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Development of a 2001 National Land-Cover Database for the United States
Open accessAbstract
Multi-Resolution Land Characterization 2001 (MRLC 2001) is a second-generation Federal consortium designed to create an updated pool of nation-wide Landsat 5 and 7 imagery and derive a second-generation National Land Cover Database (NLCD 2001). The objectives of this multi-layer, multi-source database are twofold: first, to provide consistent land cover for all 50 States, and second, to provide a data framework which allows flexibility in developing and applying each independent data component to a wide variety of other applications. Components in the database include the following: (1) normalized imagery for three time periods per path/row, (2) ancillary data, including a 30 m Digital Elevation Model (DEM) derived into slope, aspect and slope position, (3) per pixel estimates of percent imperviousness and percent tree canopy, (4) 29 classes of land cover data derived from the imagery, ancillary data, and derivatives, (5) classification rules, confidence estimates, and metadata from the land cover classification. This database is now being developed using a Mapping Zone approach, with 66 Zones in the continental United States and 23 Zones in Alaska. Results from three initial mapping Zones show single-pixel land cover accuracies ranging from 73 to 77 percent, imperviousness accuracies ranging from 83 to 91 percent, tree canopy accuracies ranging from 78 to 93 percent, and an estimated 50 percent increase in mapping efficiency over previous methods. The database has now entered the production phase and is being created using extensive partnering in the Federal government with planned completion by 2006.
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Metadata
- Authors
- Homer, C., Huang, C., Yang, L., Wylie, B., & Coan, M.
- Venue
- Photogrammetric Engineering & Remote Sensing
- Published
- 2004-07-01
- Volume
- 70
- Issue
- 7
- Pages
- 829-840
- ISSN
- 0099-1112 (ISSN-L)
- OpenAlex
- W2050830693
- Cited by
- 1,567
- References
- 0
- FWCI
- 99.52
- Type
- journal article
- Language
- en
- Open access
- hybrid
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