WorldWideScience

Sample records for current land cover

  1. Land Cover

    Data.gov (United States)

    Kansas Data Access and Support Center — The Land Cover database depicts 10 general land cover classes for the State of Kansas. The database was compiled from a digital classification of Landsat Thematic...

  2. Land Cover - Minnesota Land Cover Classification System

    Data.gov (United States)

    Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...

  3. Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

    Science.gov (United States)

    Prestele, Reinhard; Arneth, Almut; Bondeau, Alberte; de Noblet-Ducoudré, Nathalie; Pugh, Thomas A. M.; Sitch, Stephen; Stehfest, Elke; Verburg, Peter H.

    2017-05-01

    Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use-climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use-climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the

  4. Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

    Directory of Open Access Journals (Sweden)

    R. Prestele

    2017-05-01

    Full Text Available Land-use and land-cover change (LULCC represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs. The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC. Fully coupled models of climate, land use and biogeochemical cycles to explore land use–climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use–climate interaction studies: (I provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II accounting for sub-grid processes and bidirectional changes (gross changes across spatial scales, and (III the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest

  5. Gambia Land Use Land Cover

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This series of three-period land use land cover (LULC) datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is...

  6. Land Cover Characterization Program

    Science.gov (United States)

    ,

    1997-01-01

    The U.S. Geological Survey (USGS) has a long heritage of leadership and innovation in land use and land cover mapping. The USGS Anderson system defined the principles for land use and land cover mapping that have been the model both nationally and internationally for more than 20 years. The Land Cover Characterization Program (LCCP) is founded on the premise that the Nation's needs for land cover and land use data are diverse and increasingly sophisticated. The range of projects, programs, and organizations that use land cover data to meet their planning, management, development, and assessment objectives has expanded significantly. The reasons for this are numerous, and include the improved capabilities provided by geographic information systems, better and more data-intensive analytic models, and increasing requirements for improved information for decision making. The overall goals of the LCCP are to:

  7. Land Use and Land Cover - Montana Land Cover Framework 2013

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This statewide land cover theme is a baseline digital map of Montana's natural and human land cover. The baseline map is adapted from the Northwest ReGAP project...

  8. Land Cover Trends Project

    Science.gov (United States)

    Acevedo, William

    2006-01-01

    The Land Cover Trends Project is designed to document the types, rates, causes, and consequences of land cover change from 1973 to 2000 within each of the 84 U.S. Environmental Protection Agency (EPA) Level III ecoregions that span the conterminous United States. The project's objectives are to: * Develop a comprehensive methodology using probability sampling and change analysis techniques and Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper (ETM) data for estimating regional land cover change. * Characterize the spatial and temporal characteristics of conterminous U.S. land cover change for five periods from 1973 to 2000 (nominally 1973, 1980, 1986, 1992, and 2000). * Document the regional driving forces and consequences of change. * Prepare a national synthesis of land cover change.

  9. Projected 2020 Land Cover

    Data.gov (United States)

    U.S. Environmental Protection Agency — Projected 2020 land cover was developed to provide one scenario of development in the year 2020. It was used to generate several metrics to compare to 1992 metrics...

  10. CORINE Land Cover 2006

    DEFF Research Database (Denmark)

    Stjernholm, Michael

    "CORINE land cover" er en fælleseuropæisk kortlægning af arealanvendelse/arealdække. Arealanvendelse/arealdække er i Danmark kortlagt efter CORINE metode og klasseopdeling med satellitbilleder fra 3 forskellige tidsperioder, fra begyndelsen af 1990'erne (CLC90), fra år 2000 (CLC2000) og fra år 2006...

  11. CORINE Land Cover 2006

    DEFF Research Database (Denmark)

    Stjernholm, Michael

    "CORINE land cover" er en fælleseuropæisk kortlægning af arealanvendelse/arealdække. Arealanvendelse/arealdække er i Danmark kortlagt efter CORINE metode og klasseopdeling med satellitbilleder fra 3 forskellige tidsperioder, fra begyndelsen af 1990'erne (CLC90), fra år 2000 (CLC2000) og fra år 2006...

  12. Current and Historic Land Cover of Grand Bay - Banks Lake (GBBL) Ecosystem in Lanier and Lowndes County, Georgia

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This report summarizes efforts to map land cover and assess land cover cahnge from the early 1940's through 2004 witihn the Grand Bay-Banks Lake ecosystem.

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

    Science.gov (United States)

    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

  14. Allegheny County Land Cover Areas

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — The Land Cover dataset demarcates 14 land cover types by area; such as Residential, Commercial, Industrial, Forest, Agriculture, etc. If viewing this description on...

  15. Allegheny County Land Cover Areas

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — The Land Cover dataset demarcates 14 land cover types by area; such as Residential, Commercial, Industrial, Forest, Agriculture, etc. If viewing this description...

  16. Allegheny County Land Cover Areas

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — The Land Cover dataset demarcates 14 land cover types by area; such as Residential, Commercial, Industrial, Forest, Agriculture, etc. If viewing this description on...

  17. Capo Verde, Land Use Land Cover

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This series of three-period land use land cover (LULC) datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is...

  18. Assessing uncertainties in land cover projections.

    Science.gov (United States)

    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.

  19. GAP Land Cover - Image

    Data.gov (United States)

    Minnesota Department of Natural Resources — This raster dataset is a simple image of the original detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of...

  20. GAP Land Cover - Vector

    Data.gov (United States)

    Minnesota Department of Natural Resources — This vector dataset is a detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of combined two-season pairs of...

  1. The National Land Cover Database

    Science.gov (United States)

    Homer, Collin H.; 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.

  2. Land-cover change detection

    Science.gov (United States)

    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.

  3. The Analysis of Spot-5 Characteristics on land cover classification

    Institute of Scientific and Technical Information of China (English)

    徐开明

    2004-01-01

    Knowledge about land cover and land use has become increasingly important as the Nation plans to overcome the problems of uncontrolled development, deteriorating environmental quality, loss of prime agricultural lands etc. Land use and land cover data are needed in the analysis of environmental processes and problems to know if living conditions and standards are to be improved or maintained at current levels.

  4. The analysis of SPOT-5 characteristics on land cover classification

    Institute of Scientific and Technical Information of China (English)

    XUKai-ming

    2004-01-01

    Knowledge about land cover and land use has become increasingly important as the Nation plans to overeome the problems of uncontrolled development, deteriorating environmental quality, loss of prime agricultural lands etc. Land use and land cover data are needed in the analysis of environmental processes and problems to know if riving conditions and standards are to be improved or maintained at current levels.

  5. Holocene land-cover reconstructions for studies on land cover-climate feedbacks

    Directory of Open Access Journals (Sweden)

    M.-J. Gaillard

    2010-03-01

    Full Text Available The major objectives of this paper are: (1 to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC developed during the last ten years, (2 to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites, to infer long-term records of past land-cover from pollen data, (3 to present a new project (LANDCLIM: LAND cover – CLIMate interactions in NW Europe during the Holocene currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4 to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need of REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is proved to provide better estimates of the regional vegetation/land-cover changes than the traditional use of pollen percentages. Thus, the application of REVEALS opens up the possibility of achieving a more robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs at 200 BP and 6000 BP, and of the two open-land PFTs "grassland" and "agricultural land" at five time-windows from 6000 BP to recent time. The LANDCLIM results are

  6. Land Use and Land Cover, Current land use layer developed by Bay-Lake Regional Planning Commission as part of the County's 2009 Smart Growth Plan., Published in 2008, 1:2400 (1in=200ft) scale, Manitowoc County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of 2008. It is described as...

  7. Land use land cover change detection using remote sensing application for land sustainability

    Science.gov (United States)

    Balakeristanan, Maha Letchumy; Md Said, Md Azlin

    2012-09-01

    Land falls into the category of prime resources. Land use and land cover changes are identified as the prime issue in global environmental changes. Thus, it is necessary to initiate the land change detection process for land sustainability as well as to develop a competent land use planning. Tropical country like Malaysia has been experiencing land use and land cover changes rapidly for the past few decades. Thus, an attempt was made to detect the land use and land cover changes in the capital of the Selangor, Malaysia, Shah Alam over 20 years period (1990 - 2010). The study has been done through remote sensing approach using Earth Sat imagery of December 1990 and SPOT satellite imageries of March 2000 and December 2010. The current study resulted that the study area experienced land cover changes rapidly where the forest area occupied about 24.4% of Shah Alam in 1990 has decreased to 13.6% in 2010. Built up land have increased to 29.18% in 2010 from 12.47% in 1990. Other land cover classes such as wet land, wasteland and agricultural land also have undergone changes. Efficient land management and planning is necessary for land sustainability in Shah Alam.

  8. LandSat-Based Land Use-Land Cover (Raster)

    Data.gov (United States)

    Minnesota Department of Natural Resources — Raster-based land cover data set derived from 30 meter resolution Thematic Mapper satellite imagery. Classification is divided into 16 classes with source imagery...

  9. LandSat-Based Land Use-Land Cover (Vector)

    Data.gov (United States)

    Minnesota Department of Natural Resources — Vector-based land cover data set derived from classified 30 meter resolution Thematic Mapper satellite imagery. Classification is divided into 16 classes with source...

  10. National Land Cover Database: 1986-1993

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 92 (National Land Cover Dataset 1992) is a 21-category land cover classification scheme that has been applied consistently over the conterminous U.S. It is...

  11. 1990 Kansas Land Cover Patterns Update

    Data.gov (United States)

    Kansas Data Access and Support Center — In 2008, an update of the 1990 Kansas Land Cover Patterns (KLCP) database was undertaken. The 1990 KLCP database depicts 10 general land cover classes for the State...

  12. VT National Land Cover Dataset - 2001

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The NLCD2001 layer available from VCGI is a subset of the the National Land Cover Database 2001 land cover layer for mapping zone 65 was produced...

  13. National Land Cover Database: 1986-1993

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 92 (National Land Cover Dataset 1992) is a 21-category land cover classification scheme that has been applied consistently over the conterminous U.S. It is...

  14. National land-cover pattern data

    Science.gov (United States)

    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...

  15. 2014 land cover land use horseshoe bend

    Science.gov (United States)

    Hanson, Jenny L.; Hoy, Erin E.; Robinson, Larry R.

    2016-01-01

    This collection of conservation areas consists of the floodplain of the combined streams of the Iowa River and the Cedar River. The study area begins just southeast of Wapello, IA, and continues southeast until the Horseshoe Bend Division, Port Louisa NWR. The area is currently managed to maintain meadow or grassland habitat which requires intensive management due to vegetative succession. In addition, this floodplain area contains a high proportion of managed lands and private lands in the Wetland Reserve Program and is a high priority area for cooperative conservation actions. This project provides a late-summer baseline vegetation inventory to assess future management actions in an adaptive process. Changes in levees, in addition to increased water flows and flood events due to climate change and land use practices, make restoration of floodplain processes more complex. Predictive models could help determine more efficient and effective restoration and management techniques. Successful GIS tools developed for this project would be applicable to other floodplain refuges and conservation areas.

  16. West Africa land use and land cover time series

    Science.gov (United States)

    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.

  17. National Land Cover Database 2001 (NLCD01)

    Science.gov (United States)

    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.

  18. Validation of Land Cover Products Using Reliability Evaluation Methods

    Directory of Open Access Journals (Sweden)

    Wenzhong Shi

    2015-06-01

    Full Text Available Validation of land cover products is a fundamental task prior to data applications. Current validation schemes and methods are, however, suited only for assessing classification accuracy and disregard the reliability of land cover products. The reliability evaluation of land cover products should be undertaken to provide reliable land cover information. In addition, the lack of high-quality reference data often constrains validation and affects the reliability results of land cover products. This study proposes a validation schema to evaluate the reliability of land cover products, including two methods, namely, result reliability evaluation and process reliability evaluation. Result reliability evaluation computes the reliability of land cover products using seven reliability indicators. Process reliability evaluation analyzes the reliability propagation in the data production process to obtain the reliability of land cover products. Fuzzy fault tree analysis is introduced and improved in the reliability analysis of a data production process. Research results show that the proposed reliability evaluation scheme is reasonable and can be applied to validate land cover products. Through the analysis of the seven indicators of result reliability evaluation, more information on land cover can be obtained for strategic decision-making and planning, compared with traditional accuracy assessment methods. Process reliability evaluation without the need for reference data can facilitate the validation and reflect the change trends of reliabilities to some extent.

  19. Land Use and Land Cover - MO 2015 Meramec Land Cover (GDB)

    Data.gov (United States)

    NSGIC State | GIS Inventory — MoRAP produced and integrated data to map land cover and wetlands for the Meramec River bottomland in Missouri. LiDAR elevation and vegetation height information and...

  20. Land Use and Land Cover - MO 2015 Silver Land Cover (GDB)

    Data.gov (United States)

    NSGIC State | GIS Inventory — MoRAP produced and integrated data to map land cover and wetlands for the Upper Silver Creek Watershed in Illinois. LiDAR elevation and vegetation height information...

  1. International Coalition Land Use/Land Cover

    Data.gov (United States)

    Minnesota Department of Natural Resources — This data set is a product of an effort to update Minnesota's 1969 land use inventory. The project was funded in 1989 by the State Legislature per recommendation...

  2. EASE-Grid Land Cover Classifications Derived from Boston University MODIS/Terra Land Cover Data

    Data.gov (United States)

    National Aeronautics and Space Administration — These data provide land cover classifications derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The data are...

  3. Land Use and Land Cover - LAND_COVER_2006_USGS_IN: Land Cover in Indiana, Derived from the 2006 National Land Cover Database (United States Geological Survey, 30-Meter TIFF Image)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — LAND_COVER_2006_USGS_IN is a grid (30-meter cell size) showing 2006 Land Cover data in Indiana. This grid is a subset of the National Land Cover Data (NLCD 2006)...

  4. The Land Surface Temperature Impact to Land Cover Types

    Science.gov (United States)

    Ibrahim, I.; Abu Samah, A.; Fauzi, R.; Noor, N. M.

    2016-06-01

    Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R2 = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

  5. GAP Land Cover - Tiled Raster

    Data.gov (United States)

    Minnesota Department of Natural Resources — This raster dataset is a detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of combined two-season pairs of...

  6. The land-cover cascade: relationships coupling land and water

    Science.gov (United States)

    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...

  7. land use and cover change in pastoral systems of uganda

    African Journals Online (AJOL)

    ACSS

    current land use and cover changes have delineated mobility as a coping strategy to drought, contributed to degradation of ... to climate change. ... damage and woody encroachment affecting livestock ..... Total number of animals in district.

  8. EnviroAtlas - Land Cover for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset represents the percentage of land area that is classified as forest land cover, modified forest land cover, and natural land cover using the 2006...

  9. West Africa Land Use Land Cover Time Series

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This series of three-period land use land cover (LULC) datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is...

  10. Simulating feedbacks in land use and land cover change models

    NARCIS (Netherlands)

    Verburg, P.H.

    2006-01-01

    In spite of the many advances in land use and land cover change modelling over the past decade many challenges remain. One of these challenges relates to the explicit treatment of feedback mechanisms in descriptive models of the land use system. This paper argues for model-based analysis to explore

  11. Global Land Cover Characterization: 1992-1993

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey (USGS) has a long history of involvement in multi-scale, and multi-temporal land cover characterization and mapping of the world. During...

  12. C-CAP Niihau 2005 Land Cover

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land cover derived from high resolution imagery according to the Coastal Change Analysis Program (C-CAP) protocol. This data set utilized 1...

  13. Changes in historical Iowa land cover as context for assessing the environmental benefits of current and future conservation efforts on agricultural lands

    Science.gov (United States)

    Gallant, Alisa L.; Sadinski, Walt; Roth, Mark F.; Rewa, Charles A.

    2011-01-01

    Conservationists and agriculturists face unprecedented challenges trying to minimize tradeoffs between increasing demands for food, fiber, feed, and biofuels and the resulting loss or reduced values of other ecosystem services, such as those derived from wetlands and biodiversity (Millenium Ecosystem Assessment 2005a, 2005c; Maresch et al. 2008). The Food, Conservation, and Energy Act of 2008 (Pub. L. 110-234, Stat. 923, HR 2419, also known as the 2008 Farm Bill) reauthorized the USDA to provide financial incentives for agricultural producers to reduce environmental impacts via multiple conservation programs. Two prominent programs, the Wetlands Reserve Program (WRP) and the Conservation Reserve Program (CRP), provide incentives for producers to retire environmentally sensitive croplands, minimize erosion, improve water quality, restore wetlands, and provide wildlife habitat (USDA FSA 2008a, 2008b; USDA NRCS 2002). Other conservation programs (e.g., Environmental Quality Incentives Program, Conservation Stewardship Program) provide incentives to implement structural and cultural conservation practices to improve the environmental performance of working agricultural lands. Through its Conservation Effects Assessment Project, USDA is supporting evaluation of the environmental benefits obtained from the public investment in conservation programs and practices to inform decisions on where further investments are warranted (Duriancik et al. 2008; Zinn 1997).

  14. 2000 UMRS Land Cover Land Use--Pool 11

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  15. 2000 UMRS Land Cover Land Use--Pool 22

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  16. 2000 UMRS Land Cover Land Use--Pool 2

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  17. 1994 UMRS Land Cover Land Use--Pool 7

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) has created high-resolution land cover/use data sets for selected areas in the Upper...

  18. 1994 UMRS Land Cover Land Use--Pool 26

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) has created high-resolution land cover/use data sets for selected areas in the Upper...

  19. 1994 UMRS Land Cover Land Use--Pool 8

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) has created high-resolution land cover/use data sets for selected areas in the Upper...

  20. 2000 UMRS Land Cover Land Use--Pool 8

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the...

  1. 2000 UMRS Land Cover Land Use--Open River 2

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  2. 2000 UMRS Land Cover Land Use--Open River 1

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  3. 2000 UMRS Land Cover Land Use--Pool 9

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  4. 2000 UMRS Land Cover Land Use--Pool 1

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  5. 2000 UMRS Land Cover Land Use--Pool 7

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  6. 2000 UMRS Land Cover Land Use--Pool 25

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) is in the process of creating high-resolution land cover/use data sets for the Upper...

  7. Impacts of Land Cover Changes on Climate over China

    Science.gov (United States)

    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.

  8. 1997 Land Cover/Land Use Agassiz National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The land cover/land use database was developed from color infrared aerial photography flown on August 26, 1997 at a scale of 1:15,840. Photographs were flown with...

  9. From land cover change to land function dynamics: A major challenge to improve land characterization

    NARCIS (Netherlands)

    Verburg, P.H.; Steeg, van de J.; Veldkamp, A.; Willemen, L.

    2009-01-01

    Land cover change has always had a central role in land change science. This central role is largely the result of the possibilities to map and characterize land cover based on observations and remote sensing. This paper argues that more attention should be given to land use and land functions and l

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

    Science.gov (United States)

    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.

  11. Spatial Scaling of Land Cover Networks

    CERN Document Server

    Small, Christopher

    2015-01-01

    Spatial networks of land cover are well-described by power law rank-size distributions. Continuous field proxies for human settlements, agriculture and forest cover have similar spatial scaling properties spanning 4 to 5 orders of magnitude. Progressive segmentation of these continuous fields yields spatial networks with rank-size distributions having slopes near -1 for a wide range of thresholds. We consider a general explanation for this scaling that does not require different processes for each type of land cover. The same conditions that give rise to scale-free networks in general can produce power law distributions of component sizes for bounded spatial networks confined to a plane or surface. Progressive segmentation of a continuous field naturally results in growth of the network while the increasing perimeters of the growing components result in preferential attachment to the larger components with the longer perimeters. Progressive segmentation of two types of random continuous field results in progr...

  12. Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual

    Science.gov (United States)

    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).

  13. Land cover and water yield: inference problems when comparing catchments with mixed land cover

    Directory of Open Access Journals (Sweden)

    A. I. J. M. van Dijk

    2012-09-01

    Full Text Available Controlled experiments provide strong evidence that changing land cover (e.g. deforestation or afforestation can affect mean catchment streamflow (Q. By contrast, a similarly strong influence has not been found in studies that interpret Q from multiple catchments with mixed land cover. One possible reason is that there are methodological issues with the way in which the Budyko framework was used in the latter type studies. We examined this using Q data observed in 278 Australian catchments and by making inferences from synthetic Q data simulated by a hydrological process model (the Australian Water Resources Assessment system Landscape model. The previous contrasting findings could be reproduced. In the synthetic experiment, the land cover influence was still present but not accurately detected with the Budyko- framework. Likely sources of interpretation bias demonstrated include: (i noise in land cover, precipitation and Q data; (ii additional catchment climate characteristics more important than land cover; and (iii covariance between Q and catchment attributes. These methodological issues caution against the use of a Budyko framework to quantify a land cover influence in Q data from mixed land-cover catchments. Importantly, however, our findings do not rule out that there may also be physical processes that modify the influence of land cover in mixed land-cover catchments. Process model simulations suggested that lateral water redistribution between vegetation types and recirculation of intercepted rainfall may be important.

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

    Science.gov (United States)

    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

  15. Land cover change and soil fertility decline in tropical regions

    NARCIS (Netherlands)

    Hartemink, A.E.; Veldkamp, A.; Bai, Zhanguo

    2008-01-01

    Land cover changes influence the biogeochemistry, hydrology, and climate of the earth. Studies that assessed land cover changes at the global scale mostly focused on: deforestation, cropland expansion, dry land degradation, urbanisation, pasture expansion, and agricultural intensification. For the a

  16. Decadal land cover change dynamics in Bhutan.

    Science.gov (United States)

    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.

  17. Improving distributed hydrologic modeling and global land cover data

    Science.gov (United States)

    Broxton, Patrick

    -added Land Cover products (land cover type and maximum green vegetation fraction; MGVF) are developed and evaluated. The new products are good successors to current generation land cover products that are used in global models (many of which rely on 20 year old AVHRR land cover data from a single year) because they are based on 10 years of recent MODIS data. There is substantial spurious interannual variability in the MODIS land cover type data, and the MGVF product can vary substantially from year to year depending on climate conditions, suggesting the importance of using climatologies for land cover data. The new land cover type climatology also agrees better with validation sites, and the MGVF climatology is more consistent with other measures of vegetation (e.g. Leaf Area Index) than the older land cover data.

  18. National Land Cover Database 1992/2001 Retrofit Land Cover Change Product: 1999-2002

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 1992-2001 Retrofit Change Product What is the NLCD 1992/2001 Retrofit Land Cover Change Product? Although one of the guiding principles of the NLCD 2001 design...

  19. Extreme Learning Machine for land cover classification

    OpenAIRE

    Pal, Mahesh

    2008-01-01

    This paper explores the potential of extreme learning machine based supervised classification algorithm for land cover classification. In comparison to a backpropagation neural network, which requires setting of several user-defined parameters and may produce local minima, extreme learning machine require setting of one parameter and produce a unique solution. ETM+ multispectral data set (England) was used to judge the suitability of extreme learning machine for remote sensing classifications...

  20. Satellite Image Processing for Land Use and Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Ashoka Vanjare

    2014-09-01

    Full Text Available In this paper, urban growth of Bangalore region is analyzed and discussed by using multi-temporal and multi-spectral Landsat satellite images. Urban growth analysis helps in understanding the change detection of Bangalore region. The change detection is studied over a period of 39 years and the region of interest covers an area of 2182 km2. The main cause for urban growth is the increase in population. In India, rapid urbanization is witnessed due to an increase in the population, continuous development has affected the existence of natural resources. Therefore observing and monitoring the natural resources (land use plays an important role. To analyze changed detection, researcher’s use remote sensing data. Continuous use of remote sensing data helps researchers to analyze the change detection. The main objective of this study is to monitor land cover changes of Bangalore district which covers rural and urban regions using multi-temporal and multi-sensor Landsat - multi-spectral scanner (MSS, thematic mapper (TM, Enhanced Thematic mapper plus (ETM+ MSS, TM and ETM+ images captured in the years 1973, 1992, 1999, 2002, 2005, 2008 and 2011. Temporal changes were determined by using maximum likelihood classification method. The classification results contain four land cover classes namely, built-up, vegetation, water and barren land. The results indicate that the region is densely developed which has resulted in decrease of water and vegetation regions. The continuous transformation of barren land to built-up region has affected water and vegetation regions. Generally, from 1973 to 2011 the percentage of urban region has increased from 4.6% to 25.43%, mainly due to urbanization.

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

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

  3. Land Use and Land Cover - Volusia County Land Use 2000 (Polygons)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — Land cover and land use in the St. Johns River Water Management District based on 1999 and 2000 color infrared aerial photography. * Data in this layer may change...

  4. National Land Cover Database 2006: 2005-2007

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 2006 quantifies land cover and land cover change between the years 2001 to 2006 and provides an updated version of NLCD 2001. These products represent the...

  5. National Land Cover Database 2006: 2005-2007

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 2006 quantifies land cover and land cover change between the years 2001 to 2006 and provides an updated version of NLCD 2001. These products represent the first...

  6. National Land Cover Data for the National Wildlife Refuge System

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The Natural Resources Program Center conducted a land cover analysis to determine land cover types, acres and their subsequent percentages for the National Wildlife...

  7. National Land Cover Database 2006: 2005-2007

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 2006 quantifies land cover and land cover change between the years 2001 to 2006 and provides an updated version of NLCD 2001. These products represent the first...

  8. Enhanced National Land Cover Data 1992 (NLCDe 92)

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The enhanced National Land Cover Data 1992 ("NLCDe 92") served as the primary source for nationally consistent mapped land cover during the first decade of sampling...

  9. National Land Cover Data for the National Wildlife Refuge System

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The Natural Resources Program Center conducted a land cover analysis to determine land cover types, acres and their subsequent percentages for the National Wildlife...

  10. User's guide for Bristol Bay land cover maps

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The purpose of this Users Guide is to explain how to use the land cover maps and field data generated by the Bristol Bay Land Cover Mapping Project. The complete...

  11. Compilation and Assessment of Pan-European Land Cover Changes

    NARCIS (Netherlands)

    Hazeu, G.W.; Mucher, C.A.; Kramer, H.; Kienast, F.

    2008-01-01

    Land cover is changing in many parts of Europe at an increasing rate. The knowledge on these land cover changes is important for spatial planning, resource evaluation, ecological modelling etc. Modification of ecosystems is most visible through changing land cover. Furthermore, spatio-temporal

  12. EASE-Grid 2.0 Land Cover Classifications Derived from Boston University MODIS/Terra Land Cover Data

    Data.gov (United States)

    National Aeronautics and Space Administration — These data provide land cover classifications derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The data are...

  13. West Africa land use land cover time series

    Science.gov (United States)

    Tappan, G. Gray; Cushing, W. Matthew; Cotillon, Suzanne E.; Mathis, Melissa L.; Hutchinson, John A.; Dalsted, K. J.

    2016-01-01

    The West Africa Land Use Dynamics Project provides AGRHYMET and its 17 participating countries a comprehensive two-kilometer (2-km) resolution land use land cover (LULC) dataset of the region for three time periods; 1975, 2000, and 2013. Hundreds of Landsat images were visually interpreted to develop a 2-km LULC dataset for each of the three time periods. To assist in validating the interpretations, thousands of aerial photographs and high-resolution satellite images were used. From the initial datasets produced by national teams, the U.S. Geological Survey (USGS) conducted an independent, detailed review of the interpretations. In concurrence with the respective country teams, the data have been revised to produce an accurate and consistent LULC assessment from within the countries and respective transboundary areas. This West Africa Land Use Dynamics Project represents an effort to document and quantify the impacts of change in both time and space, of the environmental and land resource trends across West Africa. The project was carried out through the AGRHYMET Regional Center in Niamey, Niger, in partners from 17 participating countries, the Sahel Institute (INSAH), the USGS Earth Resources Observation and Science (EROS), and with major support from the U.S. Agency for International Development (USAID) West Africa Regional Program. The overarching goal of the West Africa Land Use Dynamics Project is to promote the awareness of the trends and use of spatial information about natural resource trends among national and regional decision-makers. For a complete description of project visit https://eros.usgs.gov/westafrica

  14. Potential climate forcing of land use and land cover change

    Directory of Open Access Journals (Sweden)

    D. S. Ward

    2014-05-01

    Full Text Available Pressure on land resources is expected to increase as global population continues to climb and the world becomes more affluent, swelling the demand for food. Changing climate may exert additional pressures on natural lands as present day productive regions may shift, or soil quality may degrade, and the recent rise in demand for biofuels increases competition with edible crops for arable land. Given these projected trends there is a need to understand the global climate impacts of land use and land cover change (LULCC. Here we quantify the climate impacts of global LULCC in terms of modifications to the balance between incoming and outgoing radiation at the top of the atmosphere (radiative forcing; RF that are caused by changes in long-lived and short-lived greenhouse gas concentrations, aerosol effects and land surface albedo. We simulate historical changes to terrestrial carbon storage, global fire emissions, secondary organic aerosol emissions, and surface albedo from LULCC using the Community Land Model version 3.5. These LULCC emissions are combined with estimates of agricultural emissions of important trace gases and mineral dust in two sets of Community Atmosphere Model simulations to calculate the RF from LULCC impacts on atmospheric chemistry and changes in aerosol concentrations. With all forcing agents considered together, we show that 45% (+30%, −20% of the present-day anthropogenic RF can be attributed to LULCC. Changes in the emission of non-CO2 greenhouse gases and aerosols from LULCC enhance the total LULCC RF by a factor of 2 to 3 with respect to the LULCC RF from CO2 alone. This enhancement factor also applies to projected LULCC RF, which we compute for four future scenarios associated with the Representative Concentration Pathways. We calculate total RFs between 1 to 2 W m−2 from LULCC for the year 2100 (relative to a preindustrial state. To place an upper bound on the potential of LULCC to alter the global radiation

  15. Land Cover Indicators for U.S. National Climate Assessments

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  17. CLC2000 land cover database of the Netherlands; monitoring land cover changes between 1986 and 2000

    NARCIS (Netherlands)

    Hazeu, G.W.

    2003-01-01

    The 1986 CORINE land cover database of the Netherlands was revised and updated on basis of Landsat satellite images and ancillary data. Interpretation of satellite images from 1986 and 2000 resulted in the CLC2000, CLC1986rev and CLCchange databases. A standard European legend and production methodo

  18. CLC2000 land cover database of the Netherlands; monitoring land cover changes between 1986 and 2000

    NARCIS (Netherlands)

    Hazeu, G.W.

    2003-01-01

    The 1986 CORINE land cover database of the Netherlands was revised and updated on basis of Landsat satellite images and ancillary data. Interpretation of satellite images from 1986 and 2000 resulted in the CLC2000, CLC1986rev and CLCchange databases. A standard European legend and production

  19. Land Use and Land Cover Change Detection and Urban Sprawl Analysis of Panamarathupatti Lake, Salem

    Directory of Open Access Journals (Sweden)

    T.Subramani

    2014-06-01

    Full Text Available Land use and land cover change has become a central component in current strategies for managing natural resources and monitoring environmental changes. Urban expansion has brought serious losses of agriculture land, vegetation land and water bodies. Urban sprawl is responsible for a variety of urban environmental issues like decreased air quality, increased runoff and subsequent flooding, increased local temperature, deterioration of water quality, etc. In this work we have taken Panamarathupatti lake salem city as case to study the urban expansion and land cover change that took place in a span of 36 years from 1973 to 2009. Remote sensing methodology is adopted to study the geographical land use changes occurred during the study period. Landsat images of TM and ETM+ of Panamarathupatti lake salem city area are collected from the USGS Earth Explorer web site. After image pre-processing, un-supervised and supervised image classification has been performed to classify the images in to different land use categories. Five land use classes have been identified as Urban (Built-up, Water body, Agricultural land, Barren land and Vegetation. Classification accuracy is also estimated using the field knowledge obtained from field surveys. The obtained accuracy is between 73 to80 percent for all the classes.

  20. Land cover diversity increases predator aggregation and consumption of prey.

    Science.gov (United States)

    Penn, Hannah J; Athey, Kacie J; Lee, Brian D

    2017-05-01

    A lower diversity of land cover types is purported to decrease arthropod diversity in agroecosystems and is dependent on patterns of land use and fragmentation. Ants, important providers of ecosystem services such as biological control, are susceptible to landscape-level changes. We determined the relationships between land cover diversity and fragmentation on the within-field spatial associations of ants to pests and resulting predation events by combining mapping and molecular tools. Increased land cover diversity and decreased fragmentation increased ant abundance, spatial association to pests and predation. Land cover diversity and fragmentation were more explanatory than land cover types. Even so, specific land cover types, such as deciduous forest, influenced ant and pest diversity more so than abundance. These results indicate that geospatial techniques and molecular gut content analysis can be combined to determine the role of land use in influencing predator-prey interactions and resulting predation events in agroecosystems. © 2017 John Wiley & Sons Ltd/CNRS.

  1. Land use and land cover change based on historical space-time model

    Science.gov (United States)

    Sun, Qiong; Zhang, Chi; Liu, Min; Zhang, Yongjing

    2016-09-01

    Land use and cover change is a leading edge topic in the current research field of global environmental changes and case study of typical areas is an important approach understanding global environmental changes. Taking the Qiantang River (Zhejiang, China) as an example, this study explores automatic classification of land use using remote sensing technology and analyzes historical space-time change by remote sensing monitoring. This study combines spectral angle mapping (SAM) with multi-source information and creates a convenient and efficient high-precision land use computer automatic classification method which meets the application requirements and is suitable for complex landform of the studied area. This work analyzes the histological space-time characteristics of land use and cover change in the Qiantang River basin in 2001, 2007 and 2014, in order to (i) verify the feasibility of studying land use change with remote sensing technology, (ii) accurately understand the change of land use and cover as well as historical space-time evolution trend, (iii) provide a realistic basis for the sustainable development of the Qiantang River basin and (iv) provide a strong information support and new research method for optimizing the Qiantang River land use structure and achieving optimal allocation of land resources and scientific management.

  2. Land Cover Differences in Soil Carbon and Nitrogen at Fort Benning, Georgia

    Energy Technology Data Exchange (ETDEWEB)

    Garten Jr., C.T.

    2004-02-09

    Land cover characterization might help land managers assess the impacts of management practices and land cover change on attributes linked to the maintenance and/or recovery of soil quality. However, connections between land cover and measures of soil quality are not well established. The objective of this limited investigation was to examine differences in soil carbon and nitrogen among various land cover types at Fort Benning, Georgia. Forty-one sampling sites were classified into five major land cover types: deciduous forest, mixed forest, evergreen forest or plantation, transitional herbaceous vegetation, and barren land. Key measures of soil quality (including mineral soil density, nitrogen availability, soil carbon and nitrogen stocks, as well as properties and chemistry of the O-horizon) were significantly different among the five land covers. In general, barren land had the poorest soil quality. Barren land, created through disturbance by tracked vehicles and/or erosion, had significantly greater soil density and a substantial loss of carbon and nitrogen relative to soils at less disturbed sites. We estimate that recovery of soil carbon under barren land at Fort Benning to current day levels under transitional vegetation or forests would require about 60 years following reestablishment of vegetation. Maps of soil carbon and nitrogen were produced for Fort Benning based on a 1999 land cover map and field measurements of soil carbon and nitrogen stocks under different land cover categories.

  3. From forest to farmland: pollen-inferred land cover change across Europe using the pseudobiomization approach.

    Science.gov (United States)

    Fyfe, Ralph M; Woodbridge, Jessie; Roberts, Neil

    2015-03-01

    Maps of continental-scale land cover are utilized by a range of diverse users but whilst a range of products exist that describe present and recent land cover in Europe, there are currently no datasets that describe past variations over long time-scales. User groups with an interest in past land cover include the climate modelling community, socio-ecological historians and earth system scientists. Europe is one of the continents with the longest histories of land conversion from forest to farmland, thus understanding land cover change in this area is globally significant. This study applies the pseudobiomization method (PBM) to 982 pollen records from across Europe, taken from the European Pollen Database (EPD) to produce a first synthesis of pan-European land cover change for the period 9000 bp to present, in contiguous 200 year time intervals. The PBM transforms pollen proportions from each site to one of eight land cover classes (LCCs) that are directly comparable to the CORINE land cover classification. The proportion of LCCs represented in each time window provides a spatially aggregated record of land cover change for temperate and northern Europe, and for a series of case study regions (western France, the western Alps, and the Czech Republic and Slovakia). At the European scale, the impact of Neolithic food producing economies appear to be detectable from 6000 bp through reduction in broad-leaf forests resulting from human land use activities such as forest clearance. Total forest cover at a pan-European scale moved outside the range of previous background variability from 4000 bp onwards. From 2200 bp land cover change intensified, and the broad pattern of land cover for preindustrial Europe was established by 1000 bp. Recognizing the timing of anthropogenic land cover change in Europe will further the understanding of land cover-climate interactions, and the origins of the modern cultural landscape.

  4. LandCarbon Conterminous United States Land-Use/Land-Cover Mosaics 1992-2050

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Source data for this variable were obtained from the USGS Land Cover Trends Project. Annual maps of LULC were extrapolated for baseline years (1992 to 2005) and...

  5. VT National Land Cover Dataset by Subbasin - 2011

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC)...

  6. VT National Land Cover Dataset by Subbasin - 2006

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC)...

  7. VT National Land Cover Dataset - Impervious Only - 2001

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The LandLandcov_IMPERV2001 layer available from VCGI is a subset of the the National Land Cover Database 2001 for mapping zone 65 was produced...

  8. Towards an Integrated Global Land Cover Monitoring and Mapping System

    Directory of Open Access Journals (Sweden)

    Martin Herold

    2016-12-01

    Full Text Available Global land cover mapping has evolved in a number of ways over the past two decades including increased activity in the areas of map validation and inter-comparison, which is the main focus of this Special Issue in Remote Sensing. Here we describe the major trends in global land cover mapping that have occurred, followed by recent advances as exemplified by the papers in the Special Issue. Finally, we consider what the future holds for global land cover mapping.

  9. Carbon emissions from land use and land-cover change

    Directory of Open Access Journals (Sweden)

    R. A. Houghton

    2012-12-01

    Full Text Available The net flux of carbon from land use and land-cover change (LULCC accounted for 12.5% of anthropogenic carbon emissions from 1990 to 2010. This net flux is the most uncertain term in the global carbon budget, not only because of uncertainties in rates of deforestation and forestation, but also because of uncertainties in the carbon density of the lands actually undergoing change. Furthermore, there are differences in approaches used to determine the flux that introduce variability into estimates in ways that are difficult to evaluate, and not all analyses consider the same types of management activities. Thirteen recent estimates of net carbon emissions from LULCC are summarized here. In addition to deforestation, all analyses considered changes in the area of agricultural lands (croplands and pastures. Some considered, also, forest management (wood harvest, shifting cultivation. None included emissions from the degradation of tropical peatlands. Means and standard deviations across the thirteen model estimates of annual emissions for the 1980s and 1990s, respectively, are 1.14 ± 0.23 and 1.12 ± 0.25 Pg C yr−1 (1 Pg = 1015 g carbon. Four studies also considered the period 2000–2009, and the mean and standard deviations across these four for the three decades are 1.14 ± 0.39, 1.17 ± 0.32, and 1.10 ± 0.11 Pg C yr−1. For the period 1990–2009 the mean global emissions from LULCC are 1.14 ± 0.18 Pg C yr−1. The standard deviations across model means shown here are smaller than previous estimates of uncertainty as they do not account for the errors that result from data uncertainty and from an incomplete understanding of all the processes affecting the net flux of carbon from LULCC. Although these errors have not been systematically evaluated, based on partial analyses available in the literature and expert opinion, they are estimated to be on the order of ± 0.5 Pg C yr−1.

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

    Science.gov (United States)

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

    2016-04-01

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

  11. Impact of land cover change on the environmental hydrology characteristics in Kelantan river basin, Malaysia

    Science.gov (United States)

    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.

  12. Commentary: A cautionary tale regarding use of the National Land Cover Dataset 1992

    Science.gov (United States)

    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

  13. Land cover changes and their biogeophysical effects on climate

    National Research Council Canada - National Science Library

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

    2014-01-01

    Land cover changes ( LCCs ) play an important role in the climate system. Research over recent decades highlights the impacts of these changes on atmospheric temperature, humidity, cloud cover, circulation, and precipitation...

  14. Spatial assessment of land surface temperature and land use/land cover in Langkawi Island

    Science.gov (United States)

    Abu Bakar, Suzana Binti; Pradhan, Biswajeet; Salihu Lay, Usman; Abdullahi, Saleh

    2016-06-01

    This study investigates the relationship between Land Surface Temperature and Land Use/Land Cover in Langkawi Island by using Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-Up Index (NDBI) and Modified Normalized Difference Water Index (MNDWI) qualitatively by using Landsat 7 ETM+ and Landsat 8 (OLI/TIRS) over the period 2002 and 2015. Pixel-based classifiers Maximum Likelihood (MLC) and Support Vector Machine (SVM), has been performed to prepare the Land Use/ Land Cover map (LU/LC) and the result shows that Support Vector Machine (SVM) achieved maximum accuracy with 90% and 90.46% compared to Maximum Likelihood (MLC) classifier with 86.62% and 86.98% respectively. The result revealed that as the impervious surface (built-up /roads) increases, the surface temperature of the area increased. However, land surface temperature decreased in the vegetated areas. Based from the linear regression between LST and NDVI, NDBI and MNDWI, these indices can be used as an indicator to monitor the impact of Land Use/Land Cover on Land Surface Temperature.

  15. Spatial Accuracy Assessment and Integration of Global Land Cover Datasets

    Directory of Open Access Journals (Sweden)

    Nandin-Erdene Tsendbazar

    2015-11-01

    Full Text Available Along with the creation of new maps, current efforts for improving global land cover (GLC maps focus on integrating maps by accounting for their relative merits, e.g., agreement amongst maps or map accuracy. Such integration efforts may benefit from the use of multiple GLC reference datasets. Using available reference datasets, this study assesses spatial accuracy of recent GLC maps and compares methods for creating an improved land cover (LC map. Spatial correspondence with reference dataset was modeled for Globcover-2009, Land Cover-CCI-2010, MODIS-2010 and Globeland30 maps for Africa. Using different scenarios concerning the used input data, five integration methods for an improved LC map were tested and cross-validated. Comparison of the spatial correspondences showed that the preferences for GLC maps varied spatially. Integration methods using both the GLC maps and reference data at their locations resulted in 4.5%–13% higher correspondence with the reference LC than any of the input GLC maps. An integrated LC map and LC class probability maps were computed using regression kriging, which produced the highest correspondence (76%. Our results demonstrate the added value of using reference datasets and geostatistics for improving GLC maps. This approach is useful as more GLC reference datasets are becoming publicly available and their reuse is being encouraged.

  16. A global dataset of crowdsourced land cover and land use reference data.

    Science.gov (United States)

    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.

  17. an assessment of the land use and land cover changes in shurugwi ...

    African Journals Online (AJOL)

    Dr Osondu

    Geographic Information System and remote sensing techniques. Three satellite ... degraded land covers 26.6% with the rest shared between vegetation (18.1%) and water (2%). There has ... decision support system employing land cover.

  18. Land Cover Classification Using ALOS Imagery For Penang, Malaysia

    Science.gov (United States)

    Sim, C. K.; Abdullah, K.; MatJafri, M. Z.; Lim, H. S.

    2014-02-01

    This paper presents the potential of integrating optical and radar remote sensing data to improve automatic land cover mapping. The analysis involved standard image processing, and consists of spectral signature extraction and application of a statistical decision rule to identify land cover categories. A maximum likelihood classifier is utilized to determine different land cover categories. Ground reference data from sites throughout the study area are collected for training and validation. The land cover information was extracted from the digital data using PCI Geomatica 10.3.2 software package. The variations in classification accuracy due to a number of radar imaging processing techniques are studied. The relationship between the processing window and the land classification is also investigated. The classification accuracies from the optical and radar feature combinations are studied. Our research finds that fusion of radar and optical significantly improved classification accuracies. This study indicates that the land cover/use can be mapped accurately by using this approach.

  19. Integrating global land cover datasets for deriving user-specific maps

    NARCIS (Netherlands)

    Tsendbazar, Nandika; Bruin, de Sytze; Herold, Martin

    2016-01-01

    Global scale land cover (LC) mapping has interested many researchers over the last two decades as it is an input data source for various applications. Current global land cover (GLC) maps often do not meet the accuracy and thematic requirements of specific users. This study aimed to create an improv

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

    Science.gov (United States)

    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.

  1. Land use and land cover dynamics in the Brazilian Amazon: understanding human-environmental interactions

    NARCIS (Netherlands)

    Souza Soler, de L.

    2014-01-01

    Land use and land cover dynamics are a result of the interactions between human activities and the environment. The objective of this thesis is to analyze Amazonian land use and land cover pattern dynamics in order to identify the underlying system dynamics. By combining empirical statistical models

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

    Science.gov (United States)

    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

  3. 100-Meter Resolution Land Cover of Hawaii - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer contains land cover data for Hawaii, in an Albers Equal-Area Conic projection and at a resolution of 100 meters. The land cover data were derived from...

  4. 100-Meter Resolution Land Cover of Alaska - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer contains land cover data for Alaska, in an Albers Equal-Area Conic projection and at a resolution of 100 meters. The land cover data were derived from...

  5. Seasonal land-cover regions of the US

    Science.gov (United States)

    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 US 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-km-resolution database of land-cover characteristics for the coterminous US 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 15?? seasonal land-cover regions. Data are used in the construction of an illustrative 1:7500 000-scale 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. -from Authors

  6. Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover

    Directory of Open Access Journals (Sweden)

    Florian Kraxner

    2009-08-01

    Full Text Available Global land cover is one of the essential terrestrial baseline datasets available for ecosystem modeling, however uncertainty remains an issue. Tools such as Google Earth offer enormous potential for land cover validation. With an ever increasing amount of very fine spatial resolution images (up to 50 cm × 50 cm available on Google Earth, it is becoming possible for every Internet user (including non remote sensing experts to distinguish land cover features with a high degree of reliability. Such an approach is inexpensive and allows Internet users from any region of the world to get involved in this global validation exercise. The Geo-Wiki Project is a global network of volunteers who wish to help improve the quality of global land cover maps. Since large differences occur between existing global land cover maps, current ecosystem and land-use science lacks crucial accurate data (e.g., to determine the potential of additional agricultural land available to grow crops in Africa, volunteers are asked to review hotspot maps of global land cover disagreement and determine, based on what they actually see in Google Earth and their local knowledge, if the land cover maps are correct or incorrect. Their input is recorded in a database, along with uploaded photos, to be used in the future for the creation of a new and improved hybrid global land cover map.

  7. Effective UV surface albedo of seasonally snow-covered lands

    Science.gov (United States)

    Tanskanen, A.; Manninen, T.

    2007-05-01

    At ultraviolet wavelengths the albedo of most natural surfaces is small with the striking exception of snow and ice. Therefore, snow cover is a major challenge for various applications based on radiative transfer modelling. The aim of this work was to determine the characteristic effective UV range surface albedo of various land cover types when covered by snow. First we selected 1 by 1 degree sample regions that met three criteria: the sample region contained dominantly subpixels of only one land cover type according to the 8 km global land cover classification product from the University of Maryland; the average slope of the sample region was less than 2 degrees according to the USGS's HYDRO1K slope data; the sample region had snow cover in March according to the NSIDC Northern Hemisphere weekly snow cover data. Next we generated 1 by 1 degree gridded 360 nm surface albedo data from the Nimbus-7 TOMS Lambertian equivalent reflectivity data, and used them to construct characteristic effective surface albedo distributions for each land cover type. The resulting distributions showed that each land cover type experiences a characteristic range of surface albedo values when covered by snow. The result is explained by the vegetation that extends upward beyond the snow cover and masks the bright snow covered surface.

  8. Towards realistic Holocene land cover scenarios: integration of archaeological, palynological and geomorphological records and comparison to global land cover scenarios.

    Science.gov (United States)

    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

  9. Land cover mapping of Greater Mesoamerica using MODIS data

    Science.gov (United States)

    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.

  10. Simulating land-cover change in Montane mainland southeast Asia.

    Science.gov (United States)

    Fox, Jefferson; Vogler, John B; Sen, Omer L; Giambelluca, Thomas W; Ziegler, Alan D

    2012-05-01

    We used the conversion of land use and its effects (CLUE-s) model to simulate scenarios of land-cover change in Montane mainland southeast Asia (MMSEA), a region in the midst of transformation due to rapid intensification of agriculture and expansion of regional trade markets. Simulated changes affected approximately 10 % of the MMSEA landscape between 2001 and 2025 and 16 % between 2001 and 2050. Roughly 9 % of the current vegetation, which consists of native species of trees, shrubs, and grasses, is projected to be replaced by tree plantations, tea, and other evergreen shrubs during the 50 years period. Importantly, 4 % of this transition is expected to be due to the expansion of rubber (Hevea brasiliensis), a tree plantation crop that may have important implications for local-to-regional scale hydrology because of its potentially high water consumption in the dry season.

  11. BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

    Science.gov (United States)

    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

  12. C-CAP Land Cover, Molokai, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine...

  13. C-CAP Hawaii 2005 Land Cover

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine...

  14. Percent Agricultural Land Cover on Steep Slopes

    Data.gov (United States)

    U.S. Environmental Protection Agency — Clearing land for agriculture tends to increase soil erosion. The amount of erosion is related to the steepness of the slope, farming methods used and soil type....

  15. C-CAP Land Cover, Kauai, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine...

  16. C-CAP Land Cover, Maui, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine...

  17. C-CAP Land Cover, Lanai, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine...

  18. C-CAP Land Cover, Niihau, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land derived from high resolution imagery and was analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine...

  19. Modeled impact of anthropogenic land cover change on climate

    Science.gov (United States)

    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.

  20. Development of 2010 national land cover database for the Nepal.

    Science.gov (United States)

    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.

  1. The CORINE Land Cover database of the Netherlands; final report of the CORINE Land Cover project in the Netherlands

    NARCIS (Netherlands)

    Thunnissen, H.A.M.; Middelaar, van H.J.

    1995-01-01

    The CORINE Land Cover Project is aimed at gathering coherent information on land cover for the European Union and at integrating this in a geographical information system (GIS). The methodology is a computer-assisted visual interpretation of earth observation satellite images, with simultaneous cons

  2. Cartographic aspects of land cover change detection (over- and underestimation in the I&CORINE Land Cover 2000 project)

    NARCIS (Netherlands)

    Feranec, J.; Hazeu, G.W.; Jaffrain, G.; Cebecauer, T.

    2007-01-01

    This paper presents the results of analysis of the data obtained by the method of computer-aided visual interpretation of satellite images used for identification of changes in land cover within the framework of the Image and CORINE Land Cover 2000 (I&CLC2000) Project (jointly managed by the Eur

  3. Regional land cover characterization using Landsat thematic mapper data and ancillary data sources

    Science.gov (United States)

    Vogelmann, J.E.; Sohl, T.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.

  4. The Relative Impact of Regional Scale Land Cover Change and Increasing CO2 over China

    Institute of Scientific and Technical Information of China (English)

    Mei ZHAO; Andrew J. PITMAN

    2005-01-01

    A series of 17-yr equilibrium simulations using the NCAR CCM3 (T42 resolution) were performed to investigate the regional scale impacts of land cover change and increasing CO2 over China. Simulations with natural and current land cover at CO2 levels of 280, 355,430, and 505 ppmv were conducted. Results show statistically significant changes in major climate fields (e.g. temperature and surface wind speed) ona 15-yr average following land cover change. We also found increases in the maximum temperature and in the diurnal temperature range due to land cover change. Increases in CO2 affect both the maximum and minimum temperature so that changes in the diurnal range are small. Both land cover change and CO2 change also impact the frequency distribution of precipitation with increasing CO2 tending to lead to more intense precipitation and land cover change leading to less intense precipitation-indeed, the impact of land cover change typically had the opposite effect versus the impacts of CO2. Our results provide support for the inclusion of future land cover change scenarios in long-term transitory climate modelling experiments of the 21st Century. Our results also support the inclusion of land surface models that can represent future land cover changes resulting from an ecological response to natural climate variability or increasing CO2. Overall, we show that land cover change can have a significant impact on the regional scale climate of China, and that regionally, this impact is of a similar magnitude to increases in CO2 of up to about 430 ppmv. This means that that the impact of land cover change must be accounted for in detection and attribution studies over China.

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

    Science.gov (United States)

    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.

  6. Collect Earth: Land Use and Land Cover Assessment through Augmented Visual Interpretation

    Directory of Open Access Journals (Sweden)

    Adia Bey

    2016-09-01

    Full Text Available Collect Earth is a free and open source software for land monitoring developed by the Food and Agriculture Organization of the United Nations (FAO. Built on Google desktop and cloud computing technologies, Collect Earth facilitates access to multiple freely available archives of satellite imagery, including archives with very high spatial resolution imagery (Google Earth, Bing Maps and those with very high temporal resolution imagery (e.g., Google Earth Engine, Google Earth Engine Code Editor. Collectively, these archives offer free access to an unparalleled amount of information on current and past land dynamics for any location in the world. Collect Earth draws upon these archives and the synergies of imagery of multiple resolutions to enable an innovative method for land monitoring that we present here: augmented visual interpretation. In this study, we provide a full overview of Collect Earth’s structure and functionality, and we present the methodology used to undertake land monitoring through augmented visual interpretation. To illustrate the application of the tool and its customization potential, an example of land monitoring in Papua New Guinea (PNG is presented. The PNG example demonstrates that Collect Earth is a comprehensive and user-friendly tool for land monitoring and that it has the potential to be used to assess land use, land use change, natural disasters, sustainable management of scarce resources and ecosystem functioning. By enabling non-remote sensing experts to assess more than 100 sites per day, we believe that Collect Earth can be used to rapidly and sustainably build capacity for land monitoring and to substantively improve our collective understanding of the world’s land use and land cover.

  7. Sensitivity of land use change emission estimates to historical land use and land cover mapping

    Science.gov (United States)

    Peng, Shushi; Ciais, Philippe; Maignan, Fabienne; Li, Wei; Chang, Jinfeng; Wang, Tao; Yue, Chao

    2017-04-01

    The carbon emissions from land use and land cover change (ELUC) are an important anthropogenic component of the global carbon budget. Yet these emissions have a large uncertainty. Uncertainty in historical land use and land cover change (LULCC) maps and their implementation in global vegetation models is one of the key sources of the spread of ELUC calculated by global vegetation models. In this study, we used the Organizing Carbon and Hydrology in Dynamic Ecosystems terrestrial biosphere model to investigate how the different transition rules to define the priority of conversion from natural vegetation to agricultural land affect the historical reconstruction of plant functional types (PFTs) and ELUC. First, we reconstructed 10 sets of historical PFT maps using different transition rules and two methods. Then, we calculated ELUC from these 10 different historical PFT maps and an additional published PFT reconstruction, using the difference between two sets of simulations (with and without LULCC). The total area of forest loss is highly correlated with the total simulated ELUC (R2 = 0.83, P < 0.001) across the reconstructed PFT maps, which indicates that the choice of transition rules is a critical (and often overlooked) decision affecting the simulated ELUC. In addition to the choice of a transition rule, the initial land cover map and the reconstruction method for the reconstruction of historical PFT maps have an important impact on the resultant estimates of ELUC.

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

    Science.gov (United States)

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

    2017-12-01

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

  9. MODIS land cover uncertainty in regional climate simulations

    Science.gov (United States)

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

    2017-02-01

    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.

  10. Land Use and Land Cover, Existing land use derived from orthoimagery. Ground-truthing from discussion with local plan commission members., Published in 2000, 1:12000 (1in=1000ft) scale, Portage County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Land Use and Land Cover dataset current as of 2000. Existing land use derived from orthoimagery. Ground-truthing from discussion with local plan commission members..

  11. Monitoring land use and land cover change in mountain regions: An example in the Jalca grasslands of the Peruvian Andes

    NARCIS (Netherlands)

    Tovar, C.; Seijmonsbergen, A.C.; Duivenvoorden, J.F.

    2013-01-01

    Mountains are rich in biodiversity and provide ecosystem services for their inhabitants. These regions are currently threatened by land use and land cover changes (LUCC), therefore an efficient monitoring is required to capture such changes. The aim of this study is to test a landscape change analys

  12. Monitoring land use and land cover change in mountain regions: An example in the Jalca grasslands of the Peruvian Andes

    NARCIS (Netherlands)

    Tovar, C.; Seijmonsbergen, A.C.; Duivenvoorden, J.F.

    2013-01-01

    Mountains are rich in biodiversity and provide ecosystem services for their inhabitants. These regions are currently threatened by land use and land cover changes (LUCC), therefore an efficient monitoring is required to capture such changes. The aim of this study is to test a landscape change

  13. Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh

    Directory of Open Access Journals (Sweden)

    Bayes Ahmed

    2013-11-01

    Full Text Available Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30 °C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth on LST and consequently to devise appropriate policy measures.

  14. Land Use / Land Cover Classification of kanniykumari Coast, Tamilnadu, India. Using Remote Sensing and Gis Techniques

    Directory of Open Access Journals (Sweden)

    Hajeeran Beevi.N,

    2015-07-01

    Full Text Available The land use/ land cover details of Kanniyakuamri coast which is Located in the southern part of Tamil Nadu (India is studied. Satellite imagery is used to identify the Land use/ Land cover status of the study area. The software like ERDAS and Arc GIS are used to demarcate the land use / Land cover features of Kanniyakuamari coast. Remote sensing and GIS provided consistent and accurate base line information than many of the conventional surveys employed for such a task. The total area of Kanniyakumari coast is 715 sq.km. The land use / land cover classes of the study area has been categorized into thirteen such as Plantation, Sandy area, Water logged area, Scrub forest, Crop Land, Water bodies, Land with scrub, Reserve forest, Land without Scrub, Salt area, Beach Ridge, Settlement and Fallow land on the basis NRSA Classifications. Among these categories, land with scrub land is predominantly found all over the study area, It is occupied about 336.36 sq.km (44.61 percent, Crop Land 273.82 sq.km(38.29 percent, water bodies lands sharing about 20.44 sq.km (2.85 percent , settlement occupied with 6.96 sq.km (0.97 percent, and Fallow land was occupied 13.98 sq.km ( 1.95 percent .

  15. Modelling land cover change in the Ganga basin

    Science.gov (United States)

    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.

  16. Determining Land Surface Temperature Relations with Land Use-Land Cover and Air Pollution

    Science.gov (United States)

    Kahya, Ceyhan; Bektas Balcik, Filiz; Burak Oztaner, Yasar; Guney, Burcu

    2016-04-01

    Rapid population growth in conjunction with unplanned urbanization, expansion, and encroachment into the limited agricultural fields and green areas have negative impacts on vegetated areas. Land Surface Temperature (LST), Urban Heat Islands (UHI) and air pollution are the most important environmental problems that the extensive part of the world suffers from. The main objective of this research is to investigate the relationship between LST, air pollution and Land Use-Land Cover (LULC) in Istanbul, using Landsat 8 OLI satellite image. Mono-window algorithm is used to compute LST from Landsat 8 TIR data. In order to determine the air pollution, in-situ measurements of particulate matter (PM10) of the same day as the Landsat 8 OLI satellite image are obtained. The results of this data are interpolated using the Inverse Distance Weighted (IDW) method and LULC categories of Istanbul were determined by using remote sensing indices. Error matrix was created for accuracy assessment. The relationship between LST, air pollution and LULC categories are determined by using regression analysis method. Keywords: Land Surface Temperature (LST), air pollution, Land Use-Land Cover (LULC), Istanbul

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

    Science.gov (United States)

    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.

  18. 2005 Kansas Land Cover Patterns, Level I, Kansas River Watershed

    Data.gov (United States)

    Kansas Data Access and Support Center — The Upper Kansas River Watershed Land Cover Patterns map represents Phase 1 of a two-phase mapping initiative occurring over a three-year period as part of a...

  19. Trends in Coastal Development and Land Cover Change: The Case ...

    African Journals Online (AJOL)

    South Africa. Keywords: Land cover change, coastal management, coastal development, ... population growth, social and economic development and climate-induced factors. The results ... changing in response to human demands and needs ...

  20. 2005 Kansas Land Cover Patterns, Level IV, Kansas River Watershed

    Data.gov (United States)

    Kansas Data Access and Support Center — The 2005 Kansas Land Cover Patterns (KLCP) Mapping Initiative was a two-phase mapping endeavor that occurred over a three-year period (2007-2009). Note that while...

  1. North American Land Cover Characteristics ? 1-Kilometer Resolution - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer is an Arc/INFO grid map of land cover characteristics for North America, excluding Hawaii, and including the Caribbean and most of Mexico. The nominal...

  2. National Land Cover Database 2001 Version 2: 1985-2006

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The National Land Cover Database 2001 Version 2 (NLCD 2001 Version 2) is being compiled across all 50 states and Puerto Rico as a cooperative mapping effort of the...

  3. A COMPARATIVE STUDY OF ALGORITHMS FOR LAND COVER CHANGE

    Data.gov (United States)

    National Aeronautics and Space Administration — A COMPARATIVE STUDY OF ALGORITHMS FOR LAND COVER CHANGE SHYAM BORIAH*, VARUN MITHAL, ASHISH GARG, VIPIN KUMAR, MICHAEL STEINBACH, CHRIS POTTER, AND STEVE KLOOSTER*...

  4. Land Cover Trends Geotagged Photography: 1999-2007

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The United States Geological Survey (USGS) Land Cover Trends field photography collection is a national-scale, ground-reference dataset which initially served as a...

  5. National Land Cover Database 2001 Version 2: 1985-2006

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The National Land Cover Database 2001 Version 2 (NLCD 2001 Version 2) is being compiled across all 50 states and Puerto Rico as a cooperative mapping effort of the...

  6. Unsupervised land cover change detection: meaningful sequential time series analysis

    CSIR Research Space (South Africa)

    Salmon, BP

    2011-06-01

    Full Text Available An automated land cover change detection method is proposed that uses coarse spatial resolution hyper-temporal earth observation satellite time series data. The study compared three different unsupervised clustering approaches that operate on short...

  7. The Changing Midwest Assessment: land cover, natural resources, and people

    Science.gov (United States)

    Robert Potts; Eric Gustafson; Susan I. Stewart; Frank R. Thompson; Kathleen Bergen; Daniel G. Brown; Roger Hammer; Volker Radeloff; David Bengston; John Sauer; Brian Sturtevant

    2004-01-01

    Documents changes in land cover, forests, selected natural resources, and human demographics and attitudes across the Midwest from roughly 1980 to 2000. The changing Midwest assessment: data and shapefiles are available from the Forest Service Research Data Archive....

  8. South African National Land-Cover Change Map

    African Journals Online (AJOL)

    Fritz Schoeman

    Various spatial modelling procedures were used to ensure compilation of comparable and .... 4.3 Temporal Land-Cover Change Modelling Issues ... The reasoning followed in developing these rules is based on logical principles associated ...

  9. Mekong Regional Land Cover Monitoring System Reference Methods

    Science.gov (United States)

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

    2016-12-01

    In 2015, SERVIR-Mekong conducted a geospatial needs assessment for the Lower Mekong countries which included individual country consultations. The assessment revealed 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 and accuracy assessment do not always meet the needs of key user groups. In addition, data products stop at political boundaries and are often not accessible. Many of the Lower Mekong 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. During this assessment, 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. This system is dependent on a sustainable source of field data that insures data quality and improves potential impact. Based on this need a collaborative workshop was held to create a robust regional reference data system that integrates results from field data, national inventories and high resolution imagery. The results presented here highlights the value of collaboratively developed systems that use data convergence to improve land cover mapping results for multiple end users.

  10. Land cover modification geoindicator applied in a tropical coastal environment

    OpenAIRE

    Palacio-Aponte, Gerardo

    2014-01-01

    Environmental changes due to natural processes and anthropic modifications can be characterized by the degree of land cover modification and its environmental implications over time. The main goal of the present study was to propose and apply a land cover modification geoindicator in order to assess the environmental condition of the territory per landscape units. It was designed to interpret diffuse information and transform it into a synthetic indicator that will be useful for environmental...

  11. Land Use and Land Cover, Published in unknown, Indianapolis Power & light Co..

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset as of unknown. Data by this publisher are often provided in State Plane coordinate system; in a Orthographic projection; The...

  12. VT Generalized Land Cover Land Use for Champlain Basin - SAL 1992

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) Circa 1992 land use - land cover (LULC) for the Lake Champlain Basin. This layer was created by performing a retrospective change detection on the...

  13. VT Generalized Land Cover Land Use for Champlain Basin - SAL 2001

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) Circa 2001 land use / land cover (LULC) for the Lake Champlain Basin. The goal in creating this layer was to generate an "improved" version of...

  14. 2005 Land Cover and Land Use Spatial Database of Big Stone National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The U.S. Geological Survey (USGS) - Upper Midwest Environmental Sciences Center (UMESC) has produced a high-resolution land cover/land use (LCU) spatial database of...

  15. 2006 Land Cover/Land Use Neal Smith National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The U.S. Geological Survey (USGS) - Upper Midwest Environmental Sciences Center (UMESC) has produced a high-resolution land cover/land use (LCU) spatial database of...

  16. 2005 Land Cover and Land Use Spatial Database of Fox River National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The U.S. Geological Survey (USGS) - Upper Midwest Environmental Sciences Center (UMESC) has produced a high-resolution land cover/land use (LCU) spatial database of...

  17. Estimating land use / land cover changes in Denmark from 1990 - 2012

    DEFF Research Database (Denmark)

    Levin, Gregor; Kastrup Blemmer, Morten; Gyldenkærne, Steen

    According to the article 3(4) of the Kyoto Protocol, Denmark is obliged to document sequestration and emission of carbon dioxide from land use and land cover and changes in these. This report documents and describes applied data end developed methods aiming at estimating amounts and changes in land...... use and land cover for Denmark for since 1990. Estimation of land use and land cover categories and changes in these is predominantly based on existing categorical (i.e. pre-classified) geographical information. Estimations are elaborated for the period from 1990 to 2005, from 2005 to 2011 and from...... 2011 to 2012. Due to limited availability of historical spatially explicit information, estimations of change in land use and land cover from 1990 up to 2011 do, to some degree, involve decisions based on expert knowledge. Due to a significant increase in the availability of detailed spatially specific...

  18. 2004 Land Cover and Land Use Spatial Database Seney National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The U.S. Geological Survey (USGS) - Upper Midwest Environmental Sciences Center (UMESC) has produced a high-resolution land cover/land use (LCU) spatial database of...

  19. Land Use and Land Cover, Published in 2009, Chautauqua County/Elk County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, was produced all or in part from Field Observation information as of 2009. Data by this publisher are often provided in State...

  20. Estimating land use / land cover changes in Denmark from 1990 - 2012

    DEFF Research Database (Denmark)

    Levin, Gregor; Kastrup Blemmer, Morten; Gyldenkærne, Steen

    According to the article 3(4) of the Kyoto Protocol, Denmark is obliged to document sequestration and emission of carbon dioxide from land use and land cover and changes in these. This report documents and describes applied data end developed methods aiming at estimating amounts and changes in land...... use and land cover for Denmark for since 1990. Estimation of land use and land cover categories and changes in these is predominantly based on existing categorical (i.e. pre-classified) geographical information. Estimations are elaborated for the period from 1990 to 2005, from 2005 to 2011 and from...... 2011 to 2012. Due to limited availability of historical spatially explicit information, estimations of change in land use and land cover from 1990 up to 2011 do, to some degree, involve decisions based on expert knowledge. Due to a significant increase in the availability of detailed spatially specific...

  1. Global Tree Cover and Biomass Carbon on Agricultural Land

    NARCIS (Netherlands)

    Zomer, Robert J.; Neufeldt, Henry; Xu, Jianchu; Ahrends, Antje; Bossio, Deborah; Trabucco, Antonio; Noordwijk, Van 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 signif

  2. A methodology to generate a synergetic land-cover map by fusion of different land-cover products

    Science.gov (United States)

    Pérez-Hoyos, A.; García-Haro, F. J.; San-Miguel-Ayanz, J.

    2012-10-01

    The main goal of this study is to develop a general framework for building a hybrid land-cover map by the synergistic combination of a number of land-cover classifications with different legends and spatial resolutions. The proposed approach assesses class-specific accuracies of datasets and establishes affinity between thematic legends using a common land-cover language such as the UN Land-Cover Classification System (LCCS). The approach is illustrated over a large region in Europe using four land-cover datasets (CORINE, GLC2000, MODIS and GlobCover), but it can be applied to any set of existing products. The multi-classification map is expected to improve the performance of individual classifications by reconciling their best characteristics while avoiding their main weaknesses. The intermap comparison reveals improved agreement of the hybrid map with all other land-cover products and therefore indicates the successful exploration of synergies between the different products. The approach offers also estimates for the classification confidence associated with the pixel label and flexibility to shift the balance between commission and omission errors, which are critical in order to obtain a desired reliable map.

  3. Thirty years of land-cover change in Bolivia.

    Science.gov (United States)

    Killeen, Timothy J; Calderon, Veronica; Soria, Liliana; Quezada, Belem; Steininger, Marc K; Harper, Grady; Solórzano, Luis A; Tucker, Compton J

    2007-11-01

    Land-cover change in eastern lowland Bolivia was documented using Landsat images from five epochs for all landscapes situated below the montane tree line at approximately 3000 m, including humid forest, inundated forest, seasonally dry forest, and cloud forest, as well as scrublands and grasslands. Deforestation in eastern Bolivia in 2004 covered 45,411 km2, representing approximately 9% of the original forest cover, with an additional conversion of 9042 km2 of scrub and savanna habitats representing 17% of total historical land-cover change. Annual rates of land-cover change increased from approximately 400 km2 y(-1) in the 1960s to approximately 2900 km2 y(-1) in the last epoch spanning 2001 to 2004. This study provides Bolivia with a spatially explicit information resource to monitor future land-cover change, a prerequisite for proposed mechanisms to compensate countries for reducing carbon emissions as a result of deforestation. A comparison of the most recent epoch with previous periods shows that policies enacted in the late 1990s to promote forest conservation had no observable impact on reducing deforestation and that deforestation actually increased in some protected areas. The rate of land-cover change continues to increase linearly nationwide, but is growing faster in the Santa Cruz department because of the expansion of mechanized agriculture and cattle farms.

  4. Determination of Land Cover/land Use Using SPOT 7 Data with Supervised Classification Methods

    Science.gov (United States)

    Bektas Balcik, F.; Karakacan Kuzucu, A.

    2016-10-01

    Land use/ land cover (LULC) classification is a key research field in remote sensing. With recent developments of high-spatial-resolution sensors, Earth-observation technology offers a viable solution for land use/land cover identification and management in the rural part of the cities. There is a strong need to produce accurate, reliable, and up-to-date land use/land cover maps for sustainable monitoring and management. In this study, SPOT 7 imagery was used to test the potential of the data for land cover/land use mapping. Catalca is selected region located in the north west of the Istanbul in Turkey, which is mostly covered with agricultural fields and forest lands. The potentials of two classification algorithms maximum likelihood, and support vector machine, were tested, and accuracy assessment of the land cover maps was performed through error matrix and Kappa statistics. The results indicated that both of the selected classifiers were highly useful (over 83% accuracy) in the mapping of land use/cover in the study region. The support vector machine classification approach slightly outperformed the maximum likelihood classification in both overall accuracy and Kappa statistics.

  5. Adding structure to land cover - using fractional cover to study animal habitat use.

    Science.gov (United States)

    Bevanda, Mirjana; Horning, Ned; Reineking, Bjoern; Heurich, Marco; Wegmann, Martin; Mueller, Joerg

    2014-01-01

    Linking animal movements to landscape features is critical to identify factors that shape the spatial behaviour of animals. Habitat selection is led by behavioural decisions and is shaped by the environment, therefore the landscape is crucial for the analysis. Land cover classification based on ground survey and remote sensing data sets are an established approach to define landscapes for habitat selection analysis. We investigate an approach for analysing habitat use using continuous land cover information and spatial metrics. This approach uses a continuous representation of the landscape using percentage cover of a chosen land cover type instead of discrete classes. This approach, fractional cover, captures spatial heterogeneity within classes and is therefore capable to provide a more distinct representation of the landscape. The variation in home range sizes is analysed using fractional cover and spatial metrics in conjunction with mixed effect models on red deer position data in the Bohemian Forest, compared over multiple spatio-temporal scales. We analysed forest fractional cover and a texture metric within each home range showing that variance of fractional cover values and texture explain much of variation in home range sizes. The results show a hump-shaped relationship, leading to smaller home ranges when forest fractional cover is very homogeneous or highly heterogeneous, while intermediate stages lead to larger home ranges. The application of continuous land cover information in conjunction with spatial metrics proved to be valuable for the explanation of home-range sizes of red deer.

  6. Minnesota Land Use and Cover - A 1990's Census of the Land - Tiled

    Data.gov (United States)

    Minnesota Department of Natural Resources — This data set integrates six different source data sets to provide a simplified overall view of Minnesota's land use / cover. The six source data sets covered...

  7. Precipitation Response to Land Cover Changes in the Netherlands

    Science.gov (United States)

    Daniels, E.; Lenderink, G.; Hutjes, R. W. A.; Holtslag, A. A.

    2015-12-01

    Precipitation has increased by 25% over the last century in the Netherlands. In this period, conversion of peat areas into grassland, expansion of urban areas, and the creation of new land in Lake Ijssel were the largest land cover changes. Both station data analysis (Daniels et al. 2014) and high-resolution (2.5 km) simulations with the atmospheric Weather Research and Forecasting (WRF) model suggest that the observed increase in precipitation is not due to these land cover changes. Instead, the change from historical (1900) to present (2000) land cover decreases precipitation in WRF (Figure). However, WRF seems to be very sensitive to changes in evapotranspiration. The creation of new land and the expansion of urban areas are similar from a moisture perspective, since they locally decrease evapotranspiration, and therefore affect the soil moisture-precipitation feedback mechanism. In our simulations, the resulting feedback is always positive, as a reduction in evapotranspiration causes a reduction of precipitation. There is a difference between urban areas and land in WRF however. Over urban areas, the planetary boundary layer (PBL) height increases more than the lifting condensation level (LCL), and the potential to trigger precipitation hereby increases. This in turn decreases the strength, but not sign, of the soil moisture-precipitation feedback. WRF is therefore unable to reproduce the observed precipitation enhancement downwind of urban areas. In all, it seems the sensitivity of WRF to changes in surface moisture might be too high and this questions the applicability of the model to investigate land cover changes. Daniels, E. E., G. Lenderink, R. W. A. Hutjes, and A. A. M. Holtslag, 2014: Spatial precipitation patterns and trends in The Netherlands during 1951-2009. International Journal of Climatology, 34, 1773-1784. Figure: Composite summer precipitation (mm) based on 19 single day cases (a), showing the decreases resulting from changing present to

  8. Impacts of Regional-Scale Land Use/Land Cover Change on Diurnal Temp erature Range

    Institute of Scientific and Technical Information of China (English)

    HUA Wen-Jian; CHEN Hai-Shan

    2013-01-01

    The NCAR Community Atmosphere Model (CAM4.0) was used to investigate the climate effects of land use/land cover change (LUCC). Two simulations, one with potential land cover without significant human intervention and the other with current land use, were conducted. Results show that the impacts of LUCC on diurnal temperature range (DTR) are more significant than on mean surface air temperature. The global average annual DTR change due to LUCC is -0.1◦C, which is three times as large as the mean temperature change. LUCC influences regional DTR as simulated by the model. In the mid-latitudes, LUCC leads to a decrease in DTR, which is mainly caused by the reduction in daily maximum temperature. However, there are some differences in the low latitudes. The reduction in DTR in East Asia is mainly the result of the decrease in daily maximum temperature, while in India, the decrease in DTR is due to the increase in daily minimum temperature. In general, the LUCC significantly controls the DTR change through the changes in canopy evaporation and transpiration.

  9. Impacts of Regional-Scale Land Use/Land Cover Change on Diurnal Temperature Range

    Institute of Scientific and Technical Information of China (English)

    HUA; Wen-Jian; CHEN; Hai-Shan

    2013-01-01

    The NCAR Community Atmosphere Model(CAM4.0)was used to investigate the climate efects of land use/land cover change(LUCC).Two simulations,one with potential land cover without significant human intervention and the other with current land use,were conducted.Results show that the impacts of LUCC on diurnal temperature range(DTR)are more significant than on mean surface air temperature.The global average annual DTR change due to LUCC is–0.1℃,which is three times as large as the mean temperature change.LUCC influences regional DTR as simulated by the model.In the mid-latitudes,LUCC leads to a decrease in DTR,which is mainly caused by the reduction in daily maximum temperature.However,there are some diferences in the low latitudes.The reduction in DTR in East Asia is mainly the result of the decrease in daily maximum temperature,while in India,the decrease in DTR is due to the increase in daily minimum temperature.In general,the LUCC significantly controls the DTR change through the changes in canopy evaporation and transpiration.

  10. Land cover changes and their biogeophysical effects on climate

    Science.gov (United States)

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

    2013-01-01

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

  11. Land Use and Land Cover, Impervious Surface - contains polygons that represent houses, buildings, roads, driveways, sidewalks, pools, patios, parking lots, pavements, Published in 2008, 1:2400 (1in=200ft) scale, Effingham County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Land Use and Land Cover dataset current as of 2008. Impervious Surface - contains polygons that represent houses, buildings, roads, driveways, sidewalks, pools,...

  12. Modelling Deforestation and Land Cover Transitions of Tropical Peatlands in Sumatra, Indonesia Using Remote Sensed Land Cover Data Sets

    Directory of Open Access Journals (Sweden)

    Ian Elz

    2015-08-01

    Full Text Available In Southeast Asia land use change associated with forest loss and degradation is a major source of greenhouse gas (GHG emissions. This is of particular concern where deforestation occurs on peat soils. A business-as-usual (BAU land change model was developed using Dinamica EGO© for a REDD+ Demonstration Activity area in south-east Jambi Province, Sumatra, Indonesia containing Berbak National Park (NP. The model output will be used as baseline land change predictions for comparison with alternative land cover management scenarios as part of a REDD+ feasibility study. The study area is approximately 376,000 ha with approximately 50% on peat soils. The model uses published 2000 and 2010 land cover maps as input and projects land cover change for thirty years until 2040. The model predicted that under a BAU scenario the forest area, 185,000 ha in 2010, will decline by 37% by 2040. In protected forest areas, approximately 50% of the study area, forest cover will reduce by 25%. Peat swamp forest will reduce by almost 37%. The greatest land cover category increases are plantation/regrowth areas (which includes oil palm and open areas which each increase by 30,000 ha. These results indicate that the site has great potential as an Indonesian REDD+ Demonstration Activity.

  13. Using ASTER Imagery in Land Use/cover Classification of Eastern Mediterranean Landscapes According to CORINE Land Cover Project

    Directory of Open Access Journals (Sweden)

    Recep Gundogan

    2008-02-01

    Full Text Available The satellite imagery has been effectively utilized for classifying land covertypes and detecting land cover conditions. The Advanced Spaceborne Thermal Emissionand Reflection Radiometer (ASTER sensor imagery has been widely used in classificationprocess of land cover. However, atmospheric corrections have to be made by preprocessingsatellite sensor imagery since the electromagnetic radiation signals received by the satellitesensors can be scattered and absorbed by the atmospheric gases and aerosols. In this study,an ASTER sensor imagery, which was converted into top-of-atmosphere reflectance(TOA, was used to classify the land use/cover types, according to COoRdination ofINformation on the Environment (CORINE land cover nomenclature, for an arearepresenting the heterogonous characteristics of eastern Mediterranean regions inKahramanmaras, Turkey. The results indicated that using the surface reflectance data ofASTER sensor imagery can provide accurate (i.e. overall accuracy and kappa values of83.2% and 0.79, respectively and low-cost cover mapping as a part of inventory forCORINE Land Cover Project.

  14. Land Use and Land Cover, Impervious Surface Raster National Land Cover Database from USGS, Published in 2001, 1:63360 (1in=1mile) scale, Iredell County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:63360 (1in=1mile) scale, was produced all or in part from Orthoimagery information as of 2001. It is described...

  15. Land Use and Land Cover, Heard County, Georgia Land Cover Map, Published in 2005, 1:12000 (1in=1000ft) scale, Chattahoochee-Flint Regional Development.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Hardcopy Maps information as of 2005. It is described...

  16. Aerial Video Processing for Land Use and Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Ashoka Vanjare

    2013-06-01

    Full Text Available In this paper, we have proposed an Automatic Aerial Video Processing System for analyzing land surface features. Analysis of aerial video is done in three steps a Image pre-processing b Image registration and c Image segmentation. Using the proposed system, we have identified Land features like Vegetation, Man-Made Structures and Barren Land. These features are identified and differentiated from each other to calculate their respective areas. Most important feature of this system is that it is an instantaneous video acquisition and processing system. In the first step, radial distortions of image are corrected using Fish-Eye correction algorithm. In the second step, the image features are matched and then images are stitched using Scale Invariant Feature Transform (SIFT followed by Random Sample Consensus (RANSAC algorithm. In the third step, the stitched images are segmented using Mean Shift Segmentation and different structures are identified using RGB model. Here we have used a hybrid system to identify Man-Made Structures using Fuzzy Edge Extraction along with Mean Shift segmentation. The results obtained are compared with the ground truth data, thus evaluating the performance of the system. The proposed system is implemented using Intel's OpenCV.

  17. Temporal Land Cover Analysis for Net Ecosystem Improvement

    Energy Technology Data Exchange (ETDEWEB)

    Ke, Yinghai; Coleman, Andre M.; Diefenderfer, Heida L.

    2013-04-09

    We delineated 8 watersheds contributing to previously defined river reaches within the 1,468-km2 historical floodplain of the tidally influenced lower Columbia River and estuary. We assessed land-cover change at the watershed, reach, and restoration site scales by reclassifying remote-sensing data from the National Oceanic and Atmospheric Administration Coastal Change Analysis Program’s land cover/land change product into forest, wetland, and urban categories. The analysis showed a 198.3 km2 loss of forest cover during the first 6 years of the Columbia Estuary Ecosystem Restoration Program, 2001–2006. Total measured urbanization in the contributing watersheds of the estuary during the full 1996-2006 change analysis period was 48.4 km2. Trends in forest gain/loss and urbanization differed between watersheds. Wetland gains and losses were within the margin of error of the satellite imagery analysis. No significant land cover change was measured at restoration sites, although it was visible in aerial imagery, therefore, the 30-m land-cover product may not be appropriate for assessment of early-stage wetland restoration. These findings suggest that floodplain restoration sites in reaches downstream of watersheds with decreasing forest cover will be subject to increased sediment loads, and those downstream of urbanization will experience effects of increased impervious surfaces on hydrologic processes.

  18. Wildfire selectivity for land cover type: does size matter?

    Science.gov (United States)

    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 ([Formula: see text] = 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.

  19. Land cover dynamics in Wa Municipality, Upper West Region of Ghana

    Directory of Open Access Journals (Sweden)

    M.S. Aduah

    2012-06-01

    Full Text Available Land cover change is pervasive in urban areas and can destabilise the ecosystem with negative consequences. To manage land effectively and to protect its cover, there is the need for a reliable inventory. GIS and remote sensing technology has become a standard in producing land cover maps worldwide. Therefore, in this study GIS and remote sensing was used to map the land cover of Wa Municipality of the Upper West Region of Ghana. Two Landsat 5 images of 1986 and 2011 were used. The images were pre-processed, subset to the study area and classified using the maximum likelihood classification algorithm. The map accuracies for the classes of interest; built-up, bare land and vegetation were not less than 70%. The land cover maps generated indicated that built-up area has increased by 34% whiles total size of bare land has increased by 47% from 1986 to 2011.These increases have reduced the total area of vegetated land by 10%. Therefore, if the current rate of degradation is not controlled, biodiversity of Wa and its surrounding areas would be lost in the near future. Also the degradation can intensify floods and droughts and other effects of climate change. The current study has demonstrated the effectiveness of GIS and remote sensing in studying environmental changes taking place in semi-arid regions. The application of remote sensing technologies should be intensified especially in the developing world to continue to provide vital data needed to manage the environment in a sustainable manner.

  20. Land-Cover Map for the Island of Maui, Hawaii, circa 2017

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This dataset describes land cover and vegetation for the island of Maui, Hawaii, circa 2017, hereinafter the 2017 land-cover map. The 2017 land-cover map is a...

  1. Land cover detection with SAR images of Delta del Llobregat

    Science.gov (United States)

    Godinho, R.; Borges, P. A. V.; Calado, H.; Broquetas, A.

    2016-08-01

    This work presents a study of a multitemporal set of C-band images collected by ERS-2, aiming to understand the differentiations of the backscatter intensity and the phase coherence of different land covers to find possible synergies that could improve land cover detection. The land cover analysis allowed to observe the perfect differentiation of urban areas from intensity images. The observation of multitemporal RGB compositions combining key dates of the different points of crops growth make possible to differentiate this land cover and also to observe fluctuations inside the class itself. This fluctuations present a pattern that correspond to the crop field structure, which suggests that more information can be obtained. The shrubs are difficult to detect from the intensity images, but once the observation is combined with coherence images the detection is possible. However, the coherence image must be generated from pairs of images with a temporal interval lower than three months, independently from the year of registration of each image due to the general decrease of coherence when larger intervals are used. The analysis allowed to observe the potential of this data to perfect distinguish urban, crops and shrubs. The study of the seasonal fluctuations of intensity for the crops land cover with precise ground truth for crops type and points of growth is proposed as a future line of research.

  2. Land use/land cover changes around Rameshwaram Island, east coast of India

    Digital Repository Service at National Institute of Oceanography (India)

    Gowthaman, R.; Dwarakish, G.S.; Sanilkumar, V.

    Land-use/land cover changes are studied using the Indian Remote Sensing satellite (IRS-1C, IRS-6) Linear Image Self-scan Sensor (LISS) III data of 1998 and 2010 Coastal land use categories such as sand, vegetation, coral reef and water have been...

  3. Characterizing the relationship between land use land cover change and land surface temperature

    Science.gov (United States)

    Tran, Duy X.; Pla, Filiberto; Latorre-Carmona, Pedro; Myint, Soe W.; Caetano, Mario; Kieu, Hoan V.

    2017-02-01

    Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi∗ statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi∗ statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management.

  4. 1975 UMRS Land Cover/Land Use -- Pool 16

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  5. 1975 UMRS Land Cover/Land Use -- Pool 13

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  6. 1975 UMRS Land Cover/Land Use -- Pool 4

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  7. 1975 UMRS Land Cover/Land Use -- Pool 7

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  8. 1975 UMRS Land Cover/Land Use -- Pool 18

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  9. 1975 UMRS Land Cover/Land Use -- Pool 10

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  10. 1975 UMRS Land Cover/Land Use -- Pool 22

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  11. 1975 UMRS Land Cover/Land Use -- Pool 15

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  12. 1975 UMRS Land Cover/Land Use -- Open River 2

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  13. 1975 UMRS Land Cover/Land Use -- Pool 24

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  14. 1975 UMRS Land Cover/Land Use -- Pool 20

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  15. 1975 UMRS Land Cover/Land Use -- Pool 8

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  16. 1975 UMRS Land Cover/Land Use -- Pool 17

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  17. 1975 UMRS Land Cover/Land Use -- Pool 3

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  18. 1975 UMRS Land Cover/Land Use -- Open River 1

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  19. 1975 UMRS Land Cover/Land Use -- Pool 14

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  20. 1975 UMRS Land Cover/Land Use -- Pool 5

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  1. 1975 UMRS Land Cover/Land Use -- Pool 19

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  2. 1975 UMRS Land Cover/Land Use -- Pool 26

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  3. 1975 UMRS Land Cover/Land Use -- Pool 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  4. 1975 UMRS Land Cover/Land Use -- Pool 11

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  5. 1975 UMRS Land Cover/Land Use -- Pool 25

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  6. 1975 UMRS Land Cover/Land Use -- Pool 9

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  7. 1975 UMRS Land Cover/Land Use -- Pool 25

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  8. 1975 UMRS Land Cover/Land Use -- Pool 21

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  9. 1975 UMRS Land Cover/Land Use -- Pool 5a

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  10. 1975 UMRS Land Cover/Land Use -- Pool 12

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Great River Environmental Action Team (GREAT) was a federal/state multi-agency cooperative program established in the late 1970's to evaluate current resource...

  11. Impact of land cover changes on the South African climate

    Energy Technology Data Exchange (ETDEWEB)

    Ngwana, T I [South African Weather Service, Pretoria (South Africa); Demory, M-E; Vidale, P L; Plant, R S [University of Reading, Earley Gate, Reading (United Kingdom); Mbedzi, M P, E-mail: isaac.ngwana@weathersa.co.z [Eskom Holdings, Cleveland (South Africa)

    2010-08-15

    The Joint UK Land Environmental Simulator (JULES) was run offline to investigate the sensitivity of land surface type changes over South Africa. Sensitivity tests were made in idealised experiments where the actual land surface cover is replaced by a single homogeneous surface type. The vegetation surface types on which some of the experiments were made are static. Experimental tests were evaluated against the control. The model results show among others that the change of the surface cover results in changes of other variables such as soil moisture, albedo, net radiation and etc. These changes are also visible in the spin up process. The model shows different surfaces spinning up at different cycles. Because JULES is the land surface model of Unified Model, the results could be more physically meaningful if it is coupled to the Unified Model.

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — 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...

  13. Land Cover and Land Use Change in a Water Controlled Environment

    Science.gov (United States)

    Elmore, A. J.; Mustard, J. F.; Manning, S. J.

    2001-05-01

    The conversion of large natural basins to managed watersheds for the purpose of providing water to urban centers has the effect of extending the influence of urban policy to rural areas. Consequences include the reduction of agricultural activity and the removal of water resources that would otherwise sustain or be available to reestablish disturbed native vegetation communities. Satisfying local and regional demands for water at a time when climatic variability is predicted to increase will be more difficult and may permanently alter natural ecosystems. Despite the services provided by natural communities, current water policy in arid lands does not always support sustainable management of the natural ecosystems. Furthermore, when water management does include information on vegetation conditions, the data are typically taken at a scale much smaller than the region of management. We studied Owens Valley, California at the watershed scale to determine the regional effects of water diversion and exportation to Los Angeles. Owens Valley is currently a managed watershed with extraction policy based on annual vegetation surveys and soil moisture measurements. This wealth of field data was combined with 13 years of Landsat TM data to identify the response in vegetative live cover to a six-year drought. During the drought, ground water extraction and the suspension of irrigation led to groundwater decline in many areas. Regions of groundwater decline were spatially correlated with areas exhibiting vegetative live cover losses of up to 80%. Following the drought, ground water recovered throughout most of the valley. Although live cover also subsequently increased, in many regions non-groundwater dependent exotic weeds increased in dominance relative to native species. This shift in cover type signals a potentially adverse shift in ecosystem function. In the most extreme case, abandoned agricultural fields have not been repopulated by native vegetation despite 100 years of

  14. Effects of different scale land cover maps in watershed modelling

    Science.gov (United States)

    Nunes, Antonio; Araújo, Antonio; Alexandridis, Thomas; Chambel, Pedro

    2013-04-01

    Water management is a rather complex process that usually involves multiple stakeholder, multiple data and sources, and complex mathematical modelling. One of the key data sets to understand a particular water system is the characterization of the land cover. Land cover maps are essential for the estimation of environmental variables (e.g. LAI, ETa) related to water quantity. Also, land cover maps are used for modelling the water quality. For instance, watersheds that have intensive agriculture can have poor water quality due to increase of nutrients loading; forest fires have a significant negative impact over the water quality by increasing the sediment loads; forest fires can increase flood risks. The land cover dynamics can as well severely affect the water quantity and quality in watersheds. In the MyWater project we are conducting a study to supply water quantity and quality information services for five study areas in five different countries (Brazil, Greece, Mozambique, Netherlands, and Portugal). In this project several land cover maps were produced both at regional and local scales, based on the exploitation of medium and high resolution satellite images (MERIS and SPOT 4). These maps were produced through semi-automatic supervised classification procedures, using an LCCS based nomenclature of 15 classes. Validation results pointed to global accuracy values greater than 80% for all maps. In this paper we focus on studying the effect of using different scale land cover maps in the watershed modelling and its impact in results. The work presented is part of the FP7-EU project "Merging hydrological models and Earth observation data for reliable information on water - MyWater".

  15. Major forest changes and land cover transitions based on plant functional types derived from the ESA CCI Land Cover product

    Science.gov (United States)

    Li, Wei; Ciais, Philippe; MacBean, Natasha; Peng, Shushi; Defourny, Pierre; Bontemps, Sophie

    2016-05-01

    Land use and land cover change are of prime concern due to their impacts on CO2 emissions, climate change and ecological services. New global land cover products at 300 m resolution from the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI LC) project for epochs centered around 2000, 2005 and 2010 were analyzed to investigate forest area change and land cover transitions. Plant functional types (PFTs) fractions were derived from these land cover products according to a conversion table. The gross global forest loss between 2000 and 2010 is 172,171 km2, accounting for 0.6% of the global forest area in year 2000. The forest changes are mainly distributed in tropical areas such as Brazil and Indonesia. Forest gains were only observed between 2005 and 2010 with a global area of 9844 km2, mostly from crops in Southeast Asia and South America. The predominant PFT transition is deforestation from forest to crop, accounting for four-fifths of the total increase of cropland area between 2000 and 2010. The transitions from forest to bare soil, shrub, and grass also contributed strongly to the total areal change in PFTs. Different PFT transition matrices and composition patterns were found in different regions. The highest fractions of forest to bare soil transitions were found in the United States and Canada, reflecting forest management practices. Most of the degradation from grassland and shrubland to bare soil occurred in boreal regions. The areal percentage of forest loss and land cover transitions generally decreased from 2000-2005 to 2005-2010. Different data sources and uncertainty in the conversion factors (converting from original LC classes to PFTs) contribute to the discrepancy in the values of change in absolute forest area.

  16. Assessment Of The Impact Of ESA CCI Land Cover Information For Global Climate Model Simulations

    Science.gov (United States)

    Khlystova, Iryna G.; Loew, A.; Hangemann, S.; Defourny, P.; Brockmann, C.; Bontemps, S.

    2013-12-01

    Addressing the issues of climate change, the European Space Agency has recently initiated the Global Monitoring of an Essential Climate Variables program (ESA Climate Change Initiative). The main objective is to realize the full potential of the long-term global Earth Observation archives that ESA has established over the last thirty years. Due to well organized data access and transparency for the data quality, as well as long-term scientific and technical support, the provided datasets have become very attractive for the use in Earth System Modeling. The Max Plank Institute for Meteorology is contributing to the ESA CCI via the Climate Modeler User Group (CMUG) activities and is responsible for providing a modeler perspective on the Land Cover and Fire Essential Climate Variables. The new ESA land cover ECV has recently released a new global 300-m land cover dataset. This dataset is supported by an interactive tool which allows flexible horizontal re-scaling and conversion from currently accepted satellite specific land classes to the model- specific Plant Functional Types (PFT) categorization. Such a dataset is an ideal starting point for the generation of the land cover information for the initialization of model cover fractions. In this presentation, we show how the usage of this new dataset affects the model performance, comparing it to the standard model set-up, in terms of energy and water fluxes. To do so, we performed a number of offline land-system simulations with original standard JSBACH land cover information and with the new ESA CCI land cover product. We have analyzed the impact of land cover on a simulated surface albedo, temperature and energy fluxes as well as on the biomass load and fire carbon emissions.

  17. A higher order conditional random field model for simultaneous classification of land cover and land use

    Science.gov (United States)

    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

  18. Modelling land change: the issue of use and cover in wide-scale applications

    NARCIS (Netherlands)

    Bakker, M.M.; Veldkamp, A.

    2008-01-01

    In this article, the underlying causes for the apparent mismatch between land cover and land use in the context of wide-scale land change modelling are explored. A land use-land cover (LU/LC) ratio is proposed as a relevant landscape characteristic. The one-to-one ratio between land use and land

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

    Science.gov (United States)

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

    2016-09-01

    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.

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

    Science.gov (United States)

    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.

  1. The land use and land cover change database and its relative studies in China

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    In the mid-1990s, we established the national operative dynamic information serving systems on natural resources and environment. During building the land-use/land-cover change (LUCC)database for the mid-1990s, 520 scenes of remotely sensed images of Landsat Thematic Mapper (TM) were interpreted into land-use/land-cover categories at scale of 1:100,000 under overall digital software environment after being geo-referenced and ortho-rectified. The vector map of land-use/land-cover in China at the scale of 1:100,000 was recently converted into a 1-km raster database that captures all ofthe high-resolution land-use information by calculating area percentage for each kind of land use category within every cell. Being designed as an operative dynamic information serving system,monitoring the change in land-use/land-cover at national level was executed. We have completed the updating of LUCC database by comparing the TM data in the mid-1990s with new data sources received during 1999-2000 and 1989-1990. The LUCC database has supported greatly the national LUCC research program in China and some relative studies are incompletely reviewed in this paper.

  2. Improving arable land heterogeneity information in available land cover products for land surface modelling using MERIS NDVI data

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2010-10-01

    Full Text Available Regionalization of physical land surface models requires the supply of detailed land cover information. Numerous global and regional land cover maps already exist but generally, they do not resolve arable land into different crop types. However, arable land comprises a huge variety of different crops with characteristic phenological behaviour, demonstrated in this paper with Leaf Area Index (LAI measurements exemplarily for maize and winter wheat. This affects the mass and energy fluxes on the land surface and thus its hydrology. The objective of this study is the generation of a land cover map for central Europe based on CORINE Land Cover (CLC 2000, merged with CORINE Switzerland, but distinguishing different crop types. Accordingly, an approach was developed, subdividing the land cover class arable land into the regionally most relevant subclasses for central Europe using multiseasonal MERIS Normalized Difference Vegetation Index (NDVI data. The satellite data were used for the separation of spring and summer crops due to their different phenological behaviour. Subsequently, the generated phenological classes were subdivided following statistical data from EUROSTAT. This database was analysed concerning the acreage of different crop types. The impact of the improved land use/cover map on evapotranspiration was modelled exemplarily for the Upper Danube catchment with the hydrological model PROMET. Simulations based on the newly developed land cover approach showed a more detailed evapotranspiration pattern compared to model results using the traditional CLC map, which is ignorant of most arable subdivisions. Due to the improved temporal behaviour and spatial allocation of evapotranspiration processes in the new land cover approach, the simulated water balance more closely matches the measured gauge.

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

    Science.gov (United States)

    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

  4. Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China

    Directory of Open Access Journals (Sweden)

    Huiran Han

    2015-04-01

    Full Text Available Land use and land cover (LULC models are essential for analyzing LULC change and predicting land use requirements and are valuable for guiding reasonable land use planning and management. However, each LULC model has its own advantages and constraints. In this paper, we explore the characteristics of LULC change and simulate future land use demand by combining a CLUE-S model with a Markov model to deal with some shortcomings of existing LULC models. Using Beijing as a case study, we describe the related driving factors from land-adaptive variables, regional spatial variables and socio-economic variables and then simulate future land use scenarios from 2010 to 2020, which include a development scenario (natural development and rapid development and protection scenarios (ecological and cultivated land protection. The results indicate good consistency between predicted results and actual land use situations according to a Kappa statistic. The conversion of cultivated land to urban built-up land will form the primary features of LULC change in the future. The prediction for land use demand shows the differences under different scenarios. At higher elevations, the geographical environment limits the expansion of urban built-up land, but the conversion of cultivated land to built-up land in mountainous areas will be more prevalent by 2020; Beijing, however, still faces the most pressure in terms of ecological and cultivated land protection.

  5. Interaction effects of climate and land use/land cover change on soil organic carbon sequestration.

    Science.gov (United States)

    Xiong, Xiong; Grunwald, Sabine; Myers, D Brenton; Ross, C Wade; Harris, Willie G; Comerford, Nicolas B

    2014-09-15

    Historically, Florida soils stored the largest amount of soil organic carbon (SOC) among the conterminous U.S. states (2.26 Pg). This region experienced rapid land use/land cover (LULC) shifts and climate change in the past decades. The effects of these changes on SOC sequestration are unknown. The objectives of this study were to 1) investigate the change in SOC stocks in Florida to determine if soils have acted as a net sink or net source for carbon (C) over the past four decades and 2) identify the concomitant effects of LULC, LULC change, and climate on the SOC change. A total of 1080 sites were sampled in the topsoil (0-20 cm) between 2008 and 2009 representing the current SOC stocks, 194 of which were selected to collocate with historical sites (n = 1251) from the Florida Soil Characterization Database (1965-1996) for direct comparison. Results show that SOC stocks significantly differed among LULC classes--sugarcane and wetland contained the highest SOC, followed by improved pasture, urban, mesic upland forest, rangeland, and pineland while crop, citrus and xeric upland forest remained the lowest. The surface 20 cm soils acted as a net sink for C with the median SOC significantly increasing from 2.69 to 3.40 kg m(-2) over the past decades. The SOC sequestration rate was LULC dependent and controlled by climate factors interacting with LULC. Higher temperature tended to accelerate SOC accumulation, while higher precipitation reduced the SOC sequestration rate. Land use/land cover change observed over the past four decades also favored the C sequestration in soils due to the increase in the C-rich wetland area by ~140% and decrease in the C-poor agricultural area by ~20%. Soils are likely to provide a substantial soil C sink considering the climate and LULC projections for this region.

  6. D Land Cover Classification Based on Multispectral LIDAR Point Clouds

    Science.gov (United States)

    Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

    2016-06-01

    Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

  7. Assessment of the thematic accuracy of land cover maps

    DEFF Research Database (Denmark)

    Høhle, Joachim

    2015-01-01

    Several land cover maps are generated from aerial imagery and assessed by different approaches. The test site is an urban area in Europe for which six classes (‘building’, ‘hedge and bush’, ‘grass’, ‘road and parking lot’, ‘tree’, ‘wall and car port’) had to be derived. Two classification methods...

  8. Transferability of decision trees for land cover classification in a ...

    African Journals Online (AJOL)

    GChandler

    1Department of Geography and Environmental Studies, Stellenbosch ... 2School of Plant Biology, University of Western Australia, Perth, Australia ... results, a normalised difference vegetation index (NDVI) threshold was applied to each scene. This ... The value of multi-temporal imagery for land cover classification was also.

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

    Science.gov (United States)

    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

  10. Landsat continuity: issues and opportunities for land cover monitoring

    Science.gov (United States)

    Michael A. Wulder; Joanne C. White; Samuel N. Goward; Jeffrey G. Masek; James R. Irons; Martin Herold; Warren B. Cohen; Thomas R. Loveland; Curtis E. Woodcock

    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...

  11. Trends in land use and land cover change in the protected and communal areas of the Zambezi Region, Namibia.

    Science.gov (United States)

    Kamwi, Jonathan Mutau; Kaetsch, Christoph; Graz, Friedrich Patric; Chirwa, Paxie; Manda, Samuel

    2017-05-01

    Land management decisions have extensively modified land use and land cover in the Zambezi Region. These decisions are influenced by land tenure classifications, legislation, and livelihoods. Land use and land cover change is an important indicator for quantifying the effectiveness of different land management strategies. However, there has been no evidence on whether protected or communal land tenure is more affected by land use and land cover changes in southern Africa and particularly Namibia. Our study attempted to fill this gap by analyzing the relationship between land use and land cover change and land tenure regimes stratified according to protected and communal area in the Zambezi Region. Multi-temporal Landsat TM and ETM+ imagery were used to determine the temporal dynamics of land use and land cover change from 1984 to 2010. The landscape showed distinctive modifications over the study period; broad trends include the increase in forest land after 1991. However, changes were not uniform across the study areas. Two landscape development stages were deduced: (1) 1984-1991 represented high deforestation and gradual increase in shrub land; (2) 1991-2000 and 2000-2010 represented lower deforestation and slower agropastoral expansion. The results further show clear patterns of the dynamics, magnitude, and direction of land use and land cover change by tenure regime. The study concluded that land tenure has a direct impact on land use and land cover, since it may restrict some activities carried out on the land in the Zambezi Region.

  12. Effects of historical land cover changes on climate

    Institute of Scientific and Technical Information of China (English)

    SHI ZhengGuo; YAN XiaoDong; YIN ChongHua; WANG ZhaoMin

    2007-01-01

    In order to explore the influence of anthropogenic land use on the climate system during the last millennium, a set of experiments is performed with an Earth system model of intermediate complexity--the McGill Paleoclimate Model (MPM-2). The present paper mainly focuses on biogeophysical effects of historical land cover changes. A dynamic scenario of deforestation is described based on changes in cropland fraction (RF99). The model simulates a decrease in global mean annual temperature in the range of 0.09-0.16℃, especially 0.14-0.22℃ in Northern Hemisphere during the last 300 years. The responses of climate system to GHGs concentration changes are also calculated for comparisons. Now, afforestation is becoming an important choice for the enhancement of terrestrial carbon sequestration and adjustment of regional climate. The results indicate that biogeophysical effects of land cover changes cannot be neglected in the assessments of climate change.

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

    Science.gov (United States)

    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 and Land-Use Change under Changing Climate in the Eurasian Arctic

    Science.gov (United States)

    Gutman, G.

    2009-04-01

    An overview of the studies conducted in the framework of the NASA Land-Cover/Land- Use Change Program focused on the Eurasian Arctic will be presented. It includes discussion of vegetation changes under climate warming and implications to carbon cycle, changes in environmental pollution, hydrologic cycle, and impacts on society. Climate change can affect land cover in the Arctic through changes in the surface reflectivity and hydrology due to changes in snow melt timing; impacts of black carbon emitted by fires and settled on bright surfaces; changes in sea ice and the consequent change in ocean circulation affecting vegetation cover patterns indirectly; and changes in the amounts of greenhouse gases emission due to permafrost melting, especially in peatlands, as warming progresses. The Arctic Eurasia is being affected by global and regional external factors that are causing its change and the positive feedbacks to this forcing may further exaggerate the situation. If the warming trend continues it will have a tremendous impact on all aspects of land cover in the Arctic region with considerable consequences at the global scale. It will cause significant changes in the natural land cover, and perhaps even greater changes in the areas where the land cover has already been considerably modified by human activities. Major changes have already taken place in how land is used in the Arctic. In many regions, there has been a clear shift from the land use practiced by indigenous people to intensive exploitation of the land for commercial and industrial uses. Results on the climate/environment - land-cover interactions will be presented.

  15. Automated Training Sample Extraction for Global Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Julien Radoux

    2014-05-01

    Full Text Available Land cover is one of the essential climate variables of the ESA Climate Change Initiative (CCI. In this context, the Land Cover CCI (LC CCI project aims at building global land cover maps suitable for climate modeling based on Earth observation by satellite sensors.  The  challenge  is  to  generate  a  set  of  successive  maps  that  are  both  accurate and consistent over time. To do so, operational methods for the automated classification of optical images are investigated. The proposed approach consists of a locally trained classification using an automated selection of training samples from existing, but outdated land cover information. Combinations of local extraction (based on spatial criteria and self-cleaning of training samples (based on spectral criteria are quantitatively assessed. Two large study areas, one in Eurasia and the other in South America, are considered. The proposed morphological cleaning of the training samples leads to higher accuracies than the statistical outlier removal in the spectral domain. An optimal neighborhood has been identified for the local sample extraction. The results are coherent for the two test areas, showing an improvement of the overall accuracy compared with the original reference datasets and a significant reduction of macroscopic errors. More importantly, the proposed method partly controls the reliability of existing land cover maps as sources of training samples for supervised classification.

  16. Albuquerque, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  17. Carlsbad, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  18. Hobbs, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  19. Raton, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  20. Brownfield, TX 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  1. Roswell, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  2. Shiprock, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  3. Shiprock, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  4. Clifton, AZ 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  5. Roswell, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  6. Gallup, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  7. Gallup, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  8. Socorro, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  9. Tularosa, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  10. Shiprock, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  11. Clovis, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  12. Tularosa, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  13. Dalhart, TX 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  14. Hobbs, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  15. Socorro, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  16. Clifton, AZ 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  17. Carlsbad, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  18. Raton, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  19. Brownfield, TX 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  20. Roswell, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  1. Clifton, AZ 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  2. Shiprock, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  3. Carlsbad, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  4. Douglas, AZ 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  5. Aztec, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  6. Aztec, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  7. Albuquerque, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  8. Tucumcari, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  9. Albuquerque, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  10. Raton, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  11. Douglas, AZ 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...

  12. Clifton, AZ 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  13. Tularosa, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  14. Dalhart, TX 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  15. Aztec, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  16. Tularosa, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  17. Raton, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  18. Socorro, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  19. Gallup, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  20. Socorro, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  1. Albuquerque, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  2. Douglas, AZ 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  3. Gallup, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  4. Douglas, AZ 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  5. Clovis, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  6. Aztec, NM 1:250,000 Quad West Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  7. Carlsbad, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  8. Tucumcari, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  9. Roswell, NM 1:250,000 Quad East Half USGS Land Use/Land Cover, 2000

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency...

  10. Trend in Land Use/Land Cover Change Detection by RS and GIS Application

    Directory of Open Access Journals (Sweden)

    S. Poongothai

    2011-09-01

    Full Text Available The study aims to effects of Land Use / Land Cover Changes (LU/LCC is the quantitative method, to expound the impact of land use/land cover changes in Manimuktha sub-watershed of Vellar basin, Tamilnadu, India. The relationship between Land Use Changes and its trend is analysed using IRS IC LISS III and PAN merged data. Further, the preparation of LU/LC map using Survey of India (SOIToposheet for the year 1972 has come in handy to know the past land use pattern. Similarly, the Land Use/Land Cover (LU/LC map of various years, namely, 1996, 2003 and 2007, which was obtained from Institute of Remote Sensing, Anna University (IRS and digitized, using Arc GIS 9.1 software. About 52.89 per cent of land is devoted to agricultural practices under agriculture and cropland has a major impact over the hydrological processes of the basin. Hence, the information obtained from change detection of LU/LC aids in providing optimal solutions for the selection, planning, implementation and monitoring of development schemes to meet the increasing demands of human needs has lead to land management.

  11. Land Cover Changes between 1974 and 2008 in Ulaanbaatar, Mongolia

    Science.gov (United States)

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

    2009-12-01

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

  12. Multitemporal unmixing of medium-spatial-resolution satellite images: A case study using MERIS images for land-cover mapping

    NARCIS (Netherlands)

    Zurita Milla, R.; Gómez-Chova, L.; Guanter, L.; Clevers, J.G.P.W.; Champs-Valls, G.

    2011-01-01

    Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mapping and land-cover change detection at regional to global scales. However, few landscapes are homogeneous at these scales, and this creates the so-called mixed-pixel problem. In this context, this

  13. Multitemporal unmixing of medium-spatial-resolution satellite images: a case study using MERIS images for land - cover mapping

    NARCIS (Netherlands)

    Zurita-Milla, R.; Gomez-Chova, L.; Guanter, L.; Clevers, J.G.P.W.; Camps-Valls, G.

    2011-01-01

    Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mapping and land-cover change detection at regional to global scales. However, few landscapes are homogeneous at these scales, and this creates the so-called mixed-pixel problem. In this context, this

  14. Multitemporal unmixing of medium-spatial-resolution satellite images: A case study using MERIS images for land-cover mapping

    NARCIS (Netherlands)

    Zurita Milla, R.; Gómez-Chova, L.; Guanter, L.; Clevers, J.G.P.W.; Champs-Valls, G.

    2011-01-01

    Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mapping and land-cover change detection at regional to global scales. However, few landscapes are homogeneous at these scales, and this creates the so-called mixed-pixel problem. In this context, this stud

  15. Deriving a per-field land use and land cover map in an agricultural mosaic catchment

    Directory of Open Access Journals (Sweden)

    B. Seo

    2014-04-01

    Full Text Available Detailed data on land use and land cover constitutes important information for Earth system models, environmental monitoring and ecosystem services research. Global land cover products are evolving rapidly, however, there is still a lack of information particularly for heterogeneous agricultural landscapes. We censused land use and land cover field by field in an agricultural mosaic catchment Haean, South Korea. We recorded the land cover types with additional information on agricultural practice and make this data available at the public repository Pangaea (doi:10.1594/PANGAEA.823677. In this paper we introduce the data, its collection and the post-processing protocol. During the studied period, a large portion of dry fields was converted to perennial crops. A comparison between our dataset and MODIS Land Cover Type (MCD12Q1 suggested that the MODIS product was restricted in this area since it does not distinguish irrigated fields from general croplands. In addition, linear landscape elements such as water bodies were not detected in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research.

  16. Historical land-use induced evapotranspiration changes estimated from present-day observations and reconstructed land-cover maps

    Directory of Open Access Journals (Sweden)

    J. P. Boisier

    2014-02-01

    Full Text Available Recent model intercomparison studies, within the framework of the LUCID project, have revealed large discrepancies in the evapotranspiration (ET changes simulated between the preindustrial period and the present in response to the historical change in land use. Distinct land-surface parameterizations are behind those discrepancies, but understanding those differences and attributing them to specific causes rely on evaluations using still very limited measurements. Model benchmarking studies with observed global-scale ET are required in order to reduce the current uncertainties in the impacts of land use in terrestrial water flows. Here we present a new estimate of historical land-use induced changes in ET based on three different state-of-the-art observation-based ET products. These products are used to derive regression models of ET as a function of land-cover partitioning, leaf area index and environmental variables. We then reconstruct past ET changes based on the set of land-cover maps of 1870 and 1992 used in LUCID. Our results show an average decrease in global terrestrial ET of 1260 ± 850 km3 yr−1 between the preindustrial period and the present-day. This estimate is of the same order but larger in magnitude than the model-mean change in ET simulated within LUCID, and substantially weaker in magnitude than other estimates based on observations. Although decreases in ET dominate in deforested regions, large summertime increases in ET are diagnosed over areas of large cropland expansion. The multiple ET reconstructions carried out here show a large spread that we attribute principally to the different land-cover maps adopted and to the crops' ET rates that are derived from the various products assessed. We therefore conclude that the current uncertainties of past ET changes could be reduced efficiently with improved historical land-cover reconstructions and better estimates of cropland ET.

  17. Fort Sumner, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  18. Clifton, AZ NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  19. Tucumcari, NM TX 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  20. Raton, NM CO 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  1. Gallup, NM AZ 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  2. Saint Johns, AZ NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  3. Carlsbad, NM TX 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  4. Socorro, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  5. Brownfield, TX NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  6. Clovis, NM TX 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  7. Hobbs, NM TX 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  8. Chaco Mesa 1:100,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  9. Tularosa, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  10. Las Cruces, NM TX 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  11. Douglas, AZ NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  12. Silver City, NM AZ 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  13. El Paso, TX NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  14. Socorro, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  15. Clifton, AZ NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  16. Historical Land-Cover Change and Land-Use Conversions Global Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A set of three estimates of land-cover types and annual transformations of land use are provided on a global 0.5 x0.5 degree lat/lon grid at annual time steps. The...

  17. Santa Fe, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  18. El Paso, TX NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  19. Santa Fe, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  20. Douglas, AZ NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  1. Fort Sumner, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

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

    NARCIS (Netherlands)

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

    2016-01-01

    Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms

  3. Clovis, NM TX 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  4. Land use/land cover changes and climate: modeling analysis and observational evidence

    NARCIS (Netherlands)

    Pielke sr., R.A.; Pitman, A.; Niyogi, D.; Mahmood, R.; McAlpine, C.; Hossain, F.; Kabat, P.

    2011-01-01

    Agreat deal of attention is devoted to changes in atmospheric composition and the associated regional responses. Less attention is given to the direct influence by human activity on regional climate caused by modification of the atmosphere’s lower boundary—the Earth’s surface. Land use/land cover ch

  5. Albuquerque, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  6. Aztec, NM CO 1:250,000 Quad USGS Land Use/Land Cover, 1986

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...

  7. Applications of the U.S. Geological survey's global land cover product

    Science.gov (United States)

    Reed, B.

    1997-01-01

    The U.S. Geological Survey (USGS), in partnership with several international agencies and universities, has produced a global land cover characteristics database. The land cover data were created using multitemporal analysis of advanced very high resolution radiometer satellite images in conjunction with other existing geographic data. A translation table permits the conversion of the land cover classes into several conventional land cover schemes that are used by ecosystem modelers, climate modelers, land management agencies, and other user groups. The alternative classification schemes include Global Ecosystems, the Biosphere Atmosphere Transfer Scheme, the Simple Biosphere, the USGS Anderson Level 2, and the International Geosphere Biosphere Programme. The distribution system for these data is through the World Wide Web ( the web site address is: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html) or by magnetic media upon special request. The availability of the data over the World Wide Web, in conjunction with the flexible database structure, allows easy data access to a wide range of users. The web site contains a user registration form that allows analysis of the diverse applications of large-area land cover data. Currently, applications are divided among mapping (20 percent), conservation (30 percent), and modeling (35 percent).

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

    Science.gov (United States)

    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.

  9. Crowdsourcing In-Situ Data on Land Cover and Land Use Using Gamification and Mobile Technology

    Directory of Open Access Journals (Sweden)

    Juan Carlos Laso Bayas

    2016-11-01

    Full Text Available Citizens are increasingly becoming involved in data collection, whether for scientific purposes, to carry out micro-tasks, or as part of a gamified, competitive application. In some cases, volunteered data collection overlaps with that of mapping agencies, e.g., the citizen-based mapping of features in OpenStreetMap. LUCAS (Land Use Cover Area frame Sample is one source of authoritative in-situ data that are collected every three years across EU member countries by trained personnel at a considerable cost to taxpayers. This paper presents a mobile application called FotoQuest Austria, which involves citizens in the crowdsourcing of in-situ land cover and land use data, including at locations of LUCAS sample points in Austria. The results from a campaign run during the summer of 2015 suggest that land cover and land use can be crowdsourced using a simple protocol based on LUCAS. This has implications for remote sensing as this data stream represents a new source of potentially valuable information for the training and validation of land cover maps as well as for area estimation purposes. Although the most detailed and challenging classes were more difficult for untrained citizens to recognize, the agreement between the crowdsourced data and the LUCAS data for basic high level land cover and land use classes in homogeneous areas (ca. 80% shows clear potential. Recommendations for how to further improve the quality of the crowdsourced data in the context of LUCAS are provided so that this source of data might one day be accurate enough for land cover mapping purposes.

  10. Land Use and Land Cover - LAND_COVER_PRESETTLEMENT_IDNR_IN: Generalized Presettlement Vegetation Types of Indiana, Circa 1820 (Indiana Department of Natural Resources, Polygon Shapefile)

    Data.gov (United States)

    NSGIC State | GIS Inventory — LAND_COVER_PRESETTLEMENT_IDNR_IN.SHP is a polygon shapefile showing generalized presettlement vegetation types of Indiana, circa 1820. The work was based on original...

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

    Science.gov (United States)

    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. The implications of alternative developer decision-making strategies on land-use and land-cover in an agent-based land market model

    NARCIS (Netherlands)

    Parker, D.C.; Sun, S.; Filatova, T.; Magliocca, N.; Huang, Q.; Brown, D.G.; Riolo, R.; Seppelt, R.; et al, .

    2012-01-01

    Land developers play a key role in land-use and land cover change, as they directly make land development decisions and bridge the land and housing markets. Developers choose and purchase land from rural land owners, develop and subdivide land into parcel lots, build structures on lots, and sell hou

  13. Land-Use and Land Cover Dynamics in South American Temperate Grasslands

    Directory of Open Access Journals (Sweden)

    José M. Paruelo

    2008-12-01

    Full Text Available In the Río de la Plata grasslands (RPG biogeographical region of South America, agricultural activities have undergone important changes during the last 15–18 years because of technological improvements and new national and international market conditions. We characterized changes in the landscape structure between 1985–1989 and 2002–2004 for eight pilot areas distributed across the main regional environmental gradients. These areas incorporated approximately 35% of the 7.5 × 105 km² of the system. Our approach involved the generation of land-use and land cover maps, the analysis of landscape metrics, and the computation of annual transition probabilities between land cover types. All of the information was summarized in 3383 cells of 8 × 8 km. The area covered by grassland decreased from 67.4 to 61.4% between the study periods. This decrease was associated with an increase in the area of annual crops, mainly soybean, sunflower, wheat, and maize. In some subunits of the RPG, i.e., Flat Inland Pampa, the grassland-to-cropland transition probability was high (pG→C = 3.7 × 10−2, whereas in others, i.e., Flooding Pampa, this transition probability was low (pG→C = 6.7 × 10−3. Our description of the magnitude, direction, and spatial distribution of land-use and land cover changes provides a basis from which to develop spatially explicit scenarios of land cover change.

  14. Land Cover Monitoring for Water Resources Management in Angola

    Science.gov (United States)

    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.

  15. Land Use and Land Cover Change in Forest Frontiers: The Role of Household Life Cycles

    Science.gov (United States)

    Walker, Robert

    2002-01-01

    Tropical deforestation remains a critical issue given its present rate and a widespread consensus regarding its implications for the global carbon cycle and biodiversity. Nowhere is the problem more pronounced than in the Amazon basin, home to the world's largest intact, tropical forest. This article addresses land cover change processes at household level in the Amazon basin, and to this end adapts a concept of domestic life cycle to the current institutional environment of tropical frontiers. In particular, it poses a risk minimization model that integrates demography with market-based factors such as transportation costs and accessibility. In essence, the article merges the theory of Chayanov with the household economy framework, in which markets exist for inputs (including labor), outputs, and capital. The risk model is specified and estimated, using survey data for 261 small producers along the Transamazon Highway in the eastern sector of the Brazilian Amazon.

  16. Land Use and Land Cover Change in Forest Frontiers: The Role of Household Life Cycles

    Science.gov (United States)

    Walker, Robert

    2002-01-01

    Tropical deforestation remains a critical issue given its present rate and a widespread consensus regarding its implications for the global carbon cycle and biodiversity. Nowhere is the problem more pronounced than in the Amazon basin, home to the world's largest intact, tropical forest. This article addresses land cover change processes at household level in the Amazon basin, and to this end adapts a concept of domestic life cycle to the current institutional environment of tropical frontiers. In particular, it poses a risk minimization model that integrates demography with market-based factors such as transportation costs and accessibility. In essence, the article merges the theory of Chayanov with the household economy framework, in which markets exist for inputs (including labor), outputs, and capital. The risk model is specified and estimated, using survey data for 261 small producers along the Transamazon Highway in the eastern sector of the Brazilian Amazon.

  17. Global and regional fluxes of carbon from land use and land cover change 1850-2015

    Science.gov (United States)

    Houghton, R. A.; Nassikas, Alexander A.

    2017-03-01

    The net flux of carbon from land use and land cover change (LULCC) is an important term in the global carbon balance. Here we report a new estimate of annual fluxes from 1850 to 2015, updating earlier analyses with new estimates of both historical and current rates of LULCC and including emissions from draining and burning of peatlands in Southeast Asia. For most of the 186 countries included we relied on data from Food and Agriculture Organization to document changes in the areas of croplands and pastures since 1960 and changes in the areas of forests and "other land" since 1990. For earlier years we used other sources of information. We used a bookkeeping model that prescribed changes in carbon density of vegetation and soils for 20 types of ecosystems and five land uses. The total net flux attributable to LULCC over the period 1850-2015 is calculated to have been 145 ± 16 Pg C (1 standard deviation). Most of the emissions were from the tropics (102 ± 5.8 Pg C), generally increasing over time to a maximum of 2.10 Pg C yr-1 in 1997. Outside the tropics emissions were roughly constant at 0.5 Pg C yr-1 until 1940, declined to zero around 1970, and then became negative. For the most recent decade (2006-2015) global net emissions from LULCC averaged 1.11 (±0.35) Pg C yr-1, consisting of a net source from the tropics (1.41 ± 0.17 Pg C yr-1), a net sink in northern midlatitudes (-0.28 ± 0.21 Pg C yr-1), and carbon neutrality in southern midlatitudes.

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

    Science.gov (United States)

    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.

  19. Analysis of Changing Land Use Land Cover in Salinity Affected Coastal Region

    Directory of Open Access Journals (Sweden)

    Vikrant Vijay Singh

    2016-04-01

    Full Text Available Anthropogenic activities have induced many changes in land use over a period of three decades in a salinity affected semi-arid region of coastal Saurashtra in Gujarat. To overcome water scarcity and quality issues, efforts have been undertaken by state authorities to conserve and effectively use surface water resource to supplement the irrigation and domestic water requirements. Surface water schemes implemented in the area have altered the general land use conditions. In the present study, remotely sensed data coupled with ancillary data are used for analysing the land use-land cover change. Supervised classification and post classification techniques are employed to classify various land use-land cover classes and to detect changes, respectively. Landscape pattern change has been studied by analysing the spatial pattern of land use land cover classes structure. The results show that the region has experienced significant changes over a thirty year period. Growth in agricultural activities, policies developed to conserve freshwater runoff, and increase in built-up area, are the main driving forces behind these changes.

  20. Assessing Hydrologic Impacts of Future Land Cover Change ...

    Science.gov (United States)

    Long‐term land‐use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed on the San Pedro River Basin to characterize hydrologic impacts from future urban growth through time. This methodology was then expanded and utilized to characterize the changing hydrology on the South Platte River Basin. Future urban growth is represented by housingdensity maps generated in decadal intervals from 2010 to 2100, produced by the U.S. Environmental Protection Agency (EPA) Integrated Climate and Land‐Use Scenarios (ICLUS) project. ICLUS developed future housing density maps by adapting the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines to the conterminous United States. To characterize hydrologic impacts from future growth, the housing density maps were reclassified to National Land Cover Database (NLCD) 2006 land cover classes and used to parameterize the Soil and Water Assessment Tool (SWAT) using the Automated Geospatial Watershed Assessment (AGWA) tool. The objectives of this project were to 1) develop and describe a methodology for adapting the ICLUS data for use in AGWA as anapproach to evaluate basin‐wide impacts of development on water‐quantity and ‐quality, 2) present initial results from the application of the methodology to

  1. Assessing Hydrologic Impacts of Future Land Cover Change ...

    Science.gov (United States)

    Long‐term land‐use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed on the San Pedro River Basin to characterize hydrologic impacts from future urban growth through time. This methodology was then expanded and utilized to characterize the changing hydrology on the South Platte River Basin. Future urban growth is represented by housingdensity maps generated in decadal intervals from 2010 to 2100, produced by the U.S. Environmental Protection Agency (EPA) Integrated Climate and Land‐Use Scenarios (ICLUS) project. ICLUS developed future housing density maps by adapting the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines to the conterminous United States. To characterize hydrologic impacts from future growth, the housing density maps were reclassified to National Land Cover Database (NLCD) 2006 land cover classes and used to parameterize the Soil and Water Assessment Tool (SWAT) using the Automated Geospatial Watershed Assessment (AGWA) tool. The objectives of this project were to 1) develop and describe a methodology for adapting the ICLUS data for use in AGWA as anapproach to evaluate basin‐wide impacts of development on water‐quantity and ‐quality, 2) present initial results from the application of the methodology to

  2. NDVI and Land Cover Change Analysis Using MODIS data in Tunisia

    Science.gov (United States)

    Kim, D.

    2014-12-01

    Desertification has been one of the global problems in respect of society, economy, and environment. However its cause and effect is diverse and complex, and yet not clearly identified. In order to understand and control desertification, monitoring using satellite images is a major and fundamental part. This study therefore aims to conduct time series analyses for Normalized Difference Vegetation Index (NDVI) and land cover change, and to analyse their area distribution between two different years targeted in Tunisia. NDVI and land cover map are obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), which includes 17 land cover types. First, the time series analysis was conducted every three years from 2002 to 2011. Second, we compared area distribution of NDVI and land cover between 2002 and 2011. We defined that there was 'severe' desertification if NDVI was under 0.24 and classified the severe area within the two images respectively. The extracted area undergone severe desertification in 2011 was then overlaid on the NDVI map of 2002 to see the change. Barren or sparsely vegetated area of 2011 was also extracted first and overlaid on the land cover map of 2002 to observe how the land cover type had been changed from the past. It is estimated that desertification has been expanded in Tunisia as low NDVI value increases and barren or sparsely vegetated area expands while water or forest area decreases. In addition, the NDVI value of 2002 was higher and there was a little distribution of barren and sparsely vegetated area compared to 2011. Based on the result, this study is useful to realize the current state of affairs and the necessity of land planning in Tunisia. The result of the study is expected to be used to cope with desertification and land degradation, and further provides base data for establishing policies. This study was carried out with the support of 'Forest Science & Technology Projects (Project No. S211214L030320)' provided by

  3. Applications of VIC for Climate Land Cover Change Imapacts

    Science.gov (United States)

    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.

  4. Interrelationships between soil cover and plant cover depending on land use

    Directory of Open Access Journals (Sweden)

    Tiina Köster

    2013-05-01

    Full Text Available Interrelationships between soil cover and plant cover of normally developed (or postlithogenic mineral soils are analysed on the basis of four sampling soil groups. The four-link pedo-ecological sequence of analysed soils, rendzinas → brown soils → pseudopodzolic soils → gley-podzols, forms a representative cross section in relation to the normal mineral soils of Estonia. All groups differ substantially from each other in terms of soil properties (calcareousness, acidity, nutrition conditions, profile fabric and humus cover. The primary tasks of the research were (1 to elucidate the main pedo-ecological characteristics of the four soil groups and their suitability for plant cover, (2 to evaluate comparatively soils in terms of productivity, sustainability, biodiversity and environmental protection ability and (3 to analyse possibilities for ecologically sound matching of soil cover with suitable plant cover. On the basis of the same material, the influence of land-use change on humus cover (epipedon fabric, properties of the entire soil cover and soil–plant interrelationship were also analysed. An ecosystem approach enables us to observe particularities caused by specific properties of a soil type (species, variety in biological turnover and in the formation of biodiversity.

  5. Accuracy assessment of global land cover maps: lessons learnt from the GlobCover and GlobCorine experiences

    NARCIS (Netherlands)

    Defourny, P.; Bontemps, S.; Obsomer, V.; Schouten, L.; Bartalev, S.; Herold, M.; Bicheron, P.; Bogaert, van E.; Leroy, M.; Arino, O.

    2010-01-01

    The validation of global land cover products becomes a critical and challenging issue as more global products are made available more regularly to the international community. The GlobCover 2005 product delivered in 2008 was the first global land cover product at 300 m resolution. Later on, the

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

    Science.gov (United States)

    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.

  7. Modelling the effects of land-use and land-cover change on water availability in the Jordan River region

    Directory of Open Access Journals (Sweden)

    R. Schaldach

    2009-08-01

    Full Text Available Within the GLOWA Jordan River project, a first-time overview of the current and possible future land and water conditions of a major part of the Eastern Mediterranean region (ca. 100 000 km2 is given. First, we applied the hydrological model TRAIN to simulate current water availability (runoff and groundwater recharge and irrigation water demand on a 1 km×1 km spatial resolution. The results demonstrate the scarcity of water resources in the study region, with extremely low values of water availability in the semi-arid and arid parts. Then, a set of four divergent scenarios on the future of water has been developed using a stakeholder driven approach. Relevant drivers for land-use/land-cover change were fed into the LandSHIFT.R model to produce land-use and land-cover maps for the different scenarios. These maps were used as input to TRAIN in order to generate scenarios of water availability and irrigation water demand for the region. For this study, two intermediate scenarios were selected, with projected developments ranging between optimistic and pessimistic futures (with regard to social and economic conditions in the region. Given that climate conditions remain unchanged, the simulations show both increases and decreases in water availability, depending on the future pattern of natural and agricultural vegetation and the related dominance of hydrological processes.

  8. Possibilities of MERIS for sub-pixel regional land cover mapping

    NARCIS (Netherlands)

    Zurita Milla, R.; Schaepman, M.E.; Clevers, J.G.P.W.

    2005-01-01

    The Medium Resolution Imaging Spectrometer, MERIS, on board of ENVISAT-1 fulfils the information gap between the current high and low spatial resolution sensors. In this respect, the use of MERIS full resolution data (300 m pixel size) has a great potential for regional and global land cover mapping

  9. Using the FORE-SCE model to project land-cover change in the southeastern United States

    Science.gov (United States)

    Sohl, T.; Sayler, K.

    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

  10. EASE-Grid Land-Ocean-Coastline-Ice Masks Derived from Boston University MODIS/Terra Land Cover Data

    Data.gov (United States)

    National Aeronautics and Space Administration — These Land-Ocean-Coastline-Ice (LOCI) files provide land classification masks derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product...

  11. 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

    Science.gov (United States)

    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.

  12. Enhancing the performance of regional land cover mapping

    Science.gov (United States)

    Wu, Weicheng; Zucca, Claudio; Karam, Fadi; Liu, Guangping

    2016-10-01

    Different pixel-based, object-based and subpixel-based methods such as time-series analysis, decision-tree, and different supervised approaches have been proposed to conduct land use/cover classification. However, despite their proven advantages in small dataset tests, their performance is variable and less satisfactory while dealing with large datasets, particularly, for regional-scale mapping with high resolution data due to the complexity and diversity in landscapes and land cover patterns, and the unacceptably long processing time. The objective of this paper is to demonstrate the comparatively highest performance of an operational approach based on integration of multisource information ensuring high mapping accuracy in large areas with acceptable processing time. The information used includes phenologically contrasted multiseasonal and multispectral bands, vegetation index, land surface temperature, and topographic features. The performance of different conventional and machine learning classifiers namely Malahanobis Distance (MD), Maximum Likelihood (ML), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs) and Random Forests (RFs) was compared using the same datasets in the same IDL (Interactive Data Language) environment. An Eastern Mediterranean area with complex landscape and steep climate gradients was selected to test and develop the operational approach. The results showed that SVMs and RFs classifiers produced most accurate mapping at local-scale (up to 96.85% in Overall Accuracy), but were very time-consuming in whole-scene classification (more than five days per scene) whereas ML fulfilled the task rapidly (about 10 min per scene) with satisfying accuracy (94.2-96.4%). Thus, the approach composed of integration of seasonally contrasted multisource data and sampling at subclass level followed by a ML classification is a suitable candidate to become an operational and effective regional land cover mapping method.

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

    Science.gov (United States)

    Elhag, Mohamed; Boteva, Silvena

    2016-10-01

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

  14. Land Use and Land Cover, Land Use Inventory for Planning, Published in 2008, 1:4800 (1in=400ft) scale, Jefferson County Land Information Office.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of 2008. It is described as...

  15. Land and Forest Management by Land Use/ Land Cover Analysis and Change Detection Using Remote Sensing and GIS

    Directory of Open Access Journals (Sweden)

    Ankana

    2016-01-01

    Full Text Available Remote sensing and Geographical Information System (GIS are the most effective tools in spatial data analysis. Natural resources like land, forest and water, these techniques have proved a valuable source of information generation as well as in the management and planning purposes. This study aims to suggest possible land and forest management strategies in Chakia tahsil based on land use and land cover analysis and the changing pattern observed during the last ten years. The population of Chakia tahsil is mainly rural in nature. The study has revealed that the northern part of the region, which offers for the settlement and all the agricultural practices constitutes nearly 23.48% and is a dead level plain, whereas the southern part, which constitute nearly 76.6% of the region is characterized by plateau and is covered with forest. The southern plateau rises abruptly from the northern alluvial plain with a number of escarpments. The contour line of 100 m mainly demarcates the boundary between plateau and plain. The plateau zone is deeply dissected and highly rugged terrain. The resultant topography comprises of a number of mesas and isolated hillocks showing elevation differences from 150 m to 385 m above mean sea level. Being rugged terrain in the southern part, nowadays human encroachment are taking place for more land for the cultivation. The changes were well observed in the land use and land cover in the study region. A large part of fallow land and open forest were converted into cultivated land.

  16. A comprehensive change detection method for updating the National Land Cover Database to circa 2011

    Science.gov (United States)

    Jin, Suming; Yang, Limin; Danielson, Patrick; Homer, Collin G.; Fry, Joyce; Xian, George

    2013-01-01

    The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and

  17. Land cover change in Colombia: surprising forest recovery trends between 2001 and 2010.

    Directory of Open Access Journals (Sweden)

    Ana María Sánchez-Cuervo

    Full Text Available 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 km(2 while 264 had a net loss (11,129 km(2, which resulted in a net gain of 16,963 km(2 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.

  18. Analysis of the Effects of Different Land Use and Land Cover Classification on Surface Meteorological Variables using WRF Model

    Science.gov (United States)

    Sati, A. P.

    2015-12-01

    The continuous population growth and the subsequent economic expansion over centuries have been the primary drivers of land use /land cover (LULC) changes resulting in the environmental changes across the globe. Most of the urban areas being developed today are on the expense of agricultural or barren lands and the changes result from various practices such as deforestation, changing agriculture practices, rapid expansion of urban centers etc.For modeling applications, classification of land use is important and periodic updates of land cover are necessary to capture change due to LULC changes.Updated land cover and land use data derived from satellites offer the possibility of consistent and regularly collected information on LULC. In this study we explore the application of Landsat based LULC classification inWeather Research and Forecasting (WRF) model in predicting the meteorology over Delhi, India. The supervised classification of Landsat 8 imagery over Delhi region is performed which update the urban extent as well as other Land use for the region. WRF model simulations are performed using LULC classification from Landsat data, United States Geological Survey (USGS) and Moderate Resolution Imaging Spectroradiometer (MODIS) for various meteorological parameters. Modifications in LULC showed a significant effect on various surface meteorological parameters such as temperature, humidity, wind circulations and other underlying surface parameters. There is a considerable improvement in the spatial distribution of the surface meteorological parameters with correction in input LULC. The study demonstrates the improved LULC classification from Landsat data than currently in vogue and their potential to improve numerical weather simulations especially for expanding urban areas.The continuous population growth and the subsequent economic expansion over centuries have been the primary drivers of land use /land cover (LULC) changes resulting in the environmental changes

  19. Spatial resolution requirements for urban land cover mapping from space

    Science.gov (United States)

    Todd, William J.; Wrigley, Robert C.

    1986-01-01

    Very low resolution (VLR) satellite data (Advanced Very High Resolution Radiometer, DMSP Operational Linescan System), low resolution (LR) data (Landsat MSS), medium resolution (MR) data (Landsat TM), and high resolution (HR) satellite data (Spot HRV, Large Format Camera) were evaluated and compared for interpretability at differing spatial resolutions. VLR data (500 m - 1.0 km) is useful for Level 1 (urban/rural distinction) mapping at 1:1,000,000 scale. Feature tone/color is utilized to distinguish generalized urban land cover using LR data (80 m) for 1:250,000 scale mapping. Advancing to MR data (30 m) and 1:100,000 scale mapping, confidence in land cover mapping is greatly increased, owing to the element of texture/pattern which is now evident in the imagery. Shape and shadow contribute to detailed Level II/III urban land use mapping possible if the interpreter can use HR (10-15 m) satellite data; mapping scales can be 1:25,000 - 1:50,000.

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

    Science.gov (United States)

    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.

  1. Resultant Land Use and Land Cover Change from Oil Spillage using Remote Sensing and GIS

    Directory of Open Access Journals (Sweden)

    E.O. Omodanisi

    2013-07-01

    Full Text Available The spill of oil into the environment threatens the existence of vegetation. This study identified the coastal area of Lagos impacted by oil spill, explosion and fire; using Landsat ETM+2005 and Ikonos 2007 and evaluated the effect. Subsequently, geo-spatial database was created for monitoring of oil pipelines Right of Way (ROW in the area. The biggest land use land cover changes were the high forest and the light forest classes of mangrove vegetation by 22.2 and 15.5% respectively. The control quadrat sampled had the highest species diversity index of 0.6758 compared to the others. The study concluded that oil spill had affected the land use land cover as well as provided oil spill emergency response centres sites as a Spatial Decision Support System (SDSS for oil pipeline management.

  2. Historical Image Registration and Land-Use Land-Cover Change Analysis

    Directory of Open Access Journals (Sweden)

    Fang-Ju Jao

    2014-12-01

    Full Text Available Historical aerial images are important to retain past ground surface information. The land-use land-cover change in the past can be identified using historical aerial images. Automatic historical image registration and stitching is essential because the historical image pose information was usually lost. In this study, the Scale Invariant Feature Transform (SIFT algorithm was used for feature extraction. Subsequently, the present study used the automatic affine transformation algorithm for historical image registration, based on SIFT features and control points. This study automatically determined image affine parameters and simultaneously transformed from an image coordinate system to a ground coordinate system. After historical aerial image registration, the land-use land-cover change was analyzed between two different years (1947 and 1975 at the Tseng Wen River estuary. Results show that sandbars and water zones were transformed into a large number of fish ponds between 1947 and 1975.

  3. Land management and land-cover change have impacts of similar magnitude on surface temperature

    DEFF Research Database (Denmark)

    Luyssaert, Sebastiaan; Jammet, Mathilde; Stoy, Paul C.

    2014-01-01

    Anthropogenic changes to land cover (LCC) remain common, but continuing land scarcity promotes the widespread intensification of land management changes (LMC) to better satisfy societal demand for food, fibre, fuel and shelter1. The biophysical effects of LCC on surface climate are largely...... understood2-5, particularly for the boreal6 and tropical zones7, but fewer studies have investigated the biophysical consequences of LMC; that is, anthropogenic modification without a change in land cover type. Harmonized analysis of ground measurements and remote sensing observations of both LCC and LMC...... revealed that, in the temperate zone, potential surface cooling from increased albedo is typically offset by warming from decreased sensible heat fluxes, with the net effect being a warming of the surface. Temperature changes from LMC and LCC were of the same magnitude, and averaged 2 K at the vegetation...

  4. Historical Image Registration and Land-Use Land-Cover Change Analysis

    OpenAIRE

    Fang-Ju Jao; Hone-Jay Chu; Yi-Hsing Tseng

    2014-01-01

    Historical aerial images are important to retain past ground surface information. The land-use land-cover change in the past can be identified using historical aerial images. Automatic historical image registration and stitching is essential because the historical image pose information was usually lost. In this study, the Scale Invariant Feature Transform (SIFT) algorithm was used for feature extraction. Subsequently, the present study used the automatic affine transformation algorithm for h...

  5. Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis

    Science.gov (United States)

    Sharpe, Jennifer B.; Soong, David T.

    2015-01-01

    The U.S. Army Corps of Engineers (USACE), Chicago District, is responsible for monitoring and computation of the quantity of Lake Michigan water diverted by the State of Illinois. As part of this effort, the USACE uses the Hydrological Simulation Program–FORTRAN (HSPF) with measured meteorological data inputs to estimate runoff from the Lake Michigan diversion special contributing areas (SCAs), the North Branch Chicago River above Niles and the Little Calumet River above South Holland gaged basins, and the Lower Des Plaines and the Calumet ungaged that historically drained to Lake Michigan. These simulated runoffs are used for estimating the total runoff component from the diverted Lake Michigan watershed, which is accountable to the total diversion by the State of Illinois. The runoff is simulated from three interpreted land cover types in the HSPF models: impervious, grass, and forest. The three land cover data types currently in use were derived from aerial photographs acquired in the early 1990s.

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

    Science.gov (United States)

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

    2009-01-01

    ), which is critical nursing ground for many Gulf fish species. A survey of Mobile Bay SAV showed widespread decreases since the 1940s. Prior to our project, coastal environmental managers in Baldwin and Mobile counties needed more understanding of the historical LULC for properly assessing the impacts of urbanization. In particular, more information on the location and extent of changing urbanization LULC patterns was needed to aid LULC planning and to assess predictions of future LULC patterns. Our products will assist the coastal environmental managers and land-use planners in making better community growth planning decisions. Our project also will help to establish a historical baseline of LULC distributions, which is a fundamental need in any stewardship plan. The primary research objective of our project was to produce historic and current geospatial LULC change products across a 34-year time frame. A multi-decadal coastal LULC change product was the major project deliverable. The geographic extent and nature of change was quantified and assessed for the upland herbaceous, barren, open water, urban, upland forest, woody wetland, and non-woody wetlanddominated land cover types. We focused on regional analyses of decadal-scale urban expansion and watershed-scaled analyses of LULC change for multiple areas of concern to the Mobile Bay NEP (Figure A). We used the following dates to derive LULC classification products from Landsat data: 1974, 1979, 1984, 1988, 1991, 1996, 2001, 2005, and 2008. We assessed the accuracy of our products using randomly sampled locations and digital geospatial reference data including field survey data, high resolution orthorectified aerial photography, high resolution multispectral and panchromatic satellite data displays (from QuickBird and Corona sensors), digital elevation model data, and National Wetlands Inventory wetland cover type data. NOAA s Coastal Change Assessment Program s (C-CAP) and National Land Cover Database (NLCD) procts

  7. Land use, land cover, and climate change across the Mississippi Basin: Impacts on selected land and water resources

    Science.gov (United States)

    Foley, Jonathan A.; Kucharik, Christopher J.; Twine, Tracy E.; Coe, Michael T.; Donner, Simon D.

    The Mississippi Basin is the third largest drainage basin in the world and is home to one of the most productive agricultural regions on Earth. Here we discuss how land use/land cover change and climatic variability may be affecting some key environmental processes across the Mississippi and how these, in turn, affect the flow of selected ecosystem goods and services in the region. Specifically, we consider the recent history of land use/land cover change, crop yields, basin river flow and hydrology, and large-scale water quality in the Mississippi Basin. We find that agricultural activities may have had a profound influence on the basin and may have shifted the flow of many ecosystem goods and services into agricultural commodities, at the expense of altering many of the important biogeochemical linkages between atmosphere, land, and water.

  8. Effect of land use/cover change on land surface temperatures - The Nile Delta, Egypt

    Science.gov (United States)

    Hereher, Mohamed E.

    2017-02-01

    In this study remote sensing techniques were employed to investigate the impact of land use/cover change on land surface temperatures (LST) for a highly dynamic landscape, i.e. the Nile Delta. Land use change was determined from analyzing a 15 years of bi-monthly normalized difference vegetation index (NDVI) dataset acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite along with a synchronized 13 years of bi-monthly LST dataset retrieved from MODIS Aqua satellite. Time series analysis for NDVI and LST data was carried out at selected locations experiencing land use change. Mean LST change was determined for each location before and after the land use change. Results indicate that NDVI composite data for 15 years proved sufficient for delineating land use change. Significant spatial changes include the transformation from agriculture to urban land, which increased the LST by 1.7 °C during the 13 years and the transformation of bare land to agriculture, which decreased the LST by 0.52 °C for the same period. Due to the explosive population growth in the Nile Delta, urban encroachment upon agricultural land could, hence, promote a prolonged regional warming by modifying the micro-climate and other climate-related phenomena.

  9. Land Use and Land Cover, Forest cover data for northeast Georgia - 1991, Published in 2004, 1:100000 (1in=8333ft) scale, Northeast Georgia Regional Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:100000 (1in=8333ft) scale, was produced all or in part from Orthoimagery information as of 2004. It is described...

  10. Land Use and Land Cover, Forest cover data for northeast Georgia - 1998, Published in 2004, 1:100000 (1in=8333ft) scale, Northeast Georgia Regional Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:100000 (1in=8333ft) scale, was produced all or in part from Orthoimagery information as of 2004. It is described...

  11. Land Use and Land Cover, Forest cover data for northeast Georgia - 1985, Published in 2004, 1:100000 (1in=8333ft) scale, Northeast Georgia Regional Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:100000 (1in=8333ft) scale, was produced all or in part from Orthoimagery information as of 2004. It is described...

  12. Land Use and Land Cover, Forest cover data for northeast Georgia - 2002, Published in 2004, 1:100000 (1in=8333ft) scale, Northeast Georgia Regional Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:100000 (1in=8333ft) scale, was produced all or in part from Orthoimagery information as of 2004. It is described...

  13. LandEx - Fast, FOSS-Based Application for Query and Retrieval of Land Cover Patterns

    Science.gov (United States)

    Netzel, P.; Stepinski, T.

    2012-12-01

    The amount of satellite-based spatial data is continuously increasing making a development of efficient data search tools a priority. The bulk of existing research on searching satellite-gathered data concentrates on images and is based on the concept of Content-Based Image Retrieval (CBIR); however, available solutions are not efficient and robust enough to be put to use as deployable web-based search tools. Here we report on development of a practical, deployable tool that searches classified, rather than raw image. LandEx (Landscape Explorer) is a GeoWeb-based tool for Content-Based Pattern Retrieval (CBPR) contained within the National Land Cover Dataset 2006 (NLCD2006). The USGS-developed NLCD2006 is derived from Landsat multispectral images; it covers the entire conterminous U.S. with the resolution of 30 meters/pixel and it depicts 16 land cover classes. The size of NLCD2006 is about 10 Gpixels (161,000 x 100,000 pixels). LandEx is a multi-tier GeoWeb application based on Open Source Software. Main components are: GeoExt/OpenLayers (user interface), GeoServer (OGC WMS, WCS and WPS server), and GRASS (calculation engine). LandEx performs search using query-by-example approach: user selects a reference scene (exhibiting a chosen pattern of land cover classes) and the tool produces, in real time, a map indicating a degree of similarity between the reference pattern and all local patterns across the U.S. Scene pattern is encapsulated by a 2D histogram of classes and sizes of single-class clumps. Pattern similarity is based on the notion of mutual information. The resultant similarity map can be viewed and navigated in a web browser, or it can download as a GeoTiff file for more in-depth analysis. The LandEx is available at http://sil.uc.edu

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

    Science.gov (United States)

    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.

  15. NLCD - MODIS land cover- albedo dataset for the continental United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — The NLCD-MODIS land cover-albedo database integrates high-quality MODIS albedo observations with areas of homogeneous land cover from NLCD. The spatial resolution...

  16. EnviroAtlas - Paterson, NJ - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Paterson, New Jersey EnviroAtlas Meter-Scale Urban Land Cover (MULC) data comprises approximately 66 km2 around the city of Paterson. The land cover data were...

  17. EnviroAtlas - Des Moines, IA - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Des Moines, IA EnviroAtlas Meter-Scale Urban Land Cover (MULC) Data were generated from the High Resolution Land Cover (HRLC) product created by the Iowa...

  18. EnviroAtlas - Paterson, NJ - One Meter Resolution Urban Land Cover (2010) Web Service

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Paterson, New Jersey EnviroAtlas One Meter-scale Urban Land Cover Web Service comprises approximately 66 km2 around the city of Paterson. The land cover data...

  19. EnviroAtlas - Paterson, NJ - One Meter Resolution Urban Land Cover Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Paterson, New Jersey EnviroAtlas One Meter-scale Urban Land Cover data comprises approximately 66 km2 around the city of Paterson. The land cover data were...

  20. EnviroAtlas -- Paterson, New Jersey -- One Meter Resolution Urban Land Cover Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Paterson, New Jersey EnviroAtlas One Meter-scale Urban Land Cover data comprises approximately 66 km2 around the city of Paterson. The land cover data were...

  1. EnviroAtlas - Paterson, New Jersey - One Meter Resolution Urban Land Cover (2010) Web Service

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Paterson, New Jersey EnviroAtlas One Meter-scale Urban Land Cover Web Service comprises approximately 66 km2 around the city of Paterson. The land cover data...

  2. EnviroAtlas -- Des Moines, IA -- One Meter Resolution Urban Land Cover Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Des Moines, IA EnviroAtlas Meter-scale Urban Land Cover Data were generated from the High Resolution Land Cover (HRLC) product created by the Iowa Department of...

  3. C-CAP Santa Cruz 2001 era High Resolution Land Cover Metadata

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents land cover for the San Lorenzo River basin in Santa Cruz County, California derived from high resolution imagery. The land cover features in...

  4. LAND USE LAND COVER DYNAMICS OF NILGIRIS DISTRICT, INDIA INFERRED FROM SATELLITE IMAGERIES

    Directory of Open Access Journals (Sweden)

    P. Nalina

    2014-01-01

    Full Text Available Land use Land cover changes are critical components in managing natural resources especially in hilly region as they trigger the erosion of soil and thus making the zone highly vulnerable to landslides. The Nilgiris district of Tamilnadu state in India is the first biosphere in Western Ghats region with rare species of flora and fauna and often suffered by frequent landslides. Therefore in this present study land use land cover dynamics of Nilgiri district has been studied from 1990 to 2010 using Satellite Remote Sensing Technique. The temporal changes of land use and land cover changes of Nilgiris district over the period of 1990 to 2010 were monitored using LISS I and LISS III of IRS 1A and IRS-P6 satellites. Land use dynamics were identified using Maximum likelihood classification under supervised classification technique. From the remote sensing study, it is found that during the study period of 1990 to 2010, area of dense forest increased by 27.17%, forest plantation area decreased by 54.64%. Conversion of forest plantation, Range land and open forest by agriculture and settlement leading to soil erosion and landslides. Tea plantation increased by 33.95% and agricultural area for plantation of vegetables increased rapidly to 217.56% in the mountain steep area. The accuracy of classification has been assessed by forming confusion matrix and evaluating kappa coefficient. The overall accuracy has been obtained as 83.7 and 89.48% for the years 1990 and 2010 respectively. The kappa coefficients were reported as 0.80 and 0.88 respectively for the years 1990 and 2010.

  5. Land Cover Mapping Using SENTINEL-1 SAR Data

    Science.gov (United States)

    Abdikan, S.; Sanli, F. B.; Ustuner, M.; Calò, F.

    2016-06-01

    In this paper, the potential of using free-of-charge Sentinel-1 Synthetic Aperture Radar (SAR) imagery for land cover mapping in urban areas is investigated. To this aim, we use dual-pol (VV+VH) Interferometric Wide swath mode (IW) data collected on September 16th 2015 along descending orbit over Istanbul megacity, Turkey. Data have been calibrated, terrain corrected, and filtered by a 5x5 kernel using gamma map approach. During terrain correction by using a 25m resolution SRTM DEM, SAR data has been resampled resulting into a pixel spacing of 20m. Support Vector Machines (SVM) method has been implemented as a supervised pixel based image classification to classify the dataset. During the classification, different scenarios have been applied to find out the performance of Sentinel-1 data. The training and test data have been collected from high resolution image of Google Earth. Different combinations of VV and VH polarizations have been analysed and the resulting classified images have been assessed using overall classification accuracy and Kappa coefficient. Results demonstrate that, combining opportunely dual polarization data, the overall accuracy increases up to 93.28% against 73.85% and 70.74% of using individual polarization VV and VH, respectively. Our preliminary analysis points out that dual polarimetric Sentinel-1SAR data can be effectively exploited for producing accurate land cover maps, with relevant advantages for urban planning and management of large cities.

  6. Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges

    Directory of Open Access Journals (Sweden)

    Annett Bartsch

    2016-11-01

    Full Text Available Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wildlife habitats. Later, in the 1990s, up-scaling of in situ measurements became central to the discipline of land cover mapping on local to regional scales at several sites across the Arctic. This includes the Kuparuk basin in Alaska, the Usa basin and the Lena Delta in Russia. All of these multi-purpose land cover maps have been derived from Landsat data. High resolution maps (from optical satellite data serve frequently as input for the characterization of periglacial features and also flux tower footprints in recent studies. The most used map to address circumpolar issues is the CAVM (Circum Arctic Vegetation Map based on AVHRR (1 km and has been manually derived. It provides the required thematic detail for many applications, but is confined to areas north of the treeline, and it is limited in spatial detail. A higher spatial resolution circumpolar land cover map with sufficient thematic content would be beneficial for a range of applications. Such a land cover classification should be compatible with existing global maps and applicable for multiple purposes. The thematic content of existing global maps has been assessed by comparison to the CAVM and regional maps. None of the maps provides the required thematic detail. Spatial resolution has been compared to used classes for local to regional applications. The required thematic detail increases with spatial resolution since coarser datasets are usually applied over larger areas covering more relevant landscape units. This is especially of concern when the entire Arctic is addressed. A spatial

  7. Land cover change detection in West Jilin using ETM+ images

    Institute of Scientific and Technical Information of China (English)

    Edward M.Osei,Jr.; ZHOU Yun-xuan

    2004-01-01

    In order to assess the information content and accuracy ofLandsat ETM+ digital images in land cover change detection,change-detection techniques of image differencing,normalized difference vegetation index,principal components analysis and tasseled-cap transformation were applied to yield 13 images. These images were thresholded into change and no change areas. The thresholded images were then checked in terms of various accuracies. The experiment results show that kappa coefficients of the 13 images range from 48.05 ~78.09. Different images do detect different types of changes. Images associated with changes in the near-infrared-reflectance or greenness detects crop-type changes and changes between vegetative and non-vegetative features. A unique means of using only Landsat imagery without reference data for the assessment of change in arid land are presented. Images of 12th June, 2000 and 2nd June, 2002 are used to validate the means. Analyses of standard accuracy and spatial agreement are performed to compare the new images (hereafter called "change images" ) representing the change between the two dates. Spatial agreement evaluates the conformity in the classified "change pixels" and "no-change pixels" at the same location on different change images and comprehensively examines the different techniques. This method would enable authorities to monitor land degradation efficiently and accurately.

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

    Science.gov (United States)

    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.

  9. Relative Efficiency of Surface Energy Budgets Over Different Land Covers

    Science.gov (United States)

    Yang, Jiachuan

    The partitioning of available solar energy into different fluxes at the Earth's surface is important in determining different physical processes, such as turbulent transport, subsurface hydrology, land-atmospheric interactions, etc. Direct measurements of these turbulent fluxes were carried out using eddy-covariance (EC) towers. However, the distribution of EC towers is sparse due to relatively high cost and practical difficulties in logistics and deployment. As a result, data is temporally and spatially limited and is inadequate to be used for researches at large scales, such as regional and global climate modeling. Besides field measurements, an alternative way is to estimate turbulent fluxes based on the intrinsic relations between surface energy budget components, largely through thermodynamic equilibrium. These relations, referred as relative efficiency, have been included in several models to estimate the magnitude of turbulent fluxes in surface energy budgets such as latent heat and sensible heat. In this study, three theoretical models based on the lumped heat transfer model, the linear stability analysis and the maximum entropy principle respectively, were investigated. Model predictions of relative efficiencies were compared with turbulent flux data over different land covers, viz. lake, grassland and suburban surfaces. Similar results were observed over lake and suburban surface but significant deviation is found over vegetation surface. The relative efficiency of outgoing longwave radiation is found to be orders of magnitude deviated from theoretic predictions. Meanwhile, results show that energy partitioning process is influenced by the surface water availability to a great extent. The study provides insight into what property is determining energy partitioning process over different land covers and gives suggestion for future models.

  10. Land cover/land use change in semi-arid Inner Mongolia: 1992-2004

    Energy Technology Data Exchange (ETDEWEB)

    John, Ranjeet; Chen Jiquan; Lu Nan; Wilske, Burkhard, E-mail: ranjeet.john@utoledo.ed [Department of Environmental Sciences, University of Toledo, Toledo, OH 43606 (United States)

    2009-10-15

    The semi-arid grasslands in Inner Mongolia (IM) are under increasing stress owing to climate change and rapid socio-economic development in the recent past. We investigated changes in land cover/land use and landscape structure between 1992 and 2004 through the analysis of AVHRR and MODIS derived land cover data. The scale of analysis included the regional level (i.e. the whole of IM) as well as the level of the dominant biomes (i.e. the grassland and desert). We quantified proportional change, rate of change and the changes in class-level landscape metrics using the landscape structure analysis program FRAGSTATS. The dominant land cover types, grassland and barren, 0.47 and 0.27 million km{sup 2}, respectively, have increased proportionally. Cropland and urban land use also increased to 0.15 million km{sup 2} and 2197 km{sup 2}, respectively. However, the results further indicated increases in both the homogeneity and fragmentation of the landscape. Increasing homogeneity was mainly related to the reduction in minority cover types such as savanna, forests and permanent wetlands and increasing cohesion, aggregation index and clumpy indices. Conversely, increased fragmentation of the landscape was based on the increase in patch density and the interspersion/juxtaposition index (IJI). It is important to note the socio-economic growth in this fragile ecosystem, manifested by an increasing proportion of agricultural and urban land use not just at the regional level but also at the biome level in the context of regional climate change and increasing water stress.

  11. Standard land-cover classification scheme for remote-sensing applications in South Africa

    CSIR Research Space (South Africa)

    Thompson, M

    1996-01-01

    Full Text Available For large areas, satellite remote-sensing techniques have now become the single most effective method for land-cover and land-use data acquisition. However, the majority of land-cover (and land-use) classification schemes used have been developed...

  12. Land-Cover Legacy Effects on Arbuscular Mycorrhizal Abundance in Human and Wildlife Dominated Systems in Tropical Savanna

    Directory of Open Access Journals (Sweden)

    Geofrey E. Soka

    2016-01-01

    Full Text Available Arbuscular mycorrhizal fungi (AMF can be important mutualists to plant hosts in acquiring soil nutrients. Past work has not explored whether previous land-cover history influences current AMF abundance in croplands and whether different land-cover histories in grazed but not cultivated areas influence AMF. This study was conducted to assess the effects of land-cover history in and near Serengeti National Park on AMF abundance in areas with three different land uses. The results showed that land-cover history influenced a number of soil physicochemical properties following conversion of grassland to cropland or woodland to cropland during the past 27 years. Different original land cover generally did not significantly influence current AMF abundance in croplands or livestock-grazed soils. However, livestock-grazed current grasslands that were formerly woodlands had lower AMF abundance than sites that had been grasslands since 1984. These results suggest that lower AMF abundance in livestock-grazed and cropland areas as compared to protected wildlife-grazed areas may reflect reduced total carbon inputs and higher disturbance and are not strongly influenced by the legacy of previous land cover. Given that recent studies have detected legacy effects on AMF, such effects may reflect more the impact on the taxonomic composition of AMF rather than their total abundance.

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Kerry A Brown

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

  15. Three distinct global estimates of historical land-cover change and land-use conversions for over 200 years

    Institute of Scientific and Technical Information of China (English)

    Prasanth MEIYAPPAN; Atul K.JAIN

    2012-01-01

    Earth's land cover has been extensively transformed over time due to both human activities and natural causes.Previous global studies have focused on developing spatial and temporal pattems of dominant human land-use activities (e.g.,cropland,pastureland,urban land,wood harvest).Process-based modeling studies adopt different strategies to estimate the changes in land cover by using these land-use data sets in combination with a potential vegetation map,and subsequently use this information for impact assessments.However,due to unaccounted changes in land cover (resulting from both indirect anthropogenic and natural causes),heterogeneity in land-use/cover (LUC) conversions among grid cells,even for the same land use activity,and uncertainty associated with potential vegetation mapping and historical estimates of human land use result in land cover estimates that are substantially different compared to results acquired from remote sensing observations.Here,we present a method to implicitly account for the differences arising from these uncertainties in order to provide historical estimates of land cover that are consistent with satellite estimates for recent years.Due to uncertainty in historical agricultural land use,we use three widely accepted global estimates of cropland and pastureland in combination with common wood harvest and urban land data sets to generate three distinct estimates of historical land-cover change and underlying LUC conversions.Hence,these distinct historical reconstructions offer a wide range of plausible regional estimates of uncertainty and the extent to which different ecosystems have undergone changes.The annual land cover maps and LUC conversion maps are reported at 0.5°×0.5° resolution and describe the area of 28 landcover types and respective underlying land-use transitions.The reconstructed data sets are relevant for studies addressing the impact of land-cover change on biogeophysics,biogeochemistry,water cycle,and global climate.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  20. Land Use and Land Cover Changes under Climate Uncertainty: Modelling the Impacts on Hydropower Production in Western Africa

    Directory of Open Access Journals (Sweden)

    Salomon Obahoundje

    2017-01-01

    Full Text Available The Bui hydropower plant plays a vital role in the socio-economic development of Ghana. This paper attempt to explore the combined effects of climate-land use land cover change on power production using the (WEAP model: Water Evaluation and Planning system. The historical analysis of rainfall and stream flow variability showed that the annual coefficient of variation of rainfall and stream flow are, respectively, 8.6% and 60.85%. The stream flow varied greatly than the rainfall, due to land use land cover changes (LULC. In fact, the LULC analysis revealed important changes in vegetative areas and water bodies. The WEAP model evaluation showed that combined effects of LULC and climate change reduce water availability for all of demand sectors, including hydropower generation at the Bui hydropower plant. However, it was projected that Bui power production will increase by 40.7% and 24.93%, respectively, under wet and adaptation conditions, and decrease by 46% and 2.5%, respectively, under dry and current conditions. The wet condition is defined as an increase in rainfall by 14%, the dry condition as the decrease in rainfall by 15%; current account is business as usual, and the adaptation is as the efficient use of water for the period 2012–2040.

  1. A Reliability-Based Multi-Algorithm Fusion Technique in Detecting Changes in Land Cover

    Directory of Open Access Journals (Sweden)

    Jiangping Chen

    2013-03-01

    Full Text Available Detecting land use or land cover changes is a challenging problem in analyzing images. Change-detection plays a fundamental role in most of land use or cover monitoring systems using remote-sensing techniques. The reliability of individual automatic change-detection algorithms is currently below operating requirements when considering the intrinsic uncertainty of a change-detection algorithm and the complexity of detecting changes in remote-sensing images. In particular, most of these algorithms are only suited for a specific image data source, study area and research purpose. Only a number of comprehensive change-detection methods that consider the reliability of the algorithm in different implementation situations have been reported. This study attempts to explore the advantages of combining several typical change-detection algorithms. This combination is specifically designed for a highly reliable change-detection task. Specifically, a fusion approach based on reliability is proposed for an exclusive land use or land cover change-detection. First, the reliability of each candidate algorithm is evaluated. Then, a fuzzy comprehensive evaluation is used to generate a reliable change-detection approach. This evaluation is a transformation between a one-way evaluation matrix and a weight vector computed using the reliability of each candidate algorithm. Experimental results reveal that the advantages of combining these distinct change-detection techniques are evident.

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

    Science.gov (United States)

    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.

  3. Land use and land cover change processes in China's eastern Loess Plateau

    Institute of Scientific and Technical Information of China (English)

    JinChang Li; HaiXia Liu; Yong Liu; ZhiZhu Su; ZiQiang Du

    2015-01-01

    Using Landsat remote sensing images, we analyzed changes in each land use type and transitions among different land use types during land use and land cover change (LUCC) in Ningwu County, located in the eastern Loess Plateau of China, from 1990 to 2010. We found that grassland, woodland, and farmland were the main land use types in the study area, and the area of each type changed slightly from 1990 to 2010, whereas the area of water, construction land, and unused land increased greatly. For the whole area, the net change and total change were insignificant due to weak human activity intensity in most of the study area, and the LUCC was dominated by quasi-balanced two-way transitions from 1990 to 2010. The insignificant overall amount of LUCC appears to have resulted from offsetting of rapid increases in population, economic growth, and the im-plementation of a program to return farmland to woodland and grassland in 2000. This program converted more farmland into woodland and grassland from 2000 to 2010 than from 1990 to 2000, but reclamation of woodland and grassland for use as farmland continued from 2000 to 2010, and is a cause for concern to the local government.

  4. Land cover classification and economic assessment of citrus groves using remote sensing

    Science.gov (United States)

    Shrivastava, Rahul J.; Gebelein, Jennifer L.

    The citrus industry has the second largest impact on Florida's economy, following tourism. Estimation of citrus area coverage and annual forecasts of Florida's citrus production are currently dependent on labor-intensive interpretation of aerial photographs. Remotely sensed data from satellites has been widely applied in agricultural yield estimation and cropland management. Satellite data can potentially be obtained throughout the year, making it especially suitable for the detection of land cover change in agriculture and horticulture, plant health status, soil and moisture conditions, and effects of crop management practices. In this study, we analyzed land cover of citrus crops in Florida using Landsat Enhanced Thematic Mapper Plus (ETM+) imagery from the University of Maryland Global Land Cover Facility (GLCF). We hypothesized that an interdisciplinary approach combining citrus production (economic) data with citrus land cover area per county would yield a correlation between observable spectral reflectance throughout the year, and the fiscal impact of citrus on local economies. While the data from official sources based on aerial photography were positively correlated, there were serious discrepancies between agriculture census data and satellite-derived cropland area using medium-resolution satellite imagery. If these discrepancies can be resolved by using imagery of higher spatial resolution, a stronger correlation would be observed for citrus production based on satellite data. This would allow us to predict the economic impact of citrus from satellite-derived spectral data analysis to determine final crop harvests.

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

    Science.gov (United States)

    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.

  6. ANALYSING THE EFFECTS OF DIFFERENT LAND COVER TYPES ON LAND SURFACE TEMPERATURE USING SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    A. Şekertekin

    2015-12-01

    Full Text Available 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.

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

    Science.gov (United States)

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

    2016-04-01

    The goal of the PAGES LandCover6k initiative is to provide relevant, empirical data on past anthropogenic land-cover change (land-use change) to climate modellers (e.g. the CMIP5 initiative). Land-use change is one of many climate forcings and its effect on climate is still badly understood. Among the effects of land-cover change on climate, the best known are the biogeochemical effects, and in particular the influence on the exchange of CO2 between the land surface and the atmosphere. The biogeophysical effects are less well understood, i.e. the net effect of changes in the albedo and evapotranspiration is complex. Moreover, the net effect of both biogeochemical and biogeophysical processes due to land-use change is still a matter of debate. The LandCover6k working group infers land-use data from fossil pollen records from lake sediments and peat deposits, and from historical archives and archaeological records (including pollen and other palaeoecological records such as wood and plant micro/macroremains). The working group is divided into two activities, i) pollen-based reconstructions of past land cover using pollen-vegetation modelling approaches, and mapping of pollen-based land-cover change using spatial statistics (e.g. Trondman et al., 2015; Pirzimanbein et al., 2014), and ii) upscaling and summarizing historical and archaeological data into maps of major land-use categories linked to quantitative attributes. Studies on pollen productivity of major plant taxa are an essential part of activity i). Pollen productivity estimates are available for a large number of the northern hemisphere, major plant taxa, but are still missing for large parts of the tropics for which research is currently in progress. The results of both activities are then used to revise existing Anthropogenic Land-Cover Change (ALCC) scenarios, the HYDE database (Klein-Goldewijk et al.,) and KK (Kaplan et al.,). Climate modellers (e.g. the CMIP5 initiative) can use the LandCover6k products

  8. Multi Sensor Evolution Analysis (MEA): Land Use and Land Cover Analysis Applied to (A)ATSR Time Series

    Science.gov (United States)

    Beccati, Alan; Folegani, Marco; D'Elia, Sergio; Barboni, Damiano; Selmi, Stefano

    2010-12-01

    The problem of (better) exploiting long-term satellite image databases is not yet resolved. Meanwhile the continuous growth of satellite data is generating an unprecedented increase in data types and volume. All this makes unrealistic to proceed with the current, mainly manual, image processing. Therefore the upcoming challenge is to find new methods permitting in near real-time to store and access large data volumes and to simplify or even automate the extraction of meaningful information for application domains, such as Land Use / Land Cover Change (LU/LCC) mapping. In the framework of the ESA Support by Pre-classification to Specific Applications (SPA) project [1] a fully automatic LU/LCC application (initially named (A)ATSR Land Classification System (ALCS)) known as Multi sensor Evolution Analysis (MEA) system [2], has been implemented and tested. MEA data store is built using 15 years of ATSR2-AATSR data (C1P 4713, C1P 5016).

  9. Impacts of changes in climate, land use and land cover on atmospheric mercury

    Science.gov (United States)

    Zhang, H.; Holmes, C. D.; Wu, S.

    2016-09-01

    Mercury is an important pollutant that can be transported globally due to its long lifetime in the atmosphere. Atmosphere-surface exchange is a major process affecting the cycling of mercury in the global environment and its impacts on food webs. We investigate the sensitivities of the air-surface exchange, atmospheric transport, and budget of mercury to projected 2000-2050 changes in climate and land use/land cover with a global chemical transport model (GEOS-Chem). We find that annual mean Hg(0) dry deposition flux over land could increase by up to 20% in northern mid-latitudes by 2050 due to increased vegetation and foliage density. Climate change can significantly affect both the wet deposition and atmospheric chemistry of mercury. In response to the projected climate change, the annual mean wet deposition flux increases over most continental regions and decreases over most of the mid-latitude and tropical oceans. The annual mean mercury wet deposition flux over northern and southern high latitudes increases by 7% and 8% respectively, largely driven by increases in precipitation there. Surface Hg(0) is predicted to increase generally, because high temperatures decrease Hg(0) oxidation by bromine and high moisture increases aqueous Hg(II) photo reduction. The combined effects of projected changes in climate, land use and land cover increase mercury deposition to the continental biosphere and decrease mercury deposition to the marine biosphere.

  10. Land-use/land-cover change and ecosystem service provision in China.

    Science.gov (United States)

    Song, Wei; Deng, Xiangzheng

    2017-01-15

    As a result of economics and policy, land-use/land-cover change (LUCC) in China has undergone a series of complicated changes over the past three decades. However, the effects of LUCCs on ecosystem service values (ESVs) have never been previously assessed at the national scale. Thus, on the basis of three Chinese LUCC maps from 1988, 2000, and 2008, we examined changes in land-use/land-cover and consequent ESVs using a value transfer method. We found that ESVs decreased by 0.45% and 0.10% during the periods 1988-2000 and 2000-2008, respectively, and that ESV changes in China during the period 2000-2008 were relatively moderate compared to the rest of the world over a similar period. The ESVs for provision, regulation, support, and culture decreased by 0.19%, 0.48%, 0.43%, and 0.45%, respectively, during the period 1988-2000, while they decreased by 0.11%, 0.09%, 0.14%, and 0.04%, respectively, during the period 2000-2008. We also developed an elasticity indicator to assess responses in ESV change relative to LUCCs. Results of this analysis show that 1% of land conversion in China resulted in 0.15% and 0.10% average changes in ESVs during the two periods, respectively.

  11. Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative

    Science.gov (United States)

    Poulter, B.; MacBean, N.; Hartley, A.; Khlystova, I.; Arino, O.; Betts, R.; Bontemps, S.; Boettcher, M.; Brockmann, C.; Defourny, P.; Hagemann, S.; Herold, M.; Kirches, G.; Lamarche, C.; Lederer, D.; Ottlé, C.; Peters, M.; Peylin, P.

    2015-07-01

    Global land cover is a key variable in the earth system with feedbacks on climate, biodiversity and natural resources. However, global land cover data sets presently fall short of user needs in providing detailed spatial and thematic information that is consistently mapped over time and easily transferable to the requirements of earth system models. In 2009, the European Space Agency launched the Climate Change Initiative (CCI), with land cover (LC_CCI) as 1 of 13 essential climate variables targeted for research development. The LC_CCI was implemented in three phases: first responding to a survey of user needs; developing a global, moderate-resolution land cover data set for three time periods, or epochs (2000, 2005, and 2010); and the last phase resulting in a user tool for converting land cover to plant functional type equivalents. Here we present the results of the LC_CCI project with a focus on the mapping approach used to convert the United Nations Land Cover Classification System to plant functional types (PFTs). The translation was performed as part of consultative process among map producers and users, and resulted in an open-source conversion tool. A comparison with existing PFT maps used by three earth system modeling teams shows significant differences between the LC_CCI PFT data set and those currently used in earth system models with likely consequences for modeling terrestrial biogeochemistry and land-atmosphere interactions. The main difference between the new LC_CCI product and PFT data sets used currently by three different dynamic global vegetation modeling teams is a reduction in high-latitude grassland cover, a reduction in tropical tree cover and an expansion in temperate forest cover in Europe. The LC_CCI tool is flexible for users to modify land cover to PFT conversions and will evolve as phase 2 of the European Space Agency CCI program continues.

  12. User Requirements from the Climate Modelling Community for Next Generation Global Products from Land Cover CCI Project

    Science.gov (United States)

    Kooistra, Lammert; van Groenestijn, Annemarie; Kalogirou, Vasileios; Arino, Olivier; Herold, Martin

    2011-01-01

    Land Cover has been selected as one of 11 Essential Climate Variables which will be elaborated during the first phase of the ESA Climate Change Initiative (2010- 2013). In the first stage of the Land Cover CCI project, an user requirements analysis has been carried out on the basis of which the detailed specifications of a global land cover product can be defined which match the requirements from the Global Climate Observing System (GCOS) and the climate modelling community. As part of the requirements analysis, an user consultation mechanism was set-up to actively involve different climate modelling groups by setting out surveys to different type of users within the climate modelling community and the broad land cover data user community. The evolution of requirements from current models to future new modelling approaches was specifically taken into account. In addition, requirements from the GCOS Implementation Plan 2004 and 2010 and associated strategic earth observation documents for land cover were assessed and a detailed literature review was carried out. The outcome of the user requirements assessment shows that although the range of requirements coming from the climate modelling community is broad, there is a good match among the requirements coming from different user groups and the broader requirements derived from GCOS, CMUG and other relevant international panels. More specific requirements highlight that future land cover datasets should be both stable and have a dynamic component; deal with the consistency in relationships between land cover classes and land surface parameters; should provide flexibility to serve different scales and purposes; and should provide transparency of product quality. As a next step within the Land Cover CCI project, the outcome of this user requirements analysis will be used as input for the product specification of the next generation Global Land Cover datasets.

  13. Geodemography: Land cover, geographical information systems and population distribution

    Directory of Open Access Journals (Sweden)

    Francisco J. Goerlich Gisbert

    2013-01-01

    Full Text Available This paper examines the recent application of the Geographical Information Systems (GIS to the analysis of population distribution. We mention the efforts of the National Statistical Institutes in this direction boosted by the last census 2011.The stating point is a growing need to have available population figures for areas not related to administrative boundaries, either user defined zones or in grid format.This allows a convenient zonal system to combine demographic characteristics with environmental and pure geographic data, so the relation between the man and the environment can be analyzed in a unified way.Eventually, we offer a practical illustration of the interactions between GIS techniques and administrative population data in the study of spatial population distribution: We build a density grid for Spain by dasymetric methods from census tracts population data and Land Cover and Use Information System of Spain (SIOSE.The analysis is done within the spatial reference framework of the European Union.

  14. Locally optimized separability enhancement indices for urban land cover mapping

    DEFF Research Database (Denmark)

    Feyisa, Gudina L.; Meilby, Henrik; Darrel Jenerette, G.

    2016-01-01

    Landsat data were used to assess urbanization-induced dynamics in Land use/cover (LULC), surface thermal intensity, and its relationships with urban biophysical composition. The study was undertaken in Addis Ababa city, Ethiopia. Ground-based data and high resolution images were used as reference...... data in LULC classification. To more accurately quantify landscape patterns and their changes, we applied new locally optimized separability enhancement indices and decision rules (SEI–DR approach) to address commonly observed classification accuracy problems in urban environments. We tested the SEI...... classification method, use of hotspot analysis, and the investigations of the UHI for an African city fill important research gaps for studies of urban thermal variation....

  15. Land Use and Land Cover Change in Sagarmatha National Park, a World Heritage Site in the Himalayas of Eastern Nepal

    National Research Council Canada - National Science Library

    Rodney Garrard; Thomas Kohler; Martin F Price; Alton C Byers; Ang Rita Sherpa; Gyanu Raja Maharjan

    2016-01-01

      Land use and land cover (LULC) changes that occurred during 1992- 2011 in Sagarmatha National Park, a United Nations Educational, Scientific, and Cultural Organization World Heritage Site in the Himalayas of eastern Nepal, were...

  16. Land Use and Land Cover, Agriculture Use, Published in 2010, 1:600 (1in=50ft) scale, Franklin County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of 2010. It is described as...

  17. EnviroAtlas - Percent Land Cover with Potentially Restorable Wetlands on Agricultural Land per 12-Digit HUC - Contiguous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset shows the percent land cover with potentially restorable wetlands on agricultural land for each 12-digit Hydrologic Unit (HUC) watershed in...

  18. Land Use and Land Cover, Published in unknown, 1:600 (1in=50ft) scale, Renaissance Downtowns, LLC..

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Land Use and Land Cover dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of unknown. Data by this...

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

    Science.gov (United States)

    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

  20. Managing water services in tropical regions: From land cover proxies to hydrologic fluxes.

    Science.gov (United States)

    Ponette-González, Alexandra G; Brauman, Kate A; Marín-Spiotta, Erika; Farley, Kathleen A; Weathers, Kathleen C; Young, Kenneth R; Curran, Lisa M

    2015-09-01

    Watershed investment programs frequently use land cover as a proxy for water-based ecosystem services, an approach based on assumed relationships between land cover and hydrologic outcomes. Water flows are rarely quantified, and unanticipated results are common, suggesting land cover alone is not a reliable proxy for water services. We argue that managing key hydrologic fluxes at the site of intervention is more effective than promoting particular land-cover types. Moving beyond land cover proxies to a focus on hydrologic fluxes requires that programs (1) identify the specific water service of interest and associated hydrologic flux; (2) account for structural and ecological characteristics of the relevant land cover; and, (3) determine key mediators of the target hydrologic flux. Using examples from the tropics, we illustrate how this conceptual framework can clarify interventions with a higher probability of delivering desired water services than with land cover as a proxy.

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

    Science.gov (United States)

    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

  2. A spatial resolution threshold of land cover in estimating terrestrial carbon sequestration in four counties in Georgia and Alabama, USA

    Science.gov (United States)

    Zhao, S.Q.; Liu, S.; Li, Z.; Sohl, T.L.

    2010-01-01

    Changes in carbon density (i.e., carbon stock per unit area) and land cover greatly affect carbon sequestration. Previous studies have shown that land cover change detection strongly depends on spatial scale. However, the influence of the spatial resolution of land cover change information on the estimated terrestrial carbon sequestration is not known. Here, we quantified and evaluated the impact of land cover change databases at various spatial resolutions (250 m, 500 m, 1 km, 2 km, and 4 km) on the magnitude and spatial patterns of regional carbon sequestration in four counties in Georgia and Alabama using the General Ensemble biogeochemical Modeling System (GEMS). Results indicated a threshold of 1 km in the land cover change databases and in the estimated regional terrestrial carbon sequestration. Beyond this threshold, significant biases occurred in the estimation of terrestrial carbon sequestration, its interannual variability, and spatial patterns. In addition, the overriding impact of interannual climate variability on the temporal change of regional carbon sequestration was unrealistically overshadowed by the impact of land cover change beyond the threshold. The implications of these findings directly challenge current continental- to global-scale carbon modeling efforts relying on information at coarse spatial resolution without incorporating fine-scale land cover dynamics.

  3. Beyond Impervious: Urban Land-Cover Pattern Variation and Implications for Watershed Management

    Science.gov (United States)

    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.

  4. The Spatiotemporal Land use/cover Change of Adana City

    Science.gov (United States)

    Akın, A.; Erdoğan, M. A.; Berberoğlu, S.

    2013-10-01

    The major driving factors for land use planning are largely limited to socio-economic inputs that do not completely represent the spatio-temporal patterns and ecological inputs have often been neglected. Integration of remote sensing and GIS techniques enabled successful applications in characterizing the spatiotemporal trends of land use/land cover (LULC) change. This study demonstrated an approach that combines remote sensing, landscape metrics, and LULC change analysis as a promising tool for understanding spatiotemporal patterns of Adana city. Calculation of spatial metrics was based on a categorical, patch-based representation of the landscape. Landscape metrics are conceptual framework for sustainable landscape and ecological planning. LULC change analysis was performed by considering the metric calculation. Post-classification technique was used for the metric based change detection and two different remotely sensed data set recorded in 1967 (CORONA) and 2007 (ALOS AVNIR) were used for the analysis. Additionally, a LULC projection for the year 2023 was also generated and integrated to the change analysis. SLEUTH model was utilised as a urban growth model for the future developments of study area in the scope of Cellular Automata (CA). SLEUTH model contains the main elements that characterize the core characteristics of CA: it works in a grid space of homogeneous cells, with a neighburhood of eight cells, two cell states and five transition rules that act in sequential time steps. Most useful and relevant metrics for landscape including: percentage of landscape, patch density, edge density, largest patch index, Euclidian mean nearest neighbor distance, area weighted mean patch fractal dimension and contagion were calculated for the 1967, 2007 and 2023 LULC maps and temporal changes were determined for the study area. Most considerable change was observed on the agricultural areas. Urban sprawl is the major driving factor of the LULC change.

  5. The impacts of land cover types on urban outdoor thermal environment: the case of Beijing, China.

    Science.gov (United States)

    Yan, Hai; Dong, Li

    2015-01-01

    This study investigated the microclimatic behavior of different land cover types in urban parks and, the correlation between air temperature and land cover composition to understand how land cover affects outdoor thermal environment during hot summer. To address this issue, air temperatures were measured on four different land cover types at four observation sites inside an urban park in Beijing, China, meanwhile, the land cover composition of each site was quantified with CAD, by drawing corresponding areas on the aerial photographs. The results showed that the average air temperature difference among four land cover types was large during the day and small during the night. At noon, the average air temperature differed significantly among four land cover types, whereas on night, there was no significant difference among different land cover types. Results of the linear regression indicated that during daytime, there was a strong negative correlation between air temperature and percent tree cover; while at nighttime, a significant negative correlation was observed between air temperature and percent lawn cover. It was shown that as the percent tree cover increased by 10 %, the air temperature decreased by 0.26 °C during daytime, while as the percent lawn cover increased by 10 %, the air temperature decreased by 0.56 °C during nighttime. Results of this study help to clarify the effects of land cover on urban outdoor thermal environment, and can provide assistance to urban planner and designer for improving green space planning and design in the future.

  6. A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed

    Science.gov (United States)

    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.

  7. Understanding Land Use and Land Cover Dynamics from 1976 to 2014 in Yellow River Delta

    Directory of Open Access Journals (Sweden)

    Baolei Zhang

    2017-03-01

    Full Text Available Long-term intensive land use/cover changes (LUCCs of the Yellow River Delta (YRD have been happening since the 1960s. The land use patterns of the LUCCs are crucial for bio-diversity conservation and/or sustainable development. This study quantified patterns of the LUCCs, explored the systematic transitions, and identified wetland change trajectory for the period 1976–2014 in the YRD. Landsat imageries of 1976, 1984, 1995, 2006, and 2014 were used to derive nine land use classes. Post classification change detection analysis based on enhanced transition matrix was applied to identify land use dynamics and trajectory of wetland change. The five cartographic outputs for changes in land use underlined major decreases in natural wetland areas and increases in artificial wetland and non-wetland, especially aquafarms, salt pans and construction lands. The systematic transitions in the YRD were wetland degradation, wetland artificialization, and urbanization. Wetland change trajectory results demonstrated that the main wetland changes were wetland degradation and wetland artificialization. Coastline change is the subordinate reason for natural wetland degradation in comparison with human activities. The results of this study allowed for an improvement in the understanding of the LUCC processes and enabled researchers and planners to focus on the most important signals of systematic landscape transitions while also allowing for a better understanding of the proximate causes of changes.

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

    Science.gov (United States)

    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.

  9. Impacts of Land Use and Cover Change on Land Surface Temperature in the Zhujiang Delta

    Institute of Scientific and Technical Information of China (English)

    QIAN Le-Xiang; CUI Hai-Sha; CHANG Jie

    2006-01-01

    Remote sensing and geographic information systems (GIS) technologies were used to detect land use/cover changes(LUCC) and to assess their impacts on land surface temperature (LST) in the Zhujiang Delta. Multi-temporal Landsat TM and Landsat ETM+ data were employed to identify patterns of LUCC as well as to quantify urban expansion and the associated decrease of vegetation cover. The thermal infrared bands of the data were used to retrieve LST. The results revealed a strong and uneven urban growth, which caused LST to raise 4.56 ℃ in the newly urbanized part of the study area. Overall, remote sensing and CIS technologies were effective approaches for monitoring and analyzing urban growth patterns and evaluating their impacts on LST.

  10. Ecological dissimilarity among land-use/land-cover types improves a heterogeneity index for predicting biodiversity in agricultural landscapes.

    Science.gov (United States)

    Yoshioka, Akira; Fukasawa, Keita; Mishima, Yoshio; Sasaki, Keiko; Kadoya, Taku

    2017-06-01

    Land-use/land-cover heterogeneity is among the most important factors influencing biodiversity in agricultural landscapes and is the key to the conservation of multi-habitat dwellers that use both terrestrial and aquatic habitats. Heterogeneity indices based on land-use/land-cover maps typically do not integrate ecological dissimilarity between land-use/land-cover types. Here, we applied the concept of functional diversity to an existing land-use/land-cover diversity index (Satoyama index) to incorporate ecological dissimilarity and proposed a new index called the dissimilarity-based Satoyama index (DSI). Using Japan as a case study, we calculated the DSI for three land-use/land-cover maps with different spatial resolutions and derived similarity information from normalized difference vegetation index values. The DSI showed better performance in the prediction of Japanese damselfly species richness than that of the existing index, and a higher correlation between the index and species richness was obtained for higher resolution maps. Thus, our approach to improve the land-use/land-cover diversity index holds promise for future development and can be effective for conservation and monitoring efforts.

  11. Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

    Directory of Open Access Journals (Sweden)

    Laura Alfonsina Chang-Martínez

    2015-09-01

    Full Text Available Spatially-explicit land cover land use change (LCLUC models are becoming increasingly useful tools for historians and archaeologists. Such kinds of models have been developed and used by geographers, ecologists and land managers over the last few decades to carry out prospective scenarios. In this paper, we review historical models to compare them with prospective models, with the assumption that the ample experience gained in the development of models of prospective simulation can benefit the development of models having as their objective the simulation of changes that happened in the past. The review is divided into three sections: in the first section, we explain the functioning of contemporary LCLUC models; in the second section, we analyze historical LCLUC models; in the third section, we compare the former two types of models, and finally, we discuss the contributions to historical LCLUC models of contemporary LCLUC models.

  12. Dynamic Predictions of Semi-Arid Land Cover Change

    Science.gov (United States)

    Foster-Wittig, T. A.

    2011-12-01

    hypothesized that the combined effects of climate change and land use lead to a destabilization of the grass-tree state and an increased tendency toward a state of desertification. If desertification is considered to be irreversible degradation, it can be detrimental not only to plant-life but also to the livelihood of those whom consider the savanna their home. Because a large population lives in savanna ecosystems, it is important to study them to hopefully be able to make changes now before conditions become irreversible. Resources: Falkenmark, M., and Rockstrom, Johan (2008). "Building Resilience to Drought in Desertification-Prone Savannas in Sub-Saharan Africa: The Water Perspective." Natural Resources Forum 32: 93-102. Sankaran, M., Hanan, Niall P., Scholes, Robert J., Ratnman, Jayashree, Augustine, David J. , et al (2005). "Determinants of Woody Cover in African Savannas." Nature 438(8): 846-849. Scanlon, T., J.D. Albertson, K.K. Caylor, & C.A.Willaims (2002). "Determining Land Surface Fractional Cover from NDVI and Rainfall Time Series for a Savanna Ecosystem." Remote Sensing of Environment. 82:376-388. Williams, C., and Albertson, J. (2005). "Contrasting Short- and Long-Timescale Effects of Vegetation Dynamics on Water and Carbon Fluxes in Water-Limited Ecosystems." Water Resources Research. 41: 1-13

  13. Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  15. Land-Use and Land-Cover Mapping Using a Gradable Classification Method

    Directory of Open Access Journals (Sweden)

    Keigo Kitada

    2012-05-01

    Full Text Available Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a group of pixels should be considered. Lacunarity is an index used to characterize different texture appearances. It is often reported that the land-use and land-cover in urban areas can be effectively classified using the lacunarity index with high-resolution images. However, the applicability of the maximum-likelihood approach for hybrid analysis has not been reported. A more effective approach that employs the original spectral data and lacunarity index can be expected to improve the accuracy of the classification. A new classification procedure referred to as “gradable classification method” is proposed in this study. This method improves the classification accuracy in incremental steps. The proposed classification approach integrates several classification maps created from original images and lacunarity maps, which consist of lacnarity values, to create a new classification map. The results of this study confirm the suitability of the gradable classification approach, which produced a higher overall accuracy (68% and kappa coefficient (0.64 than those (65% and 0.60, respectively obtained with the maximum-likelihood approach.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Sohl, Terry L.; Reker, Ryan; 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.

  18. Modelling and optimization of land use/land cover change in a developing urban catchment.

    Science.gov (United States)

    Xu, Ping; Gao, Fei; He, Junchao; Ren, Xinxin; Xi, Weijin

    2017-06-01

    The impacts of land use/cover change (LUCC) on hydrological processes and water resources are mainly reflected in changes in runoff and pollutant variations. Low impact development (LID) technology is utilized as an effective strategy to control urban stormwater runoff and pollution in the urban catchment. In this study, the impact of LUCC on runoff and pollutants in an urbanizing catchment of Guang-Ming New District in Shenzhen, China, were quantified using a dynamic rainfall-runoff model with the EPA Storm Water Management Model (SWMM). Based on the simulations and observations, the main objectives of this study were: (1) to evaluate the catchment runoff and pollutant variations with LUCC, (2) to select and optimize the appropriate layout of LID in a planning scenario for reducing the growth of runoff and pollutants under LUCC, (3) to assess the optimal planning schemes for land use/cover. The results showed that compared to 2013, the runoff volume, peak flow and pollution load of suspended solids (SS), and chemical oxygen demand increased by 35.1%, 33.6% and 248.5%, and 54.5% respectively in a traditional planning scenario. The assessment result of optimal planning of land use showed that annual rainfall control of land use for an optimal planning scenario with LID technology was 65%, and SS pollutant load reduction efficiency 65.6%.

  19. Land User and Land Cover Maps of Europe: a Webgis Platform

    Science.gov (United States)

    Brovelli, M. A.; Fahl, F. C.; Minghini, M.; Molinari, M. E.

    2016-06-01

    This paper presents the methods and implementation processes of a WebGIS platform designed to publish the available land use and land cover maps of Europe at continental scale. The system is built completely on open source infrastructure and open standards. The proposed architecture is based on a server-client model having GeoServer as the map server, Leaflet as the client-side mapping library and the Bootstrap framework at the core of the front-end user interface. The web user interface is designed to have typical features of a desktop GIS (e.g. activate/deactivate layers and order layers by drag and drop actions) and to show specific information on the activated layers (e.g. legend and simplified metadata). Users have the possibility to change the base map from a given list of map providers (e.g. OpenStreetMap and Microsoft Bing) and to control the opacity of each layer to facilitate the comparison with both other land cover layers and the underlying base map. In addition, users can add to the platform any custom layer available through a Web Map Service (WMS) and activate the visualization of photos from popular photo sharing services. This last functionality is provided in order to have a visual assessment of the available land coverages based on other user-generated contents available on the Internet. It is supposed to be a first step towards a calibration/validation service that will be made available in the future.

  20. Assessing the use of subgrid land model output to study impacts of land cover change

    Science.gov (United States)

    Schultz, Natalie M.; Lee, Xuhui; Lawrence, Peter J.; Lawrence, David M.; Zhao, Lei

    2016-06-01

    Subgrid information from land models has the potential to be a powerful tool for investigating land-atmosphere interactions, but relatively few studies have attempted to exploit subgrid output. In this study, we modify the configuration of the Community Land Model version CLM4.5 so that each plant functional type (PFT) is assigned its own soil column. We compare subgrid and grid cell-averaged air temperature and surface energy fluxes from this modified case (PFTCOL) to a case with the default configuration—a shared soil column for all PFTs (CTRL)—and examine the difference in simulated surface air temperature between grass and tree PFTs within the same grid cells (ΔTGT). The magnitude and spatial patterns of ΔTGT from PFTCOL agree more closely with observations, ranging from -1.5 K in boreal regions to +0.6 K in the tropics. We find that the column configuration has a large effect on PFT-level energy fluxes. In the CTRL configuration, the PFT-level annual mean ground heat flux (G) differs substantially from zero. For example, at a typical tropical grid cell, the annual G is 31.8 W m-2 for the tree PFTs and -14.7 W m-2 for grass PFTs. In PFTCOL, G is always close to zero. These results suggest that care must be taken when assessing local land cover change impacts with subgrid information. For models with PFTs on separate columns, it may be possible to isolate the differences in land surface fluxes between vegetation types that would be associated with land cover change from other climate forcings and feedbacks in climate model simulations.

  1. Understanding Driving Forces and Implications Associated with the Land Use and Land Cover Changes in Portugal

    Directory of Open Access Journals (Sweden)

    Bruno M. Meneses

    2017-02-01

    Full Text Available Understanding the processes of land use and land cover changes (LUCC and the associated driving forces is important for achieving sustainable development. This paper presents the LUCC in Portugal at the regional level (NUTS II from 1995 to 2010 and discusses the main driving forces and implications associated with these LUCC. The main objectives of this work are: (a to quantify the land use and land cover (LUC types (level I of LUC cartography by NUT II in Portugal for the years 1995, 2007 and 2010; (b to assess the spatio-temporal LUCC; and (c to identify and discuss the main driving forces of LUCC and corresponding implications based on correlations and Principal Components Analysis. The results revealed large regional and temporal LUCC and further highlighted the different and sometimes opposite time trends between neighboring regions. By associating driving forces to LUCC, different influences at the regional level were observed, namely LUCC into agriculture land derived from the construction of dams (Alentejo region, or the conversion of coniferous forest into eucalypt forest (Centre region associated with increased gross value added (GVA and employment in industry and forestry. Temporal differentiation was also observed, particularly in the settlements that expanded between 1995 and 2007 due to the construction of large infrastructures (e.g., highways, industrial complexes, or buildings, which is reflected on employment in industry and construction and respective GVA. However, certain LUCC have implications, particularly in energy consumption, for which different behavior between regions can be highlighted in this analysis, but also on land-use sustainability.

  2. Land-cover change and avian diversity in the conterminous United States.

    Science.gov (United States)

    Rittenhouse, Chadwick D; Pidgeon, Anna M; Albright, Thomas P; Culbert, Patrick D; Clayton, Murray K; Flather, Curtis H; Masek, Jeffrey G; Radeloff, Volker C

    2012-10-01

    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 Breeding Bird Survey data to examine land-cover change and its associations with diversity of birds with principally terrestrial life cycles (landbirds) in the conterminous United States. We used mixed-effects models and model selection to rank associations by ecoregion. Land cover in 3.22% of the area considered in our analyses changed from 1992 to 2001, and changes in species richness and abundance of birds were strongly associated with land-cover changes. Changes in species richness and abundance were primarily associated with changes in nondominant types of land cover, yet in many ecoregions different types of land cover were associated with species richness than were associated with abundance. Conversion of natural land cover to anthropogenic land cover was more strongly associated with changes in bird species richness and abundance than persistence of natural land cover in nearly all ecoregions and different covariates were most strongly associated with species richness than with abundance in 11 of 17 ecoregions. Loss of grassland and shrubland affected bird species richness and abundance in forested ecoregions. Loss of wetland was associated with bird abundance in forested ecoregions. Our findings highlight the value of understanding changes in nondominant land cover types and their association with bird diversity in the United States.

  3. Comparing and Contrasting the Benefits of Land Mass vs. Land Cover on Storm Surge Attenuation

    Science.gov (United States)

    Siverd, C. G.; Hagen, S. C.; Bilskie, M. V.; Twilley, R.; Braud, D.; Peele, H.

    2015-12-01

    From 1930 through 2012 Louisiana lost approximately 1,880 sq mi (4,870 sq km) of coastal wetlands due to land subsidence, erosion, and sea level rise among other factors. Louisiana could potentially lose an additional 1,750 sq mi (4,530 sq km) of coastal wetlands by 2062 if no action is taken to prevent this land loss (CPRA, 2012). If risk is defined as probability multiplied by consequence (Vrijling, 2006), such land loss will significantly increase the risk of flooding in coastal communities and communities located farther inland. Vital coastal infrastructure will also be at a heightened risk of flood damage. This will be attributable to the increase in frequency of hurricane storm surge events featuring greater depths and farther inland extent. This risk can be described by contrasting the surface area of land and water along the Louisiana coast. Using aerial or satellite imagery, isopleths can be plotted along the coast that describe the land to water (L:W) ratio over time (e.g., Gagliano et al., 1970, 1971 plotted the calculated 50% L:W ratio isopleths for the years 1930, and 1970, with an estimated 2000 isopleth). Risk to coastal infrastructure and coastal communities increases as the L:W ratio is reduced. One possible way to reduce the depth and extent of storm surge is to increase the land area along the coast. A second way is to modify the land cover (i.e. vary the type and density of vegetation). The L:W ratio can be used to quantify storm surge attenuation and assess such contributing factors. For this study, storm surge is simulated along coastal Louisiana for various instances - with increased land area and separately with different land cover types and densities - to determine which of these factors most effectively reduce the depth and extent of storm surge. New metrics involving hydrologic basins for evaluating storm surge attenuation are also described. The results of this study should inform policy makers which factors contribute the most to storm

  4. Mapping urban land cover from space: Some observations for future progress

    Science.gov (United States)

    Gaydos, L.

    1982-01-01

    The multilevel classification system adopted by the USGS for operational mapping of land use and land cover at levels 1 and 2 is discussed and the successes and failures of mapping land cover from LANDSAT digital data are reviewed. Techniques used for image interpretation and their relationships to sensor parameters are examined. The requirements for mapping levels 2 and 3 classes are considered.

  5. Land-use/land-cover change detection using change-vector analysis in posterior probability space

    Science.gov (United States)

    Chen, Xuehong; Chen, Jin; Shen, Miaogen; Yang, Wei

    2008-10-01

    Land use/land cover change is an important field in global environmental change research. Remote sensing is a valuable data source from which land use/land cover change information can be extracted efficiently. A number of techniques for accomplishing change detection using satellite imagery have been formulated, applied, and evaluated, which can be generally grouped into two types. (1) Those based on spectral classification of the input data such as post-classification comparison and direct two-date classification; and (2) those based on radiometric change between different acquisition dates. The shortage of type 1 is cumulative error in image classification of an individual date. However, radiometric change approaches has a strict requirement for reliable image radiometry. In light of the above mentioned drawbacks of those two types of change detection methods, this paper presents a new method named change vector analysis in posterior probability space (CVAPS). Change-vector analysis (CVA) is one of the most successful radiometric change-based approaches. CVAPS approach incorporates post-classification comparison method and CVA approach, which is expected to inherit the advantages of two traditional methods and avoid their defects at the same time. CVAPS includes the following four steps. (1) Images in different periods are classified by certain classifier which can provide posterior probability output. Then, the posterior probability can be treated as a vector, the dimension of which is equal to the number of classes. (2) A procedure similar with CVA is employed. Compared with traditional CVA, new method analyzes the change vector in posterior probability space instead of spectral feature space. (3) A semiautomatic method, named Double-Window Flexible Pace Search (DFPS), is employed to determine the threshold of change magnitude. (4) Change category is discriminated by cosines of the change vectors. CVAPS approach was applied and validated by a case study of

  6. Classifying Multi-year Land Use and Land Cover using Deep Convolutional Neural Networks

    Science.gov (United States)

    Seo, B.

    2015-12-01

    Cultivated ecosystems constitute a particularly frequent form of human land use. Long-term management of a cultivated ecosystem requires us to know temporal change of land use and land cover (LULC) of the target system. Land use and land cover changes (LUCC) in agricultural ecosystem is often rapid and unexpectedly occurs. Thus, longitudinal LULC is particularly needed to examine trends of ecosystem functions and ecosystem services of the target system. Multi-temporal classification of land use and land cover (LULC) in complex heterogeneous landscape remains a challenge. Agricultural landscapes often made up of a mosaic of numerous LULC classes, thus spatial heterogeneity is large. Moreover, temporal and spatial variation within a LULC class is also large. Under such a circumstance, standard classifiers would fail to identify the LULC classes correctly due to the heterogeneity of the target LULC classes. Because most standard classifiers search for a specific pattern of features for a class, they fail to detect classes with noisy and/or transformed feature data sets. Recently, deep learning algorithms have emerged in the machine learning communities and shown superior performance on a variety of tasks, including image classification and object recognition. In this paper, we propose to use convolutional neural networks (CNN) to learn from multi-spectral data to classify agricultural LULC types. Based on multi-spectral satellite data, we attempted to classify agricultural LULC classes in Soyang watershed, South Korea for the three years' study period (2009-2011). The classification performance of support vector machine (SVM) and CNN classifiers were compared for different years. Preliminary results demonstrate that the proposed method can improve classification performance compared to the SVM classifier. The SVM classifier failed to identify classes when trained on a year to predict another year, whilst CNN could reconstruct LULC maps of the catchment over the study

  7. Land Cover Vegetation Changes and Hydrology in Central Texas

    Science.gov (United States)

    Banta, J. R.; Slattery, R.

    2013-12-01

    Encroachment of woody vegetation into traditional savanna grassland ecosystems in central Texas has largely been attributed to land use practices of settlers, most notably overgrazing and fire suppression. Implementing changes in land cover vegetation (removing the woody vegetation and allowing native grasses to reestablish in the area, commonly referred to as brush management), could potentially change the hydrology in a watershed. The U.S. Geological Survey, in cooperation with several local, State, and Federal agencies, studied the hydrologic effects of ashe juniper (Juniperus ashei) removal as a brush management conservation practice in the Honey Creek State Natural Area in Comal County, Tex. Two adjacent watersheds of 104 and 159 hectares were used in a paired study. Rainfall, streamflow, evapotranspiration (Bowen ratio method), and water quality data were collected in both watersheds. Using a hydrologic mass balance approach, rainfall was allocated to surface-water runoff, evapotranspiration, and potential groundwater recharge. Groundwater recharge was not directly measured, but estimated as the residual of the hydrologic mass balance. After hydrologic data were collected in both watersheds for 3 years, approximately 80 percent of the woody vegetation (ashe juniper) was selectively removed from the 159 hectare watershed (treatment watershed). Brush management was not implemented in the other (reference) watershed. Hydrologic data were collected in both watersheds for six years after brush management implementation. The resulting data were examined for differences in the hydrologic budget between the reference and treatment watersheds as well as between pre- and post-brush management periods to assess effects of the treatment. Results indicate there are differences in the hydrologic budget and water quality between the reference and treatment watersheds, as well as between pre- and post-brush management periods.

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

    Science.gov (United States)

    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).

  9. Comparative evaluation of the effects of climate and land-cover changes on hydrologic responses of the Muskeg River, Alberta, Canada

    OpenAIRE

    Hyung-Il Eum; Yonas Dibike; Terry Prowse

    2016-01-01

    Study region: The Muskeg River Basin located in the Oil-Sands region of northern Alberta, Canada. Study focus: An integrated modelling framework, which combines a process-based distributed hydrologic model with a dynamic land-cover simulation model is used to evaluate the effects of climate and land-cover changes on the hydrological regime in the basin. Land-cover types corresponding to three hypothetical levels of future industrial expansion are synthesized based on the current lease hold...

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

    Science.gov (United States)

    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...

  11. Development of Decadal (1985–1995–2005 Land Use and Land Cover Database for India

    Directory of Open Access Journals (Sweden)

    Parth S. Roy

    2015-02-01

    Full Text Available India has experienced significant Land-Use and Land-Cover Change (LULCC over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS, it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.

  12. Accuracy assessment of seven global land cover datasets over China

    Science.gov (United States)

    Yang, Yongke; Xiao, Pengfeng; Feng, Xuezhi; Li, Haixing

    2017-03-01

    Land cover (LC) is the vital foundation to Earth science. Up to now, several global LC datasets have arisen with efforts of many scientific communities. To provide guidelines for data usage over China, nine LC maps from seven global LC datasets (IGBP DISCover, UMD, GLC, MCD12Q1, GLCNMO, CCI-LC, and GlobeLand30) were evaluated in this study. First, we compared their similarities and discrepancies in both area and spatial patterns, and analysed their inherent relations to data sources and classification schemes and methods. Next, five sets of validation sample units (VSUs) were collected to calculate their accuracy quantitatively. Further, we built a spatial analysis model and depicted their spatial variation in accuracy based on the five sets of VSUs. The results show that, there are evident discrepancies among these LC maps in both area and spatial patterns. For LC maps produced by different institutes, GLC 2000 and CCI-LC 2000 have the highest overall spatial agreement (53.8%). For LC maps produced by same institutes, overall spatial agreement of CCI-LC 2000 and 2010, and MCD12Q1 2001 and 2010 reach up to 99.8% and 73.2%, respectively; while more efforts are still needed if we hope to use these LC maps as time series data for model inputting, since both CCI-LC and MCD12Q1 fail to represent the rapid changing trend of several key LC classes in the early 21st century, in particular urban and built-up, snow and ice, water bodies, and permanent wetlands. With the highest spatial resolution, the overall accuracy of GlobeLand30 2010 is 82.39%. For the other six LC datasets with coarse resolution, CCI-LC 2010/2000 has the highest overall accuracy, and following are MCD12Q1 2010/2001, GLC 2000, GLCNMO 2008, IGBP DISCover, and UMD in turn. Beside that all maps exhibit high accuracy in homogeneous regions; local accuracies in other regions are quite different, particularly in Farming-Pastoral Zone of North China, mountains in Northeast China, and Southeast Hills. Special

  13. Land use and land cover data changes in Indian Ocean Islands: Case study of Unguja in Zanzibar Island.

    Science.gov (United States)

    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.

  14. Sensitivity of surface air temperature change to land use/cover types in China

    Institute of Scientific and Technical Information of China (English)

    YANG XuChao; ZHANG YiLi; LIU LinShan; ZHANG Wei; DING MingJun; WANG ZhaoFeng

    2009-01-01

    Using CRU high resolution grid observational temperature and ERA40 reanalysie surface air temperature data during 1960--1999, we investigated the sensitivity of surface air temperature change to land use/cover types in China by subtracting the reanalysis from the observed surface air temperature (observation minus reanalysis, OMR). The results show that there is a stable and systemic impact of land use/cover types on surface air temperature. The surface warming of each land use/cover type reacted differently to global warming. The OMR trends of unused land (≥0.17℃/decade), mainly comprised by sandy land, Gobi and bare rock gravel land, are obviously larger than those of the other land use/cover types. The OMR over grassland, farmland and construction land shows a moderate decadal a significant warming trend (0.06"C/decade). The overall assessment indicates that the surface warming is larger for areas that are barren and anthropogenically developed. The better the vegetation cover, the smaller the OMR warming trend. Responses of surface air temperature to land use/cover types with similar physical and chemical properties and biological processes have no significant difference. The surface air temperature would not react significantly until the intensity of land cover changes reach a certain degree. Within the same land use/cover type, areas in eastern China with intensive human activities exhibit larger warming trend. The results provide observational evidence for modeling research on the impact of land use/cover change on regional climate. Thus, projecting further surface climate of China in regional scale should not only take greenhouse gas increase into account, but also consider the impact of land use/cover types and land cover change.

  15. Sensitivity of surface air temperature change to land use/cover types in China

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Using CRU high resolution grid observational temperature and ERA40 reanalysis surface air temperature data during 1960-1999, we investigated the sensitivity of surface air temperature change to land use/cover types in China by subtracting the reanalysis from the observed surface air temperature (observation minus reanalysis, OMR). The results show that there is a stable and systemic impact of land use/cover types on surface air temperature. The surface warming of each land use/cover type reacted differently to global warming. The OMR trends of unused land (≥0.17℃/decade), mainly comprised by sandy land, Gobi and bare rock gravel land, are obviously larger than those of the other land use/cover types. The OMR over grassland, farmland and construction land shows a moderate decadal warming about 0.12℃ /decade, 0.10℃/decade, 0.12 ℃ /decade, respectively. Woodland areas do not show a significant warming trend (0.06 ℃ /decade). The overall assessment indicates that the surface warming is larger for areas that are barren and anthropogenically developed. The better the vegetation cover, the smaller the OMR warming trend. Responses of surface air temperature to land use/cover types with similar physical and chemical properties and biological processes have no significant difference. The surface air temperature would not react significantly until the intensity of land cover changes reach a certain degree. Within the same land use/cover type, areas in eastern China with intensive human activities exhibit larger warming trend. The results provide observational evidence for modeling research on the impact of land use/cover change on regional climate. Thus, projecting further surface climate of China in regional scale should not only take greenhouse gas increase into account, but also consider the impact of land use/cover types and land cover change.

  16. Complex land use and cover trajectories in the northern Choco bioregion of Colombia

    Science.gov (United States)

    Santos, Carolina

    The Choco bioregion in Northwestern Colombia is a lowland rain forest and hotspot of biodiversity. Significant land use and cover change (LUCC) is occurring throughout the region driven by global markets, illicit drug production, and civil unrest. The dominant land cover conversion is from primary forest to African Palm plantations, mediated and modified by complex combinations of social and biophysical drivers. This research combined a remote sensing based methodology to monitor LUCC in the region with an analytical approach for evaluating the possible trajectories of LUCC in a complex biological, socio-economical, and political environment. Synoptic LUCC models were developed using textural classification derived from Synthetic Aperture Radar (SAR) images for the period 1995 to 2010. LUCC models along with empirical social and spatial biophysical drivers were used to project historical land use trajectories. DINAMICA EGO a complex systems based spatial analytical framework was adopted as the platform to model land use change. The RADAR backscatter was able to capture areas were forest has been converted to African Oil Palm Plantations. However, an in depth characterization of the LUC dynamics was problematic given the spectral and spatial limitations of the sensor combined with the lack of ground data. The results of the LUC model suggest that under the current socio-political conditions African oil palm plantations will continue to expand toward forested areas into the territories traditionally inhabited by Afro-Colombians and Indigenous populations. Insecure land tenure appears as a main driver of the transformation in close association with the conditions created by the armed conflict, and the drug traffic. The rate of the transformation appears to slow down in the period after 2007. However, according to the model by 2020 most of the area inhabited by ethnic groups will be transform to AOP. This study contributes towards the understanding of land use change

  17. A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

    Directory of Open Access Journals (Sweden)

    Dong Jiang

    Full Text Available Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1 images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization with convenience.

  18. A Simple Semi-Automatic Approach for Land Cover Classification from Multispectral Remote Sensing Imagery

    Science.gov (United States)

    Jiang, Dong; Huang, Yaohuan; Zhuang, Dafang; Zhu, Yunqiang; Xu, Xinliang; Ren, Hongyan

    2012-01-01

    Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience. PMID:23049886

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

    Science.gov (United States)

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

    2008-01-01

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

  20. Edge scour in current adjacent to stone covers

    DEFF Research Database (Denmark)

    Petersen, Thor Ugelvig; Sumer, B. Mutlu; Meyer, Knud Erik;

    The present paper reports some early results of an experimental investigation of edge scour in currents. Two kinds of measurements are made (1) Particle Image Velocimetry (PIV) measurements of secondary currents that take place near a junction between the stone cover and the sand bed in a clear...

  1. Monitoring land cover changes in Isfahan Province, Iran using Landsat satellite data.

    Science.gov (United States)

    Soffianian, Alireza; Madanian, Maliheh

    2015-08-01

    Changes in land cover and land use reveal the effects of natural and human processes on the Earth's surface. These changes are predicted to exert the greatest environmental impacts in the upcoming decades. The purpose of the present study was to monitor land cover changes using Multispectral Scanner Sensor (MSS) and multitemporal Landsat Thematic Mapper (TM) data from the counties of Isfahan Province, Iran, during 1975, 1990, and 2010. The maximum likelihood supervised classification method was applied to map land cover. Postclassification change detection technique was also used to produce change images through cross-tabulation. Classification results were improved using ancillary data, visual interpretation, and local knowledge about the area. The overall accuracy of land cover change maps ranged from 88 to 90.6%. Kappa coefficients associated with the classification were 0.81 for 1975, 0.84 for 1990, and 0.85 for 2010 images. This study monitored changes related to conversion of agricultural land to impervious surfaces, undeveloped land to agricultural land, agricultural land to impervious surfaces, and undeveloped land to impervious surfaces. The analyses of land cover changes during the study period revealed the significant development of impervious surfaces in counties of Isfahan Province as a result of population growth, traffic conditions, and industrialization. The image classification indicated that agricultural lands increased from 2520.96 km(2) in 1975 to 4103.85 km(2) in 2010. These land cover changes were evaluated in different counties of Isfahan Province.

  2. Assessing the impact of land use/land cover and climate changes on water stress in the derived savanna

    CSIR Research Space (South Africa)

    Amidu, A

    2013-07-01

    Full Text Available ___________________________________________________________________________________________________ Climate and Land Surface Changes in Hydrology Proceedings of H01, IAHS-IAPSO-IASPEI Assembly, Gothenburg, Sweden, July 2013 (IAHS Publ. 359, 2013) 92-98 . Assessing the impact of land use/land cover and climate changes on water stress in the derived...

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — 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...

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — 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...

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — 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...

  6. EnviroAtlas - Green Bay, WI - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Green Bay, WI Meter-Scale Urban Land Cover (MULC) dataset comprises 936 km2 around the city of Green Bay, surrounding towns, tribal lands and rural areas in...

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

    Data.gov (United States)

    U.S. Environmental Protection Agency — 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...

  8. USGS 100-Meter Resolution Land Cover of the Conterminous United States 201501 TIFF

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer contains land cover data for the conterminous United States, in an Albers Equal-Area Conic projection and at a resolution of 100 meters. The land...

  9. PRESENTATION ON--LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

    Science.gov (United States)

    Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent landuse activities. Past efforts incorporating two-date change detection using moderate resolution data (e.g., Lands...

  10. 100-Meter Resolution Land Cover of the Conterminous United States - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer contains land cover data for the conterminous United States, in an Albers Equal-Area Conic projection and at a resolution of 100 meters. The land...

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

    Data.gov (United States)

    U.S. Environmental Protection Agency — 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...

  12. EnviroAtlas - 2011 Agricultural Land Cover on Steep Slopes for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset represents the percentage land area that is classified as agricultural land cover that occurs on slopes above a given threshold for each...

  13. EnviroAtlas - 2011 Land Cover by 12-digit HUC for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset represents the percentage of land area that is classified as natural, forest, wetland, agricultural, natural, and developed land cover using...

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — 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...

  15. Scenario simulation and forecast of land use/cover in northern China

    Institute of Scientific and Technical Information of China (English)

    LI YueChen; HE ChunYang

    2008-01-01

    Modeling land use/cover scenario changes and its potential impacts on structure and functions of ecosystem in typical regions are helpful to understanding the interactive mechanism between land use/cover system and ecosystem. Based on the analysis of the existing land use/cover simulation and forecast models, a land use/cover scenario dynamics model by the integration of System Dynamics (SD) model, Back Propagation Neural Network (BPNN) and Cellular Automata (CA) model is developed with land use/cover scenario changes in northern China in the next 30 years and simulated in this paper. The model is to simulate the land use/cover scenario demands by using a SD model at first, and then allocating the land use scenario patterns at the local scale with the considerations of land use/cover suitability, inheritance ability and neighborhood effect by using BPNN-CA model to satisfy the balance between land use/cover scenario demands and supplies. It integrates the advantages of SD, BPNN and CA. Macro-driving factors and the micro-spatial pattern are also fully taken into account. The BPNN simplifies the identification of the factors' weights used in CA model and improves the reliability of the simulation results. The simulation accuracy of the model developed in this paper was found to be about 74%. It suggests that the model has the ability to reflect the complexity of land use/cover system at different scales to some extent and it is a useful tool for assessing the potential impacts of land use system on ecosystem. The simulated results also indicate that the urban land, water area and forest will increase significantly, and farmland and unable land will decrease gradually. Obvious land use/cover changes will take place in the farming-pastoral zone and the southeast area of northern China.

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

    Science.gov (United States)

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

    2016-08-24

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

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

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2016-04-01

    Land use/land cover (LULC) activity influences climate change and one way to explore climate change is to analyse the change in LULC patterns. Modelling the Spatio-temporal pattern of LULC change requires the use of satellite remote sensing data and aerial photographs with different pre-processing steps. The aim of this research is to analyse the reciprocal effects of LUCC (Land Use and Cover Change) and the climate change on each other in the study area which covers part of Bristol, South Gloucestershire, Bath and Somerset in England for the period (1975-2015). LUCC is assessed using remote sensing data. Three sets of remotely sensed data, LanSAT-1 Multispectral Scanner (MSS) data obtained in (1975 and 1976), LanSAT-5 Thematic Mapper (TM) data obtained in (1984 and 1997), and LandSAT-7 Enhanced Thematic Mapper Plus (ETM+) acquired in (2003 and 2015), with a time span of forty years were used in the study. One of the most common problems in the satellite images is the presence of cloud covers. In this study, the cloud cover problem is handled using a novel algorithm, which is capable of reducing the cloud coverage in the classified images significantly. This study also examines a suite of possible photogrammetry techniques applicable to detect the change in LULC. At the moment photogrammertic techniques are used to derive the ground truth for supervised classification from the high resolution aerial photos which were provided by Ordnance Survey (contract number: 240215) and global mapper for the years in (2001 and 2014). After obtaining the classified images almost free of clouds, accuracy assessment is implemented with the derived classified images using confusion matrix at some ground truth points. Eight classes (Improved grassland, Built up areas and gardens, Arable and horticulture, Broad-leaved / mixed woodland, Coniferous woodland, Oceanic seas, Standing open water and reservoir, and Mountain; heath; bog) have been classified in the chosen study area. Also