WorldWideScience

Sample records for national land cover

  1. National Land Cover Database (NLCD) Land Cover Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The National Land Cover Database (NLCD) Land Cover Collection is produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC)...

  2. The National Land Cover Database

    Science.gov (United States)

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

    2012-01-01

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

  3. 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...

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

    Science.gov (United States)

    The Multi-Resolution Land Characteristics Consortium has supported the development of two national digital land cover products: the National Land Cover Dataset (NLCD) 1992 and National Land Cover Database (NLCD) 2001. Substantial differences in imagery, legends, and methods betwe...

  5. 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.

  6. South African National Land-Cover Change Map

    African Journals Online (AJOL)

    Fritz Schoeman

    monitoring land-cover change at a national scale over time using EO data. 2. .... assist with final results reporting and analysis on a sub-national level. ..... South African Land-Cover Characteristics Database: A synopsis of the landscape.

  7. Completion of the National Land Cover Database (NLCD) 1992–2001 Land Cover Change Retrofit product

    Science.gov (United States)

    Fry, J.A.; Coan, Michael; Homer, Collin G.; Meyer, Debra K.; Wickham, J.D.

    2009-01-01

    The Multi-Resolution Land Characteristics Consortium has supported the development of two national digital land cover products: the National Land Cover Dataset (NLCD) 1992 and National Land Cover Database (NLCD) 2001. Substantial differences in imagery, legends, and methods between these two land cover products must be overcome in order to support direct comparison. The NLCD 1992-2001 Land Cover Change Retrofit product was developed to provide more accurate and useful land cover change data than would be possible by direct comparison of NLCD 1992 and NLCD 2001. For the change analysis method to be both national in scale and timely, implementation required production across many Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) path/rows simultaneously. To meet these requirements, a hybrid change analysis process was developed to incorporate both post-classification comparison and specialized ratio differencing change analysis techniques. At a resolution of 30 meters, the completed NLCD 1992-2001 Land Cover Change Retrofit product contains unchanged pixels from the NLCD 2001 land cover dataset that have been cross-walked to a modified Anderson Level I class code, and changed pixels labeled with a 'from-to' class code. Analysis of the results for the conterminous United States indicated that about 3 percent of the land cover dataset changed between 1992 and 2001.

  8. National Land Cover Database (NLCD) Percent Developed Imperviousness Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The National Land Cover Database (NLCD) Percent Developed Imperviousness Collection is produced through a cooperative project conducted by the Multi-Resolution Land...

  9. 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.

  10. National Land Cover Database (NLCD) Percent Tree Canopy Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The National Land Cover Database (NLCD) Percent Tree Canopy Collection is a product of the U.S. Forest Service (USFS), and is produced through a cooperative project...

  11. USGS National Land Cover Dataset (NLCD) Downloadable Data Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 1992, NLCD 2001, NLCD 2006, and NLCD 2011 are National Land Cover Database classification schemes based primarily on Landsat data along with ancillary data...

  12. 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...

  13. Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods

    Science.gov (United States)

    Xian, George; Homer, Collin G.; Fry, Joyce

    2009-01-01

    The recent release of the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001, which represents the nation's land cover status based on a nominal date of 2001, is widely used as a baseline for national land cover conditions. To enable the updating of this land cover information in a consistent and continuous manner, a prototype method was developed to update land cover by an individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season in 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, land cover classifications at the full NLCD resolution for 2006 areas of change were completed by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain several metropolitan areas including Seattle, Washington; San Diego, California; Sioux Falls, South Dakota; Jackson, Mississippi; and Manchester, New Hampshire. Results from the five study areas show that the vast majority of land cover change was captured and updated with overall land cover classification accuracies of 78.32%, 87.5%, 88.57%, 78.36%, and 83.33% for these areas. The method optimizes mapping efficiency and has the potential to provide users a flexible method to generate updated land cover at national and regional scales by using NLCD 2001 as the baseline.

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

    Science.gov (United States)

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

    1986-01-01

    Three alternatives using digital thematic mapper (TM), analog TM, and a combination of either digital or analog TM data with low altitude photography are discussed for level I and level II land use/land cover classes for a proposed national inventory. Digital TM data should prove satisfactory for estimating acreage in level I classes, although estimates of precision...

  15. USGS Land Cover (NLCD) Overlay Map Service from The National Map - National Geospatial Data Asset (NGDA) National Land Cover Database (NLCD)

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — NLCD 1992, NLCD 2001, NLCD 2006, and NLCD 2011 are National Land Cover Database classification schemes based primarily on Landsat data along with ancillary data...

  16. 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

  17. South African National Land-Cover Change Map | Schoeman ...

    African Journals Online (AJOL)

    Globally, countries face a changing environment due to population growth, increase in agricultural production, increasing demand on natural resources, climate change and resultant degradation of the natural environment. One means of monitoring this changing scenario is through land-cover change mapping. Modern ...

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

    Science.gov (United States)

    Wilson, Tamara S.

    2011-01-01

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

  19. 2006 C-CAP Land Cover of Old Woman Creek, Ohio, National Estuarine Research Reserve

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land cover derived from high resolution orthoimagery, LiDAR data and ancillary data sources such as SSURGO and National Wetlands Inventory,...

  20. 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...

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

    Science.gov (United States)

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

    2012-01-01

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

  2. The Multi-Resolution Land Characteristics (MRLC) Consortium: 20 years of development and integration of USA national land cover data

    Science.gov (United States)

    Wickham, James D.; Homer, Collin G.; Vogelmann, James E.; McKerrow, Alexa; Mueller, Rick; Herold, Nate; Coluston, John

    2014-01-01

    The Multi-Resolution Land Characteristics (MRLC) Consortium demonstrates the national benefits of USA Federal collaboration. Starting in the mid-1990s as a small group with the straightforward goal of compiling a comprehensive national Landsat dataset that could be used to meet agencies’ needs, MRLC has grown into a group of 10 USA Federal Agencies that coordinate the production of five different products, including the National Land Cover Database (NLCD), the Coastal Change Analysis Program (C-CAP), the Cropland Data Layer (CDL), the Gap Analysis Program (GAP), and the Landscape Fire and Resource Management Planning Tools (LANDFIRE). As a set, the products include almost every aspect of land cover from impervious surface to detailed crop and vegetation types to fire fuel classes. Some products can be used for land cover change assessments because they cover multiple time periods. The MRLC Consortium has become a collaborative forum, where members share research, methodological approaches, and data to produce products using established protocols, and we believe it is a model for the production of integrated land cover products at national to continental scales. We provide a brief overview of each of the main products produced by MRLC and examples of how each product has been used. We follow that with a discussion of the impact of the MRLC program and a brief overview of future plans.

  3. 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

  4. A land-use and land-cover modeling strategy to support a national assessment of carbon stocks and fluxes

    Science.gov (United States)

    Sohl, Terry L.; Sleeter, Benjamin M.; Zhu, Zhi-Liang; Sayler, Kristi L.; Bennett, Stacie; Bouchard, Michelle; Reker, Ryan R.; Hawbaker, Todd; Wein, Anne; Liu, Shu-Guang; Kanengieter, Ronald; Acevedo, William

    2012-01-01

    Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and land-management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystem are needed, with a consistent, nationally applicable land-use and land-cover (LULC) modeling framework a key component of such analyses. The U.S. Geological Survey has initiated a project to analyze current and projected future GHG fluxes by ecosystem and quantify potential mitigation strategies. We have developed a unique LULC modeling framework to support this work. Downscaled scenarios consistent with IPCC Special Report on Emissions Scenarios (SRES) were constructed for U.S. ecoregions, and the FORE-SCE model was used to spatially map the scenarios. Results for a prototype demonstrate our ability to model LULC change and inform a biogeochemical modeling framework for analysis of subsequent GHG fluxes. The methodology was then successfully used to model LULC change for four IPCC SRES scenarios for an ecoregion in the Great Plains. The scenario-based LULC projections are now being used to analyze potential GHG impacts of LULC change across the U.S.

  5. Methods for converting continuous shrubland ecosystem component values to thematic National Land Cover Database classes

    Science.gov (United States)

    Rigge, Matthew B.; Gass, Leila; Homer, Collin G.; Xian, George Z.

    2017-10-26

    The National Land Cover Database (NLCD) provides thematic land cover and land cover change data at 30-meter spatial resolution for the United States. Although the NLCD is considered to be the leading thematic land cover/land use product and overall classification accuracy across the NLCD is high, performance and consistency in the vast shrub and grasslands of the Western United States is lower than desired. To address these issues and fulfill the needs of stakeholders requiring more accurate rangeland data, the USGS has developed a method to quantify these areas in terms of the continuous cover of several cover components. These components include the cover of shrub, sagebrush (Artemisia spp), big sagebrush (Artemisia tridentata spp.), herbaceous, annual herbaceous, litter, and bare ground, and shrub and sagebrush height. To produce maps of component cover, we collected field data that were then associated with spectral values in WorldView-2 and Landsat imagery using regression tree models. The current report outlines the procedures and results of converting these continuous cover components to three thematic NLCD classes: barren, shrubland, and grassland. To accomplish this, we developed a series of indices and conditional models using continuous cover of shrub, bare ground, herbaceous, and litter as inputs. The continuous cover data are currently available for two large regions in the Western United States. Accuracy of the “cross-walked” product was assessed relative to that of NLCD 2011 at independent validation points (n=787) across these two regions. Overall thematic accuracy of the “cross-walked” product was 0.70, compared to 0.63 for NLCD 2011. The kappa value was considerably higher for the “cross-walked” product at 0.41 compared to 0.28 for NLCD 2011. Accuracy was also evaluated relative to the values of training points (n=75,000) used in the development of the continuous cover components. Again, the “cross-walked” product outperformed NLCD

  6. Development of a digital land cover data base for the Selawik National Wildlife Refuge

    Science.gov (United States)

    Markon, Carl J.; Kirk, William

    1994-01-01

    Digital land cover and terrain data of the Selawik National Wildlife Refuge were produced by the U.S. Geological Survey's (USGS) Earth Resources Observation Systems Alaska Field Office for the U.S. Fish and Wildlife Service. These and other environmental data were incorporated into a Fish and Wildlife Service geographic information system to prepare a comprehensive conservation plan and an environmental impact statement for the refuge and to assist in research and management of the refuge.

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

    Science.gov (United States)

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

    2017-12-01

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

  8. Land Use and Land Cover Change in Sagarmatha National Park, a World Heritage Site in the Himalayas of Eastern Nepal

    Directory of Open Access Journals (Sweden)

    Rodney Garrard

    2016-08-01

    Full Text Available 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 evaluated using multitemporal satellite imagery in combination with land use data and sociological information gathered from semistructured interviews and workshops. We asked study participants about LULC changes, the causes of each change, and the likely duration of its effects, and used this information to produce high-resolution maps of local perceptions of LULC change. Satellite image analysis revealed that above 6000 m there has been a decrease in the area covered by snow and ice and a consequent expansion of glacial lakes and areas covered by rock and soil. Between 3000 and 6000 m, forest and farmland are decreasing, and areas under grazing, settlement, and shrubland are increasing. Such LULC changes within the protected area clearly indicate the prevailing danger of land degradation. Results from the interviews and workshops suggest that people tended to detect LULC change that was acute and direct, but were less aware of slower changes that could be identified by satellite imagery analysis. Most study participants said that land use changes were a result of rapid economic development and the consequent pressure on natural resources, especially in the tourism industry and especially below 6000 m elevation, as well as limitations to protected area management and a period of civil war. Human influence coupled with climate change may explain the changes at higher elevations, whereas anthropogenic activities are solely responsible in lower areas. Although global factors cannot be mitigated locally, many of the local drivers of LULC change could be addressed with improved management practices that aid local conservation and development in this high mountain ecosystem. A broader interdisciplinary approach to LULC change

  9. Historical changes in caribou distribution and land cover in and around Prince Albert National Park: land management implications

    Directory of Open Access Journals (Sweden)

    Maria L. Arlt

    2011-09-01

    Full Text Available In central Saskatchewan, boreal woodland caribou population declines have been documented in the 1940s and again in the 1980s. Although both declines led to a ban in sport hunting, a recovery was only seen in the 1950s and was attributed to wolf control and hunting closure. Recent studies suggest that this time, the population may not be increasing. In order to contribute to the conservation efforts, historical changes in caribou distribution and land cover types in the Prince Albert Greater Ecosystem (PAGE, Saskatchewan, were documented for the period of 1960s to the present. To examine changes in caribou distribution, survey observations, incidental sightings and telemetry data were collated. To quantify landscape changes, land cover maps were created for 1966 and 2006 using current and historic forest resources inventories, fire, logging, and roads data. Results indicate that woodland caribou are still found throughout the study area although their distribution has changed and their use of the National Park is greatly limited. Results of transition prob¬abilities and landscape composition analyses on the 1966 and 2006 land cover maps revealed an aging landscape for both the National Park and provincial crown land portions of the PAGE. In addition, increased logging and the development of extensive road and trail networks on provincial crown land produced significant landscape fragmentation for woodland caribou and reduced functional attributes of habitat patches. Understanding historical landscape changes will assist with ongoing provincial and federal recovery efforts for boreal caribou, forest management planning activities, and landscape restoration efforts within and beyond the Park boundaries.

  10. IMPLEMENTATION STRATEGY FOR PRODUCTION OF NATIONAL LAND-COVER DATA (NLCD) FROM THE LANDSAT 7 THEMATIC MAPPER SATELLITE

    Science.gov (United States)

    As environmental programs within and outside the federal government continue to move away from point-based studies to larger and larger spatial (not cartographic) scale, the need for land-cover and other geographic data have become ineluctable. The national land-cover mapping pr...

  11. A comparison of stratification effectiveness between the National Land Cover Data set and photointerpretation in western Oregon

    Science.gov (United States)

    Paul Dunham; Dale Weyermann; Dale Azuma

    2002-01-01

    Stratifications developed from National Land Cover Data (NLCD) and from photointerpretation (PI) were tested for effectiveness in reducing sampling error associated with estimates of timberland area and volume from FIA plots in western Oregon. Strata were created from NLCD through the aggregation of cover classes and the creation of 'edge' strata by...

  12. 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

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

    Science.gov (United States)

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

    2016-12-01

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

  14. A method for mapping corn using the US Geological Survey 1992 National Land Cover Dataset

    Science.gov (United States)

    Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.

    2006-01-01

    Long-term exposure to elevated nitrate levels in community drinking water supplies has been associated with an elevated risk of several cancers including non-Hodgkin's lymphoma, colon cancer, and bladder cancer. To estimate human exposure to nitrate, specific crop type information is needed as fertilizer application rates vary widely by crop type. Corn requires the highest application of nitrogen fertilizer of crops grown in the Midwest US. We developed a method to refine the US Geological Survey National Land Cover Dataset (NLCD) (including map and original Landsat images) to distinguish corn from other crops. Overall average agreement between the resulting corn and other row crops class and ground reference data was 0.79 kappa coefficient with individual Landsat images ranging from 0.46 to 0.93 kappa. The highest accuracies occurred in Regions where corn was the single dominant crop (greater than 80.0%) and the crop vegetation conditions at the time of image acquisition were optimum for separation of corn from all other crops. Factors that resulted in lower accuracies included the accuracy of the NLCD map, accuracy of corn areal estimates, crop mixture, crop condition at the time of Landsat overpass, and Landsat scene anomalies.

  15. The Effect of Land Cover Change on Soil Properties around Kibale National Park in South Western Uganda

    International Nuclear Information System (INIS)

    Majaliwa, J.G.M.; Twongyirwe, R.; Nyenje, R.; Oluka, M.; Ongom, B.; Sirike, J.; Mfitumukiza, D.; Azanga, E.; Natumanya, R.; Mwerera, R.; Barasa, B.

    2010-01-01

    The change from natural forest cover to tea and Eucalyptus is rampant in protected areas of western Uganda. The objectives were; to examine the trend in land-use /cover change and determine the effect of these changes on the physico-chemical properties of soils around Kibale National Park. The trend in land use/cover change was assessed by analyzing a series of Landsat images. Focused group discussions and key informant interviews were used for land-use/cover reconstruction. Three major land uses were included; wood lot (Eucalyptus grandis; 5 years old) ), tea (57 years old) and natural forest used as a control. Each of these land-uses were selected at two different North facing landscape positions and were replicated three times. A total of 36 composite soil samples were taken at 0-15 and 15-30 cm depth from natural forest, Tea plantation and eucalyptus on three ridges. Results showed that small scale farming, tea and eucalyptus plantation and built up area have increased over time, to the expense of wood lot and forest cover. Tea and Eucalyptus have induced changes in: exchangeable Mg and Ca, available P, SOM, ph, and bulk density of sub soil (P<.05). Landscape positions within land use also significantly influenced most soil properties (P<.05). Similar findings were observed by Wang et al. (2006) in commercial tea plantations in China that received nitrogen fertilizers.

  16. Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat imagery change detection methods

    Science.gov (United States)

    Xian, George; Homer, Collin G.

    2010-01-01

    A prototype method was developed to update the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001 to a nominal date of 2006. NLCD 2001 is widely used as a baseline for national land cover and impervious cover conditions. To enable the updating of this database in an optimal manner, methods are designed to be accomplished by individual Landsat scene. Using conservative change thresholds based on land cover classes, areas of change and no-change were segregated from change vectors calculated from normalized Landsat scenes from 2001 and 2006. By sampling from NLCD 2001 impervious surface in unchanged areas, impervious surface predictions were estimated for changed areas within an urban extent defined by a companion land cover classification. Methods were developed and tested for national application across six study sites containing a variety of urban impervious surface. Results show the vast majority of impervious surface change associated with urban development was captured, with overall RMSE from 6.86 to 13.12% for these areas. Changes of urban development density were also evaluated by characterizing the categories of change by percentile for impervious surface. This prototype method provides a relatively low cost, flexible approach to generate updated impervious surface using NLCD 2001 as the baseline.

  17. Assessing Land Use-Cover Changes and Modelling Change Scenarios in Two Mountain Spanish National Parks

    Directory of Open Access Journals (Sweden)

    Javier Martínez-Vega

    2017-11-01

    Full Text Available Land Use-Cover Changes (LUCCs are one of the main problems for the preservation of biodiversity. Protected Areas (PAs do not escape this threat. Some processes, such as intensive recreational use, forest fires or the expansion of artificial areas taking place inside and around them in response to their appeal, question their environmental sustainability and their efficiency. In this paper, we analyze the LUCCs that took place between 1990 and 2006 in two National Parks (NPs belonging to the Spanish network and in their surroundings: Ordesa and Monte Perdido (Ordesa NP and Sierra de Guadarrama (Guadarrama NP. We also simulate land use changes between 2006 and 2030 by means of Artificial Neural Networks (ANNs, taking into account two scenarios: trend and green. Finally, we perform a multi-temporal analysis of natural habitat fragmentation in each NP. The results show that the NPs analyzed are well-preserved and have seen hardly any significant LUCCs inside them. However, Socioeconomic Influence Zones (SIZs and buffers are subject to different dynamics. In the SIZ and buffer of the Ordesa NP, there has been an expansion of built-up areas (annual rate of change = +1.19 around small urban hubs and ski resorts. There has also been a gradual recovery of natural areas, which had been interrupted by forest fires. The invasion of sub-alpine grasslands by shrubs is clear (+2735 ha. The SIZ and buffer of the Guadarrama NP are subject to urban sprawl in forest areas and to the construction of road infrastructures (+5549 ha and an annual rate of change = +1.20. Industrial area has multiplied by 3.3 in 20 years. The consequences are an increase in the Wildland-Urban Interface (WUI, greater risk of forest fires and greater fragmentation of natural habitats (+0.04 in SIZ. In the change scenarios, if conditions change as expected, the specific threats facing each NP can be expected to increase. There are substantial differences between the scenarios depending on

  18. 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...

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

    Science.gov (United States)

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

    2016-07-20

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

  20. 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.

  1. High Resolution Population Maps for Low Income Nations: Combining Land Cover and Census in East Africa

    Science.gov (United States)

    Tatem, Andrew J.; Noor, Abdisalan M.; von Hagen, Craig; Di Gregorio, Antonio; Hay, Simon I.

    2007-01-01

    Background Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas. Methodology/Principal Findings We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps. Conclusions We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km2. The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available. PMID:18074022

  2. High resolution population maps for low income nations: combining land cover and census in East Africa.

    Directory of Open Access Journals (Sweden)

    Andrew J Tatem

    2007-12-01

    Full Text Available Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km(2. The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk and are freely available.

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

    Directory of Open Access Journals (Sweden)

    Jian Gong

    2015-11-01

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

  4. National Land Cover Database 2001 (NLCD01) Tree Canopy Layer Tile 4, Southeast United States: CNPY01_4

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the tree canopy layer 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, browse graphic: 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 (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) and 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 browse graphic: 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.

  5. National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 3, Southwest United States: IMPV01_3

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the imperviousness layer 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, browse graphic: nlcd01-partition. 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 (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) and 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 browse graphic: 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.

  6. National Land Cover Database 2001 (NLCD01) Tree Canopy Layer Tile 2, Northeast United States: CNPY01_2

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the tree canopy layer 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, browse graphic: 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 (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) and 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 browse graphic: 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.

  7. National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 4, Southeast United States: IMPV01_4

    Science.gov (United States)

    Wieczorek, Michael; LaMotte, Andrew E.

    2010-01-01

    This 30-meter resolution data set represents the imperviousness layer 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, browse graphic: nlcd01-partition. 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 (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) and 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 browse graphic: 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.

  8. National Land Cover Database 2001 (NLCD01) Tree Canopy Layer Tile 1, Northwest United States: CNPY01_1

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the tree canopy layer 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, browse graphic: 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 (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) and 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 browse graphic: nlcd01-mappingzones.jpg were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping-zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov

  9. National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 2, Northeast United States: IMPV01_2

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the imperviousness layer 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, browse graphic: nlcd01-partition. 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 (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) and 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 browse graphic: nlcd01-mappingzones.jpg were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping-zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  10. National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 1, Northwest United States: IMPV01_1

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the imperviousness layer 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, browse graphic: nlcd01-partition. 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 (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) and 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 browse graphic: nlcd01-mappingzones.jpg were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping-zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  11. National Land Cover Database 2001 (NLCD01) Tree Canopy Layer Tile 3, Southwest United States: CNPY01_3

    Science.gov (United States)

    LaMotte, Andrew E.; Wieczorek, Michael

    2010-01-01

    This 30-meter resolution data set represents the tree canopy layer 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, browse graphic: 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 (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) and 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 browse graphic: nlcd01-mappingzones.jpg were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping-zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

  12. Generating a National Land Cover Dataset for Mexico at 30m Spatial Resolution in the Framework of the NALCMS Project.

    Science.gov (United States)

    Llamas, R. M.; Colditz, R. R.; Ressl, R.; Jurado Cruz, D. A.; Argumedo, J.; Victoria, A.; Meneses, C.

    2017-12-01

    The North American Land Change Monitoring System (NALCMS) is a tri-national initiative for mapping land cover across Mexico, United States and Canada, integrating efforts of institutions from the three countries. At the continental scale the group released land cover and change maps derived from MODIS image mosaics at 250m spatial resolution for 2005 and 2010. Current efforts are based on 30m Landsat images for 2010 ± 1 year. Each country uses its own mapping approach and sources for ancillary data, while ensuring that maps are produced in a coherent fashion across the continent. This paper presents the methodology and final land cover map of Mexico for the year 2010 that was later integrated into a continental map. The principal input for Mexico was the Monitoring Activity Data for Mexico (MAD-MEX) land cover map (version 4.3), derived from all available mostly cloud-free images for the year 2010. A total of 35 classes were regrouped to 15 classes of the NALCMS legend present in Mexico. Next, various issues of the automatically generated MAD-MEX land cover mosaic were corrected, such as: filling areas of no data due no cloud-free observation or gaps in Landsat 7 ETM+ images, filling inland water bodies which were left unclassified due to masking issues, relabeling isolated unclassified of falsely classified pixels, structural mislabeling due to data gaps, reclassifying areas of adjacent scenes with significant class disagreements and correcting obvious misclassifications, mostly of water and urban areas. In a second step minor missing areas and rare class snow and ice were digitized and a road network was added. A product such as NALCMS land cover map at 30m for North America is an unprecedented effort and will be without doubt an important source of information for many users around the world who need coherent land cover data over a continental domain as an input for a wide variety of environmental studies. The product release to the general public is expected

  13. Spatial and Temporal Land Cover Changes in the Simen Mountains National Park, a World Heritage Site in Northwestern Ethiopia

    Directory of Open Access Journals (Sweden)

    Menale Wondie

    2011-04-01

    Full Text Available The trend of land cover (LC and land cover change (LCC, both in time and space, was investigated at the Simen Mountains National Park (SMNP, a World Heritage Site located in northern Ethiopia, between 1984 and 2003 using Geographical Information System (GIS and remote sensing (RS. The objective of the study was to generate spatially and temporally quantified information on land cover dynamics, providing the basis for policy/decision makers and resource managers to facilitate biodiversity conservation, including wild animals. Two satellite images (Landsat TM of 1984 and Landsat ETM+ of 2003 were acquired and supervised classification was used to categorize LC types. Ground Control Points were obtained in field condition for georeferencing and accuracy assessment. The results showed an increase in the areas of pure forest (Erica species dominated and shrubland but a decrease in the area of agricultural land over the 20 years. The overall accuracy and the Kappa value of classification results were 88 and 85%, respectively. The spatial setting of the LC classes was heterogeneous and resulted from the biophysical nature of SMNP and anthropogenic activities. Further studies are suggested to evaluate the existing LC and LCC in connection with wildlife habitat, conservation and management of SMNP.

  14. Assessment of Land-Cover/Land-Use Change and Landscape Patterns in the Two National Nature Reserves of Ebinur Lake Watershed, Xinjiang, China

    Directory of Open Access Journals (Sweden)

    Fei Zhang

    2017-05-01

    Full Text Available Land-cover and land-use change (LCLUC alters landscape patterns and affects regional ecosystems. The objective of this study was to examine LCLUC and landscape patterns in Ebinur Lake Wetland National Nature Reserve (ELWNNR and Ganjia Lake Haloxylon Forest National Nature Reserve (GLHFNNR, two biodiversity-rich national nature reserves in the Ebinur Lake Watershed (ELW, Xinjiang, China. Landsat satellite images from 1972, 1998, 2007 and 2013 were used to calculate the dynamics of a land-cover and land-use (LCLU transition matrix and landscape pattern index using ENVI 5.1 and FRAGSTATS 3.3. The results showed drastic land use modifications have occurred in ELWNNR during the past four decades. Between 1972 and 1998, 1998 and 2007, and 2007 and 2013, approximately 251.50 km2 (7.93%, 122.70 km2 (3.87%, and 195.40 km2 (6.16% of wetland were turned into salinized land. In GLHFNNR both low and medium density Haloxylon forest area declined while high density Haloxylon forest area increased. This contribution presents a method for characterizing LCLUC using one or more cross-tabulation matrices based on Sankey diagrams, demonstrating the depiction of flows of energy or materials through ecosystem network. The ecological landscape index displayed that a unique landscape patches have shrunk in size, scattered, and fragmented. It becomes a more diverse landscape. Human activities like farming were negatively correlated with the landscape diversity of wetlands. Furthermore, evidence of degraded wetlands caused by air temperature and annual precipitation, was also observed. We conclude that national and regional policies related to agriculture and water use have significantly contributed to the extensive changes; the ELWNNR and GLHFNNR are highly susceptible to LCLUC in the surrounding Ebinur Lake Watershed.

  15. 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...

  16. 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...

  17. 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...

  18. 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.

  19. Millennium Ecosystem Assessment: MA Rapid Land Cover Change

    Data.gov (United States)

    National Aeronautics and Space Administration — The Millennium Ecosystem Assessment: MA Rapid Land Cover Change provides data and information on global and regional land cover change in raster format for...

  20. High Resolution Urban Land Cover Mapping Using NAIP Aerial Photography and Image Processing for the USEPA National Atlas of Sustainability and Ecosystem Services

    Science.gov (United States)

    Pilant, A. N.; Baynes, J.; Dannenberg, M.

    2012-12-01

    The US EPA National Atlas for Sustainability is a web-based, easy-to-use, mapping application that allows users to view and analyze multiple ecosystem services in a specific region. The Atlas provides users with a visual method for interpreting ecosystem services and understanding how they can be conserved and enhanced for a sustainable future. The Urban Atlas component of the National Atlas will provide fine-scale information linking human health and well-being to environmental conditions such as urban heat islands, near-road pollution, resource use, access to recreation, drinking water quality and other quality of life indicators. The National Land Cover Data (NLCD) derived from 30 m scale 2006 Landsat imagery provides the land cover base for the Atlas. However, urban features and phenomena occur at finer spatial scales, so higher spatial resolution and more current LC maps are required. We used 4 band USDA NAIP imagery (1 m pixel size) and various classification approaches to produce urban land cover maps with these classes: impervious surface, grass and herbaceous, trees and forest, soil and barren, and water. Here we present the remote sensing methods used and results from four pilot cities in this effort, highlighting the pros and cons of the approach, and the benefits to sustainability and ecosystem services analysis. Example of high resolution land cover map derived from USDA NAIP aerial photo. Compare 30 m and 1 m resolution land cover maps of downtown Durham, NC.

  1. Central American Vegetation/Land Cover Classification and Conservation Status

    Data.gov (United States)

    National Aeronautics and Space Administration — The Central American Vegetation/Land Cover Classification and Conservation Status data set consists of GIS coverages of vegetation classes (forests, woodlands,...

  2. Land Use and Land Cover Change Analysis along the Coastal ...

    African Journals Online (AJOL)

    Agribotix GCS 077

    are carried out on the land usually effect changes in its cover. ... The FAO document on land cover classification systems, (2000) partly answers this ... over the surface land, including water, vegetation, bare soils and or artificial structures. ... diseases may occur more readily in areas exposed by Land Use and Land Cover ...

  3. 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...

  4. 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...

  5. Land use and cover change as an overarching topic in the Dutch National Research Programme on Global Air Pollution and Climate Change : issues for implementation

    NARCIS (Netherlands)

    Fresco, L.O.; Berg, van den M.M.; Zeijl-Rozema, van A.E.

    1996-01-01

    The integration study 'Land Use and Cover Change as an overarching topic in the Dutch National Research Programme on Global Air Pollution and Climate Change (NRP)' aims at identifying research fields in which the NRP can contribute most effectively to the international scientific

  6. ISLSCP II Historical Land Cover and Land Use, 1700-1990

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set...

  7. Computer implemented land cover classification using LANDSAT MSS digital data: A cooperative research project between the National Park Service and NASA. 3: Vegetation and other land cover analysis of Shenandoah National Park

    Science.gov (United States)

    Cibula, W. G.

    1981-01-01

    Four LANDSAT frames, each corresponding to one of the four seasons were spectrally classified and processed using NASA-developed computer programs. One data set was selected or two or more data sets were marged to improve surface cover classifications. Selected areas representing each spectral class were chosen and transferred to USGS 1:62,500 topographic maps for field use. Ground truth data were gathered to verify the accuracy of the classifications. Acreages were computed for each of the land cover types. The application of elevational data to seasonal LANDSAT frames resulted in the separation of high elevation meadows (both with and without recently emergent perennial vegetation) as well as areas in oak forests which have an evergreen understory as opposed to other areas which do not.

  8. Statistical Monitoring of Changes to Land Cover

    KAUST Repository

    Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying

    2018-01-01

    Accurate detection of changes in land cover leads to better understanding of the dynamics of landscapes. This letter reports the development of a reliable approach to detecting changes in land cover based on remote sensing and radiometric data

  9. 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...

  10. Land cover changes in central Sonora Mexico

    Science.gov (United States)

    Diego Valdez-Zamudio; Alejandro Castellanos-Villegas; Stuart Marsh

    2000-01-01

    Remote sensing techniques have been demonstrated to be very effective tools to help detect, analyze, and evaluate land cover changes in natural areas of the world. Changes in land cover can generally be attributed to either natural or anthropogenic forces. Multitemporal satellite imagery and airborne videography were used to detect, analyze, and evaluate land cover...

  11. Validation of land use / land cover changes for Denmark

    DEFF Research Database (Denmark)

    Levin, Gregor; Johannsen, Vivian Kvist; Caspersen, Ole Hjort

    2018-01-01

    This report presents applied methods and results for a validation of land use and land cover changes for 1990 and 2014-2016. Results indicate that generally, accuracies of land use and land cover. However, afforestation and particularly deforestation are significantly overestimated....

  12. Removing non-urban roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011

    Science.gov (United States)

    Soulard, Christopher E.; Acevedo, William; Stehman, Stephen V.

    2018-01-01

    Quantifying change in urban land provides important information to create empirical models examining the effects of human land use. Maps of developed land from the National Land Cover Database (NLCD) of the conterminous United States include rural roads in the developed land class and therefore overestimate the amount of urban land. To better map the urban class and understand how urban lands change over time, we removed rural roads and small patches of rural development from the NLCD developed class and created four wall-to-wall maps (1992, 2001, 2006, and 2011) of urban land. Removing rural roads from the NLCD developed class involved a multi-step filtering process, data fusion using geospatial road and developed land data, and manual editing. Reference data classified as urban or not urban from a stratified random sample was used to assess the accuracy of the 2001 and 2006 urban and NLCD maps. The newly created urban maps had higher overall accuracy (98.7 percent) than the NLCD maps (96.2 percent). More importantly, the urban maps resulted in lower commission error of the urban class (23 percent versus 57 percent for the NLCD in 2006) with the trade-off of slightly inflated omission error (20 percent for the urban map, 16 percent for NLCD in 2006). The removal of approximately 230,000 km2 of rural roads from the NLCD developed class resulted in maps that better characterize the urban footprint. These urban maps are more suited to modeling applications and policy decisions that rely on quantitative and spatially explicit information regarding urban lands.

  13. Land-cover change and avian diversity in the conterminous United States

    Science.gov (United States)

    Chadwick D. Rittenhouse; Anna M. Pidgeon; Thomas P. Albright; Patrick D. Culbert; Murray K. Clayton; Curtis H. Flather; Jeffrey G. Masek; Volker C. Radeloff

    2012-01-01

    Changes in land use and land cover have affected and will continue to affect biological diversity worldwide. Yet, understanding the spatially extensive effects of land-cover change has been challenging because data that are consistent over space and time are lacking. We used the U.S. National Land Cover Dataset Land Cover Change Retrofit Product and North American...

  14. Land cover's refined classification based on multi source of remote sensing information fusion: a case study of national geographic conditions census in China

    Science.gov (United States)

    Cheng, Tao; Zhang, Jialong; Zheng, Xinyan; Yuan, Rujin

    2018-03-01

    The project of The First National Geographic Conditions Census developed by Chinese government has designed the data acquisition content and indexes, and has built corresponding classification system mainly based on the natural property of material. However, the unified standard for land cover classification system has not been formed; the production always needs converting to meet the actual needs. Therefore, it proposed a refined classification method based on multi source of remote sensing information fusion. It takes the third-level classes of forest land and grassland for example, and has collected the thematic data of Vegetation Map of China (1:1,000,000), attempts to develop refined classification utilizing raster spatial analysis model. Study area is selected, and refined classification is achieved by using the proposed method. The results show that land cover within study area is divided principally among 20 classes, from subtropical broad-leaved forest (31131) to grass-forb community type of low coverage grassland (41192); what's more, after 30 years in the study area, climatic factors, developmental rhythm characteristics and vegetation ecological geographical characteristics have not changed fundamentally, only part of the original vegetation types have changed in spatial distribution range or land cover types. Research shows that refined classification for the third-level classes of forest land and grassland could make the results take on both the natural attributes of the original and plant community ecology characteristics, which could meet the needs of some industry application, and has certain practical significance for promoting the product of The First National Geographic Conditions Census.

  15. 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...

  16. 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...

  17. 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...

  18. Utilizing NASA Earth Observations to Assist the National Park Service in Monitoring Shoreline Land Cover Change in the Lower Grand Canyon

    Science.gov (United States)

    Stevens, C. L.; Phillips, A.; Young, S.; Counts, A.

    2017-12-01

    Sustained drought conditions have contributed to a significant decrease in the volume of the Colorado River in the Lake Mead reservoir and lower portion of the Grand Canyon. As a result, changes in riparian conditions have occurred in the region, such as sediment exposure and receding vegetation. These changes have large negative impacts on ecological health, including water and air pollution, aquatic, terrestrial and avian habitat alterations, and invasive species introduction. Scientists at Grand Canyon National Park seek to quantify changes in water surface and land cover area in the Lower Grand Canyon from 1998 to 2016 to better understand the effects of these changing conditions within the park. Landsat imagery was used to detect changes of the water surface and land cover area across this time period to assess the effects of long-term drought on the riparian zone. The resulting land cover and water surface time-series from this project will assist in monitoring future changes in water, sediment, and vegetation extent, increasing the ability of park scientists to create adaptation strategies for the ecosystem in the Lower Grand Canyon.

  19. Building a Continental Scale Land Cover Monitoring Framework for Australia

    Science.gov (United States)

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

    2012-04-01

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

  20. Assessment of environmental responses to land use/land cover ...

    African Journals Online (AJOL)

    aghomotsegin

    2013-12-17

    Dec 17, 2013 ... 49.86% of the land cover has been converted to other land uses, ... management information system and policies that will ensure sustainable management of fragile ...... growth in agricultural output such as food and fiber.

  1. Border Lakes land-cover classification

    Science.gov (United States)

    Marvin Bauer; Brian Loeffelholz; Doug. Shinneman

    2009-01-01

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

  2. 2005 C-CAP Land Cover of Oahu, Hawaii

    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...

  3. Towards Seamless Validation of Land Cover Data

    Science.gov (United States)

    Chuprikova, Ekaterina; Liebel, Lukas; Meng, Liqiu

    2018-05-01

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

  4. Evaluating The Land Use And Land Cover Dynamics In Borena ...

    African Journals Online (AJOL)

    The integration of satellite remote sensing and GIS was an effective approach for analyzing the direction, rate, and spatial pattern of land use change. Three land use and land cover maps were produced by analyzing remotely sensed images of Landsat satellite imageries at three time points (1972,1985,and 2003) .

  5. 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

  6. Scenarios of land cover in China

    Science.gov (United States)

    Yue, Tian Xiang; Fan, Ze Meng; Liu, Ji Yuan

    2007-02-01

    A method for surface modeling of land cover change (SMLC) is developed on the basis of establishing transition probability matrixes between land cover types and HLZ types. SMLC is used to simulate land cover scenarios of China for the years 2039, 2069 and 2099, for which HLZ scenarios are first simulated in terms of HadCM3 climatic scenarios that are downscaled in zonal model of spatial climate change in China. This paper also analyzes spatial distribution of land cover types, area change and mean center shift of each land cover type, ecotope diversity, and patch connectivity under the land cover scenarios. The results show that cultivated land would decrease and woodland would expand greatly with climatic change, which coincides with consequences expected by implementation of Grain-for-Green policy. Nival area would shrink, and desertification area would expand at a comparatively slow rate in future 100 years. Climate change would generally cause less ecotope diversity and more patch connectivity. Ecosystems in China would have a pattern of beneficial cycle after efficient ecological conservation and restoration. However, if human activities would exceed regulation capacity of ecosystems themselves, the ecosystems in China might deteriorate more seriously.

  7. 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...

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

    OpenAIRE

    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 methodology was applied. Thirty land cover classes were discerned. Most extended land cover types were pastures (231), arable land (211) and complex cultivation patterns (242). Between 1986 and 2000 aroun...

  9. Statistical Monitoring of Changes to Land Cover

    KAUST Repository

    Zerrouki, Nabil

    2018-04-06

    Accurate detection of changes in land cover leads to better understanding of the dynamics of landscapes. This letter reports the development of a reliable approach to detecting changes in land cover based on remote sensing and radiometric data. This approach integrates the multivariate exponentially weighted moving average (MEWMA) chart with support vector machines (SVMs) for accurate and reliable detection of changes to land cover. Here, we utilize the MEWMA scheme to identify features corresponding to changed regions. Unfortunately, MEWMA schemes cannot discriminate between real changes and false changes. If a change is detected by the MEWMA algorithm, then we execute the SVM algorithm that is based on features corresponding to detected pixels to identify the type of change. We assess the effectiveness of this approach by using the remote-sensing change detection database and the SZTAKI AirChange benchmark data set. Our results show the capacity of our approach to detect changes to land cover.

  10. Land cover fire proneness in Europe

    Directory of Open Access Journals (Sweden)

    Mario Gonzalez Pereira

    2014-12-01

    Full Text Available Aim of study: This study aims to identify and characterize the spatial and temporal evolution of the types of vegetation that are most affected by forest fires in Europe. The characterization of the fuels is an important issue of the fire regime in each specific ecosystem while, on the other hand, fire is an important disturbance for global vegetation dynamics.Area of study: Southern European countries: Portugal, Spain, France, Italy and Greece.Material and Methods: Corine Land Cover maps for 2000 and 2006 (CLC2000, CLC2006 and burned area (BA perimeters, from 2000 to 2013 in Europe are combined to access the spatial and temporal evolution of the types of vegetation that are most affected by wild fires using descriptive statistics and Geographical Information System (GIS techniques.Main results: The spatial and temporal distribution of BA perimeters, vegetation and burnt vegetation by wild fires was performed and different statistics were obtained for Mediterranean and entire Europe, confirming the usefulness of the proposed land cover system. A fire proneness index is proposed to assess the fire selectivity of land cover classes. The index allowed to quantify and to compare the propensity of vegetation classes and countries to fire.Research highlights: The usefulness and efficiency of the land cover classification scheme and fire proneness index. The differences between northern Europe and southern Europe and among the Mediterranean region in what concerns to vegetation cover, fire incidence, area burnt in land cover classes and fire proneness between classes for the different countries.Keywords: Fire proneness; Mixed forests; Land cover/land use; Fire regime; Europe; GIS; Corine land cover

  11. LBA-ECO ND-01 Land Cover Classification, Rondonia, Brazil: 1975-2000

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides a time series of land cover classifications for Ariquemes, Ji-Parana, and Luiza, research sites in Rondonia, Brazil. The land cover...

  12. ISLSCP II IGBP DISCover and SiB Land Cover, 1992-1993

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set describes the geographic distributions of 17 classes of land cover based on the International Geosphere-Biosphere DISCover land cover legend (Loveland...

  13. 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...

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

    Science.gov (United States)

    Latifovic, Rasim; Zhu, Zhi-Liang

    2004-01-01

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

  15. 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

  16. 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...

  17. 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...

  18. Review of Land Use and Land Cover Change research progress

    Science.gov (United States)

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

    2018-02-01

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

  19. Constancy and cover of plants in the Petersburg and Wrangell Districts, Tongass National Forest and associated private and other public lands, southeast Alaska.

    Science.gov (United States)

    Bert R. Mead

    2002-01-01

    This study provides a comprehensive and inclusive description and inventory of the vegetation within the Stikine area of southeast Alaska. Private and other public lands were included as well as Tongass National Forest lands contained in the Petersburg and Wrangell Ranger Districts. Previous inventories have concentrated almost exclusively on tree species within forest...

  20. 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).

  1. Nations need national land administration infrastructures

    NARCIS (Netherlands)

    Bennett, Rohan; Rajabifard, Abbas; Williamson, Ian; Wallace, Jude

    2012-01-01

    Many nations lack a coherent national approach to land administration. Instead, land information and processes are frequently disaggregated across states, provinces, cantons, counties, and municipalities. This is particularly the case in federated countries. The growing body of land administration

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

    Science.gov (United States)

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

    2012-01-01

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

  3. 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...

  4. 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.

  5. 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.

  6. Louisiana Land Cover Data Set, UTM Zone 15 NAD83, USGS [landcover_la_nlcd_usgs_2001.tif

    Data.gov (United States)

    Louisiana Geographic Information Center — The National Land Cover Database 2001 land cover layer for mapping zone 37A was produced through a cooperative project conducted by the Multi-Resolution Land...

  7. LBA-ECO LC-01 Landsat TM Land Use/Land Cover, Northern Ecuadorian Amazon: 1986-1999

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes:...

  8. LBA-ECO LC-01 Landsat TM Land Use/Land Cover, Northern Ecuadorian Amazon: 1986-1999

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest,...

  9. Carbon Assessment of Hawaii Land Cover Map (CAH_LandCover)

    Data.gov (United States)

    Department of the Interior — While there have been many maps produced that depict vegetation for the state of Hawai‘i only a few of these display land cover for all of the main Hawaiian Islands,...

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

    Science.gov (United States)

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

    2017-12-01

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

  11. The GOFC-GOLD/CEOS Land Cover Harmonization and Validation Initiative: Technical Design and Implementation

    Science.gov (United States)

    Herold, M.; Woodcock, C.; Stehman, S.; Nightingale, J.; Friedl, M.; Schmullius, C.

    2010-12-01

    A global effort to assess the accuracy of existing and future land cover products derived from a variety of satellite sensors over a range of spatial resolutions is being led by the Land Cover Implementation Team (LC-IT) of GOFC/GOLD (Global Observation of Land Cover Dynamics) in conjunction with the CEOS (Committee on Earth Observation Satellites) WGCV (Working Group on Calibration and Validation) LPV (Land Product Validation) subgroup. The first phase of this effort is complete and culminated in a publication of community consensus "best practices" for validation of global land cover datasets (2). The next phase is to implement the recommendations outlined in the "best practices" document. A "living database" of global randomized sample sites will form the basis of accuracy assessment for a host of global land cover products (GLC2000, MODIS land cover, GLOBCOVER, United Nation's Forest Resource Assessment (FRA2010), and the Mid-Decadal Global Land Survey. This "living dataset" will also be a community resource available for use in validation of regional or national mapping efforts using LCCS (UN FAO's Land Cover Classification System). Based on the known accuracy of existing land cover products, GOFC/GOLD will to develop and update a "best currently available" global land cover map. Individual geographic regions may be selected from different land cover products (global, national or regional), or they may be combined in various ways

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

    Science.gov (United States)

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

    1997-01-01

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

  13. The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 Streams and Catchments (Version 2.1) for the Conterminous United States: 2006 National Land Cover Database Agricultural Land Cover on Slopes

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data...

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

    Science.gov (United States)

    Efthimiou, Nikolaos; Psomiadis, Emmanouil

    2018-04-25

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

  15. 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

  16. Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams

    Science.gov (United States)

    Strode, Georgianna; Mesev, Victor; Thornton, Benjamin; Jerez, Marjorie; Tricarico, Thomas; McAlear, Tyler

    2018-05-01

    The terms `land use' and `land cover' typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

  17. Coastal Change Analysis Program (C-CAP) Regional Land Cover Data and Change Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  18. NOAA's Coastal Change Analysis Program (C-CAP) 2001 Regional Land Cover Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  19. NOAA's Coastal Change Analysis Program (C-CAP) 2016 Regional Land Cover Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  20. NOAA's Coastal Change Analysis Program (C-CAP) 2006 Regional Land Cover Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  1. NOAA's Coastal Change Analysis Program (C-CAP) 1985 Regional Land Cover Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  2. NOAA's Coastal Change Analysis Program (C-CAP) 1996 Regional Land Cover Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  3. NOAA's Coastal Change Analysis Program (C-CAP) 1992 Regional Land Cover Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  4. Coastal Change Analysis Program (C-CAP) High Resolution Land Cover and Change Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized high resolution land cover and change products for the coastal regions of the U.S....

  5. Monitoring land Cover Changes and Fragmentation dynamics in the ...

    African Journals Online (AJOL)

    Monitoring land Cover Changes and Fragmentation dynamics in the subtropical thicket of the Eastern Cape Province, South Africa. ... Baseline land use/cover maps and fragmentation analyses in a temporal framework are valuable for gaining insights into, among other things, carbon stock change trends. Keywords: Land ...

  6. 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.

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

    Science.gov (United States)

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

    2008-01-01

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

  8. 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.

  9. Land cover change in coastal watersheds 1996 to 2010

    Science.gov (United States)

    Nate Herold

    2016-01-01

    Land use and land cover play a significant role as drivers of environmental change. Information on what is changing and where those changes are occurring is essential if we are to improve our understanding of...

  10. the implications of land use/cover dynamics on resources

    African Journals Online (AJOL)

    2017-12-04

    Dec 4, 2017 ... Land use maps were produced using the GIS software packages of ... Keywords: Land use/cover, Dynamics, Remote Sensing Techniques, Geographic Information System, .... sporadic floods and landslides in Bambui which.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

    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

  12. 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.

  13. CORINE land cover and floristic variation in a Mediterranean wetland.

    Science.gov (United States)

    Giallonardo, Tommaso; Landi, Marco; Frignani, Flavio; Geri, Francesco; Lastrucci, Lorenzo; Angiolini, Claudia

    2011-11-01

    The aims of the present study were to: (1) investigate whether CORINE land cover classes reflect significant differences in floristic composition, using a very detailed CORINE land cover map (scale 1:5000); (2) decompose the relationships between floristic assemblages and three groups of explanatory variables (CORINE land cover classes, environmental characteristics and spatial structure) into unique and interactive components. Stratified sampling was used to select a set of 100-m(2) plots in each land cover class identified in the semi-natural wetland surrounding a lake in central Italy. The following six classes were considered: stable meadows, deciduous oak dominated woods, hygrophilous broadleaf dominated woods, heaths and shrublands, inland swamps, canals or watercourses. The relationship between land cover classes and floristic composition was tested using several statistical techniques in order to determine whether the results remained consistent with different procedures. The variation partitioning approach was applied to identify the relative importance of three groups of explanatory variables in relation to floristic variation. The most important predictor was land cover, which explained 20.7% of the variation in plant distribution, although the hypothesis that each land cover class could be associated with a particular floristic pattern was not verified. Multi Response Permutation Analysis did not indicate a strong floristic separability between land cover classes and only 9.5% of species showed a significant indicator value for a specific land cover class. We suggest that land cover classes linked with hygrophilous and herbaceous communities in a wetland may have floristic patterns that vary with fine scale and are not compatible with a land cover map.

  14. The impact of Future Land Use and Land Cover Changes on Atmospheric Chemistry-Climate Interactions

    NARCIS (Netherlands)

    Ganzeveld, L.N.; Bouwman, L.

    2010-01-01

    To demonstrate potential future consequences of land cover and land use changes beyond those for physical climate and the carbon cycle, we present an analysis of large-scale impacts of land cover and land use changes on atmospheric chemistry using the chemistry-climate model EMAC (ECHAM5/MESSy

  15. U.S. landowner behavior, land use and land cover changes, and climate change mitigation.

    Science.gov (United States)

    Ralph J. Alig

    2003-01-01

    Landowner behavior is a major determinant of land use and land cover changes. an important consideration for policy analysts concerned with global change. Study of landowner behavior aids in designing more effective incentives for inducing land use and land cover changes to help mitigate climate change by reducing net greenhouse gas emissions. Afforestation,...

  16. 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....

  17. EnviroAtlas - New Bedford, MA - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The New Bedford, MA Meter-Scale Urban Land Cover (MULC) data were generated from United States Department of Agriculture (USDA) National Agricultural Imagery Program...

  18. EnviroAtlas - Austin, TX - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Austin, TX EnviroAtlas One Meter-scale Urban Land Cover (MULC) Data were generated from United States Department of Agriculture (USDA) National Agricultural...

  19. EnviroAtlas - Pittsburgh, PA - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Pittsburgh, PA Meter-Scale Urban Land Cover (MULC) data was generated from United States Department of Agriculture (USDA) National Agricultural...

  20. C-CAP Land Cover, United States Virgin Islands, St Thomas, 2012

    Data.gov (United States)

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

  1. C-CAP Land Cover, United States Virgin Islands, St. Croix, 2012

    Data.gov (United States)

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

  2. LBA Regional Land Cover from AVHRR, 1-Degree, 1987 (Defries and Townshend)

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the Large Scale...

  3. SAFARI 2000 Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files formats.

  4. LBA Regional Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set is a subset of an 8-km global land cover product (DeFries et al. 1998). This subset was created for the study area of the Large Scale...

  5. LBA Regional Land Cover from AVHRR, 1-Degree, 1987 (Defries and Townshend)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the...

  6. SAFARI 2000 Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files...

  7. LBA Regional Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set is a subset of an 8-km global land cover product (DeFries et al. 1998). This subset was created for the study area of the Large Scale...

  8. LBA-ECO CD-34 Landsat Fractional Land Cover Analysis, Manaus, Brazil: 2004-2005

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides the results of fractional land cover analysis for nonphotosynthetic vegetation (NPV) from two Landsat images of Manaus, Brazil, for October...

  9. EnviroAtlas - Milwaukee, WI - Meter-Scale Urban Land Cover Data (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Milwaukee, WI Meter Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green,...

  10. EnviroAtlas - Tampa, FL - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Tampa, FL Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue...

  11. EnviroAtlas - Woodbine, IA - Meter-Scale Urban Land Cover (MULC) Data (2011)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Woodbine, IA Meter-Scale Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red,...

  12. EnviroAtlas - Phoenix, AZ - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Phoenix, AZ Meter-Scale Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red,...

  13. EnviroAtlas - Durham, NC - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Durham, NC Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue...

  14. EnviroAtlas - Portland, ME - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Portland, ME Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green,...

  15. 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

  16. Land-cover mapping of Red Rock Canyon National Conservation Area and Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern, Clark County, Nevada

    Science.gov (United States)

    Smith, J. LaRue; Damar, Nancy A.; Charlet, David A.; Westenburg, Craig L.

    2014-01-01

    DigitalGlobe’s QuickBird satellite high-resolution multispectral imagery was classified by using Visual Learning Systems’ Feature Analyst feature extraction software to produce land-cover data sets for the Red Rock Canyon National Conservation Area and the Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern in Clark County, Nevada. Over 1,000 vegetation field samples were collected at the stand level. The field samples were classified to the National Vegetation Classification Standard, Version 2 hierarchy at the alliance level and above. Feature extraction models were developed for vegetation on the basis of the spectral and spatial characteristics of selected field samples by using the Feature Analyst hierarchical learning process. Individual model results were merged to create one data set for the Red Rock Canyon National Conservation Area and one for each of the Areas of Critical Environmental Concern. Field sample points and photographs were used to validate and update the data set after model results were merged. Non-vegetation data layers, such as roads and disturbed areas, were delineated from the imagery and added to the final data sets. The resulting land-cover data sets are significantly more detailed than previously were available, both in resolution and in vegetation classes.

  17. 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.

  18. 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.

  19. 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 runoff data and LULC change patterns (only 2015 for LID-BMPs) were used. Results show that the expansion of bare land and impervious cover, soil alteration, and high amount of precipitation influenced the stormwater runoff variability during different phases of land development. The four aggregate LID-BMPs reduced runoff volume (34%-61%), peak flow (6%-19%), and pollutant concentrations (53%-83%). The results of this study, in addition to supporting local LULC planning and land development activities, also could be applied to input data for empirical modeling, and designing sustainable stormwater management guidelines and monitoring strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS

    Directory of Open Access Journals (Sweden)

    K. Fukue

    2016-06-01

    Full Text Available The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year SR(Surface Reflectance and NBAR(Nadir BRDF-Adjusted Reflectance products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.

  1. 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.

  2. Chittenden County, Vermont land cover project

    Science.gov (United States)

    Malloy, D. E.

    1981-01-01

    The testing of LANDSAT applicability to urban and agricultural land use analysis at the substate level is described. It is concluded that the LANDSAT system has a place in Vermont and places like it, but that the present operation is inadequate and the need for technology transfer and excellent communication between the producers and users is fundamental to the future of the system and for the realization of benefit from the investment.

  3. 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

  4. The causes of land-use and land-cover change : moving beyond the myths

    NARCIS (Netherlands)

    Lambin, E.F.; Turner, B.L.; Geist, H.J.; Agbola, S.B.; Angelsen, A.; Bruce, J.W.; Coomes, O.T.; Dirzo, R.; Fischer, G.; Folke, C.; George, P.S.; Homewood, K.; Imbernon, J.; Leemans, R.; Xiubin Li,; Moran, E.F.; Mortimore, M.; Ramakrishnan, P.S.; Richards, J.F.; Skanes, H.; Steffen, W.; Stone, G.D.; Svedin, U.; Veldkamp, A.; Vogel, C.; Jianchu Xu,

    2001-01-01

    Common understanding of the causes of land-use and land-cover change is dominated by simplifications which, in turn, underlie many environment-development policies. This article tracks some of the major myths on driving forces of land-cover change and proposes alternative pathways of change that are

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

    Science.gov (United States)

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

    2013-01-01

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

  6. Use of UAV-Borne Spectrometer for Land Cover Classification

    Directory of Open Access Journals (Sweden)

    Sowmya Natesan

    2018-04-01

    Full Text Available Unmanned aerial vehicles (UAV are being used for low altitude remote sensing for thematic land classification using visible light and multi-spectral sensors. The objective of this work was to investigate the use of UAV equipped with a compact spectrometer for land cover classification. The UAV platform used was a DJI Flamewheel F550 hexacopter equipped with GPS and Inertial Measurement Unit (IMU navigation sensors, and a Raspberry Pi processor and camera module. The spectrometer used was the FLAME-NIR, a near-infrared spectrometer for hyperspectral measurements. RGB images and spectrometer data were captured simultaneously. As spectrometer data do not provide continuous terrain coverage, the locations of their ground elliptical footprints were determined from the bundle adjustment solution of the captured images. For each of the spectrometer ground ellipses, the land cover signature at the footprint location was determined to enable the characterization, identification, and classification of land cover elements. To attain a continuous land cover classification map, spatial interpolation was carried out from the irregularly distributed labeled spectrometer points. The accuracy of the classification was assessed using spatial intersection with the object-based image classification performed using the RGB images. Results show that in homogeneous land cover, like water, the accuracy of classification is 78% and in mixed classes, like grass, trees and manmade features, the average accuracy is 50%, thus, indicating the contribution of hyperspectral measurements of low altitude UAV-borne spectrometers to improve land cover classification.

  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. Data mining algorithms for land cover change detection: a review

    Indian Academy of Sciences (India)

    Sangram Panigrahi

    2017-11-24

    Nov 24, 2017 ... values, poor quality measurement, high resolution and high dimensional data. The land cover .... These data sets also include quality assurance information, ...... 2012 A new data mining framework for forest fire mapping.

  9. 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...

  10. 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...

  11. 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...

  12. Assessing Wetland Health Using a Newly Developed Land Cover ...

    African Journals Online (AJOL)

    Citizen science combines environmental research with environmental education .... health of the wetland using land cover type impacts. Once the impact is ... to interpret the findings of the quantitative method using the qualitative findings.

  13. Effect of Feature Dimensionality on Object-based Land Cover ...

    African Journals Online (AJOL)

    Myburgh, G, Mnr

    features, it has not been demonstrated with land cover mapping in an ... classifiers were chosen for benchmarking as the latter is the most commonly .... Additional open-source libraries were acquired to complete the implementation of the.

  14. Land cover classification using reformed fuzzy C-means

    Indian Academy of Sciences (India)

    This paper uses segmentation based on unsupervised clustering techniques for classification of land cover. ∗ ... and unsupervised classification can be solved by FCM. ..... They also act as input to the development and monitoring of a range of ...

  15. Land use/cover change and perceived watershed status in Eastern ...

    African Journals Online (AJOL)

    ROBERT

    Five land use/cover types were identified namely; (1) ... The focus group discussion findings indicated a negative trend in land ... Awoja watershed in Kyoga Water Management Zone of eastern ... as compared to the national average of 11% (MWE, 2013). ... This was acquired from USGS Earth ... The unit of analysis was the.

  16. Temporal change detection of land use/land cover using GIS and ...

    African Journals Online (AJOL)

    Satellite images for the years 1972, 1989, 1999 and 2016 were used for LULC ... built-up areas, pastures and bare land, agricultural land and water bodies. For the accuracy of assessment classifications, matrix error and KAPPA ... Keywords: land use/land cover change; change detection; classification; remote sensing; GIS ...

  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. 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...

  19. 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...

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

    Science.gov (United States)

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

    2017-12-01

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

  1. Spatial patterns of land cover in the United States: a technical document supporting the Forest Service 2010 RPA Assessment

    Science.gov (United States)

    Kurt H. Riitters

    2011-01-01

    Land cover patterns inventoried from a national land cover map provide information about the landscape context and fragmentation of the Nation’s forests, grasslands, and shrublands. This inventory is required to quantify, map, and evaluate the capacities of landscapes to provide ecological goods and services sustainably. This report documents the procedures to...

  2. 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...

  3. 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.

  4. Classification of Land Cover and Land Use Based on Convolutional Neural Networks

    Science.gov (United States)

    Yang, Chun; Rottensteiner, Franz; Heipke, Christian

    2018-04-01

    Land cover describes the physical material of the earth's surface, whereas land use describes the socio-economic function of a piece of land. Land use information is typically collected in geospatial databases. As such databases become outdated quickly, an automatic update process is required. This paper presents a new approach to determine land cover and to classify land use objects based on convolutional neural networks (CNN). The input data are aerial images and derived data such as digital surface models. Firstly, we apply a CNN to determine the land cover for each pixel of the input image. We compare different CNN structures, all of them based on an encoder-decoder structure for obtaining dense class predictions. Secondly, we propose a new CNN-based methodology for the prediction of the land use label of objects from a geospatial database. In this context, we present a strategy for generating image patches of identical size from the input data, which are classified by a CNN. Again, we compare different CNN architectures. Our experiments show that an overall accuracy of up to 85.7 % and 77.4 % can be achieved for land cover and land use, respectively. The classification of land cover has a positive contribution to the classification of the land use classification.

  5. Land-Cover Change in the East Central Texas Plains, 1973-2000

    Science.gov (United States)

    Karstensen, Krista A.

    2009-01-01

    Project Background: The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-use and land-cover change. The objectives of the study are to: (1) develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) data for measuring regional land-cover change across the United States, (2) characterize the types, rates and temporal variability of change for a 30-year period, (3) document regional driving forces and consequences of change, and (4) prepare a national synthesis of land-cover change (Loveland and others, 1999). Using the 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) as the geographic framework, geospatial data collected between 1973 and 2000 were processed and analyzed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000. General land-cover classes such as water, developed, grassland/shrubland, and agriculture for these periods were interpreted from Landsat MSS, TM, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land-Use Land-Cover Classification System for image interpretation. The interpretation of these land-cover classes complement the program objective of looking at land-use change with cover serving as a surrogate for land use. The land-cover change rates are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historical aerial photographs from similar timeframes and other

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

    Science.gov (United States)

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

    2018-06-01

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

  7. NOAA's Coastal Change Analysis Program (C-CAP) 2006 to 2016 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  8. NOAA's Coastal Change Analysis Program (C-CAP) 2001 to 2016 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  9. NOAA's Coastal Change Analysis Program (C-CAP) 1992 to 2001 Regional Land Cover Change Data - Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  10. NOAA's Coastal Change Analysis Program (C-CAP) 1985 to 2006 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  11. NOAA's Coastal Change Analysis Program (C-CAP) 1996 to 2001 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  12. NOAA's Coastal Change Analysis Program (C-CAP) 2001 to 2005 Regional Land Cover Change Data - Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  13. NOAA's Coastal Change Analysis Program (C-CAP) 1992 to 2006 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  14. NOAA's Coastal Change Analysis Program (C-CAP) 2001 to 2006 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  15. NOAA's Coastal Change Analysis Program (C-CAP) 1996 to 2010 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  16. NOAA's Coastal Change Analysis Program (C-CAP) 2006 to 2010 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  17. NOAA's Coastal Change Analysis Program (C-CAP) 1992 to 2001 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  18. NOAA's Coastal Change Analysis Program (C-CAP) 1975 to 2010 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  19. NOAA's Coastal Change Analysis Program (C-CAP) 1996 to 2016 Regional Land Cover Change Data - Coastal United States

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

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

    Science.gov (United States)

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

    2009-01-01

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

  1. GlobeLand30 as an alternative fine-scale global land cover map

    DEFF Research Database (Denmark)

    Jokar Arsanjani, Jamal; Tayyebi, A.; Vaz, E.

    2016-01-01

    land cover information such as developing countries. In this study, we look at GlobeLand30 of 2010 for Iran in order to find out the accuracy of this dataset as well as its implications. By having looked at 6 selected study sites around larger cities representing dissimilar eco-regions covering rural...

  2. Land use/Land Cover Changes and Causes of Deforestation in the ...

    African Journals Online (AJOL)

    The objective of this paper is to provide the non-existent data on land use/land cover changes in the Wilberforce Island for the purposes of determining the causes of deforestation and changes in the vegetation cover for a 13 – year period. Accordingly, 125 questionnaires were administered in five communities to determine ...

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

    Science.gov (United States)

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

    2018-01-01

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

  4. 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...

  5. 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 unders...

  6. Rapid Land Cover Map Updates Using Change Detection and Robust Random Forest Classifiers

    Directory of Open Access Journals (Sweden)

    Konrad J. Wessels

    2016-10-01

    Full Text Available The paper evaluated the Landsat Automated Land Cover Update Mapping (LALCUM system designed to rapidly update a land cover map to a desired nominal year using a pre-existing reference land cover map. The system uses the Iteratively Reweighted Multivariate Alteration Detection (IRMAD to identify areas of change and no change. The system then automatically generates large amounts of training samples (n > 1 million in the no-change areas as input to an optimized Random Forest classifier. Experiments were conducted in the KwaZulu-Natal Province of South Africa using a reference land cover map from 2008, a change mask between 2008 and 2011 and Landsat ETM+ data for 2011. The entire system took 9.5 h to process. We expected that the use of the change mask would improve classification accuracy by reducing the number of mislabeled training data caused by land cover change between 2008 and 2011. However, this was not the case due to exceptional robustness of Random Forest classifier to mislabeled training samples. The system achieved an overall accuracy of 65%–67% using 22 detailed classes and 72%–74% using 12 aggregated national classes. “Water”, “Plantations”, “Plantations—clearfelled”, “Orchards—trees”, “Sugarcane”, “Built-up/dense settlement”, “Cultivation—Irrigated” and “Forest (indigenous” had user’s accuracies above 70%. Other detailed classes (e.g., “Low density settlements”, “Mines and Quarries”, and “Cultivation, subsistence, drylands” which are required for operational, provincial-scale land use planning and are usually mapped using manual image interpretation, could not be mapped using Landsat spectral data alone. However, the system was able to map the 12 national classes, at a sufficiently high level of accuracy for national scale land cover monitoring. This update approach and the highly automated, scalable LALCUM system can improve the efficiency and update rate of regional land

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

    International Nuclear Information System (INIS)

    Ngwana, T I; Demory, M-E; Vidale, P L; Plant, R S; Mbedzi, M P

    2010-01-01

    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.

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

    Science.gov (United States)

    Seo, B.; Bogner, C.; Poppenborg, P.; Martin, E.; Hoffmeister, M.; Jun, M.; Koellner, T.; Reineking, B.; Shope, C. L.; Tenhunen, J.

    2014-09-01

    Detailed data on land use and land cover constitute 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 the agricultural mosaic catchment Haean in South Korea. We recorded the land cover types with additional information on agricultural practice. In this paper we introduce the data, their collection and the post-processing protocol. Furthermore, because it is important to quantitatively evaluate available land use and land cover products, we compared our data with the MODIS Land Cover Type product (MCD12Q1). During the studied period, a large portion of dry fields was converted to perennial crops. Compared to our data, the forested area was underrepresented and the agricultural area overrepresented in MCD12Q1. In addition, linear landscape elements such as waterbodies were missing in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research. The data are available at the public repository Pangaea (doi:110.1594/PANGAEA.823677).

  9. C-CAP Land Cover, Kauai, Hawaii 2005

    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...

  10. C-CAP Land Cover, Territory of Guam 2011

    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...

  11. 2011 C-CAP Land Cover of Oahu, 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...

  12. C-CAP Land Cover, Big Island, 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. Land cover and topography affect the land transformation caused by wind facilities.

    Directory of Open Access Journals (Sweden)

    Jay E Diffendorfer

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

  14. Relationship between Organic Carbon Runoff to River and Land Cover

    Science.gov (United States)

    Kim, G. S.; Lee, S. G.; Lim, C. H.; Lee, W.; Yoo, S.; Kim, S. J.; Heo, S.; Lee, W. K.

    2017-12-01

    Carbon is an important unit in understanding the ecosystem and energy circulation. Each ecosystem, land, water, and atmosphere, is interconnected through the exchange of energy and organic carbon. In the rivers, primary producers utilize the organic carbon from the land. Understanding the organic carbon uptake into the river is important for understanding the mechanism of river ecosystems. The main organic carbon source of the river is land. However, it is difficult to observe the amount of organic carbon runoff to the river. Therefore, an indirect method should be used to estimate the amount of organic carbon runoff to the river. The organic carbon inflow is caused by the runoff of organic carbon dissolved in water or the inflow of organic carbon particles by soil loss. Therefore, the hydrological model was used to estimate organic carbon runoff through the flow of water. The land cover correlates with soil respiration, soil loss, and so on, and the organic carbon runoff coefficient will be estimated to the river by land cover. Using the organic carbon concentration from water quality data observed at each point in the river, we estimate the amount of organic carbon released from the land. The reason is that the runoff from the watershed converges into the rivers in the watershed, the watershed simulation is conducted based on the water quality data observation point. This defines a watershed that affects organic carbon observation sites. The flow rate of each watershed is calculated by the SWAT (Soil and Water Assessment Tool), and the total organic carbon runoff is calculated by using flow rate and organic carbon concentration. This is compared with the factors related to the amount of organic carbon such as land cover, soil loss, and soil organic carbon, and spatial analysis is carried out to estimate the organic carbon runoff coefficient per land cover.

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

    Science.gov (United States)

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

    2006-05-01

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

  16. Land-cover composition, water resources and land management in the watersheds of the Luquillo Mountains, northeastern Puerto Rico.

    Science.gov (United States)

    Tamara Heartsill Scalley; Tania del M. Lopez-Marrero

    2014-01-01

    An important element of the wise use of water-related ecosystem services provided by El Yunque National Forest, located in the Luquillo Mountains in northeastern Puerto Rico, is the facilitation of a clear understanding about the composition of land cover and its relation to water resources at different scales of analysis, management, and decision making. In this study...

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

    Science.gov (United States)

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

    2007-01-01

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

  18. Land Cover Land Use Change and Soil Organic Carbon under Climate Variability in the Semi-Arid West African Sahel (1960-2050)

    Science.gov (United States)

    Dieye, Amadou M.

    2016-01-01

    Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project…

  19. 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.

  20. 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

  1. Conversion of land use and cover in northwest Amazon (Brazil

    Directory of Open Access Journals (Sweden)

    Carlos Antonio da Silva Junior

    2014-09-01

    Full Text Available The increasing use of natural resources in a disorderly way has been demanding constant monitoring and ecological-economic zoning. The knowledge on land use and cover allows that measures that guarantee the preservation, maintenance of the environment and space management be appropriate to the reality, since through these factors it is possible to follow the probable environmental impacts and the socioeconomic development of a place in several contexts. The Geographical Information System (GIS and remote sensing techniques have been applied to land use and land cover mapping. This study aimed to analyze the conversion of land use from different perspectives, concerning geoprocessing techniques, in the southeastern of Roraima State, Brazil, in two distinct periods. In order to verify the land use and cover, two analyses were conducted, using the Spring and TerraView softwares. Great part of the cultivated areas was converted into capoeira, what probably denotes an ending of profitable agriculture, as well as its abandonment caused by the nutritional deficiency of the soil, that became inappropriate for cultivation in the subsequent years. A fuzzy logic would possibly fit well to the types of data analyzed, because the attribute query is overly complex.

  2. Integrating land cover and terrain characteristics to explain plague ...

    African Journals Online (AJOL)

    Literature suggests that higher resolution remote sensing data integrated in Geographic Information System (GIS) can provide greater possibility to refine the analysis of land cover and terrain characteristics for explanation of abundance and distribution of plague hosts and vectors and hence of health risk hazards to ...

  3. 1 Integrating land cover and terrain characteristics to explain plague ...

    African Journals Online (AJOL)

    influence of land cover and terrain factors on the abundance and spatial distribution ... factors operating at diverse scales, including climate (Debien et al., 2009; Ben Ari .... A cloud free three-band SPOT 5 image captured on 27 February 2007, ...

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

    African Journals Online (AJOL)

    KwaZulu-Natal. Abstract—Current land cover and development in the coastal zone of KwaZulu- ... 75% by 2025 in some regions (Hinrichsen, 1995). .... Functional divisions and case study areas on the KZN coast. .... Extent of development and access via major road networks along the KZN North and South Coasts. 198.

  5. Land cover classification using reformed fuzzy C-means

    Indian Academy of Sciences (India)

    This paper explains the task of land cover classification using reformed fuzzy C means. Clustering is the assignment of objects into groups called clusters so that objects from the same cluster are more similar to each other than objects from different clusters. The most basic attribute for clustering of an image is its luminance ...

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

    Science.gov (United States)

    Barile, D. D.; Pierce, R.

    1977-01-01

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

  7. A Synthesis of Studies on Land Use and Land Cover Dynamics during 1930–2015 in Bangladesh

    Directory of Open Access Journals (Sweden)

    Raju Rai

    2017-10-01

    Full Text Available Land use and land cover (LULC is dynamic and changes in it have important environmental and socio-economic consequences. The pathways and pace of change vary with space and time and are related to the interaction between human activities and biophysical conditions in an area. This study provides a systematic review of the changing status, patterns, and compositions of LULC in Bangladesh on national, regional, and local scales over the past 85 years. The primary LULC classes in Bangladesh are agricultural land, urban and built-up area, forest and vegetation, water bodies, and wetlands. Most of the country is covered with agricultural land, followed by urban areas; the latter has been expanding rapidly in the area surrounding the capital city, Dhaka, especially the southern capital area. Forest cover is mostly concentrated in southeast Bangladesh, the Chittagong district, and the mangrove forests are predominantly located in the southwest, with the Gangetic delta. High population growth, rapid urbanization, and infrastructure development have been directly associated with changing patterns of land use across the country. In recent decades, urban areas and water bodies have been increasing, to the detriment of both forests and agricultural land. Most of the studies reviewed here describe a general trend involving agricultural and forested land being transformed into urban areas.

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

    Science.gov (United States)

    Karstensen, Krista A.

    2010-01-01

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

  9. 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)...

  10. 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)...

  11. 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)...

  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 (USEPA)...

  13. 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)...

  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 (USEPA)...

  15. 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)...

  16. 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)...

  17. 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)...

  18. 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)...

  19. 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)...

  20. 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)...

  1. 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)...

  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 (USEPA)...

  3. 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)...

  4. 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)...

  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. 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)...

  8. 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)...

  9. 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)...

  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. 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)...

  12. 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)...

  13. 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)...

  14. 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)...

  15. 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)...

  16. Study on Classification Accuracy Inspection of Land Cover Data Aided by Automatic Image Change Detection Technology

    Science.gov (United States)

    Xie, W.-J.; Zhang, L.; Chen, H.-P.; Zhou, J.; Mao, W.-J.

    2018-04-01

    The purpose of carrying out national geographic conditions monitoring is to obtain information of surface changes caused by human social and economic activities, so that the geographic information can be used to offer better services for the government, enterprise and public. Land cover data contains detailed geographic conditions information, thus has been listed as one of the important achievements in the national geographic conditions monitoring project. At present, the main issue of the production of the land cover data is about how to improve the classification accuracy. For the land cover data quality inspection and acceptance, classification accuracy is also an important check point. So far, the classification accuracy inspection is mainly based on human-computer interaction or manual inspection in the project, which are time consuming and laborious. By harnessing the automatic high-resolution remote sensing image change detection technology based on the ERDAS IMAGINE platform, this paper carried out the classification accuracy inspection test of land cover data in the project, and presented a corresponding technical route, which includes data pre-processing, change detection, result output and information extraction. The result of the quality inspection test shows the effectiveness of the technical route, which can meet the inspection needs for the two typical errors, that is, missing and incorrect update error, and effectively reduces the work intensity of human-computer interaction inspection for quality inspectors, and also provides a technical reference for the data production and quality control of the land cover data.

  17. Evaluation of the National Land Database for Hydrologic Applications in Urban And Suburban Baltimore, Maryland

    Science.gov (United States)

    Monica Lipscomb Smith; Weiqi Zhou; Mary Cadenasso; J. Morgan Grove; Lawrence. Band

    2010-01-01

    We compared the National Land Cover Database (NLCD) 2001 land cover, impervious, and canopy data products to land cover data derived from 0.6-m resolution three-band digital imagery and ancillary data. We conducted this comparison at the 1 km2, 9 km2, and gauged watershed scales within the Baltimore Ecosystem Study to...

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

    African Journals Online (AJOL)

    Dr Osondu

    Zimbabwe's fast-track land reform programme and other economic activities have caused ... Geographic Information System and remote sensing techniques. ... 1990 and 2009 Landsat images of the district were downloaded from the Global Land cover Facility as well ... Information System (GIS) are now providing new.

  19. Land use and land cover dynamics in the Brazilian Amazon: an overview

    Science.gov (United States)

    Robert Walker; Alfredo Kingo Oyama Homma

    1996-01-01

    This paper presents a theoretical discussion of processes linking land use decisions and land cover outcomes at household level, with an emphasis on small proceduers. Evidence from the literature substantiating the existence of domestic cycle phenomena is brought forward and interpreted for the Brazilian case. Also considered are the relative disposition of production...

  20. 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...

  1. Projecting land-use and land cover change in a subtropical urban watershed

    Science.gov (United States)

    John J. Lagrosa IV; Wayne C. Zipperer; Michael G. Andreu

    2018-01-01

    Urban landscapes are heterogeneous mosaics that develop via significant land-use and land cover (LULC) change. Current LULC models project future landscape patterns, but generally avoid urban landscapes due to heterogeneity. To project LULC change for an urban landscape, we parameterize an established LULC model (Dyna-CLUE) under baseline conditions (continued current...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. Internal Migration and Land Use and Land Cover Changes in the Middle Mountains of Nepal

    Directory of Open Access Journals (Sweden)

    Bhawana KC

    2017-11-01

    Full Text Available The movement of rural households from remote uplands to valley floors and to semiurban and urban areas (internal migration is a common phenomenon in the middle mountain districts of Nepal. Understanding the causes and effects of internal migration is critical to the development and implementation of policies that promote land use planning and sustainable resource management. Using geospatial information technologies and social research methods, we investigated the causes and effects of internal migration on land use and land cover patterns in a western mountain district of Nepal between 1998 and 2013. The results show a decreasing number of households at high elevations (above 1400 m, where an increase in forest cover has been observed with a consequent decrease in agricultural land and shrub- or grassland. At lower elevations (below 1400 m, forest cover has remained constant over the last 25 years, and the agricultural land area has increased but has become geometrically complex to meet the diverse needs and living requirements of the growing population. Our findings indicate that internal migration plays an important role in shaping land use and land cover change in the middle mountains of Nepal and largely determines the resource management, utilization, and distribution patterns within a small geographic unit. Therefore, land use planning must take an integrated and interdisciplinary approach rather than considering social, environmental, and demographic information in isolation.

  7. 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...

  8. Drivers and Implications of Land Use and Land Cover Change in the ...

    African Journals Online (AJOL)

    This study explores the major drivers of Land-use/Land-cover (LULC) dynamics and the observed environmental degradation as a response to these changes in the Modjo watershed, central Ethiopia. Data for this study were generated through household survey and supplemented with remotely sensed image interpretation ...

  9. 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...

  10. 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...

  11. 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

    This document summarizes the major findings of a Gulf of Mexico Application Pilot project led by NASA Stennis Space Center (SSC) in conjunction with a regional collaboration network of the Gulf of Mexico Alliance (GOMA). NASA researchers processed and analyzed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL between 1974 and 2008. Our goal was to create satellite-based LULC data products using methods that could be transferable to other coastal areas of concern within the Gulf of Mexico. The Mobile Bay National Estuary Program (MBNEP) is the primary end-user, however, several other state and local groups may benefit from the project s data products that will be available through NOAA-NCDDC s Regional Ecosystem Data Management program. Mobile Bay is a critical ecologic and economic region in the Gulf of Mexico and to the entire country. Mobile Bay was designated as an estuary of national significance in 1996. This estuary receives the fourth largest freshwater inflow in the United States. It provides vital nursery habitat for commercially and recreationally important fish species. It has exceptional aquatic and terrestrial bio-diversity, however, its estuary health is influenced by changing LULC patterns, such as urbanization. Mobile and Baldwin counties have experienced a population growth of 1.1% and 20.5% from 2000-2006. Urban expansion and population growth are likely to accelerate with the construction and operation of the ThyssenKrupp steel mill in the northeast portion of Mobile County. Land-use and land-cover change can negatively impact Gulf coast water quality and ecological resources. The conversion of forest to urban cover types impacts the carbon cycle and increases the freshwater and sediment in coastal waters. Increased freshwater runoff decreases salinity and increases the turbidity of coastal waters, thus impacting the growth potential of submerged aquatic vegetation (SAV

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

    Science.gov (United States)

    Ambarwulan, W.; Widiatmaka; Nahib, I.

    2018-05-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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...

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

    Science.gov (United States)

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

    2018-03-01

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

  18. Effect of land cover change on runoff curve number estimation in Iowa, 1832-2001

    Science.gov (United States)

    Wehmeyer, Loren L.; Weirich, Frank H.; Cuffney, Thomas F.

    2011-01-01

    Within the first few decades of European-descended settlers arriving in Iowa, much of the land cover across the state was transformed from prairie and forest to farmland, patches of forest, and urbanized areas. Land cover change over the subsequent 126 years was minor in comparison. Between 1832 and 1859, the General Land Office conducted a survey of the State of Iowa to aid in the disbursement of land. In 1875, an illustrated atlas of the State of Iowa was published, and in 2001, the US Geological Survey National Land Cover Dataset was compiled. Using these three data resources for classifying land cover, the hydrologic impact of the land cover change at three points in time over a period of 132+ years is presented in terms of the effect on the area-weighted average curve number, a term commonly used to predict peak runoff from rainstorms. In the four watersheds studied, the area-weighted average curve number associated with the first 30 years of settlement increased from 61·4 to 77·8. State-wide mapped forest area over this same period decreased 19%. Over the next 126 years, the area-weighted average curve number decreased to 76·7, despite an additional forest area reduction of 60%. This suggests that degradation of aquatic resources (plants, fish, invertebrates, and habitat) arising from hydrologic alteration was likely to have been much higher during the 30 years of initial settlement than in the subsequent period of 126 years in which land cover changes resulted primarily from deforestation and urbanization. 

  19. Vegetation cover and land use of a protected coastal area and its surroundings, southeast Brazil

    OpenAIRE

    Caris,Elisa Araujo Penna; Kurtz,Bruno Coutinho; Cruz,Carla Bernadete Madureira; Scarano,Fabio Rubio

    2013-01-01

    We applied remote sensing techniques on a TM Landsat 5 image (1:50,000) to map land use and vegetation cover of the Restinga de Jurubatiba National Park and surroundings. The thematic map generated from the digital classification of the image allowed us to spatially characterize and quantify the different land uses and soil covers of the area. Thirteen classes were identified. The most representative classes in the park were the Clusia (31.99%) and Ericaceae formations (29.14%). More than 90%...

  20. LBA-ECO LC-24 Landsat TM and ETM+ Land Cover, Southern Para, Brazil: 1984-2003

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final...

  1. LBA-ECO LC-24 Landsat TM and ETM+ Land Cover, Southern Para, Brazil: 1984-2003

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final...

  2. LBA-ECO LC-07 JERS-1 SAR Wetlands Masks and Land Cover, Amazon Basin: 1995-1996

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides three Amazon Basin wetland image products: (1) a Central Amazon Wetlands Mask, (2) a Central Amazon Wetlands Vegetative-hydrologic Land Cover...

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

    Science.gov (United States)

    Bouchachi, B.; Zhong, Y.

    2017-09-01

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

  4. The Improvement of Land Cover Classification by Thermal Remote Sensing

    Directory of Open Access Journals (Sweden)

    Liya Sun

    2015-06-01

    Full Text Available Land cover classification has been widely investigated in remote sensing for agricultural, ecological and hydrological applications. Landsat images with multispectral bands are commonly used to study the numerous classification methods in order to improve the classification accuracy. Thermal remote sensing provides valuable information to investigate the effectiveness of the thermal bands in extracting land cover patterns. k-NN and Random Forest algorithms were applied to both the single Landsat 8 image and the time series Landsat 4/5 images for the Attert catchment in the Grand Duchy of Luxembourg, trained and validated by the ground-truth reference data considering the three level classification scheme from COoRdination of INformation on the Environment (CORINE using the 10-fold cross validation method. The accuracy assessment showed that compared to the visible and near infrared (VIS/NIR bands, the time series of thermal images alone can produce comparatively reliable land cover maps with the best overall accuracy of 98.7% to 99.1% for Level 1 classification and 93.9% to 96.3% for the Level 2 classification. In addition, the combination with the thermal band improves the overall accuracy by 5% and 6% for the single Landsat 8 image in Level 2 and Level 3 category and provides the best classified results with all seven bands for the time series of Landsat TM images.

  5. A high accuracy land use/cover retrieval system

    Directory of Open Access Journals (Sweden)

    Alaa Hefnawy

    2012-03-01

    Full Text Available The effects of spatial resolution on the accuracy of mapping land use/cover types have received increasing attention as a large number of multi-scale earth observation data become available. Although many methods of semi automated image classification of remotely sensed data have been established for improving the accuracy of land use/cover classification during the past 40 years, most of them were employed in single-resolution image classification, which led to unsatisfactory results. In this paper, we propose a multi-resolution fast adaptive content-based retrieval system of satellite images. Through our proposed system, we apply a Super Resolution technique for the Landsat-TM images to have a high resolution dataset. The human–computer interactive system is based on modified radial basis function for retrieval of satellite database images. We apply the backpropagation supervised artificial neural network classifier for both the multi and single resolution datasets. The results show significant improved land use/cover classification accuracy for the multi-resolution approach compared with those from single-resolution approach.

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

    Science.gov (United States)

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

    2017-08-01

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

  7. EnviroAtlas - Percent Stream Buffer Zone As Natural Land Cover for the Conterminous United States

    Science.gov (United States)

    This EnviroAtlas dataset shows the percentage of land area within a 30 meter buffer zone along the National Hydrography Dataset (NHD) high resolution stream network, and along water bodies such as lakes and ponds that are connected via flow to the streams, that is classified as forest land cover, modified forest land cover, and natural land cover using the 2006 National Land Cover Dataset (NLCD) for each Watershed Boundary Dataset (WBD) 12-digit hydrological unit (HUC) in the conterminous United States. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  8. 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.

  9. 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.

  10. 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.

  11. Land Cover Change Monitoring of Typical Functional Communities of Sichuan Province Based on ZY-3 Data

    Science.gov (United States)

    Li, G. M.; Li, S.; Ying, G. W.; Wu, X. P.

    2018-04-01

    According to the function, land space types are divided into key development areas, restricted development areas and forbidden development areas in Sichuan Province. This paper monitors and analyses the changes of land cover in different typical functional areas from 2010 to 2017, which based on ZY-3 high-score images data and combined with statistical yearbook and thematic data of Sichuan Province. The results show that: The land cover types of typical key development zones are mainly composed of cultivated land, forest land, garden land, and housing construction land, which accounts for the total area of land cover 87 %. The land cover types of typical restricted development zone mainly consists of forest land and grassland, which occupy 97.71 % of the total area of the surface coverage. The land cover types of the typical prohibition development zone mainly consist of forest land, grassland, desert and bared earth, which accounts for the total area of land cover 99.31 %.

  12. Combining NLCD and MODIS to create a land cover-albedo database for the continental United States

    Science.gov (United States)

    Wickham, J.; Barnes, Christopher A.; Nash, M.S.; Wade, T.G.

    2015-01-01

    Land surface albedo is an essential climate variable that is tightly linked to land cover, such that specific land cover classes (e.g., deciduous broadleaf forest, cropland) have characteristic albedos. Despite the normative of land-cover class specific albedos, there is considerable variability in albedo within a land cover class. The National Land Cover Database (NLCD) and the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product were combined to produce a long-term (14 years) integrated land cover-albedo database for the continental United States that can be used to examine the temporal behavior of albedo as a function of land cover. The integration identifies areas of homogeneous land cover at the nominal spatial resolution of the MODIS (MCD43A) albedo product (500 m × 500 m) from the NLCD product (30 m × 30 m), and provides an albedo data record per 500 m × 500 m pixel for 14 of the 16 NLCD land cover classes. Individual homogeneous land cover pixels have up to 605 albedo observations, and 75% of the pixels have at least 319 MODIS albedo observations (≥ 50% of the maximum possible number of observations) for the study period (2000–2013). We demonstrated the utility of the database by conducting a multivariate analysis of variance of albedo for each NLCD land cover class, showing that locational (pixel-to-pixel) and inter-annual variability were significant factors in addition to expected seasonal (intra-annual) and geographic (latitudinal) effects.

  13. Anthropogenic Influences in Land Use/Land Cover Changes in Mediterranean Forest Landscapes in Sicily

    Directory of Open Access Journals (Sweden)

    Donato S. La Mela Veca

    2016-01-01

    Full Text Available This paper analyzes and quantifies the land use/land cover changes of the main forest and semi-natural landscape types in Sicily between 1955 and 2012. We analyzed seven representative forest and shrubland landscapes in Sicily. These study areas were chosen for their importance in the Sicilian forest panorama. We carried out a diachronic survey on historical and current aerial photos; all the aerial images used to survey the land use/land cover changes were digitalized and georeferenced in the UTM WGS84 system. In order to classify land use, the Regional Forest Inventory 2010 legend was adopted for the more recent images, and the CORINE Land Cover III level used for the older, lower resolution images. This study quantifies forest landscape dynamics; our results show for almost all study areas an increase of forest cover and expansion, whereas a regressive dynamic is found in rural areas due to intensive agricultural and pasturage uses. Understanding the dynamics of forest landscapes could enhance the role of forestry policy as a tool for landscape management and regional planning.

  14. LAND COVER ASSESSMENT OF INDIGENOUS COMMUNITIES IN THE BOSAWAS REGION OF NICARAGUA

    Science.gov (United States)

    Data derived from remotely sensed images were utilized to conduct land cover assessments of three indigenous communities in northern Nicaragua. Historical land use, present land cover and land cover change processes were all identified through the use of a geographic informat...

  15. Land use, land cover, and drainage on the Albemarle-Pamlico Peninsula, Eastern North Carolina, 1974

    Science.gov (United States)

    Daniel, C.C.

    1978-01-01

    A land use, land cover, and drainage map of the 2,000-square-mile Albermarle-Pamlico peninsula of eastern North Carolina has been prepared, at a scale of 1:125,000, as part of a larger study of the effects of large-scale land clearing on regional hydrology. The peninsula includes the most extensive area of wetland in North Carolina and one of the largest in the country. In recent years the pace of land clearing on the peninsula has accelerated as land is being converted from forest, swamp, and brushland to agricultural use. Conversion of swamps to intensive farming operations requires profound changes in the landscape. Vegetation is uprooted and burned and ditches and canals are dug to remove excess water. What is the impact of these changes on ground-water supplies and on the streams and surrounding coastal waters which receive the runoff This map will aid in answering these and similar questions that have arisen about the patterns of land use and the artificial drainage system that removes excess water from the land. By showing both land use and drainage, this map can be used to identify those areas where water-related problems may occur and help assess the nature and causes of these problems. The map covers the entire area east of the Suffolk Scarp, an area of about 2,000 square miles, for the year 1974 using data from 1974-76. Land use and land cover were compiled and modified from the U.S. Geological Survey 's Rocky Mount and Manteo LUDA maps. Additional information came from U.S. Geological Survey orthophotoquads, Landsat imagery, and field checking. Drainage was mapped from orthophotoquads, some field inspection, and 7-1/2 minute topographic quadrangle maps.

  16. 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.

  17. Sustaining forest landscape connectivity under different land cover change scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Rubio, L.; Rodriguez-Freire, M.; Mateo-Sanchez, M. C.; Estreguil, C.; Saura, S.

    2012-11-01

    Managing forest landscapes to sustain functional connectivity is considered one of the key strategies to counteract the negative effects of climate and human-induced changes in forest species pools. With this objective, we evaluated whether a robust network of forest connecting elements can be identified so that it remains efficient when facing different types of potential land cover changes that may affect forest habitat networks and ecological fluxes. For this purpose we considered changes both in the forested areas and in the non-forest intervening landscape matrix. We combined some of the most recent developments in graph theory with models of land cover permeability and least-cost analysis through the forest landscape. We focused on a case of study covering the habitat of a forest dwelling bird (nuthatch, Sitta europaea) in the region of Galicia (NW Spain). Seven land-use change scenarios were analysed for their effects on connecting forest elements (patches and links): one was the simplest case in which the landscape is represented as a binary forest/non-forest pattern (and where matrix heterogeneity is disregarded), four scenarios in which forest lands were converted to other cover types (to scrubland due to wildfires, to extensive and intensive agriculture, and to urban areas), and two scenarios that only involved changes in the non-forested matrix (re naturalization and intensification). Our results show that while the network of connecting elements for the species was very robust to the conversion of the forest habitat patches to different cover types, the different change scenarios in the landscape matrix could more significantly weaken its long-term validity and effectiveness. This is particularly the case when most of the key connectivity providers for the nuthatch are located outside the protected areas or public forests in Galicia, where biodiversity-friendly measures might be more easily implemented. We discuss how the methodology can be applied to

  18. 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.

  19. 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.

  20. An Operational Framework for Land Cover Classification in the Context of REDD+ Mechanisms. A Case Study from Costa Rica

    Directory of Open Access Journals (Sweden)

    Alfredo Fernández-Landa

    2016-07-01

    Full Text Available REDD+ implementation requires robust, consistent, accurate and transparent national land cover historical data and monitoring systems. Satellite imagery is the only data source with enough periodicity to provide consistent land cover information in a cost-effective way. The main aim of this paper is the creation of an operational framework for monitoring land cover dynamics based on Landsat imagery and open-source software. The methodology integrates the entire land cover and land cover change mapping processes to produce a consistent series of Land Cover maps. The consistency of the time series is achieved through the application of a single trained machine learning algorithm to radiometrically normalized imagery using iteratively re-weighted multivariate alteration detection (IR-MAD across all dates of the historical period. As a result, seven individual Land Cover maps of Costa Rica were produced from 1985/1986 to 2013/2014. Post-classification land cover change detection was performed to evaluate the land cover dynamics in Costa Rica. The validation of the land cover maps showed an overall accuracy of 87% for the 2013/2014 map, 93% for the 2000/2001 map and 89% for the 1985/1986 map. Land cover changes between forest and non-forest classes were validated for the period between 2001 and 2011, obtaining an overall accuracy of 86%. Forest age-classes were generated through a multi-temporal analysis of the maps. By linking deforestation dynamics with forest age, a more accurate discussion of the carbon emissions along the time series can be presented.

  1. Land Use and Land Cover - Volusia County Future Land Use (FLU) 2010

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Volusia County Future Land Use 2010. This is the original land use map for 2010. It was drafted for the comprehensive plan in 1990 and contains adopted amendments.

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

    Science.gov (United States)

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

    2010-01-01

    INTRODUCTION Land-use and land-cover (LULC) data provide important information for environmental management. Data pertaining to land-cover and land-management activities are a common requirement for spatial analyses, such as watershed modeling, climate change, and hazard assessment. In coastal areas, land development, storms, and shoreline modification amplify the need for frequent and detailed land-cover datasets. The northern Gulf of Mexico coastal area is no exception. The impact of severe storms, increases in urban area, dramatic changes in land cover, and loss of coastal-wetland habitat all indicate a vital need for reliable and comparable land-cover data. Four main attributes define a land-cover dataset: the date/time of data collection, the spatial resolution, the type of classification, and the source data. The source data are the foundation dataset used to generate LULC classification and are typically remotely sensed data, such as aerial photography or satellite imagery. These source data have a large influence on the final LULC data product, so much so that one can classify LULC datasets into two general groups: LULC data derived from aerial photography and LULC data derived from satellite imagery. The final LULC data can be converted from one format to another (for instance, vector LULC data can be converted into raster data for analysis purposes, and vice versa), but each subsequent dataset maintains the imprint of the source medium within its spatial accuracy and data features. The source data will also influence the spatial and temporal resolution, as well as the type of classification. The intended application of the LULC data typically defines the type of source data and methodology, with satellite imagery being selected for large landscapes (state-wide, national data products) and repeatability (environmental monitoring and change analysis). The coarse spatial scale and lack of refined land-use categories are typical drawbacks to satellite

  3. IDENTIFICATION OF LAND COVER IN THE PAST USING INFRARED IMAGES AT PRESENT

    Directory of Open Access Journals (Sweden)

    V. Šafář

    2012-07-01

    Full Text Available Czech landscape is an old residential area used by humans since ancient times. People have influenced it since their arrival and various activities in different periods create landscape layers called a palimpsest. Land Cover of one location could have changed several times. The most important reason is meandering and subsequent straightening of rivers, deforestation, relocation and change in soil layers. These changes in the past affected the present management and it is important to identify them. A suitable tool for the determination of different sites is remote sensing in the infrared spectrum, which monitors changes in the vegetation with the support of archival materials. After identifying the different places you can search the archival materials, how the land cover looked in the past. There have been used these archival materials: maps II. and III. military mapping, basic maps and other maps and historical orthophotomap. Czech Republic has a national archive of aerial photographs with aerial photographs from the thirties of the last century maintained by MGHO Dobruska. A comparative analysis of Land Cover shows the increases and decreases in agricultural land, changes in communication line elements, forest losses and increases, comparing the legal and actual status of the forest boundaries and their changes over time, changes in the built areas and links to the surrounding countryside. Land Cover of this study was created primarily with a visual interpretation of each area with their vectorization and assigning attributes to these areas and then comparing each of archival materials.

  4. 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

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

    Science.gov (United States)

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

    2007-12-01

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

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

    Science.gov (United States)

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

    2009-04-01

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

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

    Science.gov (United States)

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

    2014-06-01

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

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  9. 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.

  10. Assessment of land use and land cover change in Tecolutla River Basin, Veracruz, Mexico; during the period 1994-2010

    Directory of Open Access Journals (Sweden)

    Ana Karen Osuna-Osuna

    2015-04-01

    Full Text Available Studies related to changes in vegetation and land use cover have gained importance in environmental research, as they allow for the assessment of time-space trends in deforestation and environmental degradation processes, especially as caused by human activity. In this context, the main goal of this study was to evaluate the impact of human activity in the basin of the Tecolutla River, in Veracruz, Mexico during a 16-year period. Landsat satellite images were used for the years 1994 and 2010, distinguishing nine land use coverage classes: rainforest, forest, agricultural land, water, disturbed vegetation, urban settlements, grasslands, citrus crops and shrubs. Thematic maps were validated, yielding overall accuracies greater than 92% and Kappa coefficients of 0.89 and 0.91 for the 1994 and 2010 classifications, respectively. Analysis of the transition matrix revealed a trend of increasing areas related to human activity (agriculture and urban use showing percentage changes of 28% and 67% within 16 years, respectively. Consequently, a decrease (-1.1% per year in areas with natural cover, specifically forest and jungle, was observed. Similar findings were reported in works done at national and state levels, where the transition of natural cover by the increasing of anthropogenic activities has been proven. The results of this study are useful for future environmental development planning, land management planning and planning strategies for the conservation of the natural resources in the basin.

  11. Measurement of semantic similarity for land use and land cover classification systems

    Science.gov (United States)

    Deng, Dongpo

    2008-12-01

    Land use and land cover (LULC) data is essential to environmental and ecological research. However, semantic heterogeneous of land use and land cover classification are often resulted from different data resources, different cultural contexts, and different utilities. Therefore, there is need to develop a method to measure, compare and integrate between land cover categories. To understand the meaning and the use of terminology from different domains, the common ontology approach is used to acquire information regarding the meaning of terms, and to compare two terms to determine how they might be related. Ontology is a formal specification of a shared conceptualization of a domain of interest. LULC classification system is a ontology. The semantic similarity method is used to compare to entities of three LULC classification systems: CORINE (European Environmental Agency), Oregon State, USA), and Taiwan. The semantic properties and relations firstly have been extracted from their definitions of LULC classification systems. Then semantic properties and relations of categories in three LULC classification systems are mutually compared. The visualization of semantic proximity is finally presented to explore the similarity or dissimilarity of data. This study shows the semantic similarity method efficiently detect semantic distance in three LULC classification systems and find out the semantic similar objects.

  12. Impact of land cover and population density on land surface temperature: case study in Wuhan, China

    Science.gov (United States)

    Li, Lin; Tan, Yongbin; Ying, Shen; Yu, Zhonghai; Li, Zhen; Lan, Honghao

    2014-01-01

    With the rapid development of urbanization, the standard of living has improved, but changes to the city thermal environment have become more serious. Population urbanization is a driving force of residential expansion, which predominantly influences the land surface temperature (LST). We obtained the land covers and LST maps of Wuhan from Landsat-5 images in 2000, 2002, 2005, and 2009, and discussed the distribution of land use/cover change and LST variation, and we analyzed the correlation between population distribution and LST values in residential regions. The results indicated massive variation of land cover types, which was shown as a reduction in cultivatable land and the expansion of building regions. High-LST regions concentrated on the residential and industrial areas with low vegetation coverage. In the residential region, the population density (PD) had effects on the LST values. Although the area or variation of residential regions was close, lower PD was associated with lower mean LST or LST variation. Thus, decreasing the high-LST regions concentration by reducing the PD may alleviate the urban heat island effect on the residential area. Taken together, these results can provide supports for urban planning projects and studies on city ecological environments.

  13. A hierarchical approach of hybrid image classification for land use and land cover mapping

    Directory of Open Access Journals (Sweden)

    Rahdari Vahid

    2018-01-01

    Full Text Available Remote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.

  14. Land Use Land Cover Change in the fringe of eThekwini ...

    African Journals Online (AJOL)

    Concerns on urban environmental quality, increasing knowledge on impacts of climate change and pursuit for sustainable development have increased the need for past, current and future knowledge on the transformation of remnant urban fringe green ecosystems. Using land-cover change modeler and a Markov chain ...

  15. Detection and Mapping of Land Use and Land Cover Classes of a ...

    African Journals Online (AJOL)

    FIRST LADY

    Cover Classes of a Developing City in Southeastern. Region of Nigeria .... The emergence of small and medium sized agro-husbandry industries in the peripheral, semi- ..... lack of spatial specialization a hindrance to integrated land management and development .... Journal of Applied Sciences Asian Network for Scientific ...

  16. Detecting and quantifying land use/land cover dynamics in Wadla ...

    African Journals Online (AJOL)

    A study was conducted in Wadla Delanta Massif to investigate land use/cover dynamics over the last four decades (1973-2014) using satellite images (1973 MSS, 1995 TM and 2014 ETM+). Global positioning system ... in the study area. Keywords: GIS, Image classification, Remote sensing, Supervised classification ...

  17. 81 An Assessment of the land use and land cover changes in ...

    African Journals Online (AJOL)

    `123456789jkl''''#

    Three satellite images for three different years (1991, 2000 and 2009) were used to come up with a ... land cover change maps among other data resources that are .... in agro-ecological region 3 that receives an average rainfall of .... After field observation and collection of .... the image along with statistical comparison of.

  18. Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

    Science.gov (United States)

    Di Vittorio, A. V.; Mao, J.; Shi, X.; Chini, L.; Hurtt, G.; Collins, W. D.

    2018-01-01

    Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. Here we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO2 in 2004, and generates carbon uncertainty that is equivalent to 80% of the net effects of CO2 and climate and 124% of the effects of nitrogen deposition during 1850-2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. We conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.

  19. 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.

  20. 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...

  1. 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...

  2. 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...

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

    Science.gov (United States)

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

    2018-01-01

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

  4. Land use/land cover study of urban features using spot imagery

    International Nuclear Information System (INIS)

    Mahmood, S.A.; Qureshi, J.; Abbas, I.

    2005-01-01

    This study is based on visual interpretation and classification of the urban area of Peshawar. Cloud free satellite image of the French SPOT System in panchromatic mode at 100m/pixel spatial detail was used for this purpose. The coverage area comprised nearly (7.5 x 6)sq. km. on the ground depicting the major portion of the city. Various image interpretation elements were exploited to accomplish the study, thirteen land cover classes were identified and demarcated on a tracing sheet. Having prepared the base map. Satellite image map was constructed by assigning disparate colors to the identified features. Dimensions of some of the prominent, regular and liner features were computed from the image. The results indicate that high-resolution satellite image can be effectively used for mapping and area estimation of urban land use/land cover features. (author)

  5. Estimation of evapotranspiration across the conterminous United States using a regression with climate and land-cover data

    Science.gov (United States)

    Sanford, Ward E.; Selnick, David L.

    2013-01-01

    Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water-balance method was combined with a climate and land-cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971-2000 across the U.S. to obtain long-term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land-cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land-cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land-cover data can also improve those predictions. Using the climate and land-cover data at an 800-m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land-cover data are plentiful.

  6. Multisource Data Fusion Framework for Land Use/Land Cover Classification Using Machine Vision

    Directory of Open Access Journals (Sweden)

    Salman Qadri

    2017-01-01

    Full Text Available Data fusion is a powerful tool for the merging of multiple sources of information to produce a better output as compared to individual source. This study describes the data fusion of five land use/cover types, that is, bare land, fertile cultivated land, desert rangeland, green pasture, and Sutlej basin river land derived from remote sensing. A novel framework for multispectral and texture feature based data fusion is designed to identify the land use/land cover data types correctly. Multispectral data is obtained using a multispectral radiometer, while digital camera is used for image dataset. It has been observed that each image contained 229 texture features, while 30 optimized texture features data for each image has been obtained by joining together three features selection techniques, that is, Fisher, Probability of Error plus Average Correlation, and Mutual Information. This 30-optimized-texture-feature dataset is merged with five-spectral-feature dataset to build the fused dataset. A comparison is performed among texture, multispectral, and fused dataset using machine vision classifiers. It has been observed that fused dataset outperformed individually both datasets. The overall accuracy acquired using multilayer perceptron for texture data, multispectral data, and fused data was 96.67%, 97.60%, and 99.60%, respectively.

  7. 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.

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

    International Nuclear Information System (INIS)

    John, Ranjeet; Chen Jiquan; Lu Nan; Wilske, Burkhard

    2009-01-01

    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 2 , respectively, have increased proportionally. Cropland and urban land use also increased to 0.15 million km 2 and 2197 km 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.

  9. Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

    Science.gov (United States)

    Hansen, M.C.; Egorov, Alexey; Potapov, P.V.; Stehman, S.V.; Tyukavina, A.; Turubanova, S.A.; Roy, David P.; Goetz, S.J.; Loveland, Thomas R.; Ju, J.; Kommareddy, A.; Kovalskyy, Valeriy; Forsyth, C.; Bents, T.

    2014-01-01

    Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ time-series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (GoogleEarth™) classification; however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national-scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by

  10. Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

    OpenAIRE

    Moran, Emilio Federico.

    2010-01-01

    High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervi...

  11. Fine Resolution Probabilistic Land Cover Classification of Landscapes in the Southeastern United States

    Directory of Open Access Journals (Sweden)

    Joseph St. Peter

    2018-03-01

    Full Text Available Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a methodology that uses recent advances in spatial analysis software to create a land cover classification over a large region in the southeastern United States at a fine (1 m spatial resolution. This methodology used image texture metrics and principle components derived from National Agriculture Imagery Program (NAIP aerial photographic imagery, visually classified locations, and a softmax neural network model. The model efficiently produced classification surfaces at 1 m resolution across roughly 11.6 million hectares (28.8 million acres with less than 10% average error in modeled probability. The classification surfaces consist of probability estimates of 13 visually distinct classes for each 1 m cell across the study area. This methodology and the tools used in this study constitute a highly flexible fine resolution land cover classification that can be applied across large extents using standard computer hardware, common and open source software and publicly available imagery.

  12. Soil chemical and physical properties that differentiate urban land-use and cover types

    Science.gov (United States)

    R.V. Pouyat; I.D. Yesilonis; J. Russell-Anelli; N.K. Neerchal

    2007-01-01

    We investigated the effects of land use and cover and surface geology on soil properties in Baltimore, MD, with the objectives to: (i) measure the physical and chemical properties of surface soils (0?10 cm) by land use and cover; and (ii) ascertain whether land use and cover explain differences in these properties relative to surface geology. Mean and median values of...

  13. Does estuarine health relate to catchment land-cover in the East ...

    African Journals Online (AJOL)

    Possible links between catchment and buffer zone land-cover class composition and the health of the East Kleinemonde Estuary were explored. There was a relationship between catchment land-cover and estuarine health within all assessed catchment delineations. Natural land-cover was determined to be the best ...

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

    Science.gov (United States)

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

    2017-10-01

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

  15. 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...

  16. Effect of land-use/land-cover change on the future of rainfed agriculture in the Jenin Governorate, Palestine

    NARCIS (Netherlands)

    Thawaba, Salem; Abu-Madi, Maher; Özerol, Gül

    2017-01-01

    Land cover has been changed by humans throughout history. At the global level, population growth and socio-economic development have a significant impact on land resources. Recently, scholars added climate change as one of the major factors affecting land-cover transformation. In the West Bank of

  17. Measuring land-use and land-cover change using the U.S. department of agriculture's cropland data layer: Cautions and recommendations

    Science.gov (United States)

    Lark, Tyler J.; Mueller, Richard M.; Johnson, David M.; Gibbs, Holly K.

    2017-10-01

    Monitoring agricultural land is important for understanding and managing food production, environmental conservation efforts, and climate change. The United States Department of Agriculture's Cropland Data Layer (CDL), an annual satellite imagery-derived land cover map, has been increasingly used for this application since complete coverage of the conterminous United States became available in 2008. However, the CDL is designed and produced with the intent of mapping annual land cover rather than tracking changes over time, and as a result certain precautions are needed in multi-year change analyses to minimize error and misapplication. We highlight scenarios that require special considerations, suggest solutions to key challenges, and propose a set of recommended good practices and general guidelines for CDL-based land change estimation. We also characterize a problematic issue of crop area underestimation bias within the CDL that needs to be accounted for and corrected when calculating changes to crop and cropland areas. When used appropriately and in conjunction with related information, the CDL is a valuable and effective tool for detecting diverse trends in agriculture. By explicitly discussing the methods and techniques for post-classification measurement of land-cover and land-use change using the CDL, we aim to further stimulate the discourse and continued development of suitable methodologies. Recommendations generated here are intended specifically for the CDL but may be broadly applicable to additional remotely-sensed land cover datasets including the National Land Cover Database (NLCD), Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover products, and other regional, national, and global land cover classification maps.

  18. 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. Copyright © 2014. Published by Elsevier Ltd.

  19. 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.

  20. 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.

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

    Science.gov (United States)

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

    2010-12-01

    vegetation at vertical distribution in the Sagamasha area located in the southern slope is slightly higer than than in the Mt. Qomolangma region due to its better regional water and heat conditions. 3. The distribution patterns of the main land cover types in the Mt. Qomolangma region during 1976-2006 don’t change greatly. The land cover changes during the two periods (1976-1988, 1988-2006) have shown a good consistency. The most prominent changing characteristics are: significant glacier retreat, more bare rock outcrops, rapid expansion of glacial lake covered bare rock, lakes shrinking and wetlands growth, wetlands being reclaimed as farmland in the prior period and significant reduce of cultivated land in the latter period. The research have been analyzed the glaciers, wetland and other cover types that are sensitive to climate change. The relationship between the land cover types and climate change, the impacts of human activities on land cover change and the effectiveness of protected area have been discussed. Foundation: The National Basic Research Program of China, Grant No.2005CB422006 & 2010CB951704; External Cooperation Program of the Chinese Academy of Sciences, No.GJHZ0954

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

    Science.gov (United States)

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

    2016-01-01

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

  3. An assessment of support vector machines for land cover classification

    Science.gov (United States)

    Huang, C.; Davis, L.S.; Townshend, J.R.G.

    2002-01-01

    The support vector machine (SVM) is a group of theoretically superior machine learning algorithms. It was found competitive with the best available machine learning algorithms in classifying high-dimensional data sets. This paper gives an introduction to the theoretical development of the SVM and an experimental evaluation of its accuracy, stability and training speed in deriving land cover classifications from satellite images. The SVM was compared to three other popular classifiers, including the maximum likelihood classifier (MLC), neural network classifiers (NNC) and decision tree classifiers (DTC). The impacts of kernel configuration on the performance of the SVM and of the selection of training data and input variables on the four classifiers were also evaluated in this experiment.

  4. Assessment of the thematic accuracy of land cover maps

    DEFF Research Database (Denmark)

    Høhle, Joachim

    2015-01-01

    were applied (‘Decision Tree’ and ‘Support Vector Machine’) using only two attributes (height above ground and normalized difference vegetation index) which both are derived from the images. The assessment of the thematic accuracy applied a stratified design and was based on accuracy measures...... methods perform equally for five classes. Trees are classified with a much better accuracy and a smaller confidence interval by means of the decision tree method. Buildings are classified by both methods with an accuracy of 99% (95% CI: 95%-100%) using independent 3D checkpoints. The average width......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...

  5. Ecology of Land Cover Change in Glaciated Tropical Mountains

    Directory of Open Access Journals (Sweden)

    Kenneth R. Young

    2014-12-01

    Full Text Available Tropical mountains contain unique biological diversity, and are subject to many consequences of global climate change, exasperated by concurrent socioeconomic shifts. Glaciers are in a negative mass balance, exposing substrates to primary succession and altering downslope wetlands and streams. A review of recent trends and future predictions suggests a likely reduction in areas of open habitat for species of high mountains due to greater woody plant cover, accompanied by land use shifts by farmers and pastoralists along the environmental gradients of tropical mountains. Research is needed on the biodiversity and ecosystem consequences of successional change, including the direct effects of retreating glaciers and the indirect consequences of combined social and ecological drivers in lower elevations. Areas in the high mountains that are protected for nature conservation or managed collectively by local communities represent opportunities for integrated research and development approaches that may provide ecological spaces for future species range shifts.

  6. Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey

    OpenAIRE

    Baysal, Gülendam

    2013-01-01

    Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies. This research was conducted to analyze the land use and land cover changes and to model the changes for the case study area Malatya, Turkey. The first step of the study was acquisition of multi temporal data in order to detect the changes over the time. For this purpose satellite images (Landsat 1990-2000-2010) have been used. In order to acquire data from satel...

  7. Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

    Science.gov (United States)

    Rußwurm, Marc; Körner, Marco

    2018-03-01

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

  8. Land Use-Land Cover dynamics of Huluka watershed, Central Rift Valley, Ethiopia

    Directory of Open Access Journals (Sweden)

    Hagos Gebreslassie

    2014-12-01

    Full Text Available Land Use-Land Cover (LULC dynamic has of human kind age and is one of the phenomenons which interweave the socio economic and environmental issues in Ethiopia. Huluka watershed is one of the watersheds in Central Rift Valley of Ethiopia which drains to Lake Langano. Few decades ago the stated watershed was covered with dense acacia forest. But, nowadays like other part of Ethiopia, it is experiencing complex dynamics of LULC. The aim of this research was thus to evaluate the LULC dynamics seen in between 1973–2009. This was achieved through collecting qualitative and quantitative data using Geographic Information System (GIS and Remote Sensing (RS technique. Field observations, discussion with elders were also employed to validate results from remotely sensed data. Based on the result, eight major dynamic LULC classes were identified from the watershed. Of these LULC classes, only cultivated and open lands had shown continuous and progressive expansion mainly at the expense of grass, shrub and forest lands. The 25% and 0% of cultivated and open land of the watershed in 1973 expanded to 84% and 4% in 2009 respectively while the 29%, 18% and 22% of grass, shrub and forest land of the watershed in 1973 degraded to 3.5%, 4% and 1.5% in 2009 respectively. As a result, land units which had been used for pastoralist before 1973 were identified under mixed agricultural system after 2000. In the end, this study came with a recommendation of an intervention of concerned body to stop the rapid degradation of vegetation on the watershed.

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

    Science.gov (United States)

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

    2017-04-01

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

  10. 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...

  11. Mozambique - National Land Administration Interventions

    Data.gov (United States)

    Millennium Challenge Corporation — The objective of this study is to establish a baseline for the impact evaluation of the institutional strengthening of the land administration system in Mozambique,...

  12. 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.

  13. Geospatial Analysis of Land Use and Land Cover Changes for Discharge at Way Kualagaruntang Watershed in Bandar Lampung

    OpenAIRE

    Yuniarti, Fieni; K, Dyah Indriana; Winarno, Dwi Joko

    2013-01-01

    Land use and land cover change in a watershed might drive some impacts, such as high amounts of discharge fluctuations. Way Kuala Garuntang Watersheed is one of watershed in Bandar Lampung that has changed significantly. This study analyzed land use and land cover change to determine how much its influence on discharce fluctuations based on Geographics Information System. The method used in this study comprised of hidrology, spatial and sensitivity analysis. Hidrology analysis based on daily ...

  14. NOAA's Coastal Change Analysis Program (C-CAP) 1985 to 2010 Regional Land Cover Change Data - Coastal United States (NODC Accession 0121254)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products...

  15. 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.

  16. An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

    Science.gov (United States)

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

    2015-12-01

    Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

  17. 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.

  18. Land use/land cover and scale influences on in-stream nitrogen uptake kinetics

    Science.gov (United States)

    Covino, Tim; McGlynn, Brian; McNamara, Rebecca

    2012-06-01

    Land use/land cover change often leads to increased nutrient loading to streams; however, its influence on stream ecosystem nutrient transport remains poorly understood. Given the deleterious impacts elevated nutrient loading can have on aquatic ecosystems, it is imperative to improve understanding of nutrient retention capacities across stream scales and watershed development gradients. We performed 17 nutrient addition experiments on six streams across the West Fork Gallatin Watershed, Montana, USA, to quantify nitrogen uptake kinetics and retention dynamics across stream sizes (first to fourth order) and along a watershed development gradient. We observed that stream nitrogen (N) uptake kinetics and spiraling parameters varied across streams of different development intensity and scale. In more developed watersheds we observed a fertilization affect. This fertilization affect was evident as increased ash-free dry mass, chlorophylla, and ambient and maximum uptake rates in developed as compared to undeveloped streams. Ash-free dry mass, chlorophylla, and the number of structures in a subwatershed were significantly correlated to nutrient spiraling and kinetic parameters, while ambient and average annual N concentrations were not. Additionally, increased maximum uptake capacities in developed streams contributed to low in-stream nutrient concentrations during the growing season, and helped maintain watershed export at low levels during base flow. Our results indicate that land use/land cover change can enhance in-stream uptake of limiting nutrients and highlight the need for improved understanding of the watershed dynamics that control nutrient export across scales and development intensities for mitigation and protection of aquatic ecosystems.

  19. 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.

  20. 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.

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Science.gov (United States)

    Crum, S.; Jenerette, D.

    2015-12-01

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

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

    Science.gov (United States)

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

    2014-12-01

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

  4. Reducing uncertainty in dust monitoring to detect aeolian sediment transport responses to land cover change

    Science.gov (United States)

    Webb, N.; Chappell, A.; Van Zee, J.; Toledo, D.; Duniway, M.; Billings, B.; Tedela, N.

    2017-12-01

    Anthropogenic land use and land cover change (LULCC) influence global rates of wind erosion and dust emission, yet our understanding of the magnitude of the responses remains poor. Field measurements and monitoring provide essential data to resolve aeolian sediment transport patterns and assess the impacts of human land use and management intensity. Data collected in the field are also required for dust model calibration and testing, as models have become the primary tool for assessing LULCC-dust cycle interactions. However, there is considerable uncertainty in estimates of dust emission due to the spatial variability of sediment transport. Field sampling designs are currently rudimentary and considerable opportunities are available to reduce the uncertainty. Establishing the minimum detectable change is critical for measuring spatial and temporal patterns of sediment transport, detecting potential impacts of LULCC and land management, and for quantifying the uncertainty of dust model estimates. Here, we evaluate the effectiveness of common sampling designs (e.g., simple random sampling, systematic sampling) used to measure and monitor aeolian sediment transport rates. Using data from the US National Wind Erosion Research Network across diverse rangeland and cropland cover types, we demonstrate how only large changes in sediment mass flux (of the order 200% to 800%) can be detected when small sample sizes are used, crude sampling designs are implemented, or when the spatial variation is large. We then show how statistical rigour and the straightforward application of a sampling design can reduce the uncertainty and detect change in sediment transport over time and between land use and land cover types.

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

    Science.gov (United States)

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

    2016-12-01

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

  6. 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

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

    Science.gov (United States)

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

    2014-02-01

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

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

    International Nuclear Information System (INIS)

    Wong, S N; Sarker, M L R

    2014-01-01

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

  9. Land Use/Cover Changes between 1966 and 1996 in Chirokella ...

    African Journals Online (AJOL)

    Abstract: Keywords: Land Cover; Dynamic; Expansion; Exposed Land; ReductionTwo periods of panchromatic aerial photographs taken in 1966 and 1996 were analyzed to determine spatial and temporal land cover changes occurring in Chirokella micro-watershed, Southeastern Ethiopia. Theresults of the analysis were ...

  10. Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty

    Science.gov (United States)

    Jan Seibert; Jeffrey J. McDonnell

    2010-01-01

    The effect of land-use or land-cover change on stream runoff dynamics is not fully understood. In many parts of the world, forest management is the major land-cover change agent. While the paired catchment approach has been the primary methodology used to quantify such effects, it is only possible for small headwater catchments where there is uniformity in...

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

    NARCIS (Netherlands)

    van Asselen, S.; Verburg, P.H.

    2013-01-01

    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

  12. 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...

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

    Science.gov (United States)

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

  14. 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.

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

    Science.gov (United States)

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

    2017-10-20

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

  16. Impacts of land cover data selection and trait parameterisation on dynamic modelling of species' range expansion.

    Directory of Open Access Journals (Sweden)

    Risto K Heikkinen

    Full Text Available Dynamic models for range expansion provide a promising tool for assessing species' capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina and one generalist (Issoria lathonia. Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity, with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning.

  17. National Level Assessment of Mangrove Forest Cover in Pakistan

    Science.gov (United States)

    Abbas, S.; Qamer, F. M.; Hussain, N.; Saleem, R.; Nitin, K. T.

    2011-09-01

    . GIS and Remote Sensing based technologies and methods are in use to map forest cover since the last two decades in Pakistan. The national level forest cover studies based upon satellite images include, Forestry Sector Master Plan (FSMP) and National Forest & Range Resources Assessment Study (NFRRAS). In FSMP, the mangrove forest extent was visually determined from Landsat images of 1988 - 1991, and was estimated to be 155,369 ha; whereas, in NFRRAS, Landsat images of 1997 - 2001 were automated processed and the mangroves areas was estimated to be 158,000 ha. To our knowledge, a comprehensive assessment of current mangroves cover of Pakistan has not been made over the last decade, although the mangroves ecosystems have become the focus of intention in context of recent climate change scenarios. This study was conducted to support the informed decision making for sustainable development in coastal areas of Pakistan by providing up-todate mangroves forest cover assessment of Pakistan. Various types of Earth Observation satellite images and processing methods have been tested in relation to mangroves mapping. Most of the studies have applied classical pixel - based approached, there are a few studies which used object - based methods of image analysis to map the mangroves ecosystems. Object - based methods have the advantage of incorporating spatial neighbourhood properties and hierarchical structures into the classification process to produce more accurate surface patterns recognition compared with classical pixel - based approaches. In this research, we applied multi-scale hierarchical approach of object-based methods of image analysis to ALOS - AVNIR-2 images of the year 2008-09 to map the land cover in the mangroves ecosystems of Pakistan. Considering the tide height and phonological effects of vegetation, particularly the algal mats, these data sets were meticulously chosen. Incorporation of multi-scale hierarchical structures made it easy to effectively discriminate

  18. Recent land cover and use changes in Miombo woodlands of ...

    African Journals Online (AJOL)

    Forest and wood land ecosystems in Tanzania occupy more than 45% of the land area, more than two thirds of which made up of the Miombo woodland. The main form of land use in the Miombo region has long been shifting and small-scale sedentary cultivation. The lack of infrastructure and prevalence of deadly diseases ...

  19. Anthropogenical Drivers on Land Use/Cover Change and their ...

    African Journals Online (AJOL)

    The study recommended to the government to facilitate participatory land use planning at village level, agro-forestry, provision of extensions services, and modern family planning services to check overpopulation for sustainable land use and improvement of rural livelihoods in and beyond the study area. Keywords: Land ...

  20. LAND COVER CHANGE MONITORING OF TYPICAL FUNCTIONAL COMMUNITIES OF SICHUAN PROVINCE BASED ON ZY-3 DATA

    Directory of Open Access Journals (Sweden)

    G. M. Li

    2018-04-01

    Full Text Available According to the function, land space types are divided into key development areas, restricted development areas and forbidden development areas in Sichuan Province. This paper monitors and analyses the changes of land cover in different typical functional areas from 2010 to 2017, which based on ZY-3 high-score images data and combined with statistical yearbook and thematic data of Sichuan Province. The results show that: The land cover types of typical key development zones are mainly composed of cultivated land, forest land, garden land, and housing construction land, which accounts for the total area of land cover 87 %. The land cover types of typical restricted development zone mainly consists of forest land and grassland, which occupy 97.71 % of the total area of the surface coverage. The land cover types of the typical prohibition development zone mainly consist of forest land, grassland, desert and bared earth, which accounts for the total area of land cover 99.31 %.

  1. Land use and land cover change in the Western Cape Province: quantification of changes & understanding of driving factors

    CSIR Research Space (South Africa)

    Tizora, P

    2016-07-01

    Full Text Available changes in land use and land cover (LULC) and incited issues such as urban sprawl, marginalization of the poor, limited public access to resources, land degradation and climate change. This paper seeks to understand the most significant drivers of LULC...

  2. Effect of landslides on the structural characteristics of land-cover based on complex networks

    Science.gov (United States)

    He, Jing; Tang, Chuan; Liu, Gang; Li, Weile

    2017-09-01

    Landslides have been widely studied by geologists. However, previous studies mainly focused on the formation of landslides and never considered the effect of landslides on the structural characteristics of land-cover. Here we define the modeling of the graph topology for the land-cover, using the satellite images of the earth’s surface before and after the earthquake. We find that the land-cover network satisfies the power-law distribution, whether the land-cover contains landslides or not. However, landslides may change some parameters or measures of the structural characteristics of land-cover. The results show that the linear coefficient, modularity and area distribution are all changed after the occurence of landslides, which means the structural characteristics of the land-cover are changed.

  3. Coastal Change Analysis Program (C-CAP) Great Lakes; Michigan 1996-2001 era land cover change analysis (NODC Accession 0042189)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is a change analysis of 1996-era C-CAP land cover and 2001-era C-CAP land cover for the State of Michigan, in the Great Lakes Region of the U.S. This...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. MODELING OF FUTURE LAND COVER LAND USE CHANGE IN NORTH CAROLINA USING MARKOV CHAIN AND CELLULAR AUTOMATA MODEL

    OpenAIRE

    Mohammad Sayemuzzaman; Manoj K. Jha

    2014-01-01

    State wide variant topographic features in North Carolina attract the hydro-climatologist. There is none modeling study found that predict future Land Cover Land Use (LCLU) change for whole North Carolina. In this study, satellite-derived land cover maps of year 1992, 2001 and 2006 of North Carolina were integrated within the framework of the Markov-Cellular Automata (Markov-CA) model which combines the Markov chain and Cellular Automata (CA) techniques. A Multi-Criteria Evaluation (MCE) was ...

  9. Urban slum structure: integrating socioeconomic and land cover data to model slum evolution in Salvador, Brazil.

    Science.gov (United States)

    Hacker, Kathryn P; Seto, Karen C; Costa, Federico; Corburn, Jason; Reis, Mitermayer G; Ko, Albert I; Diuk-Wasser, Maria A

    2013-10-20

    The expansion of urban slums is a key challenge for public and social policy in the 21st century. The heterogeneous and dynamic nature of slum communities limits the use of rigid slum definitions. A systematic and flexible approach to characterize, delineate and model urban slum structure at an operational resolution is essential to plan, deploy, and monitor interventions at the local and national level. We modeled the multi-dimensional structure of urban slums in the city of Salvador, a city of 3 million inhabitants in Brazil, by integrating census-derived socioeconomic variables and remotely-sensed land cover variables. We assessed the correlation between the two sets of variables using canonical correlation analysis, identified land cover proxies for the socioeconomic variables, and produced an integrated map of deprivation in Salvador at 30 m × 30 m resolution. The canonical analysis identified three significant ordination axes that described the structure of Salvador census tracts according to land cover and socioeconomic features. The first canonical axis captured a gradient from crowded, low-income communities with corrugated roof housing to higher-income communities. The second canonical axis discriminated among socioeconomic variables characterizing the most marginalized census tracts, those without access to sanitation or piped water. The third canonical axis accounted for the least amount of variation, but discriminated between high-income areas with white-painted or tiled roofs from lower-income areas. Our approach captures the socioeconomic and land cover heterogeneity within and between slum settlements and identifies the most marginalized communities in a large, complex urban setting. These findings indicate that changes in the canonical scores for slum areas can be used to track their evolution and to monitor the impact of development programs such as slum upgrading.

  10. Land Cover Change in the Andes of Southern Ecuador—Patterns and Drivers

    Directory of Open Access Journals (Sweden)

    Giulia F. Curatola Fernández

    2015-03-01

    Full Text Available In the megadiverse tropical mountain forest in the Andes of southern Ecuador, a global biodiversity hotspot, the use of fire to clear land for cattle ranching is leading to the invasion of an aggressive weed, the bracken fern, which is threatening diversity and the provisioning of ecosystem services. To find sustainable land use options adapted to the local situation, a profound knowledge of the long-term spatiotemporal patterns of land cover change and its drivers is necessary, but hitherto lacking. The complex topography and the high cloud frequency make the use of remote sensing in this area a challenge. To deal with these conditions, we pursued specific pre-processing steps before classifying five Landsat scenes from 1975 to 2001. Then, we quantified land cover changes and habitat fragmentation, and we investigated landscape changes in relation to key spatial elements (altitude, slope, and distance from roads. Good classification results were obtained with overall accuracies ranging from 94.5% to 98.5% and Kappa statistics between 0.75 and 0.98. Forest was strongly fragmented due to the rapid expansion of the arable frontier and the even more rapid invasion by bracken. Unexpectedly, more bracken-infested areas were converted to pastures than vice versa, a practice that could alleviate pressure on forests if promoted. Road proximity was the most important spatial element determining forest loss, while for bracken the altitudinal range conditioned the degree of invasion in deforested areas. The annual deforestation rate changed notably between periods: ~1.5% from 1975 to 1987, ~0.8% from 1987 to 2000, and finally a very high rate of ~7.5% between 2000 and 2001. We explained these inconstant rates through some specific interrelated local and national political and socioeconomic drivers, namely land use policies, credit and tenure incentives, demography, and in particular, a severe national economic and bank crisis.

  11. Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

    Science.gov (United States)

    Ganguly, S.; Kumar, U.; Nemani, R. R.; Kalia, S.; Michaelis, A.

    2017-12-01

    In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS - national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91% was achieved, which is a 6% improvement in unmixing based classification relative to per-pixel based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

  12. Estimating ground water recharge from topography, hydrogeology, and land cover.

    Science.gov (United States)

    Cherkauer, Douglas S; Ansari, Sajjad A

    2005-01-01

    Proper management of ground water resources requires knowledge of the rates and spatial distribution of recharge to aquifers. This information is needed at scales ranging from that of individual communities to regional. This paper presents a methodology to calculate recharge from readily available ground surface information without long-term monitoring. The method is viewed as providing a reasonable, but conservative, first approximation of recharge, which can then be fine-tuned with other methods as time permits. Stream baseflow was measured as a surrogate for recharge in small watersheds in southeastern Wisconsin. It is equated to recharge (R) and then normalized to observed annual precipitation (P). Regression analysis was constrained by requiring that the independent and dependent variables be dimensionally consistent. It shows that R/P is controlled by three dimensionless ratios: (1) infiltrating to overland water flux, (2) vertical to lateral distance water must travel, and (3) percentage of land cover in the natural state. The individual watershed properties that comprise these ratios are now commonly available in GIS data bases. The empirical relationship for predicting R/P developed for the study watersheds is shown to be statistically viable and is then tested outside the study area and against other methods of calculating recharge. The method produces values that agree with baseflow separation from streamflow hydrographs (to within 15% to 20%), ground water budget analysis (4%), well hydrograph analysis (12%), and a distributed-parameter watershed model calibrated to total streamflow (18%). It has also reproduced the temporal variation over 5 yr observed at a well site with an average error < 12%.

  13. Changes in Carbon Emissions in Colombian Savannas Derived From Recent Land use and Land Cover Change

    Science.gov (United States)

    Etter, A.; Sarmiento, A.

    2007-12-01

    ,500 Ha among the different savanna ecosystem types. Highest frequencies and largest burned areas occur in the less accessible well-drained savannas of the southern part of the region. The analysis also reveals a close relationship between land tenure and fire regimes, with highest frequencies in Indigenous Reserves, followed by private land ranches and National Parks, indicating that most fires are human induced. By 2000 more than 500k hectares of natural savannas were transformed to sown pastures (Brachiaria spp.), and some 100k hectares were planted with oil palm and irrigated rice. Such changes have taken place in more accessible areas and slightly better soils. In areas subject to land use change and intensification a significant reduction in fire frequency can be observed. Because such land use changes have been occurring in savanna types with better soils and higher aerial biomass values, the average effect on reduction of C-emissions is some 30 to 50% larger than the effect on fire area reduction. Our results indicate a reduction of fire frequencies greater than 80% in areas where savannas were replaced by introduced Brachiaria pastures. However the reduction in C emissions from fire reduction in these pastures is exceeded by the parallel emissions from the increase in the cattle stocking rates with a net effect of an additional emission of 0.5 Gt.CO2 equivalents. We make preliminary projections of future emission trends based on the land use change model, and we discuss the likely effects of future sources and sinks of C expected from the increase of irrigated rice crops and from projected oil palm and timber plantations.

  14. EVALUATION OF LAND USE/LAND COVER DATASETS FOR URBAN WATERSHED MODELING

    International Nuclear Information System (INIS)

    S.J. BURIAN; M.J. BROWN; T.N. MCPHERSON

    2001-01-01

    Land use/land cover (LULC) data are a vital component for nonpoint source pollution modeling. Most watershed hydrology and pollutant loading models use, in some capacity, LULC information to generate runoff and pollutant loading estimates. Simple equation methods predict runoff and pollutant loads using runoff coefficients or pollutant export coefficients that are often correlated to LULC type. Complex models use input variables and parameters to represent watershed characteristics and pollutant buildup and washoff rates as a function of LULC type. Whether using simple or complex models an accurate LULC dataset with an appropriate spatial resolution and level of detail is paramount for reliable predictions. The study presented in this paper compared and evaluated several LULC dataset sources for application in urban environmental modeling. The commonly used USGS LULC datasets have coarser spatial resolution and lower levels of classification than other LULC datasets. In addition, the USGS datasets do not accurately represent the land use in areas that have undergone significant land use change during the past two decades. We performed a watershed modeling analysis of three urban catchments in Los Angeles, California, USA to investigate the relative difference in average annual runoff volumes and total suspended solids (TSS) loads when using the USGS LULC dataset versus using a more detailed and current LULC dataset. When the two LULC datasets were aggregated to the same land use categories, the relative differences in predicted average annual runoff volumes and TSS loads from the three catchments were 8 to 14% and 13 to 40%, respectively. The relative differences did not have a predictable relationship with catchment size

  15. International Conference on Land Use / Cover Change Dynamics

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Organized by: Beijing Normal University, National Natural Science Foundation of China Hosted by: Institute of Resources Science, Beijing Normal University Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education of China Topics: 1) Detecting and monitoring LUCC 2) Temporal-spatial characteristics in LUCC 3) Driving model for LUCC 4) Forecasting and modeling LUCC 5) Phenological and biochemical response on LUCC 6) Regional LUCC and microclimate 7) LUCC in the context of global change 8) Impact of global change on the sustainable land-use modeling Abstract submission: The official language of this conference is English. We invite papers written in English and an abstract of less than one page of standard A4 size to the Conference Secretariat by Apr 15, 2001. Registration Fee: 280 US$ (300 US$ after July 15, 2001) Add:No. 19, Xinjiekouwai Street, 100875, Institute of Resources Science, Beijing Normal University, Beijing, China Tel:86-10-62207656 or 62209024 Fax:010-62208178 http:// 202.112.93.50/LUCCD2001/index.html E-mail: Pwang@bnu.edu.cn Cyh@bnu.edu.cn

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

  18. Forests as landscapes of social inequality: tropical forest cover and land distribution among shifting cultivators

    Directory of Open Access Journals (Sweden)

    Oliver T. Coomes

    2016-09-01

    Full Text Available Can social inequality be seen imprinted in a forest landscape? We studied the relationship between land holding, land use, and inequality in a peasant community in the Peruvian Amazon where farmers practice swidden-fallow cultivation. Longitudinal data on land holding, land use, and land cover were gathered through field-level surveys (n = 316 and household interviews (n = 51 in 1994/1995 and 2007. Forest cover change between 1965 and 2007 was documented through interpretation of air photos and satellite imagery. We introduce the concept of "land use inequality" to capture differences across households in the distribution of forest fallowing and orchard raising as key land uses that affect household welfare and the sustainability of swidden-fallow agriculture. We find that land holding, land use, and forest cover distribution are correlated and that the forest today reflects social inequality a decade prior. Although initially land-poor households may catch up in terms of land holdings, their use and land cover remain impoverished. Differential land use investment through time links social inequality and forest cover. Implications are discussed for the study of forests as landscapes of inequality, the relationship between social inequality and forest composition, and the forest-poverty nexus.

  19. A Continental United States High Resolution NLCD Land Cover – MODIS Albedo Database to Examine Albedo and Land Cover Change Relationships

    Science.gov (United States)

    Surface albedo influences climate by affecting the amount of solar radiation that is reflected at the Earth’s surface, and surface albedo is, in turn, affected by land cover. General Circulation Models typically use modeled or prescribed albedo to assess the influence of land co...

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

    Science.gov (United States)

    Wen, Yuming; Khosrowpanah, Shahram; Heitz, Leroy

    2011-08-01

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

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

    Science.gov (United States)

    Lu, Dengsheng; Li, Guiying; Moran, Emilio; Hetrick, Scott

    2013-01-01

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

  2. Agricultural land cover changes in metropolitan areas of Poland for the period 1990–2012

    Directory of Open Access Journals (Sweden)

    Nalej Marta

    2016-06-01

    Full Text Available Agricultural land covers more than half the area of metropolitan areas in Poland, and is therefore particularly prone to the influences of the processes associated with their development. The aim of the study was to analyse changes in agricultural land cover within the metropolitan areas of Poland for the years 1990–2012; and to capture their dynamics, types and directions. The percentage share of the total study area, for each of the forms of agricultural land cover and their changes were traced, with the spatial distribution of the changes also being determined. The results of the study show that in metropolitan areas, agricultural land cover is undergoing transformations that do not result in the loss of agricultural lands, or that involve a decrease in surface area due to their change into anthropogenic forms of land cover. The greatest transitions occurred between 2000 and 2006 and were observed in the outer zones of metropolitan areas.

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

    Science.gov (United States)

    Fox, J. M.; Hurni, K.

    2017-12-01

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

  4. Impact of Land Use Land Cover Change on East Asian monsoon

    Science.gov (United States)

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

    2017-12-01

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

  5. Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

    Science.gov (United States)

    Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

    2010-01-01

    Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

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

    2014-04-01

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

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

    Science.gov (United States)

    Kumar, Lalit; Ghosh, Manoj Kumer

    2012-01-01

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

  9. Implementación de la metodología Corine Land Cover con imágenes Ikonos The Corine Land Cover method based on Ikonos images

    Directory of Open Access Journals (Sweden)

    Germán Mauricio Valencia Hernández

    2009-07-01

    Full Text Available En Colombia, desde hace algunos años, se viene trabajando en la construcción de cartografía temática de usos del suelo escala 1:100.000, utilizando la metodología desarrollada en Europa y denominada Corine Land Cover (CLC. Esto se ha logrado con el apoyo del Instituto Forestal Nacional de Francia (ONF a varios organismos nacionales, como el Instituto Geográfico Agustín Codazzi (IGAC, la Corporación Autónoma Regional Cormagdalena y el Instituto de Estudios Ambientales (IDEAM. El objetivo de la investigación fue determinar los cambios en el uso del suelo entre 1992 y 2005 para una región de los Andes colombianos, además identificar las potencialidades y limitaciones de la metodología CLC en el ámbito colombiano. Para ello se ajustó la leyenda a las condiciones de Colombia, se mejoró la unidad mínima de mapeo a 0.5 ha, y se utilizaron como fuentes de información escenas Ikonos Geo no ortorrectificadas. Con la metodología aplicada en esta investigación, se encontró entre los años 1992 y 2005, una disminución del área total en fragmentos boscosos, una disminución del área total en pastos, y un aumento en cultivos. Esta metodología puede ser utilizada en tareas de actualización de coberturas del suelo que requieran un alto nivel de detalle, sin embargo, se recomienda disminuir los errores geométricos con imágenes ortorrectificadas al trabajar en zonas de alta pendiente como es el caso de los Andes colombianos.During the last few years, the European Corine Land Cover method has been used in Colombia in order to update land use maps. Four institutes have been involved in this process: The National Forest Institute of France (ONF, El Instituto Geográfico Agustin Codazzi (IGAC, La Corporación Autonoma Regional Cormagdalena, and El instituto de Estudios Ambientales (IDEAM. The goal of this paper was to determine Land use-land cover change based on the CLC method. The study ranges between 1992 and 2005 along a transect of the

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

    Science.gov (United States)

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

    2006-10-01

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

  11. Land use and land cover dynamics on the campus of Federal University of Lavras from 1964 to 2009

    Directory of Open Access Journals (Sweden)

    Elizabeth Ferreira

    2013-03-01

    Full Text Available This study identified, quantified and analyzed changes in land use and cover on the campus of Federal University of Lavras campus, located in Lavras city (Minas Gerais State. The 2009 QuickBird satellite imagery and 1985, 1979, 1971, 1964 vertical aerial photographs were used to produce a set of land use and land cover maps. The work started with the orthorectification of the QuickBird satellite imagery and vertical aerial photographs. The identification and definition of land cover and land use classes were obtained from field surveys in 2009. First, the land cover and land use maps were made from that information. Finally, the quantification and analysis of changes were performed at the imagery time range. The results showed that in 2009 the "urbanized area class" of the campus reached 65.79 ha and that the most significant increase of this class occurred between the years 1964 (6.24 ha and 1971 (24.4 ha. The smallest area of "forest land class" found on the campus was 38.38 ha in 1971, and from 1979 on this situation has been improved reaching 113.18 ha of "forest land class" in 2009. For the "water class" there was not any dam constructed yet in the campus before 1971. Most of the campus area, previously used for "agricultural land class" had a significant reduction within this category, from 384.19 ha in 1964 to 271.16 ha in 2009.

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

    African Journals Online (AJOL)

    Oceanographic Research Institute, PO Box 10712, Marine Parade, 4056 Durban, ... and continues to undergo rapid development due to a number of causes, ... coastal vulnerability, with the impact of .... land, agriculture and mining land, disturbed ..... attributable to the construction of Richards ... iSimangaliso wetland park.

  13. Analysis of spatial distribution of land cover maps accuracy

    Science.gov (United States)

    Khatami, R.; Mountrakis, G.; Stehman, S. V.

    2017-12-01

    Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain

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

    Science.gov (United States)

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

    2015-04-01

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

  15. Erosion of earth covers used in shallow land burial at Los Alamos, New Mexico

    International Nuclear Information System (INIS)

    Nyhan, J.W.; Depoorter, G.L.; Drennon, B.J.; Simanton, J.R.; Foster, G.R.

    1984-01-01

    The Los Alamos National Laboratory and the USDA-ARS examined soil erosion and water balance relationships for a trench cap used for the shallow land burial of low-level radioactive waters at Los Alamos, NM. Eight 3.05 by 10.7 m plots were installed with bare soil, tilled, and vegetated surface treatments on a 15 by 63 m trench cap constructed from soil and crushed tuff layers. A rotating boom rain simulator was used to estimate the soil erodibility and cover-management factors of the Universal Soil Loss Equation (USLE) for this trench cap and for two undisturbed plots with natural vegetative cover. The implications of the results of this study are discussed relative to the management of infiltration and erosion processes at waste burial sites and compared with similar USDA research performed throughout the USA

  16. Mapping land cover in urban residential landscapes using fine resolution imagery and object-oriented classification

    Science.gov (United States)

    A knowledge of different types of land cover in urban residential landscapes is important for building social and economic city-wide policies including landscape ordinances and water conservation programs. Urban landscapes are typically heterogeneous, so classification of land cover in these areas ...

  17. Assessing the land cover situation in Surkhang, Upper Mustang, Nepal, using an ASTER image

    NARCIS (Netherlands)

    Sharma, B.D.; Clevers, J.G.P.W.; Graaf, de N.R.; Chapagain, N.R.

    2003-01-01

    This paper describes the remote sensing technique used to prepare a land cover map of Surkhang, Upper Mustang Nepal. The latest ASTER image (October 2002) and an ASTER DEM were used for the land cover classification. The study was carried out in Surkhang Village Development Committee (area 799 km2)

  18. The effects of changing land cover on streamflow simulation in Puerto Rico

    Science.gov (United States)

    Van Beusekom, Ashley; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad

    2014-01-01

    This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

  19. Corine land cover change detection in Europe (case studies of the Netherlands and Slovakia)

    NARCIS (Netherlands)

    Feranec, J.; Hazeu, G.W.; Christensen, S.; Jaffrain, G.

    2007-01-01

    We present a land cover change detection methodology in the framework of the IMAGE and CORINE Land Cover 2000 (I&CLC2000) project managed jointly by the European Environment Agency in Copenhagen, Denmark and the Joint Research Centre of the European Commission in Ispra, Italy. The generated data

  20. The effects of changing land cover on streamflow simulation in Puerto Rico

    Science.gov (United States)

    A.E. Van Beusekom; L.E. Hay; R.J. Viger; W.A. Gould; J.A. Collazo; A. Henareh Khalyani

    2014-01-01

    This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from...

  1. Assessing the Accuracy of MODIS-NDVI Derived Land-Cover Across the Great Lakes Basin

    Science.gov (United States)

    This research describes the accuracy assessment process for a land-cover dataset developed for the Great Lakes Basin (GLB). This land-cover dataset was developed from the 2007 MODIS Normalized Difference Vegetation Index (NDVI) 16-day composite (MOD13Q) 250 m time-series data. Tr...

  2. Comparison and assessment of coarse resolution land cover maps for Northern Eurasia

    Science.gov (United States)

    Dirk Pflugmacher; Olga N. Krankina; Warren B. Cohen; Mark A. Friedl; Damien Sulla-Menashe; Robert E. Kennedy; Peder Nelson; Tatiana V. Loboda; Tobias Kuemmerle; Egor Dyukarev; Vladimir Elsadov; Viacheslav I. Kharuk

    2011-01-01

    Information on land cover at global and continental scales is critical for addressing a range of ecological, socioeconomic and policy questions. Global land cover maps have evolved rapidly in the last decade, but efforts to evaluate map uncertainties have been limited, especially in remote areas like Northern Eurasia. Northern Eurasia comprises a particularly diverse...

  3. Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter

    CSIR Research Space (South Africa)

    Salmon, BP

    2012-07-01

    Full Text Available - fective way to monitor and evaluate land cover changes. An operator making an image-to-image comparison is still a com- mon method in most organizations when mapping land cover change, which is time consuming and resource intensive. Au- tomated change...

  4. A procedure to obtain a refined European land use/cover map

    NARCIS (Netherlands)

    Batista e Silva, F.; Lavalle, C.; Koomen, E.

    2013-01-01

    Available land use/cover maps differ in their spatial extent and in their thematic, spatial, and temporal resolutions. Due to the costs of producing such maps, there is usually a trade-off between spatial extent and resolution. The only European-wide, consistent, and multi-temporal land use/cover

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

    Science.gov (United States)

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

    1996-01-01

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

  6. Research on Land Surface Thermal-Hydrologic Exchange in Southern China under Future Climate and Land Cover Scenarios

    Directory of Open Access Journals (Sweden)

    Jianwu Yan

    2013-01-01

    Full Text Available Climate change inevitably leads to changes in hydrothermal circulation. However, thermal-hydrologic exchanging caused by land cover change has also undergone ineligible changes. Therefore, studying the comprehensive effects of climate and land cover changes on land surface water and heat exchanges enables us to well understand the formation mechanism of regional climate and predict climate change with fewer uncertainties. This study investigated the land surface thermal-hydrologic exchange across southern China for the next 40 years using a land surface model (ecosystem-atmosphere simulation scheme (EASS. Our findings are summarized as follows. (i Spatiotemporal variation patterns of sensible heat flux (H and evapotranspiration (ET under the land cover scenarios (A2a or B2a and climate change scenario (A1B are unanimous. (ii Both H and ET take on a single peak pattern, and the peak occurs in June or July. (iii Based on the regional interannual variability analysis, H displays a downward trend (10% and ET presents an increasing trend (15%. (iv The annual average H and ET would, respectively, increase and decrease by about 10% when woodland converts to the cultivated land. Through this study, we recognize that land surface water and heat exchanges are affected greatly by the future climate change as well as land cover change.

  7. Using remote sensing imagery and GIS to identify land cover and land use within Ceahlau Massif (Romania

    Directory of Open Access Journals (Sweden)

    GEORGE CRACU

    2014-11-01

    Full Text Available Using remote sensing imagery and GIS to identify land cover and land use within Ceahlău Massif (Romania. In this study we considerer land cover and land use asessment within Ceahlău Massif (Romania using satellite imagery and GIS . To achieve this goal, we used a Landsat 7 ETM + satellite image, which was processed using specialized software in analyzing satellite images and GIS software in several stages:  Downloading, importing and layer stack of all spectral bands composing satellite image;  Establishment of areas of interest for each category of land cover and land use, which were digitized on - screen and for which spectral signatures characteristics were established;  Supervised image classification using Maximum Likelihood Method;  Importing the resulting m ap (raster in GIS environment and creating the final land cover/land use map for Ceahlău Massif. In the study area we identified nine land cover/land use classes: deciduous forests, mixed forests, coniferous forests, secondary grasslands, subalpine vegeta tion, alpine meadows, agricultural land, lakes and built area. By analizing the spatial distribution of these classes, it was found that forests are the best represented class, occupying an area of 188.4 km² (56.4% of total, followed by secondary grassl and, which occupies an area of 68.2 km² (20.4% of total, lakes (26.6 km² or 7.98% of total and agricultural land (16.1 km² or 4.86%

  8. Nitrogen Discharge due to Climate Change and Land Cover Change

    Data.gov (United States)

    U.S. Environmental Protection Agency — Simulated model output for the figures in the associated publication. Data are SWAT model simulation results for different scenarios of land-use change and climate...

  9. Percent Agricultural Land Cover on Steep Slopes (Future)

    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....

  10. Coastal Change Analysis Program (C-CAP) zone 55/58 1996-2001 era land cover change analysis (NODC Accession 0038689)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains the 1996-2001 era or land cover change classifications of the SE Atlantic, zone 55 and zone 58. This imagery was collected as part of the...

  11. IRSeL-An approach to enhance continuity and accuracy of remotely sensed land cover data

    Science.gov (United States)

    Rathjens, H.; Dörnhöfer, K.; Oppelt, N.

    2014-09-01

    Land cover data gives the opportunity to study interactions between land cover status and environmental issues such as hydrologic processes, soil properties, or biodiversity. Land cover data often are based on classification of remote sensing data that seldom provides the requisite accuracy, spatial availability and temporal observational frequency for environmental studies. Thus, there is a high demand for accurate and spatio-temporal complete time series of land cover. In the past considerable research was undertaken to increase land cover classification accuracy, while less effort was spent on interpolation techniques. The purpose of this article is to present a space-time interpolation and revision approach for remotely sensed land cover data. The approach leverages special properties known for agricultural areas such as crop rotations or temporally static land cover classes. The newly developed IRSeL-tool (Interpolation and improvement of Remotely Sensed Land cover) corrects classification errors and interpolates missing land cover pixels. The easy-to-use tool solely requires an initial land cover data set. The IRSeL specific interpolation and revision technique, the data input requirements and data output structure are described in detail. A case study in an area around the city of Neumünster in Northern Germany from 2006 to 2012 was performed for IRSeL validation with initial land cover data sets (Landsat TM image classifications) for the years 2006, 2007, 2009, 2010 and 2011. The results of the case study showed that IRSeL performs well; including years with no classification data overall accuracy values for IRSeL interpolated pixels range from 0.63 to 0.81. IRSeL application significantly increases the accuracy of the land cover data; overall accuracy values rise 0.08 in average resulting in overall accuracy values of at least 0.86. Considering estimated reliabilities, the IRSeL tool provides a temporally and spatially completed and revised land cover

  12. National Satellite Land Remote Sensing Data Archive

    Science.gov (United States)

    Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

    2013-01-01

    The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

  13. 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.

  14. Use of AMSR-E microwave satellite data for land surface characteristics and snow cover variation

    Directory of Open Access Journals (Sweden)

    Mukesh Singh Boori

    2016-12-01

    Full Text Available This data article contains data related to the research article entitled “Global land cover classification based on microwave polarization and gradient ratio (MPGR” [1] and “Microwave polarization and gradient ratio (MPGR for global land surface phenology” [2]. This data article presents land surface characteristics and snow cover variation information from sensors like EOS Advanced Microwave Scanning Radiometer (AMSR-E. This data article use the HDF Explorer, Matlab, and ArcGIS software to process the pixel latitude, longitude, snow water equivalent (SWE, digital elevation model (DEM and Brightness Temperature (BT information from AMSR-E satellite data to provide land surface characteristics and snow cover variation data in all-weather condition at any time. This data information is useful to discriminate different land surface cover types and snow cover variation, which is turn, will help to improve monitoring of weather, climate and natural disasters.

  15. Determination of Land Use/ Land Cover Changes in Igneada Alluvial (Longos) Forest Ecosystem, Turkey

    Science.gov (United States)

    Bektas Balcik, F.

    2012-12-01

    Alluvial (Longos) forests are one of the most fragile and threatened ecosystems in the world. Typically, these types of ecosystems have high biological diversity, high productivity, and high habitat dynamism. In this study, Igneada, Kirklareli was selected as study area. The region, lies between latitudes 41° 46' N and 41° 59' N and stretches between longitudes 27° 50' E and 28° 02' E and it covers approximately 24000 (ha). Igneada Longos ecosystems include mixed forests, streams, flooded (alluvial) forests, marshes, wetlands, lakes and coastal sand dunes with different types of flora and fauna. Igneada was classified by Conservation International as one of the world's top 122 Important Plant Areas, and 185 Important Bird Areas. These types of wild forest in other parts of Turkey and in Europe have been damaged due to anthropogenic effects. Remote sensing is very effective tool to monitor these types of sensitive regions for sustainable management. In this study, 1984 and 2011 dated Landsat 5 TM data were used to determine land cover/land use change detection of the selected region by using six vegetation indices such as Tasseled Cap index of greenness (TCG), brightness (TCB), and wetness (TCW), ratios of near-infrared to red image (RVI), normalized difference vegetation index (NDVI), and soil-adjusted vegetation index (SAVI). Geometric and radiometric corrections were applied in image pre-processing step. Selective Principle Component Analysis (PCA) change detection method was applied to the selected vegetation index imagery to generate change imagery for extracting the changed features between the year of 1984 and 2011. Accuracy assessment was applied based on error matrix by calculating overall accuracy and Kappa statistics.

  16. Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

    Science.gov (United States)

    Quattrochi, Dale A.; Jedlovec, Gary; Meyer, Paul

    2011-01-01

    City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will

  17. Las Cruces, 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. Santa Fe, 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)...

  19. Silver City, 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)...

  20. El Paso, TX 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. Silver City, 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. Saint Johns, 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)...

  3. Fort Sumner, 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)...

  4. Las Cruces, 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)...

  5. El Paso, TX 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. Santa Fe, 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)...

  7. Saint Johns, 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)...

  8. Fort Sumner, 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)...

  9. Investigating the feasibility of geo-Tagged photographs as sources of land cover input data

    OpenAIRE

    Antoniou, Vyron; Fonte, Cidália Costa; See, Linda; Estima, Jacinto; Arsanjani, Jamal Jokar; Lupia, Flavio; Minghini, Marco; Foody, Giles; Fritz, Steffen

    2016-01-01

    Geo-Tagged photographs are used increasingly as a source of Volunteered Geographic Information (VGI), which could potentially be used for land use and land cover applications. The purpose of this paper is to analyze the feasibility of using this source of spatial information for three use cases related to land cover: Calibration, validation and verification. We first provide an inventory of the metadata that are collected with geo-Tagged photographs and then consider what elements would be es...

  10. Exploring Land Use and Land Cover of Geotagged Social-Sensing Images Using Naive Bayes Classifier

    Directory of Open Access Journals (Sweden)

    Asamaporn Sitthi

    2016-09-01

    Full Text Available Online social media crowdsourced photos contain a vast amount of visual information about the physical properties and characteristics of the earth’s surface. Flickr is an important online social media platform for users seeking this information. Each day, users generate crowdsourced geotagged digital imagery containing an immense amount of information. In this paper, geotagged Flickr images are used for automatic extraction of low-level land use/land cover (LULC features. The proposed method uses a naive Bayes classifier with color, shape, and color index descriptors. The classified images are mapped using a majority filtering approach. The classifier performance in overall accuracy, kappa coefficient, precision, recall, and f-measure was 87.94%, 82.89%, 88.20%, 87.90%, and 88%, respectively. Labeled-crowdsourced images were filtered into a spatial tile of a 30 m × 30 m resolution using the majority voting method to reduce geolocation uncertainty from the crowdsourced data. These tile datasets were used as training and validation samples to classify Landsat TM5 images. The supervised maximum likelihood method was used for the LULC classification. The results show that the geotagged Flickr images can classify LULC types with reasonable accuracy and that the proposed approach improves LULC classification efficiency if a sufficient spatial distribution of crowdsourced data exists.

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

    Science.gov (United States)

    Vadrevu, Krishna; Ohara, Toshimasa; Justice, Chris

    2017-12-01

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

  12. Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods

    Directory of Open Access Journals (Sweden)

    Chao Yang

    2017-11-01

    Full Text Available Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of mixed pixels. This study aimed to integrate pixel unmixing and decision tree to improve LULC classification by removing mixed pixel influence. The abundance and minimum noise fraction (MNF results that were obtained from mixed pixel decomposition were added to decision tree multi-features using a three-dimensional (3D Terrain model, which was created using an image fusion digital elevation model (DEM, to select training samples (ROIs, and improve ROI separability. A Landsat-8 OLI image of the Yunlong Reservoir Basin in Kunming was used to test this proposed method. Study results showed that the Kappa coefficient and the overall accuracy of integrated pixel unmixing and decision tree method increased by 0.093% and 10%, respectively, as compared with the original decision tree method. This proposed method could effectively eliminate the influence of mixed pixels and improve the accuracy in complex LULC classifications.

  13. Hydrological impacts of global land cover change and human water use

    Directory of Open Access Journals (Sweden)

    J. H. C. Bosmans

    2017-11-01

    Full Text Available Human impacts on global terrestrial hydrology have been accelerating during the 20th century. These human impacts include the effects of reservoir building and human water use, as well as land cover change. To date, many global studies have focussed on human water use, but only a few focus on or include the impact of land cover change. Here we use PCR-GLOBWB, a combined global hydrological and water resources model, to assess the impacts of land cover change as well as human water use globally in different climatic zones. Our results show that land cover change has a strong effect on the global hydrological cycle, on the same order of magnitude as the effect of human water use (applying irrigation, abstracting water, for industrial use for example, including reservoirs, etc.. When globally averaged, changing the land cover from that of 1850 to that of 2000 increases discharge through reduced evapotranspiration. The effect of land cover change shows large spatial variability in magnitude and sign of change depending on, for example, the specific land cover change and climate zone. Overall, land cover effects on evapotranspiration are largest for the transition of tall natural vegetation to crops in energy-limited equatorial and warm temperate regions. In contrast, the inclusion of irrigation, water abstraction and reservoirs reduces global discharge through enhanced evaporation over irrigated areas and reservoirs as well as through water consumption. Hence, in some areas land cover change and water distribution both reduce discharge, while in other areas the effects may partly cancel out. The relative importance of both types of impacts varies spatially across climatic zones. From this study we conclude that land cover change needs to be considered when studying anthropogenic impacts on water resources.

  14. Inventory and change detection of urban land cover in Illinois using Landsat Thematic Mapper data

    International Nuclear Information System (INIS)

    Cook, E.A.; Iverson, L.R.

    1991-01-01

    In order to provide information about urban forests and other vegetative land cover in Illinois cities, Landsat TM data from June 17, 1988, were classified for the Chicago metropolitan region and five urban areas of central Illinois. Ten land cover classes were identified, including three types of forestland, cropland, two grassland categories, two urban classes, water, and miscellaneous vegetation. The cities inventoried have a significantly higher proportion of forests and forested residential areas than the surrounding rural areas because of preservation measures and accruement of tree cover from landscaping. Short-term change in land cover for the Chicago region was also assessed by postclassification comparison of the 1988 data with similarly derived data from a June 3, 1985, TM scene. The largest single category of change in the six-county area was cropland to urban land use. A majority of cover loss was conversion of forested tracts to residential areas, and forest cover increase was negligible. 16 refs

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

    Science.gov (United States)

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

    2007-03-01

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

  16. Global spatial assessment of WUI and related land cover in Portugal

    Science.gov (United States)

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

    2017-04-01

    Forest fires as hazardous events are assuming an increasing importance all around the world, especially in relation to climate changes and to urban sprawl, which makes it difficult to outline a border between human infrastructures and wildland areas. This zone, known as the Wildland Urban Interface (WUI), is defined as the area where structures and other human development meet or intermingle with undeveloped wildland (USDA 2001). Its extension is influenced by anthropogenic features, since, as it was proved, the distance to roads and houses negatively influence the probability of forest fires ignitions, while the population density positively affects it. Land use is also a crucial feature to be considered in the analyses of the impact of forest fires, and each natural, semi-natural and artificial land cover can be affected in a different proportion. The aim of the present study is to investigate and mapping the wildland urban interface and its temporal dynamic in Portugal at global scale. Secondly, it aims at providing a quantitative characterization of forest fires occurred in the last few decades (1990 - 2012) in relation to the burned area and the land covers evolution. The National mapping burnt area dataset (by the Institute for the Conservation of Nature and Forests) provided the information allowing to precisely localize forest fires. The land cover classes were derived from the Corinne Land Cover, available for four periods (1990-2000-2006-2012). The following two classes were retained to outline the WUI: 1) artificial surfaces, as representative of the human development; 2) forest and semi-natural area, as representative of undeveloped wildland. First, we investigated the distribution of the burned areas among the different detailed land covers classes. Then, to map the WUI, we considered a buffer distance around artificial surfaces located in proximity of forests and semi-natural areas. The descriptive statistic carried out individually within each

  17. Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations

    Science.gov (United States)

    Wei Li; Philippe Ciais; Shushi Peng; Chao Yue; Yilong Wang; Martin Thurner; Sassan S. Saatchi; Almut Arneth; Valerio Avitabile; Nuno Carvalhais; Anna B. Harper; Etsushi Kato; Charles Koven; Yi Y. Liu; Julia E. M. S. Nabel; Yude Pan; Julia Pongratz; Benjamin Poulter; Thomas A. M. Pugh; Maurizio Santoro; Stephen Sitch; Benjamin D. Stocker; Nicolas Viovy; Andy Wiltshire; Rasoul Yousefpour; Sönke Zaehle

    2017-01-01

    The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we...

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

    NARCIS (Netherlands)

    Saran, S.; Sterk, G.; Kumar, S.

    2009-01-01

    Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division

  19. 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 Understanding the impact of land use/land cover (LULC) and climate patterns on basin runoff is necessary in assessing basin water stress. This assessment requires long-term observed rainfall time series and LULC spatial data. In order to assess...

  20. Shiprock, AZ NM CO UT 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. A spatial econometric analysis of land-use change with land cover trends data: an application to the Pacific Northwest

    Science.gov (United States)

    David J. Lewis; Ralph J. Alig

    2014-01-01

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

  2. Constraining the Deforestation History of Europe: Evaluation of Historical Land Use Scenarios with Pollen-Based Land Cover Reconstructions

    Directory of Open Access Journals (Sweden)

    Jed O. Kaplan

    2017-12-01

    Full Text Available Anthropogenic land cover change (ALCC is the most important transformation of the Earth system that occurred in the preindustrial Holocene, with implications for carbon, water and sediment cycles, biodiversity and the provision of ecosystem services and regional and global climate. For example, anthropogenic deforestation in preindustrial Eurasia may have led to feedbacks to the climate system: both biogeophysical, regionally amplifying winter cold and summer warm temperatures, and biogeochemical, stabilizing atmospheric CO 2 concentrations and thus influencing global climate. Quantification of these effects is difficult, however, because scenarios of anthropogenic land cover change over the Holocene vary widely, with increasing disagreement back in time. Because land cover change had such widespread ramifications for the Earth system, it is essential to assess current ALCC scenarios in light of observations and provide guidance on which models are most realistic. Here, we perform a systematic evaluation of two widely-used ALCC scenarios (KK10 and HYDE3.1 in northern and part of central Europe using an independent, pollen-based reconstruction of Holocene land cover (REVEALS. Considering that ALCC in Europe primarily resulted in deforestation, we compare modeled land use with the cover of non-forest vegetation inferred from the pollen data. Though neither land cover change scenario matches the pollen-based reconstructions precisely, KK10 correlates well with REVEALS at the country scale, while HYDE systematically underestimates land use with increasing magnitude with time in the past. Discrepancies between modeled and reconstructed land use are caused by a number of factors, including assumptions of per-capita land use and socio-cultural factors that cannot be predicted on the basis of the characteristics of the physical environment, including dietary preferences, long-distance trade, the location of urban areas and social organization.

  3. Mapping land cover gradients through analysis of hyper-temporal NDVI imagery

    NARCIS (Netherlands)

    Ali, A.; de Bie, C.A.J.M.; Skidmore, A.K.; Scarrott, R.G.; Hamad, A.A.; Venus, V.; Lymberakis, P.

    2013-01-01

    The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but

  4. Investigating the Feasibility of Geo-Tagged Photographs as Sources of Land Cover Input Data

    Directory of Open Access Journals (Sweden)

    Vyron Antoniou

    2016-05-01

    Full Text Available Geo-tagged photographs are used increasingly as a source of Volunteered Geographic Information (VGI, which could potentially be used for land use and land cover applications. The purpose of this paper is to analyze the feasibility of using this source of spatial information for three use cases related to land cover: Calibration, validation and verification. We first provide an inventory of the metadata that are collected with geo-tagged photographs and then consider what elements would be essential, desirable, or unnecessary for the aforementioned use cases. Geo-tagged photographs were then extracted from Flickr, Panoramio and Geograph for an area of London, UK, and classified based on their usefulness for land cover mapping including an analysis of the accompanying metadata. Finally, we discuss protocols for geo-tagged photographs for use of VGI in relation to land cover applications.

  5. Simulation of Land-Cover Change in Taipei Metropolitan Area under Climate Change Impact

    International Nuclear Information System (INIS)

    Huang, Kuo-Ching; Huang, Thomas C C

    2014-01-01

    Climate change causes environment change and shows up on land covers. Through observing the change of land use, researchers can find out the trend and potential mechanism of the land cover change. Effective adaptation policies can affect pattern of land cover change and may decrease the risks of climate change impacts. By simulating land use dynamics with scenario settings, this paper attempts to explore the relationship between climate change and land-cover change through efficient adaptation polices. It involves spatial statistical model in estimating possibility of land-cover change, cellular automata model in modeling land-cover dynamics, and scenario analysis in response to adaptation polices. The results show that, without any control, the critical eco-areas, such as estuarine areas, will be destroyed and people may move to the vulnerable and important economic development areas. In the other hand, under the limited development condition for adaptation, people migration to peri-urban and critical eco-areas may be deterred

  6. A large-area, spatially continuous assessment of land cover map error and its impact on downstream analyses.

    Science.gov (United States)

    Estes, Lyndon; Chen, Peng; Debats, Stephanie; Evans, Tom; Ferreira, Stefanus; Kuemmerle, Tobias; Ragazzo, Gabrielle; Sheffield, Justin; Wolf, Adam; Wood, Eric; Caylor, Kelly

    2018-01-01

    Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high-resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel-wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative "downstream" (map-based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps' spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ∼45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National-scale maps derived from higher-resolution imagery were most accurate, followed by multi-map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland-adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%-500% greater than in input cropland maps, but ∼40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land

  7. Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey.

    Science.gov (United States)

    Reis, Selçuk

    2008-10-01

    Mapping land use/land cover (LULC) changes at regional scales is essential for a wide range of applications, including landslide, erosion, land planning, global warming etc. LULC alterations (based especially on human activities), negatively effect the patterns of climate, the patterns of natural hazard and socio-economic dynamics in global and local scale. In this study, LULC changes are investigated by using of Remote Sensing and Geographic Information Systems (GIS) in Rize, North-East Turkey. For this purpose, firstly supervised classification technique is applied to Landsat images acquired in 1976 and 2000. Image Classification of six reflective bands of two Landsat images is carried out by using maximum likelihood method with the aid of ground truth data obtained from aerial images dated 1973 and 2002. The second part focused on land use land cover changes by using change detection comparison (pixel by pixel). In third part of the study, the land cover changes are analyzed according to the topographic structure (slope and altitude) by using GIS functions. The results indicate that severe land cover changes have occurred in agricultural (36.2%) (especially in tea gardens), urban (117%), pasture (-72.8%) and forestry (-12.8%) areas has been experienced in the region between 1976 and 2000. It was seen that the LULC changes were mostly occurred in coastal areas and in areas having low slope values.

  8. Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey

    Directory of Open Access Journals (Sweden)

    Selçuk Reis

    2008-10-01

    Full Text Available Mapping land use/land cover (LULC changes at regional scales is essential for a wide range of applications, including landslide, erosion, land planning, global warming etc. LULC alterations (based especially on human activities, negatively effect the patterns of climate, the patterns of natural hazard and socio-economic dynamics in global and local scale. In this study, LULC changes are investigated by using of Remote Sensing and Geographic Information Systems (GIS in Rize, North-East Turkey. For this purpose, firstly supervised classification technique is applied to Landsat images acquired in 1976 and 2000. Image Classification of six reflective bands of two Landsat images is carried out by using maximum likelihood method with the aid of ground truth data obtained from aerial images dated 1973 and 2002. The second part focused on land use land cover changes by using change detection comparison (pixel by pixel. In third part of the study, the land cover changes are analyzed according to the topographic structure (slope and altitude by using GIS functions. The results indicate that severe land cover changes have occurred in agricultural (36.2% (especially in tea gardens, urban (117%, pasture (-72.8% and forestry (-12.8% areas has been experienced in the region between 1976 and 2000. It was seen that the LULC changes were mostly occurred in coastal areas and in areas having low slope values.

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

    Science.gov (United States)

    Sarmento, Pedro Alexandre Reis

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

  10. National Satellite Land Remote Sensing Data Archive

    Science.gov (United States)

    Faundeen, John L.; Longhenry, Ryan

    2018-06-13

    The National Satellite Land Remote Sensing Data Archive is managed on behalf of the Secretary of the Interior by the U.S. Geological Survey’s Earth Resources Observation and Science Center. The Land Remote Sensing Policy Act of 1992 (51 U.S.C. §601) directed the U.S. Department of the Interior to establish a permanent global archive consisting of imagery over land areas obtained from satellites orbiting the Earth. The law also directed the U.S. Department of the Interior, delegated to the U.S. Geological Survey, to ensure proper storage and preservation of imagery, and timely access for all parties. Since 2008, these images have been available at no cost to the user.

  11. 'COVER STORY': A STUDY IN lAND MANAGEMENT

    African Journals Online (AJOL)

    The group was concerned with soil ero- sion and the associated effect upon the vegetation cover. The first s~ge of the project was to est- ablish exactly which aspects of soil erosion should be studied. The following points were initially considered: soil types and characteristics different grasses and their carrying capacity.

  12. Detection of land cover changes around Lake Mutirikwi, Zimbabwe ...

    African Journals Online (AJOL)

    Landsat images from 1984, 1995, 2001 and 2011 were used to compute a normalised difference vegetation index (NDVI), which was then used as a proxy for indicating areas infested by surface floating aquatic weeds. Forest and shrubs covered 310.8 km2 in 1984, but had deteriorated by 24.87% to 77.3 km2 in 2011, while ...

  13. Assessment of Land-Use/Land-Cover Change and Forest Fragmentation in the Garhwal Himalayan Region of India

    Directory of Open Access Journals (Sweden)

    Amit Kumar Batar

    2017-04-01

    Full Text Available The Garhwal Himalaya has experienced extensive deforestation and forest fragmentation, but data and documentation detailing this transformation of the Himalaya are limited. The aim of this study is to analyse the observed changes in land cover and forest fragmentation that occurred between 1976 and 2014 in the Garhwal Himalayan region in India. Three images from Landsat 2 Multispectral Scanner System (MSS, Landsat 5 Thematic Mapper (TM, and Landsat 8 Operational Land Imager (OLI were used to extract the land cover maps. A cross-tabulation detection method in the geographic information system (GIS module was used to detect land cover changes during the 1st period (1976–1998 and 2nd period (1998–2014. The landscape fragmentation tool LFT v2.0 was used to construct a forest fragmentation map and analyse the forest fragmentation pattern and change during the 1st period (1976–1998 and 2nd period (1998–2014. The overall annual rate of change in the forest cover was observed to be 0.22% and 0.27% in the 1st period (1976–1998 and 2nd period (1998–2014, respectively. The forest fragmentation analysis shows that a large core forest has decreased throughout the study period. The total area of forest patches also increased from 1976 to 2014, which are completely degraded forests. The results indicate that anthropogenic activities are the main causes of the loss of forest cover and forest fragmentation, but that natural factors also contributed. An increase in the area of scrub and barren land also contributed to the accumulation of wasteland or non-forest land in this region. Determining the trend and the rate of land cover conversion is necessary for development planners to establish a rational land use policy.

  14. Using IKONOS and Aerial Videography to Validate Landsat Land Cover Maps of Central African Tropical Rain Forests

    Science.gov (United States)

    Lin, T.; Laporte, N. T.

    2003-12-01

    Compared to the traditional validation methods, aerial videography is a relatively inexpensive and time-efficient approach to collect "field" data for validating satellite-derived land cover map over large areas. In particular, this approach is valuable in remote and inaccessible locations. In the Sangha Tri-National Park region of Central Africa, where road access is limited to industrial logging sites, we are using IKONOS imagery and aerial videography to assess the accuracy of Landsat-derived land cover maps. As part of a NASA Land Cover Land Use Change project (INFORMS) and in collaboration with the Wildlife Conservation Society in the Republic of Congo, over 1500km of aerial video transects were collected in the Spring of 2001. The use of MediaMapper software combined with a VMS 200 video mapping system enabled the collection of aerial transects to be registered with geographic locations from a Geographic Positioning System. Video frame were extracted, visually interpreted, and compared to land cover types mapped by Landsat. We addressed the limitations of accuracy assessment using aerial-base data and its potential for improving vegetation mapping in tropical rain forests. The results of the videography and IKONOS image analysis demonstrate the utility of very high resolution imagery for map validation and forest resource assessment.

  15. Land-cover mapping using multitemporal, dual-frequency polarimetric SAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Schou, Jesper; Dierking, Wolfgang

    2000-01-01

    during the growing season acquired a lot of data over a Danish agricultural site. The data acquisitions were co-ordinated with ground surveys to obtain a detailed land cover map. The test area contains a large number of different land cover classes, such as more than 10 different crop types, deciduous......The Danish Center for Remote Sensing (DCRS) is, in collaboration with the Danish mapping agency, conducting a study on topographic mapping using SAR data, and land cover mapping results are presented. The Danish EMISAR system (an L- and C-band, fully polarimetric, airborne SAR) have in 1994 to 1999...

  16. Land cover mapping and GIS processing for the Savannah River Site Database

    International Nuclear Information System (INIS)

    Christel, L.M.; Guber, A.L.

    1994-07-01

    The Savannah River Site (SRS) is owned by the U.S. Department of Energy and operated by Westinghouse Savannah River Company. Located in Barnwell, Aiken, and Allendale counties in South Carolina, SRS covers an area of approximately 77,700 hectares. Land cover information for SRS was interpreted from color and color infrared aerial photography acquired between 1980 and 1989. The data were then used as the source of the land cover data layer for the SRS sitewide Geographic Information System database. This database provides SRS managers with recent land use information and has been successfully used to support cost-effective site characterization and reclamation

  17. Remote sensing as a source of land cover information utilized in the universal soil loss equation

    Science.gov (United States)

    Morris-Jones, D. R.; Morgan, K. M.; Kiefer, R. W.; Scarpace, F. L.

    1979-01-01

    In this study, methods for gathering the land use/land cover information required by the USLE were investigated with medium altitude, multi-date color and color infrared 70-mm positive transparencies using human and computer-based interpretation techniques. Successful results, which compare favorably with traditional field study methods, were obtained within the test site watershed with airphoto data sources and human airphoto interpretation techniques. Computer-based interpretation techniques were not capable of identifying soil conservation practices but were successful to varying degrees in gathering other types of desired land use/land cover information.

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

    Science.gov (United States)

    Kontgis, Caitlin

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

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

    Science.gov (United States)

    Chilukoti, N.; Xue, Y.

    2016-12-01

    The land surface play a vital role in determining the surface energy budget, accurate representation of land use and land cover (LULC) is necessary to improve forecast. In this study, we have investigated the influence of surface vegetation maps with different LULC on simulating the boreal summer monsoon rainfall. Using a National Centres for Environmental Prediction (NCEP) Coupled Forecast System version 2(CFSv2) model coupled with Simplified Simple Biosphere (SSiB) model, two experiments were conducted: one with old vegetation map and one with new vegetation map. The significant differences between new and old vegetation map were in semi-arid and arid areas. For example, in old map Tibetan plateau classified as desert, which is not appropriate, while in new map it was classified as grasslands or shrubs with bare soil. Old map classified the Sahara desert as a bare soil and shrubs with bare soil, whereas in new map it was classified as bare ground. In addition to central Asia and the Sahara desert, in new vegetation map, Europe had more cropped area and India's vegetation cover was changed from crops and forests to wooded grassland and small areas of grassland and shrubs. The simulated surface air temperature with new map shows a significant improvement over Asia, South Africa, and northern America by some 1 to 2ºC and 2 to 3ºC over north east China and these are consistent with the reduced rainfall biases over Africa, near Somali coast, north east India, Bangladesh, east China sea, eastern Pacific and northern USA. Over Indian continent and bay of Bengal dry rainfall anomalies that is the only area showing large dry rainfall bias, however, they were unchanged with new map simulation. Overall the CFSv2(coupled with SSiB) model with new vegetation map show a promising result in improving the monsoon forecast by improving the Land -Atmosphere interactions. To compare with the LULC forcing, experiment was conducted using the Global Forecast System (GFS) simulations

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

    Science.gov (United States)

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

    2009-01-01

    The Mobile Bay region has experienced noteworthy land use and land cover (LULC) change in the latter half of the 20th century. Accompanying this change has been urban expansion and a reduction of rural land uses. Much of this LULC change has reportedly occurred since the landfall of Hurricane Frederic in 1979. The Mobile Bay region provides great economic and ecologic benefits to the Nation, including important coastal habitat for a broad diversity of fisheries and wildlife. Regional urbanization threatens the estuary s water quality and aquatic-habitat dependent biota, including commercial fisheries and avian wildlife. Coastal conservation and urban land use planners require additional information on historical LULC change to support coastal habitat restoration and resiliency management efforts. This presentation discusses results of a Gulf of Mexico Application Pilot project that was conducted in 2008 to quantify and assess LULC change from 1974 to 2008. This project was led by NASA Stennis Space Center and involved multiple Gulf of Mexico Alliance (GOMA) partners, including the Mobile Bay National Estuary Program (NEP), the U.S. Army Corps of Engineers, the National Oceanic and Atmospheric Administration s (NOAA s) National Coastal Data Development Center (NCDDC), and the NOAA Coastal Services Center. Nine Landsat images were employed to compute LULC products because of their availability and suitability for the application. The project also used Landsat-based national LULC products, including coastal LULC products from NOAA s Coastal Change & Analysis Program (C-CAP), available at 5-year intervals since 1995. Our study was initiated in part because C-CAP LULC products were not available to assess the region s urbanization prior to 1995 and subsequent to post Hurricane Katrina in 2006. This project assessed LULC change across the 34-year time frame and at decadal and middecadal scales. The study area included the majority of Mobile and Baldwin counties that

  1. Characterizing Degradation Gradients through Land Cover Change Analysis in Rural Eastern Cape, South Africa

    Directory of Open Access Journals (Sweden)

    Zahn Münch

    2017-02-01

    Full Text Available Land cover change analysis was performed for three catchments in the rural Eastern Cape, South Africa, for two time steps (2000 and 2014, to characterize landscape conversion trajectories for sustained landscape health. Land cover maps were derived: (1 from existing data (2000; and (2 through object-based image analysis (2014 of Landsat 8 imagery. Land cover change analysis was facilitated using land cover labels developed to identify landscape change trajectories. Land cover labels assigned to each intersection of the land cover maps at the two time steps provide a thematic representation of the spatial distribution of change. While land use patterns are characterized by high persistence (77%, the expansion of urban areas and agriculture has occurred predominantly at the expense of grassland. The persistence and intensification of natural or invaded wooded areas were identified as a degradation gradient within the landscape, which amounted to almost 10% of the study area. The challenge remains to determine significant signals in the landscape that are not artefacts of error in the underlying input data or scale of analysis. Systematic change analysis and accurate uncertainty reporting can potentially address these issues to produce authentic output for further modelling.

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

    Science.gov (United States)

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

    2016-04-01

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

  3. CORINE Land Cover 2000 (IandCLC2000)

    International Nuclear Information System (INIS)

    Novacek, J.

    2005-01-01

    Remote Sensing for the Earth is one of the method for obtaining of information about objects of the Earth surface. Satellite snapshots were basic source of information for this project. Slovak Environmental Agency was the coordinator of this project to the Slovak Republic and co-research organisation was Geographic Institute, Slovak Academy of Sciences. Interpretation of satellite snapshots enabled to obtain information about position and area of natural ranges of 44 classes of landscape cover of Europe, from which in the Slovakia occurs 31 classes. Resulting thematic layers of landscape cover of the Slovakia during the years 1990 and 2000 are significant for analysis of trends, reasons and implications of nature and social processes which proceeds in the time and place of given territory

  4. Land use/land cover in Swisher County and Deaf Smith County locations, Palo Duro Basin, Texas

    International Nuclear Information System (INIS)

    1984-12-01

    Agriculture is the major land use/land cover in the Swisher and Deaf Smith County locations. Most of the agricultural land is irrigated. Furrow, center pivot, and lateral-wheel irrigation systems are in common use. Rangeland is the second most abundant land use/land cover; it is typically associated with stream valleys and playas. The rangeland supports cattle, which are an important source of income. The main urban areas in or near the locations are Tulia and Happy, in Swisher County, and Hereford and Vega, in Deaf Smith County. Most of the land within the locations is privately owned - corporate and government ownership is extremely limited - and large portions are currently under lease for oil exploration. County and regional agencies have no authority to regulate land-use patterns in the locations, although the Panhandle Regional Planning Commission can provide guidance to local jurisdictions. Land use within the corporate limits and extraterritorial jurisdictions of Tulia and Hereford is controlled by zoning ordinances and subdivision regulations. According to projections for the locations, agriculture will remain the major land use in the foreseeable future. Dryland farming and rangeland will become more prevalent as irrigation costs increase and marginal areas are taken out of production

  5. The Analysis of Land Use Based on CORINE Land Cover in the Romanian Part of the Tisa Catchment Area

    Directory of Open Access Journals (Sweden)

    CIPRIAN MOLDOVAN

    2010-01-01

    Full Text Available The analysis of the land use structure of the 13 counties of the Romanian part of Tisa catchment area has been made according to the 2000 edition of CORINE Land Cover, while the 1990 edition has been used for comparative purposes. Out of the total area of 8,269,229.48 hectares, the forests cover 37.92%, the arable lands 35.02% and the grasslands 17.97%. The other types of land use have lower weights, such as the continuous and discontinuous urban fabric 4.81%, the orchards 1.10% and the vineyards 0.98%. In the category of forests, the following types of land use are included: broad-leaved forests, which form the majority (24.72%, coniferous forests (6.22%, mixed forests (3.46% and transitional woodland-shrub areas (3.52%. The forests are mainly located in the Carpathians and the hills. The non-irrigated arable lands (23.50% are predominant within the arable lands. They lie mostly in the Western Plain and in the basins and corridors of the Transylvanian Depression and the Western Hills. The analysis of the dynamics of the land use structure between 1990 and 2000 indicates a relative stability in the case of forests, a decrease of arable lands and an increase of grasslands.

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

    Science.gov (United States)

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

    2008-10-01

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

  7. Feasibility Study of Land Cover Classification Based on Normalized Difference Vegetation Index for Landslide Risk Assessment

    Directory of Open Access Journals (Sweden)

    Thilanki Dahigamuwa

    2016-10-01

    Full Text Available Unfavorable land cover leads to excessive damage from landslides and other natural hazards, whereas the presence of vegetation is expected to mitigate rainfall-induced landslide potential. Hence, unexpected and rapid changes in land cover due to deforestation would be detrimental in landslide-prone areas. Also, vegetation cover is subject to phenological variations and therefore, timely classification of land cover is an essential step in effective evaluation of landslide hazard potential. The work presented here investigates methods that can be used for land cover classification based on the Normalized Difference Vegetation Index (NDVI, derived from up-to-date satellite images, and the feasibility of application in landslide risk prediction. A major benefit of this method would be the eventual ability to employ NDVI as a stand-alone parameter for accurate assessment of the impact of land cover in landslide hazard evaluation. An added benefit would be the timely detection of undesirable practices such as deforestation using satellite imagery. A landslide-prone region in Oregon, USA is used as a model for the application of the classification method. Five selected classification techniques—k-nearest neighbor, Gaussian support vector machine (GSVM, artificial neural network, decision tree and quadratic discriminant analysis support the viability of the NDVI-based land cover classification. Finally, its application in landslide risk evaluation is demonstrated.

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

    Science.gov (United States)

    Zhang, Wen-Yan; Lin, Chao-Yuan

    2017-04-01

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

  9. Conservation Reserve Program effects on floodplain land cover management.

    Science.gov (United States)

    Jobe, Addison; Kalra, Ajay; Ibendahl, Elise

    2018-05-15

    Growing populations and industrialized agriculture practices have eradicated much of the United States wetlands along river floodplains. One program available for the restoration of floodplains is the Conservation Reserve Program (CRP). The current research explores the effects CRP land change has on flooding zones, utilizing Flood Modeller and HEC-RAS. Flood Modeller is proven a viable tool for flood modeling within the United States when compared to HEC-RAS. Application of the software is used in the Nodaway River system located in the western halves of Iowa and Missouri to model effects of introducing new forest areas within the region. Flood stage during the conversion first decreases in the early years, before rising to produce greater heights. Flow velocities where CRP land is present are reduced for long-term scopes. Velocity reduction occurs as the Manning's roughness increases due to tree diameter and brush density. Flood zones become more widespread with the implementation of CRP. Future model implementations are recommended to witness the effects of smaller flood recurrence intervals. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Simulation of the influence of historical land cover changes on the global climate

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Y. [Nanjing Univ. of Aeronautics and Astronautics (China). College of Civil Aviation; Chinese Academy of Sciences, Beijing (China). Key Lab. of Regional Climate-Environment for East Asia; Yan, X. [Chinese Academy of Sciences, Beijing (China). Key Lab. of Regional Climate-Environment for East Asia; Beijing Normal Univ. (China). State Key Lab. of Earth Surface Processes and Resource Ecology (ESPRE); Wang, Z. [British Antarctic Survey, Cambridge (United Kingdom)

    2013-09-01

    In order to estimate biogeophysical effects of historical land cover change on climate during last three centuries, a set of experiments with a climate system model of intermediate complexity (MPM-2) is performed. In response to historical deforestation, the model simulates a decrease in annual mean global temperature in the range of 0.07-0.14 C based on different grassland albedos. The effect of land cover changes is most pronounced in the middle northern latitudes with maximum cooling reaching approximately 0.6 C during northern summer. The cooling reaches 0.57 C during northern spring owing to the large effects of land surface albedo. These results suggest that land cover forcing is important for study on historical climate change and that more research is necessary in the assessment of land management options for climate change mitigation. (orig.)

  11. Land Use and Land Cover Change, Urban Heat Island Phenomenon, and Health Implications: A Remote Sensing Approach

    Science.gov (United States)

    Lo, C. P.; Quattrochi, Dale A.

    2003-01-01

    Land use and land cover maps of Atlanta Metropolitan Area in Georgia were produced from Landsat MSS and TM images for 1973,1979,1983,1987,1992, and 1997, spanning a period of 25 years. Dramatic changes in land use and land cover have occurred with loss of forest and cropland to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 119% between 1973 and 1997. These land use and land cover changes have drastically altered the land surface characteristics. An analysis of Landsat images revealed an increase in surface temperature and a decline in NDVI from 1973 to 1997. These changes have forced the development of a significant urban heat island effect and an increase in ground level ozone production to such an extent, that Atlanta has violated EPA's ozone level standard in recent years. The urban heat island initiated precipitation events that were identified between 1996 and 2000 tended to occur near high-density urban areas but outside the I-285 loop that traverses around the Central Business District, i.e. not in the inner city area, but some in close proximity to the highways. The health implications were investigated by comparing the spatial patterns of volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions, the two ingredients that form ozone by reacting with sunlight, with those of rates of cardiovascular and chronic lower respiratory diseases. A clear core-periphery pattern was revealed for both VOC and NOx emissions, but the spatial pattern was more random in the cases of rates of cardiovascular and chronic lower respiratory diseases. Clearly, factors other than ozone pollution were involved in explaining the rates of these diseases. Further research is therefore needed to understand the health geography and its relationship to land use and land cover change as well as urban heat island effect. This paper illustrates the usefulness of a remote sensing approach for this purpose.

  12. EnviroAtlas - Fresno, CA - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Fresno, CA EnviroAtlas Meter-Scale Urban Land Cover (MULC) Data were generated via supervised classification of combined aerial photography and LiDAR data. The...

  13. 2005 Kansas Land Cover Patterns, Level IV, State of Kansas (300m buffer)

    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...

  14. EnviroAtlas - Portland, OR - Meter-Scale Urban Land Cover (MULC) Data (2012)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EnviroAtlas Portland, OR Meter-Scale Urban Land Cover (MULC) dataset includes data for the Portland metropolitan area plus the city of Vancouver, Washington and...

  15. LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

    Science.gov (United States)

    Monitoring the locations and spatial distributions of land-cover changes and patterns is important for establishing links between policy decisions, regulatory actions and resulting landuse activities. The monitoring of change patterns across the landscape can also supply valuable...

  16. Towards automated statewide land cover mapping in Wisconsin using satellite remote sensing and GIS techniques

    International Nuclear Information System (INIS)

    Cosentino, B.L.; Lillesand, T.M.

    1991-01-01

    Attention is given to an initial research project being performed by the University of Wisconsin-Madison, Environmental Remote Sensing Center in conjunction with seven local, state, and federal agencies to implement automated statewide land cover mapping using satellite remote sensing and geographical information system (GIS) techniques. The basis, progress, and future research needs for this mapping program are presented. The research efforts are directed toward strategies that integrate satellite remote sensing and GIS techniques in the generation of land cover data for multiple users of land cover information. The project objectives are to investigate methodologies that integrate satellite data with other imagery and spatial data resident in emerging GISs in the state for particular program needs, and to develop techniques that can improve automated land cover mapping efficiency and accuracy. 10 refs

  17. EnviroAtlas - New York, NY - Meter-Scale Urban Land Cover (MULC) Data (2008)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The New York, NY EnviroAtlas Meter-scale Urban Land Cover (MULC) Data were generated by the University of Vermont Spatial Analysis Laboratory (SAL) under the...

  18. IMPACTS OF PATCH SIZE AND LAND COVER HETEROGENEITY ON THEMATIC IMAGE CLASSIFICATION ACCURACY

    Science.gov (United States)

    Landscape characteristics such as small patch size and land cover heterogeneity have been hypothesized to increase the likelihood of miss-classifying pixels during thematic image classification. However, there has been a lack of empirical evidence to support these hypotheses,...

  19. 2005 Kansas Land Cover Patterns, Level IV, Kansas River Watershed (1,000m buffer)

    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...

  20. Generation and Assessment of Urban Land Cover Maps Using High-Resolution Multispectral Aerial Images

    DEFF Research Database (Denmark)

    Höhle, Joachim; Höhle, Michael

    2013-01-01

    a unique method for the automatic generation of urban land cover maps. In the present paper, imagery of a new medium-format aerial camera and advanced geoprocessing software are applied to derive normalized digital surface models and vegetation maps. These two intermediate products then become input...... to a tree structured classifier, which automatically derives land cover maps in 2D or 3D. We investigate the thematic accuracy of the produced land cover map by a class-wise stratified design and provide a method for deriving necessary sample sizes. Corresponding survey adjusted accuracy measures...... and their associated confidence intervals are used to adequately reflect uncertainty in the assessment based on the chosen sample size. Proof of concept for the method is given for an urban area in Switzerland. Here, the produced land cover map with six classes (building, wall and carport, road and parking lot, hedge...