Evaluation of the potential of ASAR data to estimate impervious surface area

Annals of GIS

Volumn 18, Issue 4, 2012, Pages 289-298

  Zhang, Hongsheng ^a   Zhang, Yuanzhi ^a   Lin, Hui ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

ASAR; impervious surface; imperviousness; ISA; synthetic aperture radar; Wide Swath Mode

Indexed keywords

ACCURACY ASSESSMENT; IMAGE ANALYSIS; SATELLITE IMAGERY; SPECTRAL ANALYSIS; SURFACE AREA; SYNTHETIC APERTURE RADAR; THEMATIC MAPPING;

EID: 84871169050     PISSN: 19475683     EISSN: 19475691     Source Type: Journal    
DOI: 10.1080/19475683.2012.730059     Document Type: Article

References (35)

1. Arnold, C.L. Jr. and Gibbons, C.J. 1996. Impervious surface coverage: the emergence of a key environmental indicator. Journal of the American Planning Association, 62(2): 243-258.
2. Calabresi, G. 1996. The use of ERS data for flood monitoring: an overall assessment, 237-241. London: H.T.D. Guyenne, ed. 2nd ERS application workshop, 6-8 December 1995. InParis: European Space Agency (ESA)
3. Corbane, C. 2009. Comparative study on the performance of multiparameter SAR data for operational urban areas extraction using textural features. IEEE Geoscience and Remote Sensing Letters, 6(4): 728-732.
4. Cracknell, A.P. 1998. Review article synergy in remote sensing-what's in a pixel?. International Journal of Remote Sensing, 19(11): 2025-2047.
5. Dekker, R.J. 2003. Texture analysis and classification of ERS SAR images for map updating of urban areas in the Netherlands. IEEE Transactions on Geoscience and Remote Sensing, 41(9): 1950-1958.
6. Dell'Acqua, F. and Gamba, P. 2003. Texture-based characterization of urban environments on satellite SAR images. IEEE Transactions on Geoscience and Remote Sensing, 41(1): 153-159.
7. Fan, F., Wang, Y. and Wang, Z. 2008. Temporal and spatial change detecting (1998-2003) and predicting of land use and land cover in Core corridor of Pearl River Delta (China) by using TM and ETM+ images. Environmental Monitoring and Assessment, 137: 127-147.
8. Fisher, P. 1997. The pixel: a snare and a delusion. International Journal of Remote Sensing, 18(3): 679-685.
9. Franceschetti, G., Iodice, A. and Riccio, D. 2008. "SAR images of built-up areas: models and data interpretation". In Remote sensing of impervious surfaces, Edited by: Weng, Q. 297-330. New York: CRC Press. Ined
10. Henderson, F.M. and Xia, Z. 1997. SAR applications in human settlement detection, population estimation and urban land use pattern analysis: a status report. IEEE Transactions on Geoscience and Remote Sensing, 35(1): 79-85.
11. Hurd, J.D. and Civco, D.L. 2004. "Temporal characterization of impervious surfaces for the state of Connecticut". In ASPRS annual conference proceedings, 23--28 May 2004, Denver[], CO: CD-ROM. InASPRS Publications
12. Jensen, J.R. 2007. Introductory digital image processing: a remote sensing perspective. 3rd, 501-505. London: Pearson Education Ltd.
13. Jiang, L. 2009. Synergistic use of optical and InSAR data for urban impervious surface mapping: a case study in Hong Kong. International Journal of Remote Sensing, 30(11): 2781-2796.
14. Linderman, M. 2004. Using artificial neural networks to map the spatial distribution of understorey bamboo from remote sensing data. International Journal of Remote Sensing, 25(9): 1685-1700.
15. Lombardo, P. 2003. Optimum model-based segmentation techniques for multifrequency polarimetric SAR images of urban areas. IEEE Transactions on Geoscience and Remote Sensing, 41(9): 1959-1975.
16. Lu, D., Weng, Q. and Li, G. 2006. Residential population estimation using a remote sensing derived impervious surface approach. International Journal of Remote Sensing, 27(16): 3553-3570.
17. Ray, T.W. and Murray, B.C. 1996. Nonlinear spectral mixing in desert vegetation. Remote Sensing of Environment, 55: 59-64.
18. Ridd, M.K. 1995. Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote-sensing-comparative anatomy for cities. International Journal of Remote Sensing, 16(12): 2165-2185.
19. Soergel, U. 2010. Radar remote sensing of urban areas, 133-159. Heidelberg: Springer.
20. Stasolla, M. and Gamba, P. 2008. Spatial indexes for the extraction of formal and informal human settlements from high-resolution SAR images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1(2): 98-106.
21. Tison, C. 2004. A new statistical model for Markovian classification of urban areas in high-resolution SAR images. IEEE Transactions on Geoscience and Remote Sensing, 42(10): 2046-2057.
22. Tupin, F. and Roux, M. 2003. Detection of building outlines based on the fusion of SAR and optical features. ISPRS Journal of Photogrammetry & Remote Sensing, 58: 71-82.
23. Tupin, F. and Roux, M. 2005. Markov random field on region adjacency graph for the fusion of SAR and optical data in radargrammetric applications. IEEE Transactions on Geoscience and Remote Sensing, 43(8): 1920-1928.
24. Weng, Q. 2001. Modeling urban growth effect on surface runoff with the integration of remote sensing and GIS. Environmental Management, 28(6): 737-748.
25. Weng, Q. and Hu, X. 2008. Medium spatial resolution satellite imagery for estimating and mapping urban impervious surfaces using LSMA and ANN. IEEE Transactions on Geoscience and Remote Sensing, 46(8): 2397-2406.
26. Weng, Q., Hu, X. and Liu, H. 2009. Estimating impervious surfaces using linear spectral mixture analysis with multitemporal ASTER images. International Journal of Remote Sensing, 30(18): 4807-4830.
27. Weng, Q., Lu, D. and Liang, B. 2006. Urban surface biophysical descriptors and land surface temperature variations. Photogrammetric Engineering & Remote Sensing, 72(11): 1275-1286.
28. Wu, C. 2004. Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery. Remote Sensing of Environment, 93: 480-492.
29. Wu, C. and Murray, A.T. 2003. Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment, 84: 493-505.
30. Wu, C. and Yuan, F. 2007. Seasonal sensitivity analysis of impervious surface estimation with satellite imagery. Photogrammetric Engineering & Remote Sensing, 73(12): 1393-1401.
31. Xu, H. 2010. Analysis of impervious surface and its impact on urban heat environment using the Normalized Difference Impervious Surface Index (NDISI). Photogrammetric Engineering & Remote Sensing, 76(5): 557-565.
32. Yang, F., Matsushita, B. and Fukushima, T. 2010. A pre-screened and normalized multiple endmember spectral mixture analysis for mapping impervious surface area in Lake Kasumigaura Basin, Japan. ISPRS Journal of Photogrammetry and Remote Sensing, 64(5): 479-490.
33. Yang, L. 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: 230-240.
34. Yang, L. 2009. Quantifying sub-pixel urban impervious surface through fusion of optical and in SAR imagery. GIScience & Remote Sensing, 46(2): 161-171.
35. Zhang, Y. 2008. Regional integrated experiments on air quality over Pearl River Delta 2004 (PRIDE-PRD2004): overview. Atmospheric Environment, 42: 6157-6173.