Paper
1 September 2005 Relationship between NDVI and the urban heat island effect in Beijing area of China
Weidong Liu, Chongping Ji, Xiaoyan Jiang, Jiqin Zhong
Author Affiliations +
Abstract
The Normalized Difference Vegetation Index (NDVI) and the thermal infrared information of remote sensing have been widely used to study urban climate. In this study, the time series of 8 km-spatial-resolution NDVI images obtained from the Pathfinder NOAA-AVHRR Land (PAL) dataset in the period of 1982 to 2000 was used to assess the trends of NDVI in Beijing both urban and rural areas. The relationship between the NDVI variation and urban heat island (UHI) intensity was investigated. And the results showed that the NDVI in Beijing urban region decreased with time and the NDVI in Beijing rural region had no obvious change. The annual UHI intensity increased with the increasing of NDVI difference between urban and rural regions. Meanwhile, the data of Landsat Enhanced Thematic Mapper Plus (ETM +) combined with classification-based surface emissivity in Beijing area were utilized to estimate land surface temperature (LST). The relationship between LST and NDVI derived from ETM+ showed an obviously negative correlation. In general, in Beijing area the distribution of NDVI directly defined the distribution of LST. In the urban region the NDVI was small and LST was high, while in the rural region the NDVI was large and LST was small. The derived LST from ETM+ was also compared with measured air temperature at weather stations. There was an obvious correlation between surface temperature and air temperature. This indicates that the surface temperature derived from Landsat can describe the distribution of UHI.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Weidong Liu, Chongping Ji, Xiaoyan Jiang, and Jiqin Zhong "Relationship between NDVI and the urban heat island effect in Beijing area of China", Proc. SPIE 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II, 58841R (1 September 2005); https://doi.org/10.1117/12.628854
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Cited by 2 scholarly publications.
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KEYWORDS
Vegetation

Climatology

Earth observing sensors

Landsat

Temperature metrology

Environmental sensing

Remote sensing

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