Urban development and flooding in Houston Texas, inferences from remote sensing data using neural network technique

Environmental Geology

Volumn 47, Issue 8, 2005, Pages 1120-1127

  Khan, Shuhab D ^a  

^a UNIVERSITY OF HOUSTON   (United States)

Author keywords

Flooding; Houston; Remote sensing; Texas; Urbanization

Indexed keywords

ASPHALT; CONCRETES; DATA REDUCTION; ECOSYSTEMS; FLOODS; GEOGRAPHIC INFORMATION SYSTEMS; INTERNET; NEURAL NETWORKS; REMOTE SENSING; VEGETATION; WATER;

ARC INTERNET MAP SERVER (ARCIMS); NATURAL ECOSYSTEMS; URBAN DEVELOPMENT;

GEOLOGY;

ARTIFICIAL NEURAL NETWORK; FLOODING; GIS; REMOTE SENSING; URBANIZATION;

HOUSTON; NORTH AMERICA; TEXAS; UNITED STATES; WESTERN HEMISPHERE; WORLD;

EID: 21344433009     PISSN: 09430105     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00254-005-1246-x     Document Type: Article

References (18)

1. Asrar G, Greenstone R (1995) MTPE/EOS reference handbook, NASA/Goddard Space flight center, Greenbelt, Maryland
2. Atkinson PM, Tatnall ARL (1997) Neural networks in remote sensing. Int J Remote sens 18(4):699-709
3. Barker JL (1983) Radiometeric calibration and processing procedures for reflective bands on Landsat-4 protoflight. In: Proceedings of Landsat-4 scientific characterization early results symposium, A-23-1, NAsa/GSFC, Greenbelt, MD
4. Claytor RA, Whitney EB (1996) Environmental indicators to assess stormwater control programs and practices. Prepared by the Center for Watershed Protection, Silver Spring, Maryland, in cooperation with the US Environmental Protection Agency
5. Collins JB, Woodcock CE (1996) An assessment of several linear change detection techniques for mapping forest mortality using mutlispectral Landsat TM data. Remote Sens Environ 56:66-77
6. Jensen JR (1996) Introductory digital image processing a remote sensing perspective. Prentice Hall, Englewood Cliffs
7. Jensen JR, Narumalani S, Weatherbee O, Mackey HEM (1993) Measurement of seasonal and yearly cattail and waterlily changes using multidate SPOT Panchromatic data. Photogramm Engineering Remote Sens 59(4):519-525
8. Jensen JR, Qiu F, Petterson K (1999) A neural network image interpretation system to extract rural and urban land use and land cover information from remote sensor data. Geocarto Int 16(1):19-28
9. Khorram S, Biging GS, Chrisman NR, Colby DR, Congalton RG, Dobson JE, Ferguson RL, Goodchild MF, Jensen JR, Mace TH (1999) Accuracy assessment of remote sensing devised change detection. ASPRS Monograph, American Society for Photogrammetry and Remote Sensing, Bethada
10. Lambin EF, Ehrlich D (1996) The surface temperature-vegetation index space for land cover and land cover change analysis. Int J Remote Sens 17(3):463-487
11. Landsberg HE (1981) The urban climate. Academic, New York
12. Miller DM, Kaminsky EJ, Rana S (1995) Neural network classification of remote sensing data. Comput Geosci 21(3):377-386
13. Rao VB, Rao HV (1993) C++ neural network and fuzzy logic. Management Information, New York
14. Russell SJ, Norvig P (2003) Artificial intelligence: a modern approach, 2nd edn. Prentice Hall, Upper Saddle River
15. Schueler T (1995) Environmental land planning series: site planning for urban stream protection. Prepared by the Metropolitan Washington Council of Governments and the Center for Watershed Protection, Silver Spring, Maryland
16. US Bureau of Census (1996) Land area, population, and density for metropolitan areas: Population Distribution Branch, US Bureau of the Census, Washington
17. US Bureau of Census (2001) Land area, population, and density for metropolitan areas. Population Distribution Branch, US Bureau of the Census, Washington
18. Wahl KL, Thomas WO, Hirsch RM (1995) Stream-gaging program of the U.S. Geological Survey.U.S. Geological Survey Circular 1123, Reston, Virginia