IKONOS imagery for resource management: Tree cover, impervious surfaces, and riparian buffer analyses in the mid-Atlantic region

Remote Sensing of Environment

Volumn 88, Issue 1-2, 2003, Pages 195-208

  Goetz, Scott J ^a,b   Wright, Robb K ^b   Smith, Andrew J ^b   Zinecker, Elizabeth ^b   Schaub, Erika ^b  

^a WOODS HOLE RESEARCH CENTER   (United States)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

IKONOS imagery; Mid Atlantic region; Resource management

Indexed keywords

DATA ACQUISITION; DECISION MAKING; MANAGEMENT; NATURAL RESOURCES; SATELLITES; WATERSHEDS;

DATA SETS; PHOTOGRAPHIC MAPPING;

REMOTE SENSING;

FOREST COVER; REMOTE SENSING; RESOURCE MANAGEMENT; RIPARIAN ZONE; SATELLITE IMAGERY;

RIPARIA;

EID: 0242463529     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2003.07.010     Document Type: Article

References (30)

1. Birk R.J., Stanley T., Snyder G.L. U.S. Government commercial data purchase programs for use in government-sponsored science and applications activities. Remote Sensing of Environment. 2003; doi:10.1016/S0034-4257(03) 00227-X.
2. Blonski S. IKONOS-based simulations of Landsat 7 VNIR data: Comparison with actual, coincident images. Proceedings of the 2001 High Spatial Resolution Commercial Imagery Workshop, Greenbelt, MD, USA, March 19-21 (sponsored by NASA/NIMA/USGS Joint Agency Commercial Imagery Evaluation Team). 2001;. CD-ROM.
3. Breiman L., Freidman J., Olshend R., Stone C. Classification and regression trees. 1984;Wadsworth, Monterey, CA.
4. Cooper J.R., Gilliam J.W., Daniels R.D., Robarge W.P. Riparian areas as filters for agricultural sediment. Soil Science Society of America Journal. 51:1987;416-420.
5. Correll D.L. Buffer zones and water quality protection: General principles. Haycock N.E., Burt T.P., Goulding K.W.T., Pinay G. Buffer zones: their processes and potential in water protection. 1997;7-20 Quest Environmental, Harpenden, UK.
6. Dial G.F., Bowen H., Gerlach B., Grodecki J., Oleszczuk R. IKONOS satellite, sensor, imagery, and products. Remote Sensing of Environment. 88:2003;23-36 doi:10.1016/S0034-4257(03)00229-3.
7. Fisher J., Goetz S.J. Considerations in the use of high spatial resolution imagery: An applications research assessment. American Society for Photogrammetry and Remote Sensing (ASPRS) Conference Proceedings, St. Louis, MO. 2001;8. Available from ASPRS ( http://www.asprs.org ) and at http://www.geog.umd.edu/resac.
8. Friedl M.A., Brodley C.E. Decision tree classification of land cover from remotely sensed data. Remote Sensing of Environment. 61(3):1997;399-409.
9. Friedl M., Brodley C., Strahler A. Maximizing land cover classification accuracies produced by decision trees at continental to global scales. IEEE Transactions on Geoscience and Remote Sensing. 37(2):1999;969-981.
10. Goetz S.J. Multi-sensor analysis of NDVI, surface temperature and biophysical variables at a mixed grassland site. International Journal of Remote Sensing. 18(1):1997;71-94.
11. Goward S.N., Davis P.E., Fleming D., Miller L., Townshend J.R.G. Empirical comparison of Landsat 7 and IKONOS multispectral measurements for Selected Earth Observation System (EOS) Validation Sites. Remote Sensing of Environment. 88:2003;79-98 doi:10.1016/j.rse.2003.06.007.
12. Hansen M., Dubayah R., DeFries R.S. Classification trees: An alternative to traditional land cover classifiers. International Journal of Remote Sensing. 17(5):1996;1075-1081.
13. Helder D., Coan M., Patrick K., Gaska P. IKONOS geometric characterization. Remote Sensing of Environment. 88:2003;68-78 doi:10.1016/S0034-4257(03)00232-3.
14. Hosmer D.W., Lemeshow S. Applied logistic regression. 1989;Wiley, New York.
15. Iverson L.R., Szafoni D.L., Baum S.E., Cook E.A. A riparian wildlife habitat evaluation scheme developed using GIS. Environmental Management. 28(5):2001;639-654.
16. Jantz C.A., Goetz S.J., Shelley M.A. Using the SLEUTH urban growth model to simulate the land use impacts of policy scenarios in the Baltimore- Washington metropolitan region. Environment and Planning, B. 2003;. (in press).
17. Kaufman Y.J., Tanre D. Atmospherically Resistant Vegetation Index (ARVI) for EOS-MODIS. IEEE Transactions on Geoscience and Remote Sensing. 30:1992;260-271.
18. Lonard R.I., Judd F.W., Desai M.D. Evaluation of color-infrared photography for distinguishing annual changes in riparian forest vegetation of the lower Rio Grande in Texas. Forest Ecology and Management. 128(1/2):2000;75-82.
19. Lowrance R., Altier L.S., Newbold J.D., Schnabel R.R., Groffman P.M., Denver J.M.et al. Water quality functions of riparian forest buffer systems in the Chesapeake Bay watershed. Environmental Management. 21:1997;687-712.
20. McCauley S., Goetz S.J. Mapping residential density patterns using multi-temporal Landsat imagery and a decision-tree classifier. International Journal of Remote Sensing. 2003;. (in press).
21. Menard S. Applied logistic regression analysis. Quantitative Applications in the Social Sciences. 106:1995;Sage Publications, Thousand Oaks, CA.
22. M-NCPPC (2000). Legacy Open Space functional master plan, Montgomery County Department of Park and Planning, Silver Spring, MD, 80 pp. plus appendices and maps ( http://www.mc-mncppc.org/legacy_open_space ).
23. Sawaya K., Olmanson L., Holden G., Sieracki J., Heinert N., Bauer M. Extending satellite remote sensing to local scales: Land and water resource management using high resolution imagery. Remote Sensing of Environment. 88:2003;143-155 doi:10.1016/j.rse.2003.04.006.
24. Smith, A. J., Goetz, S. J., Prince, S. D., Wright, R., Melchoir, B., Mazzacato, E. M., & Jantz, C. (fourthcoming). Estimation of sub-pixel impervious surface area using a decision tree approach, IKONOS and Landsat imagery. Remote Sensing of Environment.
25. Stoney W. The past, present, and future of the medium- and high-resolution satellite world. Baker J.C., O'Connell K.M., Williamson R.A. Commercial observation satellites: At the leading edge of global transparency. 2001;652-661 RAND Corporation and the American Society for Photogrammetry and Remote Sensing, Santa Monica, California. Available online at http://www.rand.org/publications/MR/MR1229/.
26. Stribling J.B., Jessup B.K., White J.S., Boward D., Hurd M. Development of a benthic index of biotic integrity for Maryland streams. 1998;Montgomery Department of Natural Resources, Annapolis. 62 pp.
27. Tanaka S., Toshiro S. A new frontier of remote sensing from IKONOS images. International Journal of Remote Sensing. 22(1):2001;1-5.
28. Van Ness K., Brown K., Haddaway M., Marshall D., Jordahl D. Montgomery County water quality monitoring program: Stream monitoring protocols. 1997;Watershed Management Division, Department of Environmental Protection.
29. Varlyguin D., Wright R., Goetz S.J., Prince S.D. Advances in land cover classification for applications research: A case study from the mid-Atlantic RESAC. American Society for Photogrammetry and Remote Sensing (ASPRS) Conference Proceedings, St. Louis, MO. 2001;7.
30. Weber T., Wolf J. Maryland's green infrastructure - using landscape assessment tools to identify a regional conservation strategy. Environmental Monitoring and Assessment. 63:2000;265-277.