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Results for “Land Use and Land Cover”

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At least 91 records · Page 5Linked to original sources
USGS1990

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

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

Data Users Guide↗
USGS2023

Observing coastal wetland transitions using national land cover products

Over the coming century, climate change and sea-level rise are predicted to cause widespread change to coastal wetlands. Estuarine vegetated wetlands can adapt to sea-level rise through both vertical development (i.e., biophysical feedbacks and sedimentation) and upslope/horizontal migration. Quantifying changes to estuarine vegetated wetlands over time can help to inform current and future decisions regarding land management and resource stewardship. In this study, we show how coastal land cover maps readily available in the US can be used to assess and understand estuarine vegetated wetland changes. This assessment involves two steps: (1) identifying the net gain/loss of estuarine vegetated wetlands and (2) determining which land cover types contribute to the net gain/loss. From this information, we developed estuarine vegetated wetland change scenarios that evaluate whether estuarine vegetated wetland gain kept up with loss and whether the contribution was from: (1) estuarine vegetated wetland migration or tidal restoration; (2) land building (i.e., development); or (3) both. We assessed changes from 1996 to 2016 for: (1) the conterminous US; (2) each major US coastline; and (3) focal estuaries with the most change per coast. We found that the change scenario (1, 2, or 3) varied across coastlines. Moving forward, national coastal land cover programs can be informed by utilizing methodologies that leverage contemporary information for delineating the estuarine zone from upslope/adjacent wetlands. We highlight approaches that could be used to address this challenge and provide complementary information related to wetland condition changes.

Progress in Physical Geography: Earth and Environm↗
USGS2009

Foreword to the issue on remote sensing of regional land use and land cover

This issue showcases some good work from Chinese authors who attended the International Workshop of Earth Observation and Remote Sensing Applications (EORSA), held in Beijing, China, June 30-July 2, 2008. The five articles in this issue focus on remote sensing of regional land use and land cover.

IEEE Journal of Selected Topics in Applied Earth O↗
USGS1978

Metropolitan land cover inventory using multiseasonal Landsat data

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.

Open-File Report↗
USGS2008

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

A wide variety of ecological applications require spatially explicit current and projected land-use and land-cover data. The southeastern United States has experienced massive land-use change since European settlement and continues to experience extremely high rates of forest cutting, significant urban development, and changes in agricultural land use. Forest-cover patterns and structure are projected to change dramatically in the southeastern United States in the next 50 years due to population growth and demand for wood products [Wear, D.N., Greis, J.G. (Eds.), 2002. Southern Forest Resource Assessment. General Technical Report SRS-53. U.S. Department of Agriculture, Forest Service, Southern Research Station, Asheville, NC, 635 pp]. Along with our climate partners, we are examining the potential effects of southeastern U.S. land-cover change on regional climate. The U.S. Geological Survey (USGS) Land Cover Trends project is analyzing contemporary (1973-2000) land-cover change in the conterminous United States, providing ecoregion-by-ecoregion estimates of the rates of change, descriptive transition matrices, and changes in landscape metrics. The FORecasting SCEnarios of future land-cover (FORE-SCE) model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land-cover change through 2050 for the southeastern United States. Prescriptions for future proportions of land cover for this application were provided by ecoregion-based extrapolations of historical change. Logistic regression was used to develop relationships between suspected drivers of land-cover change and land cover, resulting in the development of probability-of-occurrence surfaces for each unique land-cover type. Forest stand age was initially established with Forest Inventory and Analysis (FIA) data and tracked through model iterations. The spatial allocation procedure placed patches of new land cover on the landscape until the scenario prescriptions were met, using measured Land Cover Trends data to guide patch characteristics and the probability surfaces to guide placement. The approach provides an efficient method for extrapolating historical land-cover trends and is amenable to the incorporation of more detailed and focused studies for the establishment of scenario prescriptions.

Ecological Modelling↗