Study on the urban heat island effects and its relationship with surface biophysical characteristics using MODIS imageries

Geo-Spatial Information Science

Volumn 13, Issue 1, 2010, Pages 1-7

  Zeng, Yongnian ^a   Huang, Wei ^a   Zhan, F ^b   Zhang, Honghui ^a   Liu, Huimin ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b TEXAS STATE UNIVERSITY   (United States)

Author keywords

Biophysical indicators; Changsha zhuzhou xiangtan area; China; Modis image; Urban heat island

Indexed keywords

EID: 84977837770     PISSN: 10095020     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11806-010-0204-2     Document Type: Article

References (22)

1. Kalnay, E, and Cai, M. 2003. Impact of urbanization and land-use change on climate [J]. Nature, 423:528–531.
2. Roth, M. 2002. “ Effects of cities on local climates[C] ”. In Proceedings of Workshop of Institute for Global Environment Studies/Asia-Pacific Network (IGES/APN) Megacity Project, Kitakyushu, Japan
3. Zhou, L, Dickinson, R, Tian, Y. 2004. Evidence for a significant urbanization effect on climate in China [J]. Proceedings of the National Academy of Sciences of the United States of America, 101 (26):9540–9544.
4. Voogt, J A, and Oke, T R. 2003. Thermal remote sensing of urban climates [J]. Remote Sensing of Environment, 86:370–384.
5. Seto, C K, and Fragkias, M. 2005. Quantifying spatiotemporal patterns of urban land-use change in four cities of China with time series landscape metric [J]. Landscape Ecology, 20:871–888.
6. Klysik, K, and Fortuniak, K. 1999. Temporal and spatial characteristics of the urban heat island of Lodz, Poland[J]. Atmospheric Environment, 33:3885–3895.
7. Streutker, D R. 2003. Satellite-measured growth of the urban heat island of Houston, Texas [J]. Remote Sensing of Environment, 85:282–289.
8. Roth, M, Oke, T R, and Emery, W J. 1989. Satellite derived urban heat islands from three coastal cities and the utilisation of such data in urban climatology [J]. International Journal of Remote Sensing, 10:1699–1720.
9. Gallo, K P, and Owen, T W. 2002. A sampling strategy for satellite sensor based assessment of the urban heat-island bias [J]. International Journal of Remote Sensing, 23:1935–1939.
10. Weng, Q. 2003. Fractal analysis of satellite-detected urban heat island effect [J]. Photogrammetric Engineering and Remote Sensing, 69:555–566.
11. Carlson, T N, Gillies, R R, and Perry, E M. 1994. A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover[J]. Remote Sensing Reviews, 9:161–173.
12. Weng, Q, Lu, D, and Schubring, J. 2004. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies [J]. Remote Sensing of Environment, 89:467–483.
13. Arnold, C L, and Gibbons, C J. 1996. Impervious surface coverage:the emergence of a key environmental indicator[J]. Journal of the American Planning Association, 62:243–258.
14. Yuan, F, and Bauer, M. 2007. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery [J]. Remote Sensing of Environment, 106:375–386.
15. Lu, D, and Weng, Q. 2004. Spectral mixture analysis of the urban landscape in indianapolis with Landsat ETM+ imagery [J]. Photogrammetric Engineering and Remote Sensing, 70:1053–1062.
16. Lu, D, and Weng, Q. 2006. Use of impervious surface in urban land-use classification[J]. Remote Sensing of Environment, 102:146–160.
17. Wu, C. 2004. Normalized spectral mixture analysis for monitoring urban composition using ETM+ image [J]. Remote Sensing of Environment, 89:467–483.
18. Wu, C, and Murray, T. 2003. Estimating impervious surface distribution by spectral mixture analysis [J]. Remote Sensing of Environment, 84:493–505.
19. Mao, K, and Qin, Z. 2005. A practical split-window algorithm for retrieving land-surface temperature from MODIS data [J]. International Journal of Remote Sensing, 26 (15):3181–3204.
20. Qin, Z, and Karnieli, A. 1999. Progress in the remote sensing of land surface temperature and ground emissivity using NOAA-AVHRR Data[J]. International Journal of Remote Sensing, 20:2367–2393.
21. Kaufman, Y J, and Gao, B C. 1992. Remote sensing of water vapor in the near IP from EOS/MODIS [J]. IEEE Transactions on Geoscience and Remote Sensing, 30 (5):871–884.
22. Zha, Y, Gao, J, and Ni, S. 2003. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery[J]. International Journal of Remote Sensing, 24 (3):583–594.