A modeling approach for estimating watershed impervious surface area from National Land Cover Data 92

Photogrammetric Engineering and Remote Sensing

Volumn 70, Issue 11, 2004, Pages 1295-1307

  Jennings, David B ^a   Jarnagin, S Taylor ^a   Ebert, Donald W ^a  

^a U S ENVIRONMENTAL PROTECTION AGENCY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ERROR ANALYSIS; LINEAR EQUATIONS; MATHEMATICAL MODELS; VECTORS;

SUBWATERSHEDS; SURFACE AREA;

WATERSHEDS;

GIS; LAND COVER; LAND USE; PIXEL; WATERSHED;

EID: 7944238651     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.70.11.1295     Document Type: Review

References (43)

1. Anderson, J., E. Hardy, J. Roach, and R. Witmer, 1976. A Land Use and Land Cover Classification System for use with Remote Sensor Data, U.S. Geological Survey, Professional Paper 964, Government Printing Office, Washington, D.C., 37 p.
2. Bird, S., J. Harrison, L. Exum, S. Alberty, and C. Perkins, 2002. Screening to identify and prevent urban storm water problems: Estimating impervious area accurately and inexpensively, URL: http://www.nwqmc.org/ nationalconference/2002conference/ 2000conf.htm; last date accessed 26 August 2004. Proceedings of the National Water Quality Monitoring Council Conference, Madison, Wisconsin, May 19-23, 2002.
3. Barry, B.A., 1964. Engineering Measurements, John Wiley & Sons, Inc., New York, N.Y., 136 p.
4. Cappiella, K., and K. Brown, 2001. Impervious Cover and Land Use in the Chesapeake Bay Watershed, Center for Watershed Protection, Ellicott City, Maryland, 55 p.
5. CWP (Center for Watershed Protection), 2003. Impacts of Impervious Cover on Aquatic Systems, Center for Watershed Protection, Ellicott City, Maryland, 142 p.
6. CWP (Center for Watershed Protection), 1998. Rapid Watershed Planning Handbook, Center for Watershed Protection. Ellicott City, Maryland, 368 p.
7. Civco, D.L., and J.D. Hurd, 2002. Quantifying and describing urbanizing landscapes in the northeast United States, Photogrammetric Engineering & Remote Sensing, 68(10):1083-1090.
8. Doherty, J., and J. Johnston, 2003. Methodologies for calibration and predictive analysis of a watershed model, Journal of the American Water Resources Association, 39(2):251-265.
9. Ebert, D.W., and T.G. Wade, 2000. Analytical Tools Interface for Landscape Assessments (ATtILA) User Guide: Version 2.0, Office of Research and Development, U.S. Environmental Protection Agency. Las Vegas, NV, 23 p.
10. Endreny, T., C. Somerlot, and J. Hassett, 2003. Hydrograph sensitivity to estimates of map impervious cover: A WinHSPF BASINS case study, Hydrological Processes, 17:1019-1034.
11. Fairfax County, 2003. Fairfax County, Virginia GIS & Mapping - CD Products, URL: http://www.co.fairfax.va.us/maps/map.htm, Fairfax County GIS & Mapping Services, Fairfax, Virginia (last date accessed 26 August 2004).
12. Foody, G., 2002. Status of land cover classification accuracy assessment, Remote Sensing of Environment, 80(1):185-201.
13. Hession, W.C., T. Johnson, D. Charles, D. Hart, R. Horwitz, D. Kreeger, J. Pizzuto, D. Velinsky, J. Newbold, C. Cianfrani, T. Clason, A. Compton, N. Coulter, L. Fuselier, B. Marshall, and J. Reed, 2000. Ecological Benefits of Riparian Reforestation in Urban Watersheds: Study Design and Preliminary Results, Environmental Monitoring and Assessment, 63:211-222.
14. Homer, C.G., C. Huang, L. Yang, and B. Wylie, 2002. Development of a Circa 2000 Landcover Database for the United States, Proceedings of the ASPRS 2002 Annual Convention, April 2002, Washington D.C. (American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland), unpaginated CD-ROM.
15. Jantz, C.A., S.J. Goetz, and M.K. Shelley. 2004. Using the SLEUTH Urban Growth Model to Simulate the Impacts of Future Policy Scenarios on Urban Land Use in the Baltimore-Washington Metropolitan Area. Environment and Planning B, 31(2):251-271.
16. Jarnagin, S.T., D.B. Jennings, and D.W. Ebert, 2004. A technique for assessing the accuracy of sub-pixel estimates extracted from Landsat TM imagery, pp. 269-280 (R. S. Lunetta, and J. G. Lyon, editors), Remote Sensing and GIS Accuracy Assessment, CRC Press, Boca Raton, Florida (320 p.).
17. Jennings, D., and S.T. Jarnagin, 2002. Impervious surfaces and streamflow: A historical perspective in a mid-Atlantic subwatershed, Landscape Ecology, 17(5):471-489.
18. Ji, M., and J.R. Jensen, 1999. Effectiveness of subpixel analysis in detecting and quantifying urban imperviousness from Landsat Thematic Mapper, Geocarto International, 14(4):31-39.
19. Light, D., 1993. The National Aerial Photography Program as a geographic information resource, Photogrammetric Engineering & Remote Sensing, 59:61-65.
20. Loveland, T.R., and D.M. Shaw, 1996. Multi-Resolution Land Characterization: Building collaborative partnerships, GAP Analysis: A Landscape Approach to Biodiversity Planning (J.M. Scott, T. Tear, and F. Davis, editors), Proceedings of the ASPRS/GAP Symposium, Charlotte, North Carolina, National Biological Service, Moscow, Idaho, pp. 83-89.
21. Lunetta, R., J.G. Lyon, B. Guindon, and C.D. Elvidge, 1998. North American Landscape Characterization Dataset development and data fusion issues, Photogrammetric Engineering & Remote Sensing, 64(8):821-829.
22. Merideth, A., S. Menard, M. VanderWilt, D. Eslinger, and S. Prisloe, 2003. ISAT: A tool for determining the percentage of impervious surfaces area in a region, Proceedings of the Coastal Geotools Conference, January 2003, Charleston, South Carolina.
23. Messer, J.J., R.A. Linthurst, and W.S. Overton, 1991. An EPA program for monitoring ecological status and trends, Environmental Monitoring Assessment, 17:67-78.
24. Pitchford, A.M., J.M. Denver, A.R. Olsen, S.W. Ator, S. Cormier, M.S. Nash, and M.H. Mehaffey, 2000. Testing landscape indicators for stream vulnerability to pesticides and nutrients: Landscape indicators for pesticides study for Mid Atlantic coastal streams (LIPS-MACS), EPA/600/R-00/87, U.S. Environmental Protection Agency, Washington, D.C., 84 p.
25. Prisloe, M., L. Gianotti, and W. Sleavin, 2001. Determining impervious surfaces for watershed modeling applications, 8th National Non-point Monitoring Workshop, Hartford, Connecticut, URL: http://nemo.uconn.edu/publications/ geospatial_pubs/impervious_surfaces_for_watersheds.doc, Nonpoint Education for Municipal Officials (NEMO), University of Connecticut Cooperative Extension System (last date accessed 26 August 2004).
26. Schueler, T.R., 1994. The importance of imperviousness, Watershed Protection Techniques, 1(3):100-111.
27. Serveiss, V., 2002. Applying ecological risk principles to watershed assessment and management, Environmental Management, 29(2): 145-154.
28. Sleavin, W., D. Civco, S. Prisloe, and L. Gianotti, 2000. Measuring impervious surfaces for non-point source pollution modeling, Proceedings of the ASPRS Annual 2000 Annual Convention, 22-26 May, Washington District of Columbia (American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland), unpaginated CD-ROM.
29. Smith, A., 2001. Sub-pixel estimates of impervious cover from Landsat TM image, URL: http://www.geog.umd.edu/resac/impervious2.htm; last date accessed 26 August 2004, Mid-Atlantic Regional Earth Science Applications Center (RESAC), Department of Geography, University of Maryland, College Park, Maryland.
30. Slonecker, E.T., D. Jennings, and D. Garofalo, 2001. Remote sensing of impervious surfaces: A review, Remote Sensing Reviews, 20: 227-255.
31. Tobler, W., 1970. A computer movie simulating urban growth in the Detroit region, Economic Geography (Supplement), 46:234-240.
32. Thompson, S.K., 2002. Sampling, Second Edition, J. Wiley and Sons, New York, N.Y., 400 p.
33. USDA (United States Department of Agriculture), 1986. Urban hydrology for small watersheds, Technical Release 55, second edition, 164 p. and URL: http://www.wcc.nrcs.usda.gov/hydro/hydro-tools-models-tr55.html; last date accessed 26 August 2004, United States Department of Agriculture, Washington D.C.
34. USEPA (United States Environmental Protection Agency), 2001. Better Assessment Science Integrating Point and Nonpoint Sources: Basins Version 3.0, User's Manual, EPA823B01001, and URL: http://www.epa.gov/OST/BASINS/; last date accessed 26 August 2004, U.S. Environmental Protection Agency, Washington, D.C.
35. USEPA (United States Environmental Protection Agency), 2003a. Multi-Resolution Land Characteristics Consortium, URL: http://www.epa.gov/mrlc/; last date accessed 26 August 2004, U.S. Environmental Protection Agency, Washington, D.C.
36. USEPA (United States Environmental Protection Agency), 2003b. Environmental Monitoring and Assessment Program (EMAP), URL: http://www.epa.gov/emap; last date accessed 26 August 2004, U.S. Environmental Protection Agency, Washington, D.C.
37. USEPA (United States Environmental Protection Agency), 2003c. Total Maximum Daily Loads, URL: http://www.epa.gov/owow/ tmdl/; last date accessed 26 August 2004, U.S. Environmental Protection Agency, Washington, D.C.
38. USGS (United States Geological Survey), 2003a. Digital Orthophoto Program, URL: http://www.ndop.gov/, United States Geological Survey, Reston, Virginia (last date accessed 26 August 2004).
39. USGS (United States Geological Survey), 2003b. Earth Resources Observation Systems (EROS) Data Center, URL: http://edcwww.cr. usgs.gov; last date accessed 26 August 2004, United States Geological Survey, Sioux Falls, South Dakota.
40. Vogelmann, J.E., T. Sohl, and S.M. Howard, 1998. Regional characterization of regional land cover using multiple sources of data, Photogrammetric Engineering & Remote Sensing, 4:45-57.
41. Wu, C., and A. Murray, 2003. Estimating impervious surface distribution by spectral mixture analysis, Remote Sensing of Environment, 84:493-505.
42. Yang, L., S. Stehman, J. Smith, and J. Wickham, 2001. Thematic accuracy of MRLC land cover for the Eastern United States, Remote Sensing of Environment, 76:418-422.
43. Yang, L., C. Huang, C. Homer, B. Wylie, and M. Coan, 2003. An approach for mapping large-area impervious surfaces: Synergistic use of Landsat 7 ETM+ and high spatial resolution imagery, Canadian Journal of Remote Sensing, 29(2):230-240.