Analysis of remotely-sensed ecological indexes' influence on urban thermal environment dynamic using an integrated ecological index: a case study of Xi’an, China

ABSTRACT

The spatio-temporal pattern of surface ecological status affects urban thermal environment distribution significantly. Urban thermal pattern, however, is a complicated physical phenomenon involving a series of terrestrial environmental parameters. Thus, it is insufficient to employ only one ecological parameter for depicting the variation of land surface temperature (LST). This paper begins with the analysis of four ecological parameters' influence on LST using regression analysis, based on 24 Landsat images which cover Xi’an of China from 1992 to 2014. These four parameters include greenness degree (i.e. the soil adjusted vegetation index, SAVI), soil moisture degree (i.e. the normalized difference moisture index, NDMI), dryness degree (i.e. the normalized difference soil index, NDSI) and resident aggregation degree (i.e. the normalized difference build-up index, NDBI). Besides, contribution intensity index was introduced to investigate the contribution effect of four ecological parameters on LST, and a new ecological index, integrated ecological index (IEI), was founded using the principal component analysis technique to integratedly represent its spatial and mathematical correlations with LST. Results indicate that four ecological parameters all possessed pronounced performance in impacting LST pattern in all dates: SAVI and NDMI were found to be correlated negatively with LST, whereas NDBI and NDSI correlated positively with LST. Additionally, SAVI had a profound impact on LST distribution compared with the other three parameters, and there was the biggest heating contribution in the lowest SAVI category. Further finding suggests that IEI as a new ecological index can be used to integratedly estimate the spatio-temporal change of LST, manifesting a negative correlation with LST. Our study thinks that the comprehensive characterization of surface ecological status is conducive to benefit us to better understand the spatio-temporal mechanism of thermal environment and ecosystem and to help urban decision-makers to execute effective conservation policies for the ecosystem.

Acknowledgments

This research has been funded by grants from the National Natural Science Foundation of China (No. 41071271) and the Shaanxi Province Natural Science Foundation, China (No. 2015JM4132). In addition, the authors would like to acknowledge the United States Geological Survey Center (http://glovis.usgs.gov/) for providing remotely-sensing data as well as the Chinese meteorological data sharing network (http://data.cma.cn/) and National Aeronautics and Space Administration (https://www.nasa.gov/) for providing meteorological verification data, and the National Bureau of Statistics of China (http://www.stats.gov.cn/) and the Bureau of Statistics of Xi’an (http://tjj.xa.gov.cn/ptl/index.html) for providing the socio-economic data. The authors are also grateful to the anonymous reviewers and the editors for valuable comments and suggestions for improving the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under grant number 41071271 through the National Natural Science Fund Committee of the People’s Republic of China, and the Shaanxi Province Natural Science Foundation, China under grant number 2015JM4132 through the Education Department of Shaanxi Provincial Government, China, and the Strategic Priority Research Program of Chinese Academy of Sciences, China under grant number XDA2004030201 through Chinese Academy of Sciences, China.