Land surface temperature and its impact factors in Western Sichuan Plateau, China

Abstract

The understanding influence of multiple factors variations on land surface temperature (LST) remains elusive. LST was retrieved by the atmospheric correction algorithms. Based on the correlation coefficients, stepwise regression analysis was developed to examine how multiple factors variability led to LST variations. The differences in LST between impact factors vary depending on time in a day. The elevation and land use types significantly affect the LST in sunny slope or shadow areas has a significantly quadratic curve correlation or a negative linear correlation with it, the influence of slope and aspect is not very significant. LST for forestland, grassland and bare land in the sunny slope and shadow area was the cubic polynomial related to its elevation. Normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) effectively express LST in mountainous. LST and NDMI or NDVI have a significantly negative correlation, NDMI is more effective and more applicable for the expression of LST.

Keywords:

• Land surface temperature (LST)
• terrain factors
• NDVI
• NDMI
• remote sensing (RS)

Acknowledgements

The authors thank the editors and anonymous referees for their valuable comments and suggestions, which helped improve the manuscript. Landsat data was acquired from the USGS EROS Data Center, the Institute of Remote Sensing and Digital Earth, and Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences. The funding sources had no involvement in the collection, analysis and interpretation of data; the writing of the report; and the decision to submit the article for publication.