Science.gov

Sample records for accurate land cover

  1. Land Cover Characterization Program

    USGS Publications Warehouse

    U.S. Geological Survey

    1997-01-01

    (2) identify sources, develop procedures, and organize partners to deliver data and information to meet user requirements. The LCCP builds on the heritage and success of previous USGS land use and land cover programs and projects. It will be compatible with current concepts of government operations, the changing needs of the land use and land cover data users, and the technological tools with which the data are applied.

  2. Land Cover Trends Project

    USGS Publications Warehouse

    Acevedo, William

    2006-01-01

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

  3. Land use and land cover digital data

    USGS Publications Warehouse

    U.S. Geological Survey

    1994-01-01

    Computer tapes derived from land use and land cover (LULC) data and associated maps at scales of 1 :250,000 and 1: 100,000 are available from the U.S. Geological Survey. This data can be used alone or combined with a base map or other supplemental data for a variety of applications, using commercially available software. You can produce area summary statistics, select specific portions of a map to study or display single classifications, such as bodies of water. LULC and associated digital data offer convenient, accurate, flexible, and cost-effective access to users who are involved in environmental studies, land use planning, land management, or resource planning.

  4. Land Use and Land Cover Change

    SciTech Connect

    Brown, Daniel; Polsky, Colin; Bolstad, Paul V.; Brody, Samuel D.; Hulse, David; Kroh, Roger; Loveland, Thomas; Thomson, Allison M.

    2014-05-01

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

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

    USGS Publications Warehouse

    Fry, J.A.; Coan, M.J.; Homer, C.G.; Meyer, D.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.

  6. The National Land Cover Database

    USGS Publications Warehouse

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

    2012-01-01

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

  7. Land-cover change detection

    USGS Publications Warehouse

    Chen, Xuexia; Giri, Chandra; Vogelmann, James

    2012-01-01

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

  8. Changes in Land Use and Land Cover

    NASA Astrophysics Data System (ADS)

    Meyer, William B.; Turner, B. L., II

    1994-10-01

    This book deals with the relationship between land use and land cover: between human activities and the transformation of the Earth's surface. It describes the recent changes in the world's farmland, forests, grasslands and settlements, and the impacts of these changes on soil, water resources and the atmosphere. It explores what is known about the importance of various underlying human sources of land transformation: population growth, technological change, political-economic institutions, political structure, and attitudes and beliefs. Three working group reports outline important avenues for future research: the construction of a global land model, the division of the world into regional situations of land transformation, and a wiring diagram to structure the division of research among fields of study.

  9. Accurate Inventories Of Irrigated Land

    NASA Technical Reports Server (NTRS)

    Wall, S.; Thomas, R.; Brown, C.

    1992-01-01

    System for taking land-use inventories overcomes two problems in estimating extent of irrigated land: only small portion of large state surveyed in given year, and aerial photographs made on 1 day out of year do not provide adequate picture of areas growing more than one crop per year. Developed for state of California as guide to controlling, protecting, conserving, and distributing water within state. Adapted to any large area in which large amounts of irrigation water needed for agriculture. Combination of satellite images, aerial photography, and ground surveys yields data for computer analysis. Analyst also consults agricultural statistics, current farm reports, weather reports, and maps. These information sources aid in interpreting patterns, colors, textures, and shapes on Landsat-images.

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

    EPA Science Inventory

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

  11. The 1980 land cover for the Puget Sound region

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

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

    USGS Publications Warehouse

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

    2005-01-01

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

  13. Water dynamics under changing land cover

    NASA Astrophysics Data System (ADS)

    Vaze, J.; Zhang, Y. Q.; Zhang, L.

    2015-06-01

    Most of the forested headwater catchments are an important source of water supply in many parts of the world. A prime example is southeast Australia where forests supply major river systems and towns and cities with water. It is critical for an informed and adaptive water resource management to understand changes in streamflow caused by vegetation changes in these headwater forest catchments. Natural disturbances such as bushfires and anthropogenic activities like forestation, deforestation, or logging alter vegetation, evapotranspiration and soil water status, and may affect water supplies. Although catchment water yield is mainly controlled by climatic conditions, but it is also strongly influenced by land cover changes because of natural disturbances and anthropogenic activities. It is necessary to accurately estimate streamflow in water supply catchments subjected to dramatic land surface changes. This paper summarises the methods commonly used to investigate the impacts of land cover change on water resources, and provides some examples of impacts of afforestation/deforestation and bushfire on water resources in two southeast Australian catchments.

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

    NASA Astrophysics Data System (ADS)

    Giri, C.; Pengra, B.; Long, J.; Loveland, T. R.

    2013-12-01

    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).

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

    USGS Publications Warehouse

    Xian, G.; Homer, C.

    2009-01-01

    The U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001 is widely used as a baseline for national land cover and impervious conditions. To ensure timely and relevant data, it is important to update this base to a more recent time period. A prototype method was developed to update the land cover and impervious surface by individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season from both 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, impervious surface was estimated for areas of change by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain a variety of metropolitan areas. Results from the five study areas show that the vast majority of impervious surface changes associated with urban developments were accurately captured and updated. The approach optimizes mapping efficiency and can provide users a flexible method to generate updated impervious surface at national and regional scales. ?? 2009 IEEE.

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

    NASA Astrophysics Data System (ADS)

    De Brue, Hanne; Verstraeten, Gert; Broothaerts, Nils; Notebaert, Bastiaan

    2016-04-01

    Accurate and spatially explicit landscape reconstructions for distinct time periods in human history are essential for the quantification of the effect of anthropogenic land cover changes on, e.g., global biogeochemical cycles, ecology, and geomorphic processes, and to improve our understanding of interaction between humans and the environment in general. A long-term perspective covering Mid and Late Holocene land use changes is recommended in this context, as it provides a baseline to evaluate human impact in more recent periods. Previous efforts to assess the evolution and intensity of agricultural land cover in past centuries or millennia have predominantly focused on palynological records. An increasing number of quantitative techniques has been developed during the last two decades to transfer palynological data to land cover estimates. However, these techniques have to deal with equifinality issues and, furthermore, do not sufficiently allow to reconstruct spatial patterns of past land cover. On the other hand, several continental and global databases of historical anthropogenic land cover changes based on estimates of global population and the required agricultural land per capita have been developed in the past decennium. However, at such long temporal and spatial scales, reconstruction of past anthropogenic land cover intensities and spatial patterns necessarily involves many uncertainties and assumptions as well. Here, we present a novel approach that combines archaeological, palynological and geomorphological data for the Dijle catchment in the central Belgium Loess Belt in order to arrive at more realistic Holocene land cover histories. Multiple land cover scenarios (> 60.000) are constructed using probabilistic rules and used as input into a sediment delivery model (WaTEM/SEDEM). Model outcomes are confronted with a detailed geomorphic dataset on Holocene sediment fluxes and with REVEALS based estimates of vegetation cover using palynological data from

  17. Land cover trends dataset, 1973-2000

    USGS Publications Warehouse

    Soulard, Christopher E.; Acevedo, William; Auch, Roger F.; Sohl, Terry L.; Drummond, Mark A.; Sleeter, Benjamin M.; Sorenson, Daniel G.; Kambly, Steven; Wilson, Tamara S.; Taylor, Janis L.; Sayler, Kristi L.; Stier, Michael P.; Barnes, Christopher A.; Methven, Steven C.; Loveland, Thomas R.; Headley, Rachel; Brooks, Mark S.

    2014-01-01

    The U.S. Geological Survey Land Cover Trends Project is releasing a 1973–2000 time-series land-use/land-cover dataset for the conterminous United States. The dataset contains 5 dates of land-use/land-cover data for 2,688 sample blocks randomly selected within 84 ecological regions. The nominal dates of the land-use/land-cover maps are 1973, 1980, 1986, 1992, and 2000. The land-use/land-cover maps were classified manually from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery using a modified Anderson Level I classification scheme. The resulting land-use/land-cover data has a 60-meter resolution and the projection is set to Albers Equal-Area Conic, North American Datum of 1983. The files are labeled using a standard file naming convention that contains the number of the ecoregion, sample block, and Landsat year. The downloadable files are organized by ecoregion, and are available in the ERDAS IMAGINETM (.img) raster file format.

  18. LAND USE LAND COVER (LULC) - US GEOLOGICAL SURVEY

    EPA Science Inventory

    The National Mapping Program, a component of the U. S. Geological Survey (USGS), produces and distributes land use and land cover maps and digitized data for the conterminous U.S. and Hawaii. Land use refers to the human activities that are directly related to the land. The int...

  19. LANDSAT applications by the Adirondack Park Agency for land cover analyses and forest cover change

    NASA Technical Reports Server (NTRS)

    Banta, J. S.; Curran, R. P.

    1981-01-01

    The New York State Adirondack Park Agency is using LANDSAT imagery to provide current, consistent parkwide data on forest cover, forest change and other land cover characteristics for the Adirondack Park, an area of 9,375 sq. miles (24,280 sq km). Boundaries of the study area were digitized and the data were enhanced and geographically rectified. A classification scheme was devised which emphasized the basic land cover types of the Park: hardwoods, spruce-fir, pine, wet conifer, brushland, grassland, agricultural areas, exposed earth, urban areas, and water bodies. Cover type classifications for disturbed forest land were also chosen: cut hardwoods, regenerating hardwoods, and cut spruce fir. Field verification of 1978 classification revealed an accurate differentiation of forest types within types and between nonforested/forested areas. The classification accurately detects forest land disturbances; however, it is not always descriptive of the level of disturbance.

  20. Alaska interim land cover mapping program

    USGS Publications Warehouse

    U.S. Geological Survey

    1987-01-01

    In order to meet the requirements of the Alaska National Interest Lands Conservation Act (ANILCA) for comprehensive resource and management plans from all major land management agencies in Alaska, the USGS has begun a program to classify land cover for the entire State using Landsat digital data. Vegetation and land cover classifications, generated in cooperation with other agencies, currently exist for 115 million acres of Alaska. Using these as a base, the USGS has prepared a comprehensive plan for classifying the remaining areas of the State. The development of this program will lead to a complete interim vegetation and land cover classification system for Alaska and allow the dissemination of digital data for those areas classified. At completion, 153 Alaska 1:250,000-scale quadrangles will be published and will include land cover from digital Landsat classifications, statistical summaries of all land cover by township, and computer-compatible tapes. An interagency working group has established an Alaska classification system (table 1) composed of 18 classes modified from "A land use and land cover classification system for use with remote sensor data" (Anderson and others, 1976), and from "Revision of a preliminary classification system for vegetation of Alaska" (Viereck and Dyrness, 1982) for the unique ecoregions which are found in Alaska.

  1. Consequences of land use and land cover change

    USGS Publications Warehouse

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

    2013-01-01

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

  2. Urban land cover classification using hyperspectral data

    NASA Astrophysics Data System (ADS)

    Hegde, G.; Ahamed, J. Mohammed; Hebbar, R.; Raj, U.

    2014-11-01

    Urban land cover classification using remote sensing data is quite challenging due to spectrally and spatially complex urban features. The present study describes the potential use of hyperspectral data for urban land cover classification and its comparison with multispectral data. EO-1 Hyperion data of October 05, 2012 covering parts of Bengaluru city was analyzed for land cover classification. The hyperspectral data was initially corrected for atmospheric effects using MODTRAN based FLAASH module and Minimum Noise Fraction (MNF) transformation was applied to reduce data dimensionality. The threshold Eigen value of 1.76 in VNIR region and 1.68 in the SWIR region was used for selection of 145 stable bands. Advanced per pixel classifiers viz., Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) were used for general urban land cover classification. Accuracy assessment of the classified data revealed that SVM was quite superior (82.4 per cent) for urban land cover classification as compared to SAM (67.1 per cent). Selecting training samples using end members significantly improved the classification accuracy by 20.1 per cent in SVM. The land cover classification using multispectral LISS-III data using SVM showed lower accuracy mainly due to limitation of spectral resolution. The study indicated the requirement of additional narrow bands for achieving reasonable classification accuracy of urban land cover. Future research is focused on generating hyperspectral library for different urban features.

  3. The Land Surface Temperature Impact to Land Cover Types

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  4. SOUTHWEST REGIONAL GAP LAND COVER

    EPA Science Inventory

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

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

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

  5. Chesapeake bay watershed land cover data series

    USGS Publications Warehouse

    Irani, Frederick M.; Claggett, Peter R.

    2010-01-01

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

  6. Forum on land use and land Cover: Summary report

    USGS Publications Warehouse

    U.S. Environmental Protection Agency; U.S. Geological Survey

    1992-01-01

    This report includes the agenda and abstracts of presentations from the Forum on Land Use and Land Cover Data, cohosted by the U. S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA), February 25-27,1992 at the USGS National Center in Reston, Virginia. The Forum was conducted under the auspices of the Federal Geographic Data Committee (FGDC) and was attended by Federal and State managers of programs that produce and use land use and land cover maps and data in support of environmental analysis, monitoring, and policy development. The goal was to improve opportunities for Federal and State coordination, information exchange, data sharing, and work sharing in land use and land cover mapping.

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

    SciTech Connect

    Singh, Nagendra; Bhaduri, Budhendra L

    2010-01-01

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

  8. Land Use and Land Cover Analysis in Indian Context

    NASA Astrophysics Data System (ADS)

    Roy, P. S.; Giriraj, A.

    Information on land use/land cover in the form of maps and statistical data is very vital for spatial planning, management and utilization of land. Land-Use and Land-Cover (LULC) scenario in India has undergone a radical change since the onset of economic revolution in early 1990s. These changes involve a series of complex interaction between biophysical and socioeconomic variables. LULC follows a set of scientific themes which includes detection and monitoring, carbon and biogeochemical cycle, ecosystems and biodiversity, water and energy cycle, predictive land use modeling and climate variability and change. With the changing times and increasing demand on the availability of information on land use/land cover, it becomes necessary to have a standard classification system, precise definition of land use/land cover and its categories, uniform procedures of data collection and mapping on different scales over Indian region. The current review thus attempts to focus on development of a national goal towards changes in LULC as a necessary step for an interdisciplinary research program involving climate, ecological and socioeconomic drives, the processes of change and the responses and consequences of change.

  9. Ecoregions and land cover trends in Senegal

    USGS Publications Warehouse

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

    2004-01-01

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

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

    PubMed Central

    Yüksel, Alaaddin; Akay, Abdullah E.; Gundogan, Recep

    2008-01-01

    The satellite imagery has been effectively utilized for classifying land cover types and detecting land cover conditions. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor imagery has been widely used in classification process of land cover. However, atmospheric corrections have to be made by preprocessing satellite sensor imagery since the electromagnetic radiation signals received by the satellite sensors 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 of INformation on the Environment (CORINE) land cover nomenclature, for an area representing the heterogonous characteristics of eastern Mediterranean regions in Kahramanmaras, Turkey. The results indicated that using the surface reflectance data of ASTER sensor imagery can provide accurate (i.e. overall accuracy and kappa values of 83.2% and 0.79, respectively) and low-cost cover mapping as a part of inventory for CORINE Land Cover Project.

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  12. You Can Accurately Predict Land Acquisition Costs.

    ERIC Educational Resources Information Center

    Garrigan, Richard

    1967-01-01

    Land acquisition costs were tested for predictability based upon the 1962 assessed valuations of privately held land acquired for campus expansion by the University of Wisconsin from 1963-1965. By correlating the land acquisition costs of 108 properties acquired during the 3 year period with--(1) the assessed value of the land, (2) the assessed…

  13. Trends in Mapping, Measuring, and Monitoring Land Cover Change

    NASA Astrophysics Data System (ADS)

    Loveland, T. R.; Hansen, M.

    2007-12-01

    The necessity for improved maps and statistics documenting the rates and characteristics of land cover change from local to global scales has been driven by the acceptance that land change has pervasive and substantial environmental consequences. The expanding need for accurate land cover change characteristics data over long time periods and large geographic areas has stimulated both methodological and mission advances. Two important methodological advances include the use of the continuous fields approach for quantifying key landscape characteristics including vegetation cover and surface imperviousness, and the increased emphasis on using probability sampling to precisely estimate land cover change rates. We are using Landsat-based sampling within ecoregions to assess 1972-2000 land change in the United States. An additional methodological trend is the use of multi-source remotely sensed data for land cover change assessments. An example that blends these three elements is our use of MODIS and Landsat to map and measure 2000-2005 global deforestation. MODIS forest fraction maps provide an annual source of forest change locations that provides an efficient means to stratify probable change. Automated classification of randomly sampled Landsat scenes provide a means for detecting forest change within forest biomes and generating precise estimates of period deforestation. Studies such as this are enabled by the NASA Earth Observing System program and the NASA-USGS Landsat Data Continuity Mission. Together, these missions extend the global Earth observation record to unprecedented levels and enable new generations of detailed land change assessments.

  14. LAND USE/LAND COVER, NEUSE RIVER WATERSHED (BUFFERED)

    EPA Science Inventory

    EOSAT and the North Carolina State University Computer Graphics Center, in cooperation with the NC Center for Geographic Information and Analysis, developed the Land Use/Land Cover digital data to enhance planning, siting and impact analysis in the Albemarle-Pamlico Estuarine Stu...

  15. Climate impacts of Australian land cover change

    NASA Astrophysics Data System (ADS)

    Lawrence, P. J.

    2004-05-01

    Australian land cover has been dramatically altered since European settlement primarily for agricultural utilization, with native vegetation widely replaced or modified for cropping and intensive animal production. While there have been numerous investigations into the regional and near surface climate impacts of Australian land cover change, these investigation have not included the climate impacts of larger-scale changes in atmospheric circulation and their associated feedbacks, or the impacts of longer-term soil moisture feedbacks. In this research the CSIRO General Circulation Model (GCM) was used to investigate the climate impacts of Australian land cover change, with larger-scale and longer-term feedbacks. To avoid the common problem of overstating the magnitude and spatial extent of changes in land surface conditions prescribed in land cover change experiments, the current Australian land surface properties were described from finer-scale, satellite derived land cover datasets, with land surface conditions extrapolating from remnant native vegetation to pre-clearing extents to recreate the pre-clearing land surface properties. Aggregation rules were applied to the fine-scale data to generate the land surface parameters of the GCM, ensuring the equivalent sub-grid heterogeneity and land surface biogeophysics were captured in both the current and pre-clearing land surface parameters. The differences in climate simulated in the pre-clearing and current experiments were analyzed for changes in Australian continental and regional climate to assess the modeled climate impacts of Australian land cover change. The changes in modeled climate were compared to observed changes in Australian precipitation over the last 50 and 100 years to assess whether modeled results could be detected in the historical record. The differences in climate simulation also were analyzed at the global scale to assess the impacts of local changes on larger scale circulation and climate at

  16. Modelling land cover dynamics: integration of fine-scale land cover data with landscape attributes

    NASA Astrophysics Data System (ADS)

    Mertens, Benoît; Lambin, Eric

    Land cover change detection based on remote sensing data allows the identification of major processes of change and, by inference, the characterization of land use dynamics. Empirical diagnostic models of land use/cover change can be developed from these observations. To grasp the complexity of landscape mosaics and changes in land use, fine-scale land cover and socio-economic data are required. Case studies need to be representative of conditions at a broader scale, and selected where sufficient knowledge on social and ecological processes leading to land use changes exists. For this reason, collaboration between remote sensing specialists and human ecologists conducting long-term field-based land use studies is extremely productive. Continental-scale analysis of Africa was conducted to detect land cover change "hot spots". Fine-scale analyses were performed for validation purposes and to understand better the land cover change processes. Spatial statistical models of land cover change can be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to support the implementation of appropriate policy responses to, for example, land degradation that would lead to the depletion of essential resources. Results of a spatial model of deforestation in southern Cameroon are discussed.

  17. How Scientists Differentiate Between Land Cover Types

    NASA Technical Reports Server (NTRS)

    2002-01-01

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

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

    USGS Publications Warehouse

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

    2011-01-01

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

  19. Land cover: national inventory of vegetation and land use

    USGS Publications Warehouse

    Gergely, Kevin J.; McKerrow, Alexa

    2013-01-01

    The Gap Analysis Program (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP national land cover includes data on the vegetation and land-use patterns of the United States, including Alaska, Hawaii, and Puerto Rico. This national dataset combines land cover data generated by regional GAP projects with Landscape Fire and Resource Management Planning Tools (LANDFIRE) data. LANDFIRE is an interagency vegetation, fire, and fuel characteristics mapping program, sponsored by the U.S. Department of the Interior and the U.S. Department of Agriculture Forest Service.

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

    USGS Publications Warehouse

    Latifovic, Rasim; Zhu, Zhi-Liang

    2004-01-01

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

  1. Classifying Land Cover Using Spectral Signature

    NASA Astrophysics Data System (ADS)

    Alawiye, F. S.

    2012-12-01

    Studying land cover has become increasingly important as countries try to overcome the destruction of wetlands; its impact on local climate due to seasonal variation, radiation balance, and deteriorating environmental quality. In this investigation, we have been studying the spectral signatures of the Jamaica Bay wetland area based on remotely sensed satellite input data from LANDSAT TM and ASTER. We applied various remote sensing techniques to generate classified land cover output maps. Our classifiers relied on input from both the remote sensing and in-situ spectral field data. Based upon spectral separability and data collected in the field, a supervised and unsupervised classification was carried out. First results suggest good agreement between the land cover units mapped and those observed in the field.

  2. Land Cover Analysis of Temperate Asia

    NASA Technical Reports Server (NTRS)

    Justice, Chris

    1998-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Gaillard, M.-J.; Sugita, S.; Mazier, F.; Kaplan, J. O.; Trondman, A.-K.; Broström, A.; Hickler, T.; Kjellström, E.; Kuneš, P.; Lemmen, C.; Olofsson, J.; Smith, B.; Strandberg, G.

    2010-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Gaillard, M.-J.; Sugita, S.; Mazier, F.; Trondman, A.-K.; Broström, A.; Hickler, T.; Kaplan, J. O.; Kjellström, E.; Kokfelt, U.; Kuneš, P.; Lemmen, C.; Miller, P.; Olofsson, J.; Poska, A.; Rundgren, M.; Smith, B.; Strandberg, G.; Fyfe, R.; Nielsen, A. B.; Alenius, T.; Balakauskas, L.; Barnekow, L.; Birks, H. J. B.; Bjune, A.; Björkman, L.; Giesecke, T.; Hjelle, K.; Kalnina, L.; Kangur, M.; van der Knaap, W. O.; Koff, T.; Lagerâs, P.; Latałowa, M.; Leydet, M.; Lechterbeck, J.; Lindbladh, M.; Odgaard, B.; Peglar, S.; Segerström, U.; von Stedingk, H.; Seppä, H.

    2010-07-01

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

  5. Predicting land cover using GIS, Bayesian and evolutionary algorithm methods.

    PubMed

    Aitkenhead, M J; Aalders, I H

    2009-01-01

    Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables. PMID:18079039

  6. Development of an Independent Global Land Cover Validation Dataset

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  7. Challenges in Global Land Use/Land Cover Change Modeling

    NASA Astrophysics Data System (ADS)

    Clarke, K. C.

    2011-12-01

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

  8. EFFECTS OF LANDSCAPE CHARACTERISTICS ON LAND-COVER CLASS ACCURACY

    EPA Science Inventory



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

  9. Climate Effects of Global Land Cover Change

    SciTech Connect

    Gibbard, S G; Caldeira, K; Bala, G; Phillips, T; Wickett, M

    2005-08-24

    There are two competing effects of global land cover change on climate: an albedo effect which leads to heating when changing from grass/croplands to forest, and an evapotranspiration effect which tends to produce cooling. It is not clear which effect would dominate in a global land cover change scenario. We have performed coupled land/ocean/atmosphere simulations of global land cover change using the NCAR CAM3 atmospheric general circulation model. We find that replacement of current vegetation by trees on a global basis would lead to a global annual mean warming of 1.6 C, nearly 75% of the warming produced under a doubled CO{sub 2} concentration, while global replacement by grasslands would result in a cooling of 0.4 C. These results suggest that more research is necessary before forest carbon storage should be deployed as a mitigation strategy for global warming. In particular, high latitude forests probably have a net warming effect on the Earth's climate.

  10. Decadal land cover change dynamics in Bhutan.

    PubMed

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

    2015-01-15

    Land cover (LC) is one of the most important and easily detectable indicators of change in ecosystem services and livelihood support systems. This paper describes the decadal dynamics in LC changes at national and sub-national level in Bhutan derived by applying object-based image analysis (OBIA) techniques to 1990, 2000, and 2010 Landsat (30 m spatial resolution) data. Ten LC classes were defined in order to give a harmonized legend land cover classification system (LCCS). An accuracy of 83% was achieved for LC-2010 as determined from spot analysis using very high resolution satellite data from Google Earth Pro and limited field verification. At the national level, overall forest increased from 25,558 to 26,732 km(2) between 1990 and 2010, equivalent to an average annual growth rate of 59 km(2)/year (0.22%). There was an overall reduction in grassland, shrubland, and barren area, but the observations were highly dependent on time of acquisition of the satellite data and climatic conditions. The greatest change from non-forest to forest (277 km(2)) was in Bumthang district, followed by Wangdue Phodrang and Trashigang, with the least (1 km(2)) in Tsirang. Forest and scrub forest covers close to 75% of the land area of Bhutan, and just over half of the total area (51%) has some form of conservation status. This study indicates that numerous applications and analyses can be carried out to support improved land cover and land use (LCLU) management. It will be possible to replicate this study in the future as comparable new satellite data is scheduled to become available. PMID:24680540

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

    NASA Technical Reports Server (NTRS)

    Clayton, C.

    1981-01-01

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

  12. AVHRR channel selection for land cover classification

    USGS Publications Warehouse

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

    2002-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Pressure on land resources is expected to increase as global population continues to climb and the world becomes more affluent, swelling the demand for food. Changing climate may exert additional pressures on natural lands as present-day productive regions may shift, or soil quality may degrade, and the recent rise in demand for biofuels increases competition with edible crops for arable land. Given these projected trends there is a need to understand the global climate impacts of land use and land cover change (LULCC). Here we quantify the climate impacts of global LULCC in terms of modifications to the balance between incoming and outgoing radiation at the top of the atmosphere (radiative forcing, RF) that are caused by changes in long-lived and short-lived greenhouse gas concentrations, aerosol effects, and land surface albedo. We attribute historical changes in terrestrial carbon storage, global fire emissions, secondary organic aerosol emissions, and surface albedo to LULCC using simulations with the Community Land Model version 3.5. These LULCC emissions are combined with estimates of agricultural emissions of important trace gases and mineral dust in two sets of Community Atmosphere Model simulations to calculate the RF of changes in atmospheric chemistry and aerosol concentrations attributed to LULCC. With all forcing agents considered together, we show that 40% (±16%) of the present-day anthropogenic RF can be attributed to LULCC. Changes in the emission of non-CO2 greenhouse gases and aerosols from LULCC enhance the total LULCC RF by a factor of 2 to 3 with respect to the LULCC RF from CO2 alone. This enhancement factor also applies to projected LULCC RF, which we compute for four future scenarios associated with the Representative Concentration Pathways. We attribute total RFs between 0.9 and 1.9 W m-2 to LULCC for the year 2100 (relative to a pre-industrial state). To place an upper bound on the potential of LULCC to alter the global radiation budget

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Channan, S.; Thomson, A. M.; Collins, K. M.; Sexton, J. O.; Torrens, P.; Emanuel, W. R.

    2014-12-01

    Land is a critical resource for human habitat and for the vast majority of human activities. Many natural resources are derived from terrestrial ecosystems or otherwise extracted from the landscape. Terrestrial biodiversity depends on land attributes as do people's perceptions of the value of land, including its value for recreation or tourism. Furthermore, land surface properties and processes affect weather and climate, and land cover change and land management affect emissions of greenhouse gases. Thus, land cover with its close association with climate is so pervasive that a land cover indicator is of fundamental importance to U.S. national climate assessments and related research. Moderate resolution remote sensing products (MODIS) were used to provide systematic data on annual distributions of land cover over the period 2001-2012. Selected Landsat observations and data products further characterize land cover at higher resolution. Here we will present the prototype for a suite of land cover indicators including land cover maps as well as charts depicting attributes such as composition by land cover class, statistical indicators of landscape characteristics, and tabular data summaries indispensable for communicating the status and trends of U.S. land cover at national, regional and state levels.

  16. Mapping land cover from satellite images: A basic, low cost approach

    NASA Technical Reports Server (NTRS)

    Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.

    1978-01-01

    Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

  17. Research priorities in land use and land-cover change for the Earth system and integrated assessment modelling

    SciTech Connect

    Hibbard, Kathleen A.; Janetos, Anthony C.; Van Vuuren, Detlef; Pongratz, Julia; Rose, Steven K.; Betts, Richard; Herold, Martin; Feddema, Johannes J.

    2010-11-15

    This special issue has highlighted recent and innovative methods and results that integrate observations and AQ3 modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated Assessment modeling communities recognize the importance of an accurate representation of land use and land-cover change to understand and quantify the interactions and feedbacks with the climate and socio-economic systems, respectively. To date, cooperation between these communities has been limited. Based on common interests, this work discusses research priorities in representing land use and land-cover change for improved collaboration across modelling, observing and measurement communities. Major research topics in land use and land-cover change are those that help us better understand (1) the interaction of land use and land cover with the climate system (e.g. carbon cycle feedbacks), (2) the provision of goods and ecosystem services by terrestrial (natural and anthropogenic) land-cover types (e.g. food production), (3) land use and management decisions and (4) opportunities and limitations for managing climate change (for both mitigation and adaptation strategies).

  18. Building a hybrid land cover map with crowdsourcing and geographically weighted regression

    NASA Astrophysics Data System (ADS)

    See, Linda; Schepaschenko, Dmitry; Lesiv, Myroslava; McCallum, Ian; Fritz, Steffen; Comber, Alexis; Perger, Christoph; Schill, Christian; Zhao, Yuanyuan; Maus, Victor; Siraj, Muhammad Athar; Albrecht, Franziska; Cipriani, Anna; Vakolyuk, Mar'yana; Garcia, Alfredo; Rabia, Ahmed H.; Singha, Kuleswar; Marcarini, Abel Alan; Kattenborn, Teja; Hazarika, Rubul; Schepaschenko, Maria; van der Velde, Marijn; Kraxner, Florian; Obersteiner, Michael

    2015-05-01

    Land cover is of fundamental importance to many environmental applications and serves as critical baseline information for many large scale models e.g. in developing future scenarios of land use and climate change. Although there is an ongoing movement towards the development of higher resolution global land cover maps, medium resolution land cover products (e.g. GLC2000 and MODIS) are still very useful for modelling and assessment purposes. However, the current land cover products are not accurate enough for many applications so we need to develop approaches that can take existing land covers maps and produce a better overall product in a hybrid approach. This paper uses geographically weighted regression (GWR) and crowdsourced validation data from Geo-Wiki to create two hybrid global land cover maps that use medium resolution land cover products as an input. Two different methods were used: (a) the GWR was used to determine the best land cover product at each location; (b) the GWR was only used to determine the best land cover at those locations where all three land cover maps disagree, using the agreement of the land cover maps to determine land cover at the other cells. The results show that the hybrid land cover map developed using the first method resulted in a lower overall disagreement than the individual global land cover maps. The hybrid map produced by the second method was also better when compared to the GLC2000 and GlobCover but worse or similar in performance to the MODIS land cover product depending upon the metrics considered. The reason for this may be due to the use of the GLC2000 in the development of GlobCover, which may have resulted in areas where both maps agree with one another but not with MODIS, and where MODIS may in fact better represent land cover in those situations. These results serve to demonstrate that spatial analysis methods can be used to improve medium resolution global land cover information with existing products.

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

    USGS Publications Warehouse

    Thogmartin, Wayne E.; Gallant, Alisa L.; Knutson, Melinda G.; Fox, Timothy J.; Suarez, Manuel J.

    2004-01-01

    Digital land-cover data are among the most popular data sources used in ecological research and natural resource management. However, processes for accurate land-cover classification over large regions are still evolving. We identified inconsistencies in the National Land Cover Dataset 1992, the most current and available representation of land cover for the conterminous United States. We also report means to address these inconsistencies in a bird-habitat model. We used a Geographic Information System (GIS) to position a regular grid (or lattice) over the upper midwestern United States and summarized the proportion of individual land covers in each cell within the lattice. These proportions were then mapped back onto the lattice, and the resultant lattice was compared to satellite paths, state borders, and regional map classification units. We observed mapping inconsistencies at the borders between mapping regions, states, and Thematic Mapper (TM) mapping paths in the upper midwestern United States, particularly related to grass I and-herbaceous, emergent-herbaceous wetland, and small-grain land covers. We attributed these discrepancies to differences in image dates between mapping regions, suboptimal image dates for distinguishing certain land-cover types, lack of suitable ancillary data for improving discrimination for rare land covers, and possibly differences among image interpreters. To overcome these inconsistencies for the purpose of modeling regional populations of birds, we combined grassland-herbaceous and pasture-hay land-cover classes and excluded the use of emergent-herbaceous and small-grain land covers. We recommend that users of digital land-cover data conduct similar assessments for other regions before using these data for habitat evaluation. Further, caution is advised in using these data in the analysis of regional land-cover change because it is not likely that future digital land-cover maps will repeat the same problems, thus resulting in

  20. MRLC-LAND COVER MAPPING, ACCURACY ASSESSMENT AND APPLICATION RESEARCH

    EPA Science Inventory

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

  1. Land Cover in the Puget Sound/Georgia Basin

    EPA Science Inventory

    This indicator compares changes in two land cover metrics (urban and forest land cover area) for the Puget Sound and Georgia Basin in Washington state and part of British Columbia, Canada. Data cover the period from 1995 to 2000 for the U.S. portion of the basin and from 1992 ...

  2. Optical remotely sensed time series data for land cover classification: A review

    NASA Astrophysics Data System (ADS)

    Gómez, Cristina; White, Joanne C.; Wulder, Michael A.

    2016-06-01

    Accurate land cover information is required for science, monitoring, and reporting. Land cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring and mapping of land cover and land cover change in a consistent and robust manner over large areas is made possible with Earth Observation (EO) data. Land cover products satisfying a range of science and policy information needs are currently produced periodically at different spatial and temporal scales. The increased availability of EO data-particularly from the Landsat archive (and soon to be augmented with Sentinel-2 data)-coupled with improved computing and storage capacity with novel image compositing approaches, have resulted in the availability of annual, large-area, gap-free, surface reflectance data products. In turn, these data products support the development of annual land cover products that can be both informed and constrained by change detection outputs. The inclusion of time series change in the land cover mapping process provides information on class stability and informs on logical class transitions (both temporally and categorically). In this review, we present the issues and opportunities associated with generating and validating time-series informed annual, large-area, land cover products, and identify methods suited to incorporating time series information and other novel inputs for land cover characterization.

  3. Photo interpretation key to Michigan land cover/use

    NASA Technical Reports Server (NTRS)

    Enslin, W. R.; Hudson, W. D.; Lusch, D. P.

    1983-01-01

    A set of photo interpretation keys is presented to provide a structured approach to the identification of land cover/use categories as specified in the Michigan Resource Inventory Act. The designated categories are urban and; built up lands; agricultural lands; forest land; nonforested land; water bodies; wetlands; and barren land. The keys were developed for use with medium scale (1:20,000 to 1:24,000) color infrared aerial photography. Although each key is generalized in that it relies only upon the most distinguishing photo characteristics in separating the various land cover/use categories, additional interpretation characteristics, distinguishing features and background material are given.

  4. Necessity to adapt land use and land cover classification systems to readily accept radar data

    NASA Technical Reports Server (NTRS)

    Drake, B.

    1977-01-01

    A hierarchial, four level, standardized system for classifying land use/land cover primarily from remote-sensor data (USGS system) is described. The USGS system was developed for nonmicrowave imaging sensors such as camera systems and line scanners. The USGS system is not compatible with the land use/land cover classifications at different levels that can be made from radar imagery, and particularly from synthetic-aperture radar (SAR) imagery. The use of radar imagery for classifying land use/land cover at different levels is discussed, and a possible revision of the USGS system to more readily accept land use/land cover classifications from radar imagery is proposed.

  5. Land cover controls on river discharge in Sweden. (Invited)

    NASA Astrophysics Data System (ADS)

    Van der Velde, Y.; Vercauteren, N.; Jaramillo, F.; Dekker, S. C.; Destouni, G.; Lyon, S. W.

    2013-12-01

    As humans alter landscape, vegetation, climate and atmospheric composition, changes in the terrestrial water balance and fresh water resources are likely to occur. Understanding how climate, vegetation, humans and hydrology interact is key for accurate projections of future fresh water resources. In this study we focus on forest dominated Sweden where significant changes in climate and increasing human activity have co-occurred during the past 50 years. For 280 catchments in Sweden, we related runoff coefficients and change trends thereof to land-surface characteristics. With these relationships we created average and change trend maps for runoff and evapotranspiration across Sweden. All this information is summarized by plotting water use efficiency (actual evapotranspiration (ET)/precipitation) against energy use efficiency (actual ET/potential ET ) in a Budyko-type framework for areas with unique land cover across Sweden. This plot clearly shows that wetlands tend to have lower water and energy use efficiencies compared to 'open waters', forests and agriculture, and that agriculture and forests have comparable water and energy use efficiencies closest to those of 'open waters'. These results demonstrate how a change in land cover driven by climate change or by humans is likely to alter land-cover-atmosphere interactions, thereby changing both the water and energy balance of catchments. Looking at runoff coefficient change trends during the last 50 years we see that forests tended to become more efficient in using water and energy (i.e. the fractions of water and energy converted into river runoff and heat decreased). As this behavior coincides with an increase in precipitation it signals an acceleration of the hydrological cycle of Swedish forests. In this presentation we will discuss these findings focusing on the impact of forests on river discharges and the implications for future water cycles.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  7. Land Cover Change Detection from MODIS Vegetation Index Time Series Data

    NASA Astrophysics Data System (ADS)

    Mithal, V.; O'Connor, Z.; Steinhaeuser, K.; Boriah, S.; Kumar, V.; Potter, C. S.; Klooster, S. A.

    2012-12-01

    Quantifiable knowledge about changes occurring in land cover and land use at a global scale is key to effective planning for sustainable use of diminishing natural resources such as forest cover and agricultural land. Accurate and timely information about land cover and land use changes is therefore of significant interest to earth and climate scientists as well as policy and decision makers. Recently, global time series data sets, such as Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index (EVI), have become publicly available and have been used to identify changes in vegetation cover. In this talk, we will discuss our work that analyzes the MODIS EVI time series data sets for global land cover change detection. Our group has developed a suite of time series change detection methods that are used to identify EVI time series with patterns indicative of land cover disturbance such as abrupt or gradual change, or changes in the recurring annual vegetation pattern. These algorithms can successfully identify different land cover change events such as deforestation, forest fires, agricultural conversions, and degradation due to insect damage at a global scale. In context of land cover monitoring, one of the significant challenges is posed by the differences in inter-annual variability and noise characteristics of different land cover types. These data characteristics can significantly impact change detection performance especially in land cover types such as farms, grasslands and tropical forests. We will discuss our recent work that incorporates a bootstrap-based normalization of change detection scores to account for the natural variability present in vegetation time series data. We studied the strengths and weakness of our proposed normalizing approaches in the context of characteristics of land cover data such as seasonality and noise and showed that relative performance of normalization approaches vary significantly depending on the

  8. 43 CFR 3101.4 - Lands covered by application to close lands to mineral leasing.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

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

  9. 43 CFR 3101.4 - Lands covered by application to close lands to mineral leasing.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

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

  10. 43 CFR 3101.4 - Lands covered by application to close lands to mineral leasing.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

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

  11. 43 CFR 3101.4 - Lands covered by application to close lands to mineral leasing.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

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

  12. Determination of Magnitude and Direction of Land Use/ Land Cover Changes in Terkos Water Basin, Istanbul

    NASA Astrophysics Data System (ADS)

    Bektas Balcik, F.; Goksel, C.

    2012-08-01

    Remotely sensed data have huge importance to determine land use/cover changes for sustainable region planning and management. Variety of techniques in order to detect land cover dynamics using remote sensing imagery have been developed, tested and assessed with the results varying according to the change scenario, the information required and the imagery applied. In this study, the modified Change Vector Analysis (mCVA) technique was implemented on SPOT 4 and SPOT 5 multispectral (MS) data to monitor the dynamics of land use/land cover (LULC) change in Terkos Water Basin, İstanbul. mCVA was applied to multi-temporal data to compare the differences in the time-trajectory of the Tasseled Cap (TC) brightness, greenness and wetness for two successive time periods - 2003 and 2007. Gram Schmidt Orthogonalization Technique was used to derive the related TC coefficients for SPOT data. The efficiency of the technique was assessed based on error matrix. The overall accuracy and Kappa statistic was 84.32 % and 0.81, respectively. The results indicated that it is possible to produce accurate change detection maps with the help of mCVA and SPOT 4 &SPOT 5 satellite data.

  13. Consistent Global Land Cover Maps For Climate Modelling Communities: Current Achievements Of The ESA' Land Cover CCI

    NASA Astrophysics Data System (ADS)

    Bontemps, S.; Defourny, P.; Radoux, J.; Van Bogaert, E.; Lamarche, C.; Achard, F.; Mayaux, P.; Boettcher, M.; Brockmann, C.; Kirches, G.; Zulkhe, M.; Kalogirou, V.; Seifert, F. M.; Arino, O.

    2013-12-01

    Led by the European Space Agency, the Climate Change Initiative land cover project focuses on the land cover observed as an Essential Climate Variable. Consultation mechanisms were established with the climate modelling community in order to identify its specific needs in terms of satellite-based global land cover products. Key finding was the needs for stable land cover data and a dynamic component in form of time-series. An innovative land cover concept is proposed, along with an new global land cover mapping approach, based on multi-year earth observation datasets. The corresponding products are presented, which consist of three successive and consistent global LC maps centred to the epochs 2000, 2005 and 2010.

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

    PubMed

    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. PMID:21229303

  15. Land cover for Ukraine: the harmonization of remote sensing and ground-based data

    NASA Astrophysics Data System (ADS)

    Lesiv, M.; Shchepashchenko, D.; Shvidenko, A.; See, L. M.; Bun, R.

    2012-12-01

    This study focuses on the development of a land cover map of the Ukraine through harmonization of remote sensing and ground-based data. At present there is no land cover map of the Ukraine available that is of sufficient accuracy for use in environmental modeling. The existing remote sensing data are not enough accurate. In this study we compare the territory of the Ukraine from three global remote sensing products (GlobCover 2009, MODIS Land Cover and GLC-2000) using a fuzzy logic methodology in order to capture the uncertainty in the classification of land cover. The results for the Ukraine show that GlobCover 2009, MODIS Land Cover and GLC-2000 have a fuzzy agreement of 65%. We developed a weighted algorithm for the creation of a land cover map based on an integration of a number of global land cover and remote sensing products including the GLC-2000, GlobCover 2009, MODIS Land Cover, the Vegetation Continuous Fields product, digital map of administrative units and forest account data at the local level. This weighted algorithm is based on the results of comparing these products and an analysis of a dataset of validation points for different land cover types in the Ukraine. We applied this algorithm to generate a forest land cover type map. This raster map contains a forest expectation index that was calculated for each pixel. Forest land was then allocated based on forest statistics at the local level. Areas with a higher forest expectation index were allocated with forest first until the results matched the forest statistics. The result is the first digital map of forest (with a spatial resolution of 300m) for the Ukraine, which consistent with forest and land accounts, remote sensing datasets and GIS products. The forest land was well defined in forest rich areas (i.e. in the northern part of the Ukraine, the Carpathians and the Crimea); well less accurate areas were identified in the steppe due to heterogeneous land cover. Acknowledgements. This research was

  16. Land Cover Mapping Using SENTINEL-1 SAR Data

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  17. Spatial relationship between landslide occurrence and land cover

    NASA Astrophysics Data System (ADS)

    Lu, P.

    2013-12-01

    Landslide represents a major type of natural hazards. It may leave great threat to human lives as well as infrastructures. In this study, we tried to understand the spatial relationship between landslide occurrences and land cover types through spatial statistics. The approach was based on the bivariate K-functions which can be used to analyze whether there is spatial clustering, repelling or randomness for landslide occurring in areas within different land covers. The Arno River basin in central Italy was chosen as the study area because the landslide inventory is complete with acquired records of more than 27,000 events. According to the inventory, we divided landslides into four classifications according to their types: slides, sofluctions, falls and flows. The land cover data was derived from the CORINE Land Cover map. The land cover types of artificial lands, natural and forest areas, and agriculture lands were focused on. The results indicate that landslides tend to occur in a clustering way within both three land covers. The difference is from the clustering level and spatial dependence distance. Therefore, no evidence can be found that the spatial pattern of landslide occurrence is dependent on changes of land covers.

  18. Satellite images for land cover monitoring - Navigating through the maze

    USGS Publications Warehouse

    Künzer, Claudia; Fosnight, Gene

    2001-01-01

    The focus of this publication is satellite systems for land cover monitoring. On the reverse is a table that compares a selection of these systems, whose data are globally available in a form suitable for land cover analysis. We hope the information presented will help you assess the utility of remotely sensed image to meet your needs.

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

    EPA Science Inventory

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

  20. Estimating Landscape Pattern Metrics from a Sample of Land Cover

    EPA Science Inventory

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

  1. Seasonal land-cover regions of the US

    USGS Publications Warehouse

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

    1995-01-01

    Global-change investigations have been hindered by deficiencies in the availability and quality of land-cover data. The US Geological Survey and the University of Nebraska-Lincoln have collaborated on the development of a new approach to land-cover characterization that attempts to address requirements of the global-change research community and others interested in regional patterns of land cover. An experimental 1-km-resolution database of land-cover characteristics for the coterminous US has been prepared to test and evaluate the approach. Using multidate Advanced Very High Resolution Radiometer (AVHRR) satellite data complemented by elevation, climate, ecoregions, and other digital spatial datasets, the authors define 15?? seasonal land-cover regions. Data are used in the construction of an illustrative 1:7500 000-scale map of the seasonal land-cover regions as well as of smaller-scale maps portraying general land cover and seasonality. The seasonal land-cover characteristics database can also be tailored to provide a broad range of other landscape parameters useful in national and global-scale environmental modeling and assessment. -from Authors

  2. Seasat SAR identification of dry climate urban land cover

    NASA Technical Reports Server (NTRS)

    Henderson, F. M.; Wharton, S. W.

    1980-01-01

    Digitally processed Seasat synthetic aperture radar (SAR) imagery of the Denver, Colorado area was examined to assess its potential for mapping urban land cover and the compatibility of SAR derived classes with those described in the U.S. Geological Survey classification system. The entire scene was interpreted to generate a small-scale land cover map. In addition, six subscene enlargements representative of urban land cover categories extant in the area were used as test sites for detailed analysis of land cover types. Two distinct approaches were employed and compared in examining the imagery - a visual interpretation of black-and-white positive transparencies and an automated-machine/visual interpretation. The latter used the Image 100 interactive image analysis system to generate land cover classes by density level slicing of the image frequency histogram.

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

    USGS Publications Warehouse

    Giri, Chandra; Defourny, P.; Shrestha, Surendra

    2003-01-01

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

  4. Land cover estimation using multiple satellite platforms during CLASIC

    Technology Transfer Automated Retrieval System (TEKTRAN)

    As a part of the Department of Energy Cloud and Land Surface Interaction Campaign (CLASIC) in June 2007, the land cover/land use was characteristized over the Atmospheric Radiation Measurement Southern Great Plains Testbed in Oklahoma throughout the month long field campaign. Excessive and persiste...

  5. Land cover classification for Puget Sound, 1974-1979

    NASA Technical Reports Server (NTRS)

    Eby, J. R.

    1981-01-01

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

  6. Time-Series analysis of MODIS NDVI data along with ancillary data for Land use/Land cover mapping of Uttarakhand

    NASA Astrophysics Data System (ADS)

    Patakamuri, S. K.; Agrawal, S.; Krishnaveni, M.

    2014-12-01

    Land use and land cover plays an important role in biogeochemical cycles, global climate and seasonal changes. Mapping land use and land cover at various spatial and temporal scales is thus required. Reliable and up to date land use/land cover data is of prime importance for Uttarakhand, which houses twelve national parks and wildlife sanctuaries and also has a vast potential in tourism sector. The research is aimed at mapping the land use/land cover for Uttarakhand state of India using Moderate Resolution Imaging Spectroradiometer (MODIS) data for the year 2010. The study also incorporated smoothening of time-series plots using filtering techniques, which helped in identifying phenological characteristics of various land cover types. Multi temporal Normalized Difference Vegetation Index (NDVI) data for the year 2010 was used for mapping the Land use/land cover at 250m coarse resolution. A total of 23 images covering a single year were layer stacked and 150 clusters were generated using unsupervised classification (ISODATA) on the yearly composite. To identify different types of land cover classes, the temporal pattern (or) phenological information observed from the MODIS (MOD13Q1) NDVI, elevation data from Shuttle Radar Topography Mission (SRTM), MODIS water mask (MOD44W), Nighttime Lights Time Series data from Defense Meteorological Satellite Program (DMSP) and Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) data were used. Final map product is generated by adopting hybrid classification approach, which resulted in detailed and accurate land use and land cover map.

  7. Land cover mapping of Greater Mesoamerica using MODIS data

    USGS Publications Warehouse

    Giri, Chandra; Jenkins, Clinton N.

    2005-01-01

    A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

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

    NASA Technical Reports Server (NTRS)

    Steyaert, Lou; Hall, Forrest G.; Newcomer, Jeffrey A. (Editor); Knapp, David E. (Editor); Loveland, Thomas R.; Smith, David E. (Technical Monitor)

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape

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

    PubMed

    Uddin, Kabir; Shrestha, Him Lal; Murthy, M S R; Bajracharya, Birendra; Shrestha, Basanta; Gilani, Hammad; Pradhan, Sudip; Dangol, Bikash

    2015-01-15

    Land cover and its change analysis across the Hindu Kush Himalayan (HKH) region is realized as an urgent need to support diverse issues of environmental conservation. This study presents the first and most complete national land cover database of Nepal prepared using public domain Landsat TM data of 2010 and replicable methodology. The study estimated that 39.1% of Nepal is covered by forests and 29.83% by agriculture. Patch and edge forests constituting 23.4% of national forest cover revealed proximate biotic interferences over the forests. Core forests constituted 79.3% of forests of Protected areas where as 63% of area was under core forests in the outside protected area. Physiographic regions wise forest fragmentation analysis revealed specific conservation requirements for productive hill and mid mountain regions. Comparative analysis with Landsat TM based global land cover product showed difference of the order of 30-60% among different land cover classes stressing the need for significant improvements for national level adoption. The online web based land cover validation tool is developed for continual improvement of land cover product. The potential use of the data set for national and regional level sustainable land use planning strategies and meeting several global commitments also highlighted. PMID:25181944

  10. Modeled impact of anthropogenic land cover change on climate

    USGS Publications Warehouse

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

    2007-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  12. National Land Cover and Resource Statistics

    NASA Astrophysics Data System (ADS)

    Nilsen, A. B.; Bjørkelo, K.

    2012-08-01

    An overall societal aim is to ensure a sustainable use and management of a country's land resources. This requires continuous deliv-ery of reliable and up-to-date information to decision-makers. To be able to deliver this information the Norwegian Forest and Land-scape Institute (Skog og landskap) produces, among others, land resource statistics for all municipalities in Norway. The statistics are also produced on a county level and for the whole country. The acreage numbers are retrieved from a combination of different na-tional datasets in various scales together with interpretation of satellite images. Through a reclassification, statistics are calculated for certain land resource classes like arable land, pasture, forest based on productivity class, fresh water, snow and glacier, mountain-ous/scarcely vegetated area and built up area. Skog og landskap has for the last couple of years been using open source software. The whole statistics production line is carried out by the means of such software. The results are stored in XML-files that are published on the internet. The production requires processing of several databases with national coverage, and needs to handle geometric opera-tions efficiently and without error. The open software solution is reliable, stable and fast.

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

    PubMed Central

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

    2013-01-01

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

  14. Comparison of field and airborne laser scanning based crown cover estimates across land cover types in Kenya

    NASA Astrophysics Data System (ADS)

    Heiskanen, J.; Korhonen, L.; Hietanen, J.; Heikinheimo, V.; Schafer, E.; Pellikka, P. K. E.

    2015-04-01

    Tree crown cover (CC) provides means for the continuous land cover characterization of complex tropical landscapes with multiple land uses and variable degrees of degradation. It is also a key parameter in the international forest definitions that are basis for monitoring global forest cover changes. Recently, airborne laser scanning (ALS) has emerged as a practical method for accurate CC mapping, but ALS derived CC estimates have rarely been assessed with field data in the tropics. Here, our objective was to compare the various field and ALS based CC estimates across multiple land cover types in the Taita Hills, Kenya. The field data was measured from a total of 178 sample plots (0.1 ha) in 2013 and 2014. The most accurate field measurement method, line intersect sampling using Cajanus tube, was used in 37 plots. Other methods included CC estimate based on the tree inventory data (144 plots), crown relascope (43 plots) and hemispherical photography (30 plots). Three ALS data sets, including two scanners and flying heights, were acquired concurrently with the field data collection. According to the results, the first echo cover index (FCI) from ALS data had good agreement with the most accurate field based CC estimates (RMSD 7.1% and 2.7% depending on the area and scan). The agreement with other field based methods was considerably worse. Furthermore, we observed that ALS cover indices were robust between the different scans in the overlapping area. In conclusion, our results suggest that ALS provides a reliable method for continuous CC mapping across tropical land cover types although dense shrub layer and tree-like herbaceous plants can cause overestimation of CC.

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

    USGS Publications Warehouse

    Xian, G.; Homer, C.; Fry, J.

    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. ?? 2009 Elsevier Inc.

  16. Land Cover Classification Method Oriented to Geographic National Conditions Investigation

    NASA Astrophysics Data System (ADS)

    Cheng, T.

    2014-04-01

    Developing the project of geographic national conditions investigation is in order to obtain land cover change information which is caused by natural and human social and economic activities, and serve the information for government, enterprise and public. Land cover is an important method to describe the geographic national conditions information, which can truly reflect the land surface material type and its natural attribute. It has been contained in the content system preliminary scheme as an important portion. In this paper, it discusses and analyzes on the method and key technology, with according to the land cover content that geographic national conditions watches on. Then it evaluates the applicability of automatic classification method using in land cover information extraction, and comprehensively analyzes various extraction methods' maximum effectiveness. Finally, it proposes a method that is based on high spatial resolution remote sensing imagery and can be used in engineering applications, which provides a reference method for geographic national conditions investigation.

  17. Global Land Cover Classification Using Modis Surface Reflectance Prosucts

    NASA Astrophysics Data System (ADS)

    Fukue, Kiyonari; Shimoda, Haruhisa

    2016-06-01

    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%.

  18. [Regional evapotranspiration of different land covers based on remote sensing].

    PubMed

    He, Yan-bo; Z, Su; L, Jia; Wang, Shi-li

    2007-02-01

    In this paper, surface energy balance system (SEBS) was extended into a regional daily evapotranspiration (ET) estimation model based on remote sensing data, and the extended SEBS was applied to estimate the regional daily ET of Huanghe-Huaihe-Haihe rivers region in Northern China Plain by using MODIS/TERRA data. An analysis was made on the estimated daily ET characteristics of different land covers in the study area by using the spatial analysis module of ArcGIS. Since there were no field observations of ET on each land cover, the estimated daily ET of different land covers was compared with each other, taking the data on April 17, 2001 as an example. The results showed that the regional daily ET estimated by SEBS was reasonable. Wetland and cultivated land had the highest daily ET value, followed by forest-, bush- and grassland, and waste land. The characteristics of the daily ET over these land covers were accorded with the existing knowledge of ET over this region, and coincident to the results of previous work in this area. It was interesting that the residential area also had a higher ET value, which was explained as the higher ET of the land use types, e. g. , water body, street trees, and grass parcels in the resident areas within the pixel scale. The spatial inhomogeneity of ET among the forest-, bush-, grass- and cultivated land covers were caused by the spatial inhomogeneous soil water content under these land covers, and the spatial inhomogeneity of ET over cultivated land could be a potential indicator of making reasonable and effective irrigation schedule for the farmland. The limitations of using SEBS model in daily ET estimation were discussed, especially the possibility of underestimating the ET over water body and wetland covers due to the unsuitable surface parameterization scheme for these land types in the model. PMID:17450729

  19. PERCENT AGRICULTURAL LAND COVER ON STEEP SLOPES

    EPA Science Inventory

    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. High amounts of agriculture on steep slopes can increase the amount of soil erosion leading to increased sediment in ...

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

    USGS Publications Warehouse

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

    2001-01-01

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

  1. Characterizing The Surface Dynamics For Land Cover Mapping: Current Achievements Of The ESA CCI Land Cover

    NASA Astrophysics Data System (ADS)

    Lamarche, Celine; Bontemps, Sophie; Verhegghen, Astrid; Radoux, Jullien; Vanbogaert, Eric; Kalogirou, Vasileios; Seifert, Frank Martin; Arino, Olivier; Defourny, Pierre

    2013-12-01

    Land Cover (LC) was listed as an Essential Climate Variable by the Global Climate Observing System and included the ESA Climate Change Initiative (CCI) that aims at providing global long-term satellite-based products tailored to the need of the climate modelling community. In the framework of the CCI-LC project, the LC concept was revisited in order to reconcile the LC users' divergent needs for both stable/consistent global LC products over time and more dynamic information related to the dynamic processes of the land surface. This paper aims first at describing the three global products generated in response to this need for more dynamic information, namely the condition products. These products characterize globally the green vegetation phenology, the burnt areas and snow occurrences. The main challenge beyond the production of these datasets refers to the spatio/temporal consistency between the stable and dynamic components of the LC. The second objective of this paper is therefore to address the work on-going on the characterization of this consistency.

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

    PubMed Central

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

    2013-01-01

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

  3. Study on the Land Cover/Use Features by Using ALOS-PALSAR Data

    NASA Astrophysics Data System (ADS)

    Lim, H. S.; MatJafri, M. Z.; Abullah, K.; Saleh, N. Mohd.

    2008-11-01

    Remote sensing technique gives a very useful tool for detecting and analyzing land cover/use features in our environment. This study was carried out to identity the land cover/use features over Penang Island, Malaysia. This research is an investigation to the multi polarized data of ALOS-PALSAR data for land cover/use mapping. The ALOS-PALSAR data used in this study was acquired on 1 November 2007. The ALOS-PALSAR images of the study area were chosen for land cover mapping using the standard supervised classification techniques (Maximum Likelihood, Minimum Distance-to-mean and Parallelepiped). Some filtering and enhancement methods had to be applied in order to reduce speckle noise and to contrast the images. Composite color images were produced for visual interpretation and field surveys. After investigation of the ground truth, representative areas of each land cover type were identified and allocated to the images. The PALSAR data of training areas were choose and selected based on the high resolution optical satellite imagery and were classified using supervised classification methods. The land cover information was extracted from the digital spectral bands using PCI Geomatica 10.1 software package. The accuracies of all classifications will be analyzed to evaluate the best performing combination. The results show that accurate land cover/use distribution maps can be produced from ALOS-PALSAR data.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  5. Modelling land cover change in the Ganga basin

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    SciTech Connect

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

    2001-08-01

    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.

  7. Survey methods for assessing land cover map accuracy

    USGS Publications Warehouse

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

    2003-01-01

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

  8. Global land cover classification using annual statistical values

    NASA Astrophysics Data System (ADS)

    Soyama, Noriko; Muramatsu, Kanako; Daigo, Motomasa

    2012-10-01

    Global land cover data sets are required for the study of global environmental changes such as global biogeochemical cycles and climate change, and for the estimation of gross primary production. To determine land cover classification condition, producers examine the phenological feature of each land cover class's sample area with vegetation indices or only reflectance. In this study, to detect the phenological feature of land surfaces, we use the universal pattern decomposition method (UPDM) three coefficients and two indices; the modified vegetation index based on the UPDM (MVIUPD) and the chlorophyll index (CIgreen). The UPDM three coefficients are corresponded to actual objects; water, vegetation and soil. To detect the phenological feature of each land cover class simply, we use annual statistical values of the UPDM coefficients and two indices. By visualizing three statistical values with combination of RGB, land areas with similar phenological feature are able to detect globally. We produced the global land cover products by applying this method with MODIS Aqua Surface Reflectance 8-Day L3 Global 500m data sets of 2007. The result was roughly similar to the MOD12Q1 of the same year.

  9. Effects of landscape characteristics on land-cover class accuracy

    USGS Publications Warehouse

    Smith, Jonathan H.; Stehman, Stephen V.; Wickham, James D.; Yang, Limin

    2003-01-01

    The effects of patch size and land-cover heterogeneity on classification accuracy were evaluated using reference data collected for the National Land-Cover Data (NLCD) set accuracy assessment. Logistic regression models quantified the relationship between classification accuracy and these landscape variables for each land-cover class at both the Anderson Levels I and II classification schemes employed in the NLCD. The general relationships were consistent, with the odds of correctly classifying a pixel increasing as patch size increased and decreasing as heterogeneity increased. Specific characteristics of these relationships, however, showed considerable diversity among the various classes. Odds ratios are reported to document these relationships. Interaction between the two landscape variables was not a significant influence on classification accuracy, indicating that the effect of heterogeneity was not impacted by the sample being in a small or large patch. Landscape variables remained significant predictors of class-specific accuracy even when adjusted for regional differences in the mapping and assessment processes or landscape characteristics. The land-cover class-specific analyses provide insight into sources of classification error and a capacity for predicting error based on a pixel's mapped land-cover class, patch size and surrounding land-cover heterogeneity.

  10. Uncertainty in hurricane surge simulation due to land cover specification

    NASA Astrophysics Data System (ADS)

    Ferreira, Celso M.; Irish, Jennifer L.; Olivera, Francisco

    2014-03-01

    Hurricane storm surge is one of the most costly natural hazards in the United States. Numerical modeling to predict and estimate hurricane surge flooding is currently widely used for research, planning, decision making, and emergency response. Land cover plays an important role in hurricane surge numerical modeling because of its impacts on the forcing (changes in wind momentum transfer to water column) and dissipation (bottom friction) mechanisms of storm surge. In this study, the hydrodynamic model ADCIRC was used to investigate predicted surge response in bays on the central and lower Texas coast using different land cover data sets: (1) Coastal Change Analysis Program for 1996, 2001, and 2006; (2) the National Land Cover Dataset for 1992, 2001, and 2006; and (3) the National Wetlands Inventory for 1993. Hypothetical storms were simulated with varying the storm track, forward speed, central pressure, and radius to maximum wind, totaling 140 simulations. Data set choice impacts the mean of maximum surges throughout the study area, and variability in the surge prediction due to land cover data set choice strongly depends on storm characteristics and geographical location of the bay in relation to storm track. Errors in surge estimation due to land cover choice are approximately 7% of the surge value, with change in surge prediction varying by as much as 1 m, depending on location and storm condition. Finally, the impact of land cover choice on the accuracy of simulating surges for Hurricane Bret in 1999 is evaluated.

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

    USGS Publications Warehouse

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

    2013-01-01

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

  12. Evapotranspiration model of different complexity for multiple land cover types

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A comparison between half-hourly and daily measured and computed evapotranspiration (ET) using three models of different complexity, namely the Priestley-Taylor (P-T), reference Penman-Monteith (P-M), and Common Land Model (CLM) was conducted using three AmeriFlux sites under different land cover an...

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

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

    PubMed

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

    2007-11-01

    Land-cover change in eastern lowland Bolivia was documented using Landsat images from five epochs for all landscapes situated below the montane tree line at approximately 3000 m, including humid forest, inundated forest, seasonally dry forest, and cloud forest, as well as scrublands and grasslands. Deforestation in eastern Bolivia in 2004 covered 45,411 km2, representing approximately 9% of the original forest cover, with an additional conversion of 9042 km2 of scrub and savanna habitats representing 17% of total historical land-cover change. Annual rates of land-cover change increased from approximately 400 km2 y(-1) in the 1960s to approximately 2900 km2 y(-1) in the last epoch spanning 2001 to 2004. This study provides Bolivia with a spatially explicit information resource to monitor future land-cover change, a prerequisite for proposed mechanisms to compensate countries for reducing carbon emissions as a result of deforestation. A comparison of the most recent epoch with previous periods shows that policies enacted in the late 1990s to promote forest conservation had no observable impact on reducing deforestation and that deforestation actually increased in some protected areas. The rate of land-cover change continues to increase linearly nationwide, but is growing faster in the Santa Cruz department because of the expansion of mechanized agriculture and cattle farms. PMID:18074899

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

    EPA Science Inventory

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

  16. Change detection for Finnish CORINE land cover classification

    NASA Astrophysics Data System (ADS)

    Törmä, Markus; Härmä, Pekka; Hatunen, Suvi; Teiniranta, Riitta; Kallio, Minna; Järvenpää, Elise

    2011-11-01

    This paper describes the ideas, data and methods to produce Finnish Corine Land Cover 2006 (CLC2006) classification. This version is based on use of existing national GIS data and satellite images and their automated processing, instead of visual interpretation of satellite images. The main idea is that land use information is based on GIS datasets and land cover information interpretation of satellite images. Because Finland participated to CLC2000-project, also changes between years 2000 and 2006 are determined. Finnish approach is good example how national GIS data is used to produce data fulfilling European needs in bottom-up fashion.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    EPA Science Inventory

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

  19. Advanced multispectral sensor requirements for remote sensing of agriculture and land cover

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Modern agricultural and land cover monitoring programs require frequent data acquisitions and increased spectral resolution to acquire a greater number of parameters in a more accurate manner. Whereas hyperspectral sensors could provide the required information, agriculture's biggest need is for fr...

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

    USGS Publications Warehouse

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

    2014-01-01

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

  1. Temporal Land Cover Analysis for Net Ecosystem Improvement

    SciTech Connect

    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.

  2. Impact of land cover types and components on urban heat

    NASA Astrophysics Data System (ADS)

    Xie, L. T.; Cai, G. Y.

    2015-12-01

    This paper discussed the impact of the distribution of parks including water bodies on the relief of urban heat. An image of QuickBird on Aug. 30, 2013 was employed to perform the detailed land cover classification. One swath of Landsat 8 THIR image was collected to derive the land surface temperature. After some necessary preprocessing procedures, object-based classification method was used to classify the land cover as residential region, square and road, water body, as well as park. The results showed that water bodies and parks play an important role in reducing the land surface temperature. Grass, shrub and trees were extracted out respectively by manual from parks that were adopted to test the influence of proportions among trees, shrubs and grass on the fluctuation of land surface temperature in urban area. The results achieved in this paper could be helpful for the local governments to make a decision in urban plan and management.

  3. Impacts of Land-Use and Land-Cover Change over South America: a modeling study

    NASA Astrophysics Data System (ADS)

    Nascimento, M. G. D.; Herdies, D. L.; Souza, D. O. D.

    2014-12-01

    Changes in patterns of land use and land cover have great influence on hydrology, climate and biogeochemical cycles. In this work the influences caused by changes in patterns of land cover and land use in Brazil on the behavior of the water balance over South America were evaluated. To fulfill this objective numerical experiments were carried out with the regional model ETA for the period between 1979 and 2008, in which three different conditions of land use and land cover in Brazil was used: 1) Potential Experiment, which are not included the anthropogenic changes in vegetation cover; 2) Control Experiment, in which the map of land use and land cover used the conditions of the 90s; 3) New Experiment, which represents the current conditions of land use and land cover. The results show clearly that the constant changes in patterns of land cover and land use in Brazil cause an increase in precipitation and moisture convergence, and reduced evapotranspiration over the Amazon Region. In other words, it can be stated that with the advance of changes in patterns of land use and land cover, Amazon further intensified their behavior as a sink of moisture, mainly due to increased precipitation and significant reduction in evapotranspiration, noting also that reduction of moisture available in the atmosphere was not offset by increased moisture convergence. The results on the La Plata Basin shows that initially (CONTROL) there is an increase in precipitation and evapotranspiration over the region and reduction in moisture convergence, which is later (NEW) modified to a pattern of reduction in precipitation and evapotranspiration followed by an increase in moisture convergence. These changes in the patterns of land use and land cover of the 90s make the area potentially source of moisture to the atmosphere, even with the reduction in moisture convergence, but reversing their behavior to sink moisture by inserting current vegetation cover modifications, mainly due to reduced

  4. Determination of land degradation causes in Tongyu County, Northeast China via land cover change detection

    NASA Astrophysics Data System (ADS)

    Gao, Jay; Liu, Yansui

    2010-02-01

    Tongyu County in Northeast China is highly prone to land degradation due to its fragile physical settings characterized by a flat topography, a semi-arid climate, and a shallow groundwater table. This study aims to determine the causes of land degradation through detecting the long-term trend of land cover changes. Degraded lands were mapped from satellite images recorded in 1992 and 2002. These land cover maps revealed that the area subject to land degradation in the form of soil salinization, waterlogging and desertification increased from 2400 to 4214 km 2, in sharp contrast to most severely degraded land that decreased by 122.5 km 2. Newly degraded land stems from productive farmland (263 km 2), harvested farmland (551 km 2), and grassland (468 km 2). Therefore, the worsened degradation situation is attributed to excessive reclamation of grassland for farming, over cultivation, overgrazing, and deforestation. Mechanical, biological, ecological and engineering means should be adopted to rehabilitate the degraded land.

  5. Dependence of Polarimetric Scattering Mechanisms on Land Cover

    NASA Astrophysics Data System (ADS)

    Atwood, D. K.; Meyer, F.

    2011-03-01

    A method for statistically representing the polarimetric SAR scattering mechanisms of individual land cover classes is introduced and applied to ALOS PALSAR L-band quad-pol data. PALSAR scattering signatures are correlated with land cover classification maps to determine typical scattering mechanisms. The approach utilizes two free, open-source software tools, ESA's PolSARpro and the Alaska Satellite Facility's MapReady Remote Sensing Toolbox as well as Geographic Information System (GIS) tools, to compute the probability density functions of normalized decomposition components for each land cover class.The proposed method provides the ability to compare polarimetric decompositions, investigate scattering mechanisms, detect change in land cover classification, and discover inhomogeneities in the spectral characteristics of individual classes. The approach is first employed to compare the Freeman and Van Zyl three-component decomposition techniques, where the former is shown to introduce many pixels with 100% volume saturation.Ideally, the method yields distinctive scattering peaks for each land cover class with minimal variance in the individual scattering components. However, in some instances, bimodal peaks are found. These are shown to either represent changes between the original land classification and the SAR acquisitions, or the existence of spectral subclasses that were not differentiated in the original classification. Last, the method is used to determine the impact of Polarimetric Orientation Angle (POA) correction on the scattering signatures of urban land cover classes. POA compensation is shown to bring about a significant reduction in the volume scattering component.A method for statistically representing the polarimetric SAR scattering mechanisms of individual land cover classes is introduced and applied to ALOS PALSAR L-band quad-pol data. PALSAR scattering signatures are correlated with land cover classification maps to determine typical

  6. Classifying Urban Land Covers Using Local Indices of Spatial Complexity

    NASA Technical Reports Server (NTRS)

    Arumugam, Mahesh; Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.

    2003-01-01

    The skewed statistical distributions of land cover types in complex, heterogeneous urban areas limits the effectiveness of traditional spectrally based maximum-likelihood classifiers. This work examines the utility of fractal dimension and Moran's I index of spatial autocorrelation in segmenting high-resolution panchromatic and lower-resolution multispectral imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze multi-temporal and multi-platform imagery of Atlanta, Georgia. In this example, land cover change trajectories from forest or grassland to built up land covers lead to decreased spatial autocorrelation. In lower resolution imagery such as Landsat MSS, the complex details of forested land covers and urbanized areas are smoothed, and texture-based change detection is less effective. Although segmentation of panchromatic images is possible using fractal dimension or Moran's I, widely differing land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification.

  7. Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery

    NASA Technical Reports Server (NTRS)

    Estes, John E.; Gebelein, Jennifer

    1999-01-01

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

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

    USGS Publications Warehouse

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

    2008-01-01

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

  9. Selection of classification techniques for land use/land cover change investigation

    NASA Astrophysics Data System (ADS)

    Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; Bray, Michaela; Islam, Tanvir

    2012-11-01

    The concerns over land use/land cover (LULC) change have emerged on the global stage due to the realisation that changes occurring on the land surface also influence climate, ecosystem and its services. As a result, the importance of accurate mapping of LULC and its changes over time is on the increase. Landsat satellite is a major data source for regional to global LULC analysis. The main objective of this study focuses on the comparison of three classification tools for Landsat images, which are maximum likelihood classification (MLC), support vector machine and artificial neural network (ANN), in order to select the best method among them. The classifiers algorithms are well optimized for the gamma, penalty, degree of polynomial in case of SVM, while for ANN minimum output activation threshold and RMSE are taken into account. The overall analysis shows that the ANN is superior to the kernel based SVM (linear, radial based, sigmoid and polynomial) and MLC. The best tool (ANN) is then applied on detecting the LULC change over part of Walnut Creek, Iowa. The change analysis of the multi temporal images indicates an increase in urban areas and a major shift in the agricultural practices.

  10. Land Cover Change in the Boston Mountains, 1973-2000

    USGS Publications Warehouse

    Karstensen, Krista A.

    2009-01-01

    The U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-cover change. The objectives of the study are to: (1) to develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data to measure regional land-cover change across the United States; (2) to characterize the types, rates, and temporal variability of change for a 30-year period; (3) to document regional driving forces and consequences of change; and (4) to prepare a national synthesis of land-cover change (Loveland and others, 1999). The 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) provide the geographic framework for the geospatial data collected between 1973 and 2000. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000, and the data are evaluated using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historic aerial photographs from similar time frames and other ancillary data, such as census statistics and published literature, are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional

  11. Modeling Land Use/Cover Changes in an African Rural Landscape

    NASA Astrophysics Data System (ADS)

    Kamusoko, C.; Aniya, M.

    2006-12-01

    Land use/cover changes are analyzed in the Bindura district of Zimbabwe, Africa through the integration of data from a time series of Landsat imagery (1973, 1989 and 2000), a household survey and GIS coverages. We employed a hybrid supervised/unsupervised classification approach to generate land use/cover maps from which landscape metrics were calculated. Population and other household variables were derived from a sample of surveyed villages, while road accessibility and slope were obtained from topographic maps and digital elevation model, respectively. Markov-cellular automata modeling approach that incorporates Markov chain analysis, cellular automata and multi-criteria evaluation (MCE) / multi-objective allocation (MOLA) procedures was used to simulate land use/cover changes. A GIS-based MCE technique computed transition potential maps, whereas transition areas were derived from the 1973-2000 land use/cover maps using the Markov chain analysis. A 5 x 5 cellular automata filter was used to develop a spatially explicit contiguity- weighting factor to change the cells based on its previous state and those of its neighbors, while MOLA resolved land use/cover class allocation conflicts. The kappa index of agreement was used for model validation. Observed trends in land use/cover changes indicate that deforestation and the encroachment of cultivation in woodland areas is a continuous trend in the study area. This suggests that economic activities driven by agricultural expansion were the main causes of landscape fragmentation, leading to landscape degradation. Rigorous calibration of transition potential maps done by a MCE algorithm and Markovian transition probabilities produced accurate inputs for the simulation of land use/cover changes. Overall standard kappa index of agreement ranged from 0.73 to 0.83, which is sufficient for simulating land use/cover changes in the study area. Land use/cover simulations under the 1989 and 2000 scenario indicated further

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

    NASA Astrophysics Data System (ADS)

    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).

  13. Combining satellite data with ancillary data to produce a refined land-use/land-cover map

    USGS Publications Warehouse

    Stewart, J.S.

    1998-01-01

    As part of the U.S. Geological Survey's National Water-Quality Assessment Program in the Western Lake Michigan Drainages Study Unit, a current map of land use and land cover is needed to gain a better understanding of how land use and land cover may influence water quality. Satellite data from the Landsat Thematic Mapper provides a means to map and measure the type and amount of various land-cover types across the Study Unit and can be easily updated as changes occur in the landscape or in water quality. Translating these land cover categories to land use, however, requires the use of other thematic maps or ancillary data layers, such as wetland inventories, population data, or road networks. This report describes a process of (1) using satellite imagery to produce a land-cover map for the Fox/Wolf River basin, a portion of the Western Lake Michigan Drainages NAWQA Study Unit and (2) improving the satellite-derived land-cover map by using other thematic maps. The multiple data layers are processed in a geographic information system (GIS), and the combination provides more information than individual sources alone.

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

    USGS Publications Warehouse

    Diffendorfer, Jay E.; Compton, Roger W.

    2014-01-01

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

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

    PubMed Central

    Diffendorfer, Jay E.; Compton, Roger W.

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  17. Constraints of Predicting Land Cover Changes from Bioclimatic Models - with Special Regard to Forest Cover

    NASA Astrophysics Data System (ADS)

    Matyas, C.; Rasztovits, E.

    2009-04-01

    The determination of "climatic envelopes" of biota and especially of forests has attained a sudden actuality in the context of expected climatic changes, as zonal vegetation types serve as convenient climate indicators. Studies on bioclimatic modelling and on climate change-triggered vegetation shifts are abundant and have been considered also in the fourth report of IPCC. Present and predicted distribution of forest biota provide an illustrative impression of shift of potential land cover changes. There are, however, certain assumptions which remain often unmentioned, and which - if left unconsidered - may compromise the outcome. The bioclimatic models of actual biome or species distributions may be biased, because: (1) Present "natural" vegetation cover types are in most part of the world under strong human influence. In Europe, even the few remaining close to natural landscapes are the results of long lasting human interference of the past which continue also in the present. (2) It is a well known ecological rule that actual ranges of species and biota are regulated by complex, often hidden interactions which may modify distributions. Physiologically (more accurately: genetically) set potential limits may be per definitionem wider than the realized, actual ones. To include extrazonal outliers in bioclimatic models may cause errors. (3) The longevity and persistence of forest trees may be deceptive for climatic modelling at the retreating, xeric limits. The climatic zones move usually faster than the land (forest) cover indicating those zones. (4) Climate envelopes use standard (mean) climate parameters. It is however the effect of the sequence of consecutive extreme weather events and linked biotic damages which will concretely decide over survival or mortality. Therefore the use of climate means should be regarded only as surrogates for weather extremes. (5) The change of climatic environment may alter the phenologic behaviour which cannot be tested in advance

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  20. Evolving land cover classification algorithms for multispectral and multitemporal imagery

    NASA Astrophysics Data System (ADS)

    Brumby, Steven P.; Theiler, James P.; Bloch, Jeffrey J.; Harvey, Neal R.; Perkins, Simon J.; Szymanski, John J.; Young, Aaron C.

    2002-01-01

    The Cerro Grande/Los Alamos forest fire devastated over 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos and the adjoining Los Alamos National Laboratory. The need to measure the continuing impact of the fire on the local environment has led to the application of a number of remote sensing technologies. During and after the fire, remote-sensing data was acquired from a variety of aircraft- and satellite-based sensors, including Landsat 7 Enhanced Thematic Mapper (ETM+). We now report on the application of a machine learning technique to the automated classification of land cover using multi-spectral and multi-temporal imagery. We apply a hybrid genetic programming/supervised classification technique to evolve automatic feature extraction algorithms. We use a software package we have developed at Los Alamos National Laboratory, called GENIE, to carry out this evolution. We use multispectral imagery from the Landsat 7 ETM+ instrument from before, during, and after the wildfire. Using an existing land cover classification based on a 1992 Landsat 5 TM scene for our training data, we evolve algorithms that distinguish a range of land cover categories, and an algorithm to mask out clouds and cloud shadows. We report preliminary results of combining individual classification results using a K-means clustering approach. The details of our evolved classification are compared to the manually produced land-cover classification.

  1. Comparison of ET models over different land cover

    NASA Astrophysics Data System (ADS)

    Sun, Liang; Liang, Shunlin; Chen, Zhongxin

    2014-03-01

    The objective of this work is to compare various ET models based on a standard dataset. We selected 9 ET models for comparison, including three surface energy balance residual models (SEBS, TSEB-P and TSEB-S), four Penman-Monteith models (PM-Mu, PM-Yuan, PM-Sun and PM-SW), one Priestly-Taylor model (PT-Fi) and one semi-empirical statiacital model (ST). ET is evaluated using surface climate data from ground measurements as input. Remote sensing data including Ts, LAI and NDVI products from MODIS are used. Estimated ET is validated against 40 Fluxnet measurement sites across North United states and Europe. The sites land cover types include grassland, cropland, evergreen needle leaf forest, evergreen broadleaf forest, deciduous broadleaf forest, mixed forest, shrub land and savannas. Results show that ST model had a balanced performance with relative good precision over all the land cover types. PM-Sun has high R2 and low RMSE and bias over all land cover types. However, it overestimated high value and underestimated low value, mainly due to the overestimation of soil evaporation and underestimation of plant transpiration. The energy budget series models including SEBS, TSEB-P and TSEB-S have a bad performs on the forest land cover. PM-Mu and PM-Yuan underestimated ET obviously, resulting from the underestimation of soil evaporation.

  2. Impact of climate and land cover changes on snow cover in a small Pyrenean catchment

    NASA Astrophysics Data System (ADS)

    Szczypta, C.; Gascoin, S.; Houet, T.; Hagolle, O.; Dejoux, J.-F.; Vigneau, C.; Fanise, P.

    2015-02-01

    The seasonal snow in the Pyrenees Mountains is an essential source of runoff for hydropower production and crop irrigation in Spain and France. The Pyrenees are expected to undergo strong environmental perturbations over the 21st century because of climate change (rising temperatures) and the abandonment of agro-pastoral areas (reforestation). Both changes are happening at similar timescales and are expected to have an impact on snow cover. The effect of climate change on snow in the Pyrenees is well understood, but the effect of land cover changes is much less documented. Here, we analyze the response of snow cover to a combination of climate and land cover change scenarios in a small Pyrenean catchment (Bassiès, 14.5 km2, elevation range 940-2651 m a.s.l.) using a distributed snowpack evolution model. Climate scenarios were constructed from the output of regional climate model projections, whereas land cover scenarios were generated based on past observed changes and an inductive pattern-based model. The model was validated over a snow season using in situ snow depth measurements and high-resolution snow cover maps derived from SPOT (Satellite Pour l'Observation de la Terre - Earth Observation Satellite) satellite images. Model projections indicate that both climate and land cover changes reduce the mean snow depth. However, the impact on the snow cover duration is moderated in reforested areas by the shading effect of trees on the snow surface radiation balance. Most of the significant changes are expected to occur in the transition zone between 1500 m a.s.l. and 2000 m a.s.l. where (i) the projected increase in air temperatures decreases the snow fraction of the precipitation and (ii) the land cover changes are concentrated. However, the consequences on the runoff are limited because most of the meltwater originates from high-elevation areas of the catchment, which are less affected by climate change and reforestation.

  3. Using high-resolution digital aerial imagery to map land cover

    USGS Publications Warehouse

    Dieck, J.J.; Robinson, Larry

    2014-01-01

    The Upper Midwest Environmental Sciences Center (UMESC) has used aerial photography to map land cover/land use on federally owned and managed lands for over 20 years. Until recently, that process used 23- by 23-centimeter (9- by 9-inch) analog aerial photos to classify vegetation along the Upper Mississippi River System, on National Wildlife Refuges, and in National Parks. With digital aerial cameras becoming more common and offering distinct advantages over analog film, UMESC transitioned to an entirely digital mapping process in 2009. Though not without challenges, this method has proven to be much more accurate and efficient when compared to the analog process.

  4. Improved land cover mapping using aerial photographs and satellite images

    NASA Astrophysics Data System (ADS)

    Varga, Katalin; Szabó, Szilárd; Szabó, Gergely; Dévai, György; Tóthmérész, Béla

    2014-10-01

    Manual Land Cover Mapping using aerial photographs provides sufficient level of resolution for detailed vegetation or land cover maps. However, in some cases it is not possible to achieve the desired information over large areas, for example from historical data where the quality and amount of available images is definitely lower than from modern data. The use of automated and semiautomated methods offers the means to identify the vegetation cover using remotely sensed data. In this paper automated methods were tested on aerial photographs and satellite images to extract better and more reliable information about vegetation cover. These testswere performed by using automated analysis of LANDSAT7 images (with and without the surface model of the Shuttle Radar Topography Mission (SRTM)) and two temporally similar aerial photographs. The spectral bands were analyzed with supervised (maximum likelihood) methods. In conclusion, the SRTM and the combination of two temporally similar aerial photographs from earlier years were useful in separating the vegetation cover on a floodplain area. In addition the different date of the vegetation season also gave reliable information about the land cover. High quality information about old and present vegetation on a large area is an essential prerequisites ensuring the conservation of ecosystems

  5. Impact of 300 Years of Land Cover Change on Climate

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

    The Geophysical Fluid Dynamics Laboratory's atmosphere/land/sea ice/mixed layer ocean model is used to investigate the impact of anthropogenic land cover changes estimated to have occurred over the past 300 years. Results of two equilibrium experiments with vegetation cover representing 1990 conditions and "natural" (~1700) conditions are compared. Land cover changes occurred over about 9% of the earth's surface, including large portions of Europe extending into Western Russia, India, Eastern China, and the Eastern United States. Smaller areas of change were in Central America, Northwestern South America, along the Guinea Coast of Africa, in much of Indonesia, and in other isolated spots around the globe. These changes were primarily conversion from native forests to agriculture or grassland. The effects of irrigation or other water management practices were not included in these experiments. The model shows that observed land cover changes have little to no significant impact on globally averaged climatic fields (e.g., 2 m air temperature is 0.008 K warmer in the simulation with 1990 land cover, net radiation at the top of the atmosphere is 0.007 W/m2 lower). Field significance is not achieved in annual mean global representations of most climatic fields: for most variables, about 10% of global area passes a modified Student's t-test at the 90% significance level. Local to some of the altered regions, however, there are statistically significant changes to many climatic fields such as near-surface air temperature, evaporation, and radiative fluxes at the earth's surface. These changes are highly significant in the annual mean and in most months of the year in Eastern Europe, Eastern China, India, the Guinea Coast, and Northwestern South America, and are directly related to the local land surface changes.

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

    NASA Astrophysics Data System (ADS)

    Zabel, F.; Hank, T. B.; Mauser, W.

    2010-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Zabel, F.; Hank, T. B.; Mauser, W.

    2010-07-01

    Regionalization of physical land surface models requires the supply of detailed land cover information. Numerous global and regional land cover maps already exist, but generally they do not resolve arable land into different crop types. However, the characteristic phenological behaviour of different crops affects the mass and energy fluxes on the land surface and thus its hydrology. The objective of this study is the generation of a land cover map for Central Europe based on CORINE Land Cover 2000, merged with CORINE Switzerland, but distinguishing different crop types. Accordingly, an approach was developed, subdividing the land cover class arable land into the regionally most relevant subclasses for Central Europe using statistical data from EUROSTAT. This database was analysed concerning the acreage of different crop types, taking a multiseasonal series of MERIS Normalized Difference Vegetation Index (NDVI) into account. The satellite data were used for the separation of spring and summer crops. The hydrological impact of the improved land cover map was modelled exemplarily for the Upper Danube catchment.

  8. A supervised land cover classification of a western Kenya lowland endemic for human malaria: associations of land cover with larval Anopheles habitats

    PubMed Central

    Mutuku, FM; Bayoh, MN; Hightower, AW; Vulule, JM; Gimnig, JE; Mueke, JM; Amimo, FA; Walker, ED

    2009-01-01

    Background A supervised land cover classification was developed from very high resolution IKONOS satellite data and extensive ground truth sampling of a ca. 10 sq km malaria-endemic lowland in western Kenya. The classification was then applied to an investigation of distribution of larval Anopheles habitats. The hypothesis was that the distribution and abundance of aquatic habitats of larvae of various species of mosquitoes in the genus Anopheles is associated with identifiable landscape features. Results and discussion The classification resulted in 7 distinguishable land cover types, each with a distinguishable vegetation pattern, was highly accurate (89%, Kappa statistic = 0.86), and had a low rate of omission and commission errors. A total of 1,198 habitats and 19,776 Anopheles larvae of 9 species were quantified in samples from a rainy season, and 184 habitats and 582 larvae from a dry season. Anopheles gambiae s.l. was the dominant species complex (51% of total) and A. arabiensis the dominant species. Agricultural land covers (mature maize fields, newly cultivated fields, and pastured grasslands) were positively associated with presence of larval habitats, and were located relatively close to stream channels; whilst nonagricultural land covers (short shrubs, medium shrubs, tall shrubs, and bare soil around residences) were negatively associated with presence of larval habitats and were more distant from stream channels. Number of larval habitats declined exponentially with distance from streams. IKONOS imagery was not useful in direct detection of larval habitats because they were small and turbid (resembling bare soil), but was useful in localization of them through statistical associations with specific land covers. Conclusion A supervised classification of land cover types in rural, lowland, western Kenya revealed a largely human-modified and fragmented landscape consisting of agricultural and domestic land uses. Within it, larval habitats of Anopheles

  9. Strong dependence of CO2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization

    NASA Astrophysics Data System (ADS)

    Goll, Daniel S.; Brovkin, Victor; Liski, Jari; Raddatz, Thomas; Thum, Tea; Todd-Brown, Kathe E. O.

    2015-09-01

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

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

    NASA Technical Reports Server (NTRS)

    Barile, D. D.; Pierce, R.

    1977-01-01

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

  11. Landspotting: collecting essential land cover information via an attractive internet game

    NASA Astrophysics Data System (ADS)

    Fritz, Steffen; McCallum, Ian; Perger, Christoph; Christian, Schill; Florian, Kraxner; Erik, Lindquist; Michael, Obersteiner

    2010-05-01

    Based on the geo-wiki.org concept of collecting land cover information via crowdsourcing, we present a novel approach on how to get the crowd involved. Internet games as well as social networks are becoming increasingly popular and the full potential is yet to be exploited. However, thus far, few if any games provide anything other than entertainment. Can an attractive philanthropic game be created which uses the crowd to collect essential information needed to help to acquire better data to improve the understanding of the earth system? Since accurate and up to date information on global land cover plays a very important role in a number of different research fields such as climate change, monitoring of tropical deforestation, land use monitoring and land-use modelling, but still shows high levels of disagreement, the game will focus on how this essential land cover calibration and validation data can be collected in areas where uncertainty is currently highest. In the current version of the land spotting game, we combine uncertainty hotspot information from three global land cover datasets (GLC, MODIS and GlobCover). With an ever increasing amount of high resolution images available on Google Earth, it is becoming increasingly possible to distinguish land cover features with a high degree of accuracy. We first direct the landspotting game community to certain hotspots of land cover uncertainty and then ask them to enter/record the type of land cover they see (for this they will be able to acquire a certain number of points), possibly uploading pictures at that location (additional points will be received). Even though the development of the game "landspotting.org" is still underway, we illustrate what the functionality will be and what features are envisaged for the near future. Landspotting.org will be designed in such a way as to challenge users to help map out the remaining areas of confusion over the globe - possibly in the form of an adventure game. Users

  12. Land Cover - Nutrient Export Relationships in Space and Time

    EPA Science Inventory

    The relationship between watershed land-cover composition and nutrient export has been well established through several meta-analyses. The meta-analyses reveal that nutrient loads from watersheds dominated by natural vegetation tend to be lower than nutrient loads from watershed...

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  14. Monitoring vegetative land cover and water use using satellite imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetative land cover and water use are the key indicators required by the Global Bioenergy Partnership (GBEP) for promoting the production and use of modern bioenergy, particularly in the developing world. Since the statistical data and field observations are limited in the developing countries, re...

  15. OVERVIEW OF US NATIONAL LAND-COVER MAPPING PROGRAM

    EPA Science Inventory

    Because of escalating costs amid growing needs for large-scale, satellite-based landscape information, a group of US federal agencies agreed to pool resources and operate as a consortium to acquire the necessary data land-cover mapping of the nation . The consortium was initiated...

  16. APPLICATION OF LAND-COVER DATA FOR ENVIRONMENTAL ASSESSMENTS

    EPA Science Inventory

    In many parts of the United States, urbanization is a pervasive dynamic that has many environmental consequences. Land-cover and related (e.g. Landsat) data are fundamental for studying urbanization itself and its environmental effects.

    Well established models in economic...

  17. GREAT LAKES BASIN LAND-COVER DATA: ISSUES AND OPPORTUNITIES

    EPA Science Inventory

    The US Environmental Protection Agency (EPA) is developing a consistent land-cover (LC) data set for the entire 480,000 km2 Great Lakes Basin (GLB). The acquisition of consistent LC data has proven difficult both within the US and across GLB political boundaries due to disparate...

  18. ASSESSING ACCURACY OF NET CHANGE DERIVED FROM LAND COVER MAPS

    EPA Science Inventory

    Net change derived from land-cover maps provides important descriptive information for environmental monitoring and is often used as an input or explanatory variable in environmental models. The sampling design and analysis for assessing net change accuracy differ from traditio...

  19. Denitrification in Headwater Wetlands with Varying Surrounding Land Cover Types

    EPA Science Inventory

    Wetlands are recognized for their significant role in providing a range of ecosystem services. In light of this, research is currently being performed to characterize how forcing functions (e.g., climate change and land cover change) affect the provision of ecosystem services by ...

  20. Upper Kalamazoo watershed land cover inventory. [based on remote sensing

    NASA Technical Reports Server (NTRS)

    Richason, B., III; Enslin, W.

    1973-01-01

    Approximately 1000 square miles of the eastern portion of the watershed were inventoried based on remote sensing imagery. The classification scheme, imagery and interpretation procedures, and a cost analysis are discussed. The distributions of land cover within the area are tabulated.

  1. Use of manual densitometry in land cover classification

    NASA Technical Reports Server (NTRS)

    Jordan, D. C.; Graves, D. H.; Hammetter, M. C.

    1978-01-01

    Through use of manual spot densitometry values derived from multitemporal 1:24,000 color infrared aircraft photography, areas as small as one hectare in the Cumberland Plateau in Kentucky were accurately classified into one of eight ground cover groups. If distinguishing between undisturbed and disturbed forest areas is the sole criterion of interest, classification results are highly accurate if based on imagery taken during foliated ground cover conditions. Multiseasonal imagery analysis was superior to single data analysis, and transparencies from prefoliated conditions gave better separation of conifers and hardwoods than did those from foliated conditions.

  2. Accuracy assessment of land cover/land use classifiers in dry and humid areas of Iran.

    PubMed

    Yousefi, Saleh; Khatami, Reza; Mountrakis, Giorgos; Mirzaee, Somayeh; Pourghasemi, Hamid Reza; Tazeh, Mehdi

    2015-10-01

    Land cover/land use (LCLU) maps are essential inputs for environmental analysis. Remote sensing provides an opportunity to construct LCLU maps of large geographic areas in a timely fashion. Knowing the most accurate classification method to produce LCLU maps based on site characteristics is necessary for the environment managers. The aim of this research is to examine the performance of various classification algorithms for LCLU mapping in dry and humid climates (from June to August). Testing is performed in three case studies from each of the two climates in Iran. The reference dataset of each image was randomly selected from the entire images and was randomly divided into training and validation set. Training sets included 400 pixels, and validation sets included 200 pixels of each LCLU. Results indicate that the support vector machine (SVM) and neural network methods can achieve higher overall accuracy (86.7 and 86.6%) than other examined algorithms, with a slight advantage for the SVM. Dry areas exhibit higher classification difficulty as man-made features often have overlapping spectral responses to soil. A further observation is that spatial segregation and lower mixture of LCLU classes can increase classification overall accuracy. PMID:26403704

  3. Multi-Temporal Remote Sensing Data for Modeling of Dryland Evapotranspiration and Land Cover Change

    NASA Astrophysics Data System (ADS)

    Petrakis, R.; Hartfield, K. A.; Barrera, P.; Van Leeuwen, W. J. D.; Papuga, S. A.; Scott, C. A.

    2014-12-01

    Water security is an increasing concern around the globe. The goal of this research is to better understand the complex relationships which exist between land cover change and water use within a dryland ecosystem. The Santa Cruz watershed in southeastern Arizona is experiencing increasing population growth and reduced water resources, highlighting a direct relationship between land cover change and water use. Using multi-source and multi-scale data sets including multispectral imagery, thermal imagery, and climate variables, we present the following three-step research approach: 1) land cover change, 2) evapotranspiration modeling, and 3) data validation. Assessment of land cover change between 2003 and 2013 was performed using Landsat data and validated via high resolution imagery. Regional evapotranspiration was calculated using the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) model. Validation of the METRIC model was performed using measurements from multiple flux towers within the watershed. With the capability to observe historical changes as well as current events, this approach integrates multiple public data sources representing varying scales to accurately monitor and assess environmental change. Overall, this approach demonstrates how remote sensing capabilities combined with surface measurements can be utilized to ascertain and validate complex ecosystem relationships. Preliminary results suggest that land cover change alters the amount of evapotranspiration within the Santa Cruz watershed. We also show that METRIC performed better in agricultural areas compared to naturally vegetated shrubland areas. Finally, this research will be used as a prototype to evaluate other dryland regions of the Americas.

  4. Evaluating the need for integrated land use and land cover analysis for robust assessment of climate adaptation and mitigation strategies

    NASA Astrophysics Data System (ADS)

    Di Vittorio, Alan; Mao, Jiafu; Shi, Xiaoying

    2016-04-01

    Several climate adaptation and mitigation strategies incorporate land use and land cover change to address global carbon balance and also food, fuel, fiber, and water resource sustainability. However, Land Use and Land Cover Change (LULCC) are not consistent across the CMIP5 model simulations because only the land use input was harmonized. Differences in LULCC impede understanding of global change because such differences can dramatically alter land-atmosphere mass and energy exchange in response to differences in associated use and distribution of land resources. For example, the Community Earth System Model (CESM) overestimates 2005 atmospheric CO2 concentration by 18 ppmv, and we explore the contribution of historical LULCC to this bias in relation to the effects of CO2 fertilization and nitrogen deposition on terrestrial carbon. Using identical land use input, a chronologically referenced LULCC that accounts for pasture, as opposed to the default year-2000 referenced LULCC, increases this bias to 27 ppmv because more forest needs to be cleared for land use. Assuming maximum forest retention for all land conversion reduces the new bias to ~21 ppmv, while minimum forest retention increases the new bias to ~32 ppmv. Corresponding ecosystem carbon changes from the default in 2005 are approximately -28 PgC, -10 PgC, and -43 PgC, respectively. This 33 PgC uncertainty range due to maximizing versus minimizing forest area is 66% of the estimated 50 PgC gain in ecosystem carbon due to CO2 fertilization from 1850-2005, and 150% of the estimated 22 PgC gain due to nitrogen deposition. This range is also similar to the 28 PgC difference generated by changing the LULCC reference year and accounting for pasture. These results indicate that LULCC uncertainty is not only a major driver of bias in simulated atmospheric CO2, but that it could contribute even more to this bias than uncertainty in CO2 fertilization or nitrogen deposition. This highlights the need for more accurate

  5. Assessing hydrologic prediction uncertainty resulting from soft land cover classification

    NASA Astrophysics Data System (ADS)

    Loosvelt, Lien; De Baets, Bernard; Pauwels, Valentijn R. N.; Verhoest, Niko E. C.

    2014-09-01

    For predictions in ungauged basins (PUB), environmental data is generally not available and needs to be inferred by indirect means. Existing technologies such as remote sensing are valuable tools for estimating the lacking data, as these technologies become more widely available and have a high areal coverage. However, indirect estimates of the environmental characteristics are prone to uncertainty. Hence, an improved understanding of the quality of the estimates and the development of methods for dealing with their associated uncertainty are essential to evolve towards accurate PUB. In this study, the impact of the uncertainty associated with the classification of land cover based on multi-temporal SPOT imagery, resulting from the use of the Random Forests classifier, on the predictions of the hydrologic model TOPLATS is investigated through a Monte Carlo simulation. The results show that the predictions of evapotranspiration, runoff and baseflow are hardly affected by the classification uncertainty when area-averaged predictions are intended, implying that uncertainty propagation is only advisable in case a spatial distribution of the predictions is relevant for decision making or is coupled to other spatially distributed models. Based on the resulting uncertainty map, guidelines for additional data collection are formulated in order to reduce the uncertainty for future model applications. Because a Monte Carlo-based uncertainty analysis is computationally very demanding, especially when complex models are involved, we developed a fast indicative uncertainty assessment method that allows for generating proxies of the Monte Carlo-based result in terms of the mean prediction and its associated uncertainty based on a single model evaluation. These proxies are shown to perform well and provide a good indication of the impact of classification uncertainty on the prediction result.

  6. A Multi-Index Integrated Change Detection Method for Updating the National Land Cover Database

    NASA Astrophysics Data System (ADS)

    Jin, S.; Yang, L.; Xian, G. Z.; Danielson, P.; Homer, C.

    2010-12-01

    Land cover change is typically captured by comparing two or more dates of imagery and associating spectral change with true thematic change. A new change detection method, Multi-Index Integrated Change (MIIC), has been developed to capture a full range of land cover disturbance patterns for updating the National Land Cover Database (NLCD). Specific indices typically specialize in identifying only certain types of disturbances; for example, the Normalized Burn Ratio (NBR) has been widely used for monitoring fire disturbance. Recognizing the potential complementary nature of multiple indices, we integrated four indices into one model to more accurately detect true change between two NLCD time periods. The four indices are NBR, Normalized Difference Vegetation Index (NDVI), Change Vector (CV), and a newly developed index called the Relative Change Vector (RCV). The model is designed to provide both change location and change direction (e.g. biomass increase or biomass decrease). The integrated change model has been tested on five image pairs from different regions exhibiting a variety of disturbance types. Compared with a simple change vector method, MIIC can better capture the desired change without introducing additional commission errors. The model is particularly accurate at detecting forest disturbances, such as forest harvest, forest fire, and forest regeneration. Agreement between the initial change map areas derived from MIIC and the retained final land cover type change areas will be showcased from the pilot test sites.

  7. A Multi-Index Integrated Change detection method for updating the National Land Cover Database

    USGS Publications Warehouse

    Jin, Suming; Yang, Limin; Xian, George Z.; Danielson, Patrick; Homer, Collin

    2010-01-01

    Land cover change is typically captured by comparing two or more dates of imagery and associating spectral change with true thematic change. A new change detection method, Multi-Index Integrated Change (MIIC), has been developed to capture a full range of land cover disturbance patterns for updating the National Land Cover Database (NLCD). Specific indices typically specialize in identifying only certain types of disturbances; for example, the Normalized Burn Ratio (NBR) has been widely used for monitoring fire disturbance. Recognizing the potential complementary nature of multiple indices, we integrated four indices into one model to more accurately detect true change between two NLCD time periods. The four indices are NBR, Normalized Difference Vegetation Index (NDVI), Change Vector (CV), and a newly developed index called the Relative Change Vector (RCV). The model is designed to provide both change location and change direction (e.g. biomass increase or biomass decrease). The integrated change model has been tested on five image pairs from different regions exhibiting a variety of disturbance types. Compared with a simple change vector method, MIIC can better capture the desired change without introducing additional commission errors. The model is particularly accurate at detecting forest disturbances, such as forest harvest, forest fire, and forest regeneration. Agreement between the initial change map areas derived from MIIC and the retained final land cover type change areas will be showcased from the pilot test sites.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    1993-05-01

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

  11. Sample design for estimating change in land use and land cover ( Pennsylvania).

    USGS Publications Warehouse

    Rosenfield, G.H.

    1982-01-01

    The methodology of sample design which is applied to estimating change in land use and land cover is general and extendable to determination of change in any type of thematic mapping that is time variant. Land-use maps of the State of Pennsylvania at a scale of 1:250,000 were compiled circa 1958 with land use classified into six categories. The more detailed land-use and land-cover mapping of the State of Pennsylvania at a scale of 1:250,000 was completed by the U.S. Geological Survey circa 1977. With some rearrangement of these categories, the recent maps are very nearly compatible with a combination of five categories of the earlier maps. -from Author

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

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

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

  13. Assessing Landslide Risk Areas Using Statistical Models and Land Cover

    NASA Astrophysics Data System (ADS)

    Kim, H. G.; Lee, D. K.; Park, C.; Ahn, Y.; Sung, S.; Park, J. H.

    2015-12-01

    Recently, damages due to landslides have increased in Republic of Korea. Extreme weathers like typhoon, heavy rainfall related to climate change are the main factor of the damages. Especially, Inje-gun, Gangwon-do had severe landslide damages in 2006 and 2007. In Inje-gun, 91% areas are forest, therefore, many land covers related to human activities were adjacent to forest land. Thus, establishment of adaptation plans to landslides was urgently needed. Landslide risk assessment can serve as a good information to policy makers. The objective of this study was assessing landslide risk areas to support establishment of adaptation plans to reduce landslide damages. Statistical distribution models (SDMs) were used to evaluate probability of landslide occurrence. Various SDMs were used to make landslide probability maps considering uncertainty of SDMs. The types of land cover were classified into 5 grades considering vulnerable level to landslide. The landslide probability maps were overlaid with land cover map to calculate landslide risk. As a result of overlay analysis, landslide risk areas were derived. Especially agricultural areas and transportation areas showed high risk and large areas in the risk map. In conclusion, policy makers in Inje-gun must consider the landslide risk map to establish adaptation plans effectively.

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

    EPA Science Inventory

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

  15. LAND USE/LAND COVER , NEUSE RIVER WATERSHED, NC (RASTER VERSION)

    EPA Science Inventory

    EOSAT and the North Carolina State University Computer Graphics Center, in cooperation with the NC Center for Geographic Infor- mation and Analysis, developed the Land Use/Land Cover digital data to enhance planning, siting and impact analysis in the Albemarle-Pamlico Estuarine S...

  16. A selected bibliography: Remote sensing applications in land-use and land-cover inventory tasks

    USGS Publications Warehouse

    Todd, William J.

    1978-01-01

    The bibliography contains more than 300 citations of selected publications on the application of remote-sensing techniques to regional and metropolitan land-use and land-cover inventroy and analysis tasks.  Most of the citations were published between January 1968 and June 1977, although some earlier works of continuing interest are included.

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

    EPA Science Inventory

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  19. Land-cover classes to characterize watersheds in North Carolina

    USGS Publications Warehouse

    Terziotti, Silvia; Eimers, Jo Leslie

    2001-01-01

    This web site contains the Federal Geographic Data Committee-compliant metadata (documentation) for digital data produced for the North Carolina, Department of Environment and Natural Resources, Public Water Supply Section, Source Water Assessment Program. The metadata are for 11 individual Geographic Information System data sets. An overlay and indexing method was used with the data to derive a rating for unsaturated zone and watershed characteristics for use by the State of North Carolina in assessing more than 11,000 public water-supply wells and approximately 245 public surface-water intakes for susceptibility to contamination. For ground-water supplies, the digital data sets used in the assessment included unsaturated zone rating, vertical series hydraulic conductance, land-surface slope, and land cover. For assessment of public surface-water intakes, the data sets included watershed characteristics rating, average annual precipitation, land-surface slope, land cover, and ground-water contribution. Documentation for the land-use data set applies to both the unsaturated zone and watershed characteristics ratings. Documentation for the estimated depth-to-water map used in the calculation of the vertical series hydraulic conductance also is included.

  20. An Integrated Land Use - Land Cover Change Model for the Southern Africa Region

    NASA Astrophysics Data System (ADS)

    Desanker, P. V.

    2001-12-01

    A land use change model covering the Miombo region of Southern Africa region is presented. The model includes a structure that recognizes the scales at which land use change decisions are made in the region, namely the traditional authority for subsistence agricultural land use, and includes social-economic and biophysical constraints to land use at multiple levels. Land cover information for the 1990's based on maps derived from Landsat Thematic Mapper data are used to initiative the model. The model, called MELT, can be used to examine impacts of land use change on carbon pools, emissions from land use change (slash and burn agriculture or as a result of soil carbon changes), and spatial patterning of land cover. MELT provides a suitable representation of the process of land use in this region, and will be essential in providing the correct context for observed fire and emissions across the region of the SAFARI 2000 initiative. MELT is implemented using an object-oriented approach, and allows easy linkage with impacts models.

  1. Ground surface temperature simulation for different land covers

    NASA Astrophysics Data System (ADS)

    Herb, William R.; Janke, Ben; Mohseni, Omid; Stefan, Heinz G.

    2008-07-01

    SummaryA model for predicting temperature time series for dry and wet land surfaces is described, as part of a larger project to assess the impact of urban development on the temperature of surface runoff and coldwater streams. Surface heat transfer processes on impervious and pervious land surfaces were investigated for both dry and wet weather periods. The surface heat transfer equations were combined with a numerical approximation of the 1-D unsteady heat diffusion equation to calculate pavement and soil temperature profiles to a depth of 10 m. Equations to predict the magnitude of the radiative, convective, conductive and evaporative heat fluxes at a dry or wet surface, using standard climate data as input, were developed. A model for the effect of plant canopies on surface heat transfer was included for vegetated land surfaces. Given suitable climate data, the model can simulate the land surface and sub-surface temperatures continuously throughout a six month time period or for a single rainfall event. Land surface temperatures have been successfully simulated for pavements, bare soil, short and tall grass, a forest, and two agricultural crops (corn and soybeans). The simulations were run for three different locations in US, and different years as imposed by the availability of measured soil temperature and climate data. To clarify the effect of land use on surface temperatures, the calibrated coefficients for each land use and the same soil coefficients were used to simulate surface temperatures for a six year climate data set from Albertville, MN. Asphalt and concrete give the highest surface temperatures, as expected, while vegetated surfaces gave the lowest. Bare soil gives surface temperatures that lie between those for pavements and plant-covered surfaces. The soil temperature model predicts hourly surface temperatures of bare soil and pavement with root-mean-square errors (RMSEs) of 1-2 °C, and hourly surface temperatures of vegetation-covered surfaces

  2. Global land cover products tailored to the needs of the climate modeling community - Land Cover project of the ESA Climate Change Initiative

    NASA Astrophysics Data System (ADS)

    Bontemps, S.; Defourny, P.; Radoux, J.; Kalogirou, V.; Arino, O.

    2012-04-01

    Improving the systematic observation of land cover, as an Essential Climate Variable, will support the United Framework Convention on Climate Change effort to reduce the uncertainties in our understanding of the climate system and to better cope with climate change. The Land Cover project of the ESA Climate Change Initiative aims at contributing to this effort by providing new global land cover products tailored to the expectations of the climate modeling community. During the first three months of the project, consultation mechanisms were established with this community to identify its specific requirements in terms of satellite-based global land cover products. This assessment highlighted specific needs in terms of land cover characterization, accuracy of products, as well as stability and consistency, needs that are currently not met or even addressed. Based on this outcome, the project revisits the current land cover representation and mapping approaches. First, the stable and dynamic components of land cover are distinguished. The stable component refers to the set of land surface features that remains stable over time and thus defines the land cover independently of any sources of temporary or natural variability. Conversely, the dynamic component is directly related to this temporary or natural variability that can induce some variation in land observation over time but without changing the land cover state in its essence (e.g. flood, snow on forest, etc.). Second, the project focuses on the possibility to generate such stable global land cover maps. Previous projects, like GlobCover and MODIS Land Cover, have indeed shown that products' stability is a key issue. In delivering successive global products derived from the same sensor, they highlighted the existence of spurious year-to-year variability in land cover labels, which were not associated with land cover change but with phenology, disturbances or landscape heterogeneity. An innovative land cover

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

    PubMed

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

    2012-05-01

    In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas. PMID:22419398

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

    NASA Astrophysics Data System (ADS)

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

    2012-05-01

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

  5. A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data.

    PubMed

    Qadri, Salman; Khan, Dost Muhammad; Ahmad, Farooq; Qadri, Syed Furqan; Babar, Masroor Ellahi; Shahid, Muhammad; Ul-Rehman, Muzammil; Razzaq, Abdul; Shah Muhammad, Syed; Fahad, Muhammad; Ahmad, Sarfraz; Pervez, Muhammad Tariq; Naveed, Nasir; Aslam, Naeem; Jamil, Mutiullah; Rehmani, Ejaz Ahmad; Ahmad, Nazir; Akhtar Khan, Naeem

    2016-01-01

    The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared) while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI). Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class). By implementing a cross validation method (80-20), we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively. PMID:27376088

  6. A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data

    PubMed Central

    Qadri, Salman; Khan, Dost Muhammad; Ahmad, Farooq; Qadri, Syed Furqan; Babar, Masroor Ellahi; Shahid, Muhammad; Ul-Rehman, Muzammil; Razzaq, Abdul; Shah Muhammad, Syed; Fahad, Muhammad; Ahmad, Sarfraz; Pervez, Muhammad Tariq; Naveed, Nasir; Aslam, Naeem; Jamil, Mutiullah; Rehmani, Ejaz Ahmad; Ahmad, Nazir; Akhtar Khan, Naeem

    2016-01-01

    The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared) while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI). Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class). By implementing a cross validation method (80-20), we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively. PMID:27376088

  7. Land Covering Classifications of Boreas Modeling Grid Using AIRSAR Images

    NASA Technical Reports Server (NTRS)

    Saatchi, Sasan S.; Rignot, Eric

    1996-01-01

    Mapping forest types in the boreal ecosystem in an integrated part of any modeling excercise of biogeophysical processes characterizing the interaction of forest with the atmosphere. In this paper, we report the results of the land cover classification of the SAR data acquired during the BOREAS (BOReal Ecosystem Atmospheric Study) intensive field campaigns over the modeling sub-grid of the southern study area in Saskatchewan , Canada. A Bayesian-maximum-a-posteriori classifier has been applied on the NASA/JPL AIRSAR images covering the region during the peak of the growing season in July, 1994.

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

    USGS Publications Warehouse

    Sharpe, Jennifer B.; Soong, David T.

    2015-01-01

    This study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.

  9. Land Use and Land Cover Classification from ETM Sensor Data : A Case Study from Tamakoshi River Basin of Nepal

    NASA Astrophysics Data System (ADS)

    Shrestha, U. S.

    2014-11-01

    The mountain watershed of Nepal is highly rugged, inaccessible and difficult for acquiring field data. The application of ETM sensor Data Sat satellite image of 30 meter pixel resolutions has been used for land use and land cover classification of Tamakoshi River Basin (TRB) of Nepal. The paper tries to examine the strength of image classification methods in derivation of land use and land classification. Supervised digital image classification techniques was used for examination the thematic classification. Field verification, Google earth image, aerial photographs, topographical sheet and GPS locations were used for land use and land cover type classification, selecting training samples and assessing accuracy of classification results. Six major land use and land cover types: forest land, water bodies, bush/grass land, barren land, snow land and agricultural land was extracted using the method. Moreover, there is spatial variation of statistics of classified land uses and land cover types depending upon the classification methods. The image data revealed that the major portion of the surface area is covered by unclassified bush and grass land covering 34.62 per cent followed by barren land (28 per cent). The knowledge derived from supervised classification was applied for the study. The result based on the field survey of the area during July 2014 also verifies the same result. So image classification is found more reliable in land use and land cover classification of mountain watershed of Nepal.

  10. Time series change detection: Algorithms for land cover change

    NASA Astrophysics Data System (ADS)

    Boriah, Shyam

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

  11. The Geographic Variability of Contemporary United States Land Cover Change

    NASA Astrophysics Data System (ADS)

    Loveland, T. R.

    2004-12-01

    The U.S. Geological Survey, in cooperation with NASA and the U.S. Environmental Protection Agency, is conducing a study to document the rates, causes, and consequences of 1973 to 2000 land cover change for the eighty-four ecoregions of the conterminous United States. Estimates of change are based on the interpretation of five dates of Landsat MSS and TM data (nominally 1973, 1980, 1986, 1992, and 2000). Results from an analysis of the first twenty-five ecoregions indicate that the rates, causes, and consequences of change are relative consistent within ecoregions but there are significant differences in the rates of change and types of dominant land use and land cover conversions occurring between ecoregions. For example, high rates of cyclic change are found in ecoregions dominated by resource-based economies while lower but unidirectional change is more common in more urbanized ecoregions. The specific character of change in each ecoregion is shaped by the resource potential of each ecoregion and the historical settlement patterns. Land uses changes that determine changes in cover in a given ecoregion are typically based on the highest economic use enabled by the physical environment (i.e., climate, soils, geology, landforms, etc.) and the comparative advantages associate with resource, location, and history. The differences in rates of change combined with the prevailing land use practices and enduring environmental character of different regions have a significant impact on issues such as carbon dynamics. An assessment of the ecoregion carbon dynamics also shows significant differences in flux rates over time. Overall, the results of this study show that the fabric of change across the conterminous United States highly variable in time and space and understanding the geographic dimensions of change. This suggests that ecoregions offer a framework for projecting rates, types, and the subsequent consequences of change.

  12. The Change of Land Cover/Land Use in Ejina Oasis over 20 Years

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoyou; Men, Tongtong; Zhou, Maoxian

    Land use and land cover change have been of great concern in global change research in recent years. Base on comparison with the remote sensing data in1982 and 2000 and field investigation, the results of land cover and land use change were obtained by the method of landscape analysis. Ten types of land use were identified: riparian woods, riparian shrubbery, desert shrubbery, desert grassland, river-way and water area, salinised land, town, Gobi, shift sand dune, denudative upland. The results show that, (1) there were obvious Changes in land cover structure. The area of riparian woods decreased 0.97% and the number of patch decrease 376; The area of riparian shrubbery increased 0.92% and the number of patch decreased 1316. Meanwhile, the index of %LAND of desert shrubbery increased from 4.49% to 5.65%; patch of river-way and water area decreased from 40 to 6. The index of % dune increased 0.42%. (2) the area of riparian woods dominated by Populus euphratica and desert grassland decreased to 45.02% and 14.55%. However, the areas of riparian shrubbery dominated by Tamarix SPP and desert shrubbery increase to 35.03% and 25.88%. The transition probability is shrubbery and desert grassland. The succession trend of ecosystem was obtained: riparian woods riparian shrubbery and grassland desert grassland. Meanwhile, the succession velocity becomes higher and higher.

  13. Using an Ecoregion Framework to Analyze Land-Cover and Land-Use Dynamics

    NASA Astrophysics Data System (ADS)

    Gallant, Alisa L.; Loveland, Thomas R.; Sohl, Terry L.; Napton, Darrell E.

    2004-04-01

    The United States has a highly varied landscape because of wide-ranging differences in combinations of climatic, geologic, edaphic, hydrologic, vegetative, and human management (land use) factors. Land uses are dynamic, with the types and rates of change dependent on a host of variables, including land accessibility, economic considerations, and the internal increase and movement of the human population. There is a convergence of evidence that ecoregions are very useful for organizing, interpreting, and reporting information about land-use dynamics. Ecoregion boundaries correspond well with patterns of land cover, urban settlement, agricultural variables, and resource-based industries. We implemented an ecoregion framework to document trends in contemporary land-cover and land-use dynamics over the conterminous United States from 1973 to 2000. Examples of results from six eastern ecoregions show that the relative abundance, grain of pattern, and human alteration of land-cover types organize well by ecoregion and that these characteristics of change, themselves, change through time.

  14. EL68D Wasteway Watershed Land-Cover Generation

    USGS Publications Warehouse

    Ruhl, Sheila; Usery, E. Lynn; Finn, Michael P.

    2007-01-01

    Classification of land cover from Landsat Enhanced Thematic Mapper Plus (ETM+) for the EL68D Wasteway Watershed in the State of Washington is documented. The procedures for classification include use of two ETM+ scenes in a simultaneous unsupervised classification process supported by extensive field data collection using Global Positioning System receivers and digital photos. The procedure resulted in a detailed classification at the individual crop species level.

  15. Land Cover and Rainfall Interact to Shape Waterbird Community Composition

    PubMed Central

    Studds, Colin E.; DeLuca, William V.; Baker, Matthew E.; King, Ryan S.; Marra, Peter P.

    2012-01-01

    Human land cover can degrade estuaries directly through habitat loss and fragmentation or indirectly through nutrient inputs that reduce water quality. Strong precipitation events are occurring more frequently, causing greater hydrological connectivity between watersheds and estuaries. Nutrient enrichment and dissolved oxygen depletion that occur following these events are known to limit populations of benthic macroinvertebrates and commercially harvested species, but the consequences for top consumers such as birds remain largely unknown. We used non-metric multidimensional scaling (MDS) and structural equation modeling (SEM) to understand how land cover and annual variation in rainfall interact to shape waterbird community composition in Chesapeake Bay, USA. The MDS ordination indicated that urban subestuaries shifted from a mixed generalist-specialist community in 2002, a year of severe drought, to generalist-dominated community in 2003, of year of high rainfall. The SEM revealed that this change was concurrent with a sixfold increase in nitrate-N concentration in subestuaries. In the drought year of 2002, waterbird community composition depended only on the direct effect of urban development in watersheds. In the wet year of 2003, community composition depended both on this direct effect and on indirect effects associated with high nitrate-N inputs to northern parts of the Bay, particularly in urban subestuaries. Our findings suggest that increased runoff during periods of high rainfall can depress water quality enough to alter the composition of estuarine waterbird communities, and that this effect is compounded in subestuaries dominated by urban development. Estuarine restoration programs often chart progress by monitoring stressors and indicators, but rarely assess multivariate relationships among them. Estuarine management planning could be improved by tracking the structure of relationships among land cover, water quality, and waterbirds. Unraveling these

  16. Estimates of Historical Global Sources and Sinks of Carbon from Land Cover and Land Use Changes

    NASA Astrophysics Data System (ADS)

    Richardson, T. K.; Yang, X.; Jain, A. K.

    2009-12-01

    A geographically explicit terrestrial carbon and nitrogen cycle component of the Integrated Science Assessment Model (ISAM) is used to examine the response of plant and soil carbon stocks to historical land cover and land use changes (LCLUCs). The ISAM model is forced with three different LCLUC datasets for cropland and pastureland coupled with observed atmospheric CO2, temperature, precipitation data and estimated changes in N deposition. The model also considers wood harvesting on primary and secondary forests. The objective of this study is to evaluate uncertainties in the land use emissions by forcing a single terrestrial model with three different LCLUC datasets. This approach allows us to isolate the LCLUC data related uncertainties from the model related uncertainties in the terrestrial carbon fluxes. The evaluation of three alternative data sets for historical changes in LCLUC is important because the flux associated with land cover change is responsible for substantial uncertainty in net land-atmosphere flux for the recent decades.

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

    NASA Technical Reports Server (NTRS)

    Walker, Robert

    2004-01-01

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

  18. Continental land cover classification using meteorological satellite data

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

  19. Evaluation of space SAR as a land-cover classification

    NASA Technical Reports Server (NTRS)

    Brisco, B.; Ulaby, F. T.; Williams, T. H. L.

    1985-01-01

    The multidimensional approach to the mapping of land cover, crops, and forests is reported. Dimensionality is achieved by using data from sensors such as LANDSAT to augment Seasat and Shuttle Image Radar (SIR) data, using different image features such as tone and texture, and acquiring multidate data. Seasat, Shuttle Imaging Radar (SIR-A), and LANDSAT data are used both individually and in combination to map land cover in Oklahoma. The results indicates that radar is the best single sensor (72% accuracy) and produces the best sensor combination (97.5% accuracy) for discriminating among five land cover categories. Multidate Seasat data and a single data of LANDSAT coverage are then used in a crop classification study of western Kansas. The highest accuracy for a single channel is achieved using a Seasat scene, which produces a classification accuracy of 67%. Classification accuracy increases to approximately 75% when either a multidate Seasat combination or LANDSAT data in a multisensor combination is used. The tonal and textural elements of SIR-A data are then used both alone and in combination to classify forests into five categories.

  20. Characterization and classification of South American land cover types using satellite data

    NASA Technical Reports Server (NTRS)

    Townshend, J. R. G.; Justice, C. O.; Kalb, V.

    1987-01-01

    Various methods are compared for carrying out land cover classifications of South America using multitemporal Advanced Very High Resolution Radiometer data. Fifty-two images of the normalized difference vegetation index (NDVI) from a 1-year period are used to generate multitemporal data sets. Three main approaches to land cover classification are considered, namely the use of the principal components transformed images, the use of a characteristic curves procedure based on NDVI values plotted against time, and finally application of the maximum likelihood rule to multitemporal data sets. Comparison of results from training sites indicates that the last approach yields the most accurate results. Despite the reliance on training site figures for performance assessment, the results are nevertheless extremely encouraging, with accuracies for several cover types exceeding 90 per cent.

  1. Land-atmosphere coupling associated with snow cover

    NASA Astrophysics Data System (ADS)

    Dutra, Emanuel; Schär, Christoph; Viterbo, Pedro; Miranda, Pedro M. A.

    2011-08-01

    This study investigates the role of interannual snow cover variability in controlling the land-atmosphere coupling and its relation with near surface (T2M) and soil temperature (STL1). Global atmospheric simulations are carried out with the EC-EARTH climate model using climatological sea surface temperature and sea ice distributions. Snow climatology, derived from a control run (COUP), is used to replace snow evolution in the snow-uncoupled simulation (UNCOUP). The snow cover and depth variability explains almost 60% of the winter T2M variability in predominantly snow-covered regions. During spring the differences in interannual variability of T2M are more restricted to the snow line regions. The variability of soil temperature is also damped in UNCOUP. However, there are regions with a pronounced signal in STL1 with no counterpart in T2M. These regions are characterized by a significant interannual variability in snow depth, rather than snow cover (almost fully snow covered during winter). These results highlight the importance of both snow cover and snow depth in decoupling the soil temperature evolution from the overlying atmosphere.

  2. Estimation of Croplands in West Africa using Global Land Cover and Land Use Datasets: Preliminary Results

    NASA Astrophysics Data System (ADS)

    Adhikari, P.; de Beurs, K.

    2013-12-01

    Africa is vulnerable to the effects of global climate change resulting in reduced agricultural production and worsening food security. Studies show that Africa has the lowest cereal yield compared to other regions of the world. The situation is particularly dire in East, Central and West Africa. Despite their low cereal yield, the population of East, Central and West Africa has doubled between 1980 and 2007. Furthermore, West Africa has a history of severe and long droughts which have occasionally caused widespread famine. To understand how global climate change and land cover change have impacted crop production (yield) it is important to estimate croplands in the region. The objective of this study is to compare ten publicly available land cover and land use datasets, covering different time periods, to estimate croplands in West Africa. The land cover and land use data sets used cover the period from early 1990s to 2010. Preliminary results show a high variability in cropland estimates. For example, in Benin, the estimated cropland area varies from 2.5 to 21% of the total area, while it varies from 3 to 8% in Niger. Datasets with a finer resolution (≤ 1,000 m) have consistently estimated comparable cropland areas across all countries. Several categorical verification statistics such as probability of detection (POD), false alarm ratio (FAR) and critical success index are also used to analyze the correspondence between estimated and observed cropland pixels at the scales of 1 Km and 10 Km.

  3. Completion of the 2006 National Land Cover Database Update for the Conterminous United States

    EPA Science Inventory

    Under the organization of the Multi-Resolution Land Characteristics (MRLC) Consortium, the National Land Cover Database (NLCD) has been updated to characterize both land cover and land cover change from 2001 to 2006. An updated version of NLCD 2001 (Version 2.0) is also provided....

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

    EPA Science Inventory


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

  5. Impact of land use and land cover changes on ecosystem services in Menglun, Xishuangbanna, Southwest China.

    PubMed

    Hu, Huabin; Liu, Wenjun; Cao, Min

    2008-11-01

    Changing the landscape has serious environmental impacts affecting the ecosystem services, particularly in the tropics. In this paper, we report changes in ecosystem services in relation to land use and land cover over an 18-year period (1988--2006) in the Menglun Township, Xishuangbanna, Southwest China. We used Landsat TM/ETM and Quickbird data sets to estimate changes in ten land use and land cover categories, and generalized value coefficients to estimate changes in the ecosystem services provided by each land category. The results showed that over the 18-year period, the land use and land cover in the study area experienced significant changes. Rubber plantations increased from 12.10% of total land cover to 45.63%, while forested area and swidden field decreased from 48.73 and 13.14 to 27.57 and 0.46%, respectively. During this period, the estimated value of ecosystem services dropped by US $11.427 million (approximately 27.73%). Further analysis showed that there were significant changes in ecological functions such as nutrient cycling, erosion control, climate regulation and water treatment as well as recreation; the obvious increase in the ecological function is provision of raw material (natural rubber). Our findings conclude that an abrupt shift in land use from ecologically important tropical forests and traditionally managed swidden fields to large-scale rubber plantations result in a great loss of ecosystem services in this area. Further, the study suggests that provision of alternative economic opportunities would help in maintaining ecosystem services and for an appropriate compensation mechanisms need to be established based on rigorous valuation. PMID:18157650

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

    PubMed

    Palacio-Aponte, Gerardo

    2014-09-01

    Environmental changes due to natural processes and anthropic modifications can be characterized by the degree of land cover modification and its environmental implications over time. The main goal of the present study was to propose and apply a land cover modification geoindicator in order to assess the environmental condition of the territory per landscape units. It was designed to interpret diffuse information and transform it into a synthetic indicator that will be useful for environmental managers. The geoindicator evaluation was performed through a multi-temporal analysis of medium resolution Landsat satellite images and their unsupervised classification according to the direction of land use transitions. A change detection analysis between image pairs from 1973, 1991 and 2001 was made to detect unaffected areas and the areas in which positive or negative land cover changes could be observed. The proposed methodology was applied in the coastal palustrine area; specifically, in the marine-terrestrial ecotone of Campeche, Mexico. Geoindicator values during the 1974-1991 and 1991-2001 periods were low, 46.5% and 40.9%, respectively, due to the intrinsic limitations of coastal wetlands for productive activities. Urban and suburban transition areas showed high degrees of modification of about 39.5% and 32.1% for the first and the second period, respectively. Moderate modification, 4.9% in the first period and 5.7% in the second, was observed in isolated landscape units with recovering vegetation. The proposed geoindicator showed physiognomic and functional evidence of affectation levels from human activities, regeneration patterns and alteration of the landscape structure, modulated by the historical-economic process in the studied area. PMID:25412539

  7. Local spatial context measurements used to explore the relationship between land cover and land use functions

    NASA Astrophysics Data System (ADS)

    Wästfelt, Anders; Arnberg, Wolter

    2013-08-01

    Research making use of satellite data for land change science has developed in the last decades. However, analysis of land use has not developed with the same speed as development of new satellite sensors and available land cover data. Improvement of land use analysis is possible, but more advanced methods are needed which make it possible to link image data to analysis of land use functions. To make this linking possible, variable which affect farmer's long term decisions must be taken into account in analysis as well as the relative importance of the landscape itself. A GIS-based tool for the measurement of local spatial context in satellite data is presented in this paper and used to explore the relationship between land covers present in satellite data and land use represented in official databases. By the use of the developed tool, a land configuration image (LCI) over the Siljan area in northern Sweden was produced and used for analysis. The results are twofold. First, the produced LCI holds new information about variables that are relevant for the interpretation of land use. Second, the comparison with statistics of agricultural production shows that production in the study area varies depending on the relative land configuration. Villages consisting of relatively large-scale arable fields and less diverse landscape are less diverse in production than villages which consist of smaller-scale and more heterogonous landscapes. The result is especially relevant for land use studies and policymakers working on environmental and agricultural policies. We conclude that local spatial context is an endogenous variable in the relation between landscape configuration and agricultural land use.

  8. Creation of a global land cover and a probability map through a new map integration method

    NASA Astrophysics Data System (ADS)

    Kinoshita, Tsuguki; Iwao, Koki; Yamagata, Yoshiki

    2014-05-01

    Global land cover maps are widely used for assessment and in research of various kinds, and in recent years have also come to be used for socio-economic forecasting. However, existing maps are not very accurate, and differences between maps also contribute to their unreliability. Improving the accuracy of global land cover maps would benefit a number of research fields. In this paper, we propose a methodology for using ground truth data to integrate existing global land cover maps. We checked the accuracy of a map created using this methodology and found that the accuracy of the new map is 74.6%, which is 3% higher than for existing maps. We then created a 0.5-min latitude by 0.5-min longitude probability map. This map indicates the probability of agreement between the category class of the new map and truth data. Using the map, we found that the probabilities of cropland and grassland are relatively low compared with other land cover types. This appears to be because the definitions of cropland differ between maps, so the accuracy may be improved by including pasture and idle plot categories.

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

    USGS Publications Warehouse

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

    2003-01-01

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

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

    USGS Publications Warehouse

    LaMotte, Andrew

    2008-01-01

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

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

    USGS Publications Warehouse

    LaMotte, Andrew

    2008-01-01

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

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

    USGS Publications Warehouse

    LaMotte, Andrew

    2008-01-01

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

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

    USGS Publications Warehouse

    LaMotte, Andrew

    2008-01-01

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

  14. The role of change data in a land use and land cover map updating program

    USGS Publications Warehouse

    Milazzo, Valerie A.

    1981-01-01

    An assessment of current land use and a process for identifying and measuring change are needed to evaluate trends and problems associated with the use of our Nation's land resources. The U. S. Geological Survey is designing a program to maintain the currency of its land use and land cover maps and digital data base and to provide data on changes in our Nation's land use and land cover. Ways to produce and use change data in a map updating program are being evaluated. A dual role for change data is suggested. For users whose applications require specific polygon data on land use change, showing the locations of all individual category changes and detailed statistical data on these changes can be provided as byproducts of the map-revision process. Such products can be produced quickly and inexpensively either by conventional mapmaking methods or as specialized output from a computerized geographic information system. Secondly, spatial data on land use change are used directly for updating existing maps and statistical data. By incorporating only selected change data, maps and digital data can be updated in an efficient and timely manner without the need for complete and costly detailed remapping and redigitization of polygon data.

  15. Generation of 2D Land Cover Maps for Urban Areas Using Decision Tree Classification

    NASA Astrophysics Data System (ADS)

    Höhle, J.

    2014-09-01

    A 2D land cover map can automatically and efficiently be generated from high-resolution multispectral aerial images. First, a digital surface model is produced and each cell of the elevation model is then supplemented with attributes. A decision tree classification is applied to extract map objects like buildings, roads, grassland, trees, hedges, and walls from such an "intelligent" point cloud. The decision tree is derived from training areas which borders are digitized on top of a false-colour orthoimage. The produced 2D land cover map with six classes is then subsequently refined by using image analysis techniques. The proposed methodology is described step by step. The classification, assessment, and refinement is carried out by the open source software "R"; the generation of the dense and accurate digital surface model by the "Match-T DSM" program of the Trimble Company. A practical example of a 2D land cover map generation is carried out. Images of a multispectral medium-format aerial camera covering an urban area in Switzerland are used. The assessment of the produced land cover map is based on class-wise stratified sampling where reference values of samples are determined by means of stereo-observations of false-colour stereopairs. The stratified statistical assessment of the produced land cover map with six classes and based on 91 points per class reveals a high thematic accuracy for classes "building" (99 %, 95 % CI: 95 %-100 %) and "road and parking lot" (90 %, 95 % CI: 83 %-95 %). Some other accuracy measures (overall accuracy, kappa value) and their 95 % confidence intervals are derived as well. The proposed methodology has a high potential for automation and fast processing and may be applied to other scenes and sensors.

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

    USGS Publications Warehouse

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

    2008-01-01

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

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

    PubMed

    Yilmaz, Rüya

    2010-06-01

    The objective of the present study was to assess changes in land use/land cover patterns in the coastal town of Silivri, a part of greater Istanbul administratively. In the assessment, remotely sensed data, in the form of satellite images, and geographic information systems were used. Types of land use/land cover were designated as the percentage of the total area studied. Results calculated from the satellite data for land cover classification were compared successfully with the database Coordination of Information on the Environment (CORINE). This served as a reference to appraise the reliability of the study presented here. The CORINE Program was established by the European Commission to create a harmonized Geographical Information System on the state of the environment in the European Community. Unplanned urbanization is causing land use changes mainly in developing countries such as Turkey. This situation in Turkey is frequently observed in the city of Istanbul. There are only a few studies of land use-land cover changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Istanbul. The research area comprised greater Silivri Town which is situated by the coast of Marmara Sea, and it is located approximately 60 km west of Istanbul. The city of Istanbul is one of the largest metropolises in Europe with ca. 15 million inhabitants. Additionally, greater Silivri is located near the terminal point of the state highway connecting Istanbul with Europe. Measuring of changes occurring in land use would help control future planning of settlements; hence, it is of importance for the Greater Silivri and Silivri Town. Following our evaluations, coastal zone of Silivri was classified into the land use groups of artificial surfaces agricultural areas and forests and seminatural areas with 47.1%, 12.66%, and 22.62%, respectively. PMID:19496006

  18. AVHRR composite period selection for land cover classification

    USGS Publications Warehouse

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

    2002-01-01

    Multitemporal satellite image datasets provide valuable information on the phenological characteristics of vegetation, thereby significantly increasing the accuracy of cover type classifications compared to single date classifications. However, the processing of these datasets can become very complex when dealing with multitemporal data combined with multispectral data. Advanced Very High Resolution Radiometer (AVHRR) biweekly composite data are commonly used to classify land cover over large regions. Selecting a subset of these biweekly composite periods may be required to reduce the complexity and cost of land cover mapping. The objective of our research was to evaluate the effect of reducing the number of composite periods and altering the spacing of those composite periods on classification accuracy. Because inter-annual variability can have a major impact on classification results, 5 years of AVHRR data were evaluated. AVHRR biweekly composite images for spectral channels 1-4 (visible, near-infrared and two thermal bands) covering the entire growing season were used to classify 14 cover types over the entire state of Colorado for each of five different years. A supervised classification method was applied to maintain consistent procedures for each case tested. Results indicate that the number of composite periods can be halved-reduced from 14 composite dates to seven composite dates-without significantly reducing overall classification accuracy (80.4% Kappa accuracy for the 14-composite data-set as compared to 80.0% for a seven-composite dataset). At least seven composite periods were required to ensure the classification accuracy was not affected by inter-annual variability due to climate fluctuations. Concentrating more composites near the beginning and end of the growing season, as compared to using evenly spaced time periods, consistently produced slightly higher classification values over the 5 years tested (average Kappa) of 80.3% for the heavy early

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  20. The role of land cover variability on modelled land-atmosphere coupling

    NASA Astrophysics Data System (ADS)

    Weiß, M.; van den Hurk, B.

    2012-04-01

    Anthropogenic land-use activities have led to large-scale changes in global vegetation cover over the past centuries, and will probably continue so in the future. This impact is potentially significant, since managed crop lands and pastures are now among the largest ecosystems on earth. Their surface parameters differ largely from those of most natural vegetations they replace. Land cover changes can range from changes in the state of vegetation to vegetation type conversion. The impact of a changing land surface on climate and climate simulations has recently attracted scientific interest, but process-understanding has yet to be build up. This study investigates the role of land cover variability and vegetation in controlling the land-atmosphere coupling, and its relation with evaporation and surface temperature. Global atmospheric simulations are carried out with the EC-EARTH climate model using climatological sea surface temperature and sea ice distributions. It was found that total variance of T2m amplifies mainly in the Northern hemisphere and partly in the tropics. These areas coincide with areas with a negative correlation between soil-moisture and evapotranspiration in spring and summer, i.e. evaporation affects soil moisture by depletion. In these areas a positive impact of time varying LAI values on temperature variability is found. Changes in LAI affect evapotranspiration more strongly in non-water limited, i.e. radiation limited climate regimes, where a change in vegetation properties can translate into evapotranspiration- and subsequent temperature changes.

  1. Monitoring land use/land cover dynamics in northwestern Ethiopia using support vector machine

    NASA Astrophysics Data System (ADS)

    Zewdie, Worku; Csaplovics, E.

    2014-10-01

    Land use/land cover (LULC) change assessment explores a terrestrial ecosystem in relation to the impact of natural processes and anthropogenic activities towards temporal and spatial change. This study explores spatial and quantitative dynamics of land use change in the semi-arid regions of northwestern Ethiopia using Landsat-5 (1984) and Landsat-8 (2014) which provided recent and historical LULC conditions of the region. Supervised classification algorithm using support vector machines (SVM) was used to map and monitor land use transformations. A post-classification change detection assessment was applied to individual image classification outputs of the best performing SVM model in order to identify respective two-date change trajectories. The change detection analysis with an extended transition matrix showed a net quantity change of 44.0% and total change of 53.7% of the study area, with the latter change is due to swap changes. Post-classification comparisons of the classified imagery identified a major woodland transformation to cropland which is attributed to population size and economic activity. The area of cropland has increased significantly (52.8%) in 2014 contributing to the reduction in native vegetation cover. In the study period, 55.6% of woodland lost signifying a significant change in ecosystems. This significant land use transformation is due to accelerated human impact and subsequent agricultural land expansion. The loss in vegetation cover has exposed the surface and it is common to see a haze of cloud in a most semiarid region of NW Ethiopia.

  2. The role of land cover in high latitude land surface temperature heterogeneity

    NASA Astrophysics Data System (ADS)

    Wang, D.; Nagol, J. R.; Morton, D. C.; Masek, J. G.

    2011-12-01

    Near-surface air temperature governs a range of land surface processes, such as photosynthesis, respiration, and evapotranspiration. However, the spatiotemporal patterns of near-surface air temperature are complex. Meteorological stations provide a detailed account of temporal variations in air temperature, but fail to capture spatial heterogeneity in surface temperature, especially over remote regions with sparse station networks. Gridded climate datasets (0.5° - 2.0° spatial resolution) produced from the meteorological station observations therefore inherit these same shortcomings, since current algorithms use only latitude, longitude, and elevation to interpolate between station locations. Here, we explored the use of MODIS-based estimates of land surface temperature (LST) and land cover to estimate fine-scale heterogeneity in land surface temperature during summer months over boreal North America. We combined nighttime MODIS LST with meteorological station and gridded climate data records. Our analysis quantified the contribution from station distance (latitude and longitude) and land cover type for differences between MODIS and station-based estimates of nighttime temperatures. Finally, we estimated the impact of sub-grid cell heterogeneity in LST for ecosystem processes by comparing seasonal respiration fluxes from an ecosystem model driven by gridded climate data and MODIS LST. Our study suggests that downscaling coarse resolution temperature data using MODIS LST and land cover information can improve estimates of spatial variability in surface temperature data and related ecosystem processes.

  3. Comparative performance of ALOS PALSAR polarization bands and its combination with ALOS AVNIR-2 data for land cover classification

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

    Microwave Remote Sensing data have been widely used for land cover classification in our environment. In this study, ALOS PALSAR polarization bands were used to identify land cover features in three study areas in Malaysia. The study area consists of Penang, Perak and Kedah. The aims of this research are to investigate the performance of ALOS PALSAR datasets which are assessed independently and combination of these data with ALOS AVNIR-2 for land cover classification. Standard supervised classification method Maximum Likelihood Classifier (MLC) was applied. Various land cover classes were identified and assessed using the Transformed Divergence (TD) separability measures. The PALSAR data training areas were chosen based on the information obtained from ALOS AVNIR-2 datasets. The original data gave very poor results in identifying land cover classes due to the presence of immense speckle. The extraction and use of mean texture measures was found to be very advantageous when evaluating the separability among the different land covers. Hence, mean texture was capable to provide higher classification accuracies as compared to the original radar. The highest overall accuracy was achieved by combining the radar mean texture with ALOS AVNIR-2 data. This study proved that the land cover of Penang, Perak, and Kedah can be mapped accurately using combination of optical and radar data.

  4. Investigating the Impact of Land between the Lakes (LBL) and Land Use/Land Cover Change on Precipitation Patterns

    NASA Astrophysics Data System (ADS)

    Degu, A. M.; Hossain, F.

    2012-12-01

    Large dams/reservoirs as open water surface and as a mechanism of triggering land use/land cover changes in their vicinity have impacted local climate and extreme precipitation patterns as study show. Urbanization, agricultural development, and forestation are some of the Land Use/Land Cover Changes (LULCC) that are result of development of large dams/reservoirs. Thus creating heterogeneities. It is believed that such heterogeneities bring about a boundary of different air masses that triggers convection due to differential heating as well as variation in soil moisture. One such heterogeneities is of the Land Between the Lakes (LBL). LBL is an inland peninsula formed by Lake Kentucky on Tennessee River and Lake Barkley on Cumberland River in Western Kentucky. The development of the two lakes brought about an area of 680 sq.km forest cover. The LBL renders unique land use/land cover heterogeneities with in a shorter distance providing open water for evaporation and forest for evapotranspiration. Reports as well as a preliminary investigation of nearby weather radar data showed storms dying out as it approaches the inland peninsula and gaining strength east of LBL. The storm exhibits a wave like strength, attenuating before LBL and gaining strength after. The purpose of this study mainly is to investigate the impact of LBL and in general LULCC on precipitation in the area. In this study the following specific scientific question will be addressed a. Has the development of LBL modified precipitation in the region? b. Which LULCC predominately affects storm formation? Summer radar reflectivity data from Paducah, KY station along with North America Regional Reanalysis (NARR) geopotential height and wind direction data will be analyzed for identification of LBL effect precipitation and synoptic effect precipitation, respectively. A Weather Research and Forecasting Model (WRF) will be setup to investigate what land use/land cover predominately modifies precipitation in

  5. Simulating Land-Cover Change in Montane Mainland Southeast Asia

    NASA Astrophysics Data System (ADS)

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

    2012-05-01

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

  6. Land Cover Applications, Landscape Dynamics, and Global Change

    USGS Publications Warehouse

    Tieszen, Larry L.

    2007-01-01

    The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

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

    PubMed

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

    2012-05-01

    We used the conversion of land use and its effects (CLUE-s) model to simulate scenarios of land-cover change in Montane mainland southeast Asia (MMSEA), a region in the midst of transformation due to rapid intensification of agriculture and expansion of regional trade markets. Simulated changes affected approximately 10 % of the MMSEA landscape between 2001 and 2025 and 16 % between 2001 and 2050. Roughly 9 % of the current vegetation, which consists of native species of trees, shrubs, and grasses, is projected to be replaced by tree plantations, tea, and other evergreen shrubs during the 50 years period. Importantly, 4 % of this transition is expected to be due to the expansion of rubber (Hevea brasiliensis), a tree plantation crop that may have important implications for local-to-regional scale hydrology because of its potentially high water consumption in the dry season. PMID:22476665

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

    USGS Publications Warehouse

    Wilson, Tamara S.

    2011-01-01

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

  9. Digital elevation data as an aid to land use and land cover classification

    USGS Publications Warehouse

    Colvocoresses, Alden P.

    1981-01-01

    In relatively well mapped areas such as the United States and Europe, digital data can be developed from topographic maps or from the stereo aerial photographic movie. For poorer mapped areas (which involved most of the world's land areas), a satellite designed to obtain stereo data offers the best hope for a digital elevation database. Such a satellite, known as Mapsat, has been defined by the U.S. Geological Survey. Utilizing modern solid state technology, there is no reason why such stereo data cannot be acquired simultaneously with the multispectral response, thus simplifying the overall problem of land use and land cover classification.

  10. Collecting Sketch Maps to Understand Property Land Use and Land Cover in Large Surveys

    PubMed Central

    D’ANTONA, ÁLVARO DE OLIVEIRA; CAK, ANTHONY D.; VANWEY, LEAH K.

    2009-01-01

    This article describes a method to collect data on the spatial organization of land use within a rural property as part of a large-scale project examining the linkages between household demographic change and land use and land cover change in the Brazilian Amazon. Previous studies used several different spatial approaches, including maps and satellite images, to improve the information collected in standard survey questionnaires. However, few used sketch maps to obtain information from the point of view of the survey respondent about the spatial organization of land use and infrastructure. We developed a method of creating sketch maps with respondents to describe their properties. These maps then provided a spatially referenced database of the social and land use organization of the properties from the perspective of the respondent. Systematic rules allowed sketches to be used in subsequent spatial analyses in combination with satellite images and Global Positioning System reference points PMID:19789719

  11. Enhanced Historical Land-Use and Land-Cover Data Sets of the U.S. Geological Survey

    USGS Publications Warehouse

    Price, Curtis V.; Nakagaki, Naomi; Hitt, Kerie J.; Clawges, Rick M.

    2007-01-01

    Historical land-use and land-cover data, available from the U.S. Geological Survey (USGS) for the conterminous United States and Hawaii, have been enhanced for use in geographic information systems (GIS) applications. The original digital data sets were created by the USGS in the late 1970s and early 1980s and were later converted by USGS and the U.S. Environmental Protection Agency (USEPA) to a geographic information system (GIS) format in the early 1990s. These data were made available on USEPA's Web site since the early 1990s and have been used for many national applications, despite minor coding and topological errors. During the 1990s, a group of USGS researchers made modifications to the data set for use in the National Water-Quality Assessment Program. These edited files have been further modified to create a more accurate, topologically clean, and seamless national data set. Several different methods, including custom editing software and several batch processes, were applied to create this enhanced version of the national data set. The data sets are included in this report in the commonly used shapefile and Tagged Image Format File (TIFF) formats. In addition, this report includes two polygon data sets (in shapefile format) representing (1) land-use and land-cover source documentation extracted from the previously published USGS data files, and (2) the extent of each polygon data file.

  12. Floodplain land cover mapping using Thematic Mapper data

    NASA Technical Reports Server (NTRS)

    Kerber, A. G.; Gervin, J. C.; Lu, Y.-C.; Marcell, R.; Edwardo, H. A.

    1986-01-01

    The accuracy of land-cover classifications based on Landsat-4 TM and MSS images (obtained in August 1982) and airborne TMS images (obtained in September 1981) of the New Martinsville, West Virginia area is evaluated by comparison with ground-truth data. TM, TMS, and MSS are found to have overall mapping accuracies 80.1, 78.5, and 75.6 percent; agriculture/grass accuracies 62.0, 29.7, and 46.6 percent; and developed-area accuracies 67.2, 77.8, and 59.4 percent, respectively.

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

    NASA Astrophysics Data System (ADS)

    Netzel, P.; Stepinski, T.

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  15. Land use and land cover information and air-quality planning

    USGS Publications Warehouse

    Reed, W.E.; Lewis, J.E.

    1978-01-01

    The land use and land cover information developed by the U.S. Geological Survey in the Central Atlantic Regional Ecological Test Site project has been proven useful when used in an improved technique for estimating emissions, diffusion, and impact patterns of sulfur dioxide (S02) and particulate matter. Implementation of plans to control air quality requires land use and land cover information, which, until this time, has been inadequate. The land use and land cover data were used in updating information on the sources of point and area emissions of S02 and particulate matter affecting the Norfolk-Portsmouth area of Virginia for the 1971-72 winter (Dec.-Jan.-Feb.) and the annual 1972 period, and for a future annual period-1985. This emission information is used as input to the Air Quality Display Model of the Environmental Protection Agency to obtain diffusion and impact patterns for the three periods previously mentioned. The results are: (1) During the 1971-72 winter, estimated S02 amounts over an area with southwest-northeast axis in the central section of Norfolk exceeded both primary and secondary levels, (2) future annual levels of S02, estimated by anticipated residential development and point-source changes, are not expected to cause serious deterioration of the region's present air quality, and (3) for the 1971-72 winter, and annual 1972, period the diffusion results showed that both primary and secondary standards for particulate matter are regularly exceeded in central Norfolk and Portsmouth. In addition, on the basis of current control programs, the 1985 levels of particulate matter are expected to exceed the presently established secondary air-quality standards through central Norfolk and Portsmouth and in certain areas of Virginia Beach. Land use and land cover information can be used to estimate emissions for inputs to diffusion models and to interpret the implications of diffusion patterns for: (1) Implementing various control strategies, (2

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  17. Comparison and evaluation of five global land cover datasets for Mexico

    NASA Astrophysics Data System (ADS)

    Lopez-Espinoza, E. D.; Zavala-Hidalgo, J.; Gómez-Ramos, O.; Osorio-Tai, M. E.; Romero-Centeno, R.

    2013-05-01

    A comparison and evaluation of five global and continental land use and land cover datasets was carried out over Mexico. The analysis includes the IGBP-DISCover1993 map, version 1.2, produced by the United States Geological Survey (USGS) in collaboration with the University of Nebraska-Lincoln and the European Commission's Joint Research Centre (JRC); the GLC2000 map, produced by the JRC in collaboration with 30 institutions; the NALCMS2005 map, produced by a collaborative effort of governmental agencies in Canada, Mexico and the United States coordinated by the Commission for Environmental Cooperation (CEC); and the 2005 and 2009 GLOBCOVER maps, produced by the ESA-GlobCover (European Space Agency) project. Since the five datasets differ in map projection, resolution and legend system, a step of standardization was performed. The analysis shows that all databases have an agreement of 16.82% for the Mexican territory. The classes with a better agreement in all datasets are evergreen broadleaf forest in the Yucatán peninsula, the urban and built land in the center of the country and shrubland in the north. Moreover, the quantitative assessment showed that classification accuracy obtained by NALCMS2005 is the highest compared to the other four analyzed maps, the GLOBCOVER2005 land cover map ranked second, while the GLC2000 and IGBP-DISCover1993 maps ranked third. GLOBCOVER2009 is the map that more poorly describes the Mexican land use and land cover. In general, this analysis shows that a dataset does not represent a region more accurately by the fact of being the most recently created, so it is recommended to carry out regional reviews in order to deciding which dataset is more useful.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  19. Local topographic wetness indices predict household malaria risk better than land-use and land-cover in the western Kenya highlands

    PubMed Central

    2010-01-01

    associations with household malaria. However, these land-cover/land-use variables failed to produce unambiguous improvements in statistical predictive models controlling for important topographic factors, with none improving prediction of household-level malaria more than 75% of the time. Conclusions Topographic wetness values in this region of highly varied terrain more accurately predicted houses at greater risk of malaria than did consideration of land-cover/land-use characteristics. As such, those planning control or local elimination strategies in similar highland regions may use topographic and geographic characteristics to effectively identify high-receptivity regions that may require enhanced vigilance. PMID:21080943

  20. Controls on Watershed Biogeochemistry by Climate, Land Cover, and Soils

    NASA Astrophysics Data System (ADS)

    Fisher, T. R.; Sutton, A. J.; Gustafson, A. B.; Koskelo, A. I.; Fox, R. J.; Stone, J.

    2006-05-01

    Water and elemental discharge from catchments is largely controlled by climate, soils, and land cover. Seasonal temperature and rainfall patterns determine the water available for stream discharge, and average annual air temperature is inversely correlated with the proportion of rainfall that is annually discharged as stream flow. At higher temperatures, an increasing fraction of the soil water is evapotranspired to the atmosphere as water vapor rather than discharged as stream flow. Hydrologic soil drainage properties determine whether precipitation is primarily directed horizontally as overland flow or vertically as infiltration to groundwater for baseflow. Concentrations of N in groundwater, primarily nitrate, reflect the surface land uses, particularly agriculture and residential areas with septic systems. However, hydric soils act as a trap for anthropogenic nitrate in groundwater, probably by denitrification in oxygen-poor, C-rich, micro-environments. Likewise, the P content of surface soils controls the P concentration in overland flow due to leaching of soluble P and erosion of particulate P. At the watershed scale, concentrations of N and P in stream discharge are augmented in proportion to the fraction of the basin in anthropogenic land uses such as agriculture and urban areas, which contribute nutrients via application of fertilizers and disposal of human waste. This anthropogenic fraction of a basin's land uses represents the human footprint upon the land which primarily determines the elevated N and P losses from the basin. N is relatively easily sampled because it is primarily transported as highly soluble nitrate in groundwater-supported baseflow; however, P sampling is more difficult because transport largely occurs episodically following storm events when both stream flow and P concentrations are high during brief periods. As a result, P concentrations and fluxes are almost certainly undersampled and underestimated compared to N fluxes, and fewer

  1. Visual interpretation of synthetic aperture radar data for assessing land cover in tropical savannahs

    NASA Astrophysics Data System (ADS)

    Stuart, N.; Cameron, I.; Viergever, K. M.; Moss, D.; Wallington, E.; Woodhouse, I.

    2006-10-01

    Satellite SAR data offers land managers an affordable, all-weather capability for detailed land cover mapping. Visual classification of these data may be more appropriate to the resource base in many developing countries and human interpreters can often overcome problems of speckle more effectively than automated classification procedures. We report work in progress on the visual interpretation of SAR data to classify land cover types within tropical savannas. Airborne L-band SAR data for a region in Belize, Central America is degraded to approximate the single polarisation hh and dual polarization hh/hv data that is expected from the ALOS PALSAR satellite sensor. Interpretations of these two types of data by multiple interpreters were compared to explore how the number of polarizations, the effective spatial resolution and the visual presentation of the SAR data affected the ability of interpreters to classify land cover. An average classification accuracy of 78% for hh and 85% for hh/hv data were achieved for all classes and interpreters. Denser high forest areas were accurately interpreted using both data sets, whilst a red-green colour composite of the hh/hv data allowed grass dominated areas to be separated from areas of savanna woodland. Conclusions are drawn about the benefits of certain presentations of backscatter data to assist visual interpretation.

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

    NASA Astrophysics Data System (ADS)

    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.

  3. United States Land Cover Land Use Change, Albedo and Surface Radiative Forcing 1973 to 2000

    NASA Astrophysics Data System (ADS)

    Barnes, C. A.; Roy, D. P.

    2007-12-01

    This research responds to the recent recommendations made by the U.S. National Research Council for regional forcing studies to better understand climatic responses to land cover land use change. Surface albedo affects the earth's radiative energy balance, by controlling how much incoming solar radiation is absorbed and reflected. It is well established that Land Cover Land Use (LCLU) change results in changes in the surface albedo which has a radiative forcing effect, however, to date, studies have been limited due to data uncertainties. New spatially explicit satellite derived LCLU change and albedo data for the conterminous U.S. are used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing. The methodology and preliminary results for 42% of the U.S. processed to date are presented as spatially explicit maps and summary statistics. The results indicate a negative (cooling) radiative forcing effect due to U.S. LCLU change over the last three decades. Data used include USGS Landsat based decadal land cover maps of the conterminous U.S. located using a stratified sampling methodology across 84 ecoregions, mean 2000-2002 MODIS broadband albedo values extracted in each ecoregion for the 10 mapped LCLU classes, and monthly mean surface incoming solar radiation from the recent European Center for Medium Range Weather Forecast 40 year Reanalysis (ERA40) product.

  4. A proper Land Cover and Forest Type Classification Scheme for Mexico

    NASA Astrophysics Data System (ADS)

    Gebhardt, S.; Maeda, P.; Wehrmann, T.; Argumedo Espinoza, J.; Schmidt, M.

    2015-04-01

    The imminent implementation of a REDD+ MRV system in Mexico in 2015, demanding operational annual land cover change reporting, requires highly accurate, annual and high resolution forest type maps; not only for monitoring but also to establish the historical baseline from the 1990s onwards. The employment of any supervised classifier demands exhaustive definition of land cover classes and the representation of all classes in the training stage. This paper reports the process of a data driven class separability analysis and the definition and application of a national land cover classification scheme. All Landsat data recorded over Mexico in the year 2000 with cloud coverage below 10 percent and a national digital elevation model have been used. Automatic wall-2-wall image classification has been performed trained by national reference data on land use and vegetation types with 66 classes. Validation has been performed against field plots of the national forest inventory. Groups of non-separable classes have subsequently been discerned by automatic iterative class aggregation. Class aggregations have finally been manually revised and modified towards a proposed national land cover classification scheme at 4 levels with 35 classes at the highest level including 13 classes for primary temperate and tropical forests, 2 classes for secondary temperate and tropical forest, 1 for induced or cultivated forest, as also 8 different scrubland classes. The remaining 11 classes cover agriculture, grassland, wetland, water bodies, urban and other vegetation land cover classes. The remaining 3 levels provide further hierarchic aggregations with 14, 10, and 8 classes, respectively. Trained by the relabeled training dataset wall-2-wall classification towards the 35 classes has been performed. The final national land cover dataset has been validated against more than 200,000 polygons randomly distributed all over the country with class labels derived by manual interpretation. The

  5. Land cover and Urbanization links with stream Biota in the mid-Atlantic USA

    NASA Astrophysics Data System (ADS)

    Goetz, S. J.; Fiske, G.

    2005-12-01

    The amount of roads, parking lots, buildings and other developed land within a watershed, its impervious surface area (ISA), has long been known to impact the biotic health of streams and waterways. Vegetation in riparian zones can reduce the negative impacts of ISA by buffering runoff, filtering pollution, and reducing flow velocities that incise stream channels and transport pollutants. ISA has traditionally been mapped by assigning coefficients to land use categories, a type of 'classify and multiply' approach. This can be substantially improved using digital imagery capable of discriminating fine scale information of the land surface, including built areas and tree cover in riparian buffer zones. We used a combination of Landsat (30m) and IKONOS (4m) satellite imagery to develop accurate maps of subpixel ISA and tree cover across the Chesapeake Bay watershed, an area of highly altered land cover and rapid land use change. We report on analyses of the links between these maps and stream biotic measurements for a wide range of small watersheds across Maryland for which extensive in-stream monitoring has been established as part of the Maryland Biological Stream Survey (MBSS). A regression tree statistical approach was used to determine the relationship between land cover and indices calculated by the MBSS, focusing on benthic indices of biologic integrity (IBI). We also explored the influence of landscape configuration and distance weighting of land cover relative to stream channels and sampling points. Thresholds of impervious and tree cover within the watersheds and riparian buffer zones established using the IKONOS imagery were found to vary more substantially across the diverse range of watersheds within the state, as assessed using the Landsat subpixel maps. Nonetheless, ISA was found to be the primary predictor of stream health, followed by tree cover in riparian buffers and within the watersheds. This work advances the estimation of stream health

  6. Inferring non-point pollution from land cover analysis

    NASA Astrophysics Data System (ADS)

    Hyde, Richard F.

    Best Management Practices (BMP's) in farming were found to significantly reduce agricultural non-point water pollution in Central Indiana. Through the implementation of systems of conservation tillage practices and structural measures at the farm level, reductions in runoff were achieved, thereby minimizing erosion and subsequent sedimentation and pollution of the surface water system. These conclusions resulted from a three and one-half year study entitled, ``The Indiana Heartland Model Implementation Project'' administered by the Indiana Heartland Coordinating Commission, involving cooperation and coordination of farmers, citizens, and a multi-agency, multi-disciplinary team comprised of four universities and numerous governmental agencies. The U.S. Environmental Protection Agency funded research, while the U.S. Department of Agriculture provided cost share monies for BMP implementation. A comprehensive geographically encoded computer-aided data base was constructed which included information on land cover, elevation, slope, aspect, soils, etc. Land cover map files were compiled through remote sensing including Landsat MSS digital data and low altitude color infrared aerial photography sources. This digital data base was suited for spatial and statistical analyses and transferred easily as input to Purdue University's ANSWERS Model for further watershed assessment. The ANSWERS Model is a distributed deterministic model which simulates the monitored reaction of subwatersheds to actual storm events. Through this model inferences were made as to the expected water quality improvements, given BMP's were implemented at critical areas for erosion throughout both watersheds.

  7. Land cover classification with MODIS data in China

    NASA Astrophysics Data System (ADS)

    Wang, Changyao; Zhao, Degang; Zhan, Yulin; Zhang, Qingyuan

    2009-06-01

    In this paper, Moderate Resolution Image Spectroradiometer (MODIS) data with high spectral and temporal resolutions were used as input parameters for Chinese regional scale land cover classification. Firstly, Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI) and Normalized Difference Soil Index (NDSI) were calculated as input spectral features relies on an annual time series of twelve MODIS 8-day composite reflectance images (MOD09) acquired during the year of 2007. The monthly EVI was produced by the maximum value composite; the three indices were added in the image to form a 10-spectral-bands image. In order to reduce the input feature space dimension, we resort to the mean Jeffries-Matusita distance as a statistical separability criterion to select the best spectral feature combination according to their ability of separating the land cover classes. Once we achieved, the monthly best combination spectral bands were dealt with Principal Component Analysis (PCA) method and their first three principal components were used as input parameters for decision tree classification. The result showed that the best combination of spectral bands added temporal information as input parameters can reach a certain high classification accuracy (81.16%) at moderate spatial scales without other accessorial data.

  8. The evaluation of alternate methodologies for land cover classification in an urbanizing area

    NASA Technical Reports Server (NTRS)

    Smekofski, R. M.

    1981-01-01

    The usefulness of LANDSAT in classifying land cover and in identifying and classifying land use change was investigated using an urbanizing area as the study area. The question of what was the best technique for classification was the primary focus of the study. The many computer-assisted techniques available to analyze LANDSAT data were evaluated. Techniques of statistical training (polygons from CRT, unsupervised clustering, polygons from digitizer and binary masks) were tested with minimum distance to the mean, maximum likelihood and canonical analysis with minimum distance to the mean classifiers. The twelve output images were compared to photointerpreted samples, ground verified samples and a current land use data base. Results indicate that for a reconnaissance inventory, the unsupervised training with canonical analysis-minimum distance classifier is the most efficient. If more detailed ground truth and ground verification is available, the polygons from the digitizer training with the canonical analysis minimum distance is more accurate.

  9. Estimates of Geographically Explicit Future CO2 Emissions From Land Cover/ Land Use Changes

    NASA Astrophysics Data System (ADS)

    Richardson, T.; Yang, X.; Jain, A.; O'Neill, B.

    2007-12-01

    Land cover and land use change activities, such as deforestation, afforestation, and agriculture management, are important sources of not only CO2, but also non-CO2 GHGs and aerosols. The objective of this paper is to evaluate the potential contribution of future GHGs and reactive GHGs emissions via changes in regional land use-related activities at a 0.5 degree by 0.5 degree resolution. Regional land use is downscaled to the grid cell level based on socioeconomic, biophysical, and biogeochemical factors. Socio-economic factors include population density at the grid zone level. Land sustainability and attainable crop yields, as well as terrain conditions, are biophysical and biogeochemical factors that were also determined at each grid zone level. The productivity of land was determined by the length of growing period (LGP) using the biophysical and biochemical cycles of the Integrated Science Assessment Model (ISAM). Agro-ecological and economic indexes were constructed using historical and current-day cropping practices at the grid zone levels. In the future, the distribution of LGPs may be altered due to changes in carbon, nutrients, and climate. This paper uses two IPCC SRES (A2 and B1) emissions and land use scenarios during the time period 2000-2050 to evaluate the relative importance of land use emissions to future net terrestrial CO2 uptakes.

  10. Remote Sensing for optimum road network development by using Land use Land cover classification

    NASA Astrophysics Data System (ADS)

    More, Snehal; Bhuvana Chandra, mr.; Hebbar, R.

    2012-07-01

    Rural development plays a major role in overall development of any country. Remote Sensing may be helpful in areas like infrastructure development, agricultural development. This paper focuses on implementation of Remote Sensing methods for solving problems in laying new roads and efficient transport in undulating terrain regions. It gives an approach towards economical and ecofriendly rural development. The aim was to suggest a road network with optimum transportation path considering the major factors as slope, road length, least intervention to the natural vegetation, least transportation cost. Area of interest was chosen from Agali-Thuvaipathy area in Palakkad, Kerala. The methodology involves generation of Digital Elevation Model, slope map, land use land cover map for the area of interest. DEM was generated using Cartosat-1 stereo pairs, slope map was generated using Arc Map and land use land cover map was generated by digitizing different feature classes like cropland, vegetation, barren land, water body and town from the LISS 4 data. Weighted overlay analysis was performed for identification of an optimum path by applying required limitations on land use type and maximum slope value. The favorable area for road creation between the two given points in the image was obtained.

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

    USGS Publications Warehouse

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

    1976-01-01

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

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

    PubMed

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

    2015-09-15

    To understand the relations between land use allocation and water quality preservation within a watershed is essential to assure sustainable development. The land use and land cover (LUC) within Zêzere River watershed registered relevant changes in the last decades. These land use and land cover changes (LUCCs) have impacts in water quality, mainly in surface water degradation caused by surface runoff from artificial and agricultural areas, forest fires and burnt areas, and caused by sewage discharges from agroindustry and urban sprawl. In this context, the impact of LUCCs in the quality of surface water of the Zêzere watershed is evaluated, considering the changes for different types of LUC and establishing their possible correlations to the most relevant water quality changes. The results indicate that the loss of coniferous forest and the increase of transitional woodland-shrub are related to increased water's pH; while the growth in artificial surfaces and pastures leads mainly to the increase of soluble salts and fecal coliform concentration. These particular findings within the Zêzere watershed, show the relevance of addressing water quality impact driven from land use and should therefore be taken into account within the planning process in order to prevent water stress, namely within watersheds integrating drinking water catchments. PMID:25981942

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

    USGS Publications Warehouse

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

    2012-01-01

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

  14. Changes of Land Cover and Land Use and Greenhouse Gas Emissions in Northern Eurasia

    NASA Astrophysics Data System (ADS)

    Zhuang, Q.; Melillo, J.; Reilly, J.; McGuire, A.; Prinn, R.; Shvidenko, A.; Tchebakova, N.; Sirin, A.; Maksyutov, S.; Peregon, A.

    2009-04-01

    Northern Eurasia accounts for about 20% of the Earth's land surface and 60% of the terrestrial land cover north of 40°N. It contains 70% of the Earth's boreal forests and more than two-thirds of the Earth's land that is underlain by permafrost. The region is covered by vast areas of peatland, complex tundra in the north and semi-deserts and deserts in the south, including the Mongolia plateau. The surface air temperature has increased in the last half century and this increase will continue during this century. We present the results of climate change effects on biogeochemical processes and mechanisms governing the carbon and water dynamics in the region. Future research will address on how patterns of land use in Northern Eurasia may change in the future due to: 1) Economic pressures for providing food, fiber and fuel to a growing global population; 2) Expansion of management of land for cropping, pasture, and forestry into areas that experience a more favorable climate in the future; and 3) Abandonment of management in areas that experience a less favorable climate and the implications of these changes for (1) the exchange of CO2 and CH4 between terrestrial ecosystems and the atmosphere; (2) terrestrial carbon storage and primary productivity; (3) water supply; and (4) radiative forcing of the atmosphere through changes in surface albedo. We use a system of linked models that include the MIT Emissions Prediction and Policy Analysis (EPPA) model of the world economy, the SiBCliM bioclimatic vegetation model, and the Terrestrial Ecosystem Model (TEM) with land-cover/ land-use modeling and biogeochemical modeling based on current relationships as observed through satellite and remote sensing data.

  15. SCALING-UP INFORMATION IN LAND-COVER DATA FOR LARGE-SCALE ENVIRONMENTAL ASSESSMENTS

    EPA Science Inventory

    The NLCD project provides national-scope land-cover data for the conterminous United States. The first land-cover data set was completed in 2000, and the continuing need for recent land-cover information has motivated continuation of the project to provide current and change info...

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

    PubMed

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

    2015-01-15

    Understanding Land Cover/Land Use Change (LCLUC) in diverse regions of the world and at varied spatial scales is one of the important challenges in global change research. In this article, we provide a brief overview of the NASA LCLUC program, its focus areas, and the importance of satellite remote sensing observations in LCLUC research including future directions. The LCLUC Program was designed to be a cross-cutting theme within NASA's Earth Science program. The program aims to develop and use remote sensing technologies to improve understanding of human interactions with the environment. Since 1997, the NASA LCLUC program has supported nearly 280 research projects on diverse topics such as forest loss and carbon, urban expansion, land abandonment, wetland loss, agricultural land use change and land use change in mountain systems. The NASA LCLUC program emphasizes studies where land-use changes are rapid or where there are significant regional or global LCLUC implications. Over a period of years, the LCLUC program has contributed to large regional science programs such as Land Biosphere-Atmosphere (LBA), the Northern Eurasia Earth Science Partnership Initiative (NEESPI), and the Monsoon Area Integrated Regional Study (MAIRS). The primary emphasis of the program will remain on using remote sensing datasets for LCLUC research. The program will continue to emphasize integration of physical and social sciences to address regional to global scale issues of LCLUC for the benefit of society. PMID:25500156

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2001-12-01

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

  19. On the accurate estimation of gap fraction during daytime with digital cover photography

    NASA Astrophysics Data System (ADS)

    Hwang, Y. R.; Ryu, Y.; Kimm, H.; Macfarlane, C.; Lang, M.; Sonnentag, O.

    2015-12-01

    Digital cover photography (DCP) has emerged as an indirect method to obtain gap fraction accurately. Thus far, however, the intervention of subjectivity, such as determining the camera relative exposure value (REV) and threshold in the histogram, hindered computing accurate gap fraction. Here we propose a novel method that enables us to measure gap fraction accurately during daytime under various sky conditions by DCP. The novel method computes gap fraction using a single DCP unsaturated raw image which is corrected for scattering effects by canopies and a reconstructed sky image from the raw format image. To test the sensitivity of the novel method derived gap fraction to diverse REVs, solar zenith angles and canopy structures, we took photos in one hour interval between sunrise to midday under dense and sparse canopies with REV 0 to -5. The novel method showed little variation of gap fraction across different REVs in both dense and spares canopies across diverse range of solar zenith angles. The perforated panel experiment, which was used to test the accuracy of the estimated gap fraction, confirmed that the novel method resulted in the accurate and consistent gap fractions across different hole sizes, gap fractions and solar zenith angles. These findings highlight that the novel method opens new opportunities to estimate gap fraction accurately during daytime from sparse to dense canopies, which will be useful in monitoring LAI precisely and validating satellite remote sensing LAI products efficiently.

  20. Influences of specific land use/land cover conversions on climatological normals of near-surface temperature

    USGS Publications Warehouse

    Hale, Robert C.; Gallo, Kevin P.; Loveland, Thomas R.

    2008-01-01

    Quantification of the effects of land use/land cover (LULC) changes on proximal measurements of near-surface air temperature is crucial to a better understanding of natural and anthropogenically induced climate change. In this study, data from stations utilized in deriving U.S. climatological temperature normals were analyzed in conjunction with NCEP-NCAR 50-Year Reanalysis (NNR) estimates and highly accurate LULC change maps in order to isolate the effects of LULC change from other climatological factors. While the “Normals” temperatures exhibited considerable warming in both minima and maxima, the NNR data revealed that the majority of the warming of maximum temperatures was not due to nearby LULC change. Warming of minimum temperatures was roughly evenly split between the effects of LULC change and other influences. Furthermore, the effects of LULC change varied considerably depending upon the particular type of land cover conversion that occurred. Urbanization, in particular, was found to result in warming of minima and maxima, while some LULC conversions that might be expected to have significantly altered nearby temperatures (e.g., clear-cutting of forests) did not.

  1. Land use and land cover change in the North Central Appalachians ecoregion

    USGS Publications Warehouse

    Napton, D.E.; Sohl, T.L.; Auch, R.F.; Loveland, T.R.

    2003-01-01

    The North Central Appalachians ecoregion, spanning northern Pennsylvania and southern New York, has a long history of land use and land cover change. Turn-of-the-century logging dramatically altered the natural landscape of the ecoregion, but subsequent regeneration returned the ecoregion to a forest dominated condition. To understand contemporary land use and land cover changes, the U.S. Geological Survey with NASA and the U.S. Environmental Protection Agency used a random sample of satellite remotely sensed data for 1973, 1980, 1986, 1992, and 2000 to estimate the rates and assess the primary drivers of change in the North Central Appalachians. The overall change was 6.2%. The 1973-1980 period had the lowest rate of change (1.5%); the highest rate (2.9%) occurred during the 1992-2000 period. The primary conversions were deforestation through harvesting and natural disturbance (i.e., tornados) followed by regeneration, and conversion of forests to mining and urban lands. The primary drivers of the change included changes in access, energy and forest prices, and attitudes toward the environment.

  2. Land use, land cover change analysis with multitemporal remote sensing data

    NASA Astrophysics Data System (ADS)

    Suzanchi, K.; Sahoo, R. N.; Kalra, N.; Pandey, S.

    2006-12-01

    Presently, unplanned changes of land use have become a major problem. Most land use changes occur without a clear and logical planning with little attention to their environmental impacts. In last four-decade, urban growth in Delhi has occurred rapidly in some unwanted direction and destroyed valuable agriculture lands in its surround. Rapid changes in land use / cover occurring over large areas; remote sensing technology is an essential and useful tool in monitoring of this area. Monitoring of land use/cover change are increasingly reliant on information derived from remotely sensed data. Such information provides the data link to other techniques to understand the human processes behind these changes. Specially, in agricultural area in suburb (or countryside) of a metropolitan city like Delhi. In this paper different change detection approaches (such as Post classification comparison and spectral change detection techniques) were evaluated with available images of National Capital Territory of Delhi during 1973 to 2001. These techniques were analyzed independently, using the concept of well-known procedures to define the best approach/methodology for addressing the change detection issues in this study.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

    Mercury is an important pollutant that can be transported globally due to its long lifetime in the atmosphere. Atmosphere-surface exchange is a major process affecting the cycling of mercury in the global environment and its impacts on food webs. We investigate the sensitivities of the air-surface exchange, atmospheric transport, and budget of mercury to projected 2000-2050 changes in climate and land use/land cover with a global chemical transport model (GEOS-Chem). We find that annual mean Hg(0) dry deposition flux over land could increase by up to 20% in northern mid-latitudes by 2050 due to increased vegetation and foliage density. Climate change can significantly affect both the wet deposition and atmospheric chemistry of mercury. In response to the projected climate change, the annual mean wet deposition flux increases over most continental regions and decreases over most of the mid-latitude and tropical oceans. The annual mean mercury wet deposition flux over northern and southern high latitudes increases by 7% and 8% respectively, largely driven by increases in precipitation there. Surface Hg(0) is predicted to increase generally, because high temperatures decrease Hg(0) oxidation by bromine and high moisture increases aqueous Hg(II) photo reduction. The combined effects of projected changes in climate, land use and land cover increase mercury deposition to the continental biosphere and decrease mercury deposition to the marine biosphere.

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

    PubMed

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

    2016-01-01

    There are both semantic and technical differences between land use (LU) and land cover (LC) measurements. In cartographic approaches, these differences are often neglected, giving rise to a hybrid classification. The aim of this paper is to provide a better understanding and characterization of the two classification schemes using a comparison that allows maximization of the informative power of both. The analysis was carried out in the Molise region (Central Italy) using sample information from the Italian Land Use Inventory (IUTI). The sampling points were classified with a visual interpretation of aerial photographs for both LU and LC in order to estimate surfaces and assess the changes that occurred between 2000 and 2012. The results underscore the polarization of land use and land cover changes resulting from the following: (a) recolonization of natural surfaces, (b) strong dynamisms between the LC classes in the natural and semi-natural domain and (c) urban sprawl on the lower hills and plains. Most of the observed transitions are attributable to decreases in croplands, natural grasslands and pastures, owing to agricultural abandonment. The results demonstrate that a comparison between LU and LC estimates and their changes provides an understanding of the causes of misalignment between the two criteria. Such information may be useful for planning policies in both natural and semi-natural contexts as well as in urban areas. PMID:26687091

  5. Application of Time Series Landsat Images to Examining Land-use/Land-cover Dynamic Change.

    PubMed

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

    2012-07-01

    A hierarchical-based classification method was designed to develop time series land-use/land-cover datasets from Landsat images between 1977 and 2008 in Lucas do Rio Verde, Mato Grosso, Brazil. A post-classification comparison approach was used to examine land-use/land-cover change trajectories, which emphasis is on the conversions from vegetation or agropasture to impervious surface area, from vegetation to agropasture, and from agropasture to regenerating vegetation. Results of this research indicated that increase in impervious surface area mainly resulted from the loss of cerrado in the initial decade of the study period and from loss of agricultural lands in the last two decades. Increase in agropasture was mainly at the expense of losing cerrado in the first two decades and relatively evenly from the loss of primary forest and cerrado in the last decade. When impervious surface area was less than approximately 40 km(2) before 1999, impervious surface area was negatively related to cerrado and forest, and positively related to agropasture areas, but after impervious surface area reached 40 km(2) in 1999, no obvious relationship exists between them. PMID:25328256

  6. A review and evaluation of alternatives for updating U.S. Geological Survey land use and land cover maps

    USGS Publications Warehouse

    Milazzo, Valerie A.

    1980-01-01

    Since 1974, the U.S. Geological Survey has been engaged in a nationwide program of baseline mapping of land use and land cover and associated data at a scale of 1:250,000. As l:100,000-scale bases have become available, they have been used for mapping certain areas and for special applications. These two scales are appropriate for mapping land use and land cover data on a nationwide basis within a practical time frame, and with an acceptable degree of standardization, accuracy, and level of detail. An essential requisite to better use of the land is current information on land use and land cover conditions and on the rates and trends of changes with time. Thus, plans are underway to update these maps and data. The major considerations in planning a nationwide program for updating U.S. Geological Survey land use and land cover maps are as follows: (1) How often should maps be updated? (2) What remotely sensed source materials should be used for detecting and compiling changes in land use and land cover? (3) What base maps should be used for presenting data on land use and land cover changes? (4) What maps or portions of a map should be updated? (5) What methods should be used for identifying and mapping changes? (6) What procedures should be followed for updating maps and what formats should be used? These factors must be considered in developing a map update program that portrays an appropriate level of information, relates to and builds upon the existing U.S. Geological Survey land use and land cover digital and statistical data base, is timely, cost-effective and standardized, and meets the varying needs of land use and land cover data users.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  8. A critical analysis of EM based fusion of different polarization data for effect on land cover classification

    NASA Astrophysics Data System (ADS)

    Mittal, Vikas; Singh, D.; Saini, L. M.

    2015-09-01

    Land cover classification is an important activity in social, economical, geographical, ecological and risk planning of a country. Production of accurate land cover maps autonomously is still a challenging problem. It motivates the study and evolution of methods to tackle this problem. The purpose of the present study is to critically analyze the effects of image fusion on various land cover classification. The importance of using different polarizations of the single SAR data has been emphasized. A simplified EM algorithm for fusion of different permutations and combinations of multi-polarized PALSAR data is presented through modeling that is valid for Gaussian as well as non-Gaussian distortions. K-means unsupervised algorithm has been applied for the classification of various land cover i.e. water, urban, wetland, baresoil, short vegetation and tall vegetation. The proposed method is intuitive and simple in that it uses PALSAR data after pre-processing straightaway without any transformations and also estimates the missing information in each of the channel without any a priori knowledge. A critical analysis of fusion effects on different land covers is presented on the basis of various accuracies. This type of study will be helpful in further enhancing accuracy of land cover maps minimizing human intervention.

  9. Improving the quantification of land cover pressure on stream ecological status at the riparian scale using High Spatial Resolution Imagery

    NASA Astrophysics Data System (ADS)

    Tormos, T.; Kosuth, P.; Durrieu, S.; Villeneuve, B.; Wasson, J. G.

    The aim of this paper is to demonstrate the interest of High Spatial Resolution Imagery (HSRI) and the limits of coarse land cover data such as CORINE Land Cover (CLC), for the accurate characterization of land cover structure along river corridors and of its functional links with freshwater ecological status on a large scale. For this purpose, we compared several spatial indicators built from two land cover maps of the Herault River corridor (southern France): one derived from the CLC database, the other derived from HSRI. The HSRI-derived map was obtained using a supervised object-based classification of multi-source remotely-sensed images (SPOT 5 XS-10 m and aerial photography-0.5 m) and presents an overall accuracy of 70%. The comparison between the two sets of spatial indicators highlights that the HSRI-derived map allows more accuracy in the quantification of land cover pressures near the stream: the spatial structure of the river landscape is finely resolved and the main attributes of riparian vegetation can be quantified in a reliable way. The next challenge will consist in developing an operational methodology using HSRI for large-scale mapping of river corridor land cover, for spatial indicator computation and for the development of related pressure/impact models, in order to improve the prediction of stream ecological status.

  10. Selawik National Wildlife Refuge land cover mapping project users guide

    USGS Publications Warehouse

    Markon, Carl J.

    1988-01-01

    The U.S. Fish & Wildlife Service (USFWS) has the responsibility for collecting the resource information to address the research, management, development and planning requirements identified in Section 304. Because of the brief period provided by the Act for data collection, habitat mapping, and habitat assessment, the USFWS in cooperation with the U.S. Geological Survey's EROS Field Office, used digital Landsat multispectral scanner (MSS) data and digital terrain data to produce land cover and terrain maps. A computer assisted digital analysis of Landsat MSS data was used because coverage by aerial photographs was incomplete for the refuge and because the level of detail obtained from Landsat data was adequate to meet most USFWS research, management and planning needs. Relative cost and time requirements were also factors in the decision to use the digital analysis approach.

  11. Tetlin National Wildlife Refuge land cover mapping project users guide

    USGS Publications Warehouse

    Markon, Carl J.

    1987-01-01

    The U. S. Fish & Wildlife Service (USFWS) has the responsibility for collecting the resource information to address the research, management, development and planning requirements identified in Section 304. Because of the brief period provided by the Act for data collection, habitat mapping, and habitat assessment, the USFWS in cooperation with the U.S. Geological Survey's EROS Field Office, used digital Landsat multispectral scanner data (MSS) and digital terrain data to produce land cover and terrain maps. A computer assisted digital analysis of Landsat MSS data was used because coverage by aerial photographs was incomplete for much of the refuge and because the level of detail, obtained from the analysis of Landsat data, is adequate to meet most USFWS research, management and planning needs. Relative cost and time requirements were also factors in the decision to use the digital analysis approach.

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

    USGS Publications Warehouse

    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.

  13. Online change detection: Monitoring land cover from remotely sensed data

    SciTech Connect

    Fang, Yi; Ganguly, Auroop R; Singh, Nagendra; Vijayaraj, Veeraraghavan; Feierabend, Robert Neal; Potere, David T

    2006-01-01

    We present a fast and statistically principled approach to land cover change detection. A reference statistical distribution is fitted to prior data based on off-line analysis, and an adaptive metric based on the exponentially weighted moving average (EWMA) of normal scores derived from p-values are tracked for new or streaming data, leading to alarms for large or sustained change. Methods which can track the origin of the change are also discussed. The approach is illustrated with a geographic application which involves monitoring remotely sensed data to detect changes in the normalized difference vegetation index (NDVI) in near real-time. We use Wal-Mart store openings as a nontraditional way to monitor and validate known cases of NDVI change. The proposed approach performs well on this validation dataset.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  15. Annual Land Cover Change Impacts on Mount Kilimanjaro

    NASA Astrophysics Data System (ADS)

    Fairman, J. G.; Nair, U. S.; Christopher, S. A.

    2011-12-01

    Glacier recession on Kilimanjaro has been linked to reduction in precipitation and cloudiness largely due to large scale changes in tropical climate. Prior research has shown that land use change can alter the local patterns and elevational distribution of cloud cover and precipitation via changes in upwind temperature, moisture, and wind speed but are limited in time to the dry season, which does not address any questions about effects on convective activity on the peak. This study uses the Regional Atmospheric Modeling System to simulate orographic cloudiness, rainfall and orographic flow patterns over Kilimanjaro for current, deforested and reforested land cover scenarios at one kilometer grid spacing for one year, ranging from July 2007 through June 2008. On average, total deforestation causes temperature increases of 0.1-0.2 K at elevations from 2000-3000 m, along with moisture decreases up to 0.2 g/kg. Wind speeds are uniformly increased over deforested areas by values up to 1 m/s, causing an increase in convergence leading to enhanced vertical velocity. Clouds occur less frequently on average with decreasing amounts of forested area, however there is little difference in cloud frequency at elevations over 4000 m. Factors governing these orographic processes such as surface level moisture availability, temperature, and wind speed are examined for times of cloud and precipitation occurrence at high elevations for these three scenarios. Both the reforested and deforested scenarios increase precipitation at the peak compared to the current day, but act in this manner due to differing mechanisms. Afforestation increases local precipitation generation via the thermal circulation and diurnal processes. In contrast, deforestation causes a greater dependence on high synoptic moisture availability, which combined with enhanced updrafts leads to more precipitation occurring at elevations exceeding 5000 m.

  16. The Spatiotemporal Land use/cover Change of Adana City

    NASA Astrophysics Data System (ADS)

    Akın, A.; Erdoğan, M. A.; Berberoğlu, S.

    2013-10-01

    The major driving factors for land use planning are largely limited to socio-economic inputs that do not completely represent the spatio-temporal patterns and ecological inputs have often been neglected. Integration of remote sensing and GIS techniques enabled successful applications in characterizing the spatiotemporal trends of land use/land cover (LULC) change. This study demonstrated an approach that combines remote sensing, landscape metrics, and LULC change analysis as a promising tool for understanding spatiotemporal patterns of Adana city. Calculation of spatial metrics was based on a categorical, patch-based representation of the landscape. Landscape metrics are conceptual framework for sustainable landscape and ecological planning. LULC change analysis was performed by considering the metric calculation. Post-classification technique was used for the metric based change detection and two different remotely sensed data set recorded in 1967 (CORONA) and 2007 (ALOS AVNIR) were used for the analysis. Additionally, a LULC projection for the year 2023 was also generated and integrated to the change analysis. SLEUTH model was utilised as a urban growth model for the future developments of study area in the scope of Cellular Automata (CA). SLEUTH model contains the main elements that characterize the core characteristics of CA: it works in a grid space of homogeneous cells, with a neighburhood of eight cells, two cell states and five transition rules that act in sequential time steps. Most useful and relevant metrics for landscape including: percentage of landscape, patch density, edge density, largest patch index, Euclidian mean nearest neighbor distance, area weighted mean patch fractal dimension and contagion were calculated for the 1967, 2007 and 2023 LULC maps and temporal changes were determined for the study area. Most considerable change was observed on the agricultural areas. Urban sprawl is the major driving factor of the LULC change.

  17. FINDINGS ON THE USE OF LANDSAT-3 RETURN BEAM VIDICON IMAGERY FOR DETECTING LAND USE AND LAND COVER CHANGES.

    USGS Publications Warehouse

    Milazzo, Valerie A.

    1983-01-01

    The spatial resolution of imagery from the return beam vidicon (RBV) camera aboard the Landsat-3 satellite suggested that such data might prove useful in inspecting land use and land cover maps. In this study, a 1972 land use and land cover map derived from aerial photographs is compared with a 1978 Landsat RBV image to delineate areas of change. Findings indicate RBV imagery useful in establishing the fact of change and in identifying gross category changes.

  18. Managing water services in tropical regions: From land cover proxies to hydrologic fluxes.

    PubMed

    Ponette-González, Alexandra G; Brauman, Kate A; Marín-Spiotta, Erika; Farley, Kathleen A; Weathers, Kathleen C; Young, Kenneth R; Curran, Lisa M

    2015-09-01

    Watershed investment programs frequently use land cover as a proxy for water-based ecosystem services, an approach based on assumed relationships between land cover and hydrologic outcomes. Water flows are rarely quantified, and unanticipated results are common, suggesting land cover alone is not a reliable proxy for water services. We argue that managing key hydrologic fluxes at the site of intervention is more effective than promoting particular land-cover types. Moving beyond land cover proxies to a focus on hydrologic fluxes requires that programs (1) identify the specific water service of interest and associated hydrologic flux; (2) account for structural and ecological characteristics of the relevant land cover; and, (3) determine key mediators of the target hydrologic flux. Using examples from the tropics, we illustrate how this conceptual framework can clarify interventions with a higher probability of delivering desired water services than with land cover as a proxy. PMID:25432319

  19. Identification of Bogor regency land cover change index based on geospatial data

    NASA Astrophysics Data System (ADS)

    Virtriana, Riantini; Sumarto, Irawan; Deliar, Albertus; Pasaribu, Udjianna S.; Taufik, Moh.

    2015-04-01

    Based on Indonesia Disaster Risk Index (IRBI), Bogor Regency entered the ranks 5th most disaster-prone areas in Indonesia. This rank shows that the Bogor Regency has a variety of areas that are prone to disasters. In an effort to anticipate the existing conditions is to controlling land cover change in Bogor regency. Uncontrolled human activities on land cover may cause a negative impact on the environment both locally and globally. To determine the pattern of land cover change, required an analysis of an index of land cover change that might happen. Methodology for this research for identification index patterns of land cover change are using overlay analysis of land cover data at different time periods. The results of this study shows index of land cover change in regional scale, with the accuracy 83,645 %.

  20. Beyond Impervious: Urban Land-Cover Pattern Variation and Implications for Watershed Management

    NASA Astrophysics Data System (ADS)

    Beck, Scott M.; McHale, Melissa R.; Hess, George R.

    2016-07-01

    Impervious surfaces degrade urban water quality, but their over-coverage has not explained the persistent water quality variation observed among catchments with similar rates of imperviousness. Land-cover patterns likely explain much of this variation, although little is known about how they vary among watersheds. Our goal was to analyze a series of urban catchments within a range of impervious cover to evaluate how land-cover varies among them. We then highlight examples from the literature to explore the potential effects of land-cover pattern variability for urban watershed management. High-resolution (1 m2) land-cover data were used to quantify 23 land-cover pattern and stormwater infrastructure metrics within 32 catchments across the Triangle Region of North Carolina. These metrics were used to analyze variability in land-cover patterns among the study catchments. We used hierarchical clustering to organize the catchments into four groups, each with a distinct landscape pattern. Among these groups, the connectivity of combined land-cover patches accounted for 40 %, and the size and shape of lawns and buildings accounted for 20 %, of the overall variation in land-cover patterns among catchments. Storm water infrastructure metrics accounted for 8 % of the remaining variation. Our analysis demonstrates that land-cover patterns do vary among urban catchments, and that trees and grass (lawns) are divergent cover types in urban systems. The complex interactions among land-covers have several direct implications for the ongoing management of urban watersheds.

  1. A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed

    USGS Publications Warehouse

    2011-01-01

    Trends derived from multitemporal land-cover data can be used to make informed land management decisions and to help managers model future change scenarios. We developed a multitemporal land-use/land-cover dataset for the binational Santa Cruz watershed of southern Arizona, United States, and northern Sonora, Mexico by creating a series of land-cover maps at decadal intervals (1979, 1989, 1999, and 2009) using Landsat Multispectral Scanner and Thematic Mapper data and a classification and regression tree classifier. The classification model exploited phenological changes of different land-cover spectral signatures through the use of biseasonal imagery collected during the (dry) early summer and (wet) late summer following rains from the North American monsoon. Landsat images were corrected to remove atmospheric influences, and the data were converted from raw digital numbers to surface reflectance values. The 14-class land-cover classification scheme is based on the 2001 National Land Cover Database with a focus on "Developed" land-use classes and riverine "Forest" and "Wetlands" cover classes required for specific watershed models. The classification procedure included the creation of several image-derived and topographic variables, including digital elevation model derivatives, image variance, and multitemporal Kauth-Thomas transformations. The accuracy of the land-cover maps was assessed using a random-stratified sampling design, reference aerial photography, and digital imagery. This showed high accuracy results, with kappa values (the statistical measure of agreement between map and reference data) ranging from 0.80 to 0.85.

  2. Extending the Anthropocene? Synthesizing Land Use and land cover data for the Holocene, a new global working group

    NASA Astrophysics Data System (ADS)

    Morrison, K. D.

    2015-12-01

    Outside the geophysical sciences, the concept of the Anthropocene has been enthusiastically received. Its meaning, however, has been expanded beyond its original compass to suggest that humans have only recently had a significant impact on global processes. This is unfortunate, since paleoecological and archaeological data suggest significant anthropogenic transformation of land cover and land forms by the mid-Holocene. A new working group, LandCover 6k, is working to aggregate and synthesize global land use and land cover data across the Holocene in order to address these transformations more precisely.

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

    NASA Astrophysics Data System (ADS)

    Crum, S.; Jenerette, D.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  5. A regional analysis of drivers and impacts of land cover change and long-term land cover trends in the Great Basin, United States

    NASA Astrophysics Data System (ADS)

    Bradley, Bethany Adella

    An improved understanding of land use/land cover change at local and regional scales is important in an increasingly human-dominated biosphere. The land surface provides resources necessary for human survival (e.g., cropland, water, raw materials) as well as providing other services such as habitat for native species, carbon storage, and nutrient cycling. A goal of land change science is to identify where land cover change is taking place, understand how land use may affect that change, and determine what the consequences of change may be. In the Great Basin Desert of the Western U.S., an important form of land cover change is invasion by non-native cheatgrass (Bromus tectorum). Cheatgrass invasion destroys native shrub ecosystems, leading to a loss of biodiversity, loss of viable rangeland and increased fire frequency. In this work, I show how remote sensing can be used to detect the regional and local extents of cheatgrass invasion. Remote sensing results are then used to assess the spatial patterns of cheatgrass invasion over time to determine how land use might have affected invasion. Further, I consider the long-term impacts of cheatgrass invasion on biodiversity and carbon storage in the Great Basin. In addition to an analysis of cheatgrass, this thesis presents a new methodology for time series modeling, which can be used to better interpret annual and inter-annual vegetation community phenology. I apply this modeling methodology to all land cover in the Great Basin to assess long-term land cover trends and localized anomalous response within the range of land cover classes present. By investigating regional land cover change I am able to provide more detailed analysis of the drivers of change for land managers while working at a scale relevant to studies of global environmental change.

  6. Dynamic Predictions of Semi-Arid Land Cover Change

    NASA Astrophysics Data System (ADS)

    Foster-Wittig, T. A.

    2011-12-01

    hypothesized that the combined effects of climate change and land use lead to a destabilization of the grass-tree state and an increased tendency toward a state of desertification. If desertification is considered to be irreversible degradation, it can be detrimental not only to plant-life but also to the livelihood of those whom consider the savanna their home. Because a large population lives in savanna ecosystems, it is important to study them to hopefully be able to make changes now before conditions become irreversible. Resources: Falkenmark, M., and Rockstrom, Johan (2008). "Building Resilience to Drought in Desertification-Prone Savannas in Sub-Saharan Africa: The Water Perspective." Natural Resources Forum 32: 93-102. Sankaran, M., Hanan, Niall P., Scholes, Robert J., Ratnman, Jayashree, Augustine, David J. , et al (2005). "Determinants of Woody Cover in African Savannas." Nature 438(8): 846-849. Scanlon, T., J.D. Albertson, K.K. Caylor, & C.A.Willaims (2002). "Determining Land Surface Fractional Cover from NDVI and Rainfall Time Series for a Savanna Ecosystem." Remote Sensing of Environment. 82:376-388. Williams, C., and Albertson, J. (2005). "Contrasting Short- and Long-Timescale Effects of Vegetation Dynamics on Water and Carbon Fluxes in Water-Limited Ecosystems." Water Resources Research. 41: 1-13

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

    USGS Publications Warehouse

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

    2016-01-01

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

  8. Land User and Land Cover Maps of Europe: a Webgis Platform

    NASA Astrophysics Data System (ADS)

    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.

  9. Conterminous United States Surface Radiative Forcing due to Contemporary Land Cover Land Use Albedo Change

    NASA Astrophysics Data System (ADS)

    Barnes, C. A.; Roy, D. P.

    2012-12-01

    Recently available Landsat land cover land use (LCLU) change information for four epochs, 1973-1980, 1980-1986, 1986-1992 and 1992-2000, and MODerate Resolution Imaging Spectroradiometer (MODIS) albedo and snow cover data are used to estimate LCLU albedo change surface radiative forcing for the conterminous United States (CONUS) for each epoch and for 1973 to 2000. Landsat 10 × 10 km or 20 × 20 km LCLU classification maps for 1973, 1980, 1986, 1992 and 2000 located using a stratified random sampling methodology with respect to 84 contiguous CONUS ecoregions are used to provide ecoregion and CONUS estimates. A CONUS scale warming (0.0037 Wm-2) due to LCLU albedo change from 1973 to 2000 is estimated associated with decreasing agricultural and forested lands and increasing developed and grassland/shrublands. The 1986 to 1992 period had the highest overall CONUS forcing (0.0093 Wm-2) due to agricultural land conversion, attributed primarily to the 1985 Farm Bill that established the Conservation Reserve Program. The radiative forcing for individual ecoregions varied geographically in sign and magnitude, with the most negative forcings (as low as -0.8630 Wm-2) due to forest loss, and the most positive forcings (up to 0.2640 Wm-2) due to the conversion of grasslands/shrublands. These results make an important contribution to quantifying the role of LCLU change on the climate system, and underscore the need for repeat, wall-to-wall, spatially-explicit national LCLU mapping.

  10. Assessing the use of subgrid land model output to study impacts of land cover change

    NASA Astrophysics Data System (ADS)

    Schultz, Natalie M.; Lee, Xuhui; Lawrence, Peter J.; Lawrence, David M.; Zhao, Lei

    2016-06-01

    Subgrid information from land models has the potential to be a powerful tool for investigating land-atmosphere interactions, but relatively few studies have attempted to exploit subgrid output. In this study, we modify the configuration of the Community Land Model version CLM4.5 so that each plant functional type (PFT) is assigned its own soil column. We compare subgrid and grid cell-averaged air temperature and surface energy fluxes from this modified case (PFTCOL) to a case with the default configuration—a shared soil column for all PFTs (CTRL)—and examine the difference in simulated surface air temperature between grass and tree PFTs within the same grid cells (ΔTGT). The magnitude and spatial patterns of ΔTGT from PFTCOL agree more closely with observations, ranging from -1.5 K in boreal regions to +0.6 K in the tropics. We find that the column configuration has a large effect on PFT-level energy fluxes. In the CTRL configuration, the PFT-level annual mean ground heat flux (G) differs substantially from zero. For example, at a typical tropical grid cell, the annual G is 31.8 W m-2 for the tree PFTs and -14.7 W m-2 for grass PFTs. In PFTCOL, G is always close to zero. These results suggest that care must be taken when assessing local land cover change impacts with subgrid information. For models with PFTs on separate columns, it may be possible to isolate the differences in land surface fluxes between vegetation types that would be associated with land cover change from other climate forcings and feedbacks in climate model simulations.

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

    SciTech Connect

    Garten Jr., C.T.

    2004-02-09

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

  12. Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

    NASA Astrophysics Data System (ADS)

    Ban, Yifang; Gong, Peng; Giri, Chandra

    2015-05-01

    Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.

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

    PubMed

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

    2012-01-01

    Irrigation along the Nile River has resulted in dramatic changes in the biophysical environment of Upper Egypt. In this study we used a combination of MODIS 250 m NDVI data and Landsat imagery to identify areas that changed from 2001-2008 as a result of irrigation and water-level fluctuations in the Nile River and nearby water bodies. We used two different methods of time series analysis -- principal components (PCA) and harmonic decomposition (HD), applied to the MODIS 250 m NDVI images to derive simple three-class land cover maps and then assessed their accuracy using a set of reference polygons derived from 30 m Landsat 5 and 7 imagery. We analyzed our MODIS 250 m maps against a new MODIS global land cover product (MOD12Q1 collection 5) to assess whether regionally specific mapping approaches are superior to a standard global product. Results showed that the accuracy of the PCA-based product was greater than the accuracy of either the HD or MOD12Q1 products for the years 2001, 2003, and 2008. However, the accuracy of the PCA product was only slightly better than the MOD12Q1 for 2001 and 2003. Overall, the results suggest that our PCA-based approach produces a high level of user and producer accuracies, although the MOD12Q1 product also showed consistently high accuracy. Overlay of 2001-2008 PCA-based maps showed a net increase of 12 129 ha of irrigated vegetation, with the largest increase found from 2006-2008 around the Districts of Edfu and Kom Ombo. This result was unexpected in light of ambitious government plans to develop 336 000 ha of irrigated agriculture around the Toshka Lakes. PMID:21766045

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

    PubMed Central

    FULLER, DOUGLAS O.; PARENTI, MICHAEL S.; GAD, ADEL M.; BEIER, JOHN C.

    2011-01-01

    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. PMID:21766045

  15. Comparing and Contrasting the Benefits of Land Mass vs. Land Cover on Storm Surge Attenuation

    NASA Astrophysics Data System (ADS)

    Siverd, C. G.; Hagen, S. C.; Bilskie, M. V.; Twilley, R.; Braud, D.; Peele, H.

    2015-12-01

    From 1930 through 2012 Louisiana lost approximately 1,880 sq mi (4,870 sq km) of coastal wetlands due to land subsidence, erosion, and sea level rise among other factors. Louisiana could potentially lose an additional 1,750 sq mi (4,530 sq km) of coastal wetlands by 2062 if no action is taken to prevent this land loss (CPRA, 2012). If risk is defined as probability multiplied by consequence (Vrijling, 2006), such land loss will significantly increase the risk of flooding in coastal communities and communities located farther inland. Vital coastal infrastructure will also be at a heightened risk of flood damage. This will be attributable to the increase in frequency of hurricane storm surge events featuring greater depths and farther inland extent. This risk can be described by contrasting the surface area of land and water along the Louisiana coast. Using aerial or satellite imagery, isopleths can be plotted along the coast that describe the land to water (L:W) ratio over time (e.g., Gagliano et al., 1970, 1971 plotted the calculated 50% L:W ratio isopleths for the years 1930, and 1970, with an estimated 2000 isopleth). Risk to coastal infrastructure and coastal communities increases as the L:W ratio is reduced. One possible way to reduce the depth and extent of storm surge is to increase the land area along the coast. A second way is to modify the land cover (i.e. vary the type and density of vegetation). The L:W ratio can be used to quantify storm surge attenuation and assess such contributing factors. For this study, storm surge is simulated along coastal Louisiana for various instances - with increased land area and separately with different land cover types and densities - to determine which of these factors most effectively reduce the depth and extent of storm surge. New metrics involving hydrologic basins for evaluating storm surge attenuation are also described. The results of this study should inform policy makers which factors contribute the most to storm

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

    PubMed

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

    2012-10-01

    Changes in land use and land cover have affected and will continue to affect biological diversity worldwide. Yet, understanding the spatially extensive effects of land-cover change has been challenging because data that are consistent over space and time are lacking. We used the U.S. National Land Cover Dataset Land Cover Change Retrofit Product and North American Breeding Bird Survey data to examine land-cover change and its associations with diversity of birds with principally terrestrial life cycles (landbirds) in the conterminous United States. We used mixed-effects models and model selection to rank associations by ecoregion. Land cover in 3.22% of the area considered in our analyses changed from 1992 to 2001, and changes in species richness and abundance of birds were strongly associated with land-cover changes. Changes in species richness and abundance were primarily associated with changes in nondominant types of land cover, yet in many ecoregions different types of land cover were associated with species richness than were associated with abundance. Conversion of natural land cover to anthropogenic land cover was more strongly associated with changes in bird species richness and abundance than persistence of natural land cover in nearly all ecoregions and different covariates were most strongly associated with species richness than with abundance in 11 of 17 ecoregions. Loss of grassland and shrubland affected bird species richness and abundance in forested ecoregions. Loss of wetland was associated with bird abundance in forested ecoregions. Our findings highlight the value of understanding changes in nondominant land cover types and their association with bird diversity in the United States. PMID:22731630

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

    PubMed

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

    2015-03-01

    Maps of continental-scale land cover are utilized by a range of diverse users but whilst a range of products exist that describe present and recent land cover in Europe, there are currently no datasets that describe past variations over long time-scales. User groups with an interest in past land cover include the climate modelling community, socio-ecological historians and earth system scientists. Europe is one of the continents with the longest histories of land conversion from forest to farmland, thus understanding land cover change in this area is globally significant. This study applies the pseudobiomization method (PBM) to 982 pollen records from across Europe, taken from the European Pollen Database (EPD) to produce a first synthesis of pan-European land cover change for the period 9000 bp to present, in contiguous 200 year time intervals. The PBM transforms pollen proportions from each site to one of eight land cover classes (LCCs) that are directly comparable to the CORINE land cover classification. The proportion of LCCs represented in each time window provides a spatially aggregated record of land cover change for temperate and northern Europe, and for a series of case study regions (western France, the western Alps, and the Czech Republic and Slovakia). At the European scale, the impact of Neolithic food producing economies appear to be detectable from 6000 bp through reduction in broad-leaf forests resulting from human land use activities such as forest clearance. Total forest cover at a pan-European scale moved outside the range of previous background variability from 4000 bp onwards. From 2200 bp land cover change intensified, and the broad pattern of land cover for preindustrial Europe was established by 1000 bp. Recognizing the timing of anthropogenic land cover change in Europe will further the understanding of land cover-climate interactions, and the origins of the modern cultural landscape. PMID:25345850

  18. Development of a land-cover characteristics database for the conterminous US

    USGS Publications Warehouse

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

    1991-01-01

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

  19. Analyzing Land Cover Change in Kazakhstan: Land Surface Phenology, Climatic Variation, and Sensor Artifacts

    NASA Astrophysics Data System (ADS)

    de Beurs, K. M.; Henebry, G. M.

    2003-12-01

    The collapse of the economic and political institutions of the Soviet Union in the early 1990s led to widespread agricultural de-intensification, land abandonment, loss of livestock, and decreased grazing pressure. In semi-arid to arid regions dominated by dryland agriculture and grazing, the quantification of land cover change must distinguish anthropogenic forcings from interannual climatic variation and the peculiarities associated with specific sensor systems. Were the land cover changes that occurred in Kazakhstan following independence in 1991 of sufficient magnitude to alter the land surface phenology at resolutions relevant to climate models? To explore this question it is necessary first to partition the sources of variation in the image archive. We used the standard Pathfinder AVHRR Land (PAL) dataset, which consists of global 10 d maximum NDVI composites from 7/1981 to 9/2001 at 8 km resolution. To what extent are the PAL data affected by sensor artifacts that may mask other kinds of change? We evaluated 19 subsets of 1600 sq km, one for each ecoregion of Kazakhstan as delineated by the World Wildlife Fund. To minimize residual cloud contamination in the PAL data, a modified version of the best index slope extraction algorithm was applied. The method filters distortions without altering the seasonal NDVI pattern. We pursued two complementary aspects of change analysis: (1) detection of trends within each sensor's tenure and (2) detection of trends and discontinuities across the entire observational period. Seasonal polynomial models of NDVI phenology were developed to relate accumulated growing degree-day with NDVI. To test for trends within periods, both the residuals and the filtered data were submitted to seasonal Mann-Kendall tests that were modified to correct for serial correlation. To identify discontinuities, the entire series was tested using the standard normal homogeneity test (SNHT) without trend. The Kruskal-Wallis test with Bonferroni

  20. Classifying Multi-year Land Use and Land Cover using Deep Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Seo, B.

    2015-12-01

    Cultivated ecosystems constitute a particularly frequent form of human land use. Long-term management of a cultivated ecosystem requires us to know temporal change of land use and land cover (LULC) of the target system. Land use and land cover changes (LUCC) in agricultural ecosystem is often rapid and unexpectedly occurs. Thus, longitudinal LULC is particularly needed to examine trends of ecosystem functions and ecosystem services of the target system. Multi-temporal classification of land use and land cover (LULC) in complex heterogeneous landscape remains a challenge. Agricultural landscapes often made up of a mosaic of numerous LULC classes, thus spatial heterogeneity is large. Moreover, temporal and spatial variation within a LULC class is also large. Under such a circumstance, standard classifiers would fail to identify the LULC classes correctly due to the heterogeneity of the target LULC classes. Because most standard classifiers search for a specific pattern of features for a class, they fail to detect classes with noisy and/or transformed feature data sets. Recently, deep learning algorithms have emerged in the machine learning communities and shown superior performance on a variety of tasks, including image classification and object recognition. In this paper, we propose to use convolutional neural networks (CNN) to learn from multi-spectral data to classify agricultural LULC types. Based on multi-spectral satellite data, we attempted to classify agricultural LULC classes in Soyang watershed, South Korea for the three years' study period (2009-2011). The classification performance of support vector machine (SVM) and CNN classifiers were compared for different years. Preliminary results demonstrate that the proposed method can improve classification performance compared to the SVM classifier. The SVM classifier failed to identify classes when trained on a year to predict another year, whilst CNN could reconstruct LULC maps of the catchment over the study

  1. Determining the Impacts of Land Cover/use Categories on Land Surface Temperature Using LANDSAT8-OLI

    NASA Astrophysics Data System (ADS)

    Bektas Balcik, F.; Ergene, E. M.

    2016-06-01

    Due to unplanned and uncontrolled expansion of urban areas, rural land cover types have been replaced with artificial materials. As a result of these replacements, a wide range of negative environmental impacts seriously impacting human health, natural areas, ecosystems, climate, energy efficiency, and quality of living in town center. In this study, the impact of land surface temperature with respect to land cover and land use categories is investigated and evaluated for Istanbul, Turkey. Land surface temperature data was extracted from 21 October 2014 dated Landsat 8 OLI data using mono-window algorithm. In order to extract land use/cover information from remotely sensed data wetness, greenness and brightness components were derived using Tasseled Cap Transformation. The statistical relationship between land surface temperature and Tasseled Cap Transformation components in Istanbul was analyzed using the regression methods. Correlation between Land Surface Temperature and Meteorological Stations Temperature calculated %74.49.

  2. Land cover classification by support vector machine: training set size and selection issues.

    NASA Astrophysics Data System (ADS)

    Mathur, A.; Foody, G.

    The accuracy of land cover maps derived via supervised classification is often insufficient for operational applications. One of the important reasons for this is associated with the inputs to supervised classification analyses, especially the training data. The aim of this poster paper is to highlight the effect of variation in training set size on classification accuracy with respect to a series of supervised classifiers with particular regard to identifying an approach to allow accurate classification from small training sets. The classifiers investigated are the widely used maximum-likelihood classifier (MLC), feedforward artificial neural networks (ANN), decision trees (DT) and support vector machines (SVM). An advanced pattern recognition technique that has recently attracted the attention of the remote sensing community is support vector machines (SVM). A key attraction of the SVM based approach to classification is that it seeks to fit an optimal hyperplane between the classes and since it uses only the training samples that lie at the edge of the class distributions in feature space it may require only a small training sample. The potential of SVM classification was demonstrated from a series of analyses that classified land cover from imagery of Feltwell, Norfolk, U.K. All four classifiers were able to classify land cover accurately, each > 90% correct. However, for training sets ranging in size from 15 to 100 samples per-class, the highest accuracy was derived from the SVM. Moreover, inspection of the number of support vectors used in each SVM classification indicated a potential to reduce training set size without any negative impact on classification accuracy. This requires a means to intelligently identify training samples and the second part of this poster focuses on one such approach, based on the use of ancillary data on soil type to direct training site acquisition. It is shown that with information on soil type, training sample acquisition can be

  3. Agricultural land cover mapping with the aid of digital soil survey data

    NASA Technical Reports Server (NTRS)

    Stoner, E. R.

    1982-01-01

    A study is recounted which assessed the effect of stratifying multidate Landsat MSS data on land cover classification accuracy. The study area covered 49,184 ha (121,534 acres) in Gentry County in northwestern Missouri. A pixel-by-pixel comparison of the two land cover classifications with field-verified land cover indicated improvements in identification of all cover types when land areas were stratified by soils. The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices, soil-induced crop development differences, and background reflectance characteristics.

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

    NASA Astrophysics Data System (ADS)

    Skriver, H.

    2013-12-01

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

  5. 25 CFR 162.103 - What types of land use agreements are covered by these regulations?

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 25 Indians 1 2011-04-01 2011-04-01 false What types of land use agreements are covered by these... WATER LEASES AND PERMITS General Provisions § 162.103 What types of land use agreements are covered by.... § 81, as amended; (5) Leases of water rights associated with Indian land, except to the extent the...

  6. 25 CFR 162.103 - What types of land use agreements are covered by these regulations?

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 25 Indians 1 2012-04-01 2011-04-01 true What types of land use agreements are covered by these... WATER LEASES AND PERMITS General Provisions § 162.103 What types of land use agreements are covered by.... § 81, as amended; (5) Leases of water rights associated with Indian land, except to the extent the...

  7. 25 CFR 162.103 - What types of land use agreements are covered by these regulations?

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false What types of land use agreements are covered by these... WATER LEASES AND PERMITS General Provisions § 162.103 What types of land use agreements are covered by.... § 81, as amended; (5) Leases of water rights associated with Indian land, except to the extent the...

  8. THEMATIC ACCURACY OF MRLC LAND COVER FOR THE EASTERN UNITED STATES

    EPA Science Inventory



    One objective of the MultiResolution Land Characteristics (MRLC) consortium is to map general land-cover categories for the conterminous United States using Landsat Thematic Mapper (TM) data. Land-cover mapping and classification accuracy assessment are complete for the e...

  9. US LAND-COVER MONITORING AND DETECTION OF CHANGES IN SCALE AND CONTEXT OF FOREST

    EPA Science Inventory

    Disparate land-cover mapping programs, previously focused solely on mission-oriented goals, have organized themselves as the Multi-Resolution Land Characteristics (MRLC) Consortium with a unified goal of producing land-cover nationwide at routine intervals. Under MRLC, United Sta...

  10. Mapping urban land cover from space: Some observations for future progress

    NASA Technical Reports Server (NTRS)

    Gaydos, L.

    1982-01-01

    The multilevel classification system adopted by the USGS for operational mapping of land use and land cover at levels 1 and 2 is discussed and the successes and failures of mapping land cover from LANDSAT digital data are reviewed. Techniques used for image interpretation and their relationships to sensor parameters are examined. The requirements for mapping levels 2 and 3 classes are considered.

  11. Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity

    NASA Astrophysics Data System (ADS)

    Paneque-Gálvez, Jaime; Mas, Jean-François; Moré, Gerard; Cristóbal, Jordi; Orta-Martínez, Martí; Luz, Ana Catarina; Guèze, Maximilien; Macía, Manuel J.; Reyes-García, Victoria

    2013-08-01

    Land use/cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land use/cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims at establishing an efficient classification approach to accurately map all broad land use/cover classes in a large, heterogeneous tropical area, as a basis for further studies (e.g., land use/cover change, deforestation and forest degradation). Specifically, we first compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbor and four different support vector machines - SVM), and hybrid (unsupervised-supervised) classifiers, using hard and soft (fuzzy) accuracy assessments. We then assess, using the maximum likelihood algorithm, what textural indices from the gray-level co-occurrence matrix lead to greater classification improvements at the spatial resolution of Landsat imagery (30 m), and rank them accordingly. Finally, we use the textural index that provides the most accurate classification results to evaluate whether its usefulness varies significantly with the classifier used. We classified imagery corresponding to dry and wet seasons and found that SVM classifiers outperformed all the rest. We also found that the use of some textural indices, but particularly homogeneity and entropy, can significantly improve classifications. We focused on the use of the homogeneity index, which has so far been neglected in land use/cover classification efforts, and found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM. We observed that improvements in producer's and user's accuracies through the inclusion of homogeneity were different

  12. Land-use and land-cover dynamics in the central rift valley of Ethiopia.

    PubMed

    Garedew, Efrem; Sandewall, Mats; Söderberg, Ulf; Campbell, Bruce M

    2009-10-01

    Understanding the complexity of land-use and land-cover (LULC) changes and their driving forces and impacts on human and environmental security is important for the planning of natural resource management and associated decision making. This study combines and compares participatory field point sampling (pfps) and remote sensing to explore local LULC dynamics. The study was conducted in two peasant associations located in the central Ethiopian Rift Valley, which is a dry-land mixed farming area exposed to rapid deforestation. From 1973-2006, the area of cropland doubled at the expense of woodland and wooded-grassland in both of the study sites. Major deforestation and forest degradation took place from 1973-1986; woodland cover declined from 40% to 9% in one of the study sites, while the other lost all of its original 54% woodland cover. Our study concludes that assessing LULC dynamics using a combination of remote sensing and pfps is a valuable approach. The two methods revealed similar LULC trends, while the pfps provided additional details on how farmers view the changes. This study documents dramatic trends in LULC over time, associated with rapid population growth, recurrent drought, rainfall variability and declining crop productivity. The alarming nature of these trends is reflected in a decrease in the livelihood security of local communities and in environmental degradation. Given these dry-land conditions, there are few opportunities to improve livelihoods and environmental security without external support. If negative changes are to be halted, action must be taken, including building asset bases, instituting family planning services, and creating opportunities outside these marginal environments. PMID:19688359

  13. Land Cover Vegetation Changes and Hydrology in Central Texas

    NASA Astrophysics Data System (ADS)

    Banta, J. R.; Slattery, R.

    2013-12-01

    Encroachment of woody vegetation into traditional savanna grassland ecosystems in central Texas has largely been attributed to land use practices of settlers, most notably overgrazing and fire suppression. Implementing changes in land cover vegetation (removing the woody vegetation and allowing native grasses to reestablish in the area, commonly referred to as brush management), could potentially change the hydrology in a watershed. The U.S. Geological Survey, in cooperation with several local, State, and Federal agencies, studied the hydrologic effects of ashe juniper (Juniperus ashei) removal as a brush management conservation practice in the Honey Creek State Natural Area in Comal County, Tex. Two adjacent watersheds of 104 and 159 hectares were used in a paired study. Rainfall, streamflow, evapotranspiration (Bowen ratio method), and water quality data were collected in both watersheds. Using a hydrologic mass balance approach, rainfall was allocated to surface-water runoff, evapotranspiration, and potential groundwater recharge. Groundwater recharge was not directly measured, but estimated as the residual of the hydrologic mass balance. After hydrologic data were collected in both watersheds for 3 years, approximately 80 percent of the woody vegetation (ashe juniper) was selectively removed from the 159 hectare watershed (treatment watershed). Brush management was not implemented in the other (reference) watershed. Hydrologic data were collected in both watersheds for six years after brush management implementation. The resulting data were examined for differences in the hydrologic budget between the reference and treatment watersheds as well as between pre- and post-brush management periods to assess effects of the treatment. Results indicate there are differences in the hydrologic budget and water quality between the reference and treatment watersheds, as well as between pre- and post-brush management periods.

  14. Land cover dynamics and accounts for European Union 2001-2011

    NASA Astrophysics Data System (ADS)

    Grekousis, George; Kavouras, Marinos; Mountrakis, Giorgos

    2015-06-01

    Land cover dynamics information plays an important role in environmental research and related studies. We use the 500m NASA MODIS land cover dataset for the European Union (EU28) to calculate (a) land cover share trends on an annual temporal increment from 2001 to 2011 and (b) land cover accounts from 2001 to 2011. Raster products are firstly mosaicked to produce a single image per year, covering the study area. Reclassification for each final annual product follows to convert the original 17 IGBP MODIS classes into 7 simpler classes of broader interest. Zonal statistics are used to calculate the number of land cover pixels per class, per country, per year. Further calculations create land account tables revealing land cover trends during 2001 through 2011. Results show that for the 2001 through 2011 period forests and cropland dominated EU28, covering almost 70% of the total area. Forest has an increasing trend, with an annual change rate of 0,60%, while cropland has a negative rate of annual change (-0, 46%). On average, grassland covers approximately 21% of EU28. A closer look reveals that despite the relatively stable overall counts, grassland has experienced high turnover. Almost half (40%) of grassland original stock changed to other land cover classes during 2001 through 2011. At the same time, there was a large conversion to grassland from other land cover classes thus keeping a balance in the overall share. Our analysis provides useful information for environmental assessments in order to better frame policies for a sustainable future.

  15. Terminology as a key uncertainty in net land use and land cover change carbon flux estimates

    NASA Astrophysics Data System (ADS)

    Pongratz, J.; Reick, C. H.; Houghton, R. A.; House, J. I.

    2014-03-01

    Reasons for the large uncertainty in land use and land cover change (LULCC) emissions go beyond recognized issues related to the available data on land cover change and the fact that model simulations rely on a simplified and incomplete description of the complexity of biological and LULCC processes. The large range across published LULCC emission estimates is also fundamentally driven by the fact that the net LULCC flux is defined and calculated in different ways across models. We introduce a conceptual framework that allows us to compare the different types of models and simulation setups used to derive land use fluxes. We find that published studies are based on at least nine different definitions of the net LULCC flux. Many multi-model syntheses lack a clear agreement on definition. Our analysis reveals three key processes that are accounted for in different ways: the land use feedback, the loss of additional sink capacity, and legacy (regrowth and decomposition) fluxes. We show that these terminological differences, alone, explain differences between published net LULCC flux estimates that are of the same order as the published estimates themselves. This has consequences for quantifications of the residual terrestrial sink: the spread in estimates caused by terminological differences is conveyed to those of the residual sink. Furthermore, the application of inconsistent definitions of net LULCC flux and residual sink has led to double-counting of fluxes in the past. While the decision to use a specific definition of the net LULCC flux will depend on the scientific application and potential political considerations, our analysis shows that the uncertainty of the net LULCC flux can be substantially reduced when the existing terminological confusion is resolved.

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

    PubMed Central

    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

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

    USGS Publications Warehouse

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

    2008-01-01

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

  18. VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013.

    PubMed

    Morse-McNabb, Elizabeth; Sheffield, Kathryn; Clark, Rob; Lewis, Hayden; Robson, Susan; Cherry, Don; Williams, Steve

    2015-01-01

    Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engagement to establish product requirements such as format, classification, frequency and spatial resolution. Its genesis is significantly different to traditional methods, incorporating data from a range of jurisdictions to develop land use information designed for regular on-going creation and consistency. Covering the entire landmass of Victoria, the dataset separately describes land tenure, land use and land cover. These variables are co-registered to a common spatial base (cadastral parcels) across the state for the period 2006 to 2013; biennially for land tenure and land use, and annually for land cover. Data is produced as a spatial GIS feature class. PMID:26602150

  19. VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013

    PubMed Central

    Morse-McNabb, Elizabeth; Sheffield, Kathryn; Clark, Rob; Lewis, Hayden; Robson, Susan; Cherry, Don; Williams, Steve

    2015-01-01

    Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engagement to establish product requirements such as format, classification, frequency and spatial resolution. Its genesis is significantly different to traditional methods, incorporating data from a range of jurisdictions to develop land use information designed for regular on-going creation and consistency. Covering the entire landmass of Victoria, the dataset separately describes land tenure, land use and land cover. These variables are co-registered to a common spatial base (cadastral parcels) across the state for the period 2006 to 2013; biennially for land tenure and land use, and annually for land cover. Data is produced as a spatial GIS feature class. PMID:26602150

  20. Using Landsat-Derived Land Cover, Restructured Vegetation, and Atmospheric Mesoscale Modeling in Environmental and Global Change Research

    NASA Astrophysics Data System (ADS)

    Steyaert, L. T.; Pielke, R. A., Sr.

    developed from a GIS analysis of county-level U.S. Census data, historical maps, and various types of ancillary information. Land cover data were converted to biome-level land cover classes and aggregated as a percentage composition for model grid cell sizes on the order of 10-km. Coupled land-atmosphere modeling, for example CSU's RAMS mesoscale model with its Land Ecosystem-Atmosphere Feedback (LEAF II) subsystem, represents an important tool to understand and quantify the environmental effects of land use change. Previous mesoscale modeling experiments and empirical studies have suggested that land use change can effect land surface processes (energy, radiation, and soil moisture budgets), the exchange of fluxes between the land surface and the lower atmosphere, the properties of the atmospheric boundary layer, and potentially regional weather and climate variability. In this current study, RAMS 60-day simulations (or full annual cycle) are conducted on each historical land cover data set, but with a common set of meteorological forcing data. Model results from each simulation (e.g., surface latent and sensible heat fluxes, temperatures, total precipitation, and other variables) are analyzed for potential effects due to historical land use changes. Empirical data are used to validate model results. Landsat-derived products have not been typically used in atmospheric mesoscale modeling experiments where model domains are on the order of 500-1500 km in size. However, this research does suggest that the USGS NLCD and other large-area 30-m land cover data are important resources for mesoscale modeling. The NLCD represents a robust source of spatially accurate and thematically useful data for aggregation to model grid cells ranging from 500 m to several kilometers. Because mesoscale models typically use biome-level land cover classes, accurate percentage compositions for each model grid cell can be calculated. Landsat also explicitly captures landscape fragmentation and

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

    EPA Science Inventory

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

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  3. Modeling and mapping regional land use/land cover change in South Central Texas

    NASA Astrophysics Data System (ADS)

    Ranatunga, T.; Messen, D.

    2014-12-01

    Houston-Galveston Area Council (H-GAC) conducted a land use/land cover (LULC) change detection study to generate information about the LULC changes in a 15-county area of South Central Texas. Such information is essential in regional planning, natural resource management, monitoring and modeling of environmental characteristics. The objectives of this study are (1) Identification of regional spatial patterns of each LULC conversion, (2) Estimation of the area coverage of each LULC conversion, and (3) Estimation of the net gain and losses of each LULC classes. To achieve these objectives, ArcGIS Spatial analysis functions and data management tools were employed in python environment. Change detection was estimated from 1992 to 2011 using datasets from NLCD (National Land Cover Database) 1992, NLCD 2001 and NOAA C-CAP (National Oceanic and Atmospheric Administration, Coastal Change Analysis Program) 2011. Through visual analysis and comparisons with aerial imagery, we established that NLCD 1992 and 2001 datasets contained more classification inaccuracies than the NOAA 2011 dataset. The misclassified cells in the 1992 and 2001 NLCD datasets were corrected to be consistent with the 2011 C-CAP dataset. The NLCD 2001 dataset was first corrected using a logical evaluation with 2011 classes in each pixel. Then the NLCD 1992 dataset was corrected using the correct 2001 dataset. After correcting 1992 dataset, a cell by cell comparison was conducted with the NOAA 2011 dataset, and individual changes were recorded.

  4. Assessing global land cover reference datasets for different user communities

    NASA Astrophysics Data System (ADS)

    Tsendbazar, N. E.; de Bruin, S.; Herold, M.

    2015-05-01

    Global land cover (GLC) maps and assessments of their accuracy provide important information for different user communities. To date, there are several GLC reference datasets which are used for assessing the accuracy of specific maps. Despite significant efforts put into generating them, their availability and role in applications outside their intended use have been very limited. This study analyses metadata information from 12 existing and forthcoming GLC reference datasets and assesses their characteristics and potential uses in the context of 4 GLC user groups, i.e., climate modellers requiring data on Essential Climate Variables (ECV), global forest change analysts, the GEO Community of Practice for Global Agricultural Monitoring and GLC map producers. We assessed user requirements with respect to the sampling scheme, thematic coverage, spatial and temporal detail and quality control of the GLC reference datasets. Suitability of the datasets is highly dependent upon specific applications by the user communities considered. The LC-CCI, GOFC-GOLD, FAO-FRA and Geo-Wiki datasets had the broadest applicability for multiple uses. The re-usability of the GLC reference datasets would be greatly enhanced by making them publicly available in an expert framework that guides users on how to use them for specific applications.

  5. Assessment of the Thematic Accuracy of Land Cover Maps

    NASA Astrophysics Data System (ADS)

    Höhle, J.

    2015-08-01

    Several land cover maps are generated from aerial imagery and assessed by different approaches. The test site is an urban area in Europe for which six classes (`building', `hedge and bush', `grass', `road and parking lot', `tree', `wall and car port') had to be derived. Two classification methods 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 such as user's and producer's accuracy, and kappa coefficient. In addition, confidence intervals were computed for several accuracy measures. The achieved accuracies and confidence intervals are thoroughly analysed and recommendations are derived from the gained experiences. Reliable reference values are obtained using stereovision, false-colour image pairs, and positioning to the checkpoints with 3D coordinates. The influence of the training areas on the results is studied. Cross validation has been tested with a few reference points in order to derive approximate accuracy measures. The two classification 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 of the confidence interval of six classes was 14% of the user's accuracy.

  6. Alaska vegetated land cover change detection and classification from 2001 and 2011

    NASA Astrophysics Data System (ADS)

    Jin, S.; Yang, L.; Homer, C.

    2013-12-01

    Monitoring and mapping land cover changes are important for evaluating the status and transition of ecosystems. For state of Alaska, the National Land Cover Database (NLCD) 2001 is the first 30-m resolution baseline land cover product covering the entire state. Information on land cover changes are needed to update the status of the land covers over the past decade. However, such an effort is challenging because of the vast size of Alaska land, short growing season, complex terrain and limited amount of good-quality Landsat imagery. According to Alaska's unique land cover composition and its disturbance and succession, we designed a SKILL model (System of Knowledge-based Integrated-trajectory Landcover Labeling) to update the land cover status for the disturbed and succession area. The SKILL model includes several components: 1) identify potential disturbed and succession area, 2) initial land cover labeling through integration of multi- temporal and multispectral data, land cover trajectory, and disturbance characteristics, and 3) targeted refinement of the initial label (e.g. missing fire, shadow area). The SKILL model was tested in three areas in Alaska, each covers four Landsat image footprints. One is within the Yukon River Basin, the other two are in Southeastern Alaska extending from the city of Anchorage to Fairbank. The major natural vegetation disturbance/succession areas were identified and land cover was updated to 2010. High spatial resolution images (from Google Earth, Bing) and SPOT Ortho-images provided by the Alaska State Mapping Initiative program were utilized as reference data to evaluate the performance of the SKILL model. The preliminary results show that the SKILL model can potentially provide a robust, consistent, and cost-effective means for capturing major disturbance/succession events and updating the land cover.

  7. Data-based evidence for contrasting land cover-atmosphere interactions across Sweden.

    NASA Astrophysics Data System (ADS)

    van der Velde, Ype; Dekker, Stefan; Lyon, Steve; Destouni, Georgia

    2013-04-01

    As humans alter landscape, vegetation, climate and atmospheric composition, changes in the terrestrial water balance and fresh water resources are likely to occur. Understanding how climate, vegetation, humans and hydrology interact and feedback to the atmosphere is key for accurate projections of future fresh water resources. To this end, we will present the results of a data-driven regionalization approach for river discharges, using 280 river discharge and over 400 meteorological records (1960-2010) in Sweden. We related catchment runoff coefficients and change trends thereof to land-surface characteristics. With these relationships we were able to create average and change trend maps for runoff and evapotranspiration across Sweden. We summarized all this information by plotting water use efficiency (actual evapotranspiration (ET)/precipitation) against energy use efficiency (actual ET/potential ET by Priestley Taylor Eq.) for areas with unique land cover across Sweden. This plot clearly shows that wetlands tend to have lower water and energy use efficiencies compared to "open waters", forests and agriculture, and that agriculture has water and energy use efficiencies closest to those of "open waters". These results demonstrate how a change in land cover driven by climate change or by humans is likely to alter land-cover-atmosphere interactions, thereby changing both the water and energy balance of catchments. Looking at the change trends during the last 50 years we see that the vegetation tended to become more efficient in using water and energy (i.e. the fractions of water and energy converted into river runoff and heat decreased). As this behavior coincides with an increase in precipitation it signals an acceleration of the hydrological across Sweden. In this presentation we will discuss the potential mechanisms explaining this increase in efficiency and discuss the implications of our findings for future water cycles.

  8. A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

    PubMed

    Jiang, Dong; Huang, Yaohuan; Zhuang, Dafang; Zhu, Yunqiang; Xu, Xinliang; Ren, Hongyan

    2012-01-01

    Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience. PMID:23049886

  9. A Simple Semi-Automatic Approach for Land Cover Classification from Multispectral Remote Sensing Imagery

    PubMed Central

    Jiang, Dong; Huang, Yaohuan; Zhuang, Dafang; Zhu, Yunqiang; Xu, Xinliang; Ren, Hongyan

    2012-01-01

    Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience. PMID:23049886

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Monitoring land cover changes in Isfahan Province, Iran using Landsat satellite data.

    PubMed

    Soffianian, Alireza; Madanian, Maliheh

    2015-08-01

    Changes in land cover and land use reveal the effects of natural and human processes on the Earth's surface. These changes are predicted to exert the greatest environmental impacts in the upcoming decades. The purpose of the present study was to monitor land cover changes using Multispectral Scanner Sensor (MSS) and multitemporal Landsat Thematic Mapper (TM) data from the counties of Isfahan Province, Iran, during 1975, 1990, and 2010. The maximum likelihood supervised classification method was applied to map land cover. Postclassification change detection technique was also used to produce change images through cross-tabulation. Classification results were improved using ancillary data, visual interpretation, and local knowledge about the area. The overall accuracy of land cover change maps ranged from 88 to 90.6%. Kappa coefficients associated with the classification were 0.81 for 1975, 0.84 for 1990, and 0.85 for 2010 images. This study monitored changes related to conversion of agricultural land to impervious surfaces, undeveloped land to agricultural land, agricultural land to impervious surfaces, and undeveloped land to impervious surfaces. The analyses of land cover changes during the study period revealed the significant development of impervious surfaces in counties of Isfahan Province as a result of population growth, traffic conditions, and industrialization. The image classification indicated that agricultural lands increased from 2520.96 km(2) in 1975 to 4103.85 km(2) in 2010. These land cover changes were evaluated in different counties of Isfahan Province. PMID:26228619

  12. Characterizing a Dynamic Land Cover Change Frontier Using MODIS Phenology Metrics: Cropland Expansion in Mato Grosso, Brazil

    NASA Astrophysics Data System (ADS)

    Morton, D. C.; Defries, R. S.; Shimabukuro, Y. E.; Morisette, J.

    2005-12-01

    The state of Mato Grosso, Brazil experienced the most rapid agricultural expansion of any region in the Amazon Basin during the existing MODIS data record. Rapid conversion of Amazon forest, transitional tropical forest, and cerrado woodland-savanna for cattle ranching and grain production continues to fragment large tracts of these biomes. Tropical forest loss is estimated annually, yet the fate of cleared lands and losses of transitional forest or cerrado have not been well characterized in this region. Using phenological information from time series of MODIS 16-day composite data, it is possible to capture the temporal dynamism of land cover change and accurately separate primary and secondary land use transitions. We use time series of cloud-cleaned MODIS NDVI and EVI at 250 m resolution to characterize land cover based on metrics of wet-season, dry-season, and annual phenology from 2000-2004. Distinct phenological signatures for forest, pasture and natural grasslands, cerrado, and cropland enable accurate classification of land cover types when compared to field validation data (overall accuracy = 85%). We estimate that more than 1.6 million hectares were converted to cropland between 2000 and 2004. The majority of new cropland resulted from the direct conversion of cerrado (35%) or forest (29%); conversion of natural grassland areas or planted pasture accounted for 36% of new cropland areas. While secondary transitions from existing cattle pasture to cropland are an important source of new agricultural production, our findings contradict recent statements that cropland agriculture is not directly associated with new deforestation activities. Separation of more seasonal cerrado vegetation from transitional tropical forest based on vegetation phenology highlights land cover dynamics in regions with no previous deforestation monitoring. Phenological information from MODIS is extremely important to monitor land cover dynamics, separate forest types, and estimate

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

    USGS Publications Warehouse

    Soulard, Christopher E.; Wilson, Tamara S.

    2013-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  16. PRESENTATION ON--LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

    EPA Science Inventory

    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...

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Land use/land cover (LULC) activity influences climate change and one way to explore climate change is to analyse the change in LULC patterns. Modelling the Spatio-temporal pattern of LULC change requires the use of satellite remote sensing data and aerial photographs with different pre-processing steps. The aim of this research is to analyse the reciprocal effects of LUCC (Land Use and Cover Change) and the climate change on each other in the study area which covers part of Bristol, South Gloucestershire, Bath and Somerset in England for the period (1975-2015). LUCC is assessed using remote sensing data. Three sets of remotely sensed data, LanSAT-1 Multispectral Scanner (MSS) data obtained in (1975 and 1976), LanSAT-5 Thematic Mapper (TM) data obtained in (1984 and 1997), and LandSAT-7 Enhanced Thematic Mapper Plus (ETM+) acquired in (2003 and 2015), with a time span of forty years were used in the study. One of the most common problems in the satellite images is the presence of cloud covers. In this study, the cloud cover problem is handled using a novel algorithm, which is capable of reducing the cloud coverage in the classified images significantly. This study also examines a suite of possible photogrammetry techniques applicable to detect the change in LULC. At the moment photogrammertic techniques are used to derive the ground truth for supervised classification from the high resolution aerial photos which were provided by Ordnance Survey (contract number: 240215) and global mapper for the years in (2001 and 2014). After obtaining the classified images almost free of clouds, accuracy assessment is implemented with the derived classified images using confusion matrix at some ground truth points. Eight classes (Improved grassland, Built up areas and gardens, Arable and horticulture, Broad-leaved / mixed woodland, Coniferous woodland, Oceanic seas, Standing open water and reservoir, and Mountain; heath; bog) have been classified in the chosen study area. Also

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

    USGS Publications Warehouse

    Sohl, Terry L.; Sleeter, Benjamin M.

    2012-01-01

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

  19. Big Earth observation data analytics for land use and land cover change information

    NASA Astrophysics Data System (ADS)

    Câmara, Gilberto

    2015-04-01

    Current scientific methods for extracting information for Earth observation data lag far behind our capacity to build complex satellites. In response to this challenge, our work explores a new type of knowledge platform to improve the extraction of land use and land cover change information from big Earth Observation data sets. We take a space-time perspective of Earth Observation data, considering that each sensor revisits the same place at regular intervals. Sensor data can, in principle, be calibrated so that observations of the same place in different times are comparable and each measure from a sensor is mapped into a three dimensional array in space-time. To fully enable the use of space-time arrays for working with Earth Observation data, we use the SciDB array database. Arrays naturally fit the data structure of Earth Observation images, breaking the image-as-a-snapshot paradigm. Thus, entire collections of images can be stored as multidimensional arrays. However, array databases do not understand the specific nature of geographical data, and do not capture the meaning and the differences between spatial and temporal dimensions. In our work, we have extended SciDB to include additional information about satellite image metadata, cartographical projections, and time. We are currently developing methods to extract land use and land cover information based on space-time analysis on array databases. Our experiments show these space-time methods give us significant improvements over current space-only remote sensing image processing methods. We have been able to capture tropical forest degradation and forest regrowth and also to distinguish between single-cropping and double-cropping practices in tropical agriculture.

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

    PubMed

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

    2014-09-15

    Historically, Florida soils stored the largest amount of soil organic carbon (SOC) among the conterminous U.S. states (2.26 Pg). This region experienced rapid land use/land cover (LULC) shifts and climate change in the past decades. The effects of these changes on SOC sequestration are unknown. The objectives of this study were to 1) investigate the change in SOC stocks in Florida to determine if soils have acted as a net sink or net source for carbon (C) over the past four decades and 2) identify the concomitant effects of LULC, LULC change, and climate on the SOC change. A total of 1080 sites were sampled in the topsoil (0-20 cm) between 2008 and 2009 representing the current SOC stocks, 194 of which were selected to collocate with historical sites (n = 1251) from the Florida Soil Characterization Database (1965-1996) for direct comparison. Results show that SOC stocks significantly differed among LULC classes--sugarcane and wetland contained the highest SOC, followed by improved pasture, urban, mesic upland forest, rangeland, and pineland while crop, citrus and xeric upland forest remained the lowest. The surface 20 cm soils acted as a net sink for C with the median SOC significantly increasing from 2.69 to 3.40 kg m(-2) over the past decades. The SOC sequestration rate was LULC dependent and controlled by climate factors interacting with LULC. Higher temperature tended to accelerate SOC accumulation, while higher precipitation reduced the SOC sequestration rate. Land use/land cover change observed over the past four decades also favored the C sequestration in soils due to the increase in the C-rich wetland area by ~140% and decrease in the C-poor agricultural area by ~20%. Soils are likely to provide a substantial soil C sink considering the climate and LULC projections for this region. PMID:25010945

  1. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

    USGS Publications Warehouse

    Loveland, T.R.; Reed, B.C.; Brown, J.F.; Ohlen, D.O.; Zhu, Z.; Yang, L.; Merchant, J.W.

    2000-01-01

    Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental- to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    PubMed

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

    2010-06-01

    The microwave emissivity over land is very important for describing the characteristics of the lands, and it is also a key factor for retrieving the parameters of land and atmosphere. Different land covers have their emission behavior as a function of structure, water content, and surface roughness. In the present study the global land surface emissivities were calculated using six month (June, 2003-August, 2003, Dec, 2003-Feb, 2004) AMSR-E L2A brightness temperature, MODIS land surface temperature and the layered atmosphere temperature, and humidity and pressure profiles data retrieved from MODIS/Aqua under clear sky conditions. With the information of IGBP land cover types, "pure" pixels were used, which are defined when the fraction cover of each land type is larger than 85%. Then, the emissivity of sixteen land covers at different frequencies, polarization and their seasonal variation were analyzed respectively. The results show that the emissivity of vegetation including forests, grasslands and croplands is higher than that over bare soil, and the polarization difference of vegetation is smaller than that of bare soil. In summer, the emissivity of vegetation is relatively stable because it is in bloom, therefore the authors can use it as its emissivity in our microwave emissivity database over different land cover types. Furthermore, snow cover can heavily impact the change in land cover emissivity, especially in winter. PMID:20707126

  4. Land Cover and Landscape Diversity Analysis in the West Polesie Biosphere Reserve

    NASA Astrophysics Data System (ADS)

    Chmielewski, Szymon; Chmielewski, Tadeusz J.; Tompalski, Piotr

    2014-04-01

    The aim of this research was to present the land cover structure and landscape diversity in the West Polesie Biosphere Reserve. The land cover classification was performed using Object Based Image Analysis in Trimble eCognition Developer 8 software. The retrospective land cover changes analysis in 3 lake catchments (Kleszczów, Moszne, Bia³eW³odawskie Lakes)was performed on the basis of archival aerial photos taken in 1952, 1971, 1984, 1992, 2007 and one satellite scene from 2003 (IKONOS).On the basis of land cover map structure, Shannon diversity index was estimated with the moving window approach enabled in Fragstats software. The conducted research has shown that the land cover structure of the West Polesie Biosphere Reserve is diverse and can be simply described by selected landscape metrics. The highest level of land cover diversity, as showed by Shannon Diversity Index, was identified in the western part of the West Polesie Biosphere Reserve, which is closely related to the agricultural character of land cover structure in those regions. The examples of three regional retrospective land cover analyses demonstrated that the character of land cover structure has changed dramatically over the last 40 years.

  5. A method of characterizing land-cover swap changes in the arid zone of China

    NASA Astrophysics Data System (ADS)

    Yuan, Yecheng; Li, Baolin; Gao, Xizhang; Liu, Haijiang; Xu, Lili; Zhou, Chenghu

    2016-03-01

    Net area change analysis can dramatically underestimate total change of land cover, even sometimes seriously misinterpret ecological processes of the ecosystem, especially in arid or semiarid zones. In this paper, a suite of indices are presented to characterize land-cover swaps that may seriously damage the ecosystem in arid or semiarid zones, based on swap-change areas extracted from remotely sensed images. First, swap percentage of total area and swap intensity of total changes were used to determine the status of land-cover swap change in an area. Then, dominated swap category and individual swap-change intensity for a land-cover category were used to determine flagged land-cover swap-change categories. Finally, swap-change mode and Pielou's index were used to determine the land-cover swap-change processes of dominant categories. A case study is conducted using this approach, based on two land-cover maps in the 1980s and 2000 in Naiman Qi, Tongliao City, Inner Mongolia, China. This study shows that the approach can clearly quantify the severity and flagged classes of land-cover swap-change and reveal their relationship with ecological processes of the ecosystem. These results indicate that the approach can give deep insights into swap change, which can be very valuable to land-cover policy making and management.

  6. Recent progress on land cover change and its regional climatic effects over China during historical times

    NASA Astrophysics Data System (ADS)

    Zheng, J.; He, F.; Lin, S.

    2009-04-01

    Land cover change has been demonstrated as an important forcing driver of climate change, and many studies have been conducted that simulate the climatic effects of human-induced land cover change at global and regional scales. Land cover in China has undergone large-scale modifications, mainly through deforestation and desertification, over the last several thousand years, and the extents to which these changes have influenced climate change have increasingly attracted scientists' attention. The simulations of regional climatic effects caused by land cover changes which based on different datasets--historical reconstruction and potential land cover data--show that the human-induced land cover changes over China since 1700AD have led to the enhancement on the East Asian Winter Monsoon and cooling in winter overall, with warming over most of China but cooling at somewhere (e.g. northern China or the Middle-Lower Yangtze Valley) in summer. However, the different simulations by different models show different effects on annual mean temperature, annual precipitation and East Asian Summer Monsoon. These differences among these simulations are shown to have resulted from the disparities in the classifications of land cover types among different land cover dataset used, in the extent of land cover.

  7. A method for assessing the distinguishability of land covers and soils in land surface models: Basic principles and first results.

    NASA Astrophysics Data System (ADS)

    Eckhardt, Klaus

    2015-04-01

    Land surface-atmosphere interactions are shaped by temporally and spatially varying characteristics of land cover and soil. Yet, model parameters representing these characteristics are oftentimes highly uncertain. Against the background of the parameter uncertainty it is questionable if models are actually always able to describe the emulated systems in such detail as is claimed. Taking this into account, honesty demands that models are simplified as far as possible. A further argument for such a simplification is that the parameterisation of a model is generally an expensive task and should be avoided for land covers and soils whose physical effect cannot be distinguished by the model. On the other hand, the simplification must not go too far. Land surface models have to meet certain minimum requirements pertaining to their ability to reproduce land covers and soils in a differentiated manner. In a model which is used for a land cover change study, for example, the respective covers have to distinguished not only formally, but in their acual effect. A method is presented which contributes to answering the following fundamental questions: (1) How far should land surface models be simplified in order not to feign an explanatory power they do not possess? (2) How far can land surface models be simplified without loosing their explanatory power? (3) Which land surface model is appropriate for a given task with respect to its ability to differentiate between the land covers and soils of interest? Where is need for model improvements? Application of the method is exemplified by means of the model Noah-LSM. Ongoing studies aiming at characterising a number of wide-spread land surface models with respect to their ability to distinguish the physical effect of different land covers are outlined.

  8. Evaluation of ISLSCP Initiative II satellite-based land cover data sets and assessment of progress in land cover data for global modeling

    NASA Astrophysics Data System (ADS)

    Brown de Colstoun, Eric C.; Defries, Ruth S.; Townshend, John R. G.

    2006-11-01

    As an important component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection, eight state-of-the-art land cover/use data sets have been compiled and made consistent with the ISLSCP Initiative II land/water mask in support of global modeling efforts. These data sets contain new and improved global data sets at coarse resolutions (1/4, 1/2 and 1°) describing historical, recent and present land cover conditions and are a testament to the tremendous progress made in this area over the past decade. In addition to the historical data, data describing the subcell heterogeneity in land cover are also provided, both in terms of subcell proportions of land cover classes and vegetation continuous fields such as % tree, grass and bare cover. Here we present the various ISLSCPII land cover data sets and compare the principal satellite-derived data sets and the effect of their respective aggregation methods. We find that despite some notable disagreements among similar classes, the satellite-based data sets agree remarkably well over large portions of the Earth's surface (over 50% for all resolutions). We also find that the methods of aggregation, whether done by a strictly dominant type, or using more information on subcell tree cover, can have an important impact on the final output and need to be considered by the user. Finally, by integrating the vegetation continuous fields data into our analyses we are able to show that the principal differences in terms of discrete land cover classes are in fact transition zones between similar classes.

  9. Detecting land cover change over a 20 year time period in the Niagara Escarpment Plan using satellite remote sensing

    NASA Astrophysics Data System (ADS)

    Waite, Holly

    The Niagara Escarpment is one of Southern Ontario's most important landscapes. Due to the nature of the landform and its location, the Escarpment is subject to various development pressures including urban expansion, mineral resource extraction, agricultural practices and recreation. In 1985, Canada's first large scale environmentally based land use plan was put in place to ensure that only development that is compatible with the Escarpment occurred within the Niagara Escarpment Plan (NEP). The southern extent of the NEP is of particular interest in this study, since a portion of the Plan is located within the rapidly expanding Greater Toronto Area (GTA). The Plan area located in the Regional Municipalities of Hamilton and Halton represent both urban and rural geographical areas respectively, and are both experiencing development pressures and subsequent changes in land cover. Monitoring initiatives on the NEP have been established, but have done little to identify consistent techniques for monitoring land cover on the Niagara Escarpment. Land cover information is an important part of planning and environmental monitoring initiatives. Remote sensing has the potential to provide frequent and accurate land cover information over various spatial scales. The goal of this research was to examine land cover change in the Regional Municipalities of Hamilton and Halton portions of the NEP. This was achieved through the creation of land cover maps for each region using Landsat 5 Thematic Mapper (TM) remotely sensed data. These maps aided in determining the qualitative and quantitative changes that had occurred in the Plan area over a 20 year time period from 1986 to 2006. Change was also examined based on the NEP's land use designations, to determine if the Plan policy has been effective in protecting the Escarpment. To obtain land cover maps, five different supervised classification methods were explored: Minimum Distance, Mahalanobis Distance, Maximum Likelihood, Object

  10. Multi-year global land cover mapping at 300 m and characterization for climate modelling: achievements of the Land Cover component of the ESA Climate Change Initiative

    NASA Astrophysics Data System (ADS)

    Bontemps, S.; Boettcher, M.; Brockmann, C.; Kirches, G.; Lamarche, C.; Radoux, J.; Santoro, M.; Vanbogaert, E.; Wegmuller, U.; Herold, M.; Achard, F.; Ramoino, F.; Arino, O.; Defourny, P.

    2015-04-01

    Essential Climate Variables were listed by the Global Climate Observing System as critical information to further understand the climate system and support climate modelling. The European Space Agency launched its Climate Change Initiative in order to provide an adequate response to the set of requirements for long-term satellite-based products for climate. Within this program, the CCI Land Cover project aims at revisiting all algorithms required for the generation of global land cover products that are stable and consistent over time, while also reflecting the land surface seasonality. To this end, the land cover concept is revisited to deliver a set of three consistent global land cover products corresponding to the 1998-2002, 2003-2007 and 2008-2012 periods, along with climatological 7-day time series representing the average seasonal dynamics of the land surface over the 1998-2012 period. The full Envisat MERIS archive (2003-2012) is used as main Earth Observation dataset to derive the 300-m global land cover maps, complemented with SPOT-Vegetation time series between 1998 and 2012. Finally, a 300-m global map of open permanent water bodies is derived from the 2005-2010 archive of the Envisat Advanced SAR imagery mainly acquired in the 150m Wide Swath Mode.

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

    EPA Science Inventory

    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...

  12. Laco-Wiki AN Open Access Online Portal for Land Cover Validation

    NASA Astrophysics Data System (ADS)

    See, L.; Perger, C.; Hofer, M.; Weichselbaum, J.; Dresel, C.; Fritz, S.

    2015-08-01

    The LACO-Wiki tool represents an open access, online portal that offers standardized land cover validation at local to global scales. LACO-Wiki integrates the LACOVAL prototype for land cover validation and the Geo-Wiki system for visualization, validation and crowdsourcing of land cover. This paper presents a conceptual overview of the LACO-Wiki system and describes the main validation workflow, in which the user uploads the map for validation, creates a validation sample, carries out the sample interpretation and generates a report detailing the accuracy assessment. In addition to a land cover validation tool, LACO-Wiki is also intended to become an open access repository for calibration and validation data that can be used by the land monitoring community to improve future land cover products.

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

    USGS Publications Warehouse

    Barnes, Christopher; Roy, David P.

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Barnes, C. A.; Roy, D. P.

    2009-04-01

    Land cover and land use (LCLU) change affects Earth surface properties including albedo that impose a radiative forcing on the climate. Recently available satellite derived LCLU change data for the conterminous United States (CONUS) are used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing for 61 ecoregions covering 73% of the CONUS. Mean monthly broadband Moderate Resolution Imaging Spectroradiometer snow and snow-free albedo values are derived from decadal Landsat 60m LCLU classification maps located within ecoregions using a stratified random sampling methodology. These data and European Center for Medium-Range Weather Forecasts incoming surface solar radiation reanalysis are used to estimate ecoregion estimates of LCLU induced albedo change and surface radiative forcing. The results illustrate that radiative forcing due to contemporary LCLU albedo change varies geographically in sign and magnitude, with the most positive radiative forcing due to conversion of agriculture to other LCLU types, and the most negative radiative forcing due to forest loss, with snow modifying the results. At the ecoregion level this magnitude of radiative forcing is not insignificant, being similar in magnitude to global radiative forcing estimates due to LCLU change during the twentieth century.

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

    NASA Astrophysics Data System (ADS)

    Barnes, Christopher A.; Roy, David P.

    2008-05-01

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

  16. Land-use and land-cover change and farmer vulnerability in Xishuangbanna prefecture in southwestern China.

    PubMed

    Jianchu, Xu; Fox, Jefferson; Vogler, John B; Yongshou, Zhang Peifang Fu; Lixin, Yang; Jie, Qian; Leisz, Stephen

    2005-09-01

    This study investigated land-use and land-cover change in three hamlets and two state rubber farms in the Nan-e watershed of the Xishuangbanna prefecture of Yunnan province in Southwestern China. The overall objective of the study was to understand how state policies affected land use and land cover and how changes in these variables affected farmer vulnerability to economic, social, and political events. Emphasis was placed on the cultivation of rubber (Hevea brasiliensis), promoted in southern Yunnan province since the 1950s as a means to meet the demands of rapid economic development. The study combined remote sensing analysis with secondary data and in-field interviews in order to understand the coupling between land-use and land-cover change and farmer vulnerability in light of the geographic, historical, and sociopolitical situation. PMID:15995894

  17. Changes in Carbon Flux at the Duke Forest Hardwood Ameriflux Site Due to Land Cover/Land Use Changes

    NASA Astrophysics Data System (ADS)

    McCombs, A. G.

    2014-12-01

    The Raleigh/Durham, North Carolina metropolitan area has been ranked by Forbes as the fastest growing cities in the United States. As a result of the rapid growth, there has been a significant amount of urban sprawl. The objective of this study was to determine if the changes in land use and land cover have caused a change in the carbon flux near the Duke Forest AmeriFlux station that was active from 2001 to 2008. The land cover and land use were assessed every two years to determine how land cover has changed at the Duke Forest Hardwoods (US-Dk2) AmeriFlux site from 2001 to 2008 using Landsat scenes. The change in land cover and land use was then compared to changes in the carbon footprint that is computed annually from 2001 to 2008. The footprint model for each wind direction determined that there are changes annually and that the research will determine if these changes are due to annual weather patterns or land use and land cover changes.

  18. The FORE-SCE model: a practical approach for projecting land cover change using scenario-based modeling

    USGS Publications Warehouse

    Sohl, Terry L.; Sayler, Kristi L.; Drummond, Mark A.; Loveland, Thomas R.

    2007-01-01

    A wide variety of ecological applications require spatially explicit, historic, current, and projected land use and land cover data. The U.S. Land Cover Trends project is analyzing contemporary (1973–2000) land-cover change in the conterminous United States. The newly developed FORE-SCE model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land cover change through 2020 for multiple plausible scenarios. Projected proportions of future land use were initially developed, and then sited on the lands with the highest potential for supporting that land use and land cover using a statistically based stochastic allocation procedure. Three scenarios of 2020 land cover were mapped for the western Great Plains in the US. The model provided realistic, high-resolution, scenario-based land-cover products suitable for multiple applications, including studies of climate and weather variability, carbon dynamics, and regional hydrology.

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

    PubMed Central

    Li, Guiying; Moran, Emilio; Hetrick, Scott

    2013-01-01

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

  20. Land cover change impacts on surface ozone: an observation-based study

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Lin, Jintai

    2016-04-01

    Ozone air quality is a critical global environmental issue. Although it is clear that industrialization and urbanization has increased surface ozone through enhanced emissions of its precursors, much less is known about the role of changes in land cover and land use. Human activities have substantially altered the global land cover and land use through agriculture, urbanization, deforestation, and afforestation. Changes in Land cover and land use affect the ozone levels by altering soil emissions of nitrogen oxides (NOx), biogenic emissions of volatile organic compounds (VOCs), and dry deposition of ozone itself. This study performs a series of experiments with a chemical transport model based on satellite observation of land types to analyze the influences of changes in land cover/land use and their impact on surface ozone concentration. Our results indicate that land cover change explains 1-2 ppbv of summertime surface ozone increase in the Western United States and 1-6 ppbv of increase in Southern China between 2001 and 2012. This is largely driven by enhanced isoprene emissions and soil NOx emissions. It is also found that land cover change itself elevates summertime surface zone in Canadian coniferous forests by up to 4 ppbv mainly through substantial decreases in ozone dry deposition associated with increased vegetation density in a warmer climate.

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

    NASA Technical Reports Server (NTRS)

    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

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

    PubMed

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

    2014-04-01

    Outdoor water use is a key component in arid city water systems for achieving sustainable water use and ensuring water security. Using evapotranspiration (ET) calculations as a proxy for outdoor water consumption, the objectives of this research are to quantify outdoor water consumption of different land use and land cover types, and compare the spatio-temporal variation in water consumption between drought and wet years. An energy balance model was applied to Landsat 5 TM time series images to estimate daily and seasonal ET for the Central Arizona Phoenix Long-Term Ecological Research region (CAP-LTER). Modeled ET estimations were correlated with water use data in 49 parks within CAP-LTER and showed good agreement (r² = 0.77), indicating model effectiveness to capture the variations across park water consumption. Seasonally, active agriculture shows high ET (>500 mm) for both wet and dry conditions, while the desert and urban land cover types experienced lower ET during drought (<300 mm). Within urban locales of CAP-LTER, xeric neighborhoods show significant differences from year to year, while mesic neighborhoods retain their ET values (400-500 mm) during drought, implying considerable use of irrigation to sustain their greenness. Considering the potentially limiting water availability of this region in the future due to large population increases and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life. PMID:24499870

  3. Urban land cover thematic disaggregation, employing datasets from multiple sources and RandomForests modeling

    NASA Astrophysics Data System (ADS)

    Gounaridis, Dimitrios; Koukoulas, Sotirios

    2016-09-01

    Urban land cover mapping has lately attracted a vast amount of attention as it closely relates to a broad scope of scientific and management applications. Late methodological and technological advancements facilitate the development of datasets with improved accuracy. However, thematic resolution of urban land cover has received much less attention so far, a fact that hampers the produced datasets utility. This paper seeks to provide insights towards the improvement of thematic resolution of urban land cover classification. We integrate existing, readily available and with acceptable accuracies datasets from multiple sources, with remote sensing techniques. The study site is Greece and the urban land cover is classified nationwide into five classes, using the RandomForests algorithm. Results allowed us to quantify, for the first time with a good accuracy, the proportion that is occupied by each different urban land cover class. The total area covered by urban land cover is 2280 km2 (1.76% of total terrestrial area), the dominant class is discontinuous dense urban fabric (50.71% of urban land cover) and the least occurring class is discontinuous very low density urban fabric (2.06% of urban land cover).

  4. Beyond Impervious: Urban Land-Cover Pattern Variation and Implications for Watershed Management.

    PubMed

    Beck, Scott M; McHale, Melissa R; Hess, George R

    2016-07-01

    Impervious surfaces degrade urban water quality, but their over-coverage has not explained the persistent water quality variation observed among catchments with similar rates of imperviousness. Land-cover patterns likely explain much of this variation, although little is known about how they vary among watersheds. Our goal was to analyze a series of urban catchments within a range of impervious cover to evaluate how land-cover varies among them. We then highlight examples from the literature to explore the potential effects of land-cover pattern variability for urban watershed management. High-resolution (1 m(2)) land-cover data were used to quantify 23 land-cover pattern and stormwater infrastructure metrics within 32 catchments across the Triangle Region of North Carolina. These metrics were used to analyze variability in land-cover patterns among the study catchments. We used hierarchical clustering to organize the catchments into four groups, each with a distinct landscape pattern. Among these groups, the connectivity of combined land-cover patches accounted for 40 %, and the size and shape of lawns and buildings accounted for 20 %, of the overall variation in land-cover patterns among catchments. Storm water infrastructure metrics accounted for 8 % of the remaining variation. Our analysis demonstrates that land-cover patterns do vary among urban catchments, and that trees and grass (lawns) are divergent cover types in urban systems. The complex interactions among land-covers have several direct implications for the ongoing management of urban watersheds. PMID:27094440

  5. An evaluation of sampling strategies to improve precision of estimates of gross change in land use and land cover

    USGS Publications Warehouse

    Stehman, S.V.; Sohl, T.L.; Loveland, T.R.

    2005-01-01

    Statistical sampling offers a cost-effective, practical alternative to complete-coverage mapping for the objective of estimating gross change in land cover over large areas. Because land cover change is typically rare, the sampling strategy must take advantage of design and analysis tools that enhance precision. Using two populations of land cover change in the eastern United States, we demonstrate that the choice of sampling unit size and use of a survey sampling regression estimator can significantly improve precision with only a minor increase in cost. ?? 2005 Taylor & Francis.

  6. High resolution topography and land cover databases for wind resource assessment using mesoscale models

    NASA Astrophysics Data System (ADS)

    Barranger, Nicolas; Stathopoulos, Christos; Kallos, Georges

    2013-04-01

    In wind resource assessment, mesoscale models can provide wind flow characteristics without the use of mast measurements. In complex terrain, local orography and land cover data assimilation are essential parameters to accurately simulate the wind flow pattern within the atmospheric boundary layer. State-of-the-art Mesoscale Models such as RAMS usually provides orography and landuse data with of resolution of 30s (about 1km). This resolution is necessary for solving mesocale phenomena accurately but not sufficient when the aim is to quantitatively estimate the wind flow characteristics passing over sharp hills or ridges. Furthermore, the abrupt change in land cover characterization is nor always taken into account in the model with a low resolution land use database. When land cover characteristics changes dramatically, parameters such as roughness, albedo or soil moisture that can highly influence the Atmospheric Boundary Layer meteorological characteristics. Therefore they require to be accurately assimilated into the model. Since few years, high resolution databases derived from satellite imagery (Modis, SRTM, LandSat, SPOT ) are available online. Being converted to RAMS requirements inputs, an evaluation of the model requires to be achieved. For this purpose, three new high resolution land cover and two topographical databases are implemented and tested in RAMS. The analysis of terrain variability is performed using basis functions of space frequency and amplitude. Practically, one and two dimension Fast Fourier Transform is applied to terrain height to reveal the main characteristics of local orography according to the obtained wave spectrum. By this way, a comparison between different topographic data sets is performed, based on the terrain power spectrum entailed in the terrain height input. Furthermore, this analysis is a powerful tool in the determination of the proper horizontal grid resolution required to resolve most of the energy containing spectrum

  7. Regional carbon fluxes from land use and land cover change in Asia, 1980–2009

    NASA Astrophysics Data System (ADS)

    Calle, Leonardo; Canadell, Josep G.; Patra, Prabir; Ciais, Philippe; Ichii, Kazuhito; Tian, Hanqin; Kondo, Masayuki; Piao, Shilong; Arneth, Almut; Harper, Anna B.; Ito, Akihiko; Kato, Etsushi; Koven, Charlie; Sitch, Stephen; Stocker, Benjamin D.; Vivoy, Nicolas; Wiltshire, Andy; Zaehle, Sönke; Poulter, Benjamin

    2016-07-01

    We present a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia using multiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food and Agriculture Organization-Forest Resource Assessment (FAO-FRA 2015; country-level inventory estimates), the Emission Database for Global Atmospheric Research (EDGARv4.3), the ‘Houghton’ bookkeeping model that incorporates FAO-FRA data, an ensemble of 8 state-of-the-art Dynamic Global Vegetation Models (DGVM), and 2 recently published independent studies using primarily remote sensing techniques. The estimates are aggregated spatially to Southeast, East, and South Asia and temporally for three decades, 1980–1989, 1990–1999 and 2000–2009. Since 1980, net carbon emissions from LULCC in Asia were responsible for 20%–40% of global LULCC emissions, with emissions from Southeast Asia alone accounting for 15%–25% of global LULCC emissions during the same period. In the 2000s and for all Asia, three estimates (FAO-FRA, DGVM, Houghton) were in agreement of a net source of carbon to the atmosphere, with mean estimates ranging between 0.24 to 0.41 Pg C yr‑1, whereas EDGARv4.3 suggested a net carbon sink of ‑0.17 Pg C yr‑1. Three of 4 estimates suggest that LULCC carbon emissions declined by at least 34% in the preceding decade (1990–2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to include emissions from carbon rich peatlands and land management, such as shifting cultivation and wood harvesting, which appear to be consistently underreported.

  8. THEMATIC ACCURACY ASSESSMENT OF REGIONAL SCALE LAND COVER DATA

    EPA Science Inventory

    The Multi-Resolution Land Characteristics (MRLC) consortium, a cooperative effort of several U .S. federal agencies, including. the U.S. Geological Survey (USGS) EROS Data Center (EDC) and the U.S. Environmental Protection Agency (EP A), have jointly conducted the National Land C...

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

    USGS Publications Warehouse

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

    2013-01-01

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

  10. Mapping dominant annual land cover from 2009 to 2013 across Victoria, Australia using satellite imagery.

    PubMed

    Sheffield, Kathryn; Morse-McNabb, Elizabeth; Clark, Rob; Robson, Susan; Lewis, Hayden

    2015-01-01

    There is a demand for regularly updated, broad-scale, accurate land cover information in Victoria from multiple stakeholders. This paper documents the methods used to generate an annual dominant land cover (DLC) map for Victoria, Australia from 2009 to 2013. Vegetation phenology parameters derived from an annual time series of the Moderate Resolution Imaging Spectroradiometer Vegetation Indices 16-day 250 m (MOD13Q1) product were used to generate annual DLC maps, using a three-tiered hierarchical classification scheme. Classification accuracy at the broadest (primary) class level was over 91% for all years, while it ranged from 72 to 81% at the secondary class level. The most detailed class level (tertiary) had accuracy levels ranging from 61 to 68%. The approach used was able to accommodate variable climatic conditions, which had substantial impacts on vegetation growth patterns and agricultural production across the state between both regions and years. The production of an annual dataset with complete spatial coverage for Victoria provides a reliable base data set with an accuracy that is fit-for-purpose for many applications. PMID:26602009

  11. Mapping dominant annual land cover from 2009 to 2013 across Victoria, Australia using satellite imagery

    PubMed Central

    Sheffield, Kathryn; Morse-McNabb, Elizabeth; Clark, Rob; Robson, Susan; Lewis, Hayden

    2015-01-01

    There is a demand for regularly updated, broad-scale, accurate land cover information in Victoria from multiple stakeholders. This paper documents the methods used to generate an annual dominant land cover (DLC) map for Victoria, Australia from 2009 to 2013. Vegetation phenology parameters derived from an annual time series of the Moderate Resolution Imaging Spectroradiometer Vegetation Indices 16-day 250 m (MOD13Q1) product were used to generate annual DLC maps, using a three-tiered hierarchical classification scheme. Classification accuracy at the broadest (primary) class level was over 91% for all years, while it ranged from 72 to 81% at the secondary class level. The most detailed class level (tertiary) had accuracy levels ranging from 61 to 68%. The approach used was able to accommodate variable climatic conditions, which had substantial impacts on vegetation growth patterns and agricultural production across the state between both regions and years. The production of an annual dataset with complete spatial coverage for Victoria provides a reliable base data set with an accuracy that is fit-for-purpose for many applications. PMID:26602009

  12. Wavelet-SVM classifier based on texture features for land cover classification

    NASA Astrophysics Data System (ADS)

    Zhang, Ning; Wu, Bingfang; Zhu, Jianjun; Zhou, Yuemin; Zhu, Liang

    2008-12-01

    Texture features are recognized to be a special hint in images, which represent the spatial relations of the gray pixels. Nowadays, the applications of the texture analysis in image classification spread abroad. Combined with wavelet multi-resolution analysis or support vector machine statistical learning theory, texture analysis could improve the quality of classification increasingly. In this paper, we focus on the land cover for the Three Gorges reservoir using remote sensing data SPOT-5, a new classification method, wavelet-SVM classifier based on texture features, is employed for this study. Compare to the traditional maximum likelihood classifier and SVM classifier only use spectrum feature, this method produces more accurate classification results. According to the real environment of the Three Gorges reservoir land cover, a best texture group is selected from several texture features. Decompose the image at different levels, which is one of the main advantage of wavelet, and then compute the texture features in every sub-image, and the next step is eliminating the redundant, every texture features are centralized on the first principal components using principal component analysis. Finally, with the first principal components inputted, we can get the classification result using SVM in every decomposition scale, but what the problem we couldn't overlook is how to select the best SVM parameters. So an iterative rule based on the classification accuracy is induced, the more accuracy, the proper parameters.

  13. The Impact of Land Cover Change on a Simulated Storm Event in the Sydney Basin

    NASA Astrophysics Data System (ADS)

    Gero, A. F.; Pitman, A. J.

    2006-02-01

    The Regional Atmospheric Modeling System (RAMS) was run at a 1-km grid spacing over the Sydney basin in Australia to assess the impact of land cover change on a simulated storm event. The simulated storm used NCEP NCAR reanalysis data, first with natural (i.e., pre-European settlement in 1788) land cover and then with satellite-derived land cover representing Sydney's current land use pattern. An intense convective storm develops in the model in close proximity to Sydney's dense urban central business district under current land cover. The storm is absent under natural land cover conditions. A detailed investigation of why the change in land cover generates a storm was performed using factorial analysis, which revealed the storm to be sensitive to the presence of agricultural land in the southwest of the domain. This area interacts with the sea breeze and affects the horizontal divergence and moisture convergence—the triggering mechanisms of the storm. The existence of the storm over the dense urban area of Sydney is therefore coincidental. The results herein support efforts to develop parameterization of urban surfaces in high-resolution simulations of Sydney's meteorological environment but also highlight the need to improve the parameterization of other types of land cover change at the periphery of the urban area, given that these types dominate the explanation of the results.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  15. Topographic Maps: Rediscovering an Accessible Data Source for Land Cover Change Research

    ERIC Educational Resources Information Center

    McChesney, Ron; McSweeney, Kendra

    2005-01-01

    Given some limitations of satellite imagery for the study of land cover change, we draw attention here to a robust and often overlooked data source for use in student research: USGS topographic maps. Topographic maps offer an inexpensive, rapid, and accessible means for students to analyze land cover change over large areas. We demonstrate our…

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

    EPA Science Inventory

    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...

  17. INTEGRATING LANDSCAPE ASSESSMENT AND HYDROLOGIC MODELING FOR LAND COVER CHANGE ANALYSIS

    EPA Science Inventory

    This study is based on the assumption that land cover change and rainfall spatial variability affect the r-ainfall-runoff relationships on the watershed. Hydrologic response is an integrated indicator of watershed condition, and changes in land cover may affect the overall health...

  18. [Spatiotemporal dynamics of land cover in northern Tibetan Plateau with responses to climate change].

    PubMed

    Song, Chun-qiao; You, Song-cai; Ke, Ling-hong; Liu, Gao-huan; Zhong, Xin-ke

    2011-08-01

    By using the 2001-2008 MOMS land cover products (MCDl2Ql) and based on the modified classification scheme embodied the characteristics of land cover in northern Tibetan Plateau, the annual land cover type maps of the Plateau were drawn, with the dynamic changes of each land cover type analyzed by classification statistics, dynamic transfer matrix, and landscape pattern indices. In 2001-2008, due to the acceleration of global climate warming, the areas of glacier and snow-covered land in the Plateau decreased rapidly, and the melted snow water gathered into low-lying valley or basin, making the lake level raised and the lake area enlarged. Some permanent wetlands were formed because of partially submersed grassland. The vegetation cover did not show any evident meliorated or degraded trend. From 2001 to 2004, as the climate became warmer and wetter, the spatial distribution of desert began to shrink, and the proportions of sparse grassland and grassland increased. From 2006 to 2007, due to the warmer and drier climate, the desert bare land increased, and the sparse grassland decreased. From 2001 to 2008, both the landscape fragmentation degree and the land cover heterogeneity decreased, and the differences in the proportions of all land cover types somewhat enlarged. PMID:22097372

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

    EPA Science Inventory

    Land cover change and stream channel loss are two related global environmental changes that are expanding and intensifying. Here, we examine how different types and transitions of land cover change impact stream channel loss across a large urbanizing watershed with large areas of...

  20. Spatial and Temporal Data Fusion for Generating High-Resolution Land Cover Imagery

    NASA Astrophysics Data System (ADS)

    Xu, Yong

    Currently, remote sensing imagery has been widely used for generating global land cover products, but due to certain physical and budget limitations related to the sensors, their spatial and temporal resolution are too low to attain more accurate and more reliable global change research. In this situation, there is an urgent need to study and develop a more advanced satellite image processing method and land cover producing techniques to generate higher resolution images and land cover products for global change research. Through conducting a comprehensive study of the related theories and methods related to data fusion, various methods are systematically reviewed and summarized, such as HIS transformation image fusion, Wavelet transform image fusion, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), etc. The advantages and disadvantages of these methods are highlighted according to their specific applications in the field of remote sensing. Based on my research target, the following are the main contents of this thesis: (1) Data fusion theory will be systematically studied and summarized, including various fusion models and specific applications, such as IHS transformation, PCA transformation, Wavelet analysis based data fusion, etc. Furthermore, their advantages and disadvantages are pointed out in relation to specific applications. (2) As traditional data fusion methods rely on spatial information and it is hard to deal with multi-source data fusion with temporal variation, therefore, the traditional data fusion theory and methods will be improved by a consideration of temporal information. Accordingly, some spatial and temporal data fusion methods will be proposed, in which both high-resolution & low-temporary imagery and low-resolution & high-temporary imagery are incorporated. Our experiments also show that they are suitable for dealing with multi-temporal data integration and generating high-resolution, multi-temporal images for global

  1. A strategy for estimating the rates of recent United States land-cover changes

    USGS Publications Warehouse

    Loveland, T.R.; Sohl, T.L.; Stehman, S.V.; Gallant, A.L.; Sayler, K.L.; Napton, D.E.

    2002-01-01

    Information on the rates of land-use and land-cover change is important in addressing issues ranging from the health of aquatic resources to climate change. Unfortunately, there is a paucity of information on land-use and land-cover change except at very local levels. We describe a strategy for estimating land-cover change across the conterminous United States over the past 30 years. Change rates are estimated for 84 ecoregions using a sampling procedure and five dates of Landsat imagery. We have applied this methodology to six eastern U.S. ecoregions. Results show very high rates of change in the Plains ecoregions, high to moderate rates in the Piedmont ecoregions, and moderate to low rates in the Appalachian ecoregions. This indicates that ecoregions are appropriate strata for capturing unique patterns of land-cover change. The results of the study are being applied as we undertake the mapping of the rest of the conterminous United States.

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  3. Urban Land Cover/use Change Detection Using High Resolution SPOT 5 and SPOT 6 Images and Urban Atlas Nomenclature

    NASA Astrophysics Data System (ADS)

    Akay, S. S.; Sertel, E.

    2016-06-01

    Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was

  4. Synergistic Analysis of Coarse Resolution Vegetation and Land Cover Data for Permafrost Monitoring

    NASA Astrophysics Data System (ADS)

    Urban, M.; Herold, M.; Hese, S.; Pocking, S.; Schmullius, C.

    2010-12-01

    The boreal-tundra ecosystems in the northern hemisphere are highly affected by global climate change including a measureable impact on the permafrost dynamics. Coarse-scale vegetation data sets from Earth observations are suitable for the analysis of land cover and vegetation dynamics with respect to changing climatic pattern affecting the land surface and permafrost. This study represents preliminary results on the parameter land cover and disturbances for the contribution to the ESA Data User Element Permafrost. Based on requirements defined by the user community (1) global land cover products are synergetic combined to extract cover percentage information for vegetation physiognomy and barren areas and (2) burned area products are analyzed according similarities and inconsistencies. Future work will concentrate on the expansion of the synergy land cover product and the fire affected area database to the pan-arctic region as it is only available for Russia.

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

    PubMed Central

    Moran, Emilio Federico.

    2010-01-01

    High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

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

    USGS Publications Warehouse

    Giri, Chandra

    2005-01-01

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

  7. Temporal logic and operation relations based knowledge representation for land cover change web services

    NASA Astrophysics Data System (ADS)

    Chen, Jun; Wu, Hao; Li, Songnian; Liao, Anping; He, Chaoying; Peng, Shu

    2013-09-01

    Providing land cover spatio-temporal information and geo-computing through web service is a new challenge for supporting global change research, earth system simulation and many other societal benefit areas. This requires an integrated knowledge representation and web implementation of static land cover and change information, as well as the related operations for geo-computing. The temporal logic relations among land cover snapshots and increments were examined with a matrix-based three-step analysis. Twelve temporal logic relations were identified and five basic spatial operations were formalized with set operators, which were all used to develop algorithms for deriving implicit change information. A knowledge representation for land cover change information was then developed based on these temporal logic and operation relations. A prototype web-service system was further implemented based on OWL-DL. Both online access and conversion of land cover spatio-temporal information can be facilitated with such a web service system.

  8. Temporal Beta Diversity of Bird Assemblages in Agricultural Landscapes: Land Cover Change vs. Stochastic Processes

    PubMed Central

    Baselga, Andrés; Bonthoux, Sébastien; Balent, Gérard

    2015-01-01

    Temporal variation in the composition of species assemblages could be the result of deterministic processes driven by environmental change and/or stochastic processes of colonization and local extinction. Here, we analyzed the relative roles of deterministic and stochastic processes on bird assemblages in an agricultural landscape of southwestern France. We first assessed the impact of land cover change that occurred between 1982 and 2007 on (i) the species composition (presence/absence) of bird assemblages and (ii) the spatial pattern of taxonomic beta diversity. We also compared the observed temporal change of bird assemblages with a null model accounting for the effect of stochastic dynamics on temporal beta diversity. Temporal assemblage dissimilarity was partitioned into two separate components, accounting for the replacement of species (i.e. turnover) and for the nested species losses (or gains) from one time to the other (i.e. nestedness-resultant dissimilarity), respectively. Neither the turnover nor the nestedness-resultant components of temporal variation were accurately explained by any of the measured variables accounting for land cover change (r2<0.06 in all cases). Additionally, the amount of spatial assemblage heterogeneity in the region did not significantly change between 1982 and 2007, and site-specific observed temporal dissimilarities were larger than null expectations in only 1% of sites for temporal turnover and 13% of sites for nestedness-resultant dissimilarity. Taken together, our results suggest that land cover change in this agricultural landscape had little impact on temporal beta diversity of bird assemblages. Although other unmeasured deterministic process could be driving the observed patterns, it is also possible that the observed changes in presence/absence species composition of local bird assemblages might be the consequence of stochastic processes in which species populations appeared and disappeared from specific localities in a

  9. MODELING STREAM MACROINVERTEBRATE COMMUNITY RESPONSE TO LAND COVER IN THE WILLAMETTE BASIN

    EPA Science Inventory

    We analyzed macroinvertebrate data from 104 stream sites in the Willamette basin to develop models of macroinvertebrate response to land use/land cover data that can be used to project future conditions under various alternative land use scenarios. We assessed macroinvertebrate r...

  10. ASSESSING THE ACCURACY OF NATIONAL LAND COVER DATASET AREA ESTIMATES AT MULTIPLE SPATIAL EXTENTS

    EPA Science Inventory

    Site specific accuracy assessments provide fine-scale evaluation of the thematic accuracy of land use/land cover (LULC) datasets; however, they provide little insight into LULC accuracy across varying spatial extents. Additionally, LULC data are typically used to describe lands...

  11. Land-Cover Change in the Central Irregular Plains, 1973-2000

    USGS Publications Warehouse

    Karstensen, Krista A.

    2009-01-01

    Spearheaded by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA), the Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000 and 1973-2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land Use Land Cover Classification System for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion. The results illustrate that there is no single profile of land-cover change but instead point to geographic variability that results from land uses within ecoregions continuously adapting to various factors including environmental, technological, and socioeconomic.

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

    NASA Technical Reports Server (NTRS)

    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.

  13. A comparative study on manifold learning of hyperspectral data for land cover classification

    NASA Astrophysics Data System (ADS)

    Ozturk, Ceyda Nur; Bilgin, Gokhan

    2015-03-01

    This paper focuses on the land cover classification problem by employing a number of manifold learning algorithms in the feature extraction phase, then by running single and ensemble of classifiers in the modeling phase. Manifolds are learned on training samples selected randomly within available data, while the transformation of the remaining test samples is realized for linear and nonlinear methods via the learnt mappings and a radial-basis function neural network based interpolation method, respectively. The classification accuracies of the original data and the embedded manifolds are investigated with several classifiers. Experimental results on a 200-band hyperspectral image indicated that support vector machine was the best classifier for most of the methods, being nearly as accurate as the best classification rate of the original data. Furthermore, our modified version of random subspace classifier could even outperform the classification accuracy of the original data for local Fisher's discriminant analysis method despite of a considerable decrease in the extrinsic dimension.

  14. Spaceborne SAR data for land-cover classification and change detection

    NASA Technical Reports Server (NTRS)

    Brisco, B.; Ulaby, F. T.; Dobson, M. C.

    1983-01-01

    Supervised maximum-likelihood classifications of Seasat, SIR-A, and Landsat pixel data demonstrated that SIR-A data provided the most accurate discrimination (72 percent) between five land-cover categories. Spatial averaging of the SAR data improved classification accuracy significantly due to a reduction in both fading and within-field variability. The best multichannel classification accuracy (97.5 percent) was achieved by combining the SIR-A data with two Seasat images (ascending and descending orbits). In addition, semiquantitative analysis of Seasat-A digital data shows that orbital SAR imagery can be successfully used for multitemporal detection of change related to hydrologic and agronomic conditions by using simple machine processing techniques.

  15. A stepwise regression tree for nonlinear approximation: applications to estimating subpixel land cover

    USGS Publications Warehouse

    Huang, C.; Townshend, J.R.G.

    2003-01-01

    A stepwise regression tree (SRT) algorithm was developed for approximating complex nonlinear relationships. Based on the regression tree of Breiman et al . (BRT) and a stepwise linear regression (SLR) method, this algorithm represents an improvement over SLR in that it can approximate nonlinear relationships and over BRT in that it gives more realistic predictions. The applicability of this method to estimating subpixel forest was demonstrated using three test data sets, on all of which it gave more accurate predictions than SLR and BRT. SRT also generated more compact trees and performed better than or at least as well as BRT at all 10 equal forest proportion interval ranging from 0 to 100%. This method is appealing to estimating subpixel land cover over large areas.

  16. Land cover change using an energy transition paradigm in a statistical mechanics approach

    NASA Astrophysics Data System (ADS)

    Zachary, Daniel S.

    2013-10-01

    This paper explores a statistical mechanics approach as a means to better understand specific land cover changes on a continental scale. Integrated assessment models are used to calculate the impact of anthropogenic emissions via the coupling of technoeconomic and earth/atmospheric system models and they have often overlooked or oversimplified the evolution of land cover change. Different time scales and the uncertainties inherent in long term projections of land cover make their coupling to integrated assessment models difficult. The mainstream approach to land cover modelling is rule-based methodology and this necessarily implies that decision mechanisms are often removed from the physical geospatial realities, therefore a number of questions remain: How much of the predictive power of land cover change can be linked to the physical situation as opposed to social and policy realities? Can land cover change be understood using a statistical approach that includes only economic drivers and the availability of resources? In this paper, we use an energy transition paradigm as a means to predict this change. A cost function is applied to developed land covers for urban and agricultural areas. The counting of area is addressed using specific examples of a Pólya process involving Maxwell-Boltzmann and Bose-Einstein statistics. We apply an iterative counting method and compare the simulated statistics with fractional land cover data with a multi-national database. An energy level paradigm is used as a basis in a flow model for land cover change. The model is compared with tabulated land cover change in Europe for the period 1990-2000. The model post-predicts changes for each nation. When strong extraneous factors are absent, the model shows promise in reproducing data and can provide a means to test hypothesis for the standard rules-based algorithms.

  17. Land Cover of Northern Eurasia: Comparison and Assessment of Coarse Resolution Maps

    NASA Astrophysics Data System (ADS)

    Krankina, O. N.; Pflugmacher, D.; Cohen, W.; Kennedy, R.; Nelson, P.; Loboda, T.

    2007-12-01

    Consistent measurements of land cover are critical for addressing a range of important science questions, from quantifying the effects of vegetation on the carbon, energy, and water cycles, to understanding the social and economic causes and consequences of land-use and land-cover change. While multiple moderate and coarse- resolution land-cover products have been developed, they disagree significantly. Resolving discrepancies among maps is particularly challenging for boreal and temperate Northern Eurasia, where validation sites are sparse and processes of ecosystem disturbance and land-cover change are widespread. To identify specific needs and possibilities for improved mapping of land cover across boreal and temperate Northern Eurasia, we compared the performance of three recent land-cover products based on different sensors: MODIS (Global Land Cover Collection 4), AVHRR (DISCover v. 2.0), and SPOT VEGETATION (GLC2000 for Northern Eurasia v. 4.0). First, we examined the level of agreement among these data sets across the entire region. On a qualitative level, the assessment of general patterns indicates the highest degree of disagreement in transitional zones at the northern and southern fringes of boreal forest, in mountainous regions, and in areas of extensive wetlands, agricultural development, and urban land use. The quantitative analysis measured the level of disagreement between land-cover classes aggregated according to dominant type of vegetation (trees, shrubs, herbaceous, bare land, permanent snow/ice). Secondly, validation of these products was performed at two test sites where Landsat-based classifications were developed based on FAO Land Cover Classification System. Fractional land cover was calculated for each 1x1 km pixel and used to construct fractional error matrices. Most errors were associated with "mixed" coarse-resolution pixels (i.e. those having nearly equal percentage of multiple class types), while errors in "pure" (single class) pixels

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

    NASA Astrophysics Data System (ADS)

    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.

  19. Modeling interactions between land cover and climate in integrated assessment models (Invited)

    NASA Astrophysics Data System (ADS)

    Calvin, K. V.

    2013-12-01

    Integrated Assessment Models (IAMs) link representations of the regionally disaggregated global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate in an internally consistent framework. These models are often used as science-based decision-support tools for evaluating the consequences of climate, energy, and other policies, and their use in this framework is likely to increase in the future. Additionally, these models are used to develop future scenarios of emissions and land cover for use in climate models (e.g., RCPs and CMIP5). Land use is strongly influenced by assumptions about population, income, diet, ecosystem productivity change, and climate policy. Population, income, and diet determine the amount of food production needed in the future. Assumptions about future changes in crop yields due to agronomic developments influence the amount of land needed to produce food crops. Climate policy has implications for land when land-based mitigation options (e.g., afforestation and bioenergy) are considered. IAM models consider each of these factors in their computation of land use in the future. As each of these factors is uncertain in the future, IAM models use scenario analysis to explore the implications of each. For example, IAMs have been used to explore the effect of different mitigation policies on land cover. These models can quantify the trade-offs in terms of land cover, energy prices, food prices, and mitigation costs of each of these policies. Furthermore, IAMs are beginning to explore the effect of climate change on land productivity, and the implications that changes in productivity have on mitigation efforts. In this talk, we describe the implications for future land use and land cover of a variety of socioeconomic, technological, and policy drivers in several IAM models. Additionally, we will discuss the effects of future land cover on climate and the effects of climate on future land cover, as simulated

  20. Land-use and land-cover change in Western Ghats of India.

    PubMed

    Kale, Manish P; Chavan, Manoj; Pardeshi, Satish; Joshi, Chitiz; Verma, Prabhakar A; Roy, P S; Srivastav, S K; Srivastava, V K; Jha, A K; Chaudhari, Swapnil; Giri, Yogesh; Krishna Murthy, Y V N

    2016-07-01

    The Western Ghats (WG) of India, one of the hottest biodiversity hotspots in the world, has witnessed major land-use and land-cover (LULC) change in recent times. The present research was aimed at studying the patterns of LULC change in WG during 1985-1995-2005, understanding the major drivers that caused such change, and projecting the future (2025) spatial distribution of forest using coupled logistic regression and Markov model. The International Geosphere Biosphere Program (IGBP) classification scheme was mainly followed in LULC characterization and change analysis. The single-step Markov model was used to project the forest demand. The spatial allocation of such forest demand was based on the predicted probabilities derived through logistic regression model. The R statistical package was used to set the allocation rules. The projection model was selected based on Akaike information criterion (AIC) and area under receiver operating characteristic (ROC) curve. The actual and projected areas of forest in 2005 were compared before making projection for 2025. It was observed that forest degradation has reduced from 1985-1995 to 1995-2005. The study obtained important insights about the drivers and their impacts on LULC simulations. To the best of our knowledge, this is the first attempt where projection of future state of forest in entire WG is made based on decadal LULC and socio-economic datasets at the Taluka (sub-district) level. PMID:27256392

  1. Land use/land cover water quality nexus: quantifying anthropogenic influences on surface water quality.

    PubMed

    Wilson, Cyril O

    2015-07-01

    Anthropogenic forces widely influence the composition, configuration, and trend of land use and land cover (LULC) changes with potential implications for surface water quality. These changes have the likelihood of generating non-point source pollution with additional environmental implications for terrestrial and aquatic ecosystems. Monitoring the scope and trajectory of LULC change is pivotal for region-wide planning, tracking the sustainability of natural resources, and meeting the information needs of policy makers. A good comprehension of the dynamics of anthropogenic drivers (proximate and underlying) that influence such changes in LULC is important because any potential adverse change in LULC that may be inimical to sustainable water quality might be addressed at the anthropogenic driver level rather than the LULC change stage. Using a dense time stack of Landsat-5 Thematic Mapper images, a hydrologic water quality and socio-geospatial modeling framework, this study quantifies the role of anthropogenic drivers of LULC change on total suspended solids and total phosphorus concentrations in the Lower Chippewa River Watershed, Wisconsin, at three time steps-1990, 2000, and 2010. Results of the study demonstrated that proximate drivers of LULC change accounted for between 32 and 59% of the concentration and spatial distribution of total suspended solids, while the extent of phosphorus impairment attributed to the proximate drivers ranged between 31 and 42%. PMID:26065891

  2. Global land cover knowledge database for supporting optical remote sensing satellite intelligent imaging

    NASA Astrophysics Data System (ADS)

    Yan, Ming; Wang, Zhiyong; He, Shaoshuai; Wu, Fei; Yu, Bingyang

    2014-05-01

    With the development of high spatial resolution, high spectral resolution, high radiant resolution and high temporal resolution remote sensing satellites being put into use widely, the adaptive intelligent observation becomes an important function of a new generation of satellite remote sensing system. In order to realize the adaptive intelligent observation function, the first step is to construct the land cover priori knowledge and prejudge the land cover types and its reflectance values of the imaging areas. During the satellite imaging, the setting parameters of optimal camera including the on-orbit CCD integral time, electrical gain and image compression ratio are estimated according to the relationship of apparent radiance with sun illumination condition and land surface reflectance. In the paper, Medium Resolution Imaging Spectrometer (MERIS) bimonthly mean land surface reflectance imagery and 2009 GlobCover map are used to build the global land cover and its reflectance knowledge database. The land cover types include the cropland, urban, grassland, forest, desert, soil, water and ice land cover classes and the mean reflectance values in blue, green, red and near infrared spectral band were calculated in various seasons. The global land cover and reflectance values database has been integrated into the Beijing-1 small satellite mission programming system as the priori landscape knowledge of imaging areas to estimate the proper electrical gain of multispectral camera. After the intelligent observation mode was used in Beijing-1 small satellite, the entropy and SNR of multispectral imagery acquired by the Beijing-1 satellite had been increased greatly.

  3. Predictive Understanding of Seasonal Hydrological Dynamics under Climate and Land Use-Land Cover Change

    NASA Astrophysics Data System (ADS)

    Batra, N.; Yang, Y. E.; Choi, H. I.; Kumar, P.; Cai, X.; Fraiture, C. D.

    2008-12-01

    Water has always been and will continue to be an important factor in agricultural production and any alteration in the seasonal distribution of water availability due to climate and land use-land cover change (LULCC) will significantly impact the future production. To achieve the ecologic, economic and social objectives of sustainability, physical understanding of the linkages between climatic changes, LULCC and hydrological response is required. Aided by satellite data, modeling and understanding of the interactions between physical processes of the climate system and society, more reliable regional LULCC and climate change projections are now available. However, resulting quantitative projection of changes on the regional scale hydrological components at the seasonal time scale are sparse. This study attempts to quantify the seasonal hydrological response due to projected LULCC and climate change scenario of Intergovernmental Panel on Climate Change (IPCC) in different hydro-climatic regions of the world. The Common Land Model (CLM) is used for global assessment of future hydrologic response with the development of a consistent global GIS based database for the surface boundary conditions and meteorological forcing of the model. Future climate change projections are derived from the IPCC Fourth Assessment Report: Working Group I - The Physical Science Basis. The study is performed over nine river basins selected from Asia, Africa and North America to present the broad climatic and landscape controls on the seasonal hydrological dynamics. Future changes in water availability are quite evident from our results based upon changes in the volume and seasonality of precipitation, runoff and evapotranspiration. Severe water scarcity is projected to occur in certain seasons which may not be known through annual estimates. Knowledge of the projected seasonal hydrological response can be effectively used for developing adaptive management strategies for the sustainability

  4. Impact of AWiFS derived land use land cover on simulation of heavy rainfall

    NASA Astrophysics Data System (ADS)

    Karri, Srinivasarao; Gharai, Biswadip; Sai Krishna, S. V. S.; Rao, P. V. N.

    2016-05-01

    Land use/land cover (LU/LC) changes are considered to be one of the most important factors affecting regional climate and are thus an area of public concern. The land surface plays a crucial role in boundary layer evolution and precipitation patterns thereby establishing the need for LU/LC inputs as a critical part of modeling systems. Inaccurate LU/LC information often leads to very large errors in surface energy fluxes thus leading to errors in boundary layer state. We have investigated an incident of heavy rainfall during August 2015 over West Bengal, India using Weather Research and Forecast (WRF) model by incorporating different LU/LC datasets, IRS P6 Advanced Wide Field Sensor (AWiFS) LU/LC data for 2012-13 and the default Moderate Resolution Imaging Spectro-radiometer (MODIS) derived USGS LU/LC data for 2001. In the present study, we have made a comparative assessment between AWiFS derived LU/LC and USGS LU/LC by incorporating these datasets as one of the lower boundary conditions over Indian region in WRF model version 3.5.1 to simulate, at 10km resolution, a heavy rainfall event associated with landfall of a cyclonic system over West Bengal. The results of the study suggested influence of LU/LC in occurrence of heavy rainfall with WRF model using AWiFS LU/LC showing more realistic simulation as AWiFS LU/LC is more up-to-date and features recent changes in LU/LC over India.

  5. Comparison of MODIS derived land use and land cover with Ministry of Agriculture reported statistics for India

    NASA Astrophysics Data System (ADS)

    Acharya, Prasenjit; Punia, Milap

    2013-01-01

    The purpose of the study is to evaluate the suitability of moderate-resolution imaging spectroradiometer (MODIS) data to study the land use land cover over India. The study is based on secondary data sets pertaining to forest, cropland, pasture, and barrenland obtained from Directorate of Economics and Statistics (DES) and MODIS (Terra) global land use land cover data yearly composite from 2002 to 2005. A family of statistical and mathematical techniques is adopted here in order to compare the MODIS data with DES statistics. The comparison at the country level shows estimated forest cover has least uncertainty compared to pasture and barrenland. Comparison at the state level, on the other hand, shows high degree of association between the data sets in cropland (R2=0.9), followed by forest cover and pastureland. Barrenland shows weakest association between DES and MODIS. The computed average accuracy in cropland shows a level of 84% and has been chosen as the best fitted land cover category among all land cover classes selected for the study. Hierarchical clustering of the MODIS cropland at the state level based on the estimated accuracy shows that, except for Andhra Pradesh, Tamilnadu, Haryana, West Bengal, Chhattisgarh, and Orissa, which are far off from the true estimate, the rest of the states are in closer correspondence of the cropland statistics reported by Ministry of Agriculture.

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

    USGS Publications Warehouse

    Karstensen, Krista A.

    2009-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Use of Satellite Data to Study the Impact of Land-Cover/Land-Use Change in Madison County Alabama.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing was used to analyze and study land-use/land-cover use changes impact on the environment of Madison County Alabama. This study area was selected because it is one of the fastest growing counties in the state of Alabama. The study used data sets obtained from several sources. Remote sen...

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

    EPA Science Inventory

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

  10. USGS Historical, Current, and Projected Future Land Cover Mapping for the Northern Great Plains

    NASA Astrophysics Data System (ADS)

    Sohl, T. L.; Gallant, A.; Sayler, K. L.

    2008-12-01

    Land cover in the Northern Great Plains has changed considerably in the last several decades. While a significant proportion of the landscape has been cultivated for over one hundred years, the intensity of cultivation, crop type, and management practices have changed in response to shifts in government policy, commodity prices, access to water, and technological advances. Changes in land cover impact a wide variety of ecosystem processes and services, including carbon balances, climate, hydrology and water quality, and biodiversity. A consistent record of historical land cover is required to understand relations between land- cover change and these ecological processes, while projections of future land cover are needed for planning and potential mitigation efforts. Several U.S. Geological Survey efforts have been completed or are ongoing in the Northern Great Plains, resulting in the compilation of an unmatched record of historical, current, and future land-cover information for the region. The USGS Land Cover Trends project is using the historical record of Landsat imagery and a robust sampling approach to examine the rates, causes, and consequences of contemporary (1973-2000) land-cover change on an ecoregional basis for the conterminous United States. Results from completed Trends analyses for Great Plains ecoregions revealed changes in the proportion and distribution of grassland/shrubland and agricultural uses during the study period; Some areas exhibited considerable loss in cultivated land after initiation of the Conservation Reserve Program (CRP) in the mid 1980s. In recent years (post-2000), agricultural commodity prices have skyrocketed as food and energy compete for use of agricultural products, which in conjunction with the expiration of many CRP contracts, has led to expansion of cultivated land. In the coming decades, calls for U.S. energy independence and the development of biofuels from cellulosic stock could result in a transformation of the Great

  11. Fire Emissions Estimates in Siberia: Evaluation of Uncertainties in Area Burned, Land Cover, and Fuel Consumption

    NASA Astrophysics Data System (ADS)

    Kukavskaya, E.; Soja, A. J.; Ivanova, G. A.; Petkov, A.; Ponomarev, E. I.; Conard, S. G.

    2012-12-01

    Wildfire is one of the main disturbance factors in the boreal zone of Russia. Fires in the Russian boreal forest range from low-severity surface fires to high-severity crown fires. Estimates of carbon emissions from fires in Russia vary substantially due to differences in ecosystem classification and mapping, burned area calculations, and estimates of fuel consumption. We examined uncertainties in different parameters used to estimate biomass burning emissions. Several fire datasets (Institute of Forest burned area product, MCD45, MCD64, MOD14/MYD14, official data) were compared to estimate uncertainties in area burned in Siberia. Area burned was found to differ significantly by data source, with satellite data being by an order of magnitude greater than ground-based data. Differences between mapped ecosystems were also compared and contrasted on the basis of five land cover maps (GLC-2000, Globcover-2009, MODIS Collection 4 and 5 Global Land Cover, and the Digitized Ecosystem map of the Former Soviet Union) to evaluate the potential for error resulting from disparate vegetation structure and fuel consumption estimates. The examination of land cover maps showed that estimates of relative proportion of fire by ecosystem type varied substantially for the same year from map to map. Fuel consumption remains one of the main uncertainties in estimates of biomass burning emissions in Siberia. Accurate fuel consumption estimates are obtained in the course of fire experiments with pre- and post-fire biomass measuring. Our large-scale experiments carried out in the course of the FIRE BEAR (Fire Effects in the Boreal Eurasia Region) Project provided quantitative and qualitative data on ecosystem state and carbon emissions due to fires of known behavior in major forest types of Siberia that could be used to verify large-scale carbon emissions estimates. Global climate change is expected to result in increase of fire hazard and area burned, leading to impacts on global air

  12. Monitoring land use/cover changes on the Romanian Black Sea Coast

    NASA Astrophysics Data System (ADS)

    Zoran, L. F. V.; Dida, A. I.; Zoran, M. A.

    2014-10-01

    Remotely sensed satellite data are critical to understanding the coastal zones' physical and social systems interaction, complementing ground based methods and providing accurate wide range, objective and comparable, at widely-varying scales, synoptically data. For some environmental agreements remote sensing may provide the only viable means of compliance verification because the phenomena are monitored occurs over large and inaccessible geographic areas. The main aim of this paper was the assessment of coastal zone land cover/use changes based on fusion technique of satellite remote sensing imagery. The evaluation of coastal zone landscapes was based upon different sub-functions which refer to landscape features such as water, soil, land-use, buildings, groundwater, biotope types. A newly proposed sub-pixel mapping algorithm was applied to a set of multispectral and multitemporal satellite data for Danube Delta, Constantza and Black Sea coastal zone areas in Romania. A land cover classification and subsequent environmental quality analysis for change detection was done based on Landsat TM , Landsat ETM, QuickBird satellite images over 1990 to 2013 period of time. Spectral signatures of different terrain features have been used to separate and classify surface units of coastal zone and sub-coastal zone area.The change in the position of the coastline in Constantza area was examined in relation with the urban expansion. A distinction was made between landfill/sedimentation processes on the one hand and dredging/erosion processes on the other. We considered the Romanian Black Sea coastal zone dynamics in connection with the spatio-temporal variation of physical and biogeochemical processes and their influences on the environmental state in the near-shore area.

  13. The experience of land cover change detection by satellite data

    NASA Astrophysics Data System (ADS)

    Spivak, Lev; Vitkovskaya, Irina; Batyrbayeva, Madina; Terekhov, Alexey

    2012-06-01

    Sigificant dependence from climate and anthropogenic influences characterize ecological systems of Kazakhstan. As result of the geographical location of the republic and ecological situation vegetative degradation sites exist throughout the territory of Kazakhstan. The major process of desertification takes place in the arid and semi-arid areas. To allocate spots of stable degradation of vegetation, the transition zone was first identified. Productivity of vegetation in transfer zone is slightly dependent on climate conditions. Multi-year digital maps of vegetation index were generated with NOAA satellite images. According to the result, the territory of the republic was zoned by means of vegetation productivity criterion. All the arable lands in Kazakhstan are in the risky agriculture zone. Estimation of the productivity of agricultural lands is highly important in the context of risky agriculture, where natural factors, such as wind and water erosion, can significantly change land quality in a relatively short time period. We used an integrated vegetation index to indicate land degradation measures to assess the inter-annual features in the response of vegetation to variations in climate conditions from low-resolution satellite data for all of Kazakhstan. This analysis allowed a better understanding of the spatial and temporal variations of land degradation in the country.

  14. Quantifying Urban Watershed Stressor Gradients and Evaluating How Different Land Cover Datasets Affect Stream Management

    NASA Astrophysics Data System (ADS)

    Smucker, Nathan J.; Kuhn, Anne; Charpentier, Michael A.; Cruz-Quinones, Carlos J.; Elonen, Colleen M.; Whorley, Sarah B.; Jicha, Terri M.; Serbst, Jonathan R.; Hill, Brian H.; Wehr, John D.

    2016-03-01

    Watershed management and policies affecting downstream ecosystems benefit from identifying relationships between land cover and water quality. However, different data sources can create dissimilarities in land cover estimates and models that characterize ecosystem responses. We used a spatially balanced stream study (1) to effectively sample development and urban stressor gradients while representing the extent of a large coastal watershed (>4400 km2), (2) to document differences between estimates of watershed land cover using 30-m resolution national land cover database (NLCD) and <1-m resolution land cover data, and (3) to determine if predictive models and relationships between water quality and land cover differed when using these two land cover datasets. Increased concentrations of nutrients, anions, and cations had similarly significant correlations with increased watershed percent impervious cover (IC), regardless of data resolution. The NLCD underestimated percent forest for 71/76 sites by a mean of 11 % and overestimated percent wetlands for 71/76 sites by a mean of 8 %. The NLCD almost always underestimated IC at low development intensities and overestimated IC at high development intensities. As a result of underestimated IC, regression models using NLCD data predicted mean background concentrations of NO3 - and Cl- that were 475 and 177 %, respectively, of those predicted when using finer resolution land cover data. Our sampling design could help states and other agencies seeking to create monitoring programs and indicators responsive to anthropogenic impacts. Differences between land cover datasets could affect resource protection due to misguided management targets, watershed development and conservation practices, or water quality criteria.

  15. Quantifying Urban Watershed Stressor Gradients and Evaluating How Different Land Cover Datasets Affect Stream Management.

    PubMed

    Smucker, Nathan J; Kuhn, Anne; Charpentier, Michael A; Cruz-Quinones, Carlos J; Elonen, Colleen M; Whorley, Sarah B; Jicha, Terri M; Serbst, Jonathan R; Hill, Brian H; Wehr, John D

    2016-03-01

    Watershed management and policies affecting downstream ecosystems benefit from identifying relationships between land cover and water quality. However, different data sources can create dissimilarities in land cover estimates and models that characterize ecosystem responses. We used a spatially balanced stream study (1) to effectively sample development and urban stressor gradients while representing the extent of a large coastal watershed (>4400 km(2)), (2) to document differences between estimates of watershed land cover using 30-m resolution national land cover database (NLCD) and <1-m resolution land cover data, and (3) to determine if predictive models and relationships between water quality and land cover differed when using these two land cover datasets. Increased concentrations of nutrients, anions, and cations had similarly significant correlations with increased watershed percent impervious cover (IC), regardless of data resolution. The NLCD underestimated percent forest for 71/76 sites by a mean of 11 % and overestimated percent wetlands for 71/76 sites by a mean of 8 %. The NLCD almost always underestimated IC at low development intensities and overestimated IC at high development intensities. As a result of underestimated IC, regression models using NLCD data predicted mean background concentrations of NO3 (-) and Cl(-) that were 475 and 177 %, respectively, of those predicted when using finer resolution land cover data. Our sampling design could help states and other agencies seeking to create monitoring programs and indicators responsive to anthropogenic impacts. Differences between land cover datasets could affect resource protection due to misguided management targets, watershed development and conservation practices, or water quality criteria. PMID:26614349

  16. Land Application of Wastes: An Educational Program. Role of Vegetative Cover - Module 7, Objectives, and Script.

    ERIC Educational Resources Information Center

    Clarkson, W. W.; And Others

    This module discusses some of the objectives of incorporating vegetative cover in land treatment systems. Specific crops and forest cover are mentioned in relation to benefits associated with each, and specific treatment alternatives (irrigation, overland flow, and rapid infiltration) are included in relation to vegetative cover considerations.…

  17. Quantifying Urban Watershed Stressor Gradients and Evaluating How Different Land Cover Datasets Affect Stream Management

    EPA Science Inventory

    We used a gradient (divided into impervious cover categories), spatially-balanced, random design (1) to sample streams along an impervious cover gradient in a large coastal watershed, (2) to characterize relationships between water chemistry and land cover, and (3) to document di...

  18. Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping.

    PubMed

    Qin, Yuchu; Li, Shihua; Vu, Tuong-Thuy; Niu, Zheng; Ban, Yifang

    2015-06-01

    Urban land cover map is essential for urban planning, environmental studies and management. This paper aims to demonstrate the potential of geometric and radiometric features derived from LiDAR waveform and point cloud data in urban land cover mapping with both parametric and non-parametric classification algorithms. Small footprint LiDAR waveform data acquired by RIEGL LMS-Q560 in Zhangye city, China is used in this study. A LiDAR processing chain is applied to perform waveform decomposition, range determination and radiometric characterization. With the synergic utilization of geometric and radiometric features derived from LiDAR data, urban land cover classification is then conducted using the Maximum Likelihood Classification (MLC), Support Vector Machines (SVM) and random forest algorithms. The results suggest that the random forest classifier achieved the most accurate result with overall classification accuracy of 91.82% and the kappa coefficient of 0.88. The overall accuracies of MLC and SVM are 84.02, and 88.48, respectively. The study suggest that the synergic utilization of geometric and radiometric features derived from LiDAR data can be efficiently used for urban land cover mapping, the non-parametric random forest classifier is a promising approach for the various features with different physical meanings. PMID:26072748

  19. Multiple-class land-cover mapping at the sub-pixel scale using a Hopfield neural network

    NASA Astrophysics Data System (ADS)

    Tatem, Andrew J.; Lewis, Hugh G.; Atkinson, Peter M.; Nixon, Mark S.

    Land cover class composition of image pixels can be estimated using soft classification techniques. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Robust techniques to provide an improved spatial representation of land cover have yet to be developed. The use of a Hopfield neural network technique to map the spatial distributions of classes reliably using information of pixel composition determined from soft classification was investigated in previous papers by Tatem et al. The network converges to a minimum of an energy function defined as a goal and several constraints. The approach involved designing the energy function to produce a 'best guess' prediction of the spatial distribution of class components in each pixel. Tatem et al described the application of the technique to target mapping at the sub-pixel scale, but only for single classes. We now show how this approach can be extended to map multiple classes at the sub-pixel scale, by adding new constraints into the energy formulation. The new technique has been applied to simulated SPOT HRV and Landsat TM agriculture imagery to derive accurate estimates of land cover. The results show that this extension of the neural network now represents a simple efficient tool for mapping land cover and can deliver requisite results for the analysis of practical remotely sensed imagery at the sub pixel scale.

  20. Land cover, land use and malaria in the Amazon: a systematic literature review of studies using remotely sensed data

    PubMed Central

    2013-01-01

    The nine countries sharing the Amazon forest accounted for 89% of all malaria cases reported in the Americas in 2008. Remote sensing can help identify the environmental determinants of malaria transmission and their temporo-spatial evolution. Seventeen studies characterizing land cover or land use features, and relating them to malaria in the Amazon subregion, were identified. These were reviewed in order to improve the understanding of the land cover/use class roles in malaria transmission. The indicators affecting the transmission risk were summarized in terms of temporal components, landscape fragmentation and anthropic pressure. This review helps to define a framework for future studies aiming to characterize and monitor malaria. PMID:23758827

  1. Thematic accuracy of MRLC land cover for the eastern United States

    USGS Publications Warehouse

    Yang, Limin; Stehman, Stephen V.; Smith, Jonathan H.; Wickham, James D.

    2001-01-01

    One objective of the MultiResolution Land Characteristics (MRLC) consortium is to map general land-cover categories for the conterminous United States using Landsat Thematic Mapper (TM) data. Land-cover mapping and classification accuracy assessment are complete for the eastern United States. The accuracy assessment was based on photo-interpreted reference data obtained from a stratified probability sample of pixels. Agreement was defined as a match between primary or alternate reference land-cover labels assigned to each sample pixel and the mode (most common class) of the map's land-cover labels within a 3×3-pixel neighborhood surrounding the sampled point. At 30-m resolution, overall accuracy was 59.7% at an Anderson Level II thematic detail, and 80.5% at Anderson Level I.

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

    NASA Astrophysics Data System (ADS)

    Huang, Kuo-Ching; Huang, Thomas C. C.

    2014-02-01

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

  3. Representation of natural and anthropogenic land cover change in MPI-ESM

    NASA Astrophysics Data System (ADS)

    Reick, C. H.; Raddatz, T.; Brovkin, V.; Gayler, V.

    2013-07-01

    The purpose of this paper is to give a rather comprehensive description of the models for natural and anthropogenically driven changes in biogeography as implemented in the land component JSBACH of the Max Planck Institute Earth system model (MPI-ESM). The model for natural land cover change (DYNVEG) features two types of competition: between the classes of grasses and woody types (trees, shrubs) controlled by disturbances (fire, windthrow) and within those vegetation classes between different plant functional types based on relative net primary productivity advantages. As part of this model, the distribution of land unhospitable to vegetation (hot and cold deserts) is determined dynamically from plant productivity under the prevailing climate conditions. The model for anthropogenic land cover change implements the land use transition approach by Hurtt et al. (2006). Our implementation is based on the assumption that historically pastures have been preferentially established on former grasslands ("pasture rule"). We demonstrate that due to the pasture rule, deforestation reduces global forest area between 1850 and 2005 by 15% less than without. Because of the pasture rule the land cover distribution depends on the full history of land use transitions. This has implications for the dynamics of natural land cover change because assumptions must be made on how agriculturalists react to a changing natural vegetation in their environment. A separate model representing this process has been developed so that natural and anthropogenic land cover change can be simulated consistently. Certain aspects of our model implementation are illustrated by selected results from the recent CMIP5 simulations.

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

    NASA Astrophysics Data System (ADS)

    Stanelle, Tanja; Henrot, Alexandra; Bey, Isaelle

    2015-04-01

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

  5. The analysis accuracy assessment of CORINE land cover in the Iberian coast

    NASA Astrophysics Data System (ADS)

    Grullón, Yraida R.; Alhaddad, Bahaaeddin; Cladera, Josep R.

    2009-09-01

    Corine land cover 2000 (CLC2000) is a project jointly managed by the Joint Research Centre (JRC) and the European Environment Agency (EEA). Its aim is to update the Corine land cover database in Europe for the year 2000. Landsat-7 Enhanced Thematic Mapper (ETM) satellite images were used for the update and were acquired within the framework of the Image2000 project. Knowledge of the land status through the use of mapping CORINE Land Cover is of great importance to study of interaction land cover and land use categories in Europe scale. This paper presents the accuracy assessment methodology designed and implemented to validate the Iberian Coast CORINE Land Cover 2000 cartography. It presents an implementation of a new methodological concept for land cover data production, Object- Based classification, and automatic generalization to assess the thematic accuracy of CLC2000 by means of an independent data source based on the comparison of the land cover database with reference data derived from visual interpretation of high resolution satellite imageries for sample areas. In our case study, the existing Object-Based classifications are supported with digital maps and attribute databases. According to the quality tests performed, we computed the overall accuracy, and Kappa Coefficient. We will focus on the development of a methodology based on classification and generalization analysis for built-up areas that may improve the investigation. This study can be divided in these fundamental steps: -Extract artificial areas from land use Classifications based on Land-sat and Spot images. -Manuel interpretation for high resolution of multispectral images. -Determine the homogeneity of artificial areas by generalization process. -Overall accuracy, Kappa Coefficient and Special grid (fishnet) test for quality test. Finally, this paper will concentrate to illustrate the precise accuracy of CORINE dataset based on the above general steps.

  6. Land Cover Characterization for Hydrological Modeling Using Thermal Infrared Emissivities

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing with multispectral thermal infrared observations has the potential to improve regional scale estimation of evapotranspiration (ET) by constraining the land surface energy balance in a way that is not possible using more conventional remote sensing techniques. Current models use data f...

  7. PERCENT AGRICULTURAL LAND COVER ON STEEP SLOPES (FUTURE)

    EPA Science Inventory

    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. High amounts of agriculture on steep slopes can increase the amount of soil erosion leading to increased sediment in ...

  8. Nowitna National Wildlife Refuge land cover mapping project users guide

    USGS Publications Warehouse

    Markon, Carl J.

    1988-01-01

    Title III of the Alaska National Interest Lands Conservation Act of 1980 (ANILCA 1980) established the Nowitna National Wildlife Refuge (NNWR).  Section 304 of the Act requires the Secretary of Interior to "prepare, and from time to time revise, a comprehensive conservation plan" for the refuge.  

  9. Impact of land cover uncertainties on estimates of biospheric carbon fluxes

    NASA Astrophysics Data System (ADS)

    Quaife, T.; Quegan, S.; Disney, M.; Lewis, P.; Lomas, M.; Woodward, F. I.

    2008-12-01

    Large-scale bottom-up estimates of terrestrial carbon fluxes, whether based on models or inventory, are highly dependent on the assumed land cover. Most current land cover and land cover change maps are based on satellite data and are likely to be so for the foreseeable future. However, these maps show large differences, both at the class level and when transformed into Plant Functional Types (PFTs), and these can lead to large differences in terrestrial CO2 fluxes estimated by Dynamic Vegetation Models. In this study the Sheffield Dynamic Global Vegetation Model is used. We compare PFT maps and the resulting fluxes arising from the use of widely available moderate (1 km) resolution satellite-derived land cover maps (the Global Land Cover 2000 and several MODIS classification schemes), with fluxes calculated using a reference high (25 m) resolution land cover map specific to Great Britain (the Land Cover Map 2000). We demonstrate that uncertainty is introduced into carbon flux calculations by (1) incorrect or uncertain assignment of land cover classes to PFTs; (2) information loss at coarser resolutions; (3) difficulty in discriminating some vegetation types from satellite data. When averaged over Great Britain, modeled CO2 fluxes derived using the different 1 km resolution maps differ from estimates made using the reference map. The ranges of these differences are 254 gC m-2 a-1 in Gross Primary Production (GPP); 133 gC m-2 a-1 in Net Primary Production (NPP); and 43 gC m-2 a-1 in Net Ecosystem Production (NEP). In GPP this accounts for differences of -15.8% to 8.8%. Results for living biomass exhibit a range of 1109 gC m-2. The types of uncertainties due to land cover confusion are likely to be representative of many parts of the world, especially heterogeneous landscapes such as those found in western Europe.

  10. Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

    NASA Astrophysics Data System (ADS)

    Zhu, Z.; Woodcock, C. E.

    2012-12-01

    A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

  11. Soft supervised self-organizing mapping (3SOM) for improving land cover classification with MODIS time-series

    NASA Astrophysics Data System (ADS)

    Lawawirojwong, Siam

    Classification of remote sensing data has long been a fundamental technique for studying vegetation and land cover. Furthermore, land use and land cover maps are a basic need for environmental science. These maps are important for crop system monitoring and are also valuable resources for decision makers. Therefore, an up-to-date and highly accurate land cover map with detailed and timely information is required for the global environmental change research community to support natural resource management, environmental protection, and policy making. However, there appears to be a number of limitations associated with data utilization such as weather conditions, data availability, cost, and the time needed for acquiring and processing large numbers of images. Additionally, improving the classification accuracy and reducing the classification time have long been the goals of remote sensing research and they still require the further study. To manage these challenges, the primary goal of this research is to improve classification algorithms that utilize MODIS-EVI time-series images. A supervised self-organizing map (SSOM) and a soft supervised self-organizing map (3SOM) are modified and improved to increase classification efficiency and accuracy. To accomplish the main goal, the performance of the proposed methods is investigated using synthetic and real landscape data derived from MODIS-EVI time-series images. Two study areas are selected based on a difference of land cover characteristics: one in Thailand and one in the Midwestern U.S. The results indicate that time-series imagery is a potentially useful input dataset for land cover classification. Moreover, the SSOM with time-series data significantly outperforms the conventional classification techniques of the Gaussian maximum likelihood classifier (GMLC) and backpropagation neural network (BPNN). In addition, the 3SOM employed as a soft classifier delivers a more accurate classification than the SSOM applied as

  12. Identifying mangrove species and their surrounding land use and land cover classes using object-oriented approach with a lacunarity spatial measure

    USGS Publications Warehouse

    Myint, S.W.; Giri, C.P.; Wang, L.; Zhu, Z.; Gillete, S.C.

    2008-01-01

    Accurate and reliable information on the spatial distribution of mangrove species is needed for a wide variety of applications, including sustainable management of mangrove forests, conservation and reserve planning, ecological and biogeographical studies, and invasive species management. Remotely sensed data have been used for such purposes with mixed results. Our study employed an object-oriented approach with the use of a lacunarity technique to identify different mangrove species and their surrounding land use and land cover classes in a tsunami-affected area of Thailand using Landsat satellite data. Our results showed that the object-oriented approach with lacunarity-transformed bands is more accurate (over-all accuracy 94.2%; kappa coefficient = 0.91) than traditional per-pixel classifiers (overall accuracy 62.8%; and kappa coefficient = 0.57). Copyright ?? 2008 by Bellwether Publishing, Ltd. All rights reserved.

  13. Analysis of Land Cover Change in a Coastal Area using Remotely Sensed Data

    NASA Astrophysics Data System (ADS)

    Jaunzeme, I.; Kaļinka, M.; Reiniks, M.; Kaminskis, J.

    2015-11-01

    Coastal area monitoring is a significant task in the national development and environmental protection. Study area of this work is the Baltic Sea Region, particularly focusing on the land cover changes in the coastal area from Cape Kolka to the Latvian-Lithuanian border. The aim of this research is to estimate and illustrate different examples of monitoring and mapping land cover changes in the coastal area using remotely sensed data - orthophoto, multispectral data and radar data. The results of the research include vector maps created from satellite images and comparison between different land cover value identification methods.

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

    NASA Technical Reports Server (NTRS)

    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.

  15. A study of land use/land cover information extraction classification technology based on DTC

    NASA Astrophysics Data System (ADS)

    Wang, Ping; Zheng, Yong-guo; Yang, Feng-jie; Jia, Wei-jie; Xiong, Chang-zhen

    2008-10-01

    Decision Tree Classification (DTC) is one organizational form of the multi-level recognition system, which changes the complicated classification into simple categories, and then gradually resolves it. The paper does LULC Decision Tree Classification research on some areas of Gansu Province in the west of China. With the mid-resolution remote sensing data as the main data resource, the authors adopt decision-making classification technology method, taking advantage of its character that it imitates the processing pattern of human judgment and thinking and its fault-tolerant character, and also build the decision tree LULC classical pattern. The research shows that the methods and techniques can increase the level of automation and accuracy of LULC information extraction, and better carry out LULC information extraction on the research areas. The main aspects of the research are as follows: 1. We collected training samples firstly, established a comprehensive database which is supported by remote sensing and ground data; 2. By utilizing CART system, and based on multiply sources and time phases remote sensing data and other assistance data, the DTC's technology effectively combined the unsupervised classification results with the experts' knowledge together. The method and procedure for distilling the decision tree information were specifically developed. 3. In designing the decision tree, based on the various object of types classification rules, we established and pruned DTC'S model for the purpose of achieving effective treatment of subdivision classification, and completed the land use and land cover classification of the research areas. The accuracy of evaluation showed that the classification accuracy reached upwards 80%.

  16. Vegetation dynamics, and land use and land cover change in the Bale Mountains, Ethiopia.

    PubMed

    Kidane, Yohannes; Stahlmann, Reinhold; Beierkuhnlein, Carl

    2012-12-01

    Shifts in biological communities are occurring at rapid rates as human activities induced global climate change increases. Understanding the effects of the change on biodiversity is important to reduce loss of biodiversity and mass extinction, and to insure the long-term persistence of natural resources and natures' services. Especially in remote landscapes of developing countries, precise knowledge about on-going processes is scarce. Here we apply satellite imagery to assess spatio-temporal land use and land cover change (LULCC) in the Bale Mountains for a period of four decades. This study aims to identify the main drivers of change in vegetation patterns and to discuss the implications of LULCC on spatial arrangements and trajectories of floral communities. Remote sensing data acquired from Landsat MSS, Landsat ETM + and SPOT for four time steps (1973, 1987, 2000, and 2008) were analyzed using 11 LULC units defined based on the dominant plant taxa and cover types of the habitat. Change detection matrices revealed that over the last 40 years, the area has changed from a quite natural to a more cultural landscape. Within a representative subset of the study area (7,957.5 km(-2)), agricultural fields have increased from 1.71% to 9.34% of the total study area since 1973. Natural habitats such as upper montane forest, afroalpine grasslands, afromontane dwarf shrubs and herbaceous formations, and water bodies also increased. Conversely, afromontane grasslands have decreased in size by more than half (going from 19.3% to 8.77%). Closed Erica forest also shrank from 15.0% to 12.37%, and isolated Erica shrubs have decreased from 6.86% to 5.55%, and afroalpine dwarf shrubs and herbaceous formations reduced from 5.2% to 1.56%. Despite fluctuations the afromontane rainforest (Harenna forest), located south of the Bale Mountains, has remained relatively stable. In conclusion this study documents a rapid and ecosystem-specific change of this biodiversity hotspot due to

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  19. Temporal Variations of 12 sets (2001-2012) of MODIS Land-Cover Data over East Asia

    NASA Astrophysics Data System (ADS)

    Park, Ji Yeol; Suh, Myoung Seok

    2014-05-01

    MODIS land cover data sets are one of the widely used data in the various application studies, such as the land cover changes, desertification, and bottom boundary conditions for the numerical simulation models (NWP, RCM, GCM). In this study, we investigated the temporal variations of land cover over East Asian region using the 12 sets (2001-2012) of MODIS land cover data. The main issues addressed in this study are where and what kind of land cover type show frequent temporal variations. Because the frequent changes of land cover at the given location can be caused by the real changes of land cover or the erroneous classification. In general, there were increases in the evergreen broadleaf forest, deciduous needleleaf forest, and mixed forest. Whereas, the coverage of the woody Savannas and barren were significantly reduced. And land cover changes were reported in the 44% of total land area. In some pixels (about 26% of the land area), more than 4 times of land cover changes were found. The frequent changes of land cover types at the given location can be caused by the erroneous classification because the temporal variation of land cover is relatively slow. Among the 44% of land cover changed area, about 8.20 and 10.55% showed one and two times of land cover changes, respectively. This area can be caused by the real changes of land cover. The frequent changes in the land cover are mainly occurred at the Korean Peninsula, southern part of Shanghai, and the northern region of Beijing. Detailed analysis results on the temporal variations of MODIS land cover data will be presented.

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

    NASA Astrophysics Data System (ADS)

    Kontgis, Caitlin

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

  1. Historical land cover changes in the Great Lakes Region

    USGS Publications Warehouse

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

    1999-01-01

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

  2. Arctic National Wildlife Refuge land cover mapping project users guide

    USGS Publications Warehouse

    Markon, Carl J.

    1986-01-01

    Section 1002 of the Alaska National Interest Lands Conservation Act of 1980 (ANILCA, 1980) requires the Secretary of Interior to conduct a continuing study of fish, wildlife, and habitats on the coastal plain of the Arctic National Wildlife Refuge (ANWR). Included in this study is a determination of the extent, location, and carrying capacity of fish and wildlife habitats.

  3. Land-Cover Change in the Lower Mississippi Valley, 1973-2000

    USGS Publications Warehouse

    Karstensen, Krista A.; Sayler, Kristi L.

    2009-01-01

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

  4. Assessment of Digital Land Cover Maps for Hydrological Modeling in the Yampa River Basin, Colorado, USA

    NASA Astrophysics Data System (ADS)

    Repass, J. M.; Fassnacht, S.; Reich, R.

    2004-12-01

    Land cover data are required to parameterize watersheds for hydrological modeling. There is a multitude of different land cover maps, and determining which input data map for the model can be unclear. The goal of this study is to quantify the differences between various publically available land cover maps to determine their relative suitability for hydrological modeling of the Yampa River Basin in northern Colorado. The land cover maps compared in this study are derived from Advanced Very High Resolution Radiometer (AVHRR), Landsat Thematic Mapper (TM), and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. These maps are compared to a 30-m land cover map modeled from ground data and MODIS imagery. This map is regarded as "truth" in this investigation due to its fine resolution and use of recent ground data and imagery, and will be used to rank publicly available AVHRR and MODIS land cover maps. In order to compare the different land cover products, all data must be degraded to the coarsest spatial resolution (1 km) and the coarsest species resolution. Once this is accomplished, the maps are compared on 4 levels. The 4 comparisons are based on: (i) the relative agreement of the total aggregated land class percentages for the 1-km data present after the data has been cross-walked; (ii) pixel accuracy; (iii) scene accuracy; and (iv) cumulative streamflow model output from the US Geological Survey Precipitation-Runoff Modeling System (PRMS) in relation to observed cumulative streamflow. The results determine the best input land cover data for modeling streamflow in the Yampa River Basin, and provide information about the required spatial, spectral, and classification resolution of these maps to optimize results for streamflow modeling.

  5. Estimation of late twentieth century land-cover change in California

    USGS Publications Warehouse

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

    2011-01-01

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

  6. High resolution scenarios of land-use and land-cover change for the conterminous United States

    NASA Astrophysics Data System (ADS)

    Sleeter, B. M.; Sohl, T. L.; Bouchard, M. A.; Reker, R. R.; Sayler, K.; Sleeter, R.; Soulard, C. E.; Wilson, T. S.

    2012-12-01

    We describe a series of high resolution maps of past and projected changes in land use and land cover (LULC) for the conterminous United States for the period 1992 to 2100. Four scenarios from the Intergovernmental Panel on Climate Change's (IPCC) Special Report on Emission Scenarios (SRES) were used to create annual maps showing spatially explicit change in 15 LULC classes at a spatial resolution of 250 meters. A modular land-use modeling approach was utilized with distinct demand and spatial allocation components. To quantify demand for future LULC change (i.e. the quantity of changes in land use and land cover classes), a scenario downscaling model was developed to extend global scenarios from the IPCC to hierarchically nested ecoregions of the U.S. The Forecasting Scenarios (FORE-SCE) land use model was then employed to allocate scenario demand on the landscape. Both models were parameterized at the ecoregion scale and relied extensively on land use histories and expert knowledge. Results reveal large differences across IPCC-SRES scenarios. Scenarios prioritizing economic development over environmental protection result in the highest rates of LULC change, particularly in regions with extensive forest management, large urban areas, and/or large investments in agricultural land. Scenarios where environmental protection is emphasized result in slower rates of change and less intensity in regional land use patterns.

  7. Are We Capturing the True Impacts of Anthropogenic Land Cover Forcings in ESMs?

    NASA Astrophysics Data System (ADS)

    Feddema, J. J.

    2014-12-01

    Simulation of anthropogenically induced land cover change impacts on climate has made significant progress over the last half century, starting with impacts of albedo and land cover change and evolving to include irrigation, urbanization and wood harvest carbon cycle impacts. However, many models still simulate these processes piece meal and the historical and Integrated Assessment Model (IAM) derived datasets used to drive these processes are not necessarily internally consistent in their implementation within Earth System Models. A further important question considers how anthropogenically driven feedbacks in the LULC-climate system will take place. In the future land cover change may be small given the lack of available arable land. However, land use intensification and political actions on energy consumption in urban systems may result in significant new indirect impacts on nutrient cycles and biogeophysical and biogeochemical processes.This paper will review some of the land cover and land use (LCLU) processes simulated in ESMs and a review the sources of information used to define the geographical extent of LULC changes. One question to address is whether the current representation of these processes are adequate to simulate the totality of the anthropogenic climate impacts, given that in many cases there are differences in the intensity of land uses over space and time, and that a particular land cover class may actually encompass a wide variety of human activities. There also remain some land cover types/processes that are not well simulated in most models. For example the ill-defined land use class associated with pasture or grazing activities. Finally, it is important to consider which land cover types are most likely to change in the future. Perhaps more important than the spatial change is how processes within land cover types will change. For example, urban systems are likely to play a major role in determining LULC related influences on anthropogenic

  8. Landscape approach for quantifying land use