied by a decrease in forest and grass area. Human adaptation through land use optimization in an effort to minimize agricultural expansion is found to have little impact on the overall areas of agricultural land use. While the choice of the General Circulation Model (GCM) to derive initial and boundary conditions for the regional climate model can be a source of uncertainty in projecting the future LULCC, results from sensitivity experiments indicate that the changes

Next generation of global land cover characterization, mapping, and monitoring

USGS Publications Warehouse

Giri, Chandra; Pengra, Bruce; Long, J.; Loveland, Thomas R.

2013-01-01

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

Biomass Burning, Land-Cover Change, and the Hydrological Cycle in Northern Sub-Saharan Africa

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Ellison, Luke T.; Willmot, K. Elena; Matsui, Toshihisa; Dezfuli, Amin K.; Gatebe, Charles K.; Wang, Jun; Wilcox, Eric M.; Lee, Jejung; Adegoke, Jimmy;