Sample records for agricultural land cover

  1. 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.

  2. National land-cover data and national agricultural census estimates of agricultural land use in the northeastern United States

    USDA-ARS?s Scientific Manuscript database

    The landscape of the northeastern United States is diverse and patchy, a complex mixture of forest, agriculture, and developed lands. Many urgent social and environmental issues require spatially-referenced information on land use, a need filled by the National Land-Cover Data (NLCD). The accuracy o...

  3. 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.

  4. Livelihood profiling and sensitivity of livelihood strategies to land cover dynamics and agricultural variability

    NASA Astrophysics Data System (ADS)

    Berchoux, Tristan; Hutton, Craig; Watmough, Gary; Amoako Johnson, Fiifi; Atkinson, Peter

    2017-04-01

    With population increase and the urbanisation of rural areas, land scarcity is one of the biggest challenges now faced by communities in agrarian societies. At the household level, loss of land can be due to physical processes such as erosion, to social constraints such as inheritance, or to financial constraints such as loan reimbursement or the need of cash. For rural households, whose livelihoods are mainly based on agriculture, a decrease in the area of land cultivated can have significant consequences on their livelihood strategies, thus on their livelihood outcomes. However, it is still unclear how changes in cultivated area and agricultural productivity influence households' livelihood systems, including community capitals and households' livelihood strategies. This study aims to answer this gap by combining together earth observation from space, national census and participatory qualitative data into a community-wise analysis of the relationships between land cover dynamics, variability in agricultural production and livelihood activities. Its overarching aim is to investigate how land cover dynamics relates to changes in livelihood strategies and livelihood capitals. The study demonstrates that a change in land cover influences livelihood activities differently depending on the community capitals that households have access to. One significant aspect of integrating land dynamics with livelihood activities is its capacity to provide insights on the relationships between climate, agriculture, livelihood dynamics and rural development. More broadly, it gives policymakers new methods to characterise livelihood dynamics, thus to monitor some of the key Sustainable Development Goals: food security (SDG2), employment dynamics (SDG8), inequalities (SDG10) and sustainability of communities (SDG11).

  5. LAND COVER MAPPING IN AN AGRICULTURAL SETTING USING MULTISEASONAL THEMATIC MAPPER DATA

    EPA Science Inventory

    A multiseasonal Landsat Thematic Mapper (TM) data set consisting of five image dates from a single year was used to characterize agricultural and related land cover in the Willamette River Basin (WRB) of western Oregon. Image registration was accomplished using an automated grou...

  6. Inventory of wetlands and agricultural land cover in the upper Sevier River Basin, Utah

    NASA Technical Reports Server (NTRS)

    Jaynes, R. A.; Clark, L. D., Jr.; Landgraf, K. F. (Principal Investigator)

    1981-01-01

    The use of color infrared aerial photography in the mapping of agricultural land use and wetlands in the Sevier River Basin of south central utah is described. The efficiency and cost effectiveness of utilizing LANDSAT multispectral scanner digital data to augment photographic interpretations are discussed. Transparent overlays for 27 quadrangles showing delineations of wetlands and agricultural land cover were produced. A table summarizing the acreage represented by each class on each quadrangle overlay is provided.

  7. Spatially quantifying and attributing 17 years of land cover change to examine post-agricultural forest transition in Hawai`i

    NASA Astrophysics Data System (ADS)

    Lucas, M.; Trauernicht, C.; Carlson, K. M.; Miura, T.; Giambelluca, T. W.; Chen, Q.

    2017-12-01

    The past decades in Hawaii have seen large scale land use change and land cover shifts. However, much these dynamics are only described anecdotally or studied at a single locale, with little information on the extent, rate, or direction of change. This lack of data hinders any effort to assess, plan, and prioritize land management. To improve assessments of statewide vegetation and land cover change, this project developed high resolution, sub-pixel, percent cover maps of forest, grassland and bare earth at annual time steps from 1999 to 2016. Vegetation cover was quantified using archived LANDSAT imagery and a custom remote-sensing algorithm developed in the Google Earth Engine platform. A statistical trend analysis of annual maps of the these three proportional land covers were then used to detect land cover transitions across the archipelago. The aim of this work focused on quantifying the total area of change, annual rates of change and final vegetation cover outcomes statewide. Additionally these findings were attributed to past and current land uses and management history by compiling spatial datasets of development, agriculture, forest restoration sites and burned areas statewide. Results indicated that nearly 10% of the state's land surfaces are suspected to have transitioned between the three cover classes during the study period. Total statewide net change resulted in a gain in forest cover with largest areas of change occurring in unmanaged areas, current and past pastoral land, commercial forestry and abandoned cultivated land. The fastest annual rates of change were forest increases that occurred in restoration areas and commercial forestry. These findings indicate that Hawaii is going through a forest transition, primarily driven by agricultural abandonment with likely feedbacks from invasive species, but also influenced by the establishment of forestry production on former agricultural lands that show potential for native forest restoration. These

  8. Land Use and Land Cover Change Modeling Using Remote Sensing and Soft Computing Approach to Assess Sugarcane Expansion Impacts in Tropical Agriculture

    NASA Astrophysics Data System (ADS)

    Vicente, L. E.; Koga-Vicente, A.; Friedel, M. J.; Victoria, D.; Zullo, J., Jr.; Gomes, D.; Bayma-Silva, G.

    2014-12-01

    Agriculture is related with land-use/cover changes (LUCC) over large areas and, in recent years, increase in demand of ethanol fuel has been influence in expansion of areas occupied with corn and sugar cane, raw material for ethanol production. Nevertheless, there´s a concern regarding the impacts on food security, such as, decrease in areas planted with food crops. Considering that the LUCC is highly dynamic, the use of Remote Sensing is a tool for monitoring changes quickly and precisely in order to provide information for agricultural planning. In this work, Remote Sensing techniques were used to monitor the LUCC occurred in municipalities of São Paulo state- Brazil related with sugarcane crops expansion in order to (i) evaluate and quantify the previous land cover in areas of sugarcane crop expansion, and (ii) provide information to elaborate a future land cover scenario based on Self Organizing Map (SOM) approach. The land cover classification procedure was based on Landsat 5 TM images, obtained from the Global Land Survey. The Landsat images were then segmented into homogeneous objects, with represent areas on the ground with similar spatial and spectral characteristics. These objects are related to the distinct land cover types that occur in each municipality. The segmentation procedure resulted in polygons over the three time periods along twenty years (1990-2010). The land cover for each object was visually identified, based on its shape, texture and spectral characteristics. Land cover types considered were: sugarcane plantations, pasture lands, natural cover, forest plantation, permanent crop, short cycle crop, water bodies and urban areas. SOM technique was used to estimate the values for the future land cover scenarios for the selected municipalities, using the information of land change provided by the remote sensing and data from official sources.

  9. Global Tree Cover and Biomass Carbon on Agricultural Land: The contribution of agroforestry to global and national carbon budgets.

    PubMed

    Zomer, Robert J; Neufeldt, Henry; Xu, Jianchu; Ahrends, Antje; Bossio, Deborah; Trabucco, Antonio; van Noordwijk, Meine; Wang, Mingcheng

    2016-07-20

    Agroforestry systems and tree cover on agricultural land make an important contribution to climate change mitigation, but are not systematically accounted for in either global carbon budgets or national carbon accounting. This paper assesses the role of trees on agricultural land and their significance for carbon sequestration at a global level, along with recent change trends. Remote sensing data show that in 2010, 43% of all agricultural land globally had at least 10% tree cover and that this has increased by 2% over the previous ten years. Combining geographically and bioclimatically stratified Intergovernmental Panel on Climate Change (IPCC) Tier 1 default estimates of carbon storage with this tree cover analysis, we estimated 45.3 PgC on agricultural land globally, with trees contributing >75%. Between 2000 and 2010 tree cover increased by 3.7%, resulting in an increase of >2 PgC (or 4.6%) of biomass carbon. On average, globally, biomass carbon increased from 20.4 to 21.4 tC ha(-1). Regional and country-level variation in stocks and trends were mapped and tabulated globally, and for all countries. Brazil, Indonesia, China and India had the largest increases in biomass carbon stored on agricultural land, while Argentina, Myanmar, and Sierra Leone had the largest decreases.

  10. Global Tree Cover and Biomass Carbon on Agricultural Land: The contribution of agroforestry to global and national carbon budgets

    PubMed Central

    Zomer, Robert J.; Neufeldt, Henry; Xu, Jianchu; Ahrends, Antje; Bossio, Deborah; Trabucco, Antonio; van Noordwijk, Meine; Wang, Mingcheng

    2016-01-01

    Agroforestry systems and tree cover on agricultural land make an important contribution to climate change mitigation, but are not systematically accounted for in either global carbon budgets or national carbon accounting. This paper assesses the role of trees on agricultural land and their significance for carbon sequestration at a global level, along with recent change trends. Remote sensing data show that in 2010, 43% of all agricultural land globally had at least 10% tree cover and that this has increased by 2% over the previous ten years. Combining geographically and bioclimatically stratified Intergovernmental Panel on Climate Change (IPCC) Tier 1 default estimates of carbon storage with this tree cover analysis, we estimated 45.3 PgC on agricultural land globally, with trees contributing >75%. Between 2000 and 2010 tree cover increased by 3.7%, resulting in an increase of >2 PgC (or 4.6%) of biomass carbon. On average, globally, biomass carbon increased from 20.4 to 21.4 tC ha−1. Regional and country-level variation in stocks and trends were mapped and tabulated globally, and for all countries. Brazil, Indonesia, China and India had the largest increases in biomass carbon stored on agricultural land, while Argentina, Myanmar, and Sierra Leone had the largest decreases. PMID:27435095

  11. Land cover mapping of North and Central America—Global Land Cover 2000

    USGS Publications Warehouse

    Latifovic, Rasim; Zhu, Zhi-Liang

    2004-01-01

    The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

  12. Agricultural land cover mapping in the context of a geographically referenced digital information system. [Carroll, Macon, and Gentry Counties, Missouri

    NASA Technical Reports Server (NTRS)

    Stoner, E. R.

    1982-01-01

    The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices and background reflectance characteristics. Multiple dates of LANDSAT MSS digital were analyzed for three study areas in northern Missouri to produce cover types for major agricultural land cover classes. Digital data bases were then developed by adding ancillary data such as digitized soil and transportation network information to the LANDSAT-derived cover type map. Procedures were developed to manipulate the data base parameters to extract information applicable to user requirements. An agricultural information system combining such data can be used to determine the productive capacity of land to grow crops, fertilizer needs, chemical weed control rates, irrigation suitability, and trafficability of soil for planting.

  13. 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. 

  14. 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.

  15. 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.

  16. Clustering of Multi-Temporal Fully Polarimetric L-Band SAR Data for Agricultural Land Cover Mapping

    NASA Astrophysics Data System (ADS)

    Tamiminia, H.; Homayouni, S.; Safari, A.

    2015-12-01

    Recently, the unique capabilities of Polarimetric Synthetic Aperture Radar (PolSAR) sensors make them an important and efficient tool for natural resources and environmental applications, such as land cover and crop classification. The aim of this paper is to classify multi-temporal full polarimetric SAR data using kernel-based fuzzy C-means clustering method, over an agricultural region. This method starts with transforming input data into the higher dimensional space using kernel functions and then clustering them in the feature space. Feature space, due to its inherent properties, has the ability to take in account the nonlinear and complex nature of polarimetric data. Several SAR polarimetric features extracted using target decomposition algorithms. Features from Cloude-Pottier, Freeman-Durden and Yamaguchi algorithms used as inputs for the clustering. This method was applied to multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Canada, during June and July in 2012. The results demonstrate the efficiency of this approach with respect to the classical methods. In addition, using multi-temporal data in the clustering process helped to investigate the phenological cycle of plants and significantly improved the performance of agricultural land cover mapping.

  17. Combining global land cover datasets to quantify agricultural expansion into forests in Latin America: Limitations and challenges

    PubMed Central

    Persson, U. Martin

    2017-01-01

    While we know that deforestation in the tropics is increasingly driven by commercial agriculture, most tropical countries still lack recent and spatially-explicit assessments of the relative importance of pasture and cropland expansion in causing forest loss. Here we present a spatially explicit quantification of the extent to which cultivated land and grassland expanded at the expense of forests across Latin America in 2001–2011, by combining two “state-of-the-art” global datasets (Global Forest Change forest loss and GlobeLand30-2010 land cover). We further evaluate some of the limitations and challenges in doing this. We find that this approach does capture some of the major patterns of land cover following deforestation, with GlobeLand30-2010’s Grassland class (which we interpret as pasture) being the most common land cover replacing forests across Latin America. However, our analysis also reveals some major limitations to combining these land cover datasets for quantifying pasture and cropland expansion into forest. First, a simple one-to-one translation between GlobeLand30-2010’s Cultivated land and Grassland classes into cropland and pasture respectively, should not be made without caution, as GlobeLand30-2010 defines its Cultivated land to include some pastures. Comparisons with the TerraClass dataset over the Brazilian Amazon and with previous literature indicates that Cultivated land in GlobeLand30-2010 includes notable amounts of pasture and other vegetation (e.g. in Paraguay and the Brazilian Amazon). This further suggests that the approach taken here generally leads to an underestimation (of up to ~60%) of the role of pasture in replacing forest. Second, a large share (~33%) of the Global Forest Change forest loss is found to still be forest according to GlobeLand30-2010 and our analysis suggests that the accuracy of the combined datasets, especially for areas with heterogeneous land cover and/or small-scale forest loss, is still too poor for

  18. Combining global land cover datasets to quantify agricultural expansion into forests in Latin America: Limitations and challenges.

    PubMed

    Pendrill, Florence; Persson, U Martin

    2017-01-01

    While we know that deforestation in the tropics is increasingly driven by commercial agriculture, most tropical countries still lack recent and spatially-explicit assessments of the relative importance of pasture and cropland expansion in causing forest loss. Here we present a spatially explicit quantification of the extent to which cultivated land and grassland expanded at the expense of forests across Latin America in 2001-2011, by combining two "state-of-the-art" global datasets (Global Forest Change forest loss and GlobeLand30-2010 land cover). We further evaluate some of the limitations and challenges in doing this. We find that this approach does capture some of the major patterns of land cover following deforestation, with GlobeLand30-2010's Grassland class (which we interpret as pasture) being the most common land cover replacing forests across Latin America. However, our analysis also reveals some major limitations to combining these land cover datasets for quantifying pasture and cropland expansion into forest. First, a simple one-to-one translation between GlobeLand30-2010's Cultivated land and Grassland classes into cropland and pasture respectively, should not be made without caution, as GlobeLand30-2010 defines its Cultivated land to include some pastures. Comparisons with the TerraClass dataset over the Brazilian Amazon and with previous literature indicates that Cultivated land in GlobeLand30-2010 includes notable amounts of pasture and other vegetation (e.g. in Paraguay and the Brazilian Amazon). This further suggests that the approach taken here generally leads to an underestimation (of up to ~60%) of the role of pasture in replacing forest. Second, a large share (~33%) of the Global Forest Change forest loss is found to still be forest according to GlobeLand30-2010 and our analysis suggests that the accuracy of the combined datasets, especially for areas with heterogeneous land cover and/or small-scale forest loss, is still too poor for deriving

  19. 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

  20. Estimation of Agricultural Pesticide Use in Drainage Basins Using Land Cover Maps and County Pesticide Data. National Water-Quality Assessment Program

    DTIC Science & Technology

    2005-01-01

    National Water-Quality Assessment Program NCFAP National Center for Food and Agricultural Policy NLCD 92 National Land Cover Data 1992 NLCDe 92 enhanced...cropland acreage and state agricultural pesticide use in the early to mid-1990s reported by the National Center for Food and Agricultural Policy (NCFAP...Department of Agriculture’s National Agricultural Statistics Service (NASS). [17]. The National Center for Food and Agricultural Policy (NCFAP) is a

  1. An initial analysis of LANDSAT 4 Thematic Mapper data for the classification of agricultural, forested wetland, and urban land covers

    NASA Technical Reports Server (NTRS)

    Quattrochi, D. A.; Anderson, J. E.; Brannon, D. P.; Hill, C. L.

    1982-01-01

    An initial analysis of LANDSAT 4 thematic mapper (TM) data for the delineation and classification of agricultural, forested wetland, and urban land covers was conducted. A study area in Poinsett County, Arkansas was used to evaluate a classification of agricultural lands derived from multitemporal LANDSAT multispectral scanner (MSS) data in comparison with a classification of TM data for the same area. Data over Reelfoot Lake in northwestern Tennessee were utilized to evaluate the TM for delineating forested wetland species. A classification of the study area was assessed for accuracy in discriminating five forested wetland categories. Finally, the TM data were used to identify urban features within a small city. A computer generated classification of Union City, Tennessee was analyzed for accuracy in delineating urban land covers. An evaluation of digitally enhanced TM data using principal components analysis to facilitate photointerpretation of urban features was also performed.

  2. 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.

  3. 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.

  4. Carbon dioxide emissions from forestry and peat land using land-use/land-cover changes in North Sumatra, Indonesia

    NASA Astrophysics Data System (ADS)

    Basyuni, M.; Sulistyono, N.; Slamet, B.; Wati, R.

    2018-03-01

    Forestry and peat land including land-based is one of the critical sectors in the inventory of CO2 emissions and mitigation efforts of climate change. The present study analyzed the land-use and land-cover changes between 2006 and 2012 in North Sumatra, Indonesia with emphasis to CO2 emissions. The land-use/land-cover consists of twenty-one classes. Redd Abacus software version 1.1.7 was used to measure carbon emission source as well as the predicted 2carbon dioxide emissions from 2006-2024. Results showed that historical emission (2006-2012) in this province, significant increases in the intensive land use namely dry land agriculture (109.65%), paddy field (16.23%) and estate plantation (15.11%). On the other hand, land-cover for forest decreased significantly: secondary dry land forest (7.60%), secondary mangrove forest (9.03%), secondary swamp forest (33.98%), and the largest one in the mixed dry land agriculture (79.96%). The results indicated that North Sumatra province is still a CO2 emitter, and the most important driver of emissions mostly derived from agricultural lands that contributed 2carbon dioxide emissions by 48.8%, changing from forest areas into degraded lands (classified as barren land and shrub) shared 30.6% and estate plantation of 22.4%. Mitigation actions to reduce carbon emissions was proposed such as strengthening the forest land, rehabilitation of degraded area, development and plantation forest, forest protection and forest fire control, and reforestation and conservation activity. These mitigation actions have been simulated to reduce 15% for forestry and 18% for peat land, respectively. This data is likely to contribute to the low emission development in North Sumatra.

  5. Recent land cover history and nutrient retention in riparian wetlands

    USGS Publications Warehouse

    Hogan, D.M.; Walbridge, M.R.

    2009-01-01

    Wetland ecosystems are profoundly affected by altered nutrient and sediment loads received from anthropogenic activity in their surrounding watersheds. Our objective was to compare a gradient of agricultural and urban land cover history during the period from 1949 to 1997, with plant and soil nutrient concentrations in, and sediment deposition to, riparian wetlands in a rapidly urbanizing landscape. We observed that recent agricultural land cover was associated with increases in Nitrogen (N) and Phosphorus (P) concentrations in a native wetland plant species. Conversely, recent urban land cover appeared to alter receiving wetland environmental conditions by increasing the relative availability of P versus N, as reflected in an invasive, but not a native, plant species. In addition, increases in surface soil Fe content suggests recent inputs of terrestrial sediments associated specifically with increasing urban land cover. The observed correlation between urban land cover and riparian wetland plant tissue and surface soil nutrient concentrations and sediment deposition, suggest that urbanization specifically enhances the suitability of riparian wetland habitats for the invasive species Japanese stiltgrass [Microstegium vimenium (Trinius) A. Camus]. ?? 2009 Springer Science+Business Media, LLC.

  6. 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.

  7. Global Impacts of Long-Term Land Cover Changes Within China's Densely Populated Rural Regions

    NASA Astrophysics Data System (ADS)

    Ellis, E. C.

    2006-12-01

    Long-term changes in land cover are usually investigated in terms of large-scale change processes such as urban expansion, deforestation and land conversion to agriculture. Yet China's densely populated agricultural regions, which cover more than 2 million square kilometers of Monsoon Asia, have been transformed profoundly over the past fifty years by fine-scale changes in land cover caused by unprecedented changes in population, technology and social conditions. Using a regional sampling and upscaling design coupled with high-resolution landscape change measurements at five field sites, we investigated long-term changes in land cover and ecological processes, circa 1945 to 2002, within and across China's densely populated agricultural regions. As expected, the construction of buildings and roads increased impervious surface area over time, but the total net increase was surprising, being similar in magnitude to the total current extent of China's cities. Agricultural land area declined over the same period, while tree cover increased, by about 10%, driven by tree planting and regrowth around new buildings, the introduction of perennial agriculture, improved forestry, and declines in annual crop cultivation. Though changes in impervious surface areas were closely related to changes in population density, long-term changes in agricultural land and tree cover were unrelated to populated density and required explanation by more complex models with strong regional and biophysical components. Moreover, most of these changes occurred primarily at fine spatial scales (< 30 m), under the threshold for conventional global and regional land cover change measurements. Given that these changes in built structures and vegetation cover have the potential to contribute substantially to regional and global changes in biogeochemistry, hydrology, and land-atmosphere interactions, future investigations of these changes and their impacts across Monsoon Asia would benefit from models

  8. An Initial Analysis of LANDSAT-4 Thematic Mapper Data for the Discrimination of Agricultural, Forested Wetland, and Urban Land Covers

    NASA Technical Reports Server (NTRS)

    Quattrochi, D. A.

    1984-01-01

    An initial analysis of LANDSAT 4 Thematic Mapper (TM) data for the discrimination of agricultural, forested wetland, and urban land covers is conducted using a scene of data collected over Arkansas and Tennessee. A classification of agricultural lands derived from multitemporal LANDSAT Multispectral Scanner (MSS) data is compared with a classification of TM data for the same area. Results from this comparative analysis show that the multitemporal MSS classification produced an overall accuracy of 80.91% while the TM classification yields an overall classification accuracy of 97.06% correct.

  9. Image-based change estimation for land cover and land use monitoring

    Treesearch

    Jeremy Webb; C. Kenneth Brewer; Nicholas Daniels; Chris Maderia; Randy Hamilton; Mark Finco; Kevin A. Megown; Andrew J. Lister

    2012-01-01

    The Image-based Change Estimation (ICE) project resulted from the need to provide estimates and information for land cover and land use change over large areas. The procedure uses Forest Inventory and Analysis (FIA) plot locations interpreted using two different dates of imagery from the National Agriculture Imagery Program (NAIP). In order to determine a suitable...

  10. 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.

  11. Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watershed

    NASA Astrophysics Data System (ADS)

    Saran, Sameer; Sterk, Geert; Kumar, Suresh

    2009-10-01

    Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into HRU's requires good-quality spatial data on land use/land cover. This paper presents different approaches to attain an optimal land use/land cover map based on remote sensing imagery for a Himalayan watershed in northern India. First digital classifications using maximum likelihood classifier (MLC) and a decision tree classifier were applied. The results obtained from the decision tree were better and even improved after post classification sorting. But the obtained land use/land cover map was not sufficient for the delineation of HRUs, since the agricultural land use/land cover class did not discriminate between the two major crops in the area i.e. paddy and maize. Subsequently the digital classification on fused data (ASAR and ASTER) were attempted to map land use/land cover classes with emphasis to delineate the paddy and maize crops but the supervised classification over fused datasets did not provide the desired accuracy and proper delineation of paddy and maize crops. Eventually, we adopted a visual classification approach on fused data. This second step with detailed classification system resulted into better classification accuracy within the 'agricultural land' class which will be further combined with topography and soil type to derive HRU's for physically-based hydrological modeling.

  12. 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

  13. Impacts of Myanmar's Democratic Transition on its Land Cover Dynamics.

    NASA Astrophysics Data System (ADS)

    Biswas, S.

    2016-12-01

    Recently Myanmar transitioned from a closed economy, military government to market based economy and democracy. The impacts of the political and economic transition on its land cover can be described by characterizing the land cover dynamics during the transition period. Preliminary stratified sampling of forest conversions revealed that most changes from forest to non-forest are due to establishment of rubber plantations. Agricultural concessions are granted by the government to develop the agriculture sector and rubber is the most common plantation crop in Southern Myanmar. This study establishes a method to map and quantify the extent and age of rubber plantations in Thaton district of Myanmar using satellite remote sensing, GIS and ground data. The resultant rubber maps can be used to inform policy on land use planning, agriculture, forest and sustainable development.

  14. Land-cover change research at the U.S. Geological Survey-assessing our nation's dynamic land surface

    USGS Publications Warehouse

    Wilson, Tamara S.

    2011-01-01

    The U.S. Geological Survey (USGS) recently completed an unprecedented, 27-year assessment of land-use and land-cover change for the conterminous United States. For the period 1973 to 2000, scientists generated estimates of change in major types of land use and land cover, such as development, mining, agriculture, forest, grasslands, and wetlands. To help provide the insight that our Nation will need to make land-use decisions in coming decades, the historical trends data is now being used by the USGS to help model potential future land use/land cover under different scenarios, including climate, environmental, economic, population, public policy, and technological change.

  15. 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.

  16. Modeled historical land use and land cover for the conterminous United States

    USGS Publications Warehouse

    Sohl, Terry L.; Reker, Ryan R.; Bouchard, Michelle A.; Sayler, Kristi L.; Dornbierer, Jordan; Wika, Steve; Quenzer, Robert; Friesz, Aaron M.

    2016-01-01

    The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.

  17. Using the Landsat Archive to Estimate and Map Changes in Agriculture, Forests, and other Land Cover Types in East Africa

    NASA Astrophysics Data System (ADS)

    Healey, S. P.; Oduor, P.; Cohen, W. B.; Yang, Z.; Ouko, E.; Gorelick, N.; Wilson, S.

    2017-12-01

    Every country's land is distributed among different cover types, such as: agriculture; forests; rangeland; urban areas; and barren lands. Changes in the distribution of these classes can inform us about many things, including: population pressure; effectiveness of preservation efforts; desertification; and stability of the food supply. Good assessment of these changes can also support wise planning, use, and preservation of natural resources. We are using the Landsat archive in two ways to provide needed information about land cover change since the year 2000 in seven East African countries (Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Uganda, and Zambia). First, we are working with local experts to interpret historical land cover change from historical imagery at a probabilistic sample of 2000 locations in each country. This will provide a statistical estimate of land cover change since 2000. Second, we will use the same data to calibrate and validate annual land cover maps for each country. Because spatial context can be critical to development planning through the identification of hot spots, these maps will be a useful complement to the statistical, country-level estimates of change. The Landsat platform is an ideal tool for mapping land cover change because it combines a mix of appropriate spatial and spectral resolution with unparalleled length of service (Landsat 1 launched in 1972). Pilot tests have shown that time series analysis accessing the entire Landsat archive (i.e., many images per year) improves classification accuracy and stability. It is anticipated that this project will meet the civil needs of both governmental and non-governmental users across a range of disciplines.

  18. The global potential of bioenergy on abandoned agriculture lands.

    PubMed

    Campbell, J Elliott; Lobell, David B; Genova, Robert C; Field, Christopher B

    2008-08-01

    Converting forest lands into bioenergy agriculture could accelerate climate change by emitting carbon stored in forests, while converting food agriculture lands into bioenergy agriculture could threaten food security. Both problems are potentially avoided by using abandoned agriculture lands for bioenergy agriculture. Here we show the global potential for bioenergy on abandoned agriculture lands to be less than 8% of current primary energy demand, based on historical land use data, satellite-derived land cover data, and global ecosystem modeling. The estimated global area of abandoned agriculture is 385-472 million hectares, or 66-110% of the areas reported in previous preliminary assessments. The area-weighted mean production of above-ground biomass is 4.3 tons ha(-1) y(-1), in contrast to estimates of up to 10 tons ha(-1) y(-1) in previous assessments. The energy content of potential biomass grown on 100% of abandoned agriculture lands is less than 10% of primary energy demand for most nations in North America, Europe, and Asia, but it represents many times the energy demand in some African nations where grasslands are relatively productive and current energy demand is low.

  19. 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.

  20. 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.

  1. 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.

  2. The managed clearing: An overlooked land-cover type in urbanizing regions?

    PubMed Central

    Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K.

    2018-01-01

    Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and

  3. The managed clearing: An overlooked land-cover type in urbanizing regions?

    PubMed

    Singh, Kunwar K; Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K

    2018-01-01

    Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type-semi-natural, vegetated land surfaces with varying degrees of management practices-for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area- 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and

  4. Long-term impacts of land cover changes on stream channel loss.

    PubMed

    Julian, Jason P; Wilgruber, Nicholas A; de Beurs, Kirsten M; Mayer, Paul M; Jawarneh, Rana N

    2015-12-15

    Land cover change and stream channel loss are two related global environmental changes that are expanding and intensifying. Here, we examine how different types and transitions of land cover change impact stream channel loss across a large urbanizing watershed. We present historical land cover in the 666-km(2) Lake Thunderbird watershed in central Oklahoma (USA) over a 137 year period and coinciding stream channel length changes for the most recent 70 years of this period. Combining these two datasets allowed us to assess the interaction of land cover changes with stream channel loss. Over this period, the upper third of the watershed shifted from predominantly native grassland to an agricultural landscape, followed by widespread urbanization. The lower two-thirds of the watershed changed from a forested landscape to a mosaic of agriculture, urban, forest, and open water. Most channel length lost in the watershed over time was replaced by agriculture. Urban development gradually increased channel loss and disconnection from 1942 to 2011, particularly in the headwaters. Intensities of channel loss for both agriculture and urban increased over time. The two longest connected segments of channel loss came from the creation of two large impoundments, resulting in 46 km and 25 km of lost stream channel, respectively. Overall, the results from this study demonstrate that multiple and various land-use changes over long time periods can lead to rapid losses of large channel lengths as well as gradual (but increasing) losses of small channel lengths across all stream sizes. When these stream channel losses are taken into account, the environmental impacts of anthropogenic land-use change are compounded. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. 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

  6. 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.

  7. Land Cover as a Framework For Assessing the Risk of Water Pollution

    Treesearch

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

    2000-01-01

    A survey of numerous field studies shows that nitrogen and phosphorous export coefficients are significantly different across forest, agriculture, and urban land-cover types. We used simulations to estimate the land-cover composition at which there was a significant risk of nutrient loads representative of watersheds without forest cover. The results suggest that at...

  8. Mekong Land Cover Dasboard: Regional Land Cover Mointoring Systems

    NASA Astrophysics Data System (ADS)

    Saah, D. S.; Towashiraporn, P.; Aekakkararungroj, A.; Phongsapan, K.; Triepke, J.; Maus, P.; Tenneson, K.; Cutter, P. G.; Ganz, D.; Anderson, E.

    2016-12-01

    SERVIR-Mekong, a USAID-NASA partnership, helps decision makers in the Lower Mekong Region utilize GIS and Remote Sensing information to inform climate related activities. In 2015, SERVIR-Mekong conducted a geospatial needs assessment for the Lower Mekong countries which included individual country consultations. The team found that many countries were dependent on land cover and land use maps for land resource planning, quantifying ecosystem services, including resilience to climate change, biodiversity conservation, and other critical social issues. Many of the Lower Mekong countries have developed national scale land cover maps derived in part from remote sensing products and geospatial technologies. However, updates are infrequent and classification systems do not always meet the needs of key user groups. In addition, data products stop at political boundaries and are often not accessible making the data unusable across country boundaries and with resource management partners. Many of these countries rely on global land cover products to fill the gaps of their national efforts, compromising consistency between data and policies. These gaps in national efforts can be filled by a flexible regional land cover monitoring system that is co-developed by regional partners with the specific intention of meeting national transboundary needs, for example including consistent forest definitions in transboundary watersheds. Based on these facts, key regional stakeholders identified a need for a land cover monitoring system that will produce frequent, high quality land cover maps using a consistent regional classification scheme that is compatible with national country needs. SERVIR-Mekong is currently developing a solution that leverages recent developments in remote sensing science and technology, such as Google Earth Engine (GEE), and working together with production partners to develop a system that will use a common set of input data sources to generate high

  9. Watershed Analysis of Nitrate Transport as a Result of Agricultural Inputs for Varying Land Use/Land Cover and Soil Type

    NASA Astrophysics Data System (ADS)

    Scott, M. E.; Sykes, J. F.

    2006-12-01

    The Grand River Watershed is one of the largest watersheds in southwestern Ontario with an area of approximately 7000 square kilometers. Ninety percent of the watershed is classified as rural, and 80 percent of the watershed population relies on groundwater as their source of drinking water. Management of the watershed requires the determination of the effect of agricultural practices on long-term groundwater quality and to identify locations within the watershed that are at a higher risk of contamination. The study focuses on the transport of nitrate through the root zone as a result of agricultural inputs with attenuation due to biodegradation. The driving force for transport is spatially and temporally varying groundwater recharge that is a function of land use/land cover, soil and meteorological inputs that yields 47,229 unique soil columns within the watershed. Fertilizer sources are determined from Statistics Canada's Agricultural Census and include livestock manure and a popular commercial fertilizer, urea. Accounting for different application rates yields 60,066 unique land parcels of which 22,809 are classified as croplands where manure and inorganic fertilizes are directly applied. The transport for the croplands is simulated over a 14-year period to investigate the impact of seasonal applications of nitrate fertilizers on the concentration leaching from the root zone to the water table. Based on land use/land cover maps, ArcView GIS is used to define the location of fertilizer applications within the watershed and to spatially visualize data and analyze results. The large quantity of input data is stored and managed using MS-Access and a relational database management system. Nitrogen transformations and ammonium and nitrate uptake by plants and transport through the soil column are simulated on a daily basis using Visual Basic for Applications (VBA) within MS-Access modules. Nitrogen transformations within the soil column were simplified using

  10. 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.

  11. 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.

  12. 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.

  13. The Potential Radiative Forcing of Global Land Use and Land Cover Change Activities

    NASA Astrophysics Data System (ADS)

    Ward, D. S.; Mahowald, N. M.; Kloster, S.

    2014-12-01

    Given the expected increase in pressure on land resources over the next century, there is a need to understand the total impacts of activities associated with land use and land cover change (LULCC). Here we quantify these impacts using the radiative forcing metric, including forcings from changes in long-lived greenhouse gases, tropospheric ozone, aerosol effects, and land surface albedo. We estimate radiative forcings from the different agents for historical LULCC and for six future projections using simulations from the National Center for Atmospheric Research Community Land Model and Community Atmosphere Models and additional offline analyses. When all forcing agents are considered together we show that 45% (+30%, -20%) of the present-day (2010) anthropogenic radiative forcing can be attributed to LULCC. Changes in the emission of non-CO2 greenhouse gases and aerosols from LULCC enhance the total LULCC radiative forcing by a factor of 2 to 3 with respect to the forcing from CO2 alone. In contrast, the non-CO2 forcings from fossil fuel burning are roughly neutral, due largely to the negative (cooling) impact of aerosols from these sources. We partition the global LULCC radiative forcing into three major sources: direct modification of land cover (e.g. deforestation), agricultural activities, and fire regime changes. Contributions from deforestation and agriculture are roughly equal in the present day, while changes to wildfire activity impose a small negative forcing globally. In 2100, deforestation activities comprise the majority of the LULCC radiative forcing for all projections except one (Representative Concentration Pathway (RCP) 4.5). This suggests that realistic scenarios of future forest area change are essential for projecting the contribution of LULCC to climate change. However, the commonly used RCP land cover change projections all include decreases in global deforestation rates over the next 85 years. To place an upper bound on the potential

  14. Vegetation Analysis and Land Use Land Cover Classification of Forest in Uttara Kannada District India Through Geo-Informatics Approach

    NASA Astrophysics Data System (ADS)

    Koppad, A. G.; Janagoudar, B. S.

    2017-05-01

    The study was conducted in Uttara Kannada districts during the year 2012-2014. The study area lies between 13.92° N to 15.52° N latitude and 74.08° E to 75.09° E longitude with an area of 10,215 km2. The Indian satellite IRS P6 LISS-III imageries were used to classify the land use land cover classes with ground truth data collected with GPS through supervised classification in ERDAS software. The land use and land cover classes identified were dense forest, horticulture plantation, sparse forest, forest plantation, open land and agriculture land. The dense forest covered an area of 63.32 % (6468.70 sq km) followed by agriculture 12.88 % (1315.31 sq. km), sparse forest 10.59 % (1081.37 sq. km), open land 6.09 % (622.37 sq. km), horticulture plantation and least was forest plantation (1.07 %). Settlement, stony land and water body together cover about 4.26 percent of the area. The study indicated that the aspect and altitude influenced the forest types and vegetation pattern. The NDVI map was prepared which indicated that healthy vegetation is represented by high NDVI values between 0.1 and 1. The non-vegetated features such as water bodies, settlement, and stony land indicated less than 0.1 values. The decrease in forest area in some places was due to anthropogenic activities. The thematic map of land use land cover classes was prepared using Arc GIS Software.

  15. Land use/land cover change and implications for ecosystems services in the Likangala River Catchment, Malawi

    NASA Astrophysics Data System (ADS)

    Pullanikkatil, Deepa; Palamuleni, Lobina G.; Ruhiiga, Tabukeli M.

    2016-06-01

    Likangala River catchment in Zomba District of Southern Malawi is important for water resources, agriculture and provides many ecosystem services. Provisioning ecosystem services accrued by the populations within the catchment include water, fish, medicinal plants and timber among others. In spite of its importance, the River catchment is under threat from anthropogenic activities and land use change. This paper studies land uses and land cover change in the catchment and how the changes have impacted on the ecosystem services. Landsat 5 and 8 images (1984, 1994, 2005 and 2013) were used to map land cover change and subsequent inventorying of provisioning ecosystem services. Participatory Geographic Information Systems and Focus group discussions were conducted to identify provisioning ecosystems services that communities benefit from the catchment and indicate these on the map. Post classification comparisons indicate that since 1984, there has been a decline in woodlands from 135.3 km2 in 1984 to 15.5 km2 in 2013 while urban areas increased from 9.8 km2 to 23.8 km2 in 2013. Communities indicated that provisioning ecosystems services such as forest products, wild animals and fruits and medicinal plants have been declining over the years. In addition, evidence of catchment degradation through waste disposal, illegal sand mining, deforestation and farming on marginal lands were observed. Population growth, urbanization and demand for agricultural lands have contributed to this land use and land cover change. The study suggests addressing catchment degradation through integrated method where an ecosystems approach is used. Thus, both the proximate and underlying driving factors of land-use and land cover change need to be addressed in order to sustainably reduce ecosystem degradation.

  16. 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.

  17. 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.

  18. 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.

  19. Using land-cover change as dynamic variables in surface-water and water-quality models

    USGS Publications Warehouse

    Karstensen, Krista A.; Warner, Kelly L.; Kuhn, Anne

    2010-01-01

    Land-cover data are typically used in hydrologic modeling to establish or describe land surface dynamics. This project is designed to demonstrate the use of land-cover change data in surface-water and water-quality models by incorporating land-cover as a variable condition. The project incorporates three different scenarios that vary hydrologically and geographically: 1) Agriculture in the Plains, 2) Loon habitat in New England, and 3) Forestry in the Ozarks.

  20. The Impact of Anthropogenic Land Cover Change on Continental River Flow

    NASA Astrophysics Data System (ADS)

    Sterling, S. M.; Ducharne, A.; Polcher, J.

    2006-12-01

    The 2003 World Water Forum highlighted a water crisis that forces over one billion people to drink contaminated water and leaves countless millions with insufficient supplies for agriculture industry. This crisis has spurred numerous recent calls for improved science and understanding of how we alter the water cycle. Here we investigate how this global water crisis is affected by human-caused land cover change. We examine the impact of the present extent of land cover change on the water cycle, in particular on evapotranspiration and streamflow, through numerical experiments with the ORCHIDEE land surface model. Using Geographic Information Systems, we characterise land cover change by assembling and modifying existing global-scale maps of land cover change. To see how the land cover change impacts river runoff streamflow, we input the maps into ORCHIDEE and run 50-year "potential vegetation" and "current land cover" simulations of the land surface and energy fluxes, forced by the 50-year NCC atmospheric forcing data set. We present global maps showing the "hotspot" areas with the largest change in ET and streamflow due to anthropogenic land cover change. The results of this project enhance scientific understanding of the nature of human impact on the global water cycle.

  1. Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques

    NASA Astrophysics Data System (ADS)

    Kumar, Lalit; Ghosh, Manoj Kumer

    2012-01-01

    Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.

  2. Land cover mapping in Latvia using hyperspectral airborne and simulated Sentinel-2 data

    NASA Astrophysics Data System (ADS)

    Jakovels, Dainis; Filipovs, Jevgenijs; Brauns, Agris; Taskovs, Juris; Erins, Gatis

    2016-08-01

    Land cover mapping in Latvia is performed as part of the Corine Land Cover (CLC) initiative every six years. The advantage of CLC is the creation of a standardized nomenclature and mapping protocol comparable across all European countries, thereby making it a valuable information source at the European level. However, low spatial resolution and accuracy, infrequent updates and expensive manual production has limited its use at the national level. As of now, there is no remote sensing based high resolution land cover and land use services designed specifically for Latvia which would account for the country's natural and land use specifics and end-user interests. The European Space Agency launched the Sentinel-2 satellite in 2015 aiming to provide continuity of free high resolution multispectral satellite data thereby presenting an opportunity to develop and adapted land cover and land use algorithm which accounts for national enduser needs. In this study, land cover mapping scheme according to national end-user needs was developed and tested in two pilot territories (Cesis and Burtnieki). Hyperspectral airborne data covering spectral range 400-2500 nm was acquired in summer 2015 using Airborne Surveillance and Environmental Monitoring System (ARSENAL). The gathered data was tested for land cover classification of seven general classes (urban/artificial, bare, forest, shrubland, agricultural/grassland, wetlands, water) and sub-classes specific for Latvia as well as simulation of Sentinel-2 satellite data. Hyperspectral data sets consist of 122 spectral bands in visible to near infrared spectral range (356-950 nm) and 100 bands in short wave infrared (950-2500 nm). Classification of land cover was tested separately for each sensor data and fused cross-sensor data. The best overall classification accuracy 84.2% and satisfactory classification accuracy (more than 80%) for 9 of 13 classes was obtained using Support Vector Machine (SVM) classifier with 109 band

  3. Simulating Changes in Land-Atmosphere Interactions From Expanding Agriculture and Irrigation in India and the Potential Impacts on the Indian Monsoon.

    NASA Astrophysics Data System (ADS)

    Douglas, E. M.; Beltran-Przekurat, A.; Niyogi, D.; Pielke, R. A.

    2006-05-01

    With over 57 million hectares under irrigation in 2002, India has the largest irrigated agricultural area on the planet. Between 80 and 90% of India's water use goes to support irrigated agriculture. The Indian monsoon belt is a home to a large part of the world's population and agriculture is the major land-use activity in the region. Previous results showed that annual vapor fluxes in India have increased by 17% (340 km3) over that which would be expected from a natural (non-agricultural) land cover. Two-thirds of this increase was attributed to irrigated agriculture. The largest increases in vapor and latent heat fluxes occurred where both cropland and irrigated lands were the predominant contemporary land cover classes (particularly northwest and north-central India). Our current study builds upon this work by evaluating possible changes in near-surface energy fluxes and regional atmospheric circulation patterns resulting from the expansion of irrigated agriculture on the Indian sub-continent using a regional atmospheric model RAMS. We investigate three separate land- use scenarios: Scenario 1, with a potential (pre-agricultural) land cover, Scenario 2: the potential land-cover overlain by cropland and Scenario 3: potential land-cover overlain by cropland and irrigated area. We will assess the impact of agricultural land-cover conversion and intensive irrigation on water and energy fluxes between the land and the atmosphere and how these flux changes may affect regional weather patterns. The simulation period covers July 16-20, 2002 which allow us to assess potential impacts of land-cover changes on the onset of the Indian Monsoon.

  4. Assessment of land use and land cover change using spatiotemporal analysis of landscape: case study in south of Tehran.

    PubMed

    Sabr, Abutaleb; Moeinaddini, Mazaher; Azarnivand, Hossein; Guinot, Benjamin

    2016-12-01

    In the recent years, dust storms originating from local abandoned agricultural lands have increasingly impacted Tehran and Karaj air quality. Designing and implementing mitigation plans are necessary to study land use/land cover change (LUCC). Land use/cover classification is particularly relevant in arid areas. This study aimed to map land use/cover by pixel- and object-based image classification methods, analyse landscape fragmentation and determine the effects of two different classification methods on landscape metrics. The same sets of ground data were used for both classification methods. Because accuracy of classification plays a key role in better understanding LUCC, both methods were employed. Land use/cover maps of the southwest area of Tehran city for the years 1985, 2000 and 2014 were obtained from Landsat digital images and classified into three categories: built-up, agricultural and barren lands. The results of our LUCC analysis showed that the most important changes in built-up agricultural land categories were observed in zone B (Shahriar, Robat Karim and Eslamshahr) between 1985 and 2014. The landscape metrics obtained for all categories pictured high landscape fragmentation in the study area. Despite no significant difference was evidenced between the two classification methods, the object-based classification led to an overall higher accuracy than using the pixel-based classification. In particular, the accuracy of the built-up category showed a marked increase. In addition, both methods showed similar trends in fragmentation metrics. One of the reasons is that the object-based classification is able to identify buildings, impervious surface and roads in dense urban areas, which produced more accurate maps.

  5. 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.

  6. 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

  7. 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.

  8. A Decade of Annual National Land Cover Products - the Cropland Data Layer

    NASA Astrophysics Data System (ADS)

    Mueller, R.; Johnson, D. M.; Sandborn, A.; Willis, P.; Ebinger, L.; Yang, Z.; Seffrin, R.; Boryan, C. G.; Hardin, R.

    2017-12-01

    The Cropland Data Layer (CDL) is a national land cover product produced by the US Department of Agriculture/National Agricultural Statistics Service (NASS) to assess planted crop acreage on an annual basis. The 2017 CDL product serves as the decadal anniversary for the mapping of conterminous US agriculture. The CDL is a supervised land cover classification derived from medium resolution Earth observing satellites that capture crop phenology throughout the growing season, leveraging confidentially held ground reference information from the USDA Farm Service Agency (FSA) as training data. The CDL currently uses ancillary geospatial data from the US Geological Survey's National Land Cover Database (NLCD), and Imperviousness and Forest Canopy layers as well as the National Elevation Dataset as training for the non-agricultural domain. Accuracy assessments are documented and released annually with metadata publication. NASS is currently reprocessing the 2008 and 2009 CDL products to 30m resolution. They were originally processed and released at 56m based on the Resourcesat-1 AWiFS sensor. Additionally, best practices learned from processing the FSA ground reference data were applied to the historical training set, providing an enhanced classification at 30m. The release of these reprocessed products in the fall of 2017, along with the 2017 CDL annual product will be discussed and will complete a decade's worth of annual 30m products. Discussions of change and trend analytics as well as partnerships with key industry stakeholders will be displayed on the evolution and improvements made to this decadal geospatial crop specific land cover product.

  9. 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.

  10. 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.

  11. 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.

  12. Consequences of land use and land cover change

    USGS Publications Warehouse

    Slonecker, E. Terrence; Barnes, Christopher; Karstensen, Krista; Milheim, Lesley E.; Roig-Silva, Coral M.

    2013-01-01

    The U.S. Geological Survey (USGS) Climate and Land Use Change Mission Area is one of seven USGS mission areas that focuses on making substantial scientific "...contributions to understanding how Earth systems interact, respond to, and cause global change". Using satellite and other remotely sensed data, USGS scientists monitor patterns of land cover change over space and time at regional, national, and global scales. These data are analyzed to understand the causes and consequences of changing land cover, such as economic impacts, effects on water quality and availability, the spread of invasive species, habitats and biodiversity, carbon fluctuations, and climate variability. USGS scientists are among the leaders in the study of land cover, which is a term that generally refers to the vegetation and artificial structures that cover the land surface. Examples of land cover include forests, grasslands, wetlands, water, crops, and buildings. Land use involves human activities that take place on the land. For example, "grass" is a land cover, whereas pasture and recreational parks are land uses that produce a cover of grass.

  13. Accuracy assessment of NLCD 2006 land cover and impervious surface

    USGS Publications Warehouse

    Wickham, James D.; Stehman, Stephen V.; Gass, Leila; Dewitz, Jon; Fry, Joyce A.; Wade, Timothy G.

    2013-01-01

    Release of NLCD 2006 provides the first wall-to-wall land-cover change database for the conterminous United States from Landsat Thematic Mapper (TM) data. Accuracy assessment of NLCD 2006 focused on four primary products: 2001 land cover, 2006 land cover, land-cover change between 2001 and 2006, and impervious surface change between 2001 and 2006. The accuracy assessment was conducted by selecting a stratified random sample of pixels with the reference classification interpreted from multi-temporal high resolution digital imagery. The NLCD Level II (16 classes) overall accuracies for the 2001 and 2006 land cover were 79% and 78%, respectively, with Level II user's accuracies exceeding 80% for water, high density urban, all upland forest classes, shrubland, and cropland for both dates. Level I (8 classes) accuracies were 85% for NLCD 2001 and 84% for NLCD 2006. The high overall and user's accuracies for the individual dates translated into high user's accuracies for the 2001–2006 change reporting themes water gain and loss, forest loss, urban gain, and the no-change reporting themes for water, urban, forest, and agriculture. The main factor limiting higher accuracies for the change reporting themes appeared to be difficulty in distinguishing the context of grass. We discuss the need for more research on land-cover change accuracy assessment.

  14. Agriculture: Land Use

    EPA Pesticide Factsheets

    Land Use and agriculture. Information about land use restrictions and incentive programs.Agricultural operations sometimes involve activities regulated by laws designed to protect water supplies, threatened or endangered plants and animals, or wetlands.

  15. 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.

  16. Mapping decadal land cover changes in the woodlands of north eastern Namibia using the Landsat satellite archive (1975-2014)

    NASA Astrophysics Data System (ADS)

    Wingate, Vladimir; Phinn, Stuart; Kuhn, Nikolaus

    2016-04-01

    Woodland savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to intensive land uses. This study investigates the land cover changes over 108,038 km2 in NE Namibia using multi-sensor Landsat imagery, at decadal intervals from 1975 to 2014, with a post-classification change detection method and supervised Regression Tree classifiers. We discuss likely impacts of land tenure and reforms over the past four decades on changes in land use and land cover. These included losses, gains and exchanges between predominant land cover classes. Exchanges comprised logical conversions between woodland and agricultural classes, implying woodland clearing for arable farming, cropland abandonment and vegetation succession. The dominant change was a reduction in the area of the woodland class due to the expansion of the agricultural class, specifically, small-scale cereal and pastoral production. Woodland area decreased from 90% of the study area in 1975 to 83% in 2014, while cleared land increased from 9% to 14%. We found that the main land cover changes are conversion from woodland to agricultural and urban land uses, driven by urban expansion and woodland clearing for subsistence-based agriculture and pastoralism.

  17. 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.

  18. Managed Clearings: an Unaccounted Land-cover in Urbanizing Regions

    NASA Astrophysics Data System (ADS)

    Singh, K. K.; Madden, M.; Meentemeyer, R. K.

    2016-12-01

    Managed clearings (MC), such as lawns, public parks and grassy transportation medians, are a common and ecologically important land cover type in urbanizing regions, especially those characterized by sprawl. We hypothesize that MC is underrepresented in land cover classification schemes and data products such as NLCD (National Land Cover Database) data, which may impact environmental assessments and models of urban ecosystems. We visually interpreted and mapped fine scale land cover with special attention to MC using 2012 NAIP (National Agriculture Imagery Program) images and compared the output with NLCD data. Areas sampled were 50 randomly distributed 1*1km blocks of land in three cities of the Char-lanta mega-region (Atlanta, Charlotte, and Raleigh). We estimated the abundance of MC relative to other land cover types, and the proportion of land-cover types in NLCD data that are similar to MC. We also assessed if the designations of recreation, transportation, and utility in MC inform the problem differently than simply tallying MC as a whole. 610 ground points, collected using the Google Earth, were used to evaluate accuracy of NLCD data and visual interpretation for consistency. Overall accuracy of visual interpretation and NLCD data was 78% and 58%, respectively. NLCD data underestimated forest and MC by 14.4km2 and 6.4km2, respectively, while overestimated impervious surfaces by 10.2km2 compared to visual interpretation. MC was the second most dominant land cover after forest (40.5%) as it covered about 28% of the total area and about 13% higher than impervious surfaces. Results also suggested that recreation in MC constitutes up to 90% of area followed by transportation and utility. Due to the prevalence of MC in urbanizing regions, the addition of MC to the synthesis of land-cover data can help delineate realistic cover types and area proportions that could inform ecologic/hydrologic models, and allow for accurate prediction of ecological phenomena.

  19. Classification and Mapping of Agricultural Land for National Water-Quality Assessment

    USGS Publications Warehouse

    Gilliom, Robert J.; Thelin, Gail P.

    1997-01-01

    Agricultural land use is one of the most important influences on water quality at national and regional scales. Although there is great diversity in the character of agricultural land, variations follow regional patterns that are influenced by environmental setting and economics. These regional patterns can be characterized by the distribution of crops. A new approach to classifying and mapping agricultural land use for national water-quality assessment was developed by combining information on general land-use distribution with information on crop patterns from agricultural census data. Separate classification systems were developed for row crops and for orchards, vineyards, and nurseries. These two general categories of agricultural land are distinguished from each other in the land-use classification system used in the U.S. Geological Survey national Land Use and Land Cover database. Classification of cropland was based on the areal extent of crops harvested. The acreage of each crop in each county was divided by total row-crop area or total orchard, vineyard, and nursery area, as appropriate, thus normalizing the crop data and making the classification independent of total cropland area. The classification system was developed using simple percentage criteria to define combinations of 1 to 3 crops that account for 50 percent or more or harvested acreage in a county. The classification system consists of 21 level I categories and 46 level II subcategories for row crops, and 26 level I categories and 19 level II subcategories for orchards, vineyards, and nurseries. All counties in the United States with reported harvested acreage are classified in these categories. The distribution of agricultural land within each county, however, must be evaluated on the basis of general land-use data. This can be done at the national scale using 'Major Land Uses of the United States,' at the regional scale using data from the national Land Use and Land Cover database, or at

  20. Land Use and Land Cover Change

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

    Brown, Daniel; Polsky, Colin; Bolstad, Paul V.

    2014-05-01

    A contribution to the 3rd National Climate Assessment report, discussing the following key messages: 1. Choices about land-use and land-cover patterns have affected and will continue to affect how vulnerable or resilient human communities and ecosystems are to the effects of climate change. 2. Land-use and land-cover changes affect local, regional, and global climate processes. 3. Individuals, organizations, and governments have the capacity to make land-use decisions to adapt to the effects of climate change. 4. Choices about land use and land management provide a means of reducing atmospheric greenhouse gas levels.

  1. Nitrate-nitrogen losses through subsurface drainage under various agricultural land covers.

    PubMed

    Qi, Zhiming; Helmers, Matthew J; Christianson, Reid D; Pederson, Carl H

    2011-01-01

    Nitrate-nitrogen (NO₃-N) loading to surface water bodies from subsurface drainage is an environmental concern in the midwestern United States. The objective of this study was to investigate the effect of various land covers on NO₃-N loss through subsurface drainage. Land-cover treatments included (i) conventional corn ( L.) (C) and soybean [ (L.) Merr.] (S); (ii) winter rye ( L.) cover crop before corn (rC) and before soybean (rS); (iii) kura clover ( M. Bieb.) as a living mulch for corn (kC); and (iv) perennial forage of orchardgrass ( L.) mixed with clovers (PF). In spring, total N uptake by aboveground biomass of rye in rC, rye in rS, kura clover in kC, and grasses in PF were 14.2, 31.8, 87.0, and 46.3 kg N ha, respectively. Effect of land covers on subsurface drainage was not significant. The NO₃-N loss was significantly lower for kC and PF than C and S treatments (p < 0.05); rye cover crop did not reduce NO₃-N loss, but NO₃-N concentration was significantly reduced in rC during March to June and in rS during July to November (p < 0.05). Moreover, the increase of soil NO₃-N from early to late spring in rS was significantly lower than the S treatment (p < 0.05). This study suggests that kC and PF are effective in reducing NO₃-N loss, but these systems could lead to concerns relative to grain yield loss and change in farming practices. Management strategies for kC need further study to achieve reasonable corn yield. The effectiveness of rye cover crop on NO-N loss reduction needs further investigation under conditions of different N rates, wider weather patterns, and fall tillage. by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  2. EnviroAtlas - Phoenix, AZ - One Meter Resolution Urban Land Cover Data (2010)

    EPA Pesticide Factsheets

    The EnviroAtlas Phoenix, AZ land cover (LC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near-infrared) aerial photography taken from June through September, 2010 at 1 m spatial resolution. Seven land cover classes were mapped: water, impervious surfaces, soil and barren land, trees and forest, shrubs, grass and herbaceous non-woody vegetation, and agriculture. An accuracy assessment using a completely random sampling of 598 land cover reference points yielded an overall accuracy of 69.2%. The area mapped includes the entirety of the Central Arizona-Phoenix Long-Term Ecological Research (CAP-LTER) area, which was classified by the Environmental Remote Sensing and Geoinformatics Lab (ERSG) at Arizona State University. The land cover dataset also includes an area of approximately 625 square kilometers which is located north of Phoenix. This section was classified by the EPA land cover classification team. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each at

  3. Land cover associations of nesting territories of three sympatric buteos in shortgrass prairie

    USGS Publications Warehouse

    McConnell, S.; O'Connell, T. J.; Leslie, David M.

    2008-01-01

    Three species of Buteo hawks nest sympatrically in the southern Great Plains of the United States. Dietary overlap among them is broad and we tested the hypothesis these species partition their breeding habitat spatially. We compared land cover and topography around 224 nests of the three species breeding in shortgrass prairie in 2004 and 2005. Red-tailed Hawks (Buteo jamaicensis) nested almost exclusively in riparian timber surrounded by prairie (95% prairie land cover around nests) and disproportionately used areas with greater topographic relief within prairie landscapes. Swainson's Hawks (B. swainsoni) commonly nested in low-relief areas dominated by small-grain production agriculture but generally used habitats in proportion to availability. Most nest sites of Ferruginous Hawks (B. regalis) were in prairie (78% prairie land cover around nests), but some were in areas that were at least partially agricultural. Ferruginous Hawks had at least two times more sand sagebrush (Artemisia filifolia) around their nests than their two congeners. We conclude that sympatric breeding Buteos on the southern Great Plains spatially partitioned nest sites according to subtle differences in land cover and topography.

  4. Determinants of Urban Expansion and Agricultural Land Conversion in 25 EU Countries.

    PubMed

    Ustaoglu, Eda; Williams, Brendan

    2017-10-01

    Agricultural land conversion is resulting from ongoing complex interaction between the physical environment, policy settings and socio-economic factors. Case studies of the determinants of agricultural land conversion potentially contribute to the analysis of the main causes of land-use change. This can assist authorities and policy makers in understanding the relative importance of a wide range of factors on urban expansion and associated agricultural land-use change. This paper explores the determinants of agricultural land conversion to urban uses in the studied 25 European Union countries between 2000 and 2006. European-level as well as region-specific land-use changes are studied. The research is using the spatial data adapted from European Corine Land Cover maps of 2000 and 2006 and utilised other European sources regarding socio-economic, natural, geological, climate, and policy-related data. The differences in urbanisation processes observed in different regions in Europe emphasise the regional variations of urban conversion process of agricultural land use. This study identifies a combination of socio-economic drivers, policy-related factors, nature and location-based factors as key influences on agricultural land conversion processes in Europe. Specifically we found that the Common Agricultural Policy (CAP) subsidies were influential in curbing urbanisation and reducing agricultural land consumption.

  5. Determinants of Urban Expansion and Agricultural Land Conversion in 25 EU Countries

    NASA Astrophysics Data System (ADS)

    Ustaoglu, Eda; Williams, Brendan

    2017-10-01

    Agricultural land conversion is resulting from ongoing complex interaction between the physical environment, policy settings and socio-economic factors. Case studies of the determinants of agricultural land conversion potentially contribute to the analysis of the main causes of land-use change. This can assist authorities and policy makers in understanding the relative importance of a wide range of factors on urban expansion and associated agricultural land-use change. This paper explores the determinants of agricultural land conversion to urban uses in the studied 25 European Union countries between 2000 and 2006. European-level as well as region-specific land-use changes are studied. The research is using the spatial data adapted from European Corine Land Cover maps of 2000 and 2006 and utilised other European sources regarding socio-economic, natural, geological, climate, and policy-related data. The differences in urbanisation processes observed in different regions in Europe emphasise the regional variations of urban conversion process of agricultural land use. This study identifies a combination of socio-economic drivers, policy-related factors, nature and location-based factors as key influences on agricultural land conversion processes in Europe. Specifically we found that the Common Agricultural Policy (CAP) subsidies were influential in curbing urbanisation and reducing agricultural land consumption.

  6. 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

  7. Land cover characterization and mapping of continental southeast Asia using multi-resolution satellite sensor data

    USGS Publications Warehouse

    Giri, Chandra; Defourny, Pierre; Shrestha, Surendra

    2003-01-01

    Land use/land cover change, particularly that of tropical deforestation and forest degradation, has been occurring at an unprecedented rate and scale in Southeast Asia. The rapid rate of economic development, demographics and poverty are believed to be the underlying forces responsible for the change. Accurate and up-to-date information to support the above statement is, however, not available. The available data, if any, are outdated and are not comparable for various technical reasons. Time series analysis of land cover change and the identification of the driving forces responsible for these changes are needed for the sustainable management of natural resources and also for projecting future land cover trajectories. We analysed the multi-temporal and multi-seasonal NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite data of 1985/86 and 1992 to (1) prepare historical land cover maps and (2) to identify areas undergoing major land cover transformations (called ‘hot spots’). The identified ‘hot spot’ areas were investigated in detail using high-resolution satellite sensor data such as Landsat and SPOT supplemented by intensive field surveys. Shifting cultivation, intensification of agricultural activities and change of cropping patterns, and conversion of forest to agricultural land were found to be the principal reasons for land use/land cover change in the Oudomxay province of Lao PDR, the Mekong Delta of Vietnam and the Loei province of Thailand, respectively. Moreover, typical land use/land cover change patterns of the ‘hot spot’ areas were also examined. In addition, we developed an operational methodology for land use/land cover change analysis at the national level with the help of national remote sensing institutions.

  8. National Land Cover Database 2001 (NLCD01)

    USGS Publications Warehouse

    LaMotte, Andrew E.

    2016-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  9. 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.

  10. 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.

  11. Long-term changes in Serengeti-Mara wildebeest and land cover: Pastoralism, population, or policies?

    PubMed Central

    Homewood, K.; Lambin, E. F.; Coast, E.; Kariuki, A.; Kikula, I.; Kivelia, J.; Said, M.; Serneels, S.; Thompson, M.

    2001-01-01

    Declines in habitat and wildlife in semiarid African savannas are widely reported and commonly attributed to agropastoral population growth, livestock impacts, and subsistence cultivation. However, extreme annual and shorter-term variability of rainfall, primary production, vegetation, and populations of grazers make directional trends and causal chains hard to establish in these ecosystems. Here two decades of changes in land cover and wildebeest in the Serengeti-Mara region of East Africa are analyzed in terms of potential drivers (rainfall, human and livestock population growth, socio-economic trends, land tenure, agricultural policies, and markets). The natural experiment research design controls for confounding variables, and our conceptual model and statistical approach integrate natural and social sciences data. The Kenyan part of the ecosystem shows rapid land-cover change and drastic decline for a wide range of wildlife species, but these changes are absent on the Tanzanian side. Temporal climate trends, human population density and growth rates, uptake of small-holder agriculture, and livestock population trends do not differ between the Kenyan and Tanzanian parts of the ecosystem and cannot account for observed changes. Differences in private versus state/communal land tenure, agricultural policy, and market conditions suggest, and spatial correlations confirm, that the major changes in land cover and dominant grazer species numbers are driven primarily by private landowners responding to market opportunities for mechanized agriculture, less by agropastoral population growth, cattle numbers, or small-holder land use. PMID:11675492

  12. 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.

  13. 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.

  14. Vegetation Analysis and Land Use Land Cover Classification of Forest in Uttara Kannada District India Using Remote Sensign and GIS Techniques

    NASA Astrophysics Data System (ADS)

    Koppad, A. G.; Janagoudar, B. S.

    2017-10-01

    The study was conducted in Uttara Kannada districts during the year 2012-2014. The study area lies between 13.92° N to 15.52° N latitude and 74.08° E to 75.09° E longitude with an area of 10,215 km2. The Indian satellite IRS P6 LISS-III imageries were used to classify the land use land cover classes with ground truth data collected with GPS through supervised classification in ERDAS software. The land use and land cover classes identified were dense forest, horticulture plantation, sparse forest, forest plantation, open land and agriculture land. The dense forest covered an area of 63.32 % (6468.70 sq km) followed by agriculture 12.88 % (1315.31 sq. km), sparse forest 10.59 % (1081.37 sq. km), open land 6.09 % (622.37 sq. km), horticulture plantation and least was forest plantation (1.07 %). Settlement, stony land and water body together cover about 4.26 percent of the area. The study indicated that the aspect and altitude influenced the forest types and vegetation pattern. The NDVI map was prepared which indicated that healthy vegetation is represented by high NDVI values between 0.1 and 1. The non- vegetated features such as water bodies, settlement, and stony land indicated less than 0.1 values. The decrease in forest area in some places was due to anthropogenic activities. The thematic map of land use land cover classes was prepared using Arc GIS Software.

  15. Urbanization and agricultural land loss in India: comparing satellite estimates with census data.

    PubMed

    Pandey, Bhartendu; Seto, Karen C

    2015-01-15

    We examine the impacts of urbanization on agricultural land loss in India from 2001 to 2010. We combined a hierarchical classification approach with econometric time series analysis to reconstruct land-cover change histories using time series MODIS 250 m VI images composited at 16-day intervals and night time lights (NTL) data. We compared estimates of agricultural land loss using satellite data with agricultural census data. Our analysis highlights six key results. First, agricultural land loss is occurring around smaller cities more than around bigger cities. Second, from 2001 to 2010, each state lost less than 1% of its total geographical area due to agriculture to urban expansion. Third, the northeastern states experienced the least amount of agricultural land loss. Fourth, agricultural land loss is largely in states and districts which have a larger number of operational or approved SEZs. Fifth, urban conversion of agricultural land is concentrated in a few districts and states with high rates of economic growth. Sixth, agricultural land loss is predominantly in states with higher agricultural land suitability compared to other states. Although the total area of agricultural land lost to urban expansion has been relatively low, our results show that since 2006, the amount of agricultural land converted has been increasing steadily. Given that the preponderance of India's urban population growth has yet to occur, the results suggest an increase in the conversion of agricultural land going into the future. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. 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...

  17. 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.

  18. Understanding the drivers of agricultural land use change in south-central Senegal

    USGS Publications Warehouse

    Wood, E. C.; Tappan, G. Gray; Hadj, Amadou

    2004-01-01

    Described is (1) the land use and land cover changes that have taken place in the Department of Velingara, an area of tropical dry woodland in south-central Senegal, (2) the biophysical and socio-economic drivers of those changes with an emphasis on transition to agricultural use, and (3) an assessment of the likelihood of intensification of agriculture in the Department. Results indicate that land devoted to agriculture, either in active cultivation or short-term fallow, is increasing. There is little evidence of agricultural intensification in most of Velingara, with extensification coming largely at the cost of reduction in both upland woodlands and riparian forest.

  19. Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

    NASA Astrophysics Data System (ADS)

    Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2015-12-01

    Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

  20. 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

  1. Computer-aided boundary delineation of agricultural lands

    NASA Technical Reports Server (NTRS)

    Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

    1989-01-01

    The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.

  2. Effect of land use land cover change on soil erosion potential in an agricultural watershed.

    PubMed

    Sharma, Arabinda; Tiwari, Kamlesh N; Bhadoria, P B S

    2011-02-01

    Universal soil loss equation (USLE) was used in conjunction with a geographic information system to determine the influence of land use and land cover change (LUCC) on soil erosion potential of a reservoir catchment during the period 1989 to 2004. Results showed that the mean soil erosion potential of the watershed was increased slightly from 12.11 t ha(-1) year(-1) in the year 1989 to 13.21 t ha(-1) year(-1) in the year 2004. Spatial analysis revealed that the disappearance of forest patches from relatively flat areas, increased in wasteland in steep slope, and intensification of cultivation practice in relatively more erosion-prone soil were the main factors contributing toward the increased soil erosion potential of the watershed during the study period. Results indicated that transition of other land use land cover (LUC) categories to cropland was the most detrimental to watershed in terms of soil loss while forest acted as the most effective barrier to soil loss. A p value of 0.5503 obtained for two-tailed paired t test between the mean erosion potential of microwatersheds in 1989 and 2004 also indicated towards a moderate change in soil erosion potential of the watershed over the studied period. This study revealed that the spatial location of LUC parcels with respect to terrain and associated soil properties should be an important consideration in soil erosion assessment process.

  3. 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

  4. 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.

  5. 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

  6. EnviroAtlas -Phoenix, AZ- One Meter Resolution Urban Land Cover Data (2010) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The EnviroAtlas Phoenix, AZ land cover data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near-infrared) aerial photography taken from June through September, 2010 at 1 m spatial resolution. Seven land cover classes were mapped: water, impervious surfaces, soil and barren land, trees and forest, shrubland, grass and herbaceous non-woody vegetation, and agriculture. An accuracy assessment using a completely random sampling of 598 land cover reference points yielded an overall accuracy of 69.2%. The area mapped includes the entirety of the Central Arizona-Phoenix Long-Term Ecological Research (CAP-LTER) area, which was classified by the Environmental Remote Sensing and Geoinformatics Lab (ERSG) at Arizona State University. The land cover dataset also includes an area of approximately 625 square kilometers which is located north of Phoenix. This section was classified by the EPA land cover classification team. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data

  7. Mapping and measuring land-cover characteristics of New River Basin, Tennessee, using Landsat digital tapes

    USGS Publications Warehouse

    Hollyday, E.F.; Sauer, S.P.

    1976-01-01

    Land-cover information is needed to select subbasins within the New River basin, Tennessee, for the study of hydrologic processes and also is needed to transfer study results to other sites affected by coal mining. It was believed that data recorded by the first Earth Resources Technology Satellite (Landsat-1) could be processed to yield the needed land-cover information. This study demonstrates that digital computer processing of the spectral information contained in each picture element (pixel) of 1.1 acres (4,500 m2) can produce maps and tables of the areal extent of selected land-cover categories.The distribution of water, rock, agricultural areas, evergreens, bare earth, hardwoods, and uncategorized areas, is portrayed on a map of the entire New River basin (1:62,500 scale) and on 15 quadrangles (1:24,000 scale). Although some categories are a mixture of land-cover types, they portray the predominant component named. Tables quantify the area of each category and indicate that agriculture covers 5 percent of the basin, evergreens cover 7 percent, bare earth covers 6 percent, three categories of hardwoods cover 81 percent, and water, rock, and uncategorized areas each cover less than 1 percent of the basin.

  8. Effect of Land Cover Type and Structure on Water Cycling Dynamics for Agricultural and Wetland Sites in the Sacramento/San Joaquin River Delta

    NASA Astrophysics Data System (ADS)

    Eichelmann, E.; Hemes, K. S.; Baldocchi, D. D.

    2016-12-01

    The Sacramento/San Joaquin river delta is an important source of fresh water for California. To reverse soil subsidence, which is linked to draining the natural wetlands for agriculture, parts of the Sacramento/San Joaquin river delta have been restored to managed wetlands. While these restored wetlands provide greenhouse gas benefits compared to agricultural use of the land, implications for the water balance of these ecosystems, specifically evapotranspiration, are not well known. Based on multiple years of eddy covariance measurements of water, CO2, and sensible energy fluxes we explored the water cycling dynamics for several sites under different land use covers in the Sacramento/San Joaquin river delta. We investigated four sites under agricultural use (rice, corn, and alfalfa crops and cow pasture) and three restored wetland sites of varying ages and structures to examine the influence of land cover type and structure on evapotranspiration, sensible energy flux, and water use efficiency. While the wetland and the rice sites are usually flooded for the majority of the year, the alfalfa, corn, and pasture sites have a water table that is maintained to be below ground level throughout the year. The three wetland sites also have different fractions of open water to vegetation, covering a gradient from very dense vegetation with no open water to a fairly open structure with large pools of open water. These differences in land cover (dry vs flooded and fraction of open water to vegetation) have an effect on the patterns of evapotranspiration on diurnal to annual timescales. Although the flooded sites (wetland sites and rice) tend to have larger annual evapotranspiration than the drained sites (cow pasture, alfalfa, and corn), the fraction of open water to vegetation affects the extend to which the flooded sites' evapotranspiration exceeds that of drained sites. On diurnal timescales, we found that flooded sites with a larger fraction of open water to vegetation

  9. EnviroAtlas - New York, NY - One Meter Resolution Urban Land Cover Data (2008)

    EPA Pesticide Factsheets

    The New York, NY EnviroAtlas Meter-scale Urban Land Cover (MULC) Data were generated by the University of Vermont Spatial Analysis Laboratory (SAL) under the direction of Jarlath O'Neil-Dunne as part of the United States Forest Service Urban Tree Canopy (UTC) assessment program. Seven classes were mapped using LiDAR and high resolution orthophotography: Tree Canopy, Grass/Shrub, Bare Soil, Water, Buildings, Roads/Railroads, and Other Paved Surfaces. These data were subsequently merged to fit with the EPA classification. The SAL project covered the five boroughs within the NYC city limits. However the EPA study area encompassed that area plus a 1 kilometer buffer. Additional land cover for the buffer area was generated from United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP) four band (red, green, blue, and near infrared) aerial photography at 1 m spatial resolution from July, 2011 and LiDAR from 2010. Six land cover classes were mapped: water, impervious surfaces, soil and barren land, trees, grass-herbaceous non-woody vegetation, and agriculture. An accuracy assessment of 600 completely random and 55 stratified random photo interpreted reference points yielded an overall User's fuzzy accuracy of 87 percent. The area mapped is the US Census Bureau's 2010 Urban Statistical Area for New York City plus a 1 km buffer. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAt

  10. Projecting large-scale area changes in land use and land cover for terrestrial carbon analyses.

    PubMed

    Alig, Ralph J; Butler, Brett J

    2004-04-01

    One of the largest changes in US forest type areas over the last half-century has involved pine types in the South. The area of planted pine has increased more than 10-fold since 1950, mostly on private lands. Private landowners have responded to market incentives and government programs, including subsidized afforestation on marginal agricultural land. Timber harvest is a crucial disturbance affecting planted pine area, as other forest types are converted to planted pine after harvest. Conversely, however, many harvested pine plantations revert to other forest types, mainly due to passive regeneration behavior on nonindustrial private timberlands. We model land use and land cover changes as a basis for projecting future changes in planted pine area, to aid policy analysts concerned with mitigation activities for global climate change. Projections are prepared in two stages. Projected land use changes include deforestation due to pressures to develop rural land as the human population expands, which is a larger area than that converted from other rural lands (e.g., agriculture) to forestry. In the second stage, transitions among forest types are projected on land allocated to forestry. We consider reforestation, influences of timber harvest, and natural succession and disturbance processes. Baseline projections indicate a net increase of about 5.6 million ha in planted pine area in the South over the next 50 years, with a notable increase in sequestered carbon. Additional opportunities to expand pine plantation area warrant study of landowner behavior to aid in designing more effective incentives for inducing land use and land cover changes to help mitigate climate change and attain other goals.

  11. 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

  12. 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.

  13. Optimal land use/cover classification using remote sensing imagery for hydrological modelling in a Himalayan watershed

    NASA Astrophysics Data System (ADS)

    Saran, Sameer; Sterk, Geert; Kumar, Suresh

    2007-10-01

    Land use/cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into HRU's requires good-quality spatial data on land use/cover. This paper presents different approaches to attain an optimal land use/cover map based on remote sensing imagery for a Himalayan watershed in northern India. First digital classifications using maximum likelihood classifier (MLC) and a decision tree classifier were applied. The results obtained from the decision tree were better and even improved after post classification sorting. But the obtained land use/cover map was not sufficient for the delineation of HRUs, since the agricultural land use/cover class did not discriminate between the two major crops in the area i.e. paddy and maize. Therefore we adopted a visual classification approach using optical data alone and also fused with ENVISAT ASAR data. This second step with detailed classification system resulted into better classification accuracy within the 'agricultural land' class which will be further combined with topography and soil type to derive HRU's for physically-based hydrological modelling.

  14. Past and predicted future changes in the land cover of the Upper Mississippi River floodplain, USA

    USGS Publications Warehouse

    De Jager, N. R.; Rohweder, J.J.; Nelson, J.C.

    2013-01-01

    This study provides one historical and two alternative future contexts for evaluating land cover modifications within the Upper Mississippi River (UMR) floodplain. Given previously documented changes in land use, river engineering, restoration efforts and hydro-climatic changes within the UMR basin and floodplain, we wanted to know which of these changes are the most important determinants of current and projected future floodplain land cover. We used Geographic Information System data covering approximately 37% of the UMR floodplain (3232 km2) for ca 1890 (pre-lock and dam) and three contemporary periods (1975, 1989 and 2000) across which river restoration actions have increased and hydro-climatic changes have occurred. We further developed two 50-year future scenarios from the spatially dependent land cover transitions that occurred from 1975 to 1989 (scenario A) and from 1989 to 2000 (scenario B) using Markov models.Land cover composition of the UMR did not change significantly from 1975 to 2000, indicating that current land cover continues to reflect historical modifications that support agricultural production and commercial navigation despite some floodplain restoration efforts and variation in river discharge. Projected future land cover composition based on scenario A was not significantly different from the land cover for 1975, 1989 or 2000 but was different from the land cover of scenario B, which was also different from all other periods. Scenario B forecasts transition of some forest and marsh habitat to open water by the year 2050 for some portions of the northern river and projects that some agricultural lands will transition to open water in the southern portion of the river. Future floodplain management and restoration planning efforts in the UMR should consider the potential consequences of continued shifts in hydro-climatic conditions that may occur as a result of climate change and the potential effects on floodplain land cover.

  15. Application of remote sensing data to land use and land cover assessment in the Tubarao River coastal plain, Santa Catarina, Brazil

    NASA Technical Reports Server (NTRS)

    1982-01-01

    By means of aerial photography and MSS-LANDSAT data a land use/land cover classification was applied to the Tubarao River coastal plain. The following classes were identified: coal related areas, permanently flooded wetlands, periodically flooded wetlands, agricultural lands, bare soils, water bodies, urban areas, forestlands.

  16. 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).

  17. 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.

  18. 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.

  19. Land cover changes assessment using object-based image analysis in the Binah River watershed (Togo and Benin)

    NASA Astrophysics Data System (ADS)

    Badjana, Hèou Maléki; Helmschrot, Jörg; Selsam, Peter; Wala, Kpérkouma; Flügel, Wolfgang-Albert; Afouda, Abel; Akpagana, Koffi

    2015-10-01

    In this study, land cover changes between 1972 and 2013 were investigated in the Binah River watershed (North of Togo and Benin) using remote sensing and geographic information system technologies. Multitemporal satellite images—Landsat MSS (1972), TM (1987), and OLI-TIRS (2013)—were processed using object-based image analysis and post-classification comparison methods including landscape metrics and changes trajectories analysis. Land cover maps referring to five main land cover classes, namely, agricultural land, forest land, savannah, settlements, and water bodies, were produced for each acquisition date. The overall accuracies were 76.64% (1972), 83.52% (1987), and 88.84% (2013) with respective Kappa statistics of 0.69, 0.78, and 0.86. The assessment of the spatiotemporal pattern of land cover changes indicates that savannah, the main vegetation type, has undergone the most dominant change, decreasing from 67% of the basin area in 1972 to 56% in 1987 and 33% in 2013. At the same time, agricultural land has significantly increased from 15% in 1972 to 24% in 1987 and 43% in 2013, while some proportions of agricultural land were converted to savannah relating to fallow agriculture. In total, more than 55% of the landscape experienced changes between 1972 and 2013. These changes are primarily due to human activities and population growth. In addition, agricultural activities significantly contributed to the increase in the number of patches, degree of division, and splitting index of forest and savannah vegetations and the decrease in their effective mesh sizes. These results indicate further fragmentation of forest and savannah vegetations between 1972 and 2013. Further research is needed to quantitatively evaluate the influences of individual factors of human activities and to separate these from the impacts of climate change-driven disturbances.

  20. 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.

  1. EnviroAtlas -- Green Bay, Wisconsin -- One Meter Resolution Urban Land Cover Data (2010)

    EPA Pesticide Factsheets

    The Green Bay, WI one meter-scale urban land cover (LC) dataset comprises 936 km2 around the city of Green Bay, surrounding towns, tribal lands and rural areas in Brown and Outagamie Counties. These leaf-on LC data and maps were derived from 1-m pixel, four-band (red, green, blue, and near-infrared) aerial photography acquired from the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) on three dates in 2010: July 3, July 25, and August 5. LiDAR data collected on November 18, 2010 was integrated for the Brown County portion. Eight land cover classes were mapped: water, impervious surfaces, soil and barren land, trees and forest, grass and herbaceous non-woody vegetation, agriculture, and wetlands (woody and emergent). Wetlands were copied from the best available existing wetlands data. Analysis of a random sampling of 566 photo-interpreted land cover reference points yielded an overall accuracy of 91.3%. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can b

  2. Interactive boundary delineation of agricultural lands using graphics workstations

    NASA Technical Reports Server (NTRS)

    Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

    1992-01-01

    A review is presented of the computer-assisted stratification and sampling (CASS) system developed to delineate the boundaries of sample units for survey procedures. CASS stratifies the sampling units by land-cover and land-use type, employing image-processing software and hardware. This procedure generates coverage areas and the boundaries of stratified sampling units that are utilized for subsequent sampling procedures from which agricultural statistics are developed.

  3. Reconstructed historical land cover and biophysical parameters for studies of land-atmosphere interactions within the eastern United States

    USGS Publications Warehouse

    Steyaert, Louis T.; Knox, R.G.

    2008-01-01

    Over the past 350 years, the eastern half of the United States experienced extensive land cover changes. These began with land clearing in the 1600s, continued with widespread deforestation, wetland drainage, and intensive land use by 1920, and then evolved to the present-day landscape of forest regrowth, intensive agriculture, urban expansion, and landscape fragmentation. Such changes alter biophysical properties that are key determinants of land-atmosphere interactions (water, energy, and carbon exchanges). To understand the potential implications of these land use transformations, we developed and analyzed 20-km land cover and biophysical parameter data sets for the eastern United States at 1650, 1850, 1920, and 1992 time slices. Our approach combined potential vegetation, county-level census data, soils data, resource statistics, a Landsat-derived land cover classification, and published historical information on land cover and land use. We reconstructed land use intensity maps for each time slice and characterized the land cover condition. We combined these land use data with a mutually consistent set of biophysical parameter classes, to characterize the historical diversity and distribution of land surface properties. Time series maps of land surface albedo, leaf area index, a deciduousness index, canopy height, surface roughness, and potential saturated soils in 1650, 1850, 1920, and 1992 illustrate the profound effects of land use change on biophysical properties of the land surface. Although much of the eastern forest has returned, the average biophysical parameters for recent landscapes remain markedly different from those of earlier periods. Understanding the consequences of these historical changes will require land-atmosphere interactions modeling experiments.

  4. 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...

  5. Forecasting land cover change impacts on drinking water treatment costs in Minneapolis, Minnesota

    NASA Astrophysics Data System (ADS)

    Woznicki, S. A.; Wickham, J.

    2017-12-01

    Source protection is a critical aspect of drinking water treatment. The benefits of protecting source water quality in reducing drinking water treatment costs are clear. However, forecasting the impacts of environmental change on source water quality and its potential to influence future treatment processes is lacking. The drinking water treatment plant in Minneapolis, MN has recognized that land cover change threatens water quality in their source watershed, the Upper Mississippi River Basin (UMRB). Over 1,000 km2 of forests, wetlands, and grasslands in the UMRB were lost to agriculture from 2008-2013. This trend, coupled with a projected population increase of one million people in Minnesota by 2030, concerns drinking water treatment plant operators in Minneapolis with respect to meeting future demand for clean water in the UMRB. The objective of this study is to relate land cover change (forest and wetland loss, agricultural expansion, urbanization) to changes in treatment costs for the Minneapolis, MN drinking water utility. To do this, we first developed a framework to determine the relationship between land cover change and water quality in the context of recent historical changes and projected future changes in land cover. Next we coupled a watershed model, the Soil and Water Assessment Tool (SWAT) to projections of land cover change from the FOREcasting SCEnarios of Land-use Change (FORE-SCE) model for the mid-21st century. Using historical Minneapolis drinking water treatment data (chemical usage and costs), source water quality in the UMRB was linked to changes in treatment requirements as a function of projected future land cover change. These analyses will quantify the value of natural landscapes in protecting drinking water quality and future treatment processes requirements. In addition, our study provides the Minneapolis drinking water utility with information critical to their planning and capital improvement process.

  6. Remote sensing of land use/cover changes and its effect on wind erosion potential in southern Iran

    PubMed Central

    Sameni, Abdolmajid; Fallah Shamsi, Seyed Rashid; Bartholomeus, Harm

    2016-01-01

    Wind erosion is a complex process influenced by different factors. Most of these factors are stable over time, but land use/cover and land management practices are changing gradually. Therefore, this research investigates the impact of changing land use/cover and land management on wind erosion potential in southern Iran. We used remote sensing data (Landsat ETM+ and Landsat 8 imagery of 2004 and 2013) for land use/cover mapping and employed the Iran Research Institute of Forest and Rangeland (IRIFR) method to estimate changes in wind erosion potential. For an optimal mapping, the performance of different classification algorithms and input layers was tested. The amount of changes in wind erosion and land use/cover were quantified using cross-tabulation between the two years. To discriminate land use/cover related to wind erosion, the best results were obtained by combining the original spectral bands with synthetic bands and using Maximum Likelihood classification algorithm (Kappa Coefficient of 0.8 and 0.9 for Landsat ETM+ and Landsat 8, respectively). The IRIFR modelling results indicate that the wind erosion potential has increased over the last decade. The areas with a very high sediment yield potential have increased, whereas the areas with a low, medium, and high sediment yield potential decreased. The area with a very low sediment yield potential have remained constant. When comparing the change in erosion potential with land use/cover change, it is evident that soil erosion potential has increased mostly in accordance with the increase of the area of agricultural practices. The conversion of rangeland to agricultural land was a major land-use change which lead to more agricultural practices and associated soil loss. Moreover, results indicate an increase in sandification in the study area which is also a clear evidence of increasing in soil erosion. PMID:27547511

  7. 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.

  8. 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

  9. The effects of war on land-use/land-cover change: An analysis of Landsat imagery for northeast Bosnia

    NASA Astrophysics Data System (ADS)

    Witmer, Frank D. W.

    The use of satellite technology by military planners has a relatively long history as a tool of warfare, but little research has used satellite technology to study the effects of war. This research addresses this gap by applying satellite remote sensing imagery to study the effects of war on land-use/land-cover change in northeast Bosnia. The war in Bosnia, 1992-1995, resulted in over 100,000 deaths, many more wounded, and the mass displacement of nearly half the population of 4.2 million. When combined with the destruction of much of the transportation infrastructure and housing stock, widespread mine placement, and loss of agricultural machinery, the impacts to both the people and land were dramatic. Though the most severe war impacts are visible at local scales (e.g. destroyed buildings), this study focuses on impacts to agricultural land, a larger scale visible to satellite sensors. Multispectral Landsat Thematic Mapper (TM) data (30m pixels) from before and during the war in addition to recent imagery from 2004/05 were used to detect abandoned agricultural land. The satellite images were co-registered to enable a perpixel analysis of changes based on the statistical properties of the pixels using multiple change detection methods. Ground reference data were collected in May of 2006 at survey sites selected using a stratified random sampling approach based on the derived map of abandoned agricultural land. Fine resolution (60cm) Quickbird imagery was also used to verify the accuracy of the classification. The remote sensing analysis results were then used to test two hypotheses related to war outcomes: (a) land abandonment is due to wartime minefields and (b) land abandonment is greater in pre-war Croat areas and areas where ethnic cleansing was heaviest. The effects of minefields on land abandonment was first tested in a geographic information system (GIS), and then by using multiple regression models that account for spatial autocorrelation among observations

  10. Land-cover change in the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative, 1973 to 2000

    USGS Publications Warehouse

    Drummond, Mark A.; Stier, Michael P.; Coffin, Alisa W.

    2015-01-01

    This report summarizes baseline land-cover change information for four time intervals from between 1973 and 2000 for the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (LCC). The study used sample data from the USGS Land Cover Trends dataset to develop estimates of change for 10 land-cover classes in the LCC. The results show that an estimated 17.7 percent of the LCC land cover had a change during the 27-year period. Cyclic forest dynamics—of timber harvest and regrowth—are the most extensive types of land conversion. Agricultural land had an estimated net decline of 3.5 percent as cropland and pasture were urbanized and developed and converted to forest use. Urban and other developed land covers expanded from 2.0 percent of the LCC in 1973 to 3.1 percent in 2000. The report also highlights causes and challenges of land-cover change.

  11. Hydrogeomorphic features mediate the effects of land use/cover on reservoir productivity and food webs

    USGS Publications Warehouse

    Bremigan, M.T.; Soranno, P.A.; Gonzalez, M.J.; Bunnell, D.B.; Arend, K.K.; Renwick, W.H.; Stein, R.A.; Vanni, M.J.

    2008-01-01

    Although effects of land use/cover on nutrient concentrations in aquatic systems are well known, half or more of the variation in nutrient concentration remains unexplained by land use/cover alone. Hydrogeomorphic (HGM) landscape features can explain much remaining variation and influence food web interactions. To explore complex linkages among land use/cover, HGM features, reservoir productivity, and food webs, we sampled 11 Ohio reservoirs, ranging broadly in agricultural catchment land use/cover, for 3 years. We hypothesized that HGM features mediate the bottom-up effects of land use/cover on reservoir productivity, chlorophyll a, zooplankton, and recruitment of gizzard shad, an omnivorous fish species common throughout southeastern U.S. reservoirs and capable of exerting strong effects on food web and nutrient dynamics. We tested specific hypotheses using a model selection approach. Percent variation explained was highest for total nitrogen (R2 = 0.92), moderately high for total phosphorus, chlorophyll a, and rotifer biomass (R2 = 0.57 to 0.67), relatively low for crustacean zooplankton biomass and larval gizzard shad hatch abundance (R2 = 0.43 and 0.42), and high for larval gizzard shad survivor abundance (R2 = 0.79). The trophic status models included agricultural land use/cover and an HGM predictor, whereas the zooplankton models had few HGM predictors. The larval gizzard shad models had the highest complexity, including more than one HGM feature and food web components. We demonstrate the importance of integrating land use/cover, HGM features, and food web interactions to investigate critical interactions and feedbacks among physical, chemical, and biological components of linked land-water ecosystems.

  12. West Africa land use and land cover time series

    USGS Publications Warehouse

    Cotillon, Suzanne E.

    2017-02-16

    Started in 1999, the West Africa Land Use Dynamics project represents an effort to map land use and land cover, characterize the trends in time and space, and understand their effects on the environment across West Africa. The outcome of the West Africa Land Use Dynamics project is the production of a three-time period (1975, 2000, and 2013) land use and land cover dataset for the Sub-Saharan region of West Africa, including the Cabo Verde archipelago. The West Africa Land Use Land Cover Time Series dataset offers a unique basis for characterizing and analyzing land changes across the region, systematically and at an unprecedented level of detail.

  13. Land use and land cover changes in Zêzere watershed (Portugal)--Water quality implications.

    PubMed

    Meneses, B M; Reis, R; Vale, M J; Saraiva, R

    2015-09-15

    To understand the relations between land use allocation and water quality preservation within a watershed is essential to assure sustainable development. The land use and land cover (LUC) within Zêzere River watershed registered relevant changes in the last decades. These land use and land cover changes (LUCCs) have impacts in water quality, mainly in surface water degradation caused by surface runoff from artificial and agricultural areas, forest fires and burnt areas, and caused by sewage discharges from agroindustry and urban sprawl. In this context, the impact of LUCCs in the quality of surface water of the Zêzere watershed is evaluated, considering the changes for different types of LUC and establishing their possible correlations to the most relevant water quality changes. The results indicate that the loss of coniferous forest and the increase of transitional woodland-shrub are related to increased water's pH; while the growth in artificial surfaces and pastures leads mainly to the increase of soluble salts and fecal coliform concentration. These particular findings within the Zêzere watershed, show the relevance of addressing water quality impact driven from land use and should therefore be taken into account within the planning process in order to prevent water stress, namely within watersheds integrating drinking water catchments. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Linking land cover and water quality in New York City's water supply watersheds.

    PubMed

    Mehaffey, M H; Nash, M S; Wade, T G; Ebert, D W; Jones, K B; Rager, A

    2005-08-01

    The Catskill/Delaware reservoirs supply 90% of New York City's drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.

  15. National land-cover pattern data

    Treesearch

    Kurt H. Riitters; James D. Wickham; James E. Vogelmann; K. Bruce Jones

    2000-01-01

    Land cover and its spatial patterns are key ingredients in ecological studies that consider large regions and the impacts of human activities. Because humanity is a principal driver of land-cover change over large regions (Turner et al. 1990), land-cover data provide direct measures of human activity, and both direct and indirect measures of ecological conditions...

  16. 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...

  17. Land cover change assessment using object-oriented classification based on image segmentation in the Binah river watershed (Togo and Benin)

    NASA Astrophysics Data System (ADS)

    Badjana, M. H.; Helmschrot, J.; Wala, K.; Flugel, W. A.; Afouda, A.; Akpagana, K.

    2014-12-01

    Assessing and monitoring land cover changes over time, especially in Sub-Saharan Africa characterized by both a high population growth and the highest rate of land degradation in the world is of high relevance for sustainable land management, water security and food production. In this study, land cover changes between 1972 and 2013 were investigated in the Binah river watershed (North of Togo and Benin) using advanced remote sensing and GIS technologies to support sustainable land and water resources management efforts. To this end, multi-temporal satellite images - Landsat MSS (1972), TM (1987) and ETM+ (2013) were processed using object-oriented classification based on image segmentation and post-classification comparison methods. Five main land cover classes namely agricultural land, forest land, savannah, settlements and water bodies have been identified with overall accuracies of 75.11% (1972), 81.82% (1987), and 86.1% (2013) and respective Kappa statistics of 0.67, 0.76 and 0.83. These classification results helped to explicitly assess the spatio-temporal pattern of land cover within the basin. The results indicate that savannah as the main vegetation type in the basin has decreased from 63.3% of the basin area in 1972 to 60.4% in 1987 and 35.6% in 2013. Also the forest land which covered 20.7% in 1972 has decreased to 12.7% in 1987 and 11.7% in 2013. This severe decrease in vegetation mainly resulted from the extension of agricultural areas and settlements, which is, thus, considered as the main driving force. In fact, agricultural land increased of 61.4% from 1972 to 1987, 81.4% from 1987 to 2013 and almost twice from 1972 to 2013 while human settlements increased from 0.8% of the basin area in 1972 to 2.5% in 1987 and 7.7% in 2013. The transition maps illustrate the conversion of savannah to agricultural land at each time step relating to slash and burn agriculture, but also demonstrate the threat of environmental degradation of the savannah biome

  18. EnviroAtlas - New York, NY - One Meter Resolution Urban Land Cover Data (2008) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas ). The New York, NY EnviroAtlas Meter-scale Urban Land Cover (MULC) Data were generated by the University of Vermont Spatial Analysis Laboratory (SAL) under the direction of Jarlath O'Neil-Dunne as part of the United States Forest Service Urban Tree Canopy (UTC) assessment program. Seven classes were mapped using LiDAR and high resolution orthophotography: Tree Canopy, Grass/Shrub, Bare Soil, Water, Buildings, Roads/Railroads, and Other Paved Surfaces. These data were subsequently merged to fit with the EPA classification. The SAL project covered the five boroughs within the NYC city limits. However the EPA study area encompassed that area plus a 1 kilometer buffer. Additional land cover for the buffer area was generated from United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP) four band (red, green, blue, and near infrared) aerial photography at 1 m spatial resolution from July, 2011 and LiDAR from 2010. Six land cover classes were mapped: water, impervious surfaces, soil and barren land, trees, grass-herbaceous non-woody vegetation, and agriculture. An accuracy assessment of 600 completely random and 55 stratified random photo interpreted reference points yielded an overall User's fuzzy accuracy of 87 percent. The area mapped is the US Census Bureau's 2010 Urban Statistical Area for New Yor

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  1. Assessments of SENTINEL-2 Vegetation Red-Edge Spectral Bands for Improving Land Cover Classification

    NASA Astrophysics Data System (ADS)

    Qiu, S.; He, B.; Yin, C.; Liao, Z.

    2017-09-01

    The Multi Spectral Instrument (MSI) onboard Sentinel-2 can record the information in Vegetation Red-Edge (VRE) spectral domains. In this study, the performance of the VRE bands on improving land cover classification was evaluated based on a Sentinel-2A MSI image in East Texas, USA. Two classification scenarios were designed by excluding and including the VRE bands. A Random Forest (RF) classifier was used to generate land cover maps and evaluate the contributions of different spectral bands. The combination of VRE bands increased the overall classification accuracy by 1.40 %, which was statistically significant. Both confusion matrices and land cover maps indicated that the most beneficial increase was from vegetation-related land cover types, especially agriculture. Comparison of the relative importance of each band showed that the most beneficial VRE bands were Band 5 and Band 6. These results demonstrated the value of VRE bands for land cover classification.

  2. The dynamics of human-induced land cover change in miombo ecosystems of southern Africa

    NASA Astrophysics Data System (ADS)

    Jaiteh, Malanding Sambou

    Understanding human-induced land cover change in the miombo require the consistent, geographically-referenced, data on temporal land cover characteristics as well as biophysical and socioeconomic drivers of land use, the major cause of land cover change. The overall goal of this research to examine the applications of high-resolution satellite remote sensing data in studying the dynamics of human-induced land cover change in the miombo. Specific objectives are to: (1) evaluate the applications of computer-assisted classification of Landsat Thematic Mapper (TM) data for land cover mapping in the miombo and (2) analyze spatial and temporal patterns of landscape change locations in the miombo. Stepwise Thematic Classification, STC (a hybrid supervised-unsupervised classification) procedure for classifying Landsat TM data was developed and tested using Landsat TM data. Classification accuracy results were compared to those from supervised and unsupervised classification. The STC provided the highest classification accuracy i.e., 83.9% correspondence between classified and referenced data compared to 44.2% and 34.5% for unsupervised and supervised classification respectively. Improvements in the classification process can be attributed to thematic stratification of the image data into spectrally homogenous (thematic) groups and step-by-step classification of the groups using supervised or unsupervised classification techniques. Supervised classification failed to classify 18% of the scene evidence that training data used did not adequately represent all of the variability in the data. Application of the procedure in drier miombo produced overall classification accuracy of 63%. This is much lower than that of wetter miombo. The results clearly demonstrate that digital classification of Landsat TM can be successfully implemented in the miombo without intensive fieldwork. Spatial characteristics of land cover change in agricultural and forested landscapes in central Malawi

  3. Upper Washita River experimental watersheds: Land cover data sets (1974-2007) for two southwestern Oklahoma agricultural watersheds

    USDA-ARS?s Scientific Manuscript database

    A retrospective land cover analysis covering the time period from the early 1970s to early 1990s was conducted to gain a sense of the dynamics of land cover changes on the Little Washita River and Fort Cobb Reservoir experimental watersheds (LWREW, FCREW), located in southwestern Oklahoma. This stu...

  4. 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.

  5. Land Grabbing and the Commodification of Agricultural Land in Africa

    NASA Astrophysics Data System (ADS)

    D'Odorico, P.; Rulli, M. C.

    2014-12-01

    The increasing global demand for farmland products is placing unprecedented pressure on the global agricultural system. The increasing demand can be met through either the intensification or the expansion of agricultural production at the expenses of other ecosystems. The ongoing escalation of large scale land acquisitions in the developing world may contribute to both of these two processes. Investments in agriculture have become a priority for a number of governments and corporations that are trying to expand their agricultural production while securing good profits. It is unclear however to what extent these investments are driving the intensification or the expansion of agriculture. In the last decade large scale land acquisitions by external investors have increased at unprecedented rates. This global land rush was likely enhanced by recent food crises, when prices skyrocketed in response to crop failure, new bioenergy policies, and the increasing demand for agricultural products by a growing and increasingly affluent human population. Corporations recognized the potential for high return investments in agricultural land, while governments started to enhance their food security by purchasing large tracts of land in foreign countries. It has been estimated that, to date, about 35.6 million ha of cropland - more than twice the agricultural land of Germany - have been acquired by foreign investors worldwide. As an effect of these land deals the local communities lose legal access to the land and its products. Here we investigate the effect of large scale land acquisition on agricultural intensification or expansion in African countries. We discuss the extent to which these investments in agriculture may increase crop production and stress how this phenomenon can greatly affect the local communities, their food security, economic stability and the long term resilience of their livelihoods, regardless of whether the transfer of property rights is the result of an

  6. Ecosystem Services Provided by Agricultural Land as Modeled by Broad Scale Geospatial Analysis

    NASA Astrophysics Data System (ADS)

    Kokkinidis, Ioannis

    Agricultural ecosystems provide multiple services including food and fiber provision, nutrient cycling, soil retention and water regulation. Objectives of the study were to identify and quantify a selection of ecosystem services provided by agricultural land, using existing geospatial tools and preferably free and open source data, such as the Virginia Land Use Evaluation System (VALUES), the North Carolina Realistic Yield Expectations (RYE) database, and the land cover datasets NLCD and CDL. Furthermore I sought to model tradeoffs between provisioning and other services. First I assessed the accuracy of agricultural land in NLCD and CDL over a four county area in eastern Virginia using cadastral parcels. I uncovered issues concerning the definition of agricultural land. The area and location of agriculture saw little change in the 19 years studied. Furthermore all datasets have significant errors of omission (11.3 to 95.1%) and commission (0 to 71.3%). Location of agriculture was used with spatial crop yield databases I created and combined with models I adapted to calculate baseline values for plant biomass, nutrient composition and requirements, land suitability for and potential production of biofuels and the economic impact of agriculture for the four counties. The study area was then broadened to cover 97 counties in eastern Virginia and North Carolina, investigating the potential for increased regional grain production through intensification and extensification of agriculture. Predicted yield from geospatial crop models was compared with produced yield from the NASS Survey of Agriculture. Area of most crops in CDL was similar to that in the Survey of Agriculture, but a yield gap is present for most years, partially due to weather, thus indicating potential for yield increase through intensification. Using simple criteria I quantified the potential to extend agriculture in high yield land in other uses and modeled the changes in erosion and runoff should

  7. 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

  8. 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.

  9. The Significance of Land Cover Delineation on Soil Erosion Assessment.

    PubMed

    Efthimiou, Nikolaos; Psomiadis, Emmanouil

    2018-04-25

    The study aims to evaluate the significance of land cover delineation on soil erosion assessment. To that end, RUSLE (Revised Universal Soil Loss Equation) was implemented at the Upper Acheloos River catchment, Western Central Greece, annually and multi-annually for the period 1965-92. The model estimates soil erosion as the linear product of six factors (R, K, LS, C, and P) considering the catchment's climatic, pedological, topographic, land cover, and anthropogenic characteristics, respectively. The C factor was estimated using six alternative land use delineations of different resolution, namely the CORINE Land Cover (CLC) project (2000, 2012 versions) (1:100,000), a land use map conducted by the Greek National Agricultural Research Foundation (NAGREF) (1:20,000), a land use map conducted by the Greek Payment and Control Agency for Guidance and Guarantee Community Aid (PCAGGCA) (1:5,000), and the Landsat 8 16-day Normalized Difference Vegetation Index (NDVI) dataset (30 m/pixel) (two approximations) based on remote sensing data (satellite image acquired on 07/09/2016) (1:40,000). Since all other factors remain unchanged per each RUSLE application, the differences among the yielded results are attributed to the C factor (thus the land cover pattern) variations. Validation was made considering the convergence between simulated (modeled) and observed sediment yield. The latter was estimated based on field measurements conducted by the Greek PPC (Public Power Corporation). The model performed best at both time scales using the Landsat 8 (Eq. 13) dataset, characterized by a detailed resolution and a satisfactory categorization, allowing the identification of the most susceptible to erosion areas.

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

    NASA Astrophysics Data System (ADS)

    McCleary, Amy L.

    This dissertation examines contemporary land use and land cover (LULC) change in the communities and protected areas of Isabela Island to provide insights into human-environment interactions in the Galapagos Islands of Ecuador. The growing human presence in Galapagos over the last four decades has been accompanied by significant changes in LULC on inhabited islands in the archipelago. Local stakeholders and decision-makers have recently called for a more integrative approach to understanding interactions between people and the environment in the archipelago. This study is guided by two complementary bodies of work situated within the human-environment tradition of Geography---land change science and landscape ecology. First, support Vector Machine (SVM) and Object Based Image Analysis (OBIA) classifiers are evaluated for mapping LULC from high spatial resolution satellite images. The results show that thematic LULC classifications produced by OBIA are more accurate overall than those generated by SVM. However, important tradeoffs exist between improvements in classification accuracy and processing requirements. The composition and spatial configuration of LULC change are then mapped and quantified from a time series of QuickBird and WorldView-2 satellite images from 2003 to 2010. The pattern metric and change detection analyses reveal that land use change is extensive within the communities due to the expansion and consolidation of built-up areas, and fragmentation of and declines in agriculture. The Galapagos National Park is primarily transformed by exotic plant invasion, forests expansion, and shrinking coastal lagoons. Patterns of agricultural land abandonment, plant invasion, and forest expansion over the same period are described from pattern metric and overlay analyses. Potential drivers of these LULC transitions are identified from logistic regression models, descriptive statistics of agricultural surveys and population censuses, and interviews with

  11. 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...

  12. Integrating multisource land use and land cover data

    USGS Publications Warehouse

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

    1995-01-01

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

  13. Land-cover effects on soil organic carbon stocks in a European city.

    PubMed

    Edmondson, Jill L; Davies, Zoe G; McCormack, Sarah A; Gaston, Kevin J; Leake, Jonathan R

    2014-02-15

    Soil is the vital foundation of terrestrial ecosystems storing water, nutrients, and almost three-quarters of the organic carbon stocks of the Earth's biomes. Soil organic carbon (SOC) stocks vary with land-cover and land-use change, with significant losses occurring through disturbance and cultivation. Although urbanisation is a growing contributor to land-use change globally, the effects of urban land-cover types on SOC stocks have not been studied for densely built cities. Additionally, there is a need to resolve the direction and extent to which greenspace management such as tree planting impacts on SOC concentrations. Here, we analyse the effect of land-cover (herbaceous, shrub or tree cover), on SOC stocks in domestic gardens and non-domestic greenspaces across a typical mid-sized U.K. city (Leicester, 73 km(2), 56% greenspace), and map citywide distribution of this ecosystem service. SOC was measured in topsoil and compared to surrounding extra-urban agricultural land. Average SOC storage in the city's greenspace was 9.9 kg m(-2), to 21 cm depth. SOC concentrations under trees and shrubs in domestic gardens were greater than all other land-covers, with total median storage of 13.5 kg m(-2) to 21 cm depth, more than 3 kg m(-2) greater than any other land-cover class in domestic and non-domestic greenspace and 5 kg m(-2) greater than in arable land. Land-cover did not significantly affect SOC concentrations in non-domestic greenspace, but values beneath trees were higher than under both pasture and arable land, whereas concentrations under shrub and herbaceous land-covers were only higher than arable fields. We conclude that although differences in greenspace management affect SOC stocks, trees only marginally increase these stocks in non-domestic greenspaces, but may enhance them in domestic gardens, and greenspace topsoils hold substantial SOC stores that require protection from further expansion of artificial surfaces e.g. patios and driveways. Copyright

  14. EnviroAtlas -- Austin, TX -- One Meter Resolution Urban Land Cover Data (2010)

    EPA Pesticide Factsheets

    The Austin, TX EnviroAtlas One Meter-scale Urban Land Cover (MULC) Data were generated from United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP) four band (red, green, blue, and near infrared) aerial photography at 1 m spatial resolution from multiple dates in May, 2010. Six land cover classes were mapped: water, impervious surfaces, soil and barren land, trees, grass-herbaceous non-woody vegetation, and agriculture. An accuracy assessment of 600 completely random and 55 stratified random photo interpreted reference points yielded an overall User's fuzzy accuracy of 87 percent. The area mapped is the US Census Bureau's 2010 Urban Statistical Area for Austin, TX plus a 1 km buffer. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  15. Land cover mapping for development planning in Eastern and Southern Africa

    NASA Astrophysics Data System (ADS)

    Oduor, P.; Flores Cordova, A. I.; Wakhayanga, J. A.; Kiema, J.; Farah, H.; Mugo, R. M.; Wahome, A.; Limaye, A. S.; Irwin, D.

    2016-12-01

    Africa continues to experience intensification of land use, driven by competition for resources and a growing population. Land cover maps are some of the fundamental datasets required by numerous stakeholders to inform a number of development decisions. For instance, they can be integrated with other datasets to create value added products such as vulnerability impact assessment maps, and natural capital accounting products. In addition, land cover maps are used as inputs into Greenhouse Gas (GHG) inventories to inform the Agriculture, Forestry and other Land Use (AFOLU) sector. However, the processes and methodologies of creating land cover maps consistent with international and national land cover classification schemes can be challenging, especially in developing countries where skills, hardware and software resources can be limiting. To meet this need, SERVIR Eastern and Southern Africa developed methodologies and stakeholder engagement processes that led to a successful initiative in which land cover maps for 9 countries (Malawi, Rwanda, Namibia, Botswana, Lesotho, Ethiopia, Uganda, Zambia and Tanzania) were developed, using 2 major classification schemes. The first sets of maps were developed based on an internationally acceptable classification system, while the second sets of maps were based on a nationally defined classification system. The mapping process benefited from reviews from national experts and also from technical advisory groups. The maps have found diverse uses, among them the definition of the Forest Reference Levels in Zambia. In Ethiopia, the maps have been endorsed by the national mapping agency as part of national data. The data for Rwanda is being used to inform the Natural Capital Accounting process, through the WAVES program, a World Bank Initiative. This work illustrates the methodologies and stakeholder engagement processes that brought success to this land cover mapping initiative.

  16. Land cover change mapping using MODIS time series to improve emissions inventories

    NASA Astrophysics Data System (ADS)

    López-Saldaña, Gerardo; Quaife, Tristan; Clifford, Debbie

    2016-04-01

    MELODIES is an FP7 funded project to develop innovative and sustainable services, based upon Open Data, for users in research, government, industry and the general public in a broad range of societal and environmental benefit areas. Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A land cover product was created for 2003 to 2015 and a bayesian approach was created to identified land cover changes. We will present the results of the time series development and the first exercises when creating the land cover and land cover changes products.

  17. Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

    NASA Astrophysics Data System (ADS)

    Li, Xiaoxiao; Myint, Soe W.; Zhang, Yujia; Galletti, Chritopher; Zhang, Xiaoxiang; Turner, Billie L.

    2014-12-01

    Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

  18. US agricultural policy, land use change, and biofuels: are we driving our way to the next dust bowl?

    NASA Astrophysics Data System (ADS)

    Wright, Christopher K.

    2015-05-01

    Lark et al (2015 Environ. Res. Lett. 10 044003), analyze recent shifts in US agricultural land use (2008-2012) using newly-available, high-resolution geospatial information, the Cropland Data Layer. Cropland expansion documented by Lark et al suggests the need to reform national agricultural policies in the wake of an emerging, new era of US agriculture characterized by rapid land cover/land use change.

  19. About soil cover heterogeneity of agricultural research stations' experimental fields

    NASA Astrophysics Data System (ADS)

    Rannik, Kaire; Kõlli, Raimo; Kukk, Liia

    2013-04-01

    Depending on local pedo-ecological conditions (topography, (geo) diversity of soil parent material, meteorological conditions) the patterns of soil cover and plant cover determined by soils are very diverse. Formed in the course of soil-plant mutual relationship, the natural ecosystems are always influenced to certain extent by the other local soil forming conditions or they are site specific. The agricultural land use or the formation of agro-ecosystems depends foremost on the suitability of soils for the cultivation of feed and food crops. As a rule, the most fertile or the best soils of the area, which do not present any or present as little as possible constraints for agricultural land use, are selected for this purpose. Compared with conventional field soils, the requirements for the experimental fields' soil cover quality are much higher. Experimental area soils and soil cover composition should correspond to local pedo-ecological conditions and, in addition to that, represent the soil types dominating in the region, whereas the fields should be as homogeneous as possible. The soil cover heterogeneity of seven arable land blocks of three research stations (Jõgeva, Kuusiku and Olustvere) was studied 1) by examining the large scale (1:10 000) digital soil map (available via the internet), and 2) by field researches using the transect method. The stages of soils litho-genetic and moisture heterogeneities were estimated by using the Estonian normal soils matrix, however, the heterogeneity of top- and subsoil texture by using the soil texture matrix. The quality and variability of experimental fields' soils humus status, was studied more thoroughly from the aspect of humus concentration (g kg-1), humus cover thickness (cm) and humus stocks (Mg ha-1). The soil cover of Jõgeva experimental area, which presents an accumulative drumlin landscape (formed during the last glacial period), consist from loamy Luvisols and associated to this Cambisols. In Kuusiku area

  20. Rubber and Land-Cover Land-Use Change in Mainland Southeast Asia

    NASA Astrophysics Data System (ADS)

    Fox, J. M.; Hurni, K.

    2017-12-01

    Over the past half century, the five countries of Mainland Southeast Asia (MSEA) - Cambodia, Laos, Myanmar, Thailand, and Vietnam - have witnessed major shifts from predominantly subsistence agrarian economies to increasingly commercialized agriculture. Major drivers of change include policy initiatives that fostered regional economic integration and promoted among other changes rapid expansion of boom-crop plantations. Among the many types of commercial boom crops promoted and grown in MSEA are numerous tree-based products such as rubber, coffee, tree species for pulp and paper (particularly eucalyptus and acacia), cashews, and fruits such as oranges, lychees, and longans. The project proposal hypothesized that most (but not all) tree crops replaced swidden cultivation fields and hence are not necessarily accompanied by deforestation. We used MODIS EVI and SWIR time-series from 2001-2014 to classify changes in tree cover across MSEA; a total of 6849 sample points were used to train the classifier (75%) and verification (25%). The classification consists of 24 classes and 17 classes represent tree crops. Project results suggest that 4.4 m ha of rubber have been planted since 2003; 50% of rubber is planted on former evergreen forest land, 18% on deciduous forest land, and 32% on low vegetation area (former crop lands, bushes, scrub). Tree crops occupy about 8% of the landscape (half of that is rubber). Due to the differences in their political and economic histories these countries display different LCLUCs. In northern Laos, smallholder rubber plantations dominate and shifting cultivation is common in the upland. In southern Laos, large-scale plantations of rubber, coffee, eucalyptus, and sugarcane are widespread. In Thailand, vast areas are covered by annual agriculture; fruit trees and rubber are the prevailing tree crops and are mostly planted by smallholders. In Cambodia, large-scale rubber plantations have expanded in recent years on forest lands; smallholder

  1. Assessment of Large Scale Land Cover Change Classifications and Drivers of Deforestation in Indonesia

    NASA Astrophysics Data System (ADS)

    Wijaya, A.; Sugardiman Budiharto, R. A.; Tosiani, A.; Murdiyarso, D.; Verchot, L. V.

    2015-04-01

    Indonesia possesses the third largest tropical forests coverage following Brazilian Amazon and Congo Basin regions. This country, however, suffered from the highest deforestation rate surpassing deforestation in the Brazilian Amazon in 2012. National capacity for forest change assessment and monitoring has been well-established in Indonesia and the availability of national forest inventory data could largely assist the country to report their forest carbon stocks and change over more than two decades. This work focuses for refining forest cover change mapping and deforestation estimate at national scale applying over 10,000 scenes of Landsat scenes, acquired in 1990, 1996, 2000, 2003, 2006, 2009, 2011 and 2012. Pre-processing of the data includes, geometric corrections and image mosaicking. The classification of mosaic Landsat data used multi-stage visual observation approaches, verified using ground observations and comparison with other published materials. There are 23 land cover classes identified from land cover data, presenting spatial information of forests, agriculture, plantations, non-vegetated lands and other land use categories. We estimated the magnitude of forest cover change and assessed drivers of forest cover change over time. Forest change trajectories analysis was also conducted to observe dynamics of forest cover across time. This study found that careful interpretations of satellite data can provide reliable information on forest cover and change. Deforestation trend in Indonesia was lower in 2000-2012 compared to 1990-2000 periods. We also found that over 50% of forests loss in 1990 remains unproductive in 2012. Major drivers of forest conversion in Indonesia range from shrubs/open land, subsistence agriculture, oil palm expansion, plantation forest and mining. The results were compared with other available datasets and we obtained that the MOF data yields reliable estimate of deforestation.

  2. 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.

  3. 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...

  4. Interactive Effects of Storms, Drought, and Weekly Land Cover Changes on Water Quality Patterns in an Agricultural-dominated Subtropical Catchment in New Zealand

    NASA Astrophysics Data System (ADS)

    Julian, J.; Owsley, B.; de Beurs, K.; Hughes, A.

    2013-12-01

    Rivers are the funnels of landscapes, with the quality of water at the catchment outlet reflecting interactions among geomorphic processes, vegetation characteristics, weather patterns, and anthropogenic land uses. The impacts of changing climate and land cover on water quality are not straightforward; but instead, are set by the interaction of numerous landscape components at multiple spatiotemporal scales. In agricultural-dominated subtropical landscapes such as the Hoteo River Catchment in northern North Island of New Zealand, the land surface can be very dynamic, responding quickly to storms, drought, forest clearings, and grazing practices. In order to capture these short-term fluctuations, we created an 8-day land disturbance index for the catchment using MODIS Nadir BRDF-adjusted reflectance (NBAR) data (500 meter resolution) from 2000 to 2013. We also fused this time-series with Landsat TM/ETM surface reflectance data (30 meter resolution) to more precisely capture the location and extent of these land disturbances. This high-resolution land disturbance time-series was then compared to daily rainfall, daily river discharge, and monthly water samples to assess the effects of changing weather and land cover on a suite of water quality variables including water clarity, turbidity, ammonium (NH4), nitrate (NO3), total nitrogen (TN), dissolved reactive phosphate (DRP), total phosphorus (TP), and fecal coliforms. Forest clearings in the early part of our study period created the most intense land disturbances, which led to elevated turbidity and DRP during subsequent storms. Pasture areas during drought were also characterized by high disturbance indices, particularly in 2013 - the worst drought on record for northern New Zealand. Seasonal effects on land disturbance and water quality were also detected, especially for water clarity and turbidity. From 2011 to 2013, river discharge and turbidity from three sub-catchments were measured at 5-minute intervals to

  5. 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

  6. 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

  7. The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

    NASA Technical Reports Server (NTRS)

    Hogan, Christine A.

    1996-01-01

    A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation

  8. The Regional Land Cover Monitoring System: Building regional capacity through innovative land cover mapping approaches

    NASA Astrophysics Data System (ADS)

    Saah, D.; Tenneson, K.; Hanh, Q. N.; Aekakkararungroj, A.; Aung, K. S.; Goldstein, J.; Cutter, P. G.; Maus, P.; Markert, K. N.; Anderson, E.; Ellenburg, W. L.; Ate, P.; Flores Cordova, A. I.; Vadrevu, K.; Potapov, P.; Phongsapan, K.; Chishtie, F.; Clinton, N.; Ganz, D.

    2017-12-01

    Earth observation and Geographic Information System (GIS) tools, products, and services are vital to support the environmental decision making by governmental institutions, non-governmental agencies, and the general public. At the heart of environmental decision making is the monitoring land cover and land use change (LCLUC) for land resource planning and for ecosystem services, including biodiversity conservation and resilience to climate change. A major challenge for monitoring LCLUC in developing regions, such as Southeast Asia, is inconsistent data products at inconsistent intervals that have different typologies across the region and are typically made in without stakeholder engagement or input. Here we present the Regional Land Cover Monitoring System (RLCMS), a novel land cover mapping effort for Southeast Asia, implemented by SERVIR-Mekong, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries. The RLCMS focuses on mapping biophysical variables (e.g. canopy cover, tree height, or percent surface water) at an annual interval and in turn using those biophysical variables to develop land cover maps based on stakeholder definitions of land cover classes. This allows for flexible and consistent land cover classifications that can meet the needs of different institutions across the region. Another component of the RLCMS production is the stake-holder engagement through co-development. Institutions that directly benefit from this system have helped drive the development for regional needs leading to services for their specific uses. Examples of services for regional stakeholders include using the RLCMS to develop maps using the IPCC classification scheme for GHG emission reporting and developing custom annual maps as an input to hydrologic modeling/flood forecasting systems. In addition to the implementation of this system and the service stemming from the RLCMS in Southeast Asia, it is

  9. Agricultural Land Cover from Multitemporal C-Band SAR Data

    NASA Astrophysics Data System (ADS)

    Skriver, H.

    2013-12-01

    Henning Skriver DTU Space, Technical University of Denmark Ørsteds Plads, Building 348, DK-2800 Lyngby e-mail: hs@space.dtu.dk Problem description This paper focuses on land cover type from SAR data using high revisit acquisitions, including single and dual polarisation and fully polarimetric data, at C-band. The data set were acquired during an ESA-supported campaign, AgriSAR09, with the Radarsat-2 system. Ground surveys to obtain detailed land cover maps were performed during the campaign. Classification methods using single- and dual-polarisation data, and fully polarimetric data are used with multitemporal data with short revisit time. Results for airborne campaigns have previously been reported in Skriver et al. (2011) and Skriver (2012). In this paper, the short revisit satellite SAR data will be used to assess the trade-off between polarimetric SAR data and data as single or dual polarisation SAR data. This is particularly important in relation to the future GMES Sentinel-1 SAR satellites, where two satellites with a relatively wide swath will ensure a short revisit time globally. Questions dealt with are: which accuracy can we expect from a mission like the Sentinel-1, what is the improvement of using polarimetric SAR compared to single or dual polarisation SAR, and what is the optimum number of acquisitions needed. Methodology The data have sufficient number of looks for the Gaussian assumption to be valid for the backscatter coefficients for the individual polarizations. The classification method used for these data is therefore the standard Bayesian classification method for multivariate Gaussian statistics. For the full-polarimetric cases two classification methods have been applied, the standard ML Wishart classifier, and a method based on a reversible transform of the covariance matrix into backscatter intensities. The following pre-processing steps were performed on both data sets: The scattering matrix data in the form of SLC products were

  10. 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.

  11. Watershed-Scale Cover Crops Reduce Nutrient Export From Agricultural Landscapes.

    NASA Astrophysics Data System (ADS)

    Tank, J. L.; Hanrahan, B.; Christopher, S. F.; Trentman, M. T.; Royer, T. V.; Prior, K.

    2016-12-01

    The Midwestern US has undergone extensive land use change as forest, wetlands, and prairies have been converted to agroecosystems. Today, excess fertilizer nutrients from farm fields enter Midwestern agricultural streams, which degrades both local and downstream water quality, resulting in algal blooms and subsequent hypoxic "dead zones" far from the nutrient source. We are quantifying the benefits of watershed-scale conservation practices that may reduce nutrient runoff from adjacent farm fields. Specifically, research is lacking on whether the planting of winter cover crops in watersheds currently dominated by row-crop agriculture can significantly reduce nutrient inputs to adjacent streams. Since 2013, farmers have planted cover crops on 70% of croppable acres in the Shatto Ditch Watershed (IN), and "saturation level" implementation of this conservation practice has been sustained for 3 years. Every 14 days, we have quantified nutrient loss from fields by sampling nutrient fluxes from multiple subsurface tile drains and longitudinally along the stream channel throughout the watershed. Cover crops improved stream water quality by reducing dissolved inorganic nutrients exported downstream; nitrate-N and DRP concentrations and fluxes were significantly lower in tiles draining fields with cover crops compared to those without. Annual watershed nutrient export also decreased, and reductions in N and P loss ( 30-40%) exceeded what we expected based on only a 6-10% reduction in runoff due to increased watershed water holding capacity. We are also exploring the processes responsible for increased nutrient retention, where they are occurring (terrestrial vs. aquatic) and when (baseflow vs. storms). For example, whole-stream metabolism also responded to cover crop planting, showing reduced variation in primary production and respiration in years after watershed-scale planting of cover crops. In summary, widespread land cover change, through cover crop planting, can

  12. Bayesian spatial modelling and the significance of agricultural land use to scrub typhus infection in Taiwan.

    PubMed

    Wardrop, Nicola A; Kuo, Chi-Chien; Wang, Hsi-Chieh; Clements, Archie C A; Lee, Pei-Fen; Atkinson, Peter M

    2013-11-01

    Scrub typhus is transmitted by the larval stage of trombiculid mites. Environmental factors, including land cover and land use, are known to influence breeding and survival of trombiculid mites and, thus, also the spatial heterogeneity of scrub typhus risk. Here, a spatially autoregressive modelling framework was applied to scrub typhus incidence data from Taiwan, covering the period 2003 to 2011, to provide increased understanding of the spatial pattern of scrub typhus risk and the environmental and socioeconomic factors contributing to this pattern. A clear spatial pattern in scrub typhus incidence was observed within Taiwan, and incidence was found to be significantly correlated with several land cover classes, temperature, elevation, normalized difference vegetation index, rainfall, population density, average income and the proportion of the population that work in agriculture. The final multivariate regression model included statistically significant correlations between scrub typhus incidence and average income (negatively correlated), the proportion of land that contained mosaics of cropland and vegetation (positively correlated) and elevation (positively correlated). These results highlight the importance of land cover on scrub typhus incidence: mosaics of cropland and vegetation represent a transitional land cover type which can provide favourable habitats for rodents and, therefore, trombiculid mites. In Taiwan, these transitional land cover areas tend to occur in less populated and mountainous areas, following the frontier establishment and subsequent partial abandonment of agricultural cultivation, due to demographic and socioeconomic changes. Future land use policy decision-making should ensure that potential public health outcomes, such as modified risk of scrub typhus, are considered.

  13. 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.

  14. 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

  15. Conversion of prime agricultural land to urban land uses in Kansas City

    NASA Technical Reports Server (NTRS)

    Shaklee, R. V.

    1976-01-01

    In an expanding urban environment, agriculture and urban land uses are the two primary competitors for regional land resources. As a result of an increasing awareness of the effects which urban expansion has upon the regional environment, the conversion of prime agricultural land to urban land uses has become a point of concern to urban planners. A study was undertaken for the Kansas City Metropolitan Region, to determine the rate at which prime agricultural land has been converted to urban land uses over a five year period from 1969 to 1974. Using NASA high altitude color infrared imagery acquired over the city in October, 1969 and in May, 1974 to monitor the extent and location of urban expansion in the interim period, it was revealed that 42% of that expansion had occurred upon land classified as having prime agricultural potential. This involved a total of 10,727 acres of prime agricultural land and indicated a 7% increase over the 1969 which showed that 35% of the urban area had been developed on prime agricultural land.

  16. EnviroAtlas -Portland, ME- One Meter Resolution Urban Land Cover (2010)

    EPA Pesticide Factsheets

    The EnviroAtlas Portland, ME land cover map was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from Late Summer 2010 at 1 m spatial resolution. Eight land cover classes were mapped: water, impervious surfaces, soil and barren land, trees and forest, grass and herbaceous non-woody vegetation, agriculture, and wetlands (woody and emergent). An accuracy assessment using a stratified random sampling of 600 samples yielded an overall accuracy of 87.5 percent using a minimum mapping unit of 9 pixels (3x3 pixel window). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Portland. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  17. Late twentieth century land-cover change in the basin and range ecoregions of the United States

    USGS Publications Warehouse

    Soulard, Christopher E.; Sleeter, Benjamin M.

    2012-01-01

    As part of the US Geological Survey's Land Cover Trends project, land-use/land-cover change estimates between 1973 and 2000 are presented for the basin and range ecoregions, including Northern, Central, Mojave, and Sonoran. Landsat data were employed to estimate and characterize land-cover change from 1973, 1980, 1986, 1992, and 2000 using a post-classification comparison. Overall, spatial change was 2.5% (17,830 km2). Change increased steadily between 1973 and 1986 but decreased slightly between 1992 and 2000. The grassland/shrubland class, frequently used for livestock grazing, constituted the majority of the study area and had a net decrease from an estimated 83.8% (587,024 km2) in 1973 to 82.6% (578,242 km2) in 2000. The most common land-use/land-cover conversions across the basin and range ecoregions were indicative of the changes associated with natural, nonmechanical disturbances (i.e., fire), and grassland/shrubland loss to development, agriculture, and mining. This comprehensive look at contemporary land-use/land-cover change provides critical insight into how the deserts of the United States have changed and can be used to inform adaptive management practices of public lands.

  18. 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.

  19. Land-use poverty traps identified in shifting cultivation systems shape long-term tropical forest cover

    PubMed Central

    Coomes, Oliver T.; Takasaki, Yoshito; Rhemtulla, Jeanine M.

    2011-01-01

    In this article we illustrate how fine-grained longitudinal analyses of land holding and land use among forest peasant households in an Amazonian village can enrich our understanding of the poverty/land cover nexus. We examine the dynamic links in shifting cultivation systems among asset poverty, land use, and land cover in a community where poverty is persistent and primary forests have been replaced over time—with community enclosure—by secondary forests (i.e., fallows), orchards, and crop land. Land cover change is assessed using aerial photographs/satellite imagery from 1965 to 2007. Household and plot level data are used to track land holding, portfolios, and use as well as land cover over the past 30 y, with particular attention to forest status (type and age). Our analyses find evidence for two important types of “land-use” poverty traps—a “subsistence crop” trap and a “short fallow” trap—and indicate that the initial conditions of land holding by forest peasants have long-term effects on future forest cover and household welfare. These findings suggest a new mechanism driving poverty traps: insufficient initial land holdings induce land use patterns that trap households in low agricultural productivity. Path dependency in the evolution of household land portfolios and land use strategies strongly influences not only the wellbeing of forest people but also the dynamics of tropical deforestation and secondary forest regrowth. PMID:21873179

  20. Remote sensing and GIS-based integrated analysis of land cover change in Duzce plain and its surroundings (north western Turkey).

    PubMed

    Ikiel, Cercis; Ustaoglu, Beyza; Dutucu, Ayse Atalay; Kilic, Derya Evrim

    2013-02-01

    The aim of this study is to research natural land cover change caused by the permanent effects of human activities in Duzce plain and its surroundings, and to determine the current status of the land cover. For this purpose, two Landsat TM images were used in the study for the years 1987 and 2010. These images are analysed by using data image processing techniques in ERDAS Imagine©10.0 and ArcGIS©10.0 software. Land cover change nomenclature is classified according to the Coordination of Information on the Environment Level 2 Classification (1--urban fabric, 2--industrial, commercial and transport units, 3--heterogeneous agricultural areas, 4--forests, and 5--inland wetlands). Furthermore, the image analysis results are confirmed by the field research. According to the results, a decrease of 33.5 % was recorded in forest areas from 24,840.7 to 16,529.0 ha; an increase of 11.2 % was recorded in heterogeneous agricultural areas from 47,702.7 to 53,051.7 ha. Natural vegetation, which is the large part of land cover in the research area, has been changing rapidly because of rapid urbanisation and agricultural activities. As a result, it is concluded that significant changes have occurred on the natural land cover between the years 1987 and 2010 in the Duzce plain and its surroundings.

  1. Challenges for Sustainable Land Management through Climate-Smart Agriculture

    NASA Astrophysics Data System (ADS)

    Dougill, Andrew; Stringer, Lindsay

    2017-04-01

    There are increasing pushes for agricultural land management to be both sustainable and climate-smart (in terms of increasing productivity, building resilience to climate change and enhancing carbon storage). Climate-smart agriculture initiatives include conservation agriculture, based on minimum soil disturbance, permanent soil cover and crop rotation, and agroforestry. Such efforts address key international goals of the United Nations Convention to Combat Desertification (UNCCD) and United Nations Framework Convention on Climate Change (UNFCCC), but as yet have not seen widespread uptake. Based on analyses of different project interventions from across a range of southern African countries, we outline the inter-related challenges that are preventing adoption of climate-smart agriculture initiatives. We then identify routes to building multi-stakeholder partnerships and empowering communities through participatory monitoring with the aim of increasing uptake of such sustainable land management practices. Good practice examples remain largely restricted to local-level project interventions with significant donor (or private-sector) support, aligned to short-term community priorities relating to access to inputs or reduced labour requirements. Scaling-up to district- and national-level initiatives is yet to be widely successful due to problems of: limited policy coherence; a lack of communication between stakeholders at different levels; and limited understanding of long-term benefits associated with changes in agricultural practices. We outline opportunities associated with improved communication of climate information, empowerment of district-level adaptation planning and diversification of agricultural livelihood strategies as key routes to guide farmers towards more sustainable, and climate-smart, land management practices. Recent experiences in Malawi, which has experienced significant floods and an El Niño drought year in the last two years, are used to

  2. Monitoring conservation effectiveness in a global biodiversity hotspot: the contribution of land cover change assessment.

    PubMed

    Joseph, Shijo; Blackburn, George Alan; Gharai, Biswadip; Sudhakar, S; Thomas, A P; Murthy, M S R

    2009-11-01

    Tropical forests, which play critical roles in global biogeochemical cycles, radiation budgets and biodiversity, have undergone rapid changes in land cover in the last few decades. This study examines the complex process of land cover change in the biodiversity hotspot of Western Ghats, India, specifically investigating the effects of conservation measures within the Indira Gandhi Wildlife Sanctuary. Current vegetation patterns were mapped using an IRS P6 LISS III image and this was used together with Landsat MSS data from 1973 to map land cover transitions. Two major and divergent trends were observed. A dominant degradational trend can be attributed to agricultural expansion and infrastructure development while a successional trend, resulting from protection of the area, showed the resilience of the system after prolonged disturbances. The sanctuary appears susceptible to continuing disturbances under the current management regime but at lower rates than in surrounding unprotected areas. The study demonstrates that remotely sensed land cover assessments can have important contributions to monitoring land management strategies, understanding processes underpinning land use changes and helping to inform future conservation strategies.

  3. Implications of agricultural land use change to ecosystem services in the Ganges delta.

    PubMed

    Islam, G M Tarekul; Islam, A K M Saiful; Shopan, Ahsan Azhar; Rahman, Md Munsur; Lázár, Attila N; Mukhopadhyay, Anirban

    2015-09-15

    Ecosystems provide the basis for human civilization and natural capital for green economy and sustainable development. Ecosystem services may range from crops, fish, freshwater to those that are harder to see such as erosion regulation, carbon sequestration, and pest control. Land use changes have been identified as the main sources of coastal and marine pollution in Bangladesh. This paper explores the temporal variation of agricultural land use change and its implications with ecosystem services in the Ganges delta. With time agricultural lands have been decreased and wetlands have been increased at a very high rate mainly due to the growing popularity of saltwater shrimp farming. In a span of 28 years, the agricultural lands have been reduced by approximately 50%, while the wetlands have been increased by over 500%. A large portion (nearly 40%) of the study area is covered by the Sundarbans which remained almost constant which can be attributed to the strict regulatory intervention to preserve the Sundarbans. The settlement & others land use type has also been increased to nearly 5%. There is a gradual uptrend of shrimp and fish production in the study area. The findings suggest that there are significant linkages between agricultural land use change and ecosystem services in the Ganges delta in Bangladesh. The continuous decline of agricultural land (due to salinization) and an increase of wetland have been attributed to the conversion of agricultural land into shrimp farming in the study area. Such land use change requires significant capital, therefore, only investors and wealthier land owners can get the higher profit from the land conversion while the poor people is left with the environmental consequences that affect their long-term lives and livelihood. An environmental management plan is proposed for sustainable land use in the Ganges delta in Bangladesh. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. 12 CFR 619.9025 - Agricultural land.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Agricultural land. 619.9025 Section 619.9025 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM DEFINITIONS § 619.9025 Agricultural land. Land improved or unimproved which is devoted to or available for the production of crops and other...

  5. 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.

  6. Space-based monitoring of land-use/land-cover in the Upper Rio Grande Basin: An opportunity for understanding urbanization trends in a water-scarce transboundary river basin.

    NASA Astrophysics Data System (ADS)

    Mubako, S. T.; Hargrove, W. L.; Heyman, J. M.; Reyes, C. S.

    2016-12-01

    Urbanization is an area of growing interest in assessing the impact of human activities on water resources in arid regions. Remote sensing techniques provide an opportunity to analyze land cover change over time, and are useful in monitoring areas undergoing rapid urban growth. This case study for the water-scarce Upper Rio Grande River Basin uses a supervised classification algorithm to quantify the rate and evaluate the pattern of urban sprawl. A focus is made on the fast growing El-Paso-Juarez metropolitan area on the US-Mexico border and the City of Las Cruces in New Mexico, areas where environmental challenges and loss of agricultural and native land to urban development are major concerns. Preliminary results show that the land cover is dominantly native with some significant agriculture along the Rio Grande River valley. Urban development across the whole study area expanded from just under 3 percent in 1990, to more than 11 percent in 2015. The urban expansion is occurring mainly around the major urban areas of El Paso, Ciudad Juarez, and Las Cruces, although there is visible growth of smaller urban settlements scattered along the Rio Grande River valley during the same analysis period. The proportion of native land cover fluctuates slightly depending on how much land is under crops each analysis year, but there is a decreasing agricultural land cover trend suggesting that land from this sector is being lost to urban development. This analysis can be useful in planning to protect the environment, preparing for growth in infrastructure such as schools, increased traffic demands, and monitoring availability of resources such as groundwater as the urban population grows.

  7. Land Cover Monitoring for Water Resources Management in Angola

    NASA Astrophysics Data System (ADS)

    Miguel, Irina; Navarro, Ana; Rolim, Joao; Catalao, Joao; Silva, Joel; Painho, Marco; Vekerdy, Zoltan

    2016-08-01

    The aim of this paper is to assess the impact of improved temporal resolution and multi-source satellite data (SAR and optical) on land cover mapping and monitoring for efficient water resources management. For that purpose, we developed an integrated approach based on image classification and on NDVI and SAR backscattering (VV and VH) time series for land cover mapping and crop's irrigation requirements computation. We analysed 28 SPOT-5 Take-5 images with high temporal revisiting time (5 days), 9 Sentinel-1 dual polarization GRD images and in-situ data acquired during the crop growing season. Results show that the combination of images from different sources provides the best information to map agricultural areas. The increase of the images temporal resolution allows the improvement of the estimation of the crop parameters, and then, to calculate of the crop's irrigation requirements. However, this aspect was not fully exploited due to the lack of EO data for the complete growing season.

  8. Impacts of land-use and land-cover change on stream hydrochemistry in the Cerrado and Amazon biomes.

    PubMed

    Nóbrega, Rodolfo L B; Guzha, Alphonce C; Lamparter, Gabriele; Amorim, Ricardo S S; Couto, Eduardo G; Hughes, Harold J; Jungkunst, Hermann F; Gerold, Gerhard

    2018-09-01

    Studies on the impacts of land-use and land-cover change on stream hydrochemistry in active deforestation zones of the Amazon agricultural frontier are limited and have often used low-temporal-resolution datasets. Moreover, these impacts are not concurrently assessed in well-established agricultural areas and new deforestations hotspots. We aimed to identify these impacts using an experimental setup to collect high-temporal-resolution hydrological and hydrochemical data in two pairs of low-order streams in catchments under contrasting land use and land cover (native vegetation vs. pasture) in the Amazon and Cerrado biomes. Our results indicate that the conversion of natural landscapes to pastures increases carbon and nutrient fluxes via streamflow in both biomes. These changes were the greatest in total inorganic carbon in the Amazon and in potassium in the Cerrado, representing a 5.0- and 5.5-fold increase in the fluxes of each biome, respectively. We found that stormflow, which is often neglected in studies on stream hydrochemistry in the tropics, plays a substantial role in the carbon and nutrient fluxes, especially in the Amazon biome, as its contributions to hydrochemical fluxes are mostly greater than the volumetric contribution to the total streamflow. These findings demonstrate that assessments of the impacts of deforestation in the Amazon and Cerrado biomes should also take into account rapid hydrological pathways; however, this can only be achieved through collection of high-temporal-resolution data. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. 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-...

  10. Climate change - Agricultural land use - Food security

    NASA Astrophysics Data System (ADS)

    Nagy, János; Széles, Adrienn

    2015-04-01

    change contributes to the proliferation of the pests of agricultural produces, the spreading of diseases and the development of new pathogens, while it could also increase the food risk caused by bacterial infection during the food chain phase between the producer and the consumer. Climate change has an impact on the world's food prices, especially that of cereals. The food production of the world needs to be doubled in order to cover the need of the population by 2050, especially if it rises above nine billion. As a result of the increase of population, there is an increased demand for agricultural products and it also necessitates the more efficient use of agricultural lands. As a consequence of increasing food prices, there is a risk of increased starvation and food consumption may decrease (especially in developing countries), while the health care inequality is expected to grow. Food security is one of the most important elements of adapting to global climate change. For this reason, it is extremely important to breed new biological resources, as well as to introduce production systems which facilitate the adaptation to changed circumstances.

  11. Aligning land use with land potential: The role of integrated agriculture

    USDA-ARS?s Scientific Manuscript database

    Contemporary agricultural land use is dominated by an emphasis on provisioning services by applying energy-intensive inputs through relatively uniform production systems across variable landscapes. This approach to agricultural land use is not sustainable. Achieving sustainable use of agricultural...

  12. 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.

  13. 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.

  14. 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.

  15. Seasonal land-cover regions of the United States

    USGS Publications Warehouse

    Loveland, Thomas R.; Merchant, James W.; Brown, Jesslyn F.; Ohlen, Donald O.; Reed, Bradley C.; Olson, Paul; Hutchinson, John

    1995-01-01

    Global-change investigations have been hindered by deficiencies in the availability and quality of land-cover data. The U.S. Geological Survey and the University of Nebraska-Lincoln have collaborated on the development of a new approach to land-cover characterization that attempts to address requirements of the global-change research community and others interested in regional patterns of land cover. An experimental 1 -kilometer-resolution database of land-cover characteristics for the coterminous U.S. has been prepared to test and evaluate the approach. Using multidate Advanced Very High Resolution Radiometer (AVHRR) satellite data complemented by elevation, climate, ecoregions, and other digital spatial datasets, the authors define 152, seasonal land-cover regions. The regionalization is based on a taxonomy of areas with respect to data on land cover, seasonality or phenology, and relative levels of primary production. The resulting database consists of descriptions of the vegetation, land cover, and seasonal, spectral, and site characteristics for each region. These data are used in the construction of an illustrative 1:7,500,000-scaIe map of the seasonal land-cover regions as well as of smaller-scale maps portraying general land cover and seasonality. The seasonal land-cover characteristics database can also be tailored to provide a broad range of other landscape parameters useful in national and global-scale environmental modeling and assessment.

  16. Land-use change affects water recycling in Brazil's last agricultural frontier.

    PubMed

    Spera, Stephanie A; Galford, Gillian L; Coe, Michael T; Macedo, Marcia N; Mustard, John F

    2016-10-01

    Historically, conservation-oriented research and policy in Brazil have focused on Amazon deforestation, but a majority of Brazil's deforestation and agricultural expansion has occurred in the neighboring Cerrado biome, a biodiversity hotspot comprised of dry forests, woodland savannas, and grasslands. Resilience of rainfed agriculture in both biomes likely depends on water recycling in undisturbed Cerrado vegetation; yet little is known about how changes in land-use and land-cover affect regional climate feedbacks in the Cerrado. We used remote sensing techniques to map land-use change across the Cerrado from 2003 to 2013. During this period, cropland agriculture more than doubled in area from 1.2 to 2.5 million ha, with 74% of new croplands sourced from previously intact Cerrado vegetation. We find that these changes have decreased the amount of water recycled to the atmosphere via evapotranspiration (ET) each year. In 2013 alone, cropland areas recycled 14 km(3) less (-3%) water than if the land cover had been native Cerrado vegetation. ET from single-cropping systems (e.g., soybeans) is less than from natural vegetation in all years, except in the months of January and February, the height of the growing season. In double-cropping systems (e.g., soybeans followed by corn), ET is similar to or greater than natural vegetation throughout a majority of the wet season (December-May). As intensification and extensification of agricultural production continue in the region, the impacts on the water cycle and opportunities for mitigation warrant consideration. For example, if an environmental goal is to minimize impacts on the water cycle, double cropping (intensification) might be emphasized over extensification to maintain a landscape that behaves more akin to the natural system. © 2016 John Wiley & Sons Ltd.

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

    NASA Astrophysics Data System (ADS)

    Jeuck, James A.

    This dissertation consists of research projects related to forest land use / land cover (LULC): (1) factors predicting LULC change and (2) methodology to predict particular forest use, or "potential working timberland" (PWT), from current forms of land data. The first project resulted in a published paper, a meta-analysis of 64 econometric models from 47 studies predicting forest land use changes. The response variables, representing some form of forest land change, were organized into four groups: forest conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified, from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratio estimates were developed based on (1) proportion of times independent variables successfully achieved statistical significance (p ≤0.10), and (2) proportion of times independent variables successfully met the original researchers'expectations. In F2D models, popular independent variables such as population, income, and urban proximity often achieved statistical significance. In F2A models, popular independent variables such as forest and agricultural rents and costs, governmental programs, and site quality often achieved statistical significance. In U2D models, successful independent variables included urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. F2NF models high success variables were found to be agricultural rents, site quality, population, and income. This meta

  18. A prototype for automation of land-cover products from Landsat Surface Reflectance Data Records

    NASA Astrophysics Data System (ADS)

    Rover, J.; Goldhaber, M. B.; Steinwand, D.; Nelson, K.; Coan, M.; Wylie, B. K.; Dahal, D.; Wika, S.; Quenzer, R.

    2014-12-01

    Landsat data records of surface reflectance provide a three-decade history of land surface processes. Due to the vast number of these archived records, development of innovative approaches for automated data mining and information retrieval were necessary. Recently, we created a prototype utilizing open source software libraries for automatically generating annual Anderson Level 1 land cover maps and information products from data acquired by the Landsat Mission for the years 1984 to 2013. The automated prototype was applied to two target areas in northwestern and east-central North Dakota, USA. The approach required the National Land Cover Database (NLCD) and two user-input target acquisition year-days. The Landsat archive was mined for scenes acquired within a 100-day window surrounding these target dates, and then cloud-free pixels where chosen closest to the specified target acquisition dates. The selected pixels were then composited before completing an unsupervised classification using the NLCD. Pixels unchanged in pairs of the NLCD were used for training decision tree models in an iterative process refined with model confidence measures. The decision tree models were applied to the Landsat composites to generate a yearly land cover map and related information products. Results for the target areas captured changes associated with the recent expansion of oil shale production and agriculture driven by economics and policy, such as the increase in biofuel production and reduction in Conservation Reserve Program. Changes in agriculture, grasslands, and surface water reflect the local hydrological conditions that occurred during the 29-year span. Future enhancements considered for this prototype include a web-based client, ancillary spatial datasets, trends and clustering algorithms, and the forecasting of future land cover.

  19. 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

  20. 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

  1. Examining Land-Use/Land-Cover Change in the Lake Dianchi Watershed of the Yunnan-Guizhou Plateau of Southwest China with Remote Sensing and GIS Techniques: 1974-2008

    PubMed Central

    Zhao, Yaolong; Zhang, Ke; Fu, Yingchun; Zhang, Hong

    2012-01-01

    Monitoring land-use/land-cover change (LULCC) and exploring its mechanisms are important processes in the environmental management of a lake watershed. The purpose of this study was to examine the spatiotemporal pattern of LULCC by using multi landscape metrics in the Lake Dianchi watershed, which is located in the Yunnan-Guizhou Plateau of Southwest China. Landsat images from the years 1974, 1988, 1998, and 2008 were analyzed using geographical information system (GIS) techniques. The results reveal that land-use/land-cover has changed greatly in the watershed since 1974. This change in land use structure was embodied in the rapid increase of developed areas with a relative change rate of up to 324.4%. The increase in developed areas mainly occurred in agricultural land, especially near the shores of Lake Dianchi. The spatial pattern and structure of the change was influenced by the urban sprawl of the city of Kunming. The urban sprawl took on the typical expansion mode of cyclic structures and a jigsaw pattern and expanded to the shore of Lake Dianchi. Agricultural land changed little with respect to the structure but changed greatly in the spatial pattern. The landscape in the watershed showed a trend of fragmentation with a complex boundary. The dynamics of land-use/land-cover in the watershed correlate with land-use policies and economic development in China. PMID:23202820

  2. 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...

  3. 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.

  4. 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.

  5. 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

  6. Attempt at quantifying human-induced land-cover change during the Holocene in central eastern China

    NASA Astrophysics Data System (ADS)

    Li, Furong; Gaillard, Marie-José; Mazier, Florence; Sugita, Shinya; Xu, Qinghai; Li, Yuecong; Zhou, Zhongze

    2016-04-01

    China is one of the key regions of the world where agricultural civilizations already flourished several millennia ago. However, the role of human activity in vegetation change is not yet fully understood. As a contribution to the PAGES LandCover6k initiative, this study aims to achieve a first attempt at Holocene land-cover reconstructions in the temperate zone of China using the REVEALS model (Sugita, 2007). Pollen productivity estimates (PPEs) are key parameters required for the model and were lacking so far for major taxa characteristic of ancient cultural landscapes in that part of the world. Remains of traditional agricultural structures and practices are still found in the low mountain ranges of the Shandong province located in central-eastern China. The area was chosen for a study of pollen-vegetation relationships and calculation of pollen productivity estimates. Pollen counts and vegetation data from 37 random sites within an area of 200 x 100 km are used for calculation. The vegetation inventory within 100 meters from the pollen sampling site follows the standard methods of Bunting et al. (2013). Vegetation data beyond 100 meters up to 1.5 km from the pollen sampling site is extracted from satellite images. The PPEs are calculated using the three sub-models of the Extended R-value model and compared with existing PPEs from northern China's biomes and temperate Europe. The PPEs' relevance for reconstruction of past human-induced land-cover change in temperate China are evaluated. Key words China, traditional agricultural landscape, ERV model, pollen productivity estimates References Bunting, M. J., et al. (2013). "Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover." Quaternary Science Reviews 82: 41-55. Sugita, S. (2007). "Theory of quantitative reconstruction of vegetation I: pollen from large sites REVEALS regional vegetation composition." The Holocene 17(2): 229-241.

  7. EnviroAtlas -Pittsburgh, PA- One Meter Resolution Urban Land Cover Data (2010)

    EPA Pesticide Factsheets

    The EnviroAtlas Pittsburgh, PA land cover map was generated from United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP) four band (red, green, blue, and near infrared) aerial photography at 1 m spatial resolution. Imagery was collected on multiple dates in June 2010. Five land cover classes were mapped: water, impervious surfaces, soil and barren land, trees and forest, and grass and herbaceous non-woody vegetation. An accuracy assessment of 500 completely random and 81 stratified random points yielded an overall accuracy of 86.57 percent. The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Pittsburgh, PA. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  8. Quantification of land cover and land use within the rural complex of the Democratic Republic of Congo

    NASA Astrophysics Data System (ADS)

    Molinario, G.; Hansen, M. C.; Potapov, P. V.; Tyukavina, A.; Stehman, S.; Barker, B.; Humber, M.

    2017-10-01

    The rural complex is the inhabited agricultural land cover mosaic found along the network of rivers and roads in the forest of the Democratic Republic of Congo. It is a product of traditional small-holder shifting cultivation. To date, thanks to its distinction from primary forest, this area has been mapped as relatively homogenous, leaving the proportions of land cover heterogeneity within it unknown. However, the success of strategies for sustainable development, including land use planning and payment for ecosystem services, such as Reduced Emissions from Deforestation and Degradation, depends on the accurate characterization of the impacts of land use on natural resources, including within the rural complex. We photo-interpreted a simple random sample of 1000 points in the established rural complex, using 3106 high resolution satellite images obtained from the National Geospatial-Intelligence Agency, together with 406 images from Google Earth, spanning the period 2008-2016. Results indicate that nationally the established rural complex includes 5% clearings, 10% active fields, 26% fallows, 34% secondary forest, 2% wetland forest, 11% primary forest, 6% grasslands, 3% roads and settlements and 2% commercial plantations. Only a small proportion of sample points were plantations, while other commercial dynamics, such as logging and mining, were not detected in the sample. The area of current shifting cultivation accounts for 76% of the established rural complex. Added to primary forest (11%), this means that 87% of the rural complex is available for shifting cultivation. At the current clearing rate, it would take ~18 years for a complete rotation of the rural complex to occur. Additional pressure on land results in either the cultivation of non-preferred land types within the rural complex (such as wetland forest), or expansion of agriculture into nearby primary forests, with attendant impacts on emissions, habitat loss and other ecosystems services.

  9. Integration of land use and land cover inventories for landscape management and planning in Italy.

    PubMed

    Sallustio, Lorenzo; Munafò, Michele; Riitano, Nicola; Lasserre, Bruno; Fattorini, Lorenzo; Marchetti, Marco

    2016-01-01

    There are both semantic and technical differences between land use (LU) and land cover (LC) measurements. In cartographic approaches, these differences are often neglected, giving rise to a hybrid classification. The aim of this paper is to provide a better understanding and characterization of the two classification schemes using a comparison that allows maximization of the informative power of both. The analysis was carried out in the Molise region (Central Italy) using sample information from the Italian Land Use Inventory (IUTI). The sampling points were classified with a visual interpretation of aerial photographs for both LU and LC in order to estimate surfaces and assess the changes that occurred between 2000 and 2012. The results underscore the polarization of land use and land cover changes resulting from the following: (a) recolonization of natural surfaces, (b) strong dynamisms between the LC classes in the natural and semi-natural domain and (c) urban sprawl on the lower hills and plains. Most of the observed transitions are attributable to decreases in croplands, natural grasslands and pastures, owing to agricultural abandonment. The results demonstrate that a comparison between LU and LC estimates and their changes provides an understanding of the causes of misalignment between the two criteria. Such information may be useful for planning policies in both natural and semi-natural contexts as well as in urban areas.

  10. 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...

  11. 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.

  12. Thematic accuracy assessment of the 2011 National Land Cover Database (NLCD)

    USGS Publications Warehouse

    Wickham, James; Stehman, Stephen V.; Gass, Leila; Dewitz, Jon; Sorenson, Daniel G.; Granneman, Brian J.; Poss, Richard V.; Baer, Lori Anne

    2017-01-01

    Accuracy assessment is a standard protocol of National Land Cover Database (NLCD) mapping. Here we report agreement statistics between map and reference labels for NLCD 2011, which includes land cover for ca. 2001, ca. 2006, and ca. 2011. The two main objectives were assessment of agreement between map and reference labels for the three, single-date NLCD land cover products at Level II and Level I of the classification hierarchy, and agreement for 17 land cover change reporting themes based on Level I classes (e.g., forest loss; forest gain; forest, no change) for three change periods (2001–2006, 2006–2011, and 2001–2011). The single-date overall accuracies were 82%, 83%, and 83% at Level II and 88%, 89%, and 89% at Level I for 2011, 2006, and 2001, respectively. Many class-specific user's accuracies met or exceeded a previously established nominal accuracy benchmark of 85%. Overall accuracies for 2006 and 2001 land cover components of NLCD 2011 were approximately 4% higher (at Level II and Level I) than the overall accuracies for the same components of NLCD 2006. The high Level I overall, user's, and producer's accuracies for the single-date eras in NLCD 2011 did not translate into high class-specific user's and producer's accuracies for many of the 17 change reporting themes. User's accuracies were high for the no change reporting themes, commonly exceeding 85%, but were typically much lower for the reporting themes that represented change. Only forest loss, forest gain, and urban gain had user's accuracies that exceeded 70%. Lower user's accuracies for the other change reporting themes may be attributable to the difficulty in determining the context of grass (e.g., open urban, grassland, agriculture) and between the components of the forest-shrubland-grassland gradient at either the mapping phase, reference label assignment phase, or both. NLCD 2011 user's accuracies for forest loss, forest gain, and urban gain compare favorably with results from other

  13. 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...

  14. Sensitivity of MODIS evapotranspiration algorithm (MOD16) to the acuracy of meteorological data and land use and land cover parameterization

    NASA Astrophysics Data System (ADS)

    Ruhoff, Anderson; Santini Adamatti, Daniela

    2017-04-01

    MODIS evapotranspiration (MOD16) is currently available with 1 km of spatial resolution over 109.03 Million km2 of vegetated land surface areas and this information is widely used to evaluate the linkages between hydrological, energy and carbon cycles. The algorithm is driven by meteorological reanalysis data and MODIS remotely-sensed data, which include land use and land cover classification (MCD12Q1), leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) (MOD15A2) and albedo (MOD43b3). For calibration and parameterization, the algorithm uses a Biome Property Look-up Table (BPLUT) based on MCD12Q1 land cover classification. Several studies evaluated MOD16 accuracy using evapotranspiration measurements and water balance analysis, showing that this product can reproduce global evapotranspiration effectively under a variety climate condition, from local to wide-basin scale, with uncertainties up to 25%. In this study, we evaluated the sensitivity of MOD16 algorithm to land use and land cover parameterization and to meteorological data. Considering that MCD12Q1 has an accuracy between 70 and 85% at continental scale, we changed land cover parametererization to understand the influence of land use and land cover classification on MOD16 evapotranspiration estimations. Knowing that meteorological reanalysis data also have uncertainties (mostly related to the coarse spatial resolution), we compared MOD16 evapotranspiration driven by observed meteorological data to those driven by the reanalysis data. Our analysis were carried in South America, with evapotranspiration and meteorological measurements from the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) at 8 different sites, including tropical rainforest, tropical dry forest, selective logged forest, seasonal flooded forest and pasture/agriculture. Our results indicate that land use and land cover classification has a strong influence on MOD16 algorithm. The use of

  15. Local- and landscape-scale land cover affects microclimate and water use in urban gardens.

    PubMed

    Lin, Brenda B; Egerer, Monika H; Liere, Heidi; Jha, Shalene; Bichier, Peter; Philpott, Stacy M

    2018-01-01

    Urban gardens in Central California are highly vulnerable to the effects of climate change, experiencing both extended high heat periods as well as water restrictions because of severe drought conditions. This puts these critical community-based food production systems at risk as California is expected to experience increasing weather extremes. In agricultural systems, increased vegetation complexity, such as greater structure or biodiversity, can increase the resilience of food production systems from climate fluctuations. We test this theory in 15 urban gardens across California's Central Coast. Local- and landscape-scale measures of ground, vegetation, and land cover were collected in and around each garden, while climate loggers recorded temperatures in each garden in 30min increments. Multivariate analyses, using county as a random factor, show that both local- and landscape-scale factors were important. All factors were significant predictors of mean temperature. Tallest vegetation, tree/shrub species richness, grass cover, mulch cover, and landscape level agricultural cover were cooling factors; in contrast, garden size, garden age, rock cover, herbaceous species richness, and landscape level urban cover were warming factors. Results were similar for the maximum temperature analysis except that agriculture land cover and herbaceous species richness were not significant predictors of maximum temperature. Analysis of gardener watering behavior to observed temperatures shows that garden microclimate was significantly related to the number of minutes watered as well as the number of liters of water used per watering event. Thus gardeners seem to respond to garden microclimate in their watering behavior even though this behavior is most probably motivated by a range of other factors such as water regulations and time availability. This research shows that local management of ground cover and vegetation can reduce mean and maximum temperatures in gardens, and the

  16. Development of deforestation and land cover database for Bhutan (1930-2014).

    PubMed

    Reddy, C Sudhakar; Satish, K V; Jha, C S; Diwakar, P G; Murthy, Y V N Krishna; Dadhwal, V K

    2016-12-01

    Bhutan is a mountainous country located in the Himalayan biodiversity hotspot. This study has quantified the total area under land cover types, estimated the rate of forest cover change, analyzed the changes across forest types, and modeled forest cover change hotpots in Bhutan. The topographical maps and satellite remote sensing images were analyzed to get the spatial patterns of forest and associated land cover changes over the past eight decades (1930-1977-1987-1995-2005-2014). Forest is the largest land cover in Bhutan and constitutes 68.3% of the total geographical area in 2014. Subtropical broad leaved hill forest is predominant type occupies 34.1% of forest area in Bhutan, followed by montane dry temperate (20.9%), montane wet temperate (18.9%), Himalayan moist temperate (10%), and tropical moist sal (8.1%) in 2014. The major forest cover loss is observed in subtropical broad leaved hill forest (64.5 km 2 ) and moist sal forest (9.9 km 2 ) from 1977 to 2014. The deforested areas have mainly been converted into agriculture and contributed for 60.9% of forest loss from 1930 to 2014. In spite of major decline of forest cover in time interval of 1930-1977, there is no net rate of deforestation is recorded in Bhutan since 1995. Forest cover change analysis has been carried out to evaluate the conservation effectiveness in "Protected Areas" of Bhutan. Hotspots that have undergone high transformation in forest cover for afforestation and deforestation were highlighted in the study for conservation prioritisation. Forest conservation policies in Bhutan are highly effective in controlling deforestation as compared to neighboring Asian countries and such service would help in mitigating climate change.

  17. Examining land-use/land-cover change in the Lake Dianchi watershed of the Yunnan-Guizhou Plateau of Southwest China with remote sensing and GIS techniques: 1974–2008.

    PubMed

    Zhao, Yaolong; Zhang, Ke; Fu, Yingchun; Zhang, Hong

    2012-10-24

    Monitoring land-use/land-cover change (LULCC) and exploring its mechanisms are important processes in the environmental management of a lake watershed. The purpose of this study was to examine the spatiotemporal pattern of LULCC by using multi landscape metrics in the Lake Dianchi watershed, which is located in the Yunnan-Guizhou Plateau of Southwest China. Landsat images from the years 1974, 1988, 1998, and 2008 were analyzed using geographical information system (GIS) techniques. The results reveal that land-use/land-cover has changed greatly in the watershed since 1974. This change in land use structure was embodied in the rapid increase of developed areas with a relative change rate of up to 324.4%. The increase in developed areas mainly occurred in agricultural land, especially near the shores of Lake Dianchi. The spatial pattern and structure of the change was influenced by the urban sprawl of the city of Kunming. The urban sprawl took on the typical expansion mode of cyclic structures and a jigsaw pattern and expanded to the shore of Lake Dianchi. Agricultural land changed little with respect to the structure but changed greatly in the spatial pattern. The landscape in the watershed showed a trend of fragmentation with a complex boundary. The dynamics of land-use/land-cover in the watershed correlate with land-use policies and economic development in China.

  18. 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.

  19. 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.

  20. EnviroAtlas -- Memphis, TN (2012) -- One Meter Resolution Urban Land Cover Data

    EPA Pesticide Factsheets

    The Memphis, TN EnviroAtlas One Meter-scale Urban Land Cover (MULC) dataset comprises 2,733 km2 around the city of Memphis, surrounding towns, and rural areas. These leaf-on LC data and maps were derived from 1-m pixel, four-band (red, green, blue, and near-infrared) aerial photography acquired from the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) on four dates in 2012: June 15, June 18, June 21 and June 23, and one date in 2013: July 12. Three separate LiDAR (Light Detection and Ranging) data sets collected on February 19, 2009 00e2?? August 2, 2010, December 1-2, 2011 and January 23-24, 2012 were integrated for Shelby Co., TN, Crittenden Co., AR, and DeSoto Co, MS. Five MULC classes were mapped directly from the NAIP and LiDAR data: Water, Impervious, Soil, Trees, and Grass/Herbaceous. Agriculture was derived from USDA Common Land Unit (CLU) data. Woody and emergent wetlands were copied from existing National Wetlands Inventory (NWI) data. Analysis of a random sampling of 612 photo-interpreted land cover reference points yielded an overall users accuracy of 86.9%. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as do

  1. 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 ...

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. Assessing the effects of land use/cover change on carbon dioxide fluxes in a semiarid shrubland

    NASA Astrophysics Data System (ADS)

    Gong, Tingting; Lei, Huimin; Yang, Dawen; Jiao, Yang; Yang, Hanbo

    2017-04-01

    Land use/cover change has been generally considered a local environmental issue. Our study focuses on the effects of land use/cover change on the carbon cycle using long-term continuous field observation data, which is measured by the eddy covariance (EC) technique. The study site is at Yulin (38.45N, 109.47E), which is a desert shrubland ecosystem in Mu Us sandland, China. Before June 2012, the vegetation in this site was covered with mixed vegetation: typical desert shrubs (e.g., Salix psammophila and Artemisia ordosica) and grass. After July 2012, a part of the land use/cover condition within the footprint was changed by the local farmers, which converted the land use/cover condition changed first from mixed vegetation to bare soil and then from bare soil to grassland resulting from the re-growing grass. Four-year carbon fluxes are selected and separated into three periods: Period I is from July 1 2011 to June 30 2012 when land use/cover condition did not change; Period II is from July 1 2012 to June 30 2014 when land use/cover condition changed from mixed vegetation (shrubs and grass) to the mix of bare soil and desert shrubs; Period III is from July 1 2014 to June 30 2015 when land use/cover condition changed from the mix of desert shrubs and bare soil to the mix of desert shrubs and re-growing grass. A linear statistical model will be used to evaluate and quantify the effects of land use/cover change on the uptake or release of carbon fluxes (net ecosystem exchange (NEE), ecosystem respiration (Reco) and gross primary production (GPP)). Moreover, this study is expected to get insights into how agricultural cultivation influences on the local carbon balance (e.g., how NEE, Reco and GPP respond to the land use/cover change; Is the annual carbon balance changed during the land use/cover change process; and the contribution of land use/cover change on these changes of carbon fluxes).

  7. Prospects for land-use sustainability on the agricultural frontier of the Brazilian Amazon.

    PubMed

    Galford, Gillian L; Soares-Filho, Britaldo; Cerri, Carlos E P

    2013-06-05

    The Brazilian Amazon frontier shows how remarkable leadership can work towards increased agricultural productivity and environmental sustainability without new greenhouse gas emissions. This is due to initiatives among various stakeholders, including national and state government and agents, farmers, consumers, funding agencies and non-governmental organizations. Change has come both from bottom-up and top-down actions of these stakeholders, providing leadership, financing and monitoring to foster environmental sustainability and agricultural growth. Goals to reduce greenhouse gas emissions from land-cover and land-use change in Brazil are being achieved through a multi-tiered approach that includes policies to reduce deforestation and initiatives for forest restoration, as well as increased and diversified agricultural production, intensified ranching and innovations in agricultural management. Here, we address opportunities for the Brazilian Amazon in working towards low-carbon rural development and environmentally sustainable landscapes.

  8. Prospects for land-use sustainability on the agricultural frontier of the Brazilian Amazon

    PubMed Central

    Galford, Gillian L.; Soares-Filho, Britaldo; Cerri, Carlos E. P.

    2013-01-01

    The Brazilian Amazon frontier shows how remarkable leadership can work towards increased agricultural productivity and environmental sustainability without new greenhouse gas emissions. This is due to initiatives among various stakeholders, including national and state government and agents, farmers, consumers, funding agencies and non-governmental organizations. Change has come both from bottom-up and top-down actions of these stakeholders, providing leadership, financing and monitoring to foster environmental sustainability and agricultural growth. Goals to reduce greenhouse gas emissions from land-cover and land-use change in Brazil are being achieved through a multi-tiered approach that includes policies to reduce deforestation and initiatives for forest restoration, as well as increased and diversified agricultural production, intensified ranching and innovations in agricultural management. Here, we address opportunities for the Brazilian Amazon in working towards low-carbon rural development and environmentally sustainable landscapes. PMID:23610175

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  10. The role of protected areas in land use/land cover change and the carbon cycle in the conterminous United States

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

    Lu, Xiaoliang; Zhou, Yuyu; Liu, Yaling

    Protected areas (PAs) cover about 22% of the conterminous United States. Understanding their role on historical land use and land cover change (LULCC) and on the carbon cycle is essential to provide guidance for environmental policies. In this study, we compiled historical LULCC and PAs data to explore these interactions within the terrestrial ecosystem model (TEM). We found that intensive LULCC occurred in the conterminous United States from 1700 to 2005. More than 3 million km2 of forest, grassland and shrublands were converted into agricultural lands, which caused 10,607 Tg C release from land ecosystems to atmosphere. PAs had experiencedmore » little LULCC as they were generally established in the 20th century after most of the agricultural expansion had occurred. PAs initially acted as a carbon source due to land use legacies, but their accumulated carbon budget switched to a carbon sink in the 1960s, sequestering an estimated 1,642 Tg C over 1700–2005, or 13.4% of carbon losses in non-PAs. We also find that PAs maintain larger carbon stocks and continue sequestering carbon in recent years (2001–2005), but at a lower rate due to increased heterotrophic respiration as well as lower productivity associated to aging ecosystems. It is essential to continue efforts to maintain resilient, biodiverse ecosystems and avoid large-scale disturbances that would release large amounts of carbon in PAs.« less

  11. Hydrochemistry and land cover in the upper Naryn river basin, Kyrgyzstan

    NASA Astrophysics Data System (ADS)

    Schneider, K.; Dernedde, Y.; Breuer, L.; Frede, H. G.

    2009-04-01

    concentrations remain below detection limit for the most part. The study shows that tributaries of high electrical conductivity do not affect hydrochemistry of the main river during summer because glacier and snow melt dominates runoff generation. Daily cycles of increased runoff due to snow and ice melt in the afternoon could be observed along the tributaries in the upper parts of the study area. Effects of agricultural production on ecohydrology remain weak as application of fertilizers and pesticides is currently low due to financial constraints. The data will be linked to land use data derived from satellite image products in order to analyse the effect of land cover and land cover changes on ecohydrological processes. Former observation of remote sensing data and related literature showed evidence for a change in land use management in the Naryn Valley. In 2008 training areas of land use classes for a supervised classification of 2008 remote sensing data have been recorded. A land use classification of the Naryn Valley on the base of Landsat ETM+ Data of 2008 and 1993 was done to get information on land use change on a regional scale. The classification uses spectral and spatial data in a hard classifier and object oriented combined approach. Comparing the two datasets with respect to changes in pattern of irrigated area and pasture area, change in cultivated crops and the change of agricultural cell sizes gives further information for hydrological modeling and land use monitoring purposes.

  12. Stream fish occurrence in response to impervious cover, historic land use, and hydrogeomorphic factors

    USGS Publications Warehouse

    Wenger, Seth J.; Peterson, James T.; Freeman, Mary C.; Freeman, Byron J.; Homans, D. David

    2008-01-01

    We evaluated competing models explaining the occurrence of five stream fishes in an urbanizing watershed to determine the relative importance of (a) impervious surface and other indicators of current land use, (b) historic land use (e.g., agriculture, impoundments), and (c) hydrogeomorphic characteristics (e.g., stream size, elevation, geology). For four of five species, the best-supported models were those that included both current effective impervious cover and historic land use predictor variables, although models with only effective impervious cover were equally well supported for two of those species. For the best-supported models for three species, occurrence probability was predicted to approach zero at levels of development equivalent to about 2%–4% effective impervious cover in the surrounding region. Data were drawn from 357 fish collections made in the Etowah River basin, Georgia, USA, between 1998 and 2003 and analyzed using hierarchical logistic regression accounting for imperfect species detection. This is the first study we know of to examine the response of individual fish species to both increasing impervious cover and historic land use. Such individual species assessments will be increasingly necessary to guide policies for managing urban effects and preventing extirpations of sensitive species.

  13. 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.

  14. Land Cover Change in Colombia: Surprising Forest Recovery Trends between 2001 and 2010

    PubMed Central

    Sánchez-Cuervo, Ana María; Aide, T. Mitchell; Clark, Matthew L.; Etter, Andrés

    2012-01-01

    Background Monitoring land change at multiple spatial scales is essential for identifying hotspots of change, and for developing and implementing policies for conserving biodiversity and habitats. In the high diversity country of Colombia, these types of analyses are difficult because there is no consistent wall-to-wall, multi-temporal dataset for land-use and land-cover change. Methodology/Principal Findings To address this problem, we mapped annual land-use and land-cover from 2001 to 2010 in Colombia using MODIS (250 m) products coupled with reference data from high spatial resolution imagery (QuickBird) in Google Earth. We used QuickBird imagery to visually interpret percent cover of eight land cover classes used for classifier training and accuracy assessment. Based on these maps we evaluated land cover change at four spatial scales country, biome, ecoregion, and municipality. Of the 1,117 municipalities, 820 had a net gain in woody vegetation (28,092 km2) while 264 had a net loss (11,129 km2), which resulted in a net gain of 16,963 km2 in woody vegetation at the national scale. Woody regrowth mainly occurred in areas previously classified as mixed woody/plantation rather than agriculture/herbaceous. The majority of this gain occurred in the Moist Forest biome, within the montane forest ecoregions, while the greatest loss of woody vegetation occurred in the Llanos and Apure-Villavicencio ecoregions. Conclusions The unexpected forest recovery trend, particularly in the Andes, provides an opportunity to expand current protected areas and to promote habitat connectivity. Furthermore, ecoregions with intense land conversion (e.g. Northern Andean Páramo) and ecoregions under-represented in the protected area network (e.g. Llanos, Apure-Villavicencio Dry forest, and Magdalena-Urabá Moist forest ecoregions) should be considered for new protected areas. PMID:22952816

  15. Earth observation data for assessment of nationwide land cover and long-term deforestation in Afghanistan

    NASA Astrophysics Data System (ADS)

    Sudhakar Reddy, C.; Saranya, K. R. L.

    2017-08-01

    This study has generated a national level spatial database of land cover and changes in forest cover of Afghanistan for the 1975-1990, 1990-2005 and 2005-2014 periods. Using these results we have analysed the annual deforestation rates, spatial changes in forests, forest types and fragmentation classes over a period of 1975 to 2014 in Afghanistan. The land cover map of 2014 provides distribution of forest (dry evergreen, moist temperate, dry temperate, pine, sub alpine) and non-forest (grassland, scrub, agriculture, wetlands, barren land, snow and settlements) in Afghanistan. The largest land cover, barren land, contributes to 56% of geographical area of country. Forest is distributed mostly in eastern Afghanistan and constitutes an area of 1.02% of geographical area in 2014. The annual deforestation rate in Afghanistan's forests for the period from 1975 to 1990 estimated as 0.06% which was declined significantly from 2005 to 2014. The predominant forest type in Afghanistan is moist temperate which shows loss of 80 km2 of area during the last four decades of the study period. At national level, the percentage of large core forest area was calculated as 52.20% in 2014.

  16. Environmental, land cover and land use constraints on the distributional patterns of anurans: Leptodacylus species (Anura, Leptodactylidae) from Dry Chaco

    PubMed Central

    Medina, Regina Gabriela; Aráoz, Ezequiel

    2016-01-01

    Subtropical dry forests are among the most vulnerable biomes to land transformation at a global scale. Among them, the Dry Chaco suffers an accelerated change due to agriculture expansion and intensification. The Dry Chaco ecoregion is characterized by high levels of endemisms and species diversity, which are the result of a variety of climates and reliefs, allowing a wide variety of environments. The amphibian group exhibits a high richness in the Dry Chaco, which has been barely studied in relation to land cover changes. We used ecological niche models (ENMs) to assess the potential geographic distribution of 10 Leptodactylus species (Anura, Leptodactylidae), which are mainly distributed within the Dry Chaco. We characterized these distributions environmentally, analyzed their overlap with land cover classes, and assessed their diversity of ecoregions. Also, we evaluated how these species potential distribution is affected by the transformation of land, and quantified the proportional area of the potential distribution in protected areas. We found that temperature seasonality is the main constraint to the occurrence of the species studied, whose main habitats are savannas, grasslands and croplands. The main threats to these species are the effects of climate change over spatial patterns of seasonality, which could affect their breeding and reproduction mode; the loss of their natural habitat; the exposure to contaminants used by intensive agriculture and their underrepresentation in protected areas. PMID:27833796

  17. Environmental, land cover and land use constraints on the distributional patterns of anurans: Leptodacylus species (Anura, Leptodactylidae) from Dry Chaco.

    PubMed

    Medina, Regina Gabriela; Ponssa, Maria Laura; Aráoz, Ezequiel

    2016-01-01

    Subtropical dry forests are among the most vulnerable biomes to land transformation at a global scale. Among them, the Dry Chaco suffers an accelerated change due to agriculture expansion and intensification. The Dry Chaco ecoregion is characterized by high levels of endemisms and species diversity, which are the result of a variety of climates and reliefs, allowing a wide variety of environments. The amphibian group exhibits a high richness in the Dry Chaco, which has been barely studied in relation to land cover changes. We used ecological niche models (ENMs) to assess the potential geographic distribution of 10 Leptodactylus species (Anura, Leptodactylidae), which are mainly distributed within the Dry Chaco. We characterized these distributions environmentally, analyzed their overlap with land cover classes, and assessed their diversity of ecoregions. Also, we evaluated how these species potential distribution is affected by the transformation of land, and quantified the proportional area of the potential distribution in protected areas. We found that temperature seasonality is the main constraint to the occurrence of the species studied, whose main habitats are savannas, grasslands and croplands. The main threats to these species are the effects of climate change over spatial patterns of seasonality, which could affect their breeding and reproduction mode; the loss of their natural habitat; the exposure to contaminants used by intensive agriculture and their underrepresentation in protected areas.

  18. Do Surface Energy Fluxes Reveal Land Use/Land Cover Change in South Florida?: A Remote Sensing Perspective

    NASA Astrophysics Data System (ADS)

    Kandel, H. P.; Melesse, A. M.

    2017-12-01

    Series of changes on land use/ land cover in South Florida resulting from drainage and development activities during early to mid-20th followed by restoration measures since late-20th century have had prominent impacts on hydrologic regime and energy fluxes in the region. Previous results from numerical modeling and MODIS-based analysis have shown a shift in dominance of heat fluxes: from latent to sensible along the axes of urbanization, and an opposite along the axes of restoration. This study implements a slightly modified version of surface energy balance algorithm (SEBAL) on cloud-masked Landsat imageries archived over the period of 30-years combined with ground-meteorological data for South Florida using spatial analysis model in ArcGIS and calculates energy flux components: sensible heat flux, latent heat flux, and ground heat flux. The study finally computes variation of Bowen's ratio (BR) and daily evapotranspiration (ET) rate over various land covers for different years. Coexistences are apparent between increased BR and increased intensity of urbanization, and between increased daily ET rates and improved best management practices in agricultural areas. An increase in mean urban BR from 1.67 in 1984 to 3.06 in 2010 show plausible link of BR with urban encroachment of open lands, and expulsion of additional heat by increased population/automobiles/factories/air conditioning units. Likewise, increase in mean agricultural daily ET rates from 0.21 mm/day to 3.60 mm/day between 1984 to 2010 probably shows the effects of improved moisture conditions on the northern farm lands as the results of restoration practices. Once new observed data become available to corroborate these results, remote sensing methods-owing to their greater spatial and temporal details-can be used as assessment measures both for the progress of restoration evaluation and for the extent detection of human-induced climate change.

  19. Analysis of spatio-temporal land cover changes for hydrological impact assessment within the Nyando River Basin of Kenya.

    PubMed

    Olang, Luke Omondi; Kundu, Peter; Bauer, Thomas; Fürst, Josef

    2011-08-01

    The spatio-temporal changes in the land cover states of the Nyando Basin were investigated for auxiliary hydrological impact assessment. The predominant land cover types whose conversions could influence the hydrological response of the region were selected. Six Landsat images for 1973, 1986, and 2000 were processed to discern the changes based on a methodology that employs a hybrid of supervised and unsupervised classification schemes. The accuracy of the classifications were assessed using reference datasets processed in a GIS with the help of ground-based information obtained through participatory mapping techniques. To assess the possible hydrological effect of the detected changes during storm events, a physically based lumped approach for infiltration loss estimation was employed within five selected sub-basins. The results obtained indicated that forests in the basin declined by 20% while agricultural fields expanded by 16% during the entire period of study. Apparent from the land cover conversion matrices was that the majority of the forest decline was a consequence of agricultural expansion. The model results revealed decreased infiltration amounts by between 6% and 15%. The headwater regions with the vast deforestation were noted to be more vulnerable to the land cover change effects. Despite the haphazard land use patterns and uncertainties related to poor data quality for environmental monitoring and assessment, the study exposed the vast degradation and hence the need for sustainable land use planning for enhanced catchment management purposes.

  20. 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.

  1. Change in agricultural land use constrains adaptation of national wildlife refuges to climate change

    USGS Publications Warehouse

    Hamilton, Christopher M.; Thogmartin, Wayne E.; Radeloff, Volker C.; Plantinga, Andrew J.; Heglund, Patricia J.; Martinuzzi, Sebastian; Pidgeon, Anna M.

    2015-01-01

    Land-use change around protected areas limits their ability to conserve biodiversity by altering ecological processes such as natural hydrologic and disturbance regimes, facilitating species invasions, and interfering with dispersal of organisms. This paper informs USA National Wildlife Refuge System conservation planning by predicting future land-use change on lands within 25 km distance of 461 refuges in the USA using an econometric model. The model contained two differing policy scenarios, namely a ‘business-as-usual’ scenario and a ‘pro-agriculture’ scenario. Regardless of scenario, by 2051, forest cover and urban land use were predicted to increase around refuges, while the extent of range and pasture was predicted to decrease; cropland use decreased under the business-as-usual scenario, but increased under the pro-agriculture scenario. Increasing agricultural land value under the pro-agriculture scenario slowed an expected increase in forest around refuges, and doubled the rate of range and pasture loss. Intensity of land-use change on lands surrounding refuges differed by regions. Regional differences among scenarios revealed that an understanding of regional and local land-use dynamics and management options was an essential requirement to effectively manage these conserved lands. Such knowledge is particularly important given the predicted need to adapt to a changing global climate.

  2. 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

  3. Changes in land cover and vegetation carbon stocks in Andalusia, Southern Spain (1956-2007).

    PubMed

    Muñoz-Rojas, M; De la Rosa, D; Zavala, L M; Jordán, A; Anaya-Romero, M

    2011-06-15

    Land use has significantly changed during the recent decades at global and local scale, while the importance of ecosystems as sources/sinks of C has been highlighted, emphasizing the global impact of land use changes. Land use changes can increase C loss rates which are extremely difficult to reverse, in the short term, opposite to organic carbon (OC) which accumulates in soil in the long-term. The aim of this research is to improve and test methodologies to assess land cover change (LCC) dynamics and temporal and spatial variability in C stored in vegetation at a wide scale. LCCs between 1956 and 2007 in Andalusia (Southern Spain) were selected for this pilot study, assessed by comparison of spatial data from 1956 to 2007 and were reclassified following land cover flows (LCFs) reported in major areas in Europe. Carbon vegetation densities were related to land cover, and C vegetation stocks for 1956 and 2007 were calculated by multiplying C density for each land cover class with land cover areas. The study area has supported important changes during the studied period with significant consequences for vegetation C stocks, mainly due to afforestation and intensification of agriculture, resulting in a total vegetation C stock of 156.08Tg in 2007, with an increase of 17.24Tg since 1956. This study demonstrates the importance of LCC for C sequestration in vegetation from Mediterranean areas, highlighting possible directions for management policies in order to mitigate climate change as well as promoting land conservation. The methodologies and information generated in this project will be a useful basis for designing land management strategies helpful for decision makers. Copyright © 2011 Elsevier B.V. All rights reserved.

  4. Land cover controls on depression-focused recharge: an example from southern Ontario

    NASA Astrophysics Data System (ADS)

    Buttle, J. M.; Greenwood, W. J.

    2015-12-01

    The Oak Ridges Moraine (ORM) is a critical hydrogeologic feature in southern Ontario. Although previous research has highlighted the implications of spatially-focused recharge in closed topographic depressions for regional groundwater resources, such depression-focused recharge (DFR) has not been empirically demonstrated on the ORM. Permeable surficial sands and gravels mantling much of the ORM imply that water fluxes will largely be vertical recharge rather than lateral downslope transfer into depressions. Nevertheless, lateral fluxes may occur in winter and spring, when concrete frost development encourages surface runoff of rainfall and snowmelt. The potential for DFR was examined under forest and agricultural land cover with similar soils and surficial geology. Soil water contents, soil temperatures and ground frost thickness were measured at the crest and base of closed depressions in two agricultural fields and two forest stands on permeable ORM outcrops. Recharge from late-fall to the end of spring snowmelt was estimated via 1-d water balances and surface-applied bromide tracing. Both forest and agricultural sites experienced soil freezing; however, greater soil water contents prior to freeze-up at the latter led to concrete soil frost development. This resulted in lateral movement of snowmelt and rainfall into topographic depressions and surface ponding, which did not occur in forest depressions. Water balance recharge exceeded estimates from the bromide tracer approach at all locations; nevertheless, both methods indicated DRF exceeded recharge at the depression crest in agricultural areas with little difference in forest areas. Water balance estimates suggest winter-spring DFR (1300 - 2000 mm) is 3-5× recharge on level agricultural sites. Differences in the potential for DFR between agricultural and forest land covers have important implications for the spatial variability of recharge fluxes and the quality of recharging water on the ORM.

  5. Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s.

    PubMed

    Gibbs, H K; Ruesch, A S; Achard, F; Clayton, M K; Holmgren, P; Ramankutty, N; Foley, J A

    2010-09-21

    Global demand for agricultural products such as food, feed, and fuel is now a major driver of cropland and pasture expansion across much of the developing world. Whether these new agricultural lands replace forests, degraded forests, or grasslands greatly influences the environmental consequences of expansion. Although the general pattern is known, there still is no definitive quantification of these land-cover changes. Here we analyze the rich, pan-tropical database of classified Landsat scenes created by the Food and Agricultural Organization of the United Nations to examine pathways of agricultural expansion across the major tropical forest regions in the 1980s and 1990s and use this information to highlight the future land conversions that probably will be needed to meet mounting demand for agricultural products. Across the tropics, we find that between 1980 and 2000 more than 55% of new agricultural land came at the expense of intact forests, and another 28% came from disturbed forests. This study underscores the potential consequences of unabated agricultural expansion for forest conservation and carbon emissions.

  6. EnviroAtlas -Milwaukee, WI- One Meter Resolution Urban Land Cover Data (2010)

    EPA Pesticide Factsheets

    The EnviroAtlas Milwaukee, WI land cover data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from Late Summer 2010 at 1 m spatial resolution. Nine land cover classes were mapped: water, impervious surfaces (dark and light), soil and barren land, trees and forest, grass and herbaceous non-woody vegetation, agriculture, and wetlands (woody and emergent). An accuracy assessment using a completely random sampling of 600 samples yielded an overall accuracy of 85.39% percent using a minimum mapping unit of 9 pixels (3x3 pixel window). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Milwaukee. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  7. EnviroAtlas -- Woodbine, IA -- One Meter Resolution Urban Land Cover Data (2011)

    EPA Pesticide Factsheets

    The EnviroAtlas Woodbine, IA land cover (LC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from Late Summer 2011 at 1 m spatial resolution. Six land cover classes were mapped: water, impervious surfaces (dark and light), soil and barren land, trees and forest, grass and herbaceous non-woody vegetation, and agriculture. An accuracy assessment using a completely random sampling of 600 samples yielded an overall accuracy of 87.03% percent using a minimum mapping unit of 9 pixels (3x3 pixel window). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Woodbine. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  8. Abundance and distribution of sylvatic dengue virus vectors in three different land cover types in Sarawak, Malaysian Borneo.

    PubMed

    Young, Katherine I; Mundis, Stephanie; Widen, Steven G; Wood, Thomas G; Tesh, Robert B; Cardosa, Jane; Vasilakis, Nikos; Perera, David; Hanley, Kathryn A

    2017-08-31

    Mosquito-borne dengue virus (DENV) is maintained in a sylvatic, enzootic cycle of transmission between canopy-dwelling non-human primates and Aedes mosquitoes in Borneo. Sylvatic DENV can spill over into humans living in proximity to forest foci of transmission, in some cases resulting in severe dengue disease. The most likely vectors of such spillover (bridge vectors) in Borneo are Ae. albopictus and Ae. niveus. Borneo is currently experiencing extensive forest clearance. To gauge the effect of this change in forest cover on the likelihood of sylvatic DENV spillover, it is first necessary to characterize the distribution of bridge vectors in different land cover types. In the current study, we hypothesized that Ae. niveus and Ae. albopictus would show significantly different distributions in different land cover types; specifically, we predicted that Ae. niveus would be most abundant in forests whereas Ae. albopictus would have a more even distribution in the landscape. Mosquitoes were collected from a total of 15 sites using gravid traps and a backpack aspirator around Kampong Puruh Karu, Sarawak, Malaysian Borneo, where sylvatic DENV spillover has been documented. A total of 2447 mosquitoes comprising 10 genera and 4 species of Aedes, were collected over the three years, 2013, 2014 and 2016, in the three major land cover types in the area, homestead, agriculture and forest. Mosquitoes were identified morphologically, pooled by species and gender, homogenized, and subject to DNA barcoding of each Aedes species and to arbovirus screening. As predicted, Ae. niveus was found almost exclusively in forests whereas Ae. albopictus was collected in all land cover types. Aedes albopictus was significantly (P = 0.04) more abundant in agricultural fields than forests. Sylvatic DENV was not detected in any Aedes mosquito pools, however genomes of 14 viruses were detected using next generation sequencing. Land cover type affects the abundance and distribution of the most

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

    Currently within the EU's Earth Observation (EO) monitoring framework, there is a need for low-cost methods for acquiring high quality in-situ data to create accurate and well-validated environmental monitoring products. To help address this need, a new four year Horizon 2020 project entitled LandSense will link remote sensing data with modern participatory data collection methods that involve citizen scientists. This paper will describe the citizen science activities within the LandSense Observatory that aim to deliver concrete, measurable and quality-assured ground-based data that will complement existing satellite monitoring systems. LandSense will deploy advanced tools, services and resources to mobilize and engage citizens to collect in-situ observations (i.e. ground-based data and visual interpretations of EO imagery). Integrating these citizen-driven in-situ data collections with established authoritative and open access data sources will help reduce costs, extend GEOSS and Copernicus capacities, and support comprehensive environmental monitoring systems. Policy-relevant campaigns will be implemented in close collaboration with multiple stakeholders to ensure that citizen observations address user requirements and contribute to EU-wide environmental governance and decision-making. Campaigns for addressing local and regional Land Use and Land Cover (LULC) issues are planned for select areas in Austria, France, Germany, Spain, Slovenia and Serbia. Novel LandSense services (LandSense Campaigner, FarmLand Support, Change Detector and Quality Assurance & Control) will be deployed and tested in these areas to address critical LULC issues (i.e. urbanization, agricultural land use and forest/habitat monitoring). For example, local residents in the cities of Vienna, Tulln, and Heidelberg will help cooperatively detect and map changes in land cover and green space to address key issues of urban sprawl, land take and flooding. Such campaigns are facilitated through

  11. 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

  12. Profiling agricultural land cover change in the North Central U.S. using ten years of the Cropland Data Layer

    NASA Astrophysics Data System (ADS)

    Sandborn, A.; Ebinger, L.

    2016-12-01

    The Cropland Data Layer (CDL), produced by the USDA/National Agricultural Statistics Service, provides annual, georeferenced crop specific land cover data over the contiguous United States. Several analyses were performed on ten years (2007-2016) of CDL data in order to visualize and quantify agricultural change over the North Central region (North Dakota, South Dakota, and Minnesota). Crop masks were derived from the CDL and layered to produce a ten-year time stack of corn, soybeans, and spring wheat at 30m spatial resolution. Through numerous image analyses, a temporal profile of each crop type was compiled and portrayed cartographically. For each crop, analyses included calculating the mean center of crop area over the ten year sequence, identifying the first and latest year the crop was grown on each pixel, and distinguishing crop rotation patterns and replacement statistics. Results show a clear north-western expansion trend for corn and soybeans, and a western migration trend for spring wheat. While some change may be due to commonly practiced crop rotation, this analysis shows that crop footprints have extended into areas that were previously other crops, idle cropland, and pasture/rangeland. Possible factors contributing to this crop migration pattern include profit advantages of row crops over small grains, improved crop genetics, climate change, and farm management program changes. Identifying and mapping these crop planting differences will better inform agricultural best practices, help to monitor the latest crop migration patterns, and present researchers with a way to quantitatively measure and forecast future agricultural trends.

  13. Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka Metropolitan of Bangladesh during 1960-2005.

    PubMed

    Dewan, Ashraf M; Yamaguchi, Yasushi

    2009-03-01

    This paper illustrates the result of land use/cover change in Dhaka Metropolitan of Bangladesh using topographic maps and multi-temporal remotely sensed data from 1960 to 2005. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images such as SPOT, IRS, IKONOS and field data. The overall accuracy of land cover change maps, generated from Landsat and IRS-1D data, ranged from 85% to 90%. The analysis indicated that the urban expansion of Dhaka Metropolitan resulted in the considerable reduction of wetlands, cultivated land, vegetation and water bodies. The maps showed that between 1960 and 2005 built-up areas increased approximately 15,924 ha, while agricultural land decreased 7,614 ha, vegetation decreased 2,336 ha, wetland/lowland decreased 6,385 ha, and water bodies decreased about 864 ha. The amount of urban land increased from 11% (in 1960) to 344% in 2005. Similarly, the growth of landfill/bare soils category was about 256% in the same period. Much of the city's rapid growth in population has been accommodated in informal settlements with little attempt being made to limit the risk of environmental impairments. The study quantified the patterns of land use/cover change for the last 45 years for Dhaka Metropolitan that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning.

  14. Analysis of potential flooding in the education Jatinangor based approach morphology, land cover, and geology

    NASA Astrophysics Data System (ADS)

    Rifai, Achmad; Hadian, Sapari Dwi; Mufti, Iqbal Jabbari; Fathoni, Azmi Rizqi; Azy, Fikri Noor; Jihadi, Lutfan Harisan

    2017-07-01

    Jatinangor formerly an agricultural area dominated by rice field. Water in Jatinangor comes from a spring located in north Jatinangor or proximal region of Manglayang mountain to flow to the south and southwest Jatinangor up to Citarum River. Jatinangor plain that was once almost all the rice fields, but now become a land settlement that grew very rapidly since its founding colleges. Flow and puddle were originally be used for agricultural land, but now turned into a disaster risks for humans. The research method using qualitative methods with the weighing factor, scoring, and overlay maps. The cause of the flood is distinguished into two: the first is the natural factors such as the condition of landform, lithology, river flow patterns, and annual rainfall. The second is non-natural factors such as land cover of settlement, irrigation, and land use. The amount of flood risks using probability Gilbert White frequency, magnitude and duration of existing events then correlated with these factors. Based on the results of the study, were divided into 3 zones Jatinangor disaster-prone (high, medium, and safe). High flood zone is located in the South Jatinangor which covers an area Cikeruh Village, Sayang Village, Cipacing village, Mekargalih village, Cintamulya village, west of Jatimukti village, and South Hegarmanah village, has a dominant causative factor is the use of solid land, poor drainage, lithology lacustrine conditions with low permeability, and flat topography. Medium flood zone was located in the central and western regions covering Cibeusi village, Cileles village, south of Cilayung village, Hegarmanah village and Padjadjaran Region, has a dominant causative factor is rather dense land use, lithology breccias and Tuffaceous Sand with moderate permeability, topography is moderately steep. Safe flood zone is located in the east Jatinangor covering Jatiroke village, Cisepur village, east Hegarmanah village, has a dominant factor in the form of a rather steep

  15. Linking Landsat observations with MODIS derived Land Surface Phenology data to map agricultural expansion and contraction in Russia

    NASA Astrophysics Data System (ADS)

    Caliskan, S.; de Beurs, K.

    2010-12-01

    Direct human impacts on the land surface are especially pronounced in agricultural regions that cover a substantial portion of the global land surface: 12% of the terrestrial surface is under active agricultural management. Crops display phenologies distinct from natural vegetation; the growing seasons are often shifted in time, crop establishment is generally fast and the vegetation is rapidly removed at harvest. Previously we have demonstrated that agricultural land abandonment alters land surface phenology sufficiently to be detectable from a time series of coarse resolution imagery. With land surface phenology models based on accumulated growing degree-days (AGDD) and AVHRR NDVI, we demonstrated that abandoned croplands covered with native grasses and weeds typically greened-up and peaked sooner than active croplands. Here we present an expansion of these analyses for the MODIS time period with the ultimate goal to map agricultural abandonment and expansion in European Russia from 2000 to 2010. We used the 8-day, 1km L3 Land Surface Temperature data (MOD11A2) to generate the accumulated growing degree days and the 16-day L3 Nadir BRDF-Adjusted reflectance data at 500m resolution (MCD43A4) to calculate NDVI. We calculated phenological metrics based on three methods: 1) Double-logistic models such as those applied to produce the standard MODIS phenology product (MOD12Q2); 2) A combination of NDII and NDVI; this method has been shown to provide start/end of season measurement closest to field observations in snowy areas; and 3) A quadratic model linking accumulated growing degree days and vegetation indices which we successfully applied in agricultural areas of Kazakhstan and semi-arid Africa. We selected Landsat imagery for two vastly different regions in Russia and present a Landsat-guided probabilistic detection of abandoned and active croplands for all available years of the MODIS image time series (2000-2010). For each region, we selected at least two images

  16. Analysis of land cover change and its driving forces in a desert oasis landscape of southern Xinjiang, China

    NASA Astrophysics Data System (ADS)

    Amuti, T.; Luo, G.

    2014-07-01

    The combined effects of drought, warming and the changes in land cover have caused severe land degradation for several decades in the extremely arid desert oases of Southern Xinjiang, Northwest China. This study examined land cover changes during 1990-2008 to characterize and quantify the transformations in the typical oasis of Hotan. Land cover classifications of these images were performed based on the supervised classification scheme integrated with conventional vegetation and soil indexes. Change-detection techniques in remote sensing (RS) and a geographic information system (GIS) were applied to quantify temporal and spatial dynamics of land cover changes. The overall accuracies, Kappa coefficients, and average annual increase rate or decrease rate of land cover classes were calculated to assess classification results and changing rate of land cover. The analysis revealed that major trends of the land cover changes were the notable growth of the oasis and the reduction of the desert-oasis ecotone, which led to accelerated soil salinization and plant deterioration within the oasis. These changes were mainly attributed to the intensified human activities. The results indicated that the newly created agricultural land along the margins of the Hotan oasis could result in more potential areas of land degradation. If no effective measures are taken against the deterioration of the oasis environment, soil erosion caused by land cover change may proceed. The trend of desert moving further inward and the shrinking of the ecotone may lead to potential risks to the eco-environment of the Hotan oasis over the next decades.

  17. 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.

  18. 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.

  19. Annual land cover change mapping using MODIS time series to improve emissions inventories.

    NASA Astrophysics Data System (ADS)

    López Saldaña, G.; Quaife, T. L.; Clifford, D.

    2014-12-01

    Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A prototype land cover product was created for 2006 to 2008. Several machine learning classifiers were tested as well as different sets of input features going from the BRDF parameters to spectral Albedo. We will present the results of the time series development and the first exercises when creating the prototype land cover product.

  20. Land cover change interacts with drought severity to change fire regimes in Western Amazonia.

    PubMed

    Gutiérrez-Vélez, Víctor H; Uriarte, María; DeFries, Ruth; Pinedo-Vásquez, Miguel; Fernandes, Katia; Ceccato, Pietro; Baethgen, Walter; Padoch, Christine

    Fire is becoming a pervasive driver of environmental change in Amazonia and is expected to intensify, given projected reductions in precipitation and forest cover. Understanding of the influence of post-deforestation land cover change on fires in Amazonia is limited, even though fires in cleared lands constitute a threat for ecosystems, agriculture, and human health. We used MODIS satellite data to map burned areas annually between 2001 and 2010. We then combined these maps with land cover and climate information to understand the influence of land cover change in cleared lands and dry-season severity on fire occurrence and spread in a focus area in the Peruvian Amazon. Fire occurrence, quantified as the probability of burning of individual 232-m spatial resolution MODIS pixels, was modeled as a function of the area of land cover types within each pixel, drought severity, and distance to roads. Fire spread, quantified as the number of pixels burned in 3 × 3 pixel windows around each focal burned pixel, was modeled as a function of land cover configuration and area, dry-season severity, and distance to roads. We found that vegetation regrowth and oil palm expansion are significantly correlated with fire occurrence, but that the magnitude and sign of the correlation depend on drought severity, successional stage of regrowing vegetation, and oil palm age. Burning probability increased with the area of nondegraded pastures, fallow, and young oil palm and decreased with larger extents of degraded pastures, secondary forests, and adult oil palm plantations. Drought severity had the strongest influence on fire occurrence, overriding the effectiveness of secondary forests, but not of adult plantations, to reduce fire occurrence in severely dry years. Overall, irregular and scattered land cover patches reduced fire spread but irregular and dispersed fallows and secondary forests increased fire spread during dry years. Results underscore the importance of land cover

  1. Quantitative analysis of agricultural land use change in China

    NASA Astrophysics Data System (ADS)

    Chou, Jieming; Dong, Wenjie; Wang, Shuyu; Fu, Yuqing

    This article reviews the potential impacts of climate change on land use change in China. Crop sown area is used as index to quantitatively analyze the temporal-spatial changes and the utilization of the agricultural land. A new concept is defined as potential multiple cropping index to reflect the potential sowing ability. The impacting mechanism, land use status and its surplus capacity are investigated as well. The main conclusions are as following; During 1949-2010, the agricultural land was the greatest in amount in the middle of China, followed by that in the country's eastern and western regions. The most rapid increase and decrease of agricultural land were observed in Xinjiang and North China respectively, Northwest China and South China is also changed rapid. The variation trend before 1980 differed significantly from that after 1980. Agricultural land was affected by both natural and social factors, such as regional climate and environmental changes, population growth, economic development, and implementation of policies. In this paper, the effects of temperature and urbanization on the coverage of agriculture land are evaluated, and the results show that the urbanization can greatly affects the amount of agriculture land in South China, Northeast China, Xinjiang and Southwest China. From 1980 to 2009, the extent of agricultural land use had increased as the surplus capacity had decreased. Still, large remaining potential space is available, but the future utilization of agricultural land should be carried out with scientific planning and management for the sustainable development.

  2. Integrated Assessment of Climate Change, Agricultural Land Use, and Regional Carbon Changes

    NASA Astrophysics Data System (ADS)

    MU, J.

    2014-12-01

    Changes in land use have caused a net release of carbon to the atmosphere over the last centuries and decades1. On one hand, agriculture accounts for 52% and 84% of global anthropogenic methane and nitrous oxide emissions, respectively. On the other hand, many agricultural practices can potentially mitigate greenhouse gas (GHG) emissions, the most prominent of which are improved cropland and grazing land management2. From this perspective, land use change that reduces emissions and/or increases carbon sequestration can play an important role in climate change mitigation. As shown in Figure 1, this paper is an integrated study of climate impacts, land uses, and regional carbon changes to examine, link and assess climate impacts on regional carbon changes via impacts on land uses. This study will contribute to previous research in two aspects: impacts of climate change on future land uses under an uncertain future world and projections of regional carbon dynamics due to changes in future land use. Specifically, we will examine how land use change under historical climate change using observed data and then project changes in land use under future climate projections from 14 Global Climate Models (GCMs) for two emission scenarios (i.e., RCP4.5 and RCP8.5). More importantly, we will investigate future land use under uncertainties with changes in agricultural development and social-economic conditions along with a changing climate. By doing this, we then could integrate with existing efforts by USGS land-change scientists developing and parameterizing models capable of projecting changes across a full spectrum of land use and land cover changes and track the consequences on ecosystem carbon to provide better information for land managers and policy makers when informing climate change adaptation and mitigation policies.

  3. Differences in Nutrient Sources Caused by Variations in Monsoon Strength and Land Use/Land Cover, Middle Rio Grande, NM

    NASA Astrophysics Data System (ADS)

    Oelsner, G. P.; Brooks, P. D.; Hogan, J. F.

    2006-12-01

    Synoptic sampling of the Middle Rio Grande (MRG) in central New Mexico was conducted each year during August from 2001 through 2006. Land use in the basin includes a large urban area around Albuquerque, agricultural areas, and rangeland. Because the Rio Grande is a highly managed river, the affects of land use and land cover on water quality are associated primarily with active management of river flows and water diversions and secondarily by episodic precipitation events that circumvent these management structures. A persistent monsoon regime brought heavy rains to the MRG in central New Mexico during July and August making 2006 the 8th wettest year on record for Albuquerque, NM. This summer's heavy rains increased river discharge and inputs from tributaries and ephemeral streams which served to reconnect the river to its floodplain and riparian area and transport solutes to the river from normally disconnected sources. Discharge in the Middle Rio Grande was 39 cms during the 2006 sampling event which is 250% higher than discharge during the previous sampling events. Under non-flood conditions, wastewater treatment plants (WWTP) are the primary source of nitrogen to the river. However, N loading from the Albuquerque WWTP was 40% lower in 2006 than previous years due to a decrease in effluent TDN concentrations. Tributaries had similar TDN concentrations in all years, but due to increased discharge, TDN loads from tributaries were an order of magnitude higher in 2006 and exceeded the TDN input from WWTPs. In all years, agricultural drains had lower TDN concentrations than the river water originally diverted for irrigation, suggesting that the agricultural areas function as a sink for nitrogen under a wide range of hydrologic conditions. Increased TDN concentrations and discharge rates resulted in a five-fold increase of N loading to Elephant Butte Reservoir from 1000 kgN/day to more than 5000 kgN/day. Analysis of DOC and stable isotopes of water should help to

  4. 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.

  5. Hydrologic and land-cover features of the Caloosahatchee River Basin, Lake Okeechobee to Franklin Lock, Florida

    USGS Publications Warehouse

    LaRose, Henry R.; McPherson, Benjamin F.

    1980-01-01

    The freshwater part of the Caloosahatchee River basin, Fla., from Franklin Lock to Lake Okeechobee, is shown at a scale of 1 inch equals 1 mile on an aerial photomosaic, dated January 1979. The basin is divided into 16 subbasins, and the land cover and land use in each subbasin are given. The basin is predominantly rangeland and agricultural land. Surface-water flow in the basin is largely controlled. Some selected data on water quality are given. (USGS)

  6. MODIS land cover uncertainty in regional climate simulations

    NASA Astrophysics Data System (ADS)

    Li, Xue; Messina, Joseph P.; Moore, Nathan J.; Fan, Peilei; Shortridge, Ashton M.

    2017-12-01

    MODIS land cover datasets are used extensively across the climate modeling community, but inherent uncertainties and associated propagating impacts are rarely discussed. This paper modeled uncertainties embedded within the annual MODIS Land Cover Type (MCD12Q1) products and propagated these uncertainties through the Regional Atmospheric Modeling System (RAMS). First, land cover uncertainties were modeled using pixel-based trajectory analyses from a time series of MCD12Q1 for Urumqi, China. Second, alternative land cover maps were produced based on these categorical uncertainties and passed into RAMS. Finally, simulations from RAMS were analyzed temporally and spatially to reveal impacts. Our study found that MCD12Q1 struggles to discriminate between grasslands and croplands or grasslands and barren in this study area. Such categorical uncertainties have significant impacts on regional climate model outputs. All climate variables examined demonstrated impact across the various regions, with latent heat flux affected most with a magnitude of 4.32 W/m2 in domain average. Impacted areas were spatially connected to locations of greater land cover uncertainty. Both biophysical characteristics and soil moisture settings in regard to land cover types contribute to the variations among simulations. These results indicate that formal land cover uncertainty analysis should be included in MCD12Q1-fed climate modeling as a routine procedure.

  7. Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)

    USGS Publications Warehouse

    DeJager, Nathan R.; Rohweder, Jason J.

    2017-01-01

    Quantifying changes in the cover of river-floodplain systems can provide important insights into the processes that structure these landscapes as well as the potential consequences to the ecosystem services they provide. We examined net changes in 13 different aquatic and floodplain land cover classes using photo interpreted maps of the navigable portions of the Upper Mississippi River (UMR, above the confluence with the Ohio River) and Illinois River from 1989 to 2000 and from 2000 to 2010. We detected net decreases in vegetated aquatic area in nearly all river reaches from 1989 to 2000. The only river reaches that experienced a subsequent recovery of vegetated aquatic area from 2000 to 2010 were located in the northern portion of the UMR (above navigation pool 14) and two reaches in the Illinois River. Changes on the floodplain were dominated by urban development, which increased in nearly every river reach studied from 1989 to 2000. Agricultural lands declined in most river reaches from 2000 to 2010. The loss of agricultural land cover in the northern UMR was accompanied by increases in forest cover, whereas in the lower UMR and Illinois River, declines in agriculture were accompanied by increases in forest and shallow marsh communities. The changes in aquatic vegetation occupied between 5 and 20% of the total aquatic area and are likely associated with previously reported regional improvements in water clarity, while smaller (1–15% of the total floodplain area) changes in anthropogenic land cover types on the floodplain are likely driven by broad-scale socio-economic conditions.

  8. Land use, population dynamics, and land-cover change in eastern Puerto Rico: Chapter B in Water quality and landscape processes of four watersheds in eastern Puerto Rico

    USGS Publications Warehouse

    Gould, William A.; Martinuzzi, Sebastián; Pares-Ramos, Isabel K.; Murphy, Sheila F.; Stallard, Robert F.; Murphy, Sheila F.; Stallard, Robert F.

    2012-01-01

    We assessed current and historic land use and land cover in the Luquillo Mountains and surrounding area in eastern Puerto Rico, including four small subwatersheds that are study watersheds of the U.S. Geological Survey's Water, Energy, and Biogeochemical Budgets (WEBB) program. This region occupies an area of 1,616 square kilometers, about 18 percent of the total land in Puerto Rico. Closed forests occupy about 37 percent of the area, woodlands and shrublands 7 percent, nonforest vegetation 43 percent, urban development 10 percent, and water and natural barrens total less than 2 percent. The area has been classified into three main land-use categories by integrating recent census information (population density per barrio in the year 2000) with satellite image analyses (degree of developed area versus natural land cover). Urban land use (in this analysis, land with more than 20 percent developed cover within a 1-square-kilometer area and population density greater than 500 people per square kilometer) covered 16 percent of eastern Puerto Rico. Suburban land use (more than 80 percent natural land cover, more than 500 people per square kilometer, and primarily residential) covers 50 percent of the area. Rural land use (more than 80 percent natural land cover, less than 500 people per square kilometer, and primarily active or abandoned agricultural, wetland, steep slope, or protected conservation areas) covered 34 percent of the area. Our analysis of land-cover change indicates that in the 1990s, forest cover increased at the expense of woodlands and grasslands. Urban development increased by 16 percent during that time. The most pronounced change in the last seven decades has been the shift from a nonforested to a forested landscape and the intensification of the ring of urbanization that surrounds the long-protected Luquillo Experimental Forest.

  9. Nickel, Cobalt, Chromium and Copper in agricultural and grazing land soils of Europe

    NASA Astrophysics Data System (ADS)

    Albanese, Stefano; Sadeghi, Martiya; De Vivo, Benedetto; Lima, Annamaria; Cicchella, Domenico; Dinelli, Enrico

    2014-05-01

    In the framework of the GEMAS (Geochemical Mapping of Agricultural and Grazing Land Soils) project, concentrations of Ni, Co, Cu and Cr were determined for the whole available dataset (2218 samples of agricultural soil and 2127 samples of grazing land soil) covering a total area of 5.6 million sq km all over Europe. The distribution pattern of Ni in the European soils (both agricultural and grazing land soils) shows the highest concentrations in correspondence with the Mediterranean area (especially in Greece, the Balcan Peninsula and NW Italy) with average values generally ranging between 40 mg/kg and 140 mg/kg and anomalous areas characterized by peaks higher than 2400 mg/kg. Concentrations between 10 mg/kg and 40 mg/kg characterize Continental Europe north of Alps and, partly, the Scandinavian countries. Lower concentrations (< 10 mg/kg) occurs near the Trans-European Suture Zone, one of the main tectonic borders in Europe, and they are limited on the south by the maximum extent limit of the last glaciation. Cobalt and Cr show distribution patterns similar to Ni in both agricultural and grazing land soils. The maximum concentration peaks of Cobalt and Cr rise up to respectively 126 mg/kg and 696 mg/kg in agricultural soils and up to 255 mg/kg and 577 mg/kg in grazing land soils. Copper distribution in the soils collected across Europe, although has a general correspondence with the patterns of Ni, Co, Cr, shows some peculiarities. Specifically, Cu is characterized by high concentration values (up to 395 mg/kg in agricultural soils and 373 mg/kg in Grazing land soils) also in correspondence with the Roman Comagmatic Province and the south western coast of France characterized by a wide spread of vineyards.

  10. Plastic-covered agriculture forces the regional climate to change

    NASA Astrophysics Data System (ADS)

    Yang, D.; Chen, J.; Chen, X.; Cao, X.

    2016-12-01

    The practice of plastic-covered agriculture as a solution to moderate the dilemma of global food shortage, meanwhile, brings great pressure to the local environment. This research was conducted to reveal the impacts of plastic-covered agritulture on regional climate change by experimenting in a plastic greenhouse (PG) dominated area - Weifang district, Shandong province, China. Based on a new plastic greenhouse index (PGI) proposed in this study, we reconstructed the spatial distribution of PG across 1995-2015 in the study area. With that, land surface temperature (LST) dataset combined with surface evapotranspiration, surface reflectance and precipitation data, was applied to the probe of PG's climatic impacts. Results showed that PG, in the study area, has experienced a striking spatial expansion during the past 20 years, and more important, the expansion correlated strongly to the local climate change. It showed that the annual precipitation, in the study area, decreased during these years, which constrasts to a slightly increasing trend of the adjacent districts without PG construction. In addition, resulting from the greenhouse effect, PG area presented a harsher increase of surface temperature compared to the non-PG areas. Our study also telled that the evapotranspiration of PG area has been largely cutted down ascribing to the gas tightness of plastic materials, showing a decline around 40%. This indicates a way that the development of plastic-covered agriculture may contribute to the change of the local climate.

  11. EnviroAtlas -- Austin, TX -- One Meter Resolution Urban Land Cover Data (2010) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas ). The Austin, TX EnviroAtlas One Meter-scale Urban Land Cover (MULC) Data were generated from United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP) four band (red, green, blue, and near infrared) aerial photography at 1 m spatial resolution from multiple dates in May, 2010. Six land cover classes were mapped: water, impervious surfaces, soil and barren land, trees, grass-herbaceous non-woody vegetation, and agriculture. An accuracy assessment of 600 completely random and 55 stratified random photo interpreted reference points yielded an overall User's fuzzy accuracy of 87 percent. The area mapped is the US Census Bureau's 2010 Urban Statistical Area for Austin, TX plus a 1 km buffer. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas

  12. Cost, drivers and action against land degradation through land use and cover change in Russia

    NASA Astrophysics Data System (ADS)

    Sorokin, Alexey; Strokov, Anton; Johnson, Timothy; Mirzabaev, Alisher

    2016-04-01

    The natural conditions and socio-economic factors determine the structure and the principles of land use in Russia. The increasing degradation of land resources in many parts of Russia manifested in numerous forms such as desertification, soil erosion, secondary salinization, water-logging and overgrazing. The major drivers of degradation include: climatic change, unsustainable agricultural practices, industrial and mining activities, expansion of crop production to fragile and marginal areas, inadequate maintenance of irrigation and drainage networks. Several methods for estimating Total Economic Value of land-use and land-cover change were used: 1) the cost of production per hectare (only provisional services were included); 2) the value of ecosystem services provided by Costanza et al, 1997; 3) coefficients of basic transfer and contingent approaches based on Tianhong et al, 2008 and Xie et al, 2003, who interviewed 200 ecologists to give a value of ecosystem services of different land types in China; 4) coefficients on a basic transfer and contingent approaches based on author's interview of 20 experts in Lomonosov Moscow State University. In general, the estimation of the prices for action and inaction in addressing the degradation and improvement of the land resources on a national scale (the Federal districts) with an emphasis on the period of economic reforms from 1990-2009 in Russia, where the area of arable lands decreased by 25% showed that the total land use/cover dynamic changes are about 130 mln ha, and the total annual costs of land degradation due to land-use change only, are about 189 bln USD in 2009 as compared with 2001, e.g. about 23.6 bln USD annually, or about 2% of Russia's Gross Domestic Product in 2010. The costs of action against land degradation are lower than the costs of inaction in Russia by 5-6 times over the 30 year horizon. Almost 92% of the costs of action are made up of the opportunity costs of action. The study was performed with

  13. 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.

  14. Assessing changes in the value of ecosystem services in response to land-use/land-cover dynamics in Nigeria.

    PubMed

    Arowolo, Aisha Olushola; Deng, Xiangzheng; Olatunji, Olusanya Abiodun; Obayelu, Abiodun Elijah

    2018-09-15

    Increasing human activities worldwide have significantly altered the natural ecosystems and consequently, the services they provide. This is no exception in Nigeria, where land-use/land-cover has undergone a series of dramatic changes over the years mainly due to the ever-growing large population. However, estimating the impact of such changes on a wide range of ecosystem services is seldom attempted. Thus, on the basis of GlobeLand30 land-cover maps for 2000 and 2010 and using the value transfer methodology, we evaluated changes in the value of ecosystem services in response to land-use/land-cover dynamics in Nigeria. The results showed that over the 10-year period, cultivated land sprawl over the forests and savannahs was predominant, and occurred mainly in the northern region of the country. During this period, we calculated an increase in the total ecosystem services value (ESV) in Nigeria from 665.93 billion (2007 US$) in 2000 to 667.44 billion (2007 US$) in 2010, 97.38% of which was contributed by cultivated land. The value of provisioning services increased while regulation, support, recreation and culture services decreased, amongst which, water regulation (-11.01%), gas regulation (-7.13%), cultural (-4.84%) and climate regulation (-4.3%) ecosystem functions are estimated as the most impacted. The increase in the total ESV in Nigeria associated with the huge increase in ecosystem services due to cultivated land expansion may make land-use changes (i.e. the ever-increasing agricultural expansion in Nigeria) appear economically profitable. However, continuous loss of services such as climate and water regulation that are largely provided by the natural ecosystems can result in huge economic losses that may exceed the apparent gains from cultivated land development. Therefore, we advocate that the conservation of the natural ecosystem should be a priority in future land-use management in Nigeria, a country highly vulnerable to climate change and incessantly

  15. Targeting land-use change for nitratenitrogen load reductions in an agricultural watershed

    USGS Publications Warehouse

    Jha, M.K.; Schilling, K.E.; Gassman, Philip W.; Wolter, C.F.

    2010-01-01

    The research was conducted as part of the USDA's Conservation Effects Assessment Project. The objective of the project was to evaluate the environmental effects of land-use changes, with a focus on understanding how the spatial distribution throughout a watershed influences their effectiveness.The Soil and Water AssessmentTool (SWAT) water quality model was applied to the Squaw Creek watershed, which covers 4,730 ha (11,683 ac) of prime agriculture land in southern Iowa. The model was calibrated (2000 to 2004) and validated (1996 to 1999) for overall watershed hydrology and for streamflow and nitrate loadings at the watershed outlet on an annual and monthly basis. Four scenarios for land-use change were evaluated including one scenario consistent with recent land-use changes and three scenarios focused on land-use change on highly erodible land areas, upper basin areas, and floodplain areas. Results for the Squaw Creek watershed suggested that nitrate losses were sensitive to land-use change. If land-use patterns were restored to 1990 conditions, nitrate loads may be reduced 7% to 47% in the watershed and subbasins, whereas converting row crops to grass in highly erodible land, upper basin, and floodplain areas would reduce nitrate loads by 47%, 16%, and 8%, respectively. These SWAT model simulations can provide guidance on how to begin targeting land-use change for nitrate load reductions in agricultural watersheds.

  16. A small-scale land-sparing approach to conserving biological diversity in tropical agricultural landscapes.

    PubMed

    Chandler, Richard B; King, David I; Raudales, Raul; Trubey, Richard; Chandler, Carlin; Chávez, Víctor Julio Arce

    2013-08-01

    Two contrasting strategies have been proposed for conserving biological diversity while meeting the increasing demand for agricultural products: land sparing and land sharing production systems. Land sparing involves increasing yield to reduce the amount of land needed for agriculture, whereas land-sharing agricultural practices incorporate elements of native ecosystems into the production system itself. Although the conservation value of these systems has been extensively debated, empirical studies are lacking. We compared bird communities in shade coffee, a widely practiced land-sharing system in which shade trees are maintained within the coffee plantation, with bird communities in a novel, small-scale, land-sparing coffee-production system (integrated open canopy or IOC coffee) in which farmers obtain higher yields under little or no shade while conserving an area of forest equal to the area under cultivation. Species richness and diversity of forest-dependent birds were higher in the IOC coffee farms than in the shade coffee farms, and community composition was more similar between IOC coffee and primary forest than between shade coffee and primary forest. Our study represents the first empirical comparison of well-defined land sparing and land sharing production systems. Because IOC coffee farms can be established by allowing forest to regenerate on degraded land, widespread adoption of this system could lead to substantial increases in forest cover and carbon sequestration without compromising agricultural yield or threatening the livelihoods of traditional small farmers. However, we studied small farms (<5 ha); thus, our results may not generalize to large-scale land-sharing systems. Furthermore, rather than concluding that land sparing is generally superior to land sharing, we suggest that the optimal approach depends on the crop, local climate, and existing land-use patterns. © 2013 Society for Conservation Biology.

  17. Assessment of Classification Accuracies of SENTINEL-2 and LANDSAT-8 Data for Land Cover / Use Mapping

    NASA Astrophysics Data System (ADS)

    Hale Topaloğlu, Raziye; Sertel, Elif; Musaoğlu, Nebiye

    2016-06-01

    This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.

  18. 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.

  19. 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).

  20. 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.

  1. 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.

  2. EnviroAtlas -- Fresno, California -- One Meter Resolution Urban Land Cover Data (2010)

    EPA Pesticide Factsheets

    The Fresno, CA EnviroAtlas One-Meter-scale Urban Land Cover Data were generated via supervised classification of combined aerial photography and LiDAR data. The air photos were United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP) four band (red, green, blue, and near infrared) aerial photography at 1-m spatial resolution. Aerial photography ('imagery') was collected on multiple dates in summer 2010. Seven land cover classes were mapped: Water, impervious surfaces (Impervious), soil and barren (Soil), trees and forest (Tree), and grass and herbaceous non-woody vegetation (Grass), agriculture (Ag), and Orchards. An accuracy assessment of 500 completely random and 103 stratified random points yielded an overall User's fuzzy accuracy of 81.1 percent (see below). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Fresno, CA plus a 1-km buffer. Where imagery was available, additional areas outside the 1-km boundary were also mapped but not included in the accuracy assessment. We expect the accuracy of the areas outside of the 1-km boundary to be consistent with those within. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The da

  3. Land cover, land use, and climate change impacts on agriculture in southern Vietnam

    NASA Astrophysics Data System (ADS)

    Kontgis, Caitlin

    Global environmental change is rapidly changing the surface of the Earth in varied and irrevocable ways. Across the world, land cover and land use have been altered to accommodate the needs of expanding populations, and climate change has required plant, animal, and human communities to adapt to novel climates. These changes have created unprecedented new ecosystems that affect the planet in ways that are not fully understood and difficult to predict. Of utmost concern is food security, and whether agro-ecosystems will adapt and respond to widespread changes so that growing global populations can be sustained. To understand how one staple food crop, rice, responds to global environmental change in southern Vietnam, this dissertation aims to accomplish three main tasks: (1) quantify the rate and form of urban and peri-urban expansion onto cropland using satellite imagery and demographic data, (2) track changes to annual rice paddy harvests using time series satellite data, and (3) model the potential effects of climate change on rice paddies by incorporating farmer interview data into a crop systems model. The results of these analyses show that the footprint of Ho Chi Minh City grew nearly five times between 1990 and 2012. Mismatches between urban development and population growth suggest that peri-urbanization is driven by supply-side investment, and that much of this form of land expansion has occurred near major transit routes. In the nearby Mekong River Delta, triple-cropped rice paddy area doubled between 2000 and 2010, from one-third to two-thirds of rice fields, while paddy area expanded by about 10%. These results illustrate the intensification of farming practices since Vietnam liberalized its economy, yet it is not clear whether such practices are environmentally sustainable long-term. Although triple-cropped paddy fields have expanded, future overall production is estimated to decline without the effects of CO2 fertilization. Temperatures are anticipated

  4. GC23G-1310: Investigation Into the Effects of Climate Variability and Land Cover Change on the Hydrologic System of the Lower Mekong Basin

    NASA Technical Reports Server (NTRS)

    Markert, Kel N.; Griffin, Robert; Limaye, Ashutosh S.; McNider, Richard T.; Anderson, Eric R.

    2016-01-01

    The Lower Mekong Basin (LMB) is an economically and ecologically important region that experiences hydrologic hazards such as floods and droughts, which can directly affect human well-being and limit economic growth and development. To effectively develop long-term plans for addressing hydrologic hazards, the regional hydrological response to climate variability and land cover change needs to be evaluated. This research aims to investigate how climate variability, specifically variations in the precipitation regime, and land cover change will affect hydrologic parameters both spatially and temporally within the LMB. The research goal is achieved by (1) modeling land cover change for a baseline land cover change scenario as well as changes in land cover with increases in forest or agriculture and (2) using projected climate variables and modeled land cover data as inputs into the Variable Infiltration Capacity (VIC) hydrologic model to simulate the changes to the hydrologic system. The VIC model outputs were analyzed against historic values to understand the relative contribution of climate variability and land cover to change, where these changes occur, and to what degree these changes affect the hydrology. This study found that the LMB hydrologic system is more sensitive to climate variability than land cover change. On average, climate variability was found to increase discharge and evapotranspiration (ET) while decreasing water storage. The change in land cover show that increasing forest area will slightly decrease discharge and increase ET while increasing agriculture area increases discharge and decreases ET. These findings will help the LMB by supporting individual country policy to plan for future hydrologic changes as well as policy for the basin as a whole.

  5. Techniques for delineation and portrayal of land cover types using ERTS-1 data. [Pennsylvania, Montana, and Texas

    NASA Technical Reports Server (NTRS)

    Mcmurtry, G. J.; Petersen, G. W. (Principal Investigator); Wilson, A. D.

    1974-01-01

    The author has identified the following significant results. ERTS data was used to map land cover in agricultural areas, although in some parts of Pennsylvania, with small irregular fields, many of the pixels overlap field boundaries and cause difficulties in classification. Various techniques and devices were used to display the results of these land cover analyses. The most promising approach would be a user-interactive color monitor interfaced with a large computer so that classification results could be displayed on the CRT and these results output by a hard complete copier.

  6. 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

  7. 43 CFR 3400.3-3 - Department of Agriculture lands.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Department of Agriculture lands. 3400.3-3 Section 3400.3-3 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND...: General § 3400.3-3 Department of Agriculture lands. Subject to the provisions of § 3400.3-1, the Secretary...

  8. 43 CFR 3400.3-3 - Department of Agriculture lands.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Department of Agriculture lands. 3400.3-3 Section 3400.3-3 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND...: General § 3400.3-3 Department of Agriculture lands. Subject to the provisions of § 3400.3-1, the Secretary...

  9. 43 CFR 3400.3-3 - Department of Agriculture lands.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Department of Agriculture lands. 3400.3-3 Section 3400.3-3 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND...: General § 3400.3-3 Department of Agriculture lands. Subject to the provisions of § 3400.3-1, the Secretary...

  10. 43 CFR 3400.3-3 - Department of Agriculture lands.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Department of Agriculture lands. 3400.3-3 Section 3400.3-3 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND...: General § 3400.3-3 Department of Agriculture lands. Subject to the provisions of § 3400.3-1, the Secretary...

  11. 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.

  12. Tracking Agricultural Land Degradation with Landsat

    NASA Astrophysics Data System (ADS)

    Lam, K.; Jimenez, U.; Mclean, A.

    2013-12-01

    Land preservation and in particular, soil preservation, is key to maintaining the stability of wildlife on earth. The necessity to maintain land quality isn't unique to any specific area, it is a global issue. Land degradation can be witnessed across the globe, from the Heihe River Basin, China to the San Joaquin River in Central Valley, California. Large-scale 'traditional' agricultural practices such as widespread monoculture, overuse of chemical fertilizers and pesticides, and over-farming, have been found to cause significant land degradation in many regions. Once the causes of land degradation have been established, it is important to research preventative and rehabilitative measures. This is where the popularization of agricultural sustainability has proven wildly important, manifesting in a world-wide phenomenon. This research used Landsat and ENVI to: (1) identify changes in vegetation, over time, along the Heihe River, in an effort to measure the effectiveness of a new mandate focused on rehabilitating this desertification-prone area; and (2) show changes in the San Joaquin River through three droughts (1986 to present). The sudden spur of interest in agricultural sustainability and land preservation has led to changes in legislation, such as the Heihe River Basin Mandate, increased concern over the use of land degrading techniques, tools, chemicals, and more research on extreme weather events.

  13. Nitrogen deposition, land cover conversion, climate, and contemporary carbon balance of Europe (Invited)

    NASA Astrophysics Data System (ADS)

    Churkina, G.; Zahle, S.; Hughes, J.; Viovy, N.; Chen, Y.; Jung, M.; Ramankutty, N.; Roedenbeck, C.; Heimann, M.; Jones, C.

    2009-12-01

    In Europe, atmospheric nitrogen deposition has more than doubled, air temperature was rising, forest cover was steadily increasing, while agricultural area was declining over the last 50 years. What effect have these changes had on the European carbon balance? In this study we estimate responses of the European land ecosystems to nitrogen deposition, rising CO2, land cover conversion and climate change. We use results from three ecosystem process models such as BIOME-BGC, JULES, and ORCHIDEE (-CN) to address this question. We discuss to which degree carbon balance of Europe has been altered by nitrogen deposition in comparison to other drivers and identify areas which carbon balance has been affected by anthropogenic changes the most. We also analyze ecosystems carbon pools which were affected by the abovementioned environmental changes.

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

    USGS Publications Warehouse

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

    2005-01-01

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

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

    PubMed

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

    2014-01-01

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

  16. 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.

  17. Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: NLCD 2001 Land Use and Land Cover

    USGS Publications Warehouse

    Wieczorek, Michael; LaMotte, Andrew E.

    2010-01-01

    This tabular data set represents the estimated area of land use and land cover from the National Land Cover Dataset 2001 (LaMotte, 2008), compiled for every MRB_E2RF1 catchment of the Major River Basins (MRBs, Crawford and others, 2006). The source data set represents land use and land cover for the conterminous United States for 2001. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering the South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5) and the Pacific Northwest (MRB7) river basins.

  18. Land cover, land use changes and air pollution in Asia: a synthesis

    NASA Astrophysics Data System (ADS)

    Vadrevu, Krishna; Ohara, Toshimasa; Justice, Chris

    2017-12-01

    A better understanding of land cover/land use changes (LCLUC) and their interactions with the atmospheric environment is essential for the sustainable management of natural resources, environmental protection, air quality, agricultural planning and food security. The 15 papers published in this focus issue showcase a variety of studies relating to drivers and impacts of LCLUC and air pollution in different South/Southeast Asian (S/SEA) countries. This synthesis article, in addition to giving context to the articles in this focus issue, also reviews the broad linkages between population, LCLUC and air pollution. Additionally, we identify knowledge gaps and research priorities that are essential in addressing air pollution issues in the region. We conclude that for effective pollution mitigation in S/SEA countries, quantifying drivers, sources and impacts of pollution need a thorough data analysis through ground-based instrumentation, models and integrated research approaches. We also stress the need for the development of sustainable technologies and strengthening the scientific and resource management communities through capacity building and training activities to address air pollution issues in S/SEA countries.

  19. Agricultural land use change in the Northeast

    USDA-ARS?s Scientific Manuscript database

    The USDA Census of Agriculture (http://www.agcensus.usda.gov/) provides county-level estimates of farm numbers, land use area and livestock and crop production every five years. In 2007, only eight of the 299 counties that make up the twelve Northeastern states had no agricultural land use. About 20...

  20. Land use and land cover digital data from 1:250,000- and 1:100,000- scale maps

    USGS Publications Warehouse

    ,

    1990-01-01

    The Earth Science Information Centers (ESIC) distribute digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. The data files are grouped into four basic types. The first type, called a Digital Line Graph (DLG), is line map information in digital form. These data files include information on planimetric base categories, such as transportation, hydrography, and boundaries. The second type, called a Digital Elevation Model (DEM), consists of a sampled array of elevations for ground positions that are usually at regularly spaced intervals. The third type, Land Use and Land Cover digital data, provide information on nine major classes of land use such as urban, agricultural, or forest as well as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for known places, features, and areas in the United States identified by a proper name.

  1. Radiative forcing over the conterminous United States due to contemporary land cover land use albedo change

    USGS Publications Warehouse

    Barnes, Christopher; Roy, David P.

    2008-01-01

    Recently available satellite land cover land use (LCLU) and albedo data are used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing for 36 ecoregions covering 43% of the conterminous United States (CONUS). Moderate Resolution Imaging Spectroradiometer (MODIS) snow-free broadband albedo values are derived from Landsat LCLU classification maps located using a stratified random sampling methodology to estimate ecoregion estimates of LCLU induced albedo change and surface radiative forcing. The results illustrate that radiative forcing due to LCLU change may be disguised when spatially and temporally explicit data sets are not used. The radiative forcing due to contemporary LCLU albedo change varies geographically in sign and magnitude, with the most positive forcings (up to 0.284 Wm−2) due to conversion of agriculture to other LCLU types, and the most negative forcings (as low as −0.247 Wm−2) due to forest loss. For the 36 ecoregions considered a small net positive forcing (i.e., warming) of 0.012 Wm−2 is estimated.

  2. 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.

  3. Impacts of agricultural land use on biological integrity: A causal analysis

    USGS Publications Warehouse

    Riseng, C.M.; Wiley, M.J.; Black, R.W.; Munn, M.D.

    2011-01-01

    Agricultural land use has often been linked to nutrient enrichment, habitat degradation, hydrologic alteration, and loss of biotic integrity in streams. The U.S. Geological Survey's National Water Quality Assessment Program sampled 226 stream sites located in eight agriculture-dominated study units across the United States to investigate the geographic variability and causes of agricultural impacts on stream biotic integrity. In this analysis we used structural equation modeling (SEM) to develop a national and set of regional causal models linking agricultural land use to measured instream conditions. We then examined the direct, indirect, and total effects of agriculture on biotic integrity as it acted through multiple water quality and habitat pathways. In our nation-wide model, cropland affected benthic communities by both altering structural habitats and by imposing water quality-related stresses. Regionspecific modeling demonstrated that geographic context altered the relative importance of causal pathways through which agricultural activities affected stream biotic integrity. Cropland had strong negative total effects on the invertebrate community in the national, Midwest, and Western models, but a very weak effect in the Eastern Coastal Plain model. In theWestern Arid and Eastern Coastal Plain study regions, cropland impacts were transmitted primarily through dissolved water quality contaminants, but in the Midwestern region, they were transmitted primarily through particulate components of water quality. Habitat effects were important in the Western Arid model, but negligible in the Midwest and Eastern Coastal Plain models. The relative effects of riparian forested wetlands also varied regionally, having positive effects on biotic integrity in the Eastern Coastal Plain andWestern Arid region models, but no statistically significant effect in the Midwest. These differences in response to cropland and riparian cover suggest that best management practices and

  4. 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.

  5. Agricultural Land Conversion: Background and Issues.

    ERIC Educational Resources Information Center

    Furuseth, Owen J.

    1982-01-01

    Analyzes forces contributing to the conversion of agricultural land for other uses, causes for the depletion of the land, major issues surrounding the loss of farmland, and current policies designed to control haphazard land conversion. Concludes that the United States lacks a national farmland protection policy. (KC)

  6. 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.

  7. 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

  8. Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: NLCD 2001 Land Use and Land Cover

    USGS Publications Warehouse

    Wieczorek, Michael; LaMotte, Andrew E.

    2010-01-01

    This data set represents the estimated area of land use and land cover from the National Land Cover Dataset 2001 (LaMotte, 2008), compiled for every catchment of NHDPlus for the conterminous United States. The source data set represents land use and land cover for the conterminous United States for 2001. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality

  9. EnviroAtlas -- Memphis, TN (2012) -- One Meter Resolution Urban Land Cover Data Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas ). The Memphis, TN EnviroAtlas One Meter-scale Urban Land Cover (MULC) dataset comprises 2,733 km2 around the city of Memphis, surrounding towns, and rural areas. These leaf-on LC data and maps were derived from 1-m pixel, four-band (red, green, blue, and near-infrared) aerial photography acquired from the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) on four dates in 2012: June 15, June 18, June 21 and June 23, and one date in 2013: July 12. Three separate LiDAR (Light Detection and Ranging) data sets collected on February 19, 2009 00e2?? August 2, 2010, December 1-2, 2011 and January 23-24, 2012 were integrated for Shelby Co., TN, Crittenden Co., AR, and DeSoto Co, MS. Five MULC classes were mapped directly from the NAIP and LiDAR data: Water, Impervious, Soil, Trees, and Grass/Herbaceous. Agriculture was derived from USDA Common Land Unit (CLU) data. Woody and emergent wetlands were copied from existing National Wetlands Inventory (NWI) data. Analysis of a random sampling of 612 photo-interpreted land cover reference points yielded an overall users accuracy of 86.9%. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-u

  10. How Scientists Differentiate Between Land Cover Types

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Before scientists can transform raw satellite image data into land cover maps, they must decide on what categories of land cover they would like to use. Categories are simply the types of landscape that the scientists are trying to map and can vary greatly from map to map. For flood maps, there may be only two categories-dry land and wet land-while a standard global land cover map may have seventeen categories including closed shrub lands, savannas, evergreen needle leaf forest, urban areas, and ice/snow. The only requirement for any land cover category is that it have a distinct spectral signature that a satellite can record. As can be seen through a prism, many different colors (wavelengths) make up the spectra of sunlight. When sunlight strikes objects, certain wavelengths are absorbed and others are reflected or emitted. The unique way in which a given type of land cover reflects and absorbs light is known as its spectral signature. Anyone who has flown over the midwestern United States has seen evidence of this phenomenon. From an airplane window, the ground appears as a patchwork of different colors formed by the fields of crops planted there. The varying pigments of the leaves, the amount of foliage per square foot, the age of the plants, and many other factors create this tapestry. Most imaging satellites are sensitive to specific wavelengths of light, including infrared wavelengths that cannot be seen with the naked eye. Passive satellite remote sensors-such as those flown on Landsat 5, Landsat 7, and Terra-have a number of light detectors (photoreceptors) on board that measure the energy reflected or emitted by the Earth. One light detector records only the blue part of the spectrum coming off the Earth. Another observes all the yellow-green light and still another picks up on all the near-infrared light. The detectors scan the Earth's surface as the satellite travels in a circular orbit very nearly from pole-to-pole. To differentiate between types of

  11. 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.

  12. Has the conversion of natural wetlands to agricultural land increased the incidence and severity of damaging freezes in south Florida?

    USGS Publications Warehouse

    Marshall, C.H.; Pielke, R.A.; Steyaert, L.T.

    2004-01-01

    On several occasions, winter freezes have wrought severe destruction on Florida agriculture. A series of devastating freezes around the turn of the twentieth century, and again during the 1980s, were related to anomalies in the large-scale flow of the ocean–atmosphere system. During the twentieth century, substantial areas of wetlands in south Florida were drained and converted to agricultural land for winter fresh vegetable and sugarcane production. During this time, much of the citrus industry also was relocated to those areas to escape the risk of freeze farther to the north. The purpose of this paper is to present a modeling study designed to investigate whether the conversion of the wetlands to agriculture itself could have resulted in or exacerbated the severity of recent freezes in those agricultural areas of south Florida.For three recent freeze events, a pair of simulations was undertaken with the Regional Atmospheric Modeling System. One member of each pair employed land surface properties that represent pre-1900s (near natural) land cover, whereas the other member of each pair employed data that represent near-current land-use patterns as derived from analysis of Landsat data valid for 1992/93. These two different land cover datasets capture well the conversion of wetlands to agriculture in south Florida during the twentieth century. Use of current land surface properties resulted in colder simulated minimum temperatures and temperatures that remained below freezing for a longer period at locations of key agricultural production centers in south Florida that were once natural wetlands. Examination of time series of the surface energy budget from one of the cases reveals that when natural land cover is used, a persistent moisture flux from the underlying wetlands during the nighttime hours served to prevent the development of below-freezing temperatures at those same locations. When the model results were subjected to an important sensitivity factor

  13. 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.

  14. The impact of gold mining and agricultural concessions on the tree cover and local communities in northern Myanmar.

    PubMed

    Papworth, Sarah; Rao, Madhu; Oo, Myint Myint; Latt, Kyaw Thinn; Tizard, Robert; Pienkowski, Thomas; Carrasco, L Roman

    2017-04-24

    Myanmar offers unique opportunities for both biodiversity conservation and foreign direct investment due to projected economic growth linked to natural resource exploitation. Industrial-scale development introduces new land uses into the landscape, with unknown repercussions for local communities and biodiversity conservation. We use participatory mapping of 31 communities, focus groups in 28 communities, and analyses of forest cover change during 2000-2010 using MODIS vegetation continuous fields images, to understand the social and environmental impacts of gold mining and agricultural concessions in Myanmar's Hukaung Valley (~21,800 km 2 ). Local communities, particularly the poorest households, benefit from work and trade opportunities offered by gold mining and agricultural companies but continue to depend on forests for house construction materials, food, and income from the sale of forest resources. However, gold mining and agricultural concessions reduce tree cover, potentially reducing access to forest resources and further marginalizing these households. Our analyses do not provide evidence that long-term resident communities contributed to forest cover loss between 2000 and 2010. We argue that landscape management, which recognizes local community rights to customary community use areas, and appropriate zoning for commercial land uses and protected areas could contribute to both local livelihoods and protect biodiversity throughout Myanmar during economic growth.

  15. The impact of gold mining and agricultural concessions on the tree cover and local communities in northern Myanmar

    PubMed Central

    Papworth, Sarah; Rao, Madhu; Oo, Myint Myint; Latt, Kyaw Thinn; Tizard, Robert; Pienkowski, Thomas; Carrasco, L. Roman

    2017-01-01

    Myanmar offers unique opportunities for both biodiversity conservation and foreign direct investment due to projected economic growth linked to natural resource exploitation. Industrial-scale development introduces new land uses into the landscape, with unknown repercussions for local communities and biodiversity conservation. We use participatory mapping of 31 communities, focus groups in 28 communities, and analyses of forest cover change during 2000–2010 using MODIS vegetation continuous fields images, to understand the social and environmental impacts of gold mining and agricultural concessions in Myanmar’s Hukaung Valley (~21,800 km2). Local communities, particularly the poorest households, benefit from work and trade opportunities offered by gold mining and agricultural companies but continue to depend on forests for house construction materials, food, and income from the sale of forest resources. However, gold mining and agricultural concessions reduce tree cover, potentially reducing access to forest resources and further marginalizing these households. Our analyses do not provide evidence that long-term resident communities contributed to forest cover loss between 2000 and 2010. We argue that landscape management, which recognizes local community rights to customary community use areas, and appropriate zoning for commercial land uses and protected areas could contribute to both local livelihoods and protect biodiversity throughout Myanmar during economic growth. PMID:28436455

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. A spatially-explicit data driven approach to assess the effect of agricultural land occupation on species groups

    NASA Astrophysics Data System (ADS)

    Elshout, P.; van Zelm, R.; Karuppiah, R.; Laurenzi, I.; Huijbregts, M.

    2013-12-01

    Change of vegetation cover and increased land use intensity can directly affect the natural habitat and the wildlife it houses. The actual impact of agricultural land use is region specific as crops are grown under various climatic conditions and ways of cultivation and refining. Furthermore, growing a specific crop in a tropical region may require clearance of rainforest while the same crop may replace natural grasslands in temperate regions. Within life cycle impact assessment (LCIA), methods to address impacts of land use on a global scale are still in need of development. We aim to extend existing methods to improve the robustness of LCIA by allowing spatial differentiation of agricultural land use impacts. The goal of this study is to develop characterization factors for the direct impact of land use on biodiversity, which results from the replacement of natural habitat with farmland. The characterization factor expresses the change in species richness under crop cultivation compared to the species richness in the natural situation over a certain area. A second goal was to identify the differences in impacts caused by cultivation of different crop types, sensitivity of different taxonomic groups, and differences in natural land cover. Empirical data on species richness were collected from literature for both natural reference situations and agricultural land use situations. Reference situations were selected on an ecoregion or biome basis. We calculated characterization factors for four crop groups (oil palm, low crops, cereals, and perennial grasses), four species groups (arthropods, birds, mammals, vascular plants), and six biomes.

  1. Influence of local riparian cover and watershed runoff potential on invertebrate communities in agricultural streams in the Minnesota River Basin

    USGS Publications Warehouse

    ZumBerge, Jeremy Ryan; Perry, James A.; Lee, Kathy E.

    2003-01-01

    While it is difficult to determine the relative influence of watershed runoff potential and local riparian cover, invertebrate communities may be more strongly influenced by local wooded riparian cover than by watershed runoff potential. Invertebrate community measures indicate greater degradation at the open riparian cover, high runoff potential sites and less degradation at the wooded riparian cover, low runoff potential sites. In addition, differences between streams with wooded riparian cover and sites with open riparian cover were greater in watersheds with high runoff potential. The variance explained by riparian cover and runoff potential is relatively independent of other land-use effects. Wooded riparian cover influences invertebrate community composition by its relation to the other physical environmental variables. This study indicates that wooded riparian cover may be effective in maintaining stream biotic integrity in watersheds dominated by agricultural land use.

  2. Topography Mediates the Influence of Cover Crops on Soil Nitrate Levels in Row Crop Agricultural Systems

    PubMed Central

    Ladoni, Moslem; Kravchenko, Alexandra N.; Robertson, G. Phillip

    2015-01-01

    Supplying adequate amounts of soil N for plant growth during the growing season and across large agricultural fields is a challenge for conservational agricultural systems with cover crops. Knowledge about cover crop effects on N comes mostly from small, flat research plots and performance of cover crops across topographically diverse agricultural land is poorly understood. Our objective was to assess effects of both leguminous (red clover) and non-leguminous (winter rye) cover crops on potentially mineralizable N (PMN) and NO3--N levels across a topographically diverse landscape. We studied conventional, low-input, and organic managements in corn-soybean-wheat rotation. The rotations of low-input and organic managements included rye and red clover cover crops. The managements were implemented in twenty large undulating fields in Southwest Michigan starting from 2006. The data collection and analysis were conducted during three growing seasons of 2011, 2012 and 2013. Observational micro-plots with and without cover crops were laid within each field on three contrasting topographical positions of depression, slope and summit. Soil samples were collected 4–5 times during each growing season and analyzed for NO3--N and PMN. The results showed that all three managements were similar in their temporal and spatial distributions of NO3 —N. Red clover cover crop increased NO3--N by 35% on depression, 20% on slope and 32% on summit positions. Rye cover crop had a significant 15% negative effect on NO3--N in topographical depressions but not in slope and summit positions. The magnitude of the cover crop effects on soil mineral nitrogen across topographically diverse fields was associated with the amount of cover crop growth and residue production. The results emphasize the potential environmental and economic benefits that can be generated by implementing site-specific topography-driven cover crop management in row-crop agricultural systems. PMID:26600462

  3. Topography Mediates the Influence of Cover Crops on Soil Nitrate Levels in Row Crop Agricultural Systems.

    PubMed

    Ladoni, Moslem; Kravchenko, Alexandra N; Robertson, G Phillip

    2015-01-01

    Supplying adequate amounts of soil N for plant growth during the growing season and across large agricultural fields is a challenge for conservational agricultural systems with cover crops. Knowledge about cover crop effects on N comes mostly from small, flat research plots and performance of cover crops across topographically diverse agricultural land is poorly understood. Our objective was to assess effects of both leguminous (red clover) and non-leguminous (winter rye) cover crops on potentially mineralizable N (PMN) and [Formula: see text] levels across a topographically diverse landscape. We studied conventional, low-input, and organic managements in corn-soybean-wheat rotation. The rotations of low-input and organic managements included rye and red clover cover crops. The managements were implemented in twenty large undulating fields in Southwest Michigan starting from 2006. The data collection and analysis were conducted during three growing seasons of 2011, 2012 and 2013. Observational micro-plots with and without cover crops were laid within each field on three contrasting topographical positions of depression, slope and summit. Soil samples were collected 4-5 times during each growing season and analyzed for [Formula: see text] and PMN. The results showed that all three managements were similar in their temporal and spatial distributions of NO3-N. Red clover cover crop increased [Formula: see text] by 35% on depression, 20% on slope and 32% on summit positions. Rye cover crop had a significant 15% negative effect on [Formula: see text] in topographical depressions but not in slope and summit positions. The magnitude of the cover crop effects on soil mineral nitrogen across topographically diverse fields was associated with the amount of cover crop growth and residue production. The results emphasize the potential environmental and economic benefits that can be generated by implementing site-specific topography-driven cover crop management in row

  4. 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

  5. Multitemporal analysis of Landsat images to detect land use land cover changes for monitoring soil sealing in the Nola area (Naples, Italy)

    NASA Astrophysics Data System (ADS)

    De Giglio, Michaela; Allocca, Maria; Franci, Francesca

    2016-10-01

    Land Use Land Cover Changes (LULCC) data provide objective information to support environmental policy, urban planning purposes and sustainable land development. Understanding of past land use/cover practices and current landscape patterns is critical to assess the effects of LULCC on the Earth system. Within the framework of soil sealing in Italy, the present study aims to assess the LULCC of the Nola area (Naples metropolitan area, Italy), relating to a thirty year period from 1984 to 2015. The urban sprawl affects this area causing the impervious surface increase, the loss in rural areas and landscape fragmentation. Located near Vesuvio volcano and crossed by artificial filled rivers, the study area is subject to landslide, hydraulic and volcanic risks. Landsat time series has been processed by means of the supervised per-pixel classification in order to produce multitemporal Land Use Land Cover maps. Then, post-classification comparison approach has been applied to quantify the changes occurring between 1984 and 2015, also analyzing the intermediate variations in 1999, namely every fifteen years. The results confirm the urban sprawl. The increase of the built-up areas mainly causes the habitat fragmentation and the agricultural land conversion of the Nola area that is already damaged by unauthorized disposal of urban waste. Moreover, considering the local risk maps, it was verified that some of the new urban areas were built over known hazardous sites. In order to limit the soil sealing, urgent measures and sustainable urban planning are required.

  6. Growth of Cities and Loss of Streams: Land Cover Change Impacts on Stream Channel Loss in Central Oklahoma from 1874 to 2010

    EPA Science Inventory

    Central Oklahoma has undergone substantial land cover changes since the 1800’s. Accordingly, regional watersheds have been covered by impervious surfaces, peripheral agricultural areas have been subdivided or intensified, and large reservoirs have been constructed. Here, we...

  7. 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. ...

  8. 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,...

  9. Analysis of the spatio-temporal and semantic aspects of land-cover/use change dynamics 1991-2001 in Albania at national and district levels.

    PubMed

    Jansen, Louisa J M; Carrai, Giancarlo; Morandini, Luca; Cerutti, Paolo O; Spisni, Andrea

    2006-08-01

    In the turmoil of a rapidly changing economy the Albanian government needs accurate and timely information for management of their natural resources and formulation of land-use policies. The transformation of the forestry sector has required major changes in the legal, regulatory and management framework. The World Bank financed Albanian National Forest Inventory project provides an analysis of spatially explicit land-cover/use change dynamics in the period 1991-2001 using the FAO/UNEP Land Cover Classification System for codification of classes, satellite remote sensing and field survey for data collection and elements of the object-oriented geo-database approach to handle changes as an evolution of land-cover/use objects, i.e. polygons, over time to facilitate change dynamics analysis. Analysis results at national level show the trend of natural resources depletion in the form of modifications and conversions that lead to a gradual shift from land-cover/use types with a tree cover to less dense tree covers or even a complete removal of trees. Policy failure (e.g., corruption, lack of law enforcement) is seen as the underlying cause. Another major trend is urbanisation of areas near large urban centres that change urban-rural linkages. Furthermore, after privatisation agricultural areas increased in the hills where environmental effects may be detrimental, while prime agricultural land in the plains is lost to urbanisation. At district level, the local variability of spatially explicit land-cover/use changes shows different types of natural resources depletion. The distribution of changes indicates a regional prevalence, thus a decentralised approach to the natural resources management could be advocated.

  10. Land cover changes associated with recent energy development in the Williston Basin; Northern Great Plains, USA

    USGS Publications Warehouse

    Preston, Todd M.; Kim, Kevin

    2016-01-01

    The Williston Basin in the Northern Great Plains has experienced rapid energy development since 2000. To evaluate the land cover changes resulting from recent (2000 – 2015) development, the area and previous land cover of all well pads (pads) constructed during this time was determined, the amount of disturbed and reclaimed land adjacent to pads was estimated, land cover changes were analyzed over time for three different well types, and the effects from future development were predicted. The previous land cover of the 12,990 ha converted to pads was predominately agricultural (49.5%) or prairie (47.4%) with lesser amounts of developed (2.3%), aquatic (0.5%), and forest (0.4%). Additionally, 12,121 ha have likely been disturbed and reclaimed. The area required per gas well remained constant through time while the land required per oil well increased initially and then decreased as development first shifted from conventional to unconventional drilling and then to multi-bore pads. For non-oil-and- gas wells (i.e. stratigraphic test wells, water wells, injection wells, etc.), the area per well increased through time likely due to increased produced water disposal requirements. Future land cover change is expected to be 2.7 times greater than recent development with much of the development occurring in five counties in the core Bakken development area. Direct land cover change and disturbance from recent and expected development are predicted to affect 0.4% of the landscape across the basin; however, in the core Bakken development area, 2.3% of the landscape will be affected including 2.1% of the remaining grassland. Although future development will result in significant land cover change, evolving industry practices and proactive siting decisions, such as development along energy corridors and placing pads in areas previously altered by human activity, have the potential to reduce the ecological effects of future energy development in the Williston Basin.

  11. EnviroAtlas -Portland, ME- One Meter Resolution Urban Land Cover (2010) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The Portland, ME land cover map was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from Late Summer 2010 at 1 m spatial resolution. Nine land cover classes were mapped: water, impervious surfaces (dark and light), soil and barren land, trees and forest, grass and herbaceous non-woody vegetation, agriculture, and wetlands (woody and emergent). An accuracy assessment using a stratified random sampling of 600 samples yielded an overall accuracy of 87.5 percent using a minimum mapping unit of 9 pixels (3x3 pixel window). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Portland.This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  12. 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.

  13. Land cover in the Guayas Basin using SAR images from low resolution ASAR Global mode to high resolution Sentinel-1 images

    NASA Astrophysics Data System (ADS)

    Bourrel, Luc; Brodu, Nicolas; Frappart, Frédéric

    2016-04-01

    Remotely sensed images allow a frequent monitoring of land cover variations at regional and global scale. Recently launched Sentinel-1 satellite offers a global cover of land areas at an unprecedented spatial (20 m) and temporal (6 days at the Equator). We propose here to compare the performances of commonly used supervised classification techniques (i.e., k-nearest neighbors, linear and Gaussian support vector machines, naive Bayes, linear and quadratic discriminant analyzes, adaptative boosting, loggit regression, ridge regression with one-vs-one voting, random forest, extremely randomized trees) for land cover applications in the Guayas Basin, the largest river basin of the Pacific coast of Ecuator (area ~32,000 km²). The reason of this choice is the importance of this region in Ecuatorian economy as its watershed represents 13% of the total area of Ecuador where 40% of the Ecuadorian population lives. It also corresponds to the most productive region of Ecuador for agriculture and aquaculture. Fifty percents of the country shrimp farming production comes from this watershed, and represents with agriculture the largest source of revenue of the country. Similar comparisons are also performed using ENVISAT ASAR images acquired in global mode (1 km of spatial resolution). Accuracy of the results will be achieved using land cover map derived from multi-spectral images.

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

    USGS Publications Warehouse

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

    2018-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2018-04-01

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

  16. EnviroAtlas - Austin, TX - Land Cover by Block Group

    EPA Pesticide Factsheets

    This EnviroAtlas dataset describes the percentage of each block group that is classified as impervious, forest, green space, and agriculture. Forest is defined as Trees & Forest. Green space is defined as Trees & Forest, Grass & Herbaceous, and Agriculture. This dataset also includes the area per capita for each block group for some land cover types. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  17. 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...

  18. EnviroAtlas -Pittsburgh, PA- One Meter Resolution Urban Land Cover Data (2010) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas).The EnviroAtlas Pittsburgh, PA land cover map was generated from United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP) four band (red, green, blue, and near infrared) aerial photography at 1 m spatial resolution. Imagery was collected on multiple dates in June 2010. Five land cover classes were mapped: water, impervious surfaces, soil and barren land, trees and forest, and grass and herbaceous non-woody vegetation. An accuracy assessment of 500 completely random and 81 stratified random points yielded an overall accuracy of 86.57 percent. The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Pittsburgh, PA. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  19. 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.

  20. 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.

  1. EnviroAtlas -Tampa, FL- One Meter Resolution Urban Land Cover (2010)

    EPA Pesticide Factsheets

    The EnviroAtlas Tampa, FL land cover map was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from April-May 2010 at 1 m spatial resolution. Eight land cover classes were mapped: impervious surface, soil and barren, grass and herbaceous, trees and forest, water, agriculture, woody wetland, and emergent wetland. The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Tampa, and includes the cities of Clearwater and St. Petersburg, as well as additional out-lying areas. An accuracy assessment using a stratified random sampling of 600 samples (100 per class) yielded an overall accuracy of 70.67 percent and an area weighted accuracy of 81.87 percent using a minimum mapping unit of 9 pixels (3x3 pixel window). This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  2. Digital spatial soil and land information for agriculture development

    NASA Astrophysics Data System (ADS)

    Sharma, R. K.; Laghathe, Pankaj; Meena, Ranglal; Barman, Alok Kumar; Das, Satyendra Nath

    2006-12-01

    Natural resource management calls for study of natural system prevailing in the country. In India floods and droughts visit regularly, causing extensive damages of natural wealth including agriculture that are crucial for sustenance of economic growth. The Indian Sub-continent drained by many major rivers and their tributaries where watershed, the hydrological unit forms a natural system that allows management and development of land resources following natural harmony. Acquisition of various kinds and levels of soil and land characteristics using both conventional and remote sensing techniques and subsequent development of digital spatial data base are essential to evolve strategy for planning watershed development programmes, their monitoring and impact evaluation. The multi-temporal capability of remote sensing sensors helps to update the existing data base which are of dynamic in nature. The paper outlines the concept of spatial data base development, generation using remote sensing techniques, designing of data structure, standardization and integration with watershed layers and various non spatial attribute data for various applications covering watershed development planning, alternate land use planning, soil and water conservation, diversified agriculture practices, generation of soil health card, soil and land reclamation, etc. The soil and land characteristics are vital to derive various interpretative groupings or master table that helps to generate the desired level of information of various clients using the GIS platform. The digital spatial data base on soils and watersheds generated by All India Soil and Land Use Survey will act as a sub-server of the main GIS based Web Server being hoisted by the planning commission for application of spatial data for planning purposes under G2G domain. It will facilitate e-governance for natural resource management using modern technology.

  3. 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.

  4. The 1980 land cover for the Puget Sound region

    NASA Technical Reports Server (NTRS)

    Shinn, R. D.; Westerlund, F. V.; Eby, J. R.

    1982-01-01

    Both LANDSAT imagery and the video information communications and retrieval software were used to develop a land cover classifiction of the Puget Sound of Washington. Planning agencies within the region were provided with a highly accurate land cover map registered to the 1980 census tracts which could subsequently be incorporated as one data layer in a multi-layer data base. Many historical activities related to previous land cover mapping studies conducted in the Puget Sound region are summarized. Valuable insight into conducting a project with a large community of users and in establishing user confidence in a multi-purpose land cover map derived from LANDSAT is provided.

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. Aspects of agricultural land use in Ireland

    NASA Astrophysics Data System (ADS)

    Lee, J.

    1986-02-01

    Ireland's soil regions consist largely of Luvisols, Cambisols, and Gleysols. Approximately 60% of Ireland's land area is subject to varying degrees of soil limitations. Twenty-five percent of the land area comprises wet lowland mineral soils. Ninety percent of Ireland's agricultural area comprises pasture, hay, and silage. Approximately 30% of the agricultural area is devoted to dairying, and 55% to cattle production. is devoted to dairying, and 55% to cattle production. Trends in agricultural land use indicate that tillage declined substantially while livestock showed a substantial increase particularly in the decade 1965 1975. Research concludes that over 2.8 million ha has a capacity to carry at least 100 LU/40 ha (100 acres). Levels of fertilizer use in Ireland are below EEC levels. The highest fertilizer use levels are associated with the eastern and southern areas of Ireland. Tillage crops occupy only 10% of the agricultural area, while they account for 26% of tertilizer and lime use.

  10. 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

  11. 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.

  12. Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics

    USGS Publications Warehouse

    Pervez, Md Shahriar; Brown, Jesslyn F.

    2010-01-01

    Accurate geospatial information on the extent of irrigated land improves our understanding of agricultural water use, local land surface processes, conservation or depletion of water resources, and components of the hydrologic budget. We have developed a method in a geospatial modeling framework that assimilates irrigation statistics with remotely sensed parameters describing vegetation growth conditions in areas with agricultural land cover to spatially identify irrigated lands at 250-m cell size across the conterminous United States for 2002. The geospatial model result, known as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset (MIrAD-US), identified irrigated lands with reasonable accuracy in California and semiarid Great Plains states with overall accuracies of 92% and 75% and kappa statistics of 0.75 and 0.51, respectively. A quantitative accuracy assessment of MIrAD-US for the eastern region has not yet been conducted, and qualitative assessment shows that model improvements are needed for the humid eastern regions where the distinction in annual peak NDVI between irrigated and non-irrigated crops is minimal and county sizes are relatively small. This modeling approach enables consistent mapping of irrigated lands based upon USDA irrigation statistics and should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. An improved version of the model with revised datasets is planned and will employ 2007 USDA irrigation statistics.

  13. Spatio-temporal analysis of agricultural land-use intensity across the Western Siberian grain belt.

    PubMed

    Kühling, Insa; Broll, Gabriele; Trautz, Dieter

    2016-02-15

    The Western Siberian grain belt covers 1millionkm² in Asiatic Russia and is of global importance for agriculture. Massive land-use changes took place in that region after the dissolution of the Soviet Union and the collapse of the state farm system. Decreasing land-use intensity (LUI) in post-Soviet Western Siberia was observed on grassland due to declining livestock whilst on cropland trends of land abandonment reversed in the early 2000s. Recultivation of abandoned cropland as well as increasing fertilizer inputs and narrowing crop rotations led to increasing LUI on cropland during the last two decades. Beyond that general trend, no information is available about spatial distribution and magnitude but a crucial precondition for the development of strategies for sustainable land management. To quantify changes and patterns in LUI, we developed an intensity index that reflects the impacts of land-based agricultural production. Based on subnational yearly statistical data, we calculated two separate input-orientated indices for cropland and grassland, respectively. The indices were applied on two spatial scale: at seven provinces covering the Western Siberian grain belt (Altay Kray, Chelyabinsk, Kurgan, Novosibirsk, Omsk, Sverdlovsk and Tyumen) and at all districts of the central province Tyumen. The spatio-temporal analysis clearly showed opposite trends for the two land-use types: decreasing intensity on grassland (-0.015 LUI units per year) and intensification on cropland (+0.014 LUI units per year). Furthermore, a spatial concentration towards intensity centres occurred during transition from a planned to a market economy. A principal component analysis enabled the individual calculations of both land-use types to be combined and revealed a strong link between biophysical conditions and LUI. The findings clearly showed the need for having a different strategy for future sustainable land management for grassland (predominantly used by livestock of households

  14. 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.

  15. 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.

  16. EnviroAtlas - Minneapolis/St. Paul, MN - One Meter Resolution Urban Area Land Cover Map (MULC) (2010)

    EPA Pesticide Factsheets

    The Minneapolis-St. Paul, MN EnviroAtlas Meter-scale Urban Land Cover (MULC) data were generated from four-band (red, green, blue, and near infrared) aerial photography provided by the United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP). The NAIP imagery for the state of Minnesota was collected during the summer and fall of 2010. Lidar data and relevant ancillary datasets contributed to the classification. Eight land cover types were classified: water, impervious surface, soil and barren land, trees and forest, grass and herbaceous, agriculture, woody wetland, and emergent wetland. An accuracy assessment of 644 completely random and 62 stratified random photointerpreted reference points yielded an overall User's Accuracy of 83 percent. The boundary of this data layer is delineated by the US Census Bureau's 2010 Urban Statistical Area for Minneapolis-St. Paul, MN plus a 1-km buffer. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associat

  17. The importance of agricultural lands for Himalayan birds in winter.

    PubMed

    Elsen, Paul R; Kalyanaraman, Ramnarayan; Ramesh, Krishnamurthy; Wilcove, David S

    2017-04-01

    The impacts of land-use change on biodiversity in the Himalayas are poorly known, notwithstanding widespread deforestation and agricultural intensification in this highly biodiverse region. Although intact primary forests harbor many Himalayan birds during breeding, a large number of bird species use agricultural lands during winter. We assessed how Himalayan bird species richness, abundance, and composition during winter are affected by forest loss stemming from agriculture and grazing. Bird surveys along 12 elevational transects within primary forest, low-intensity agriculture, mixed subsistence agriculture, and intensively grazed pastures in winter revealed that bird species richness and abundance were greatest in low-intensity and mixed agriculture, intermediate in grazed pastures, and lowest in primary forest at both local and landscape scales; over twice as many species and individuals were recorded in low-intensity agriculture than in primary forest. Bird communities in primary forests were distinct from those in all other land-use classes, but only 4 species were unique to primary forests. Low-, medium-, and high-intensity agriculture harbored 32 unique species. Of the species observed in primary forest, 80% had equal or greater abundance in low-intensity agricultural lands, underscoring the value of these lands in retaining diverse community assemblages at high densities in winter. Among disturbed landscapes, bird species richness and abundance declined as land-use intensity increased, especially in high-intensity pastures. Our results suggest that agricultural landscapes are important for most Himalayan bird species in winter. But agricultural intensification-especially increased grazing-will likely result in biodiversity losses. Given that forest reserves alone may inadequately conserve Himalayan birds in winter, comprehensive conservation strategies in the region must go beyond protecting intact primary forests and ensure that low-intensity agricultural

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

    PubMed

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

    2017-08-01

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

  19. Soil respiration and carbon loss relationship with temperature and land use conversion in freeze-thaw agricultural area.

    PubMed

    Ouyang, Wei; Lai, Xuehui; Li, Xia; Liu, Heying; Lin, Chunye; Hao, Fanghua

    2015-11-15

    Soil respiration (Rs) was hypothesized to have a special response pattern to soil temperature and land use conversion in the freeze-thaw area. The Rs differences of eight types of land use conversions during agricultural development were observed and the impacts of Rs on soil organic carbon (SOC) loss were assessed. The land use conversions during last three decades were categorized into eight types, and the 141 SOC sampling sites were grouped by conversion type. The typical soil sampling sites were subsequently selected for monitoring of soil temperature and Rs of each land use conversion types. The Rs correlations with temperature at difference depths and different conversion types were identified with statistical analysis. The empirical mean error model and the biophysical theoretical model with Arrhenius equation about the Rs sensitivity to temperature were both analyzed and shared the similar patterns. The temperature dependence of soil respiration (Q10) analysis further demonstrated that the averaged value of eight types of land use in this freeze-thaw agricultural area ranged from 1.15 to 1.73, which was lower than the other cold areas. The temperature dependence analysis demonstrated that the Rs in the top layer of natural land covers was more sensitive to temperature and experienced a large vertical difference. The natural land covers exhibited smaller Rs and the farmlands had the bigger value due to tillage practices. The positive relationships between SOC loss and Rs were identified, which demonstrated that Rs was the key chain for SOC loss during land use conversion. The spatial-vertical distributions of SOC concentration with the 1.5-km grid sampling showed that the more SOC loss in the farmland, which was coincided with the higher Rs in farmlands. The analysis of Rs dynamics provided an innovative explanation for SOC loss in the freeze-thaw agricultural area. The analysis of Rs dynamics provided an innovative explanation for SOC loss in the freeze

  20. Modelling analysis of water and land effects on agricultural development in the Heihe Agricultural Production Area, China

    NASA Astrophysics Data System (ADS)

    Wang, G.

    2017-12-01

    Water and land resources play vital roles in agricultural growth. They not only remarkably support overall economic growth, but may also restrict agricultural development. To document the influence of water and land on agriculture, we examined the "drag effects" of these two resources in limiting agricultural production. In this study, data from eight counties collected during 2000-2012 from the Heihe Agricultural Production Area in Gansu Province were used to analyze the drag effects of water and land resources on agricultural growth. These effects varied largely among the eight counties, which was consistent with the availability of these resources. This study will give scientific support to coordinating development with the availability of water and land resources in agricultural areas of China

  1. 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...

  2. Agroforestry: working trees for sequestering carbon on agricultural lands

    Treesearch

    M.M. Schoeneberger

    2008-01-01

    Agroforestry is an appealing option for sequestering carbon on agricultural lands because it can sequester significant amounts of carbon while leaving the bulk of the land in agricultural production. Simultaneously, it can help landowners and society address many other issues facing these lands, such as economic diversification, biodiversity, and water quality....

  3. 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

  4. 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

  5. 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

  6. 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).

  7. Impacts of land-use history on the recovery of ecosystems after agricultural abandonment

    NASA Astrophysics Data System (ADS)

    Krause, Andreas; Pugh, Thomas A. M.; Bayer, Anita D.; Lindeskog, Mats; Arneth, Almut

    2016-09-01

    Land-use changes have been shown to have large effects on climate and biogeochemical cycles, but so far most studies have focused on the effects of conversion of natural vegetation to croplands and pastures. By contrast, relatively little is known about the long-term influence of past agriculture on vegetation regrowth and carbon sequestration following land abandonment. We used the LPJ-GUESS dynamic vegetation model to study the legacy effects of different land-use histories (in terms of type and duration) across a range of ecosystems. To this end, we performed six idealized simulations for Europe and Africa in which we made a transition from natural vegetation to either pasture or cropland, followed by a transition back to natural vegetation after 20, 60 or 100 years. The simulations identified substantial differences in recovery trajectories of four key variables (vegetation composition, vegetation carbon, soil carbon, net biome productivity) after agricultural cessation. Vegetation carbon and composition typically recovered faster than soil carbon in subtropical, temperate and boreal regions, and vice versa in the tropics. While the effects of different land-use histories on recovery periods of soil carbon stocks often differed by centuries across our simulations, differences in recovery times across simulations were typically small for net biome productivity (a few decades) and modest for vegetation carbon and composition (several decades). Spatially, we found the greatest sensitivity of recovery times to prior land use in boreal forests and subtropical grasslands, where post-agricultural productivity was strongly affected by prior land management. Our results suggest that land-use history is a relevant factor affecting ecosystems long after agricultural cessation, and it should be considered not only when assessing historical or future changes in simulations of the terrestrial carbon cycle but also when establishing long-term monitoring networks and

  8. 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.

  9. Land-Cover Trends of the Southern California Mountains Ecoregion

    USGS Publications Warehouse

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

    2007-01-01

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

  10. Climate change impacts on global rainfed agricultural land availability

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Cai, X.

    2010-12-01

    Global rainfed agricultural land availability can be subject to significant changes in both magnitude and spatial distribution due to climate change. We assess the possible changes using current and projected climate data from thirteen general circulation models (GCMs) under two emission scenarios, A1B & B1, together with global databases on land, including soil properties and slope. Two ensemble methods with the set of GCMs, Simple Average Method (SAM) and Root Mean Square Error Ensemble Method (RMSEMM), are employed to abate uncertainty involved in global GCM projections for assembling regional climate. Fuzzy logic, which handles land classification in an approximate yet efficient way, is adopted to estimate the land suitability through empirically determined membership functions and fuzzy rules chosen through a learning process based on remote sensed crop land products. Land suitability under five scenarios, which include the present-climate baseline scenario and four projected scenarios, A1B-SAM, A1B-RMSEMM, B1-SAM, and B1-RMSEMM, are assessed for both global and seven important agricultural regions in the world, Africa, China, India, Europe (excluding Russia), Russia, South America, and U.S. It is found that countries at the high latitudes of north hemisphere are more likely to benefit from climate change with respect to agricultural land availability; while countries at mid- and low latitudes may suffer different levels of loss of potential arable land. Expansions of the gross potential arable land are likely to occur in regions at the north high latitudes, including Russia, North China and U.S., while land shrinking can be expected in South America, Africa, India and Europe. Although the greatest potential for agricultural expansion lies in Africa and South America, with current cultivated land accounting for 20% and 13% respectively of the net potential arable land, negative effects from climate change may decline the potential. In summary, climate change

  11. Spatially differentiated trends in urbanization, agricultural land abandonment and reclamation, and woodland recovery in Northern China.

    PubMed

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

    2016-11-22

    Uncovering magnitude, trend, and spatial pattern of land cover/land use changes (LCLUC) is crucial for understanding mechanisms of LCLUC and assisting land use planning and conservation. China has been undergoing unprecedented economic growth, massive rural-to-urban migration, and large-scale policy-driven ecological restoration, and therefore encountering enormous LCLUC in recent decades. However, comprehensive understandings of spatiotemporal LCLUC dynamics and underlying mechanisms are still lacking. Based on classification of annual LCLU maps from MODIS satellite imagery, we proposed a land change detection method to capture significant land change hotspots over Northern China during 2001-2013, and further analyzed temporal trends and spatial patterns of LCLUC. We found rapid decline of agricultural land near urban was predominantly caused by urban expansion. The process was especially strong in North China Plain with 14,057 km 2 of urban gain and -21,017 km 2 of agricultural land loss. To offset the loss of agricultural land, Northeast China Plain and Xinjiang were reclaimed. Substantial recovery of forests (49,908 km 2 ) and closed shrubland (60,854 km 2 ) occurred in mountainous regions due to abandoned infertile farmland, secondary succession, and governmental conservation policies. The spatial patterns and trends of LCLUC in Northern China provide information to support effective environmental policies towards sustainable development.

  12. Spatially differentiated trends in urbanization, agricultural land abandonment and reclamation, and woodland recovery in Northern China

    PubMed Central

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

    2016-01-01

    Uncovering magnitude, trend, and spatial pattern of land cover/land use changes (LCLUC) is crucial for understanding mechanisms of LCLUC and assisting land use planning and conservation. China has been undergoing unprecedented economic growth, massive rural-to-urban migration, and large-scale policy-driven ecological restoration, and therefore encountering enormous LCLUC in recent decades. However, comprehensive understandings of spatiotemporal LCLUC dynamics and underlying mechanisms are still lacking. Based on classification of annual LCLU maps from MODIS satellite imagery, we proposed a land change detection method to capture significant land change hotspots over Northern China during 2001–2013, and further analyzed temporal trends and spatial patterns of LCLUC. We found rapid decline of agricultural land near urban was predominantly caused by urban expansion. The process was especially strong in North China Plain with 14,057 km2 of urban gain and −21,017 km2 of agricultural land loss. To offset the loss of agricultural land, Northeast China Plain and Xinjiang were reclaimed. Substantial recovery of forests (49,908 km2) and closed shrubland (60,854 km2) occurred in mountainous regions due to abandoned infertile farmland, secondary succession, and governmental conservation policies. The spatial patterns and trends of LCLUC in Northern China provide information to support effective environmental policies towards sustainable development. PMID:27874092

  13. Spatially differentiated trends in urbanization, agricultural land abandonment and reclamation, and woodland recovery in Northern China

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

    Uncovering magnitude, trend, and spatial pattern of land cover/land use changes (LCLUC) is crucial for understanding mechanisms of LCLUC and assisting land use planning and conservation. China has been undergoing unprecedented economic growth, massive rural-to-urban migration, and large-scale policy-driven ecological restoration, and therefore encountering enormous LCLUC in recent decades. However, comprehensive understandings of spatiotemporal LCLUC dynamics and underlying mechanisms are still lacking. Based on classification of annual LCLU maps from MODIS satellite imagery, we proposed a land change detection method to capture significant land change hotspots over Northern China during 2001-2013, and further analyzed temporal trends and spatial patterns of LCLUC. We found rapid decline of agricultural land near urban was predominantly caused by urban expansion. The process was especially strong in North China Plain with 14,057 km2 of urban gain and -21,017 km2 of agricultural land loss. To offset the loss of agricultural land, Northeast China Plain and Xinjiang were reclaimed. Substantial recovery of forests (49,908 km2) and closed shrubland (60,854 km2) occurred in mountainous regions due to abandoned infertile farmland, secondary succession, and governmental conservation policies. The spatial patterns and trends of LCLUC in Northern China provide information to support effective environmental policies towards sustainable development.

  14. Land-cover change in the Lower Mississippi Valley, 1973-2000

    USGS Publications Warehouse

    Karstensen, Krista A.; Sayler, Kristi L.

    2009-01-01

    The Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. The project is coordinated by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in conjunction with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 were processed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into four temporal periods: 1973 to1980, 1980 to 1986, 1986 to 1992, 1992 to 2000 and overall from 1973 to 2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation.The rates of land-cover change were estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images were used to interpret land-cover change. The sample block data then were incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion.

  15. Analysing land and vegetation cover dynamics during last three decades in Katerniaghat wildlife sanctuary, India

    NASA Astrophysics Data System (ADS)

    Chitale, V. S.; Behera, M. D.

    2014-10-01

    The change in the tropical forests could be clearly linked to the expansion of the human population and economies. An understanding of the anthropogenic forcing plays an important role in analyzing the impacts of climate change and the fate of tropical forests in the present and future scenario. In the present study, we analyze the impact of natural and anthropogenic factors in forest dynamics in Katerniaghat wildlife sanctuary situated along the Indo-Nepal border in Uttar Pradesh state, India. The study site is under tremendous pressure due to anthropogenic factors from surrounding areas since last three decades. The vegetation cover of the sanctuary primarily comprised of Shorea robusta forests, Tectona grandis plantation, and mixed deciduous forest; while the land cover comprised of agriculture, barren land, and water bodies. The classification accuracy was 83.5%, 91.5%, and 95.2% with MSS, IKONOS, and Quickbird datasets, respectively. Shorea robusta forests showed an increase of 16 km2; while Tectona grandis increased by 63.01 km2 during 1975-2010. The spatial heterogeneity in these tropical vegetation classes surrounded by the human dominated agricultural lands could not be addressed using Landsat MSS data due to coarse spatial resolution; whereas the IKONOS and Quickbird satellite datasets proved to advantageous, thus being able to precisely address the variations within the vegetation classes as well as in the land cover classes and along the edge areas. Massive deforestation during 1970s along the adjoining international boundary with Nepal has led to destruction of the wildlife corridor and has exposed the wildlife sanctuary to human interference like grazing and poaching. Higher rates of forest dynamics during the 25-year period indicate the vulnerability of the ecosystem to the natural and anthropogenic disturbances in the proximity of the sanctuary.

  16. 25 CFR 166.300 - How is Indian agricultural land managed?

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false How is Indian agricultural land managed? 166.300 Section 166.300 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER GRAZING PERMITS Land and Operations Management § 166.300 How is Indian agricultural land managed? Tribes, individual...

  17. 25 CFR 166.300 - How is Indian agricultural land managed?

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 25 Indians 1 2014-04-01 2014-04-01 false How is Indian agricultural land managed? 166.300 Section 166.300 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER GRAZING PERMITS Land and Operations Management § 166.300 How is Indian agricultural land managed? Tribes, individual...

  18. Land cover effects on infiltration and preferential flow pathways in the high rainfall zone of Madagascar

    NASA Astrophysics Data System (ADS)

    Zwartendijk, Bob; van Meerveld, Ilja; Ravelona, Maafaka; Razakamanarivo, Herintsitohaina; Ghimire, Chandra; Bruijnzeel, Sampurno; Jones, Julia

    2015-04-01

    Shortened slash-and-burn cycles exhaust agricultural land and have resulted in extensive tracts of highly degraded land across the tropics. Land degradation typically results in decreased rainfall infiltration due to a reduced field-saturated hydraulic conductivity of the topsoil because of a progressive decline in soil organic matter, exposure to raindrop impact, surface sealing and compaction. This results, in turn, in enhanced surface runoff and erosion, and consequently less subsurface flow and groundwater recharge. On the other hand, natural vegetation regrowth or active reforestation can lead to a renewed accumulation of soil organic matter, macropore development and increased infiltration rates. As part of the P4GES project (Can Paying 4 Global Ecosystem Services values reduce poverty?; www.p4ges.org), we study the effects of land use change and reforestation on water resources in the Corridor Ankeniheny-Zahamena (CAZ) in eastern Madagascar. In this poster, we present the results of infiltration and preferential flow measurements in four different land uses in the southern part of the CAZ: (i) closed canopy forest, (ii) 3-14 year-old regrowth on fallow land (savokas), (iii) exhausted and severely degraded land (tany maty), and (iv) recently reforested sites (6-8 years old). The results show that infiltrability increases significantly after several years of forest regrowth after land abandonment, but it remains unclear whether active replanting decreases the time required for restoration of soil hydrological functioning. Preferential flow pathways differed strikingly between the respective land cover types: infiltration in mature forests was predominantly characterized by macropore flow (preferential flow pathways), whereas infiltration in exhausted agricultural land was dominated by matrix flow (few preferential flow pathways). Occurrence of preferential flow pathways in reforestation and fallow sites varied considerably. These results suggest that land

  19. 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.

  20. EnviroAtlas -- Fresno, California -- One Meter Resolution Urban Land Cover Data (2010) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The Fresno, CA EnviroAtlas One-Meter-scale Urban Land Cover Data were generated via supervised classification of combined aerial photography and LiDAR data. The air photos were United States Department of Agriculture (USDA) National Agricultural Imagery Program (NAIP) four band (red, green, blue, and near infrared) aerial photography at 1-m spatial resolution. Aerial photography ('imagery') was collected on multiple dates in summer 2010. Seven land cover classes were mapped: Water, impervious surfaces (Impervious), soil and barren (Soil), trees and forest (Tree), and grass and herbaceous non-woody vegetation (Grass), agriculture (Ag), and Orchards. An accuracy assessment of 500 completely random and 103 stratified random points yielded an overall User's fuzzy accuracy of 81.1 percent (see below). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Fresno, CA plus a 1-km buffer. Where imagery was available, additional areas outside the 1-km boundary were also mapped but not included in the accuracy assessment. We expect the accuracy of the areas outside of the 1-km boundary to be consistent with those within. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with

  1. 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

  2. EnviroAtlas -Milwaukee, WI- One Meter Resolution Urban Land Cover Data (2010) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The EnviroAtlas Milwaukee, WI land cover data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from Late Summer 2010 at 1 m spatial resolution. Nine land cover classes were mapped: water, impervious surfaces (dark and light), soil and barren land, trees and forest, grass and herbaceous non-woody vegetation, agriculture, and wetlands (woody and emergent). An accuracy assessment using a completely random sampling of 600 samples yielded an overall accuracy of 85.39% percent using a minimum mapping unit of 9 pixels (3x3 pixel window). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Milwaukee. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-

  3. EnviroAtlas -- Woodbine, IA -- One Meter Resolution Urban Land Cover Data (2011) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The EnviroAtlas Woodbine, IA land cover (LC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from Late Summer 2011 at 1 m spatial resolution. Six land cover classes were mapped: water, impervious surfaces (dark and light), soil and barren land, trees and forest, grass and herbaceous non-woody vegetation, and agriculture. An accuracy assessment using a completely random sampling of 600 samples yielded an overall accuracy of 87.03% percent using a minimum mapping unit of 9 pixels (3x3 pixel window). The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Woodbine. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  4. Agriculture land suitability analysis evaluation based multi criteria and GIS approach

    NASA Astrophysics Data System (ADS)

    Bedawi Ahmed, Goma; Shariff, Abdul Rashid M.; Balasundram, Siva Kumar; Abdullah, Ahmad Fikri bin

    2016-06-01

    Land suitability evaluation (LSE) is a valuable tool for land use planning in major countries of the world as well as in Malaysia. However, previous LSE studies have been conducted with the use of biophysical and ecological datasets for the design of equally important socio-economic variables. Therefore, this research has been conducted at the sub national level to estimate suitable agricultural land for rubber crops in Seremban, Malaysia by application of physical variables in combination with widely employed biophysical and ecological variables. The objective of this study has been to provide an up-to date GIS-based agricultural land suitability evaluation (ALSE) for determining suitable agricultural land for Rubber crops in Malaysia. Biophysical and ecological factors were assumed to influence agricultural land use were assembled and the weights of their respective contributions to land suitability for agricultural uses were assessed using an analytic hierarchical process. The result of this study found Senawang, Mambau, Sandakan and Rantau as the most suitable areas for cultivating Rubber; whereas, Nilai and Labu are moderately suitable for growing rubber. Lenggeng, Mantin and Pantai are not suitable for growing rubber as the study foresaw potential environmental degradation of these locations from agricultural intensification. While this study could be useful in assessing the potential agricultural yields and potential environmental degradation in the study area, it could also help to estimate the potential conversion of agricultural land to non-agricultural uses.

  5. The Land Use Change From Agricultural to Non-Agricultural in Bungo Regency, Jambi Province, Indonesia

    NASA Astrophysics Data System (ADS)

    Dolly, Fajar Ifan; Kismartini, Kismartini; Purnaweni, Hartuti

    2018-02-01

    This study aimed at observing the development of agricultural land use in Bungo Regency, Jambi Province, for other purposes, such as plantation, mining, and other commercial buildings. According to the sustainable agriculture supposed by the government, a change in land use has become an important issue to be taken into account as such that the change does not tend to damage the environment. The research findings from Bungo Regency demonstrated the change in agricultural land into copra and rubber plantation areas. Local people had changed their mindset towards reluctance to become farmers, which caused the loss of farmer regeneration and weakened the farmer exchange rate towards the agricultural commodities.

  6. [Study of the microwave emissivity characteristics over different land cover types].

    PubMed

    Zhang, Yong-Pan; Jiang, Ling-Mei; Qiu, Yu-Bao; Wu, Sheng-Li; Shi, Jian-Cheng; Zhang, Li-Xin

    2010-06-01

    The microwave emissivity over land is very important for describing the characteristics of the lands, and it is also a key factor for retrieving the parameters of land and atmosphere. Different land covers have their emission behavior as a function of structure, water content, and surface roughness. In the present study the global land surface emissivities were calculated using six month (June, 2003-August, 2003, Dec, 2003-Feb, 2004) AMSR-E L2A brightness temperature, MODIS land surface temperature and the layered atmosphere temperature, and humidity and pressure profiles data retrieved from MODIS/Aqua under clear sky conditions. With the information of IGBP land cover types, "pure" pixels were used, which are defined when the fraction cover of each land type is larger than 85%. Then, the emissivity of sixteen land covers at different frequencies, polarization and their seasonal variation were analyzed respectively. The results show that the emissivity of vegetation including forests, grasslands and croplands is higher than that over bare soil, and the polarization difference of vegetation is smaller than that of bare soil. In summer, the emissivity of vegetation is relatively stable because it is in bloom, therefore the authors can use it as its emissivity in our microwave emissivity database over different land cover types. Furthermore, snow cover can heavily impact the change in land cover emissivity, especially in winter.

  7. eFarm: A Tool for Better Observing Agricultural Land Systems

    PubMed Central

    Yu, Qiangyi; Shi, Yun; Tang, Huajun; Yang, Peng; Xie, Ankun; Liu, Bin; Wu, Wenbin

    2017-01-01

    Currently, observations of an agricultural land system (ALS) largely depend on remotely-sensed images, focusing on its biophysical features. While social surveys capture the socioeconomic features, the information was inadequately integrated with the biophysical features of an ALS and the applications are limited due to the issues of cost and efficiency to carry out such detailed and comparable social surveys at a large spatial coverage. In this paper, we introduce a smartphone-based app, called eFarm: a crowdsourcing and human sensing tool to collect the geotagged ALS information at the land parcel level, based on the high resolution remotely-sensed images. We illustrate its main functionalities, including map visualization, data management, and data sensing. Results of the trial test suggest the system works well. We believe the tool is able to acquire the human–land integrated information which is broadly-covered and timely-updated, thus presenting great potential for improving sensing, mapping, and modeling of ALS studies. PMID:28245554

  8. National Land Cover Database 2001 (NLCD01) Tile 2, Northeast United States: NLCD01_2

    USGS Publications Warehouse

    LaMotte, Andrew

    2008-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  9. National Land Cover Database 2001 (NLCD01) Tile 3, Southwest United States: NLCD01_3

    USGS Publications Warehouse

    LaMotte, Andrew

    2008-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg).The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  10. National Land Cover Database 2001 (NLCD01) Tile 1, Northwest United States: NLCD01_1

    USGS Publications Warehouse

    LaMotte, Andrew

    2008-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  11. National Land Cover Database 2001 (NLCD01) Tile 4, Southeast United States: NLCD01_4

    USGS Publications Warehouse

    LaMotte, Andrew

    2008-01-01

    This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  12. Land-cover trends in the Mojave basin and range ecoregion

    USGS Publications Warehouse

    Sleeter, Benjamin M.; Raumann, Christian G.

    2006-01-01

    The U.S. Geological Survey's Land-Cover Trends Project aims to estimate the rates of contemporary land-cover change within the conterminous United States between 1972 and 2000. A random sampling approach was used to select a representative sample of 10-km by 10-km sample blocks and to estimate change within +/- 1 percent at an 85-percent confidence interval. Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus data were used, and each 60-m pixel was assigned to one of 11 distinct land-cover classes based upon a modified Anderson classification system. Upon completion of land-cover change mapping for five dates, land-cover change statistics were generated and analyzed. This paper presents estimates for the Mojave Basin and Range ecoregion located in the southwestern United States. Our research suggests land-cover change within the Mojave to be relatively rare and highly localized. The primary shift in land cover is unidirectional, with natural desert grass/shrubland being converted to development. We estimate that more than 1,300 km2 have been converted since 1973 and that the conversion is being largely driven by economic and recreational opportunities provided by the Mojave ecoregion. The time interval with the highest rate of change was 1986 to 1992, in which the rate was 0.21 percent (321.9 km2) per year total change.

  13. Influence of land use and land cover on the spatial variability of dissolved organic matter in multiple aquatic environments.

    PubMed

    Singh, Shatrughan; Dash, Padmanava; Silwal, Saurav; Feng, Gary; Adeli, Ardeshir; Moorhead, Robert J

    2017-06-01

    Water quality of lakes, estuaries, and coastal areas serves as an indicator of the overall health of aquatic ecosystems as well as the health of the terrestrial ecosystem that drains to the water body. Land use and land cover plays not only a significant role in controlling the quantity of the exported dissolved organic matter (DOM) but also influences the quality of DOM via various biogeochemical and biodegradation processes. We examined the characteristics and spatial distribution of DOM in five major lakes, in an estuary, and in the coastal waters of the Mississippi, USA, and investigated the influence of the land use and land cover of their watersheds on the DOM composition. We employed absorption and fluorescence spectroscopy including excitation-emission matrix (EEM) combined with parallel factor (PARAFAC) analysis modeling techniques to determine optical properties of DOM and its characteristics in this study. We developed a site-specific PARAFAC model to evaluate DOM characteristics resulting in five diverse DOM compositions that included two terrestrial humic-like (C1 and C3), two microbial humic-like (C2 and C5), and one protein-like (C4) DOM. Our results showed elevated fluorescence levels of microbial humic-like or protein-like DOM in the lakes and coastal waters, while the estuarine waters showed relatively high fluorescence levels of terrestrial humic-like DOM. The results also showed that percent forest and wetland coverage explained 68 and 82% variability, respectively, in terrestrial humic-like DOM exports, while 87% variability in microbially derived humiclike DOM was explained by percent agricultural lands. Strong correlations between microbial humic-like DOM and fluorescence-derived DOM indices such as biological index (BIX) and fluorescence index (FI) indicated autochthonous characteristics in the lakes, while the estuary showed largely allochthonous DOM of terrestrial origin. We also observed higher concentrations of total dissolved

  14. Global land-water nexus: Agricultural land and freshwater use embodied in worldwide supply chains.

    PubMed

    Chen, B; Han, M Y; Peng, K; Zhou, S L; Shao, L; Wu, X F; Wei, W D; Liu, S Y; Li, Z; Li, J S; Chen, G Q

    2018-02-01

    As agricultural land and freshwater inextricably interrelate and interact with each other, the conventional water and land policy in "silos" should give way to nexus thinking when formulating the land and water management strategies. This study constructs a systems multi-regional input-output (MRIO) model to expound global land-water nexus by simultaneously tracking agricultural land and freshwater use flows along the global supply chains. Furthermore, land productivity and irrigation water requirements of 160 crops in different regions are investigated to reflect the land-water linkage. Results show that developed economies (e.g., USA and Japan) and major large developing economies (e.g., mainland China and India) are the overriding drivers of agricultural land and freshwater use globally. In general, significant net transfers of these two resources are identified from resource-rich and less-developed economies to resource-poor and more-developed economies. For some crops, blue water productivity is inversely related to land productivity, indicating that irrigation water consumption is sometimes at odds with land use. The results could stimulus international cooperation for sustainable land and freshwater management targeting on original suppliers and final consumers along the global supply chains. Moreover, crop-specific land-water linkage could provide insights for trade-off decisions on minimizing the environmental impacts on local land and water resources. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Global land cover mapping: a review and uncertainty analysis

    USGS Publications Warehouse

    Congalton, Russell G.; Gu, Jianyu; Yadav, Kamini; Thenkabail, Prasad S.; Ozdogan, Mutlu

    2014-01-01

    Given the advances in remotely sensed imagery and associated technologies, several global land cover maps have been produced in recent times including IGBP DISCover, UMD Land Cover, Global Land Cover 2000 and GlobCover 2009. However, the utility of these maps for specific applications has often been hampered due to considerable amounts of uncertainties and inconsistencies. A thorough review of these global land cover projects including evaluating the sources of error and uncertainty is prudent and enlightening. Therefore, this paper describes our work in which we compared, summarized and conducted an uncertainty analysis of the four global land cover mapping projects using an error budget approach. The results showed that the classification scheme and the validation methodology had the highest error contribution and implementation priority. A comparison of the classification schemes showed that there are many inconsistencies between the definitions of the map classes. This is especially true for the mixed type classes for which thresholds vary for the attributes/discriminators used in the classification process. Examination of these four global mapping projects provided quite a few important lessons for the future global mapping projects including the need for clear and uniform definitions of the classification scheme and an efficient, practical, and valid design of the accuracy assessment.

  16. Impacts of land use/cover classification accuracy on regional climate simulations

    NASA Astrophysics Data System (ADS)

    Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

    2007-03-01

    Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

  17. Impacts of incorporating land exchanges between forestry and agriculture in sector models.

    Treesearch

    Ralph J. Alig; Darius M. Adams; Bruce A. McCarl

    1998-01-01

    The forest and agriculture sectors are linked by having a portion of their land bases suitable for use in either sector. A substantial part of the southern land base is suitable for either forestry or agriculture use, with most of forestation on U.S. agriculture land in the South. We examine how land exchanges between forestry and agriculture are influenced by specific...

  18. 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

  19. High dimensional land cover inference using remotely sensed modis data

    NASA Astrophysics Data System (ADS)

    Glanz, Hunter S.

    Image segmentation persists as a major statistical problem, with the volume and complexity of data expanding alongside new technologies. Land cover classification, one of the most studied problems in Remote Sensing, provides an important example of image segmentation whose needs transcend the choice of a particular classification method. That is, the challenges associated with land cover classification pervade the analysis process from data pre-processing to estimation of a final land cover map. Many of the same challenges also plague the task of land cover change detection. Multispectral, multitemporal data with inherent spatial relationships have hardly received adequate treatment due to the large size of the data and the presence of missing values. In this work we propose a novel, concerted application of methods which provide a unified way to estimate model parameters, impute missing data, reduce dimensionality, classify land cover, and detect land cover changes. This comprehensive analysis adopts a Bayesian approach which incorporates prior knowledge to improve the interpretability, efficiency, and versatility of land cover classification and change detection. We explore a parsimonious, parametric model that allows for a natural application of principal components analysis to isolate important spectral characteristics while preserving temporal information. Moreover, it allows us to impute missing data and estimate parameters via expectation-maximization (EM). A significant byproduct of our framework includes a suite of training data assessment tools. To classify land cover, we employ a spanning tree approximation to a lattice Potts prior to incorporate spatial relationships in a judicious way and more efficiently access the posterior distribution of pixel labels. We then achieve exact inference of the labels via the centroid estimator. To detect land cover changes, we develop a new EM algorithm based on the same parametric model. We perform simulation studies

  20. 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.

  1. Meter-scale Urban Land Cover Mapping for EPA EnviroAtlas Using Machine Learning and OBIA Remote Sensing Techniques

    NASA Astrophysics Data System (ADS)

    Pilant, A. N.; Baynes, J.; Dannenberg, M.; Riegel, J.; Rudder, C.; Endres, K.

    2013-12-01

    US EPA EnviroAtlas is an online collection of tools and resources that provides geospatial data, maps, research, and analysis on the relationships between nature, people, health, and the economy (http://www.epa.gov/research/enviroatlas/index.htm). Using EnviroAtlas, you can see and explore information related to the benefits (e.g., ecosystem services) that humans receive from nature, including clean air, clean and plentiful water, natural hazard mitigation, biodiversity conservation, food, fuel, and materials, recreational opportunities, and cultural and aesthetic value. EPA developed several urban land cover maps at very high spatial resolution (one-meter pixel size) for a portion of EnviroAtlas devoted to urban studies. This urban mapping effort supported analysis of relations among land cover, human health and demographics at the US Census Block Group level. Supervised classification of 2010 USDA NAIP (National Agricultural Imagery Program) digital aerial photos produced eight-class land cover maps for several cities, including Durham, NC, Portland, ME, Tampa, FL, New Bedford, MA, Pittsburgh, PA, Portland, OR, and Milwaukee, WI. Semi-automated feature extraction methods were used to classify the NAIP imagery: genetic algorithms/machine learning, random forest, and object-based image analysis (OBIA). In this presentation we describe the image processing and fuzzy accuracy assessment methods used, and report on some sustainability and ecosystem service metrics computed using this land cover as input (e.g., carbon sequestration from USFS iTREE model; health and demographics in relation to road buffer forest width). We also discuss the land cover classification schema (a modified Anderson Level 1 after the National Land Cover Data (NLCD)), and offer some observations on lessons learned. Meter-scale urban land cover in Portland, OR overlaid on NAIP aerial photo. Streets, buildings and individual trees are identifiable.

  2. Land cover as an important factor for landslide risk assessment

    NASA Astrophysics Data System (ADS)

    Promper, C.; Glade, T.; Puissant, A.; Malet, J.-P.

    2012-04-01

    Landcover change is a crucial component of hazard and vulnerability in terms of quantification of possible future landslide risk, and the importance for spatial planners but also individuals is obvious. Damage of property, losses of agricultural land, loss of production but also damaged infrastructures and fatalities may be the result of landslide hazards. To avoid these economic damages as well as possible fatalities in the future, a method of assessing spatial but also temporal patterns of landslides is necessary. This study represents results of landcover modeling as a first step to the proposition of scenario of landslide risk for the future. The method used for future land cover analysis is the CLUE modeling framework combining past and actual observed landcover conditions. The model is based on a statistical relationship between the actual land cover and driving forces. The allocation of landcover pixel is modified by possible autonomous developments and competition between land use types. (Verburg et al. 1999) The study area is located in a district in the alpine foreland of Lower Austria: Waidhofen/Ybbs, of about 130km2. The topography is characterized by narrow valleys, flat plateau and steep slopes. The landcover is characterized by region of densely populated areas in the valley bottom along the Ybbs River, and a series of separated farm houses on the top of the plateau. Population density is about 90 persons / km2 which represent the observed population density of Austria. The initial landcover includes forest, grassland, culture, built-up areas and individual farms. Most of the observed developments are controlled by the topography (along the valleys) and the actual road network. The results of the landcover model show different scenarios of changes in the landslide prone landcover types. These maps will be implemented into hazard analysis but also into vulnerability assessment regarding elements at risk. Verburg, P.H., de Koning, G.H.J., Kok, K

  3. Shuttle landing facility cloud cover study: Climatological analysis and two tenths cloud cover rule evaluation

    NASA Technical Reports Server (NTRS)

    Atchison, Michael K.; Schumann, Robin; Taylor, Greg; Warburton, John; Wheeler, Mark; Yersavich, Ann

    1993-01-01

    The two-tenths cloud cover rule in effect for all End Of Mission (EOM) STS landings at the Kennedy Space Center (KSC) states: 'for scattered cloud layers below 10,000 feet, cloud cover must be observed to be less than or equal to 0.2 at the de-orbit burn go/no-go decision time (approximately 90 minutes before landing time)'. This rule was designed to protect against a ceiling (below 10,000 feet) developing unexpectedly within the next 90 minutes (i.e., after the de-orbit burn decision and before landing). The Applied Meteorological Unit (AMU) developed and analyzed a database of cloud cover amounts and weather conditions at the Shuttle Landing Facility for a five-year (1986-1990) period. The data indicate the best time to land the shuttle at KSC is during the summer while the worst time is during the winter. The analysis also shows the highest frequency of landing opportunities occurs for the 0100-0600 UTC and 1300-1600 UTC time periods. The worst time of the day to land a shuttle is near sunrise and during the afternoon. An evaluation of the two-tenths cloud cover rule for most data categorizations has shown that there is a significant difference in the proportions of weather violations one and two hours subsequent to initial conditions of 0.2 and 0.3 cloud cover. However, for May, Oct., 700 mb northerly wind category, 1500 UTC category, and 1600 UTC category there is some evidence that the 0.2 cloud cover rule may be overly conservative. This possibility requires further investigation. As a result of these analyses, the AMU developed nomograms to help the Spaceflight Meteorological Group (SMG) and the Cape Canaveral Forecast Facility (CCFF) forecast cloud cover for EOM and Return to Launch Site (RTLS) at KSC. Future work will include updating the two tenths database, further analysis of the data for several categorizations, and developing a proof of concept artificial neural network to provide forecast guidance of weather constraint violations for shuttle

  4. Using hyperspectral remote sensing for land cover classification

    NASA Astrophysics Data System (ADS)

    Zhang, Wendy W.; Sriharan, Shobha

    2005-01-01

    This project used hyperspectral data set to classify land cover using remote sensing techniques. Many different earth-sensing satellites, with diverse sensors mounted on sophisticated platforms, are currently in earth orbit. These sensors are designed to cover a wide range of the electromagnetic spectrum and are generating enormous amounts of data that must be processed, stored, and made available to the user community. The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) collects data in 224 bands that are approximately 9.6 nm wide in contiguous bands between 0.40 and 2.45 mm. Hyperspectral sensors acquire images in many, very narrow, contiguous spectral bands throughout the visible, near-IR, and thermal IR portions of the spectrum. The unsupervised image classification procedure automatically categorizes the pixels in an image into land cover classes or themes. Experiments on using hyperspectral remote sensing for land cover classification were conducted during the 2003 and 2004 NASA Summer Faculty Fellowship Program at Stennis Space Center. Research Systems Inc.'s (RSI) ENVI software package was used in this application framework. In this application, emphasis was placed on: (1) Spectrally oriented classification procedures for land cover mapping, particularly, the supervised surface classification using AVIRIS data; and (2) Identifying data endmembers.

  5. Comparing long-term geomorphic model outcomes with sediment archives highlights the need for high-resolution Holocene land cover reconstructions

    NASA Astrophysics Data System (ADS)

    De Brue, Hanne; Verstraeten, Gert

    2013-04-01

    During the last decade, several global land cover reconstructions have been produced that enable to quantify human impact on the landscape since the introduction of agriculture. Application of these land cover maps in geomorphic models potentially allows to estimate the anthropogenic impact on sediment fluxes and thus to reconstruct changes in landscape morphology through time. However, current land cover reconstructions face some drawbacks. First of all, their low spatial resolution (i.e. 5 arc-minutes at best) questions their use in geomorphic models, as sub-catchment vegetation patterns play an important role in sediment dynamics. Existing global land cover reconstructions also do not differentiate the typology of human impact (cropland, grazing land, disturbed forests), although the susceptibility of different anthropogenic land uses towards erosion varies greatly. Finally, the various land cover reconstructions differ significantly regarding the estimated intensity of human impact for the preindustrial period. In this study, we assessed the performance of a spatially distributed erosion and sediment redistribution model that operates at high resolution (100 m) to the quality and spatial resolution of input land cover maps. This was done through a comparison of two sets of model runs. Firstly, low-resolution land cover (expressed as percentage of non-natural vegetation) maps were resampled to a spatial resolution of 100 m without differentiation of non-natural vegetation types. For the second set of model runs, estimated non-natural vegetation was differentiated in areas of cropland and grassland, and spatially allocated to a high-resolution grid (100 m) using a logistic model that relates contemporary land cover classes to slope, soil characteristics, landforms and distance to rivers. For both land cover maps, different scenarios for the ratio between cropland and grassland were simulated. Analyses were performed for several time periods throughout the

  6. 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.

  7. Global assessment of rural-urban interface in Portugal related to land cover changes

    NASA Astrophysics Data System (ADS)

    Tonini, Marj; Parente, Joana; Pereira, Mário G.

    2018-06-01

    The rural-urban interface (RUI), known as the area where structures and other human developments meet or intermingle with wildland and rural area, is at present a central focus of wildfire policy and its mapping is crucial for wildfire management. In the Mediterranean Basin, humans cause the vast majority of fires and fire risk is particularly high in the proximity of infrastructure and of rural/wildland areas. RUI's extension changes under the pressure of environmental and anthropogenic factors, such as urban growth, fragmentation of rural areas, deforestation and, more in general, land use/land cover change (LULCC). As with other Mediterranean countries, Portugal has experienced significant LULCC in the last decades in response to migration, rural abandonment, ageing of population and trends associated with the high socioeconomic development. In the present study, we analyzed the LULCC occurring in this country in the 1990-2012 period with the main objective of investigating how these changes affected RUI's evolution. Moreover, we performed a qualitative and quantitative characterization of burnt areas within the RUI in relation to the observed changes. Obtained results disclose important LULCC and reveal their spatial distribution, which is far from uniform within the territory. A significant increase in artificial surfaces was registered near the main metropolitan communities of the northwest, littoral-central and southern regions, whilst the abandonment of agricultural land near the inland urban areas led to an increase in uncultivated semi-natural and forest areas. Within agricultural areas, heterogeneous patches suffered the greatest changes and were the main contributors to the increase in urban areas; moreover, this land cover class, together with forests, was highly affected by wildfires in terms of burnt area. Finally, from this analysis and during the investigated period, it appears that RUI increased in Portugal by more than two-thirds, while the total

  8. Terra Incognita: Absence of Concentrated Animal Feeding Operations from the National Land Cover Database and Implications for Environmental Risk

    NASA Astrophysics Data System (ADS)

    Martin, K. L.; Emanuel, R. E.; Vose, J. M.

    2016-12-01

    The number of concentrated animal feeding operations (CAFOs) has increased rapidly in recent decades. Although important to food supplies, CAFOs may present significant risks to human health and environmental quality. The National land cover database (NLCD) is a publically available database of land cover whose purpose is to provide assessment of ecosystem health, facilitate nutrient modeling, land use planning, and developing land management practices. However, CAFOs do not align with any existing NLCD land cover classes. This is especially concerning due to their distinct nutrient loading characteristics, potential for other environmental impacts, and given that individual CAFOs may occupy several NLCD pixels worth of ground area. Using 2011 NLCD data, we examined the land cover classification of CAFO sites in North Carolina (USA). Federal regulations require CAFOs with a liquid waste disposal system to obtain a water quality permit. In North Carolina, there were 2679 permitted sites as of 2015, primarily in the southeastern part of the state. As poultry operations most frequently use dry waste disposal systems, they are not required to obtain a permit and thus, their locations are undocumented. For each permitted CAFO, we determined the mode of the NLCD land uses within a 50m buffer surrounding point coordinates. We found permitted CAFOS were most likely to be classified as hay/pasture (58%). An additional 13% were identified as row crops, leaving 29% as a non-agricultural land cover class, including wetlands (12%). This misclassification of CAFOs can have implications for environmental management and public policy. Scientists and land managers need access to better spatial data on the distribution of these operations to monitor the environmental impacts and identify the best landscape scale mitigation strategies. We recommend adding a new land cover class (concentrated animal operations) to the NLCD database.

  9. An Iterative Inference Procedure Applying Conditional Random Fields for Simultaneous Classification of Land Cover and Land Use

    NASA Astrophysics Data System (ADS)

    Albert, L.; Rottensteiner, F.; Heipke, C.

    2015-08-01

    Land cover and land use exhibit strong contextual dependencies. We propose a novel approach for the simultaneous classification of land cover and land use, where semantic and spatial context is considered. The image sites for land cover and land use classification form a hierarchy consisting of two layers: a land cover layer and a land use layer. We apply Conditional Random Fields (CRF) at both layers. The layers differ with respect to the image entities corresponding to the nodes, the employed features and the classes to be distinguished. In the land cover layer, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Both CRFs model spatial dependencies between neighbouring image sites. The complex semantic relations between land cover and land use are integrated in the classification process by using contextual features. We propose a new iterative inference procedure for the simultaneous classification of land cover and land use, in which the two classification tasks mutually influence each other. This helps to improve the classification accuracy for certain classes. The main idea of this approach is that semantic context helps to refine the class predictions, which, in turn, leads to more expressive context information. Thus, potentially wrong decisions can be reversed at later stages. The approach is designed for input data based on aerial images. Experiments are carried out on a test site to evaluate the performance of the proposed method. We show the effectiveness of the iterative inference procedure and demonstrate that a smaller size of the super-pixels has a positive influence on the classification result.

  10. Satellite-derived land covers for runoff estimation using SCS-CN method in Chen-You-Lan Watershed, Taiwan

    NASA Astrophysics Data System (ADS)

    Zhang, Wen-Yan; Lin, Chao-Yuan

    2017-04-01

    The Soil Conservation Service Curve Number (SCS-CN) method, which was originally developed by the USDA Natural Resources Conservation Service, is widely used to estimate direct runoff volume from rainfall. The runoff Curve Number (CN) parameter is based on the hydrologic soil group and land use factors. In Taiwan, the national land use maps were interpreted from aerial photos in 1995 and 2008. Rapid updating of post-disaster land use map is limited due to the high cost of production, so the classification of satellite images is the alternative method to obtain the land use map. In this study, Normalized Difference Vegetation Index (NDVI) in Chen-You-Lan Watershed was derived from dry and wet season of Landsat imageries during 2003 - 2008. Land covers were interpreted from mean value and standard deviation of NDVI and were categorized into 4 groups i.e. forest, grassland, agriculture and bare land. Then, the runoff volume of typhoon events during 2005 - 2009 were estimated using SCS-CN method and verified with the measured runoff data. The result showed that the model efficiency coefficient is 90.77%. Therefore, estimating runoff by using the land cover map classified from satellite images is practicable.

  11. 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.

  12. Simulating urban land cover changes at sub-pixel level in a coastal city

    NASA Astrophysics Data System (ADS)

    Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang

    2014-10-01

    The simulation of urban expansion or land cover changes is a major theme in both geographic information science and landscape ecology. Yet till now, almost all of previous studies were based on grid computations at pixel level. With the prevalence of spectral mixture analysis in urban land cover research, the simulation of urban land cover at sub-pixel level is being put into agenda. This study provided a new approach of land cover simulation at sub-pixel level. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover data through supervised classification. Then the two classified land cover data were utilized to extract the transformation rule between 2002 and 2007 using logistic regression. The transformation possibility of each land cover type in a certain pixel was taken as its percent in the same pixel after normalization. And cellular automata (CA) based grid computation was carried out to acquire simulated land cover on 2007. The simulated 2007 sub-pixel land cover was testified with a validated sub-pixel land cover achieved by spectral mixture analysis in our previous studies on the same date. And finally the sub-pixel land cover of 2017 was simulated for urban planning and management. The results showed that our method is useful in land cover simulation at sub-pixel level. Although the simulation accuracy is not quite satisfactory for all the land cover types, it provides an important idea and a good start in the CA-based urban land cover simulation.

  13. 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

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

    USGS Publications Warehouse

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

    2009-01-01

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

  15. Agricultural lands preservation: a sociology of survival

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

    White, T.S.

    1983-01-01

    This is a rural sociological study investigating the viability of agricultural lands use-values and rural communities in the context of the structure of US agriculture. It outlines the theoretical foundation, ideology, and praxis of a sociology of survival. It is undertaken within the framework of environmental sociology, which focuses on the dynamic interpenetration of social and biotic systems. The concepts of carrying capacity, sustained multiple-use yield, and land-use compatibility and their significance are discussed. The phenomenon of phantom carrying capacity is explored, and its ominous portent noted; but the astonishing potential of agricultural lands to produce huge net gains inmore » use values and in real carrying capacity is affirmed. The theory of unlimited resources, substitution, and market-allocation is falsified. Absolute shortages of renewable and nonrenewable resources are documented, and the necessity for population control, conservation, expanded sustained-yield production, and social allocation is established.« less

  16. 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.

  17. Land cover mapping at sub-pixel scales

    NASA Astrophysics Data System (ADS)

    Makido, Yasuyo Kato

    One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has

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

    USGS Publications Warehouse

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

    2017-01-01

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

  19. 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.

  20. EVALUATING ECOREGIONS FOR SAMPLING AND MAPPING LAND-COVER PATTERNS

    EPA Science Inventory

    Ecoregional stratification has been proposed for sampling and mapping land- cover composition and pattern over time. Using a wall-to-wall land-cover map of the United States, we evaluated geographic scales of variance for 17 landscape pattern indices, and compared stratification ...

  1. Comparison of two Classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia

    NASA Astrophysics Data System (ADS)

    Rokni Deilmai, B.; Ahmad, B. Bin; Zabihi, H.

    2014-06-01

    Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification.

  2. Simulation of urban land surface temperature based on sub-pixel land cover in a coastal city

    NASA Astrophysics Data System (ADS)

    Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang

    2014-11-01

    The sub-pixel urban land cover has been proved to have obvious correlations with land surface temperature (LST). Yet these relationships have seldom been used to simulate LST. In this study we provided a new approach of urban LST simulation based on sub-pixel land cover modeling. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover and then extract the transformation rule using logistic regression. The transformation possibility was taken as its percent in the same pixel after normalization. And cellular automata were used to acquire simulated sub-pixel land cover on 2007 and 2017. On the other hand, the correlations between retrieved LST and sub-pixel land cover achieved by spectral mixture analysis in 2002 were examined and a regression model was built. Then the regression model was used on simulated 2007 land cover to model the LST of 2007. Finally the LST of 2017 was simulated for urban planning and management. The results showed that our method is useful in LST simulation. Although the simulation accuracy is not quite satisfactory, it provides an important idea and a good start in the modeling of urban LST.

  3. Spatio-temporal Characteristics of Land Use Land Cover Change Driven by Large Scale Land Transactions in Cambodia

    NASA Astrophysics Data System (ADS)

    Ghosh, A.; Smith, J. C.; Hijmans, R. J.

    2017-12-01

    Since mid-1990s, the Cambodian government granted nearly 300 `Economic Land Concessions' (ELCs), occupying approximately 2.3 million ha to foreign and domestic organizations (primarily agribusinesses). The majority of Cambodian ELC deals have been issued in areas of both relatively low population density and low agricultural productivity, dominated by smallholder production. These regions often contain highly biodiverse areas, thereby increasing the ecological cost associated with land clearing for extractive purposes. These large-scale land transactions have also resulted in substantial and rapid changes in land-use patterns and agriculture practices by smallholder farmers. In this study, we investigated the spatio-temporal characteristics of land use change associated with large-scale land transactions across Cambodia using multi-temporal multi-reolution remote sensing data. We identified major regions of deforestation during the last two decades using Landsat archive, global forest change data (2000-2014) and georeferenced database of ELC deals. We then mapped the deforestation and land clearing within ELC boundaries as well as areas bordering or near ELCs to quantify the impact of ELCs on local communities. Using time-series from MODIS Vegetation Indices products for the study period, we also estimated the time period over which any particular ELC deal initiated its proposed activity. We found evidence of similar patterns of land use change outside the boundaries of ELC deals which may be associated with i) illegal land encroachments by ELCs and/or ii) new agricultural practices adopted by local farmers near ELC boundaries. We also detected significant time gaps between ELC deal granting dates and initiation of land clearing for ELC purposes. Interestingly, we also found that not all designated areas for ELCs were put into effect indicating the possible proliferation of speculative land deals. This study demonstrates the potential of remote sensing techniques

  4. 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.

  5. Mapping Land Cover and Land Use Changes in the Congo Basin Forests with Optical Satellite Remote Sensing: a Pilot Project Exploring Methodologies that Improve Spatial Resolution and Map Accuracy

    NASA Astrophysics Data System (ADS)

    Molinario, G.; Baraldi, A.; Altstatt, A. L.; Nackoney, J.

    2011-12-01

    The University of Maryland has been a USAID Central Africa Rregional Program for the Environment (CARPE) cross-cutting partner for many years, providing remote sensing derived information on forest cover and forest cover changes in support of CARPE's objectives of diminishing forest degradation, loss and biodiversity loss as a result of poor or inexistent land use planning strategies. Together with South Dakota State University, Congo Basin-wide maps have been provided that map forest cover loss at a maximum of 60m resolution, using Landsat imagery and higher resolution imagery for algorithm training and validation. However, to better meet the needs within the CARPE Landscapes, which call for higher resolution, more accurate land cover change maps, UMD has been exploring the use of the SIAM automatic spectral -rule classifier together with pan-sharpened Landsat data (15m resolution) and Very High Resolution imagery from various sources. The pilot project is being developed in collaboration with the African Wildlife Foundation in the Maringa Lopori Wamba CARPE Landscape. If successful in the future this methodology will make the creation of high resolution change maps faster and easier, making it accessible to other entities in the Congo Basin that need accurate land cover and land use change maps in order, for example, to create sustainable land use plans, conserve biodiversity and resources and prepare Reducing Emissions from forest Degradation and Deforestation (REDD) Measurement, Reporting and Verification (MRV) projects. The paper describes the need for higher resolution land cover change maps that focus on forest change dynamics such as the cycling between primary forests, secondary forest, agriculture and other expanding and intensifying land uses in the Maringa Lopori Wamba CARPE Landscape in the Equateur Province of the Democratic Republic of Congo. The Methodology uses the SIAM remote sensing imagery automatic spectral rule classifier, together with pan

  6. Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

    NASA Astrophysics Data System (ADS)

    Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

    2014-12-01

    This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

  7. Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

    NASA Astrophysics Data System (ADS)

    Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

    2015-12-01

    This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

  8. Decadal land cover change dynamics in Bhutan.

    PubMed

    Gilani, Hammad; Shrestha, Him Lal; Murthy, M S R; Phuntso, Phuntso; Pradhan, Sudip; Bajracharya, Birendra; Shrestha, Basanta

    2015-01-15

    Land cover (LC) is one of the most important and easily detectable indicators of change in ecosystem services and livelihood support systems. This paper describes the decadal dynamics in LC changes at national and sub-national level in Bhutan derived by applying object-based image analysis (OBIA) techniques to 1990, 2000, and 2010 Landsat (30 m spatial resolution) data. Ten LC classes were defined in order to give a harmonized legend land cover classification system (LCCS). An accuracy of 83% was achieved for LC-2010 as determined from spot analysis using very high resolution satellite data from Google Earth Pro and limited field verification. At the national level, overall forest increased from 25,558 to 26,732 km(2) between 1990 and 2010, equivalent to an average annual growth rate of 59 km(2)/year (0.22%). There was an overall reduction in grassland, shrubland, and barren area, but the observations were highly dependent on time of acquisition of the satellite data and climatic conditions. The greatest change from non-forest to forest (277 km(2)) was in Bumthang district, followed by Wangdue Phodrang and Trashigang, with the least (1 km(2)) in Tsirang. Forest and scrub forest covers close to 75% of the land area of Bhutan, and just over half of the total area (51%) has some form of conservation status. This study indicates that numerous applications and analyses can be carried out to support improved land cover and land use (LCLU) management. It will be possible to replicate this study in the future as comparable new satellite data is scheduled to become available. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Estimating Hydrologic Fluxes, Crop Water Use, and Agricultural Land Area in China using Data Assimilation

    NASA Astrophysics Data System (ADS)

    Smith, Tiziana; McLaughlin, Dennis B.; Hoisungwan, Piyatida

    2016-04-01

    Crop production has significantly altered the terrestrial environment by changing land use and by altering the water cycle through both co-opted rainfall and surface water withdrawals. As the world's population continues to grow and individual diets become more resource-intensive, the demand for food - and the land and water necessary to produce it - will continue to increase. High-resolution quantitative data about water availability, water use, and agricultural land use are needed to develop sustainable water and agricultural planning and policies. However, existing data covering large areas with high resolution are susceptible to errors and can be physically inconsistent. China is an example of a large area where food demand is expected to increase and a lack of data clouds the resource management dialogue. Some assert that China will have insufficient land and water resources to feed itself, posing a threat to global food security if they seek to increase food imports. Others believe resources are plentiful. Without quantitative data, it is difficult to discern if these concerns are realistic or overly dramatized. This research presents a quantitative approach using data assimilation techniques to characterize hydrologic fluxes, crop water use (defined as crop evapotranspiration), and agricultural land use at 0.5 by 0.5 degree resolution and applies the methodology in China using data from around the year 2000. The approach uses the principles of water balance and of crop water requirements to assimilate existing data with a least-squares estimation technique, producing new estimates of water and land use variables that are physically consistent while minimizing differences from measured data. We argue that this technique for estimating water fluxes and agricultural land use can provide a useful basis for resource management modeling and policy, both in China and around the world.

  10. 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...

  11. Land-Cover and Land-Use Change in the Brazilian Amazon: Smallholders, Ranchers and Frontier Stratification

    NASA Technical Reports Server (NTRS)

    Aldrich, Stephen P.; Walker, Robert T.; Arima, Eugenio Y.; Caldas, Marcellus M.; Browder, John O.; Perz, Stephen

    2006-01-01

    Tropical deforestation is a significant driver of global environmental change, given its impacts on the carbon cycle and biodiversity. Loss of the Amazon forest, the focus of this article, is of particular concern because of the size and the rapid rate at which the forest is being converted to agricultural use. In this article, we identify what has been the most important driver of deforestation in a specific colonization frontier in the Brazilian Amazon. To this end, we consider (1) the land-use dynamics of smallholder households, (2) the formation of pasture by large-scale ranchers, and (3) structural processes of land aggregation by ranchers. Much has been written about relations between smallholders and ranchers in the Brazilian Amazon, particularly those involving conflict over land, and this article explicates the implications of such social processes for land cover. Toward this end, we draw on panel data (1996-2002) and satellite imagery (1986-1999) to show the deforestation that is attributable to small- and largeholders, and the deforestation that is attributable to aggregations of property arising from a process that we refer to as frontier stratification. Evidently, most of the recent deforestation in the study area has resulted from the household processes of smallholders, not from conversions to pasture pursuant to the appropriations of smallholders' property by well-capitalized ranchers or speculators.

  12. 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.

  13. The American Land. Its History, Soil, Water, Wildlife, Agricultural Land Planning, and Land Problems of Today and Tomorrow.

    ERIC Educational Resources Information Center

    Soil Conservation Service (USDA), Washington, DC.

    Presented in this booklet is the commentary for "The American Land," a television series prepared by the Soil Conservation Service and the Graduate School, United States Department of Agriculture, in cooperation with WETA - TV, Washington, D.C. It explores the resource of land in America, its history, soil, water, wildlife, agricultural land…

  14. Land cover change of watersheds in Southern Guam from 1973 to 2001.

    PubMed

    Wen, Yuming; Khosrowpanah, Shahram; Heitz, Leroy

    2011-08-01

    Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.

  15. Changes in the dissolved nitrogen pool across land cover gradients in Wisconsin streams.

    PubMed

    Stanley, Emily H; Maxted, Jeffrey T

    2008-10-01

    Increases in anthropogenic nitrogen fixation have resulted in wide-scale enrichment of aquatic ecosystems. Existing biogeochemical theory suggests that N enrichment is associated with increasing concentrations of nitrate; however, dissolved organic nitrogen (DON) is often a major component of the total dissolved nitrogen (TDN) pool in streams and rivers, and its concentration can be significantly elevated in human-influenced basins. We examined N concentrations during summer base flow conditions in 324 Wisconsin streams to determine whether DON was a significant component of TDN and how its relative contribution changed across a gradient of increasing human (agriculture and urban) land use for 84 of these sites. Total dissolved nitrogen varied from 0.09 to 20.74 mg/L, and although DON was significantly higher in human-dominated basins relative to forested and mixed-cover basins, its concentration increased relatively slowly in response to increasing human land cover. This limited response reflected a replacement of wetland-derived DON in low-N streams by anthropogenic sources in human-dominated sites, such that net changes in DON were small across the land use gradient. Nitrate-N increased exponentially in response to greater human land cover, and NH4-N and NO2-N were present at low levels. Nitrite-N exceeded NH4-N at 20% of sites and reached a maximum concentration of 0.10 mg/L. This examination suggests that basic mechanisms driving N losses from old-growth forests subject to N saturation also shape the summertime N pool in Wisconsin streams, in addition to other processes dictated by landscape context. The overwhelming role of human land use in determining the relative and absolute composition of the summertime N pool included (1) rapid increases in NO3-N, (2) limited changes in DON, and (3) the unexpected occurrence of NO2-N. High (>3 mg/L) TDN conditions dominated by NO3-N, regardless of landscape context or forms of N inputs, indicate a state of "N

  16. Weed science and management, in soil sciences, land cover, and land use

    USDA-ARS?s Scientific Manuscript database

    An integral component of conservation agriculture systems in cotton is the use of a high-residue winter cover crop; however, terminating such cover crops is a cost and planting into high-residue is a challenge. Black oat, rye, and wheat winter cover crops were flattened with a straight-blade mechan...

  17. 43 CFR 3101.4 - Lands covered by application to close lands to mineral leasing.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... lands to mineral leasing. 3101.4 Section 3101.4 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) OIL AND GAS LEASING Issuance of Leases § 3101.4 Lands covered by application to close lands to mineral...

  18. 43 CFR 3101.4 - Lands covered by application to close lands to mineral leasing.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... lands to mineral leasing. 3101.4 Section 3101.4 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) OIL AND GAS LEASING Issuance of Leases § 3101.4 Lands covered by application to close lands to mineral...

  19. 43 CFR 3101.4 - Lands covered by application to close lands to mineral leasing.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... lands to mineral leasing. 3101.4 Section 3101.4 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) OIL AND GAS LEASING Issuance of Leases § 3101.4 Lands covered by application to close lands to mineral...

  20. Quantify the Biophysical and Socioeconomic Drivers of Changes in Forest and Agricultural Land in South and Southeast Asia

    NASA Astrophysics Data System (ADS)

    Xu, X.; Jain, A. K.; Calvin, K. V.

    2017-12-01

    Due to the rapid socioeconomic development and biophysical factors, South and Southeast Asia (SSEA) has become a hotspot region of land use and land cover changes (LULCCs) in past few decades. Uncovering the drivers of LULCC is crucial for improving the understanding of LULCC processes. Due to the differences from spatiotemporal scales, methods and data sources in previous studies, the quantitative relationships between the LULCC activities and biophysical and socioeconomic drivers at the regional scale of SSEA have not been established. Here we present a comprehensive estimation of the biophysical and socioeconomic drivers of the major LULCC activities in SSEA: changes in forest and agricultural land. We used the Climate Change Initiative land cover data developed by European Space Agency to reveal the dynamics of forest and agricultural land from 1992 to 2015. Then we synthesized 200 publications about LULCC drivers at different spatial scales in SSEA to identify the major drivers of these LULCC activities. Corresponding representative variables of the major drivers were collected. The geographically weighted regression was employed to assess the spatiotemporally heterogeneous drivers of LULCC. Moreover, we validated our results with some national level case studies in SSEA. The results showed that both biophysical conditions such as terrain, soil, and climate, and socioeconomic factors such as migration, poverty, and economy played important roles in driving the changes of forest and agricultural land. The major drivers varied in different locations and periods. Our study integrated the bottom-up knowledge from local scale case studies with the top-down estimation of LULCC drivers, therefore generated more accurate and credible results. The identified biophysical and socioeconomic components could be used to improve the LULCC modelling and projection.

  1. Landsat continuity: Issues and opportunities for land cover monitoring

    USGS Publications Warehouse

    Wulder, M.A.; White, Joanne C.; Goward, S.N.; Masek, J.G.; Irons, J.R.; Herold, M.; Cohen, W.B.; Loveland, Thomas R.; Woodcock, C.E.

    2008-01-01

    Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures

  2. Using indigenous knowledge to link hyper-temporal land cover mapping with land use in the Venezuelan Amazon: "The Forest Pulse".

    PubMed

    Olivero, Jesús; Ferri, Francisco; Acevedo, Pelayo; Lobo, Jorge M; Fa, John E; Farfán, Miguel Á; Romero, David; Real, Raimundo

    2016-12-01

    Remote sensing and traditional ecological knowledge (TEK) can be combined to advance conservation of remote tropical regions, e.g. Amazonia, where intensive in situ surveys are often not possible. Integrating TEK into monitoring and management of these areas allows for community participation, as well as for offering novel insights into sustainable resource use. In this study, we developed a 250 m resolution land-cover map of the Western Guyana Shield (Venezuela) based on remote sensing, and used TEK to validate its relevance for indigenous livelihoods and land uses. We first employed a hyper-temporal remotely sensed vegetation index to derive a land classification system. During a 1 300 km, eight day fluvial expedition in roadless areas in the Amazonas State (Venezuela), we visited six indigenous communities who provided geo-referenced data on hunting, fishing and farming activities. We overlaid these TEK data onto the land classification map, to link land classes with indigenous use. We characterized land classes using patterns of greenness temporal change and topo-hydrological information, and proposed 12 land-cover types, grouped into five main landscapes: 1) water bodies; 2) open lands/forest edges; 3) evergreen forests; 4) submontane semideciduous forests, and 5) cloud forests. Each land cover class was identified with a pulsating profile describing temporal changes in greenness, hence we labelled our map as "The Forest Pulse". These greenness profiles showed a slightly increasing trend, for the period 2000 to 2009, in the land classes representing grassland and scrubland, and a slightly decreasing trend in the classes representing forests. This finding is consistent with a gain in carbon in grassland as a consequence of climate warming, and also with some loss of vegetation in the forests. Thus, our classification shows potential to assess future effects of climate change on landscape. Several classes were significantly connected with agriculture, fishing

  3. Mapping environmental land use conflict potentials and ecosystem services in agricultural watersheds.

    PubMed

    Kim, Ilkwon; Arnhold, Sebastian

    2018-07-15

    In mountainous watersheds, agricultural land use cause changes in ecosystem services, with trade-offs between crop production and erosion regulation. Management of these watersheds can generate environmental land use conflicts among regional stakeholders with different interests. Although several researches have made a start in mapping land use conflicts between human activities and conservation, spatial assessment of land use conflicts on environmental issues and ecosystem service trade-offs within agricultural areas has not been fully considered. In this study, we went further to map land use conflicts between agricultural preferences for crop production and environmental emphasis on erosion regulation. We applied an agricultural land suitability index, based on multi-criteria analysis, to estimate the spatial preference of agricultural activities, while applying the Revised Universal Soil Loss Equation (RUSLE) to reflect the environmental importance of soil erosion. Then, we classified the agricultural catchment into four levels of land use conflicts (lowest, low, high and highest) according to preference and importance of farmland areas, and we compared the classes by crop type. Soil loss in agricultural areas was estimated as 45.1thayr, and agricultural suitability as 0.873; this indicated that land use conflicts in the catchment could arise between severe soil erosion (environmental importance) and agricultural suitability (land preferences). Dry-field farms are mainly located in areas of low land use conflict level, where land preference outweighs environmental importance. When we applied farmland management scenarios with consideration of services, conversion to highest-conflict areas (Scenario 1) as 7.5% of the total area could reduce soil loss by 24.6%, while fallow land management (Scenario 2) could decrease soil loss 19.4% more than the current scenario (Business as usual). The result could maximize land management plans by extracting issues of spatial

  4. Characterization of agricultural land using singular value decomposition

    NASA Astrophysics Data System (ADS)

    Herries, Graham M.; Danaher, Sean; Selige, Thomas

    1995-11-01

    A method is defined and tested for the characterization of agricultural land from multi-spectral imagery, based on singular value decomposition (SVD) and key vector analysis. The SVD technique, which bears a close resemblance to multivariate statistic techniques, has previously been successfully applied to problems of signal extraction for marine data and forestry species classification. In this study the SVD technique is used as a classifier for agricultural regions, using airborne Daedalus ATM data, with 1 m resolution. The specific region chosen is an experimental research farm in Bavaria, Germany. This farm has a large number of crops, within a very small region and hence is not amenable to existing techniques. There are a number of other significant factors which render existing techniques such as the maximum likelihood algorithm less suitable for this area. These include a very dynamic terrain and tessellated pattern soil differences, which together cause large variations in the growth characteristics of the crops. The SVD technique is applied to this data set using a multi-stage classification approach, removing unwanted land-cover classes one step at a time. Typical classification accuracy's for SVD are of the order of 85-100%. Preliminary results indicate that it is a fast and efficient classifier with the ability to differentiate between crop types such as wheat, rye, potatoes and clover. The results of characterizing 3 sub-classes of Winter Wheat are also shown.

  5. An analysis of IGBP global land-cover characterization process

    USGS Publications Warehouse

    Loveland, Thomas R.; Zhu, Zhiliang; Ohlen, Donald O.; Brown, Jesslyn F.; Reed, Bradley C.; Yang, Limin

    1999-01-01

    The international Geosphere Biosphere Programme (IGBP) has called for the development of improved global land-cover data for use in increasingly sophisticated global environmental models. To meet this need, the staff of the U.S. Geological Survey and the University of Nebraska-Lincoln developed and applied a global land-cover characterization methodology using 1992-1993 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) and other spatial data. The methodology, based on unsupervised classification with extensive postclassification refinement, yielded a multi-layer database consisting of eight land-cover data sets, descriptive attributes, and source data. An independent IGBP accuracy assessment reports a global accuracy of 73.5 percent, and continental results vary from 63 percent to 83 percent. Although data quality, methodology, interpreter performance, and logistics affected the results, significant problems were associated with the relationship between AVHRR data and fine-scale, spectrally similar land-cover patterns in complex natural or disturbed landscapes.

  6. Operational monitoring of land-cover change using multitemporal remote sensing data

    NASA Astrophysics Data System (ADS)

    Rogan, John

    2005-11-01

    Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation

  7. An Inventory of Ohio's Land Use/Land Cover as Seen by Landsat

    NASA Technical Reports Server (NTRS)

    Schaal, Gary M.

    1977-01-01

    LANDSAT 2 (Land Satellite) was launched at Vandenburg, AFB, California on January 22, 1975. The satellite orbits the earth at an altitude of about 920 km (570 miles) and scans the earth's surface in a continuous track 185 km (115 miles) wide. LANDSAT 2 passes over the same spot every 18 days transmitting scanned data to receiving stations scattered around the globe. LANDSAT's continuously-scanning sensors provide useful information about the earth, one of the most important categories being land use. The statistics contained in the appendices of this report represent acreage and percentage of seven types of land cover in Ohio as seen by LANDSAT. The inventory represents a trial effort at determining the Sate's land cover by a method which is inexpensive, reliable, accurate and rapid. Given a successful method, the inventory and periodic updates could provide information to land use decision-makers and, over a period of time, would reveal patterns of land use change. Technical aspects of the project (process, methodology, and verification) are discussed in Schaal (1977) and Schmidt (1976).

  8. The Monitoring Erosion of Agricultural Land and spatial database of erosion events

    NASA Astrophysics Data System (ADS)

    Kapicka, Jiri; Zizala, Daniel

    2013-04-01

    In 2011 originated in The Czech Republic The Monitoring Erosion of Agricultural Land as joint project of State Land Office (SLO) and Research Institute for Soil and Water Conservation (RISWC). The aim of the project is collecting and record keeping information about erosion events on agricultural land and their evaluation. The main idea is a creation of a spatial database that will be source of data and information for evaluation and modeling erosion process, for proposal of preventive measures and measures to reduce negative impacts of erosion events. A subject of monitoring is the manifestations of water erosion, wind erosion and slope deformation in which cause damaged agriculture land. A website, available on http://me.vumop.cz, is used as a tool for keeping and browsing information about monitored events. SLO employees carry out record keeping. RISWC is specialist institute in the Monitoring Erosion of Agricultural Land that performs keeping the spatial database, running the website, managing the record keeping of events, analysis the cause of origins events and statistical evaluations of keeping events and proposed measures. Records are inserted into the database using the user interface of the website which has map server as a component. Website is based on database technology PostgreSQL with superstructure PostGIS and MapServer UMN. Each record is in the database spatial localized by a drawing and it contains description information about character of event (data, situation description etc.) then there are recorded information about land cover and about grown crops. A part of database is photodocumentation which is taken in field reconnaissance which is performed within two days after notify of event. Another part of database are information about precipitations from accessible precipitation gauges. Website allows to do simple spatial analysis as are area calculation, slope calculation, percentage representation of GAEC etc.. Database structure was designed

  9. Error and Uncertainty in the Accuracy Assessment of Land Cover Maps

    NASA Astrophysics Data System (ADS)

    Sarmento, Pedro Alexandre Reis

    Traditionally the accuracy assessment of land cover maps is performed through the comparison of these maps with a reference database, which is intended to represent the "real" land cover, being this comparison reported with the thematic accuracy measures through confusion matrixes. Although, these reference databases are also a representation of reality, containing errors due to the human uncertainty in the assignment of the land cover class that best characterizes a certain area, causing bias in the thematic accuracy measures that are reported to the end users of these maps. The main goal of this dissertation is to develop a methodology that allows the integration of human uncertainty present in reference databases in the accuracy assessment of land cover maps, and analyse the impacts that uncertainty may have in the thematic accuracy measures reported to the end users of land cover maps. The utility of the inclusion of human uncertainty in the accuracy assessment of land cover maps is investigated. Specifically we studied the utility of fuzzy sets theory, more precisely of fuzzy arithmetic, for a better understanding of human uncertainty associated to the elaboration of reference databases, and their impacts in the thematic accuracy measures that are derived from confusion matrixes. For this purpose linguistic values transformed in fuzzy intervals that address the uncertainty in the elaboration of reference databases were used to compute fuzzy confusion matrixes. The proposed methodology is illustrated using a case study in which the accuracy assessment of a land cover map for Continental Portugal derived from Medium Resolution Imaging Spectrometer (MERIS) is made. The obtained results demonstrate that the inclusion of human uncertainty in reference databases provides much more information about the quality of land cover maps, when compared with the traditional approach of accuracy assessment of land cover maps. None

  10. 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.

  11. Exploring geo-tagged photos for land cover validation with deep learning

    NASA Astrophysics Data System (ADS)

    Xing, Hanfa; Meng, Yuan; Wang, Zixuan; Fan, Kaixuan; Hou, Dongyang

    2018-07-01

    Land cover validation plays an important role in the process of generating and distributing land cover thematic maps, which is usually implemented by high cost of sample interpretation with remotely sensed images or field survey. With an increasing availability of geo-tagged landscape photos, the automatic photo recognition methodologies, e.g., deep learning, can be effectively utilised for land cover applications. However, they have hardly been utilised in validation processes, as challenges remain in sample selection and classification for highly heterogeneous photos. This study proposed an approach to employ geo-tagged photos for land cover validation by using the deep learning technology. The approach first identified photos automatically based on the VGG-16 network. Then, samples for validation were selected and further classified by considering photos distribution and classification probabilities. The implementations were conducted for the validation of the GlobeLand30 land cover product in a heterogeneous area, western California. Experimental results represented promises in land cover validation, given that GlobeLand30 showed an overall accuracy of 83.80% with classified samples, which was close to the validation result of 80.45% based on visual interpretation. Additionally, the performances of deep learning based on ResNet-50 and AlexNet were also quantified, revealing no substantial differences in final validation results. The proposed approach ensures geo-tagged photo quality, and supports the sample classification strategy by considering photo distribution, with accuracy improvement from 72.07% to 79.33% compared with solely considering the single nearest photo. Consequently, the presented approach proves the feasibility of deep learning technology on land cover information identification of geo-tagged photos, and has a great potential to support and improve the efficiency of land cover validation.

  12. Relation of land use/land cover to resource demands

    NASA Technical Reports Server (NTRS)

    Clayton, C.

    1981-01-01

    Predictive models for forecasting residential energy demand are investigated. The models are examined in the context of implementation through manipulation of geographic information systems containing land use/cover information. Remotely sensed data is examined as a possible component in this process.

  13. 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

  14. Vegetated land cover near residence is associated with ...

    EPA Pesticide Factsheets

    Abstract Background: Greater exposure to urban green spaces has been linked to reduced risks of depression, cardiovascular disease, diabetes and premature death. Alleviation of chronic stress is a hypothesized pathway to improved health. Previous studies linked chronic stress with biomarker-based measures of physiological dysregulation known as allostatic load. This study aimed to assess the relationship between vegetated land cover near residences and allostatic load. Methods: This cross-sectional population-based study involved 204 adult residents of the Durham-Chapel Hill, North Carolina metropolitan area. Exposure was quantified using high-resolution metrics of trees and herbaceous vegetation within 500 m of each residence derived from the U.S. Environmental Protection Agency’s EnviroAtlas land cover dataset. Eighteen biomarkers of immune, neuroendocrine, and metabolic functions were measured in serum or saliva samples. Allostatic load was defined as a sum of biomarker values dichotomized at specific percentiles of sample distribution. Regression analysis was conducted using generalized additive models with two-dimensional spline smoothing function of geographic coordinates, weighted measures of vegetated land cover allowing decay of effects with distance, and geographic and demographic covariates. Results: An inter-quartile range increase in distance-weighted vegetated land cover was associated with 37% (46%; 27%) reduced allostatic load; significantly

  15. Sensitivity of June Near-Surface Temperatures and Precipitation in the Eastern United States to Historical Land Cover Changes Since European Settlement

    NASA Technical Reports Server (NTRS)

    Strack, John E.; Pielke, Roger A.; Steyaert, Louis T.; Knox, Robert G.

    2008-01-01

    Land cover changes alter the near surface weather and climate. Changes in land surface properties such as albedo, roughness length, stomatal resistance, and leaf area index alter the surface energy balance, leading to differences in near surface temperatures. This study utilized a newly developed land cover data set for the eastern United States to examine the influence of historical land cover change on June temperatures and precipitation. The new data set contains representations of the land cover and associated biophysical parameters for 1650, 1850, 1920, and 1992, capturing the clearing of the forest and the expansion of agriculture over the eastern United States from 1650 to the early twentieth century and the subsequent forest regrowth. The data set also includes the inferred distribution of potentially water-saturated soils at each time slice for use in the sensitivity tests. The Regional Atmospheric Modeling System, equipped with the Land Ecosystem-Atmosphere Feedback (LEAF-2) land surface parameterization, was used to simulate the weather of June 1996 using the 1992, 1920, 1850, and 1650 land cover representations. The results suggest that changes in surface roughness and stomatal resistance have caused present-day maximum and minimum temperatures in the eastern United States to warm by about 0.3 C and 0.4 C, respectively, when compared to values in 1650. In contrast, the maximum temperatures have remained about the same, while the minimums have cooled by about 0.1 C when compared to 1920. Little change in precipitation was found.

  16. Integration of strategic inventory and monitoring programs for the forest lands, wood lands, range lands and agricultural lands of the United States

    Treesearch

    Raymond L. Czaplewski

    1999-01-01

    The United States Department of Agriculture uses the Forest Inventory and Analysis (FIA) program to monitor the nation's forests and wood lands, and the National Resources Inventory (NRI) program to monitor the nation's agricultural and range lands. Although their measurement methods and sampling frames are very different, both programs are developing annual...

  17. Effects of spatial resolution and landscape structure on land cover characterization

    NASA Astrophysics Data System (ADS)

    Yang, Wenli

    This dissertation addressed problems in scaling, problems that are among the main challenges in remote sensing. The principal objective of the research was to investigate the effects of changing spatial scale on the representation of land cover. A second objective was to determine the relationship between such effects, characteristics of landscape structure and scaling procedures. Four research issues related to spatial scaling were examined. They included: (1) the upscaling of Normalized Difference Vegetation Index (NDVI); (2) the effects of spatial scale on indices of landscape structure; (3) the representation of land cover databases at different spatial scales; and (4) the relationships between landscape indices and land cover area estimations. The overall bias resulting from non-linearity of NDVI in relation to spatial resolution is generally insignificant as compared to other factors such as influences of aerosols and water vapor. The bias is, however, related to land surface characteristics. Significant errors may be introduced in heterogeneous areas where different land cover types exhibit strong spectral contrast. Spatially upscaled SPOT and TM NDVIs have information content comparable with the AVHRR-derived NDVI. Indices of landscape structure and spatial resolution are generally related, but the exact forms of the relationships are subject to changes in other factors including the basic patch unit constituting a landscape and the proportional area of foreground land cover under consideration. The extent of agreement between spatially aggregated coarse resolution land cover datasets and full resolution datasets changes with the properties of the original datasets, including the pixel size and class definition. There are close relationships between landscape structure and class areas estimated from spatially aggregated land cover databases. The relationships, however, do not permit extension from one area to another. Inversion calibration across different

  18. Green Infrastructure and Watershed-Scale Hydrology in a Mixed Land Cover System

    NASA Astrophysics Data System (ADS)

    Hoghooghi, N.; Golden, H. E.; Bledsoe, B. P.

    2017-12-01

    Urbanization results in replacement of pervious areas (e.g., vegetation, topsoil) with impervious surfaces such as roads, roofs, and parking lots, which cause reductions in interception, evapotranspiration, and infiltration, and increases in surface runoff (overland flow) and pollutant loads and concentrations. Research on the effectiveness of different Green Infrastructure (GI), or Low Impact Development (LID), practices to reduce these negative impacts on stream flow and water quality has been mostly focused at the local scale (e.g., plots, small catchments). However, limited research has considered the broader-scale effects of LID, such as how LID practices influence water quantity, nutrient removal, and aquatic ecosystems at watershed scales, particularly in mixed land cover and land use systems. We use the Visualizing Ecosystem Land Management Assessments (VELMA) model to evaluate the effects of different LID practices on daily and long-term watershed-scale hydrology, including infiltration surface runoff. We focus on Shayler Crossing (SHC) watershed, a mixed land cover (61% urban, 24% agriculture, 15% forest) subwatershed of the East Fork Little Miami River watershed, Ohio, United States, with a drainage area of 0.94 km2. The model was calibrated to daily stream flow at the outlet of SHC watershed from 2009 to 2010 and was applied to evaluate diverse distributions (at 25% to 100% implementation levels) and types (e.g., pervious pavement and rain gardens) of LID across the watershed. Results show reduced surface water runoff and higher rates of infiltration concomitant with increasing LID implementation levels; however, this response varies between different LID practices. The highest magnitude response in streamflow at the watershed outlet is evident when a combination of LID practices is applied. The combined scenarios elucidate that the diverse watershed-scale hydrological responses of LID practices depend primarily on the type and extent of the implemented

  19. High Resolution Land Use Land Cover Classification using Landsat Earth Observation Data for the Continental Africa

    NASA Astrophysics Data System (ADS)

    Midekisa, A.; Bennet, A.; Gething, P. W.; Holl, F.; Andrade-Pacheco, R.; Savory, D. J.; Hugh, S. J.

    2016-12-01

    Spatially detailed and temporally dynamic land use land cover data is necessary to monitor the state of the land surface for various applications. Yet, such data at a continental to global scale is lacking. Here, we developed high resolution (30 meter) annual land use land cover layers for the continental Africa using Google Earth Engine. To capture ground truth training data, high resolution satellite imageries were visually inspected and used to identify 7, 212 sample Landsat pixels that were comprised entirely of one of seven land use land cover classes (water, man-made impervious surface, high biomass, low biomass, rock, sand and bare soil). For model validation purposes, 80% of points from each class were used as training data, with 20% withheld as a validation dataset. Cloud free Landsat 7 annual composites for 2000 to 2015 were generated and spectral bands from the Landsat images were then extracted for each of the training and validation sample points. In addition to the Landsat spectral bands, spectral indices such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used as covariates in the model. Additionally, calibrated night time light imageries from the National Oceanic and Atmospheric Administration (NOAA) were included as a covariate. A decision tree classification algorithm was applied to predict the 7 land cover classes for the periods 2000 to 2015 using the training dataset. Using the validation dataset, classification accuracy including omission error and commission error were computed for each land cover class. Model results showed that overall accuracy of classification was high (88%). This high resolution land cover product developed for the continental Africa will be available for public use and can potentially enhance the ability of monitoring and studying the state of the Earth's surface.

  20. Evaluating ecoregions for sampling and mapping land-cover patterns

    Treesearch

    Kurt H. Riitters; James D. Wickham; Timothy G. Wade

    2006-01-01

    Ecoregional stratification has been proposed for sampling and mapping land-cover composition and pattern over time. Using a wall-to-wall land-cover map of the United States, we evaluated geographic scales of variance for nine landscapelevel and eight forest pattern indices, and compared stratification by ecoregions, administrative units, and watersheds. Ecoregions...

  1. Extraction of land cover change information from ENVISAT-ASAR data in Chengdu Plain

    NASA Astrophysics Data System (ADS)

    Xu, Wenbo; Fan, Jinlong; Huang, Jianxi; Tian, Yichen; Zhang, Yong

    2006-10-01

    Land cover data are essential to most global change research objectives, including the assessment of current environmental conditions and the simulation of future environmental scenarios that ultimately lead to public policy development. Chinese Academy of Sciences generated a nationwide land cover database in order to carry out the quantification and spatial characterization of land use/cover changes (LUCC) in 1990s. In order to improve the reliability of the database, we will update the database anytime. But it is difficult to obtain remote sensing data to extract land cover change information in large-scale. It is hard to acquire optical remote sensing data in Chengdu plain, so the objective of this research was to evaluate multitemporal ENVISAT advanced synthetic aperture radar (ASAR) data for extracting land cover change information. Based on the fieldwork and the nationwide 1:100000 land cover database, the paper assesses several land cover changes in Chengdu plain, for example: crop to buildings, forest to buildings, and forest to bare land. The results show that ENVISAT ASAR data have great potential for the applications of extracting land cover change information.

  2. Patterns of land use, extensification, and intensification of Brazilian agriculture.

    PubMed

    Dias, Lívia C P; Pimenta, Fernando M; Santos, Ana B; Costa, Marcos H; Ladle, Richard J

    2016-08-01

    Sustainable intensification of agriculture is one of the main strategies to provide global food security. However, its implementation raises enormous political, technological, and social challenges. Meeting these challenges will require, among other things, accurate information on the spatial and temporal patterns of agricultural land use and yield. Here, we investigate historical patterns of agricultural land use (1940-2012) and productivity (1990-2012) in Brazil using a new high-resolution (approximately 1 km(2) ) spatially explicit reconstruction. Although Brazilian agriculture has been historically known for its extensification over natural vegetation (Amazon and Cerrado), data from recent years indicate that extensification has slowed down and was replaced by a strong trend of intensification. Our results provide the first comprehensive historical overview of agricultural land use and productivity in Brazil, providing clear insights to guide future territorial planning, sustainable agriculture, policy, and decision-making. © 2016 John Wiley & Sons Ltd.

  3. EnviroAtlas - Portland, ME - Land Cover by Block Group

    EPA Pesticide Factsheets

    This EnviroAtlas dataset describes the percentage of each block group that is classified as impervious, forest, green space, wetland, and agriculture. Impervious is a combination of dark and light impervious. Forest is combination of trees and forest and woody wetlands. Green space is a combination of trees and forest, grass and herbaceous, agriculture, woody wetlands, and emergent wetlands. Wetlands includes both Woody and Emergent Wetlands. This dataset also includes the area per capita for each block group for impervious, forest, and green space land cover. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  4. 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...

  5. 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.

  6. Assessing land use and cover change effects on hydrological response in the river C

    NASA Astrophysics Data System (ADS)

    Nunes, A.

    2009-04-01

    Assessing the impacts of land use change, especially the role of vegetation, on hydrological response from the plot to the catchment scale has become one of the widespread issues of scientific concern,in recent decades. The continuous expansion of urban areas, the dramatic changes in land-cover and land-use patterns and the climate change which have taken place on a global scale explain this increasing interest. Although scientists have long recognized that changes in land use and land cover are important factors affecting water circulation and the spatial-temporal variations in the distribution of water resources, little is known about the quantitative relation between land use/coverage characteristics and runoff generation or processes. Therefore, a better understanding of how land-use changes impact watershed hydrological processes will become a crucial issue for the planning, management, and sustainable development of water resources. In the past decades, abandonment of marginal agricultural land has been a widespread phenomenon in Portugal, as well as in many other countries of Europe, especially in the Mediterranean countries. The abandonment of arable land typically leads to natural succession and to the development of shrub and woodland. Shrubs like Cytisus spp.usually establish in study area. A Quercus pyrenaica Willd. wood generally appears after a long time, about 3 or 4 decades. The general aim of this work is to analyse the temporal evolution of water supplies in a Côa basins (located between 41°00'' N and 40°15'' N and 7°15'' W and 6°55'' W Greenwich)and relate its behaviour with changes undergone by the plant cover and by the main climatic variables (temperatures and precipitation). To achieve this goal, dynamics on the land use and land cover were estimated after the second half of the 20th century. The hydrological response under different land uses and plant covers were monitored during 2005 and 2006, using small permanently establish bounded

  7. Complex land cover change, water and sediment yield in a degraded Andean environment

    NASA Astrophysics Data System (ADS)

    Molina, Armando; Vanacker, Veerle; Balthazar, Vincent; Mora, Diego; Govers, Gerard

    2012-11-01

    SummaryRapid land use/-cover change has increasingly transformed the hydrological functioning of tropical Andean ecosystems. The hydrological response to forest cover change strongly depends on the initial state of the ecosystem. Relatively little is known about human-disturbed ecosystems where forest plantations have been established on highly degraded land. In this paper, we analyze the impact of forest change on water and sediment fluxes for a highly degraded Andean catchment. Different pathways of land cover change (1963-2007) are observed in the Jadan catchment, with deforestation taking place in remote uplands and recovery and reforestation in the middle and lower parts where agricultural and bare lands are prevalent. Time series analyses of streamflow and rainfall data (1979/1982-2005/2007) show significant shifts in the distribution of rainfall and flow data. Changes in discharge are not resulting from changes in precipitation, as the direction of change is opposite. The removal of native forest for rangeland or croplands (by -20 km2) is likely to have contributed to the increase in total annual water yield, through an increase in annual baseflow by 25 mm. The observed changes in peakflow are important as the 1st percentile highest flow rates were 54% lower, while the 1st percentile rainfall amounts increased by 52%. The observed decrease in peakflow cannot be explained by clearcut of native forest, but is likely to be related to reforestation of degraded lands as well as spontaneous recovery of vegetation on remaining grazing lands. Over the same time period, a major decrease in specific sediment yields and suspended sediment loads was observed. Although deforestation in the upper parts led to increased landslide activity, this change is not reflected in an increased sediment yield. Small upland rivers are often nearly completely blocked by landslide material, thereby reducing their potential to transport sediment. In contrast, the reduction in estimated

  8. 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).

  9. Agricultural land use mapping. [Pennsylvania, Montana, and Texas

    NASA Technical Reports Server (NTRS)

    Mcmurtry, G. J.; Petersen, G. W. (Principal Investigator); Wilson, A. D.

    1973-01-01

    The author has identified the following significant results. Agricultural areas were selected or analysis in southeastern Pennsylvania, north central Montana, and southern Texas. These three sites represent a broad range of soils, soil parent materials, climate, modes of agricultural operation, crops, and field sizes. In each of these three sites, ERTS-1 digital data were processed to determine the feasibility of automatically mapping agricultural land use. In Pennsylvania, forest land, cultivated land, and water were separable within a 25,000 acre area. Four classes of water were also classified and identified, using ground truth. A less complex land use pattern was analyzed in Hill County, Montana. A land use map was prepared shown alternating patterns of summer fallow and stubble fields. The location of farmsteads could be inferred, along with that of a railroad line. A river and a creek flowing into the river were discernible. Six categories of water, related to sediment content and depth, were defined in the reservoir held by the Fresno dam. These classifications were completed on a 150 square mile area. Analysis of the data from Texas is in its formative stages. A test site has been selected and a brightness map has been produced.

  10. A proposed periodic national inventory of land use land cover change

    Treesearch

    Hans T. Schreuder; Paul W. Snook; Raymond L. Czaplewski; Glenn P. Catts

    1986-01-01

    Three alternatives using digital thematic mapper (TM), analog TM, and a combination of either digital or analog TM data with low altitude photography are discussed for level I and level II land use/land cover classes for a proposed national inventory. Digital TM data should prove satisfactory for estimating acreage in level I classes, although estimates of precision...

  11. Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA

    USGS Publications Warehouse

    Stapanian, Martin A.; Gara, Brian; Schumacher, William

    2018-01-01

    The loss of wetland habitats and their often-unique biological communities is a major environmental concern. We examined vegetation data obtained from 380 wetlands sampled in a statistical survey of wetlands in the USA. Our goal was to identify which surrounding land cover types best predict two indices of vegetation quality in wetlands at the regional scale. We considered palustrine wetlands in four regions (Coastal Plains, North Central East, Interior Plains, and West) in which the dominant vegetation was emergent, forested, or scrub-shrub. For each wetland, we calculated weighted proportions of eight land cover types surrounding the area in which vegetation was assessed, in four zones radiating from the edge of the assessment area to 2 km. Using Akaike's Information Criterion, we determined the best 1-, 2- and 3-predictor models of the two indices, using the weighted proportions of the land cover types as potential predictors. Mean values of the two indices were generally higher in the North Central East and Coastal Plains than the other regions for forested and emergent wetlands. In nearly all cases, the best predictors of the indices were not the dominant surrounding land cover types. Overall, proportions of forest (positive effect) and agriculture (negative effect) surrounding the assessment area were the best predictors of the two indices. One or both of these variables were included as predictors in 65 of the 72 models supported by the data. Wetlands surrounding the assessment area had a positive effect on the indices, and ranked third (33%) among the predictors included in supported models. Development had a negative effect on the indices and was included in only 28% of supported models. These results can be used to develop regional management plans for wetlands, such as creating forest buffers around wetlands, or to conserve zones between wetlands to increase habitat connectivity.

  12. 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

  13. SCALING-UP INFORMATION IN LAND-COVER DATA FOR LARGE-SCALE ENVIRONMENTAL ASSESSMENTS

    EPA Science Inventory

    The NLCD project provides national-scope land-cover data for the conterminous United States. The first land-cover data set was completed in 2000, and the continuing need for recent land-cover information has motivated continuation of the project to provide current and change info...

  14. Regional land cover characterization using Landsat thematic mapper data and ancillary data sources

    USGS Publications Warehouse

    Vogelmann, James E.; Sohl, Terry L.; Campbell, P.V.; Shaw, D.M.; ,

    1998-01-01

    As part of the activities of the Multi-Resolution Land Characteristics (MRLC) Interagency Consortium, an intermediate-scale land cover data set is being generated for the conterminous United States. This effort is being conducted on a region-by-region basis using U.S. Standard Federal Regions. To date, land cover data sets have been generated for Federal Regions 3 (Pennsylvania, West Virginia, Virginia, Maryland, and Delaware) and 2 (New York and New Jersey). Classification work is currently under way in Federal Region 4 (the southeastern United States), and land cover mapping activities have been started in Federal Regions 5 (the Great Lakes region) and 1 (New England). It is anticipated that a land cover data set for the conterminous United States will be completed by the end of 1999. A standard land cover classification legend is used, which is analogous to and compatible with other classification schemes. The primary MRLC regional classification scheme contains 23 land cover classes.The primary source of data for the project is the Landsat thematic mapper (TM) sensor. For each region, TM scenes representing both leaf-on and leaf-off conditions are acquired, preprocessed, and georeferenced to MRLC specifications. Mosaicked data are clustered using unsupervised classification, and individual clusters are labeled using aerial photographs. Individual clusters that represent more than one land cover unit are split using spatial modeling with multiple ancillary spatial data layers (most notably, digital elevation model, population, land use and land cover, and wetlands information). This approach yields regional land cover information suitable for a wide array of applications, including landscape metric analyses, land management, land cover change studies, and nutrient and pesticide runoff modeling.

  15. Comparing Minnesota land cover/use area estimates using NRI and FIA data

    Treesearch

    Veronica C. Lessard; Mark H. Hansen; Mark D. Nelson

    2002-01-01

    Areas for land cover/use categories on non-Federal land in Minnesota were estimated from Forest Inventory and Analysis (FIA) data and National Resources Inventory (NRI) data. Six common land cover/use categories were defined, and the NRI and FIA land cover/use categories were assigned to them. Area estimates for these categories were calculated from the FIA and NRI...

  16. Land use and land cover change in the North Central Appalachians ecoregion

    USGS Publications Warehouse

    Napton, D.E.; Sohl, Terry L.; Auch, Roger F.; Loveland, Thomas R.

    2003-01-01

    The North Central Appalachians ecoregion, spanning northern Pennsylvania and southern New York, has a long history of land use and land cover change. Turn-of-the-century logging dramatically altered the natural landscape of the ecoregion, but subsequent regeneration returned the ecoregion to a forest dominated condition. To understand contemporary land use and land cover changes, the U.S. Geological Survey with NASA and the U.S. Environmental Protection Agency used a random sample of satellite remotely sensed data for 1973, 1980, 1986, 1992, and 2000 to estimate the rates and assess the primary drivers of change in the North Central Appalachians. The overall change was 6.2%. The 1973-1980 period had the lowest rate of change (1.5%); the highest rate (2.9%) occurred during the 1992-2000 period. The primary conversions were deforestation through harvesting and natural disturbance (i.e., tornados) followed by regeneration, and conversion of forests to mining and urban lands. The primary drivers of the change included changes in access, energy and forest prices, and attitudes toward the environment.

  17. THEMATIC ACCURACY OF MRLC LAND COVER FOR THE EASTERN UNITED STATES

    EPA Science Inventory



    One objective of the MultiResolution Land Characteristics (MRLC) consortium is to map general land-cover categories for the conterminous United States using Landsat Thematic Mapper (TM) data. Land-cover mapping and classification accuracy assessment are complete for the e...

  18. Land-Cover Change Within the Peatlands Along the Rocky Mountain Front, Montana: 1937-2009

    NASA Astrophysics Data System (ADS)

    Klene, A. E.; Milbrath, J. T.; Shelly, J. S.

    2013-12-01

    While peatlands are globally abundant, the fens of the Rocky Mountain Front (RMF), are the eastern-most, rich, peatlands in Montana, and are unique wetland habitats in this region of semi-arid continental climate. The peatlands provide critical riparian connectivity between the mountains and the plains and are habitat for grizzly bears, wolves, and within just the 450 ha Pine Butte Fen at least 93 species of vascular plants, including seven of Montana's Plant Species of Concern. Aerial photographs of the nine peatlands along the RMF in Montana were analyzed in a GIS. The boundary of each wetland was hand-digitized and the area within was classified into land-cover types: total area, open fen, open water, woody vegetation, and non-wetland/agriculture. Changes in wetland extent and land-cover categories were evaluated from the earliest available imagery in 1937 to the last available imagery in 2009. Images prior to 1995 were orthorectified, and all georectified. Climate change, wildlife, and agriculture were examined as potential drivers of land-cover change at these sites. Results indicate little change in overall peatland area between 1937 and 2009 despite increasing air temperatures in the region. Approximately 16% of these peatlands is 'open fen' and that proportion remained stable over the last seventy years. Area of open water quadrupled and the number of ponds which could be delineated tripled over the study period, reflecting a recovering beaver population. The non-wetland/agricultural area halved over the course of the study, primarily due to declines in agriculture within the three largest remaining peatlands: Pine Butte Fen, McDonald Swamp, and the Blackleaf Creek wetland complex. Most of the first two fens were purchased outright by the Nature Conservancy (TNC) and they hold a conservation easement on the third (as well as two other fens), all of which have been been put in place since the late 1970s. One fen is owned by the State of Montana and another

  19. Carbon dynamics on agricultural land reverting to woody land in Ontario, Canada.

    PubMed

    Voicu, Mihai F; Shaw, Cindy; Kurz, Werner A; Huffman, Ted; Liu, Jiangui; Fellows, Max

    2017-05-15

    The 2015 Paris Agreement reinforces the importance of the land sector and its contribution to greenhouse gas (GHG) reductions. Thus, there is growing interest in improving estimates of the GHG balance in response to land-use changes (LUCs) involving agriculture and forestry, for national-scale reporting, and for carbon (C) offsets. Large agricultural areas in Europe, Russia and North America are reverting to forest, either naturally or through planting, after abandonment of agricultural land, and this trend may have a substantial impact on carbon budgets. We report results of a pilot project in the Mixedwood Plains ecozone of eastern Canada to analyze the change in the C budget on a landscape over 15 years on abandoned cropland where woody vegetation is regenerating. Thirty-six plots (2 km × 2 km) with paired aerial photographs taken circa 1994 and circa 2008 at a scale of 1:10,000 or larger were randomly selected from the 20 km × 20 km National Forest Inventory (NFI) grid. A spatially-explicit version of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) was used to estimate impacts of LUC on C stocks and fluxes. Polygons identifying areas of LUC within each photo plot were delineated, classified, and evaluated to provide input data for the model. The rate of C accumulation in our study area was found to be relatively constant over the entire simulation period, at 1.07 Mg C/ha/yr. Abandoned agricultural land reverting to woody lands could play an important role in regional and national C sequestration in Canada, but more research is required to quantify the areal extent of this LUC. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

  20. Global forest cover mapping for the United Nations Food and Agriculture Organization forest resources assessment 2000 program

    USGS Publications Warehouse

    Zhu, Z.; Waller, E.

    2003-01-01

    Many countries periodically produce national reports on the status and changes of forest resources, using statistical surveys and spatial mapping of remotely sensed data. At the global level, the Food and Agriculture Organization (FAO) of the United Nations has conducted a Forest Resources Assessment (FRA) program every 10 yr since 1980, producing statistics and analysis that give a global synopsis of forest resources in the world. For the year 2000 of the FRA program (FRA2000), a global forest cover map was produced to provide spatial context to the extensive survey. The forest cover map, produced at the U.S. Geological Survey (USGS) EROS Data Center (EDC), has five classes: closed forest, open or fragmented forest, other wooded land, other land cover, and water. The first two forested classes at the global scale were delineated using combinations of temporal compositing, modified mixture analysis, geographic stratification, and other classification techniques. The remaining three FAO classes were derived primarily from the USGS global land cover characteristics database (Loveland et al. 1999). Validated on the basis of existing reference data sets, the map is estimated to be 77% accurate for the first four classes (no reference data were available for water), and 86% accurate for the forest and nonforest classification. The final map will be published as an insert to the FAO FRA2000 report.

  1. 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.

  2. Quality Evaluation of Land-Cover Classification Using Convolutional Neural Network

    NASA Astrophysics Data System (ADS)

    Dang, Y.; Zhang, J.; Zhao, Y.; Luo, F.; Ma, W.; Yu, F.

    2018-04-01

    Land-cover classification is one of the most important products of earth observation, which focuses mainly on profiling the physical characters of the land surface with temporal and distribution attributes and contains the information of both natural and man-made coverage elements, such as vegetation, soil, glaciers, rivers, lakes, marsh wetlands and various man-made structures. In recent years, the amount of high-resolution remote sensing data has increased sharply. Accordingly, the volume of land-cover classification products increases, as well as the need to evaluate such frequently updated products that is a big challenge. Conventionally, the automatic quality evaluation of land-cover classification is made through pixel-based classifying algorithms, which lead to a much trickier task and consequently hard to keep peace with the required updating frequency. In this paper, we propose a novel quality evaluation approach for evaluating the land-cover classification by a scene classification method Convolutional Neural Network (CNN) model. By learning from remote sensing data, those randomly generated kernels that serve as filter matrixes evolved to some operators that has similar functions to man-crafted operators, like Sobel operator or Canny operator, and there are other kernels learned by the CNN model that are much more complex and can't be understood as existing filters. The method using CNN approach as the core algorithm serves quality-evaluation tasks well since it calculates a bunch of outputs which directly represent the image's membership grade to certain classes. An automatic quality evaluation approach for the land-cover DLG-DOM coupling data (DLG for Digital Line Graphic, DOM for Digital Orthophoto Map) will be introduced in this paper. The CNN model as an robustness method for image evaluation, then brought out the idea of an automatic quality evaluation approach for land-cover classification. Based on this experiment, new ideas of quality evaluation

  3. 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...

  4. MODIS-derived atmospheric water vapor (AWV) content and its correlation to land use and land cover in Northeast China

    NASA Astrophysics Data System (ADS)

    Song, Kaishan; Wu, Junjie; Li, Lin; Wang, Zongming; Lu, Dongmei; Du, Jia; Zhang, Bai

    2010-08-01

    Atmospheric water vapor (AWV) content is closely related to precipitation that in turn has effects on the productivity of agricultural, forestry and range land. MODIS images have been used for AWV retrieval, and the method uses either two (0.841-0.876 μm and 0.915-0.965 μm) or three (0.841-0.876, 0.915-0.965 and 1.230-0-1.250 μm) MODIS channel ratios. We applied both methods to the MODIS data over Northeast China acquired from June to August, 2008 to retrieve AWV content, and the results were validated on ground observed data from 10 radio sonde stations characterized by various land cover. The bulk results indicate that the two-channel ratio outperformed the three-channel ratio based on the coefficient of determination R2 = 0.81 vs. 0.78. The validation results for individual land cover types also support this observation with R2 = 0.92 vs. 0.84 for woodland, 0.82 vs. 0.79 for cropland, 0.90 vs. 0.86 for grassland and 0.673 vs. 0.669 for urban areas. The spatial distribution of AWV derived using the two-channel ratio method was correlated to land-use classification data, and a high correlation was evident when other conditions were similar. With the exception of dry cropland, the amount of average water vapor content over different land use types demonstrates a consistent order: water-body > paddy-field > woodland > grassland > barren for the analyzed multi-temporal MODIS data. This order partially matches the evapotranspiration pattern of underlying surface, and future work is required for analyzing the association of the landscape pattern with AWV in the region.

  5. Holocene Changes in Land Cover and Greenhouse-gas Concentrations: Rethinking Natural vs Anthropogenic Causation

    NASA Astrophysics Data System (ADS)

    Roberts, C.

    2008-12-01

    The Holocene has witnessed a switch from a nature-dominated to a human-dominated Earth system. Although globally-significant human impacts (wildfire, megafaunal extinctions) occurred during the late Pleistocene, it was the advent of agriculture that led to the progressive transformation of land cover, and which distinguishes the Holocene from previous interglacial periods. A wide array of data provide clear evidence of local-to-regional human disturbance from ~5 ka BP, in some cases earlier. There is more uncertainty about when the anthropogenic "footprint" became detectable at a global scale, and there has consequently been debate about how much of the pre-industrial increase in atmospheric greenhouse gas concentrations is attributable to human causation, linked to processes such as deforestation (CO2) and wet rice cultivation (CH4). Although there has been recent progress in developing quantitative methods for translating pollen data into palaeo-land cover, such as the REVEALS model of Sugita (Holocene 2007) coupled to GIS, this has yet to be widely applied to existing data bases, and most pollen-based land-use reconstructions remain qualitative or semi-quantitative. Lake trophic status, sediment flux / soil erosion, and microcharcoal records of biomass burning provide alternative proxies that integrate regional-scale landscape disturbance. These proxy data along with documentary sources imply that globally-significant changes in land cover occurred prior to ~250 BP which must have altered atmospheric greenhouse gas concentrations by this time. The polarised debate for and against early anthropogenic impact on global carbon cycling mirrors our industrial-era division between nature and society, both conceptually (e.g. Cartesian dualism) and on the ground (e.g. demarcating land between monoculture agriculture and wilderness). However, for the period before ~1750 AD, this likely represents a false dichotomy, because pre-industrial societies more often formed part

  6. 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.

  7. A small-scale land-sparing approach to conserving biological diversity in tropical agricultural landscapes

    Treesearch

    Richard B. Chandler; David I. King; Raul Raudales; Richard Trubey; Carlin Chandler; Víctor Julio Arce Chávez

    2013-01-01

    Two contrasting strategies have been proposed for conserving biological diversity while meeting the increasing demand for agricultural products: land sparing and land sharing production systems. Land sparing involves increasing yield to reduce the amount of land needed for agriculture, whereas land-sharing agricultural practices incorporate elements of native...

  8. 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

  9. Factors Influencing Farmers' Expectations to Sell Agricultural Land for Non-Agricultural Uses

    ERIC Educational Resources Information Center

    Zollinger, Brett; Krannich, Richard S.

    2002-01-01

    In this study we identify factors that influence farmers' expectations to sell some or all of their farming operation in areas where the increase in the conversion of agricultural land has been relatively rapid. Findings indicate that the following factors increase farmers' propensity to sell some or all of the agricultural operation for…

  10. The Use of Thematic Mapper Data for Land Cover Discrimination: Preliminary Results from the UK Satmap Programme

    NASA Technical Reports Server (NTRS)

    Jackson, M. J.; Baker, J. R.; Townshend, J. R. G.; Gayler, J. E.; Hardy, J. R.

    1984-01-01

    In assessing the accuracy of classification techniques for Thematic Mapper data the consistency of the detector-to-detector response is critical. Preliminary studies were undertaken, therefore, to assess the significance of this factor for the TM. The overall structure of the band relationships can be examined by principal component analysis. In order to examine the utility of the Thematic Mapper data more carefully, six different land cover classes approximately Anderson level 1 were selected. These included an area of water from the sediment-laden Mississippi, woodland, agricultural land and urban land. A plume class was also selected which includes the plume of smoke emanating from the power station and drifting over the Mississippi river.

  11. Sensitivity of June near‐surface temperatures and precipitation in the eastern United States to historical land cover changes since European settlement

    USGS Publications Warehouse

    Strack, John E.; Pielke, Roger A.; Steyaert, Louis T.; Knox, Robert G.

    2008-01-01

    Land cover changes alter the near surface weather and climate. Changes in land surface properties such as albedo, roughness length, stomatal resistance, and leaf area index alter the surface energy balance, leading to differences in near surface temperatures. This study utilized a newly developed land cover data set for the eastern United States to examine the influence of historical land cover change on June temperatures and precipitation. The new data set contains representations of the land cover and associated biophysical parameters for 1650, 1850, 1920, and 1992, capturing the clearing of the forest and the expansion of agriculture over the eastern United States from 1650 to the early twentieth century and the subsequent forest regrowth. The data set also includes the inferred distribution of potentially water‐saturated soils at each time slice for use in the sensitivity tests. The Regional Atmospheric Modeling System, equipped with the Land Ecosystem‐Atmosphere Feedback (LEAF‐2) land surface parameterization, was used to simulate the weather of June 1996 using the 1992, 1920, 1850, and 1650 land cover representations. The results suggest that changes in surface roughness and stomatal resistance have caused present‐day maximum and minimum temperatures in the eastern United States to warm by about 0.3°C and 0.4°C, respectively, when compared to values in 1650. In contrast, the maximum temperatures have remained about the same, while the minimums have cooled by about 0.1°C when compared to 1920. Little change in precipitation was found.

  12. 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

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

    NASA Astrophysics Data System (ADS)

    Karakacan Kuzucu, A.; Bektas Balcik, F.

    2017-11-01

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

  14. Land-Sparing Opportunities for Solar Energy Development in Agricultural Landscapes: A Case Study of the Great Central Valley, CA, United States.

    PubMed

    Hoffacker, Madison K; Allen, Michael F; Hernandez, Rebecca R

    2017-12-19

    Land-cover change from energy development, including solar energy, presents trade-offs for land used for the production of food and the conservation of ecosystems. Solar energy plays a critical role in contributing to the alternative energy mix to mitigate climate change and meet policy milestones; however, the extent that solar energy development on nonconventional surfaces can mitigate land scarcity is understudied. Here, we evaluate the land sparing potential of solar energy development across four nonconventional land-cover types: the built environment, salt-affected land, contaminated land, and water reservoirs (as floatovoltaics), within the Great Central Valley (CV, CA), a globally significant agricultural region where land for food production, urban development, and conservation collide. Furthermore, we calculate the technical potential (TWh year -1 ) of these land sparing sites and test the degree to which projected electricity needs for the state of California can be met therein. In total, the CV encompasses 15% of CA, 8415 km 2 of which was identified as potentially land-sparing for solar energy development. These areas comprise a capacity-based energy potential of at least 17 348 TWh year -1 for photovoltaic (PV) and 2213 TWh year -1 for concentrating solar power (CSP). Accounting for technology efficiencies, this exceeds California's 2025 projected electricity demands up to 13 and 2 times for PV and CSP, respectively. Our study underscores the potential of strategic renewable energy siting to mitigate environmental trade-offs typically coupled with energy sprawl in agricultural landscapes.

  15. Simulation of Land-Cover Change in Taipei Metropolitan Area under Climate Change Impact

    NASA Astrophysics Data System (ADS)

    Huang, Kuo-Ching; Huang, Thomas C. C.

    2014-02-01

    Climate change causes environment change and shows up on land covers. Through observing the change of land use, researchers can find out the trend and potential mechanism of the land cover change. Effective adaptation policies can affect pattern of land cover change and may decrease the risks of climate change impacts. By simulating land use dynamics with scenario settings, this paper attempts to explore the relationship between climate change and land-cover change through efficient adaptation polices. It involves spatial statistical model in estimating possibility of land-cover change, cellular automata model in modeling land-cover dynamics, and scenario analysis in response to adaptation polices. The results show that, without any control, the critical eco-areas, such as estuarine areas, will be destroyed and people may move to the vulnerable and important economic development areas. In the other hand, under the limited development condition for adaptation, people migration to peri-urban and critical eco-areas may be deterred.

  16. EnviroAtlas One Meter Resolution Urban Land Cover Data (2008-2012) Web Service

    EPA Pesticide Factsheets

    This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas ). The EnviroAtlas One Meter-scale Urban Land Cover (MULC) Data were generated individually for each EnviroAtlas community. Source imagery varies by community. Land cover classes mapped also vary by community and include the following: water, impervious surfaces, soil and barren land, trees, shrub, grass and herbaceous, agriculture, orchards, woody wetlands, and emergent wetlands. Accuracy assessments were completed for each community's classification. For specific information about methods and accuracy of each community's land cover classification, consult their individual metadata records: Austin, TX (https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B91A32A9D-96F5-4FA0-BC97-73BAD5D1F158%7D); Cleveland, OH (https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B82ab1edf-8fc8-4667-9c52-5a5acffffa34%7D); Des Moines, IA (https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BA4152198-978D-4C0B-959F-42EABA9C4E1B%7D); Durham, NC (https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B2FF66877-A037-4693-9718-D1870AA3F084%7D); Fresno, CA (https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B87041CF3-05BC-43C3-82DA-F066267C9871%7D); Green Bay, WI (https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BD602E7C9-7F53-4C24

  17. 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), ...

  18. Stormwater dissolved organic matter: influence of land cover and environmental factors.

    PubMed

    McElmurry, Shawn P; Long, David T; Voice, Thomas C

    2014-01-01

    Dissolved organic matter (DOM) plays a major role in defining biological systems and it influences the fate and transport of many pollutants. Despite the importance of DOM, understanding of how environmental and anthropogenic factors influence its composition and characteristics is limited. This study focuses on DOM exported as stormwater from suburban and urban sources. Runoff was collected before entering surface waters and DOM was characterized using specific ultraviolet absorbance at 280 nm (a proxy for aromaticity), molecular weight, polydispersity and the fraction of DOM removed from solution via hydrophobic and H-bonding mechanisms. General linear models (GLMs) incorporating land cover, precipitation, solar radiation and selected aqueous chemical measurements explained variations in DOM properties. Results show (1) molecular characteristics of DOM differ as a function of land cover, (2) DOM produced by forested land is significantly different from other landscapes, particularly urban and suburban areas, and (3) DOM from land cover that contains paved surfaces and sewers is more hydrophobic than from other types of land cover. GLMs incorporating environmental factors and land cover accounted for up to 86% of the variability observed in DOM characteristics. Significant variables (p < 0.05) included solar radiation, water temperature and water conductivity.

  19. The Land Use and Land Cover Dichotomy: A Comparison of Two Land Classification Systems in Support of Urban Earth Science Applications

    NASA Technical Reports Server (NTRS)

    McAllister, William K.

    2003-01-01

    One is likely to read the terms 'land use' and 'land cover' in the same sentence, yet these concepts have different origins and different applications. Land cover is typically analyzed by earth scientists working with remotely sensed images. Land use is typically studied by urban planners who must prescribe solutions that could prevent future problems. This apparent dichotomy has led to different classification systems for land-based data. The works of earth scientists and urban planning practitioners are beginning to come together in the field of spatial analysis and in their common use of new spatial analysis technology. In this context, the technology can stimulate a common 'language' that allows a broader sharing of ideas. The increasing amount of land use and land cover change challenges the various efforts to classify in ways that are efficient, effective, and agreeable to all groups of users. If land cover and land uses can be identified by remote methods using aerial photography and satellites, then these ways are more efficient than field surveys of the same area. New technology, such as high-resolution satellite sensors, and new methods, such as more refined algorithms for image interpretation, are providing refined data to better identify the actual cover and apparent use of land, thus effectiveness is improved. However, the closer together and the more vertical the land uses are, the more difficult the task of identification is, and the greater is the need to supplement remotely sensed data with field study (in situ). Thus, a number of land classification methods were developed in order to organize the greatly expanding volume of data on land characteristics in ways useful to different groups. This paper distinguishes two land based classification systems, one developed primarily for remotely sensed data, and the other, a more comprehensive system requiring in situ collection methods. The intent is to look at how the two systems developed and how they

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

    NASA Astrophysics Data System (ADS)

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

    2017-11-01

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