Science.gov

Sample records for accurate land cover

  1. Land Cover Characterization Program

    USGS Publications Warehouse

    ,

    1997-01-01

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

  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 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.

  4. An Exploration of Hyperion Hyperspectral Imagery Combined with Different Supervised Classification Approaches Towards Obtaining More Accurate Land Use/Cover Cartography

    NASA Astrophysics Data System (ADS)

    Igityan, Nune

    2014-05-01

    Land use and land cover (LULC) constitutes a key variable of the Earth's system that has in general shown a close correlation with human activities and the physical environment. Describing the pattern and the spatial distribution of LULC is traditionally based on remote sensing data analysis and, evidently, one of the most commonly techniques applied has been image classification. The main objective of the present study has been to evaluate the combined use of Hyperion hyperspectral imagery with a range of supervised classification algorithms widely available today for discriminating LULC classes in a typical Mediterranean setting. Accuracy assessment of the derived thematic maps was based on the analysis of the classification confusion matrix statistics computed for each classification map, using for consistency the same set of validation points. Those were selected on the basis of photo-interpretation of high resolution aerial imagery and of panchromatic imagery available for the studied region at the time of the Hyperion overpass. Results indicated close classification accuracy between the different classifiers with the SVMs outperforming the other classification approaches. The higher classification accuracy by SVMs was attributed principally to the ability of this classifier to identify an optimal separating hyperplane for classes' separation which allows a low generalisation error, thus producing the best possible classes' separation. Although all classifiers produced close results, SVMs generally appeared most useful in describing the spatial distribution and the cover density of each land cover category. All in all, this study demonstrated that, provided that a Hyperion hyperspectral imagery can be made available at regular time intervals over a given region, when combined with SVMs classifiers, can potentially enable a wider approach in land use/cover mapping. This can be of particular importance, especially for regions like in the Mediterranean basin

  5. CoverCAM - a land cover composition change assessment method

    NASA Astrophysics Data System (ADS)

    Ali, A.; Bie, C. D.; Skidmore, A. K.

    2013-12-01

    The cover-composition on a specific piece of land can change over time due to natural and anthropogenic factors. Accurate detection of where and when changes occur requires a method that uses remotely sensed imagery that represents a continuous and consistent record on the state of the green land-cover. Such data are offered through hyper-temporal NDVI-imagery. Until recently, NDVI-images were mainly used for anomaly mapping to monitor the influence of weather on vegetation; the monitoring basically assume that, over time, the land cover composition of a studied area remains static. This study presents a novel cover change assessment method, labelled ';CoverCAM' that extracts from hyper-temporal NDVI-imagery the probabilities that the original land cover composition did change. CoverCAM, unlike all existing change-detection methods, makes adjustments based on seasonal NDVI-anomalies experienced at landscape level. We tested the method by processing SPOT-VGT NDVI-imagery (10-day Maximum Value Composites; 1km pixels) for Andalucía, Spain. CoverCAM requires specification that two time periods are specified: a reference period (we used 2000-04), and a change detection period (we used 2005-10). All images of the reference period were classified using the ISODATA algorithm and by evaluating divergence statistics. The generated map depicts strata (group of polygons), characterized by temporal NDVI and standard deviation (SD) profiles. For the change assessment period, first, mean NDVI-values were calculated by decade and polygon (NDVId,p), and then for each pixel of the polygon its pixel change values specified through the remaining difference between the pixel NDVI and [NDVId,p × the SD value of the stratum for that decade]. The above process was repeated to produce decadal land cover change probability maps, each with its own undefined scale. The decadal change maps were then aggregated to annual change probability maps. This validation was only carried out for

  6. 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.

  7. 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.

  8. 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.

  9. Land use and land cover digital data

    USGS Publications Warehouse

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

    1983-01-01

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

  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. National Land Cover Database 2001 (NLCD01)

    USGS Publications Warehouse

    LaMotte, Andrew E.

    2016-01-01

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

  12. 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.

  13. 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

  14. Regional characterization of land cover using multiple sources of data

    USGS Publications Warehouse

    Vogelmann, J.E.; Sohl, T.; Howard, S.M.

    1998-01-01

    Many organizations require accurate intermediate-scale land-cover information for many applications, including modeling nutrient and pesticide runoff, understanding spatial patterns of biodiversity, land-use planning, and policy development. While many techniques have been successfully used to classify land cover in relatively small regions, there are substantial obstacles in applying these methods to large, multiscene regions. The purpose of this study was to generate and evaluate a large region land-cover classification product using a multiple-layer land-characteristics database approach. To derive land-cover information, mosaicked Landsat thematic mapper (TM) scenes were analyzed in conjunction with digital elevation data (and derived slope, aspect, and shaded relief), population census information, Defense Meteorological Satellite Program city lights data, prior land-use and land-cover data, digital line graph data, and National Wetlands Inventory data. Both leaf-on and leaf-off TM data sets were analyzed. The study area was U.S. Federal Region III, which includes the states of Pennsylvania, Virginia, Maryland, Delaware, and West Virginia. The general procedure involved (1) generating mosaics of multiple scenes of leaves-on TM data using histogram equalization methods; (2) clustering mosaics into 100 spectral classes using unsupervised classification; (3) interpreting and labeling spectral classes into approximately 15 land-cover categories (analogous to Anderson Level 1 and 2 classes) using aerial photographs; (4) developing decision-making rules and models using from one to several ancillary data layers to resolve confusion in spectral classes that represented two or more targeted land-cover categories; and (5) incorporating data from other sources (for example, leaf-off TM data and National Wetlands Inventory data) to yield a final land-cover product. Although standard accuracy assessments were not done, a series of consistency checks using available

  15. Improving Land Cover Product-Based Estimates of the Extent of Fragmented Cover Types

    NASA Technical Reports Server (NTRS)

    Hlavka, Christine A.; Dungan, Jennifer

    2002-01-01

    The effects of changing land use/land cover on regional and global climate ecosystems depends on accurate estimates of the extent of critical land cover types such as Arctic wetlands and fire scars in boreal forests. To address this information requirement, land cover products at coarse spatial resolution such as Advanced Very High Resolution Radiometer (AVHRR) -based maps and the MODIS Land Cover Product are being produced. The accuracy of the extent of highly fragmented cover types such as fire scars and ponds is in doubt because much (the numerous scars and ponds smaller than the pixel size) is missed. A promising method for improving areal estimates involves modeling the observed distribution of the fragment sizes as a type of truncated distribution, then estimating the sum of unobserved sizes in the lower, truncated tail and adding it to the sum of observed fragment sizes. The method has been tested with both simulated and actual cover products.

  16. 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).

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  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. Land cover mapping from remote sensing data

    NASA Astrophysics Data System (ADS)

    Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Saleh, N. M.; Wong, C. J.; AlSultan, Sultan

    2006-04-01

    Remote sensing data have been widely used for land cover mapping using supervised and unsupervised methods. The produced land cover maps are useful for various applications. This paper examines the use of remote sensing data for land cover mapping over Saudi Arabia. Three supervised classification techniques Maximum Likelihood, ML, Minimum Distance-to-Mean, MDM, and Parallelepiped, P were applied to the imageries to extract the thematic information from the acquired scene by using PCI Geomatica software. Training sites were selected within each scene. This study shows that the ML classifier was the best classifier and produced superior results and achieved a high degree of accuracy. The preliminary analysis gave promising results of land cover mapping over Saudi Arabia by using Landsat TM imageries.

  7. Land cover classification for Fanno Creek, Oregon

    USGS Publications Warehouse

    Sobieszczyk, Steven

    2011-01-01

    Fanno Creek is a tributary to the Tualatin River and flows though parts of the southwest Portland metropolitan area. The stream is heavily influenced by urban runoff and shows characteristic flashy streamflow and poor water quality commonly associated with urban streams. This data set represents the floodplain land cover as derived from light detection and ranging (LiDAR) data and aerial photographic imagery. The land cover classifications represent current conditions (2009).

  8. 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.

  9. 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.

  10. Edwards plateau: Analysis of land cover trends

    USGS Publications Warehouse

    Friesen, B.A.; Hester, D.J.; Casey, K.A.

    2004-01-01

    The Land Cover Trends project studies the rates, causes, and consequences of contemporary (1973-2000) change in land use and land cover in the United States on an ecoregional basis. The Edwards Plateau ecoregion is the focus of this report. Landsat imagery from five dates during a nearly 30-year period are interpreted for randomly selected sample blocks. The resulting data provide the foundation for estimating change. Along with the image analysis, site visits to 90% of the sampled areas, geographical profiles, and socioeconomic data for the ecoregion are synthesized to assess regional driving forces and consequences of change. Complete project methodology can be found in Loveland et al [1].

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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 ...

  20. 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.

  1. 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.

  2. 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.

  3. 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

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

    NASA Astrophysics Data System (ADS)

    Balakeristanan, Maha Letchumy; Md Said, Md Azlin

    2012-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  6. Classification of impervious land cover using fractals

    NASA Astrophysics Data System (ADS)

    Quackenbush, Lindi J.

    Runoff from urban areas is a leading source of nonpoint source pollution in estuaries, lakes, and streams. The extent and type of impervious land cover are considered to be critical factors in evaluating runoff amounts and the potential for environmental damage. Land cover information for watershed modeling is frequently derived using remote sensing techniques, and improvements in image classification are expected to enhance the reliability of runoff models. In order to understand potential pollutant loads there is a need to characterize impervious areas based on land use. However, distinguishing between impervious features such as roofs and roads using only spectral information is often challenging due to the similarity in construction materials. Since spectral information alone is often lacking, spatial complexity measured using fractal dimension was analyzed to determine its utility in performing detailed classification. Fractal dimension describes the complexity of curves and surfaces in non-integer dimensions. Statistical analysis demonstrated that fractal dimension varies between roofs, roads, and driveways. Analysis also observed the impact of scale by determining statistical differences in fractal dimension, based on the size of the window considered and the ground sampled distance of the pixels under consideration. The statistical differences in fractal dimension translated to minor improvements in classification accuracy when separating roofs, roads, and driveways.

  7. High-Resolution Land Use and Land Cover Mapping

    USGS Publications Warehouse

    ,

    1999-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  9. 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

  10. 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

  11. 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.

  12. Ultra-wideband tomography of land cover

    NASA Astrophysics Data System (ADS)

    Kochetkova, Tatiana D.; Zapasnoy, Andrey S.; Klokov, Andrey V.; Shipilov, Sergey E.; Yakubov, Vladimir P.; Yurchenko, Alexey V.

    2014-11-01

    This paper describes a comprehensive approach which combines the application of OKO-2 ground penetrating radar, conventional method of cross sectioning accepted in edaphology, soil-testing parameters, mobile and laboratory research of dielectric permittivity for stratified soil cover research. Dielectric characteristics measurements of selected contact samples by the waveguide-coaxial technique showed a correlation between electrophysic characteristics of soil with soil moisture and density. Location of deep aquifers was detected and the real local topography was restored. Research was performed within the Timiryazevskoye forest district near Tomsk. Comparing the results of radar non-destructive sounding and contact measurements demonstrated high correlation of detected structural soil features. The suggested approach provides a solid basis for verifying the non-contact radiophysical methods of research in the interests of rational nature management and land utilization.

  13. 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.

  14. 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.

  15. 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

  16. 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).

  17. 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.

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

    PubMed

    Sajikumar, N; Remya, R S

    2015-09-15

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

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

    PubMed

    Sajikumar, N; Remya, R S

    2015-09-15

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

  20. 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.

  1. Enhancing the performance of regional land cover mapping

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  2. 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

  3. 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.

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. Land Cover Feature Recognition by Fusion of POLSAR, PolInSAR and Optical Data

    NASA Astrophysics Data System (ADS)

    Shimoni, M.; Borghys, D.; Heremans, R.; Milisavljević, N.; Derauw, D.; Pernel, C.; Orban, A.

    2007-03-01

    Classification of land cover is one of the primary objectives in the analysis of remotely sensed data. To aid in this process, data from multiple sensors are often utilised, since each potentially provides different information about the characteristics of the land cover. The main research goal of this study is to fuse different frequency E-SARPolSAR data as well as Po lInSA R with Daedalus optical data for land cover classification and land cover feature recognition . The studied area is located in Croatia and is covered by several land features including different types of crops, residential areas, roads, pastures, bare so il , forest and river. Two different level fusion techniques are applied and compared in th is study: the Log istic Regression (LR) as 'feature based fusion' method and the Fuzzy method for higher decision level fusion . The LR technique was used to fuse in to tal 102 features extracted from the comp lete data set. Iterations of the different land cover training areas using different features sets produced different probability images of the detected land cover types. The outputs of the feature-based fusion are 19 supervised classifications that were used as database for the h igher-level fusion . For both fusion methods the overall accuracy for each of the fused sets is better than the accuracy for the separate sets of features. Based on the results presented in th is research we found that: (1) Fused features from different SA R frequencies are comp lementary and adequate for land cover classification ; (2) Po lIn SA R features are comp lementary to the Po l SA R information and essential for producing accurate classification of different land cover types as man-made object, water bodies, forest, crops and bare soils; (3) The optical data is comp lementary information for the SA R data but not necessary for the production of accurate land-cover classification .

  9. 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

  10. 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.

  11. 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.

  12. 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...

  13. 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

  14. 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.

  15. 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.

  16. Videometric terminal guidance method and system for UAV accurate landing

    NASA Astrophysics Data System (ADS)

    Zhou, Xiang; Lei, Zhihui; Yu, Qifeng; Zhang, Hongliang; Shang, Yang; Du, Jing; Gui, Yang; Guo, Pengyu

    2012-06-01

    We present a videometric method and system to implement terminal guidance for Unmanned Aerial Vehicle(UAV) accurate landing. In the videometric system, two calibrated cameras attached to the ground are used, and a calibration method in which at least 5 control points are applied is developed to calibrate the inner and exterior parameters of the cameras. Cameras with 850nm spectral filter are used to recognize a 850nm LED target fixed on the UAV which can highlight itself in images with complicated background. NNLOG (normalized negative laplacian of gaussian) operator is developed for automatic target detection and tracking. Finally, 3-D position of the UAV with high accuracy can be calculated and transfered to control system to direct UAV accurate landing. The videometric system can work in the rate of 50Hz. Many real flight and static accuracy experiments demonstrate the correctness and veracity of the method proposed in this paper, and they also indicate the reliability and robustness of the system proposed in this paper. The static accuracy experiment results show that the deviation is less-than 10cm when target is far from the cameras and lessthan 2cm in 100m region. The real flight experiment results show that the deviation from DGPS is less-than 20cm. The system implement in this paper won the first prize in the AVIC Cup-International UAV Innovation Grand Prix, and it is the only one that achieved UAV accurate landing without GPS or DGPS.

  17. Land-cover classification in SAR images using dictionary learning

    NASA Astrophysics Data System (ADS)

    Aktaş, Gizem; Bak, Çaǧdaş; Nar, Fatih; Şen, Nigar

    2015-10-01

    Land-cover classification in Synthetic Aperture Radar (SAR) images has significance in both civil and military remote sensing applications. Accurate classification is a challenging problem due to variety of natural and man-made objects, seasonal changes at acquisition time, and diversity of image reconstruction algorithms.. In this study, Feature Preserving Despeckling (FPD), which is an edge preserving total variation based speckle reduction method, is applied as a preprocessing step. To handle the mentioned challenges, a novel feature extraction schema combined with a super-pixel segmentation and dictionary learning based classification is proposed. Computational complexity is another issue to handle in processing of high dimensional SAR images. Computational complexity of the proposed method is linearly proportional to the size of the image since it does not require a sliding window that accesses the pixels multiple times. Accuracy of the proposed method is validated on the dataset composed of TerraSAR-X high resolutions spot mode SAR images.

  18. 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.

  19. 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

  20. 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.

  1. A spatial-temporal contextual Markovian kernel method for multi-temporal land cover mapping

    NASA Astrophysics Data System (ADS)

    Wehmann, Adam; Liu, Desheng

    2015-09-01

    Due to a lack of spatial-temporal consistency, the current generation of multi-temporal land cover products is subject to significant error propagation in change detection results. To address the evolving needs of land change science, the next generation of land cover products must be derived from new classification methods that are designed specifically for multi-temporal land cover mapping. In this paper, a next generation classifier is proposed that fully exploits contextual information by combining results born from the machine learning paradigm in remote sensing with domain knowledge from multi-temporal land cover mapping. This classifier, the Spatial-Temporal Markovian Support Vector Classifier, exhibits an entirely new level of accuracy of change detection when evaluated for the classification of seven Landsat images from an Appalachian Ohio study area. It exceeds previous leading techniques employing machine learning kernel methods and Markov Random Field models of image context on all accuracy metrics for the creation of a spatial-temporally consistent land cover product. It owes its performance to the greatly improved decision-making about contextual information afforded by the extension and integration of these previous techniques. With such a classifier, substantially more accurate and spatial-temporally consistent multi-temporal land cover products are possible that are suitable for the detailed study of land cover change.

  2. 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.

  3. 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.

  4. [Difference of Karst Carbon Sink Under Different Land Use and Land Cover Areas in Dry Season].

    PubMed

    Zhao, Rui-yi; Liang, Zuo-bing; Wang, Zun-bo; Yu, Zheng-liang; Jiang, Ze-li

    2015-05-01

    In order to identify the distinction of soil CO2 consumed by carbonate rock dissolution, Baishuwan spring, Lanhuagou spring and Hougou spring were selected as objects to monitor the hydrochemistry from November 2013 to May 2014. The results showed that the highest HCO3- concentration was observed in Baishuwan spring which is covered by pine forest, while the lowest HCO3- concentration was observed in Hougou spring which is mainly covered by cultivated land. In Baishuwan spring, HCO3- was mainly derived from carbonic acid dissolving carbonate rock and the molar ratio between Ca(2+) + Mg2+ and HCO3- was close to 0. 5; while the molar ratio between Ca(2+) + Mg2+ and HCO3- exceeded 0.5 because the carbonate rock in Lanhuagou spring and Hougou spring was mainly dissolved by nitric acid and sulfuric acid. Because of the input of litter and the fact that gas-permeability of soil was limited in Baishuwan spring catchment, most of soil CO2 was dissolved in infiltrated water and reacted with bedrock. However, in Lanhuagou spring catchment and Hougou spring catchment, porous soil made soil CO2 easier to return to the atmosphere in the form of soil respiration. Therefore, in order to accurately estimate karst carbon sink, it was required to clarify the distinction of CO2 consumption by carbonate rock dissolution under different land use and land cover areas. PMID:26314105

  5. 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

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  9. Validation of current land cover maps utilizing astronaut acquired photography

    NASA Astrophysics Data System (ADS)

    Gebelein, Jennifer; Estes, John E.

    2000-01-01

    This investigation focuses on the potential use of astronaut acquired photography for the validation of current, land cover maps. More specifically, this study is directed at assessing the potential for the use of astronaut acquired photography to document and validate land cover change. Space Shuttle, astronaut acquired photography is employed to test the potential utility of data that may be acquired by astronauts employing the Window Observational Rack Facility (WORF) on International Space Station (ISS). The majority of astronaut acquired photography has been obtained under conditions similar to ISS operations in terms of both spectral as well as spatial resolution. Validation of land cover maps utilizing this type of imagery is being accomplished through a process of comparison among three different land cover classification legends created from the Eros Data Center (EDC) Land Characteristics Database. Our study area is a subregional scale portion of an Advanced Very High Resolution Radiometer (AVHRR) based global Land Characteristics Database. The goal of this research is to attempt to establish: 1. which legend derived for this area provides the highest overall accuracy for the land cover classes present: 2. which legend is best validated using astronaut acquired photography; and 3. which classes of these legends best lend themselves to validation with astronaut acquired photography. Preliminary results indicate that astronaut acquired photography can be employed to validate land cover maps and that results achieved using this imagery corresponds well to those achieved utilizing Landsat data. .

  10. 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

  11. 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.

  12. Land use/land cover change in Yellow River Delta, China during fast development period

    NASA Astrophysics Data System (ADS)

    Zhou, Wenzuo; Tian, Yongzhong; Zhu, Lifen

    2007-09-01

    Terrestrial eco-system in coastal zones is unstable and land-use and Land-cover of its land resource are crucial for its sustainability. Therefore it is necessary to understand distribution of land use/cover changes in those tender areas. This paper was to analyze changes of land use/cover in Yellow River Delta in China during recent ten years, which was its fast development period, by remote sensing monitoring. Two Landsat TM images in October of 1995 and 2004 were processed using ERDAS software and supervised classification method in study for the land use and land cover of those two years. The two land use/cover maps were overlaid to discover the changes. It was showed that lots of land use/cover changes in the Yellow River Delta had taken place in past ten years. Because abundant sand that carried by river water filled up at estuary of the Yellow River, new land increased fleetly. The rates that foreshore were turned into fishery land was high for aquaculture with salt water had been developed quickly. Another important effect of human activity was that part of waste land and grassland had been cultivated for crops. With industry and economy development, land for urbanization had been outspreaded. Although fast exploitation had been carried out in Yellow River Delta going though those years, some human activities on land use were inharmonious for sustainable development of land resource in this area. This must be pay attention to by local government and people.

  13. 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

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

    PubMed

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

    2012-09-01

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

  15. 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.

  16. Accuracy assessment of land cover dynamic in hill land on integration of DEM data and TM image

    NASA Astrophysics Data System (ADS)

    Li, Yunmei; Wang, Xin; Wang, Qiao; Wu, Chuanqing; Huang, Jiazhu

    2010-04-01

    To accurately assess the area of land cover in hill land, we integrated DEM data and remote sensing image in Lihe River Valley, China. Firstly, the DEM data was combined into decision tree to increase the accuracy of land cover classification. Secondly, a slope corrected model was built to transfer the projected area to surface area by DEM data. At last, the area of different land cover was calculated and the dynamic of land cover in Lihe River Valley were analyzed from 1998 to 2003. The results show that: the area of forestland increased more than 10% by the slope corrected model, that indicates the area correcting is very important for hill land; the accuracy of classification especially for forestland and garden plot is enhanced by integrating of DEM data. It can be greater than 85%. The indexes of land use extent were 266.2 in 1998, 273.1 in 2001, and 276.7 in 2003. The change rates of land use extent were 2.59 during 1998 to 2001 and 1.34 during 2001 to 2003.

  17. 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.

  18. [Simulation of hydrological response to land-cover changes].

    PubMed

    Chen, Junfeng; Li, Xiubin

    2004-05-01

    Hydrological modeling methodology had a quick development in recent years. In this article, a distributed hydrological model SWAT was used to simulate the rainfall-runoff relationship of the Suomo Basin under different land covers in order to evaluate the impact of land-cover changes on runoff, evapotransperation and peak flow. The results showed that if the land-cover changed from non-vegetation-cover to full-forest-cover scenarios, the runoff depth decreased, evaporation increased, while the reduced extent of runoff in dry season was less than that in rainy season, and in the first rainy season, the reduced extent of runoff was more than that in the second rainy season. With the same recurrent flood flow, the peak flow value under full-forest-cover scenario was 31.2% less than that under non-vegetation-cover scenario. The effect of land-cover between current cover and optimum cover on hydrology was small for large storm, and big for small storm events.

  19. 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

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

    PubMed

    van Asselen, Sanneke; Verburg, Peter H

    2013-12-01

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

  1. Land cover applications from IFSAR imagery

    NASA Astrophysics Data System (ADS)

    Jaroszewski, Steve; Pieramico, Alan; Lefevre, Russell J.; Corbeil, Allan F.; Fox, Bernard; Jackson, Christopher R.

    1999-08-01

    In the next few years, there will be a substantial increase in the number of commercial space-based and airborne Synthetic Aperture Radar (SAR) systems and three-dimensional Synthetic Aperture Radar systems (Interferometric SAR:IFSAR). This will result in affordable, new types of data that can be used to complement other sensor systems, e.g., LandSat, SPOT, and in some cases, solve serious data collection deficiencies. The availability of this data has resulted in high interest in developing a commercial market for products derived from this data. This paper describes a methodology for developing such products and presents results from applying the methodology.

  2. Assessing the use of global land cover data for guiding large area population distribution modelling.

    PubMed

    Linard, Catherine; Gilbert, Marius; Tatem, Andrew J

    2011-10-01

    Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover data, thus restricting application of the approach to this region. If gridded population data are to be improved across Africa, an alternative, consistent and comparable source of land cover data is required. Here these analyses were repeated for Kenya using four continent-wide land cover datasets combined with detailed settlement extents and accuracies were assessed against detailed census data. The aim was to identify the large area land cover dataset that, combined with detailed settlement extents, produce the most accurate population distribution data. The effectiveness of the population distribution modelling procedures in the absence of high resolution census data was evaluated, as was the extrapolation ability of population densities between different regions. Results showed that the use of the GlobCover dataset refined with detailed settlement extents provided significantly more accurate gridded population data compared to the use of refined AVHRR-derived, MODIS-derived and GLC2000 land cover datasets. This study supports the hypothesis that land cover information is important for improving population distribution model accuracies, particularly in countries where only coarse resolution census data are available. Obtaining high resolution census data must however remain the priority. With its higher spatial resolution and its more recent data acquisition, the GlobCover dataset was found as the most valuable resource to use in combination with detailed settlement extents for the production of gridded population datasets

  3. 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.

  4. Evaluation of land use/land cover datasets for urban watershed modeling

    SciTech Connect

    Burian, S. J.; Brown, M. J.; McPherson, T. N.

    2001-01-01

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

  5. Evaluation of land use/land cover datasets for urban watershed modeling.

    PubMed

    Burian, S J; Brown, M J; McPherson, T N

    2002-01-01

    Land use/land cover (LULC) data are a vital component for nonpoint source pollution modeling. Most watershed hydrology and pollutant loading models use, in some capacity, LULC information to generate runoff and pollutant loading estimates. Simple equation methods predict runoff and pollutant loads using runoff coefficients or pollutant export coefficients that are often correlated to LULC type. Complex models use input variables and parameters to represent watershed characteristics and pollutant buildup and washoff rates as a function of LULC type. Whether using simple or complex models an accurate LULC dataset with an appropriate spatial resolution and level of detail is paramount for reliable predictions. The study presented in this paper compared and evaluated several LULC dataset sources for application in urban environmental modeling. The commonly used USGS LULC datasets have coarser spatial resolution and lower levels of classification than other LULC datasets. In addition, the USGS datasets do not accurately represent the land use in areas that have undergone significant land use change during the past two decades. We performed a watershed modeling analysis of three urban catchments in Los Angeles, California, USA to investigate the relative difference in average annual runoff volumes and total suspended solids (TSS) loads when using the USGS LULC dataset versus using a more detailed and current LULC dataset. When the two LULC datasets were aggregated to the same land use categories, the relative differences in predicted average annual runoff volumes and TSS loads from the three catchments were 8 to 14% and 13 to 40%, respectively. The relative differences did not have a predictable relationship with catchment size. PMID:12079113

  6. 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.

  7. 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.

  8. 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.

  9. Improving distributed hydrologic modeling and global land cover data

    NASA Astrophysics Data System (ADS)

    Broxton, Patrick

    Distributed models of the land surface are essential for global climate models because of the importance of land-atmosphere exchanges of water, energy, momentum. They are also used for high resolution hydrologic simulation because of the need to capture non-linear responses to spatially variable inputs. Continued improvements to these models, and the data which they use, is especially important given ongoing changes in climate and land cover. In hydrologic models, important aspects are sometimes neglected due to the need to simplify the models for operational simulation. For example, operational flash flood models do not consider the role of snow and are often lumped (i.e. do not discretize a watershed into multiple units, and so do not fully consider the effect of intense, localized rainstorms). To address this deficiency, an overland flow model is coupled with a subsurface flow model to create a distributed flash flood forecasting system that can simulate flash floods that involve rain on snow. The model is intended for operational use, and there are extensive algorithms to incorporate high-resolution hydrometeorologic data, to assist in the calibration of the models, and to run the model in real time. A second study, which is designed to improve snow simulation in forested environments, demonstrates the importance of explicitly representing a near canopy environment in snow models, instead of only representing open and canopy covered areas (i.e. with % canopy fraction), as is often done. Our modeling, which uses canopy structure information from Aerial Laser Survey Mapping at 1 meter resolution, suggests that areas near trees have more net snow water input than surrounding areas because of the lack of snow interception, shading by the trees, and the effects of wind. In addition, the greatest discrepancy between our model simulations that explicitly represent forest structure and those that do not occur in areas with more canopy edges. In addition, two value

  10. 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.

  11. 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...

  12. Relationships between aerodynamic roughness and land use and land cover in Baltimore, Maryland

    USGS Publications Warehouse

    Nicholas, F.W.; Lewis, J.E.

    1980-01-01

    Urbanization changes the radiative, thermal, hydrologic, and aerodynamic properties of the Earth's surface. Knowledge of these surface characteristics, therefore, is essential to urban climate analysis. Aerodynamic or surface roughness of urban areas is not well documented, however, because of practical constraints in measuring the wind profile in the presence of large buildings. Using an empirical method designed by Lettau, and an analysis of variance of surface roughness values calculated for 324 samples averaging 0.8 hectare (ha) of land use and land cover sample in Baltimore, Md., a strong statistical relation was found between aerodynamic roughness and urban land use and land cover types. Assessment of three land use and land cover systems indicates that some of these types have significantly different surface roughness characteristics. The tests further indicate that statistically significant differences exist in estimated surface roughness values when categories (classes) from different land use and land cover classification systems are used as surrogates. A Level III extension of the U.S. Geological Survey Level II land use and land cover classification system provided the most reliable results. An evaluation of the physical association between the aerodynamic properties of land use and land cover and the surface climate by numerical simulation of the surface energy balance indicates that changes in surface roughness within the range of values typical of the Level III categories induce important changes in the surface climate.

  13. Precipitation Response to Land Cover Changes in the Netherlands

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  14. 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.

  15. 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.

  16. Land Cover Trends in the Southern Florida Coastal Plain

    USGS Publications Warehouse

    Kambly, Steven; Moreland, Thomas R.

    2009-01-01

    This report presents an assessment of land use and land cover change in the Southern Florida Coastal Plain ecoregion for the period from 1973 to 2000. The ecoregion is one of 84 level III ecoregions defined by the Environmental Protection Agency; ecoregions have been designed to serve as a spatial framework for environmental resource management and denote areas that contain a geographically distinct assemblage of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The Southern Florida Coastal Plain ecoregion covers an area of approximately 22,407 square kilometers [8,651 square miles] across the lower portion of the Florida peninsula, from Lake Okeechobee southward through the Florida Keys. It comprises flat plains with wet soils, marshland and swamp land cover with Everglades and palmetto prairie vegetation types.

  17. 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.

  18. 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.

  19. 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. ...

  20. Wildfire Selectivity for Land Cover Type: Does Size Matter?

    PubMed Central

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

    2014-01-01

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

  1. 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.

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

    PubMed

    Hogan, Dianna M; Walbridge, Mark R

    2009-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  4. 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.

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

    USGS Publications Warehouse

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

    2009-01-01

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

  6. 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.

  7. 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

  8. 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.

  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. 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

  13. 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).

  14. 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.

  15. United states national land cover data base development? 1992-2001 and beyond

    USGS Publications Warehouse

    Yang, L.

    2008-01-01

    An accurate, up-to-date and spatially-explicate national land cover database is required for monitoring the status and trends of the nation's terrestrial ecosystem, and for managing and conserving land resources at the national scale. With all the challenges and resources required to develop such a database, an innovative and scientifically sound planning must be in place and a partnership be formed among users from government agencies, research institutes and private sectors. In this paper, we summarize major scientific and technical issues regarding the development of the NLCD 1992 and 2001. Experiences and lessons learned from the project are documented with regard to project design, technical approaches, accuracy assessment strategy, and projecti imiplementation.Future improvements in developing next generation NLCD beyond 2001 are suggested, including: 1) enhanced satellite data preprocessing in correction of atmospheric and adjacency effect and the topographic normalization; 2) improved classification accuracy through comprehensive and consistent training data and new algorithm development; 3) multi-resolution and multi-temporal database targeting major land cover changes and land cover database updates; 4) enriched database contents by including additional biophysical parameters and/or more detailed land cover classes through synergizing multi-sensor, multi-temporal, and multi-spectral satellite data and ancillary data, and 5) transform the NLCD project into a national land cover monitoring program. ?? 2008 IEEE.

  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. 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

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

    PubMed

    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.

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

    PubMed

    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

  20. 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.

  1. 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.

  2. Application of multi-sensor images for detecting land cover change and analysis of urban expansion

    NASA Astrophysics Data System (ADS)

    Deng, Jinsong; Wang, Ke; Deng, Yanhua; Li, Jun

    2005-10-01

    Zhejiang province is playing an increasingly vital role in China's overall economic growth. Concomitant with the dramatic economic development, this region has been undergoing tremendous urban growth on an unprecedented scale and rate. Many urbanization-related problems have been identified, including agricultural land and wetland loss, water pollution and soil erosion. There is an urgent need to detect and monitor the land cover change and analyze the magnitude and pattern, accurately and timely for planning and management. Remote sensing is a powerful tool for monitoring rapid change in the landscape resulting from urban development. However, change detection capabilities are intrinsically limited by the spatial resolution of the digital imagery in urban. The application of multi-sensor data provides the potential to more accurately detect land-cover changes through integration of different features of sensor data. Taking Hangzhou city as case study, this paper presents a method that combines principal component analysis (PCA) of multi-sensor data (SPOT-5 XS and ETM Pan data) and a hybrid classification involving unsupervised and supervised classier to detect and analysis land cover change. The study demonstrates that this method provides a very useful way in monitoring rapid land cover change in urban environment.

  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. 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.

  5. 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.

  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.

    2010-07-01

    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.

  7. 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

  8. Dangers of predicting bird species distributions in response to land-cover changes.

    PubMed

    Vallecillo, Sara; Brotons, Lluís; Thuiller, Wilfried

    2009-03-01

    Land-cover changes from the last decades are leading to important declines in habitat quality, giving rise to changes in bird species distribution all over the world. However, land-cover changes result from a variety of different processes, and it is not clear how effective species distribution models are in capturing species responses to these changes. In this study, we evaluated our ability to predict the effects of land-cover changes on shifts in species distributions at large spatial and temporal scales using Mediterranean landscapes and early-successional, open-habitat birds as study models. Based on presence-absence data from the second Catalan Breeding Bird Atlas (1999-2002), we applied six different species distribution modeling techniques for 10 bird species using climate, topographic, and land-cover data as predictor variables. Then we back-projected the models on land-cover conditions from 1980 to evaluate the projections with field observation data from the first Catalan Breeding Bird Atlas (1975-1983). Finally, we assessed if, in addition to changes in habitat suitability resulting from land-cover shifts, descriptors of fire impact contributed to further explain species distribution dynamics: colonization and local extinction. We developed accurate model projections of current and past global patterns of species distribution, but our ability to predict species distribution dynamics was reduced. Colonization dynamics were generally more strongly related to fire descriptors than to changes in overall habitat suitability derived from land-cover changes. Our results warn of the dangers of projecting species distribution models onto future conditions if processes behind species distribution dynamics are not explicitly included. Consideration of ecologically meaningful processes for species (i.e., fire disturbance) when modeling species' distribution might contribute to a better explanation of species' colonization dynamics.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Rogan, John

    2005-11-01

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

  11. 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.

  12. 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.

  13. 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...

  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. 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.

  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. 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...

  18. 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 ...

  19. 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...

  20. 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.

  1. Integrating the system dynamic and cellular automata models to predict land use and land cover change

    NASA Astrophysics Data System (ADS)

    Xu, Xiaoming; Du, Ziqiang; Zhang, Hong

    2016-10-01

    Land use and land cover change (LULCC) is a widely researched topic in related studies. A number of models have been established to simulate LULCC patterns. However, the integration of the system dynamic (SD) and the cellular automata (CA) model have been rarely employed in LULCC simulations, although it allows for combining the advantages of each approach and therefore improving the simulation accuracy. In this study, we integrated an SD model and a CA model to predict LULCC under three future development scenarios in Northern Shanxi province of China, a typical agro-pastoral transitional zone. The results indicated that our integrated approach represented the impacts of natural and socioeconomic factors on LULCC well, and could accurately simulate the magnitude and spatial pattern of LULCC. The modeling scenarios illustrated that different development pathways would lead to various LULCC patterns. This study demonstrated the advantages of the integration approach for simulating LULCC and suggests that LULCC is affected to a large degree by natural and socioeconomic factors.

  2. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  4. 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. 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 G.

    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.

  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. 25 CFR 162.210 - When can BIA grant a permit covering agricultural land?

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false When can BIA grant a permit covering agricultural land... covering agricultural land? (a) We may grant a permit covering agricultural land in the same manner as we... no substantial injury to the land will occur. (b) We may grant a permit covering agricultural...

  8. Comparing Methods for Land Surface Temperature Retrieval over Heterogeneous Land Cover Using Landsat-5 TM Thermal Infrared Data

    NASA Astrophysics Data System (ADS)

    Windahl, E.; de Beurs, K.

    2014-12-01

    Among other applications, remotely sensed land surface temperature (LST) has become critical for monitoring the surface urban heat island (SUHI) effect in cities across the world. While daily MODIS thermal infrared data is invaluable for examining changes in LST over time, the large 1 km spatial resolution makes studying the spatial patterns of LST in a heterogeneous urban environment difficult. The 120 m spatial resolution of Landsat 4-5 TM, as well the archive of data stretching back to 1982, make Landsat 4-5 TM sensors valuable resources for thermal data, especially in urban areas. However, the difficulty accurately correcting for atmospheric effects with only one thermal band, as well as the necessity for a priori knowledge of land surface emissivity (LSE), mean it is underutilized. Research to determine best practices for deriving LST from Landsat TM data given homogenous, usually vegetated land cover is relatively extensive; however, the accuracy of these methods given heterogeneous land cover is less well known, especially given Land Surface Emissivity (LSE) calculations that often rely heavily on NDVI. In order to determine the best methodology for measuring LST across heterogeneous land cover in the central United States, this study derives LST from Landsat 5 TM band 6 for Oklahoma City and the surrounding countryside on a fall and a spring date using three different methods: no atmospheric correction, the radiative transfer equation, and the mono-window algorithm. With all three methods, the common NDVI-based approach for estimating LSE is used; a fourth LST calculation with no atmospheric correction and an assumed emissivity of one is therefore included as contrast. Using regression analysis, these four LST measurements are compared to air temperatures recorded concurrently by approximately 40 Oklahoma Mesonet stations across the study area, and results are broken down by land cover type to explore potential biases or variations in accuracy.

  9. 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.

  10. Metropolitan land cover inventory using multiseasonal Landsat data

    USGS Publications Warehouse

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

    1978-01-01

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

  11. Land use and land cover, 1972-77, Culpeper Basin, Virginia-Maryland

    USGS Publications Warehouse

    ,

    1980-01-01

    In showing land use and land cover in the Culpeper Basin, this map features a consistent level of detail and standardization of categories.  The use of the 1:125,000 compilation scale is appropriate, because this type of data is used frequently for different purposes by people representing several disciplines- land use planners, land managers, resource managemnet planners, and others.  For example, maps and data similar to this publication have been used for river basin planning, for analysis of land use and land cover changes relative to recreation, for river quality assessment, for preparation of environmental impact statements, and for studies on urbanization.  These efforts have been made at the multicounty regional, State, and Federal levels.

  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. 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...

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. Evaluations of LIDAR reflectance amplitude sensitivity towards land cover conditions

    NASA Astrophysics Data System (ADS)

    Hasegawa, Hiroyuki

    2006-03-01

    This study aims to investigate the characteristics of LIDAR intensity data for executing land cover classification. The quantitative and qualitative analyses, the LIDAR intensity feasibility for classification was discussed. The survey found that intensity is inversely proportional to angle and distance, though their relation did not agree with the theoretical model. The survey also found that intensity correction with distance and angle is not always applicable, the effect of correction is not significant, and consequently raw intensity value usage is justified. We conclude that some land cover and building materials were separable with intensity data. Old asphalt and grass were separable though cement, slate & zinc, brick, and trees were not easy to recognize. Soil, gravel, and grass could be distinguishable each other.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. Holocene land cover change on the Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Dallmeyer, A.; Claussen, M.

    2010-12-01

    The Tibetan Plateau is expected to be one of the most climatic sensitive regions of the earth. Due to its large horizontal and vertical extend it has a large influence on the regional as well as global climate. As a heat source for the atmosphere in spring and summer it plays an important role for the onset and maintenance of the Asian summer monsoon and therewith influences one of the strongest monsoon circulations of the world. On the other hand, monsoon related convection above the Plateau leads to large-scale subsiding air-masses and dry climate in the regions north and west of the Plateau. These processes depend to a large part on the land cover as it controls the energy balance at the surface and the strength of the diabatic heat fluxes. Land cover changes on the Tibetan Plateau may thus exert strong influence on the regional and northern hemispheric climate. Therefore it is very important to represent past and future land cover changes correctly in global climate models, not only to understand the mechanism behind these land cover changes, but also to understand past and future climate change in Asia. To assess the performance of the comprehensive Earth system model ECHAM5-JSBACH/MPIOM with respect to the land cover on the Tibetan Plateau, we compare results of a transient numerical experiment with pollen-based vegetation reconstructions from four representative sites on the Plateau, covering the last 6000 years. Generally, the reconstructed and simulated trends are similar for most sites. Data and model show a strong decrease of forests on the Plateau. According to the model results, the averaged forest fraction has been reduced by almost one-third from mid-Holocene (41.4%) to present-day (28.3%) and is replaced by shrub and grass. The model mainly identifies differences in near-surface air temperatures due to an orbital induced insolation change as the reason for the vegetation change. Reconstructions rather indicate decreasing summer monsoon precipitation

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Using an ecoregion framework to analyze land-cover and land-use dynamics.

    USGS Publications Warehouse

    Gallant, A.L.; Loveland, T.R.; Sohl, T.L.; Napton, D.E.

    2004-01-01

    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.

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

    PubMed

    Fox, Jefferson; Vogler, John B

    2005-09-01

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

  19. 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...

  20. 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....

  1. 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.

  2. 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.

  3. 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

  4. Top-down analysis of collated streamflow data from heterogeneous catchments leads to underestimation of land cover influence

    NASA Astrophysics Data System (ADS)

    van Dijk, A. I. J. M.; Peña-Arancibia, J. L.; (Sampurno) Bruijnzeel, L. A.

    2011-04-01

    Controlled experiments have provided strong evidence that changing land cover (e.g. deforestation or afforestation) can affect the water balance. However a similarly strong influence has not been detected in analyses of collated streamflow data from catchments with mixed land cover. We tried to explain this "land cover paradox" using streamflow observations from 278 Australian catchments, a "top-down" model (the Zhang formulation of the Budyko model); and a "bottom-up" dynamic hydrological process model (the Australian Water Resources Assessment system Landscape model, AWRA-L). Analysis with the Zhang model confirmed the previously reported absence of a strong land cover signal. However, absence of evidence does not equate to the proof of absence, and AWRA-L was able to reconcile the streamflow data from the 278 catchments with experimental knowledge. Experiments were performed in which the Zhang model was used to analyse synthetic AWRA-L streamflow simulations for the 278 catchments. This demonstrated three reasons why the Zhang model did not accurately quantify the land cover signal: (1) measurement and estimation errors in land cover, precipitation and streamflow, (2) the importance of additional climate factors; (3) the presence of covariance in the streamflow and catchment attribute data. These methodological issues are likely to prevent the use of any top-down method to quantify land cover signal in data from catchments with mixed land cover. Our findings do not rule out physical processes that diminish land cover influence in catchments with mixed land cover, including atmospheric feedback associated with rainfall interception.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

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

    USGS Publications Warehouse

    Daniel, C.C.

    1978-01-01

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

  13. 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.

  14. 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

  15. 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

  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. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. Using landsat data to determine land use/land cover changes in Samsun, Turkey.

    PubMed

    Güler, Mustafa; Yomralioğlu, Tahsin; Reis, Selçuk

    2007-04-01

    The rapid industrialization and urbanization of an area require quick preparation of actual land use/land cover (LU/LC) maps in order to detect and avoid overuse and damage of the landscape beyond sustainable development limits. Remote sensing technology fits well for long-term monitoring and assessment of such effects. The aim of this study was to analyze LU/LC changes between 1980 and 1999 in Samsun, Turkey, using satellite images. Three Landsat images from 1980, 1987 and 1999 were used to determine changes. A post classification technique was used based on a hybrid classification approach (unsupervised and supervised). Images were classified into six LU/LC types; urban, agriculture, dense forest, open forest-hazelnut, barren land and water area. It is found that significant changes in land cover occurred over the study period. The results showed an increase in urban, open forest/hazelnut, barren land and water area and a decrease in agriculture and dense forest in between 1980 and 1999. In this period, urban land increased from 0.77% to 2.47% of the total area, primarily due to conversions from agricultural land and forest to a lesser degree. While the area of dense forest decreased from 41.09% to 29.64% of the total area, the area of open forest and hazelnut increased from 6.73% to 11.88%.

  8. 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.

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

    PubMed

    Alig, Ralph J; Butler, Brett J

    2004-04-01

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

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Hester, David Barry

    The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Controls of climatic variability and land cover on land surface hydrology of northern Wisconsin, USA

    NASA Astrophysics Data System (ADS)

    Vano, Julie A.; Foley, Jonathan A.; Kucharik, Christopher J.; Coe, Michael T.

    2008-12-01

    Ecosystem processes are strongly affected by the magnitude, timing, and variability of water flows. As such, our understanding of biogeochemical and ecological processes can be enhanced when our ability to track water flow and storage within ecosystems is improved. We assess how climatic variability and land cover change affect water flow and storage within a temperate forest region of the north central United States (46°N, 89°W). We use a well-validated process-based ecosystem model (IBIS) to investigate evapotranspiration, surface runoff, and drainage rates across a continuum of time scales. We found from 1951 to 2000, climatic variability imposed a large, detectable signal on both annual and seasonal surface water balance that resulted in changes in total runoff that ranged from 30% to 200% of the 50-year average. Conversely, land cover change resulted in subtler, persistent changes (i.e., forest to grassland changed total runoff by 10% annually), which were not detectable from year to year. If, however, changes in land cover persist, within 6 years the cumulative difference from land cover change became slightly more than two standard deviations of annual runoff variability, and within 15 years the accumulated differences were greater than changes between the largest and smallest runoff events within the 50-year period. As a result, in the context of this study, climatic variations typically had a strong effect on the surface water balance in the short term (season or year-to-year variations), but land cover change had influence on water balance over the long-term (6 years and beyond). These changes in hydrology from land cover were detectable as subtle, yet persistent differences that accumulate as changes in magnitude and shifts in seasonal cycles. Through this, we provide a process-based context for understanding the historical causes of water cycle variability, which allows us to better identify the hydrology of this system. Ultimately, this allows for

  1. 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

  2. An improved methodology for land-cover classification using artificial neural networks and a decision tree classifier

    NASA Astrophysics Data System (ADS)

    Arellano-Neri, Olimpia

    Mapping is essential for the analysis of the land and land-cover dynamics, which influence many environmental processes and properties. When creating land-cover maps it is important to minimize error, since error will propagate into later analyses based upon these land cover maps. The reliability of land cover maps derived from remotely sensed data depends upon an accurate classification. For decades, traditional statistical methods have been applied in land-cover classification with varying degrees of accuracy. One of the most significant developments in the field of land-cover classification using remotely sensed data has been the introduction of Artificial Neural Networks (ANN) procedures. In this research, Artificial Neural Networks were applied to remotely sensed data of the southwestern Ohio region for land-cover classification. Three variants on traditional ANN-based classifiers were explored here: (1) the use of a customized architecture of the neural network in terms of the input layer for each land-cover class, (2) the use of texture analysis to combine spectral information and spatial information which is essential for urban classes, and (3) the use of decision tree (DT) classification to refine the ANN classification and ultimately to achieve a more reliable land-cover thematic map. The objective of this research was to prove that a classification based on Artificial Neural Networks (ANN) and decision tree (DT) would outperform by far the National Land Cover Data (NLCD). The NLCD is a land-cover classification produced by a cooperative effort between the United States Geological Survey (USGS) and the United States Environmental Protection Agency (USEPA). In order to achieve this objective, an accuracy assessment was conducted for both NLCD classification and ANN/DT classification. Error matrices resulting from the accuracy assessments provided overall accuracy, accuracy of each class, omission errors, and commission errors for each classification. The

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. Detecting land-use/land-cover change in rural-urban fringe areas using extended change-vector analysis

    NASA Astrophysics Data System (ADS)

    He, Chunyang; Wei, Anni; Shi, Peijun; Zhang, Qiaofeng; Zhao, Yuanyuan

    2011-08-01

    Detecting land-use/land-cover (LULC) changes in rural-urban fringe areas (RUFAs) timely and accurately using satellite imagery is essential for land-use planning and management in China. Although traditional spectral-based change-vector analysis (CVA) can effectively detect LULC change in many cases, it encounters difficulties in RUFAs because of deficiencies in the spectral information of satellite images. To detect LULC changes in RUFAs effectively, this paper proposes an extended CVA approach that incorporates textural change information into the traditional spectral-based CVA. The extended CVA was applied to three different pilot RUFAs in China with different remotely sensed data, including Landsat Thematic Mapper (TM), China-Brazil Earth Resources Satellite (CBERS) and Advanced Land Observing Satellite (ALOS) images. The results demonstrated the improvement of the extended CVA compared to the traditional spectral-based CVA with the overall accuracy increased between 4.66% and 8.00% and the kappa coefficient increased between 0.10 and 0.15, respectively. The advantage of the extended CVA lies in its integration of both spectral and textural change information to detect LULC changes, allowing for effective discrimination of LULC changes that are spectrally similar but texturally different in RUFAs. The extended CVA has great potential to be widely used for LULC-change detection in RUFAs, which are often heterogeneous and fragmental in nature, with rich textural information.

  10. 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.

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

    PubMed

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

    Stormwater runoff quality is sensitive to land use and land cover (LULC) change. It is difficult to understand their relationship in predicting the pollution potential and developing watershed management practices to eliminate or reduce the pollution risk. In this study, the relationship between LULC change and stormwater runoff quality in two separate monitoring sites comprising a construction area (Site 1) and mixed land use (Site 2) was analyzed using geographic information system (GIS), event mean concentration (EMC), and correlation analysis. It was detected that bare land area increased, while other land use areas such as agriculture, commercial, forest, grassland, parking lot, residential, and road reduced. Based on the analyses performed, high maximum range and average EMCs were found in Site 2 for most of the water pollutants. Also, urban areas and increased conversion of LULC into bare land corresponded to degradation of stormwater quality. Correlation analysis between LULC and stormwater quality showed the influence of different factors such as farming practices, geographical location, and amount of precipitation, vegetation loss, and anthropogenic activities in monitoring sites. This research found that GIS application was an efficient tool for monthly monitoring, validation and statistical analysis of LULC change in the study area. PMID:25051467

  13. 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.

  14. Water table fluctuations under three riparian land covers, Iowa (USA)

    USGS Publications Warehouse

    Schilling, K.E.

    2007-01-01

    Water table depth is known to play an important role in nitrogen cycling in riparian zones, but little detailed monitoring of water table fluctuations has been reported. In this study, results of high-resolution water table monitoring under three common riparian land covers (forest, cool season grass, corn) were analysed to gain a better understanding of the relation of vegetation cover to water table depth. Three riparian wells located at the Neal Smith National Wildlife Refuge in Jasper County, Iowa, were instrumented with data loggers to record hourly water table behaviour from July to December 2004. Water table depth under the forest showed a diurnal pattern of rising and falling water levels, whereas the grass and corn exhibited a stepped pattern of greater drawdown during the day and less drainage at night. Clear daytime and night-time water table signals were related to daily plant water demands and lateral groundwater flow. Using two estimates of specific yield, hourly and daily ET rates were estimated to be higher under the forest cover than the grass and corn, with peak ET rates in July ranging from 5.02 to 6.32 mm day-1 for forest and from 1.81 to 4.13 mm day-1 for corn and grass. Following plant senescence in October, water table declines were associated with lateral flow to Walnut Creek. The results from this study suggest that consideration should be given to monitoring water table behaviour more frequently to capture daily and seasonal patterns related to riparian vegetation type. Copyright ?? 2007 John Wiley & Sons, Ltd.

  15. 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

  16. 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

  17. 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.

  18. 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.

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

    PubMed

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

    2011-02-01

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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

    Covino, Tim; McGlynn, Brian; McNamara, Rebecca

    2012-06-01

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

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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...

  16. 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.

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  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 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.

  3. The impact of land use and land cover changes on land surface temperature in a karst area of China.

    PubMed

    Xiao, Honglin; Weng, Qihao

    2007-10-01

    Satellite images have been used extensively to study temporal changes in land use and land cover (LULC) in China. However, few studies have been conducted in the karst areas despite the large area and population involved and the fragile ecosystem. In this study, LULC changes were examined in part of Guizhou Province of southern China from 1991 to 2001 based on Landsat Thematic Mapper (TM) images of November 7, 1991, December 5, 1994, and December 19, 2001. Land surface temperature (LST) and normalized difference vegetation index (NDVI) were computed based on LULC types. The results show that agricultural land decreased, while urban areas expanded dramatically, and forest land increased slightly. Barren land increased from 1991 to 1994, and then decreased from 1994 to 2001. These changes in LULC widened the temperature difference between the urban and the rural areas. The change in LST was mainly associated with changes in construction materials in the urban area and in vegetation abundance both in the urban and rural areas. Vegetation had a dual function in the temperatures of different LULC types. While it could ease the warming trend in the urban or built-up areas, it helped to keep other lands warmer in the cold weather. The study also reveals that due to the government's efforts on reforestation, rural ecosystems in some of the study area were being restored. The time required for the karst ecosystem to recover was shorter than previously thought.

  4. 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.

  5. 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), ...

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. Modelling the water balance of a mesoscale catchment basin using remotely sensed land cover data

    NASA Astrophysics Data System (ADS)

    Montzka, Carsten; Canty, Morton; Kunkel, Ralf; Menz, Gunter; Vereecken, Harry; Wendland, Frank

    2008-05-01

    SummaryHydrological modelling of mesoscale catchments is often adversely affected by a lack of adequate information about specific site conditions. In particular, digital land cover data are available from data sets which were acquired on a European or a national scale. These data sets do not only exhibit a restricted spatial resolution but also a differentiation of crops and impervious areas which is not appropriate to the needs of mesoscale hydrological models. In this paper, the impact of remote sensing data on the reliability of a water balance model is investigated and compared to model results determined on the basis of CORINE (Coordination of Information on the Environment) Land Cover as a reference. The aim is to quantify the improved model performance achieved by an enhanced land cover representation and corresponding model modifications. Making use of medium resolution satellite imagery from SPOT, LANDSAT ETM+ and ASTER, detailed information on land cover, especially agricultural crops and impervious surfaces, was extracted over a 5-year period (2000-2004). Crop-specific evapotranspiration coefficients were derived by using remote sensing data to replace grass reference evapotranspiration necessitated by the use of CORINE land cover for rural areas. For regions classified as settlement or industrial areas, degrees of imperviousness were derived. The data were incorporated into the hydrological model GROWA (large-scale water balance model), which uses an empirical approach combining distributed meteorological data with distributed site parameters to calculate the annual runoff components. Using satellite imagery in combination with runoff data from gauging stations for the years 2000-2004, the actual evapotranspiration calculation in GROWA was methodologically extended by including empirical crop coefficients for actual evapotranspiration calculations. While GROWA originally treated agricultural areas as homogeneous, now a consideration and differentiation

  1. 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...

  2. 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...

  3. 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

  4. 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

  5. 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

    2016-08-24

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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Mapping Land Use/Land Cover in the Ambos Nogales Study Area

    USGS Publications Warehouse

    Norman, Laura M.; Wallace, Cynthia S.A.

    2008-01-01

    The Ambos Nogales watershed, which surrounds the twin cities of Nogales, Arizona, United States and Nogales, Sonora, Mexico, has a history of problems related to flooding. This paper describes the process of creating a high-resolution, binational land-cover dataset to be used in modeling the Ambos Nogales watershed. The Automated Geospatial Watershed Assessment tool will be used to model the Ambos Nogales watershed to identify focal points for planning efforts and to anticipate ramifications of implementing detention reservoirs at certain watershed planes.

  14. [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.

  15. [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

  16. Effect of land cover change on snow free surface albedo across the continental United States

    NASA Astrophysics Data System (ADS)

    Wickham, J.; Nash, M. S.; Barnes, C. A.

    2016-11-01

    Land cover changes (e.g., forest to grassland) affect albedo, and changes in albedo can influence radiative forcing (warming, cooling). We empirically tested albedo response to land cover change for 130 locations across the continental United States using high resolution (30 m-×-30 m) land cover change data and moderate resolution (~ 500 m-×-500 m) albedo data. The land cover change data spanned 10 years (2001 - 2011) and the albedo data included observations every eight days for 13 years (2001 - 2013). Empirical testing was based on autoregressive time series analysis of snow free albedo for verified locations of land cover change. Approximately one-third of the autoregressive analyses for woody to herbaceous or forest to shrub change classes were not significant, indicating that albedo did not change significantly as a result of land cover change at these locations. In addition, ~ 80% of mean differences in albedo arising from land cover change were less than ± 0.02, a nominal benchmark for precision of albedo measurements that is related to significant changes in radiative forcing. Under snow free conditions, we found that land cover change does not guarantee a significant albedo response, and that the differences in mean albedo response for the majority of land cover change locations were small.

  17. 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.

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

    USGS Publications Warehouse

    Vogelmann, J.E.; Sohl, T.L.; Campbell, P.V.; Shaw, D.M.; ,

    1998-01-01

    As part of the activities of the Multi-Resolution Land Characteristics (MRLC) Interagency Consortium, an intermediate-scale land cover data set is being generated for the conterminous United States. This effort is being conducted on a region-by-region basis using U.S. Standard Federal Regions. To date, land cover data sets have been generated for Federal Regions 3 (Pennsylvania, West Virginia, Virginia, Maryland, and Delaware) and 2 (New York and New Jersey). Classification work is currently under way in Federal Region 4 (the southeastern United States), and land cover mapping activities have been started in Federal Regions 5 (the Great Lakes region) and 1 (New England). it is anticipated that a land cover data set for the conterminous United States will be completed by the end of 1999. A standard land cover classification legend is used, which is analogous to and compatible with other classification schemes. The primary MRLC regional classification scheme contains 23 land cover classes. The primary source of data for the project is the Landsat thematic mapper (TM) sensor. For each region, TM scenes representing both leaf-on and leaf-off conditions are acquired, preprocessed, and georeferenced to MRLC specifications. Mosaicked data are clustered using unsupervised classification, and individual clusters are labeled using aerial photographs. Individual clusters that represent more than one land cover unit are split using spatial modeling with multiple ancillary spatial data layers (most notably, digital elevation model, population, land use and land cover, and wetlands information). This approach yields regional land cover information suitable for a wide array of applications, including landscape metric analyses, land management, land cover change studies, and nutrient and pesticide runoff modeling.

  19. Validation of Global Land Cover Products using an Independent Global Reference Validation Database

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    As production of global land cover products from remote sensing becomes more routine, new data sets and methods in support of global land cover validation are urgently needed. In this paper we describe efforts to (1) compile a new global reference land cover validation database, and (2) develop standardized accuracy assessment procedures to validate regional and global land cover products. To this end, we developed a global stratification of land areas by intersecting the Koppen climate classification with gridded population density maps. The resulting stratification includes 21 strata and incorporated the influence of human activity on land cover. This stratification was used to select 500 validation sites based on a stratified random sample design. Because the base stratification is independent of land cover, this design provides an unbiased basis for sampling different land cover maps and can be augmented with reference information or additional sites in specific strata or regions of interest. The response design provides reference classifications at high spatial resolution for 5km x 5km blocks centered on each validation sample point. Interpretation and classification of these blocks is based on segmentation and classification of very high-resolution satellite imagery using the UN FAO Land Cover Classification System. To evaluate this design, we propose a methodology for overlaying the high-resolution reference site classifications on coarse-resolution land cover products such as the MODIS Land Cover Type Product (MCD12Q1). Initial accuracy results are presented in the form of error matrices and measures of agreement between class area proportions. Initial results suggest that high-resolution reference imagery is useful for understanding sources of coarse-resolution mapping errors, especially among mixture classes. As part of this analysis we examine issues of semantic similarity among classes, and explore how this issue affects estimates of classification

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

    PubMed

    Cherkauer, Douglas S; Ansari, Sajjad A

    2005-01-01

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

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

    PubMed

    Wen, Yuming; Khosrowpanah, Shahram; Heitz, Leroy

    2011-08-01

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

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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).

  10. 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

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

    PubMed

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

    2013-01-01

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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. The Impact of Land Cover and Land Use Changes on Atmosphere-Biosphere Exchanges and Atmospheric Chemistry

    NASA Astrophysics Data System (ADS)

    Ganzeveld, L.; Bouwman, L.; Eickhout, B.; Stehfest, E.; van Vuuren, D.; Tanarthe, M.; Tost, H.; Lelieveld, J.

    2007-12-01

    One of the challenging foci of global atmospheric chemistry research is how the atmospheric oxidizing (or cleansing) capacity, which also controls the lifetime of greenhouse gases such as methane, will change in response to climate- and land cover and land use changes. This is also motivated by anticipated global land cover and land use scenarios, which indicate that the terrestrial biosphere is expected to be affected significantly by anthropogenic activities, e.g., tropical deforestation. Analysis with a single-column chemistry-climate model has indicated that short-term (days) changes in the atmospheric oxidizing capacity due to Amazonian deforestation not only depend on changes in surface trace gas exchanges. There are also significant changes in vertical convective and turbulent transport and the hydrological cycle due to changes in surface energy and water exchanges. We apply the global chemistry-climate model ECHAM5/MESSy to present an analysis of the long-term impact of land-cover and land-use changes on surface exchanges and global atmospheric chemistry. The land cover and land use change scenarios are taken from the Integrated Model to Assess the Global Environment (IMAGE). In addition to changes in surface trace gas exchanges associated with land use changes, we include changes in micro- and boundary layer meteorology and hydrology and elaborate on the relative importance of land use changes compared to anticipated increases in anthropogenic emissions for atmospheric chemistry.

  17. 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

  18. 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.

  19. 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...

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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...

  8. 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...

  9. A study of stratified class design for global land cover classification

    NASA Astrophysics Data System (ADS)

    Soyama, Noriko; Muramatsu, Kanako; Daigo, Motomasa; Ochiai, Fumio

    A high accuracy global land cover data is required for the study of the estimation of gross primary production (GPP) using satellite data sets. Recently, information of the Flux sites where are located various land cover situation, is used for GPP estimation study. A number of global land cover products have been produced, and their legends are less consistent. The more fragmenting legends, accuracy of land cover product intend to be reduced. From the perspective of the GPP estimation study, all legends of each global land cover system are not necessarily set so that user need legends. For example, Broad leaf forest is important for the GPP estimation, but values in which used to determine the formula of GPP estimation, are very different among Flux sites. In this study, we propose a stratified class design for global land cover classification to effectively use in the GPP estimation, and produce global land cover data using MODIS Aqua Surface Reflectance 8-Day L3 Global 500m SIN Grid V005. This study is pilot study of developing the global land cover classification algorithm in the Global Change Observation, Mission-Climate (GCOM-C) project by the Japan Aerospace Exploration Agency (JAXA).

  10. 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...

  11. 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…

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. REVIEW: Accuracies of Global Land Cover Maps Checked against Fluxnet Sites

    NASA Astrophysics Data System (ADS)

    Gong, Peng

    2008-01-01

    Global land cover data products are key sources of information in understanding the complex interactions between human activities and global change. They play a critical role in improving performances of ecosystem, hydrological and atmospheric models. Three freely available global land cover products developed in the United States are popularly used by the scientific community. These include two global maps developed separately by the United States Geological Survey (USGS) and the University of Maryland (UMD) with NOAA Advanced Very High Resolution Radiometer (AVHRR) data, and one developed by Boston University with the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) data. They are compared with known land cover types at 250 available Fluxnet sites around the world. The overall accuracies are 37%, 36% and 42%, respectively for the USGS, UMD and Boston global land cover maps. Some future global land cover mapping strategies are suggested.

  18. 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.

  19. Temporal Beta Diversity of Bird Assemblages in Agricultural Landscapes: Land Cover Change vs. Stochastic Processes.

    PubMed

    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 (r(2)<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

  20. 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

  1. 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...

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. Land-Cover Trends of the Sierra Nevada Ecoregion, 1973-2000

    USGS Publications Warehouse

    Raumann, Christian G.; Soulard, Christopher E.

    2007-01-01

    The U.S. Geological Survey has developed and is implementing the Land Cover Trends project to estimate and describe the temporal and spatial distribution and variability of contemporary land-use and land-cover change in the United States. As part of the Land Cover Trends project, the purpose of this study was to assess land-use/land-cover change in the Sierra Nevada ecoregion for the period 1973 to 2000 using a probability sampling technique and satellite imagery. We randomly selected 36 100-km2 sample blocks to derive thematic images of land-use/land-cover for five dates of Landsat imagery (1973, 1980, 1986, 1992, 2000). We visually interpreted as many as 11 land-use/land-cover classes using a 60-meter minimum mapping unit from the five dates of imagery yielding four periods for analysis. Change-detection results from post-classification comparison of our mapped data showed that landscape disturbance from fire was the dominant change from 1973-2000. The second most-common change was forest disturbance resulting from harvest of timber resources by way of clear-cutting. The rates of forest regeneration from temporary fire and harvest disturbances coincided with the rates of disturbance from the previous period. Relatively minor landscape changes were caused by new development and reservoir drawdown. Multiple linear regression analysis suggests that land ownership and the proportion of forest and developed cover types were significant determinants of the likelihood of direct human-induced change occurring in sampling units. Driving forces of change include land ownership, land management such as fire suppression policy, and demand for natural resources.

  7. 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.

  8. 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

  9. Impact of Upwind Land Cover Change on Mount Kilimanjaro

    NASA Astrophysics Data System (ADS)

    Fairman, J. G.; Nair, U. S.; Christopher, S. A.; Mark, B. G.; Plummer, M. A.

    2008-12-01

    Studies show local climate in mountain regions are impacted by deforestation at upwind locations. Low land deforestation alters surface energy budget, especially during dry season, altering orographic cloud formation and also surface meteorology at montane locations. While the prior investigations have focused on the effect of low land deforestation on Tropical Montane Cloud Forests, low land deforestation also has the potential to impact alpine glaciers. Retreat of alpine glaciers around the globe has be attributed to global climate change, but at sites such as Kilimanjaro impact of low land deforestation also need to considered. The focus of this study is to address this issue through the use of Regional Atmospheric Modeling System (RAMS) utilizing satellite data to specify realistic land use change scenarios. The atmospheric fields from the RAMS modeling system will be linked to glacier mass energy balance and ice flow model to study the impact of low land deforestation on glacier retreat. The presentation will include details of model development and initial results from the use of the modeling system.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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%.

  15. [Land use and land cover charnge (LUCC) and landscape service: Evaluation, mapping and modeling].

    PubMed

    Song, Zhang-jian; Cao, Yu; Tan, Yong-zhong; Chen, Xiao-dong; Chen, Xian-peng

    2015-05-01

    Studies on ecosystem service from landscape scale aspect have received increasing attention from researchers all over the world. Compared with ecosystem scale, it should be more suitable to explore the influence of human activities on land use and land cover change (LUCC), and to interpret the mechanisms and processes of sustainable landscape dynamics on landscape scale. Based on comprehensive and systematic analysis of researches on landscape service, this paper firstly discussed basic concepts and classification of landscape service. Then, methods of evaluation, mapping and modeling of landscape service were analyzed and concluded. Finally, future trends for the research on landscape service were proposed. It was put forward that, exploring further connotation and classification system of landscape service, improving methods and quantitative indicators for evaluation, mapping and modelling of landscape service, carrying out long-term integrated researches on landscape pattern-process-service-scale relationships and enhancing the applications of theories and methods on landscape economics and landscape ecology are very important fields of the research on landscape service in future.

  16. 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

  17. The impacts of land use / land cover changes on the tropical maritime climate of Puerto Rico

    NASA Astrophysics Data System (ADS)

    Torres-Valcarcel, Angel R.

    Previous studies of the influences of Land Use / Land Cover Changes (LULCC) on the climate of continental areas have provided a basis for our current understanding of LULCC impacts. However continental climates may not provide complete explanations or answer specific scientific questions for other regions, such as small tropical-maritime dominated islands. Here we provide a detailed analysis of century-scale climate change for Puerto Rico, and assess the degree to which some of this change might be related to LULCC. We used long-term data, Geographic Information Systems (GIS), statistical analysis and Regional Atmospheric Modeling Systems (RAMS) to detect and assess the impact of local urban development on temperature and precipitation. We found strong evidence of a relationship linking temperature and precipitation magnitudes to local urban development. Findings for maximum, average and minimum temperature are robust showing that urbanization has increased local temperatures and levels of impact found here represent minimum estimates since they were based on data that had some prior adjustment intended to control for urban signals. Strong evidence of this relationship was also found in the precipitation data analysis, but no clear correlation was found in the direction, magnitude, period and location of rain with urban development implying that other factors dominate or are playing some role in this relationship. RAMS numerical modeling results were inconclusive suggesting that further tuning of settings and parameters are needed before model results can be used to guide decision-making.

  18. 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.

  19. Application of Spectral Mixture Analysis to Urban Land use/Land cover Extraction

    NASA Astrophysics Data System (ADS)

    Argany, M.; Sarajian, M. R.

    2009-04-01

    Remote sensing satellite imagery represent important source of information for urban analysis. But because of large spatial pixel sizes for multispectral and hyperspectral sensors that numerous disparate substances can contribute to the spectrum measured from a single pixel, spectral unmixing algorithms can be used to determine the land use/land cover and sub pixel data. In this paper, in order to determine the individual constituent materials present in pixels, the linear spectral unmixing method has been used. By using the linear spectral unmixing method, the components in mixed pixels are identified, and by performing inverse operation, the proportions of the materials are determined and the measured spectrum of a mixed pixel is decomposed into a collection of constituent spectra, or endmembers. Accordingly, a set of corresponding fractions, or abundances, that indicate the proportion of each endmember present in the pixel are specified. Endmembers normally correspond to familiar objects in the scene, and here they are green vegetation, impervious surface, soil and shade, etc. So, in the next stage endmembers have been selected using Pixel Purity Index (PPI) to find the most spectrally pure pixels. The PPI was computed by repeatedly projecting n-dimensional scatter plots on to a random unit vector. In the final stage, abundances have been extracted by an inversion algorithm and fraction images have been made. Study area in this paper is Karaj city and ETM+ image taken by Landsat satellite has been used.

  20. 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.

  1. 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

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

    EPA Science Inventory

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

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

    NASA Astrophysics Data System (ADS)

    Ganzeveld, L.; Bouwman, L.; Stehfest, E.; van Vuuren, D.; Eickhout, B.; Lelieveld, J.

    2010-12-01

    To demonstrate potential future consequences of land-cover and land-use changes beyond those for physical climate and the carbon cycle, we present an analysis of the impacts of land-cover and land-use changes on atmospheric chemistry and climate simulated with the chemistry-climate model EMAC. Future (2050) land-use and land-cover changes are expected to result in an increase of global annual soil NO emissions by ~1.2 TgN yr-1 (9%) whereas isoprene emissions decrease by ~50 TgC yr-1 (-12%) compared to present-day. The analysis shows increases in simulated boundary layer ozone mixing ratios up to ~9 ppbv and more then a doubling in hydroxyl radical concentrations over tropical deforested areas. However, small changes in global atmosphere-biosphere fluxes of NOx and ozone point to the significance of compensating effects. Our study indicates that assessment of the impact of land-cover and land-use changes on atmospheric chemistry requires a consistent representation of emissions, deposition, canopy interactions and their dependence on physical and biogeochemical drivers to properly account for these compensating effects. It results in negligible changes in the atmospheric oxidizing capacity and, consequently, in the lifetime of methane. In contrast, the analysis indicates a pronounced increase in oxidizing capacity as a consequence of anticipated increases in anthropogenic emissions.

  4. 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 ...

  5. 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...

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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.…

  11. 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...

  12. Monitoring urbanization and land cover change in the Yangtze River Delta: a case study of Pudong New Area, Shanghai

    NASA Astrophysics Data System (ADS)

    Xia, Junshi; Du, Peijun; Cao, Wen

    2009-06-01

    In this paper, Pudong New Area in Shanghai was selected as the study area, and medium resolution Landsat TM/ETM+ and CBERS (China-Brazil Earth Resources Satellite) images were used as data source. Two classification methods were applied to generate land cover maps: Maximum Likelihood Classifier (MLC) and a hierarchical method based on the V-I-S model (H-VIS). After comparing the results derived from these two methods, H-VIS model provides more accurate results than MLC. By analyzing the land cover change from 1989 to 2008, it was found that agricultural land has decreased greatly, while impervious surface area (ISA, including residential and commercial/industrial/traffic land) has increased year by year. In order to better monitor urbanization, diversity index, shape index, fractal dimension and isolation were selected to analyze the landscape pattern in the study area. The results show that the complexity of landscape structure and the fragmentation of the landscape increased from 1989 to 2008, however, the intensity and tendency of the landscape changes varied during the two comparative periods: 1989-2001 and 2001-2008. Finally, using data obtained from image interpretation and other data source, land cover change patterns and their driving forces, including economy, population and policies were analyzed.

  13. 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.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Huang, Kuo-Ching; Huang, Thomas C. C.

    2014-02-01

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

  16. 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.

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

    USGS Publications Warehouse

    Sleeter, Benjamin M.; Raumann, Christian G.

    2006-01-01

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

  18. Spatially varying relationships between land-cover change and driving factors at multiple sampling scales.

    PubMed

    Du, Shihong; Wang, Qiao; Guo, Luo

    2014-05-01

    Modeling the relationships between environment, human activity, and natural conditions is very important for understanding human-environment interactions. This study aims at examining how these relationships vary over spatial sampling scales and investigating the spatially varying relationships between land-cover changes and driving factors, as well as the variations in the relationships at different sampling scales in the Tibetan Autonomous Prefecture of Qinghai Province, P.R. China. Regular sampling methods are used first to generate eight sets of data points at different scales, and then the values for land-cover changes and the factors are extracted for these data points. Geographically weighted regression (GWR) model is applied to analyze the relationships between land-cover changes and the factors at different sampling scales. The results indicate that the influences of the factors (e.g. the signs, significances, and values of coefficients) change greatly over different sampling scales; similarly, for different types of land-cover changes, the contributions of the factors also vary. Generally, roads, rivers, and lakes contribute greatly to land-cover changes, while villages, temples, and elevations contribute less. A possible reason is that the densities of roads, rivers, and lakes is much greater than those of villages and temples, and the populations in temples and villages are too small to have much effect on land-cover changes. The results demonstrate that the sampling scales have an important influence on the relationships between land-cover change and the factors. PMID:24603033

  19. Spatially varying relationships between land-cover change and driving factors at multiple sampling scales.

    PubMed

    Du, Shihong; Wang, Qiao; Guo, Luo

    2014-05-01

    Modeling the relationships between environment, human activity, and natural conditions is very important for understanding human-environment interactions. This study aims at examining how these relationships vary over spatial sampling scales and investigating the spatially varying relationships between land-cover changes and driving factors, as well as the variations in the relationships at different sampling scales in the Tibetan Autonomous Prefecture of Qinghai Province, P.R. China. Regular sampling methods are used first to generate eight sets of data points at different scales, and then the values for land-cover changes and the factors are extracted for these data points. Geographically weighted regression (GWR) model is applied to analyze the relationships between land-cover changes and the factors at different sampling scales. The results indicate that the influences of the factors (e.g. the signs, significances, and values of coefficients) change greatly over different sampling scales; similarly, for different types of land-cover changes, the contributions of the factors also vary. Generally, roads, rivers, and lakes contribute greatly to land-cover changes, while villages, temples, and elevations contribute less. A possible reason is that the densities of roads, rivers, and lakes is much greater than those of villages and temples, and the populations in temples and villages are too small to have much effect on land-cover changes. The results demonstrate that the sampling scales have an important influence on the relationships between land-cover change and the factors.

  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. 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.

  2. 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.

  3. 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.

  4. What you should know about land-cover data

    USGS Publications Warehouse

    Gallant, A.L.

    2009-01-01

    Wildlife biologists are using land-characteristics data sets for a variety of applications. Many kinds of landscape variables have been characterized and the resultant data sets or maps are readily accessible. Often, too little consideration is given to the accuracy or traits of these data sets, most likely because biologists do not know how such data are compiled and rendered, or the potential pitfalls that can be encountered when applying these data. To increase understanding of the nature of land-characteristics data sets, I introduce aspects of source information and data-handling methodology that include the following: ambiguity of land characteristics; temporal considerations and the dynamic nature of the landscape; type of source data versus landscape features of interest; data resolution, scale, and geographic extent; data entry and positional problems; rare landscape features; and interpreter variation. I also include guidance for determining the quality of land-characteristics data sets through metadata or published documentation, visual clues, and independent information. The quality or suitability of the data sets for wildlife applications may be improved with thematic or spatial generalization, avoidance of transitional areas on maps, and merging of multiple data sources. Knowledge of the underlying challenges in compiling such data sets will help wildlife biologists to better assess the strengths and limitations and determine how best to use these data.

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

    PubMed Central

    Reis, Selçuk

    2008-01-01

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

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. Integrated remote sensing for multi-temporal analysis of urban land cover-climate interactions

    NASA Astrophysics Data System (ADS)

    Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.

    2016-08-01

    Climate change is considered to be the biggest environmental threat in the future in the South- Eastern part of Europe. In frame of predicted global warming, urban climate is an important issue in scientific research. Surface energy processes have an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. This paper investigated the influences of urban growth on thermal environment in relationship with other biophysical variables in Bucharest metropolitan area of Romania. Remote sensing data from Landsat TM/ETM+ and time series MODIS Terra/Aqua sensors have been used to assess urban land cover- climate interactions over period between 2000 and 2015 years. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Based on these parameters, the urban growth, and urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

  16. 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

  17. 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

  18. Land Cover Classification Method using Combined Signatures of L-band Radar and Radiometer

    NASA Astrophysics Data System (ADS)

    Colliander, A.

    2011-12-01

    This study investigates the utility of combining L-band radar and radiometer measurements for more accurate land cover classification in terms of vegetation type and density. This investigation is relevant in the context of two NASA missions which employ L-band active and passive measurements. The first one, Aquarius, was launched in June 2011 and the second one, SMAP (Soil Moisture Active Passive) is proposed for launch in late 2014. The results of this study can be applied in the observation situation of both of these missions to improve L-band land cover characterization for the benefit of retrieval accuracy of parameters such as soil moisture and freeze/thaw state. Brightness temperature, measured by radiometer, is the product of the physical temperature and emissivity of the target. Reflectivity describes how much of radiation incident on the surface reflects and scatters away from it to all directions. The sum of emissivity and reflectivity equals one. On the other hand, backscatter, measured by radar, expresses how much of radiation incident on the surface reflects back to the direction of the radar. The difference between reflectivity and backscatter can be quantified by introducing Normalized Reflection Difference (NRD), which is normalized difference between reflectivity and backscatter. In the proposed method the NRD value is merged with brightness temperature polarization index (MPI) and cross-polarized backscatter to classify the land cover of the measured area. The method is tested using the experimental data obtained with the PALS (Passive and Active L- band System) airborne instrument over numerous locations in US between 1999 and 2008. The PALS instrument performs coincidental radiometer and radar measurements. The in situ data recorded in the abovementioned campaigns allow classification based on not only vegetation type but also based on Vegetation Water Content (VWC), biomass, Leaf Area Index (LAI) soil texture and surface roughness. The

  19. Land cover data from Landsat single-date archive imagery: an integrated classification approach

    NASA Astrophysics Data System (ADS)

    Bajocco, Sofia; Ceccarelli, Tomaso; Rinaldo, Simone; De Angelis, Antonella; Salvati, Luca; Perini, Luigi

    2012-10-01

    The analysis of land cover dynamics provides insight into many environmental problems. However, there are few data sources which can be used to derive consistent time series, remote sensing being one of the most valuable ones. Due to their multi-temporal and spatial coverage needs, such analysis is usually based on large land cover datasets, which requires automated, objective and repeatable procedures. The USGS Landsat archives provide free access to multispectral, high-resolution remotely sensed data starting from the mid-eighties; in many cases, however, only single date images are available. This paper suggests an objective approach for generating land cover information from 30m resolution and single date Landsat archive satellite imagery. A procedure was developed integrating pixel-based and object-oriented classifiers, which consists of the following basic steps: i) pre-processing of the satellite image, including radiance and reflectance calibration, texture analysis and derivation of vegetation indices, ii) segmentation of the pre-processed image, iii) its classification integrating both radiometric and textural properties. The integrated procedure was tested for an area in Sardinia Region, Italy, and compared with a purely pixel-based one. Results demonstrated that a better overall accuracy, evaluated against the available land cover cartography, was obtained with the integrated (86%) compared to the pixel-based classification (68%) at the first CORINE Land Cover level. The proposed methodology needs to be further tested for evaluating its trasferability in time (constructing comparable land cover time series) and space (for covering larger areas).

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

    USGS Publications Warehouse

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

    2009-01-01

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

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

    USGS Publications Warehouse

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

    2007-01-01

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

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

    SciTech Connect

    Not Available

    1984-12-01

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

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

    USGS Publications Warehouse

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

    2012-01-01

    The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the r