The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat 7 ETM+ data

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Abstract:

The relationship between land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) associated with urban land-use type and land-use pattern is discussed in the City of Shanghai, China using data collected by the Enhanced Thematic Mapper Plus (ETM+) and aerial photographic remote sensing system. There is an apparent correlation between LST and NDVI from the visual interpretation of LST and NDVI contrasts. Mean LST and NDVI values associated with different land-use types are significantly different. Multiple comparisons of mean LST and NDVI values associated with pairings of each land-use type are also shown to be significantly different. The result of a regressive analysis shows an inverse correlation relationship between LST and NDVI within all land-use polygons, the same to each land-use type, but correlation coefficients associated with land-use types are different. An analysis on the relationship between LST, NDVI and Shannon Diversity Index (SHDI) shows a positive correlation between LST and SHDI and a negative correlation between NDVI and SHDI. According to the above results, LST, SHDI and NDVI can be considered to be three basic indices to study the urban ecological environment and to contribute to further validation of the applicability of relatively low cost, moderate spatial resolution satellite imagery in evaluating environmental impacts of urban land function zoning, then to examine the impact of urban land-use on the urban environment in Shanghai City. This provides an effective tool in evaluating the environmental influences of zoning in urban ecosystems with remote sensing and geographical information systems.

Keywords: LST; NDVI; SHDI; Urban land use

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160500306906

Affiliations: 1: Department of Land Management, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310029, People's Republic of China 2: Department of Geography, Key Lab of GIScience, Ministry of Education, East China Normal University, Shanghai 200062, People's Republic of China

Publication date: January 1, 2007

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