RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2020, Vol. 29 >> Issue (1): 200-210.doi: 10.11870/cjlyzyyhj202001018

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Multi-scale Analysis of Main Factors of Summer Thermal Field in Wuhan Based on POI Data

WU Qiong1, GONG Jian1.2, YANG Jian-xin1   

  1. (1. College of Public Administration, China university of Geosciences, Wuhan 430074, China;2. Legal Evaluation Laboratory 
    of the Ministry of Natural Resources, Wuhan 430074, China)
  • Online:2020-01-20 Published:2020-03-24

Abstract: Clarifying the effects and relative importance of surface parameters on Land Surface Temperature (LST) at different scales can provide a reference for the adjustment and optimization of urban ecological space layout. We used Point of Interest (POI) data to characterize the micro-scale human activity intensity and use the atmospheric correction method to invert the LST of the outer ring region of Wuhan in the summer of 2016. Using Method of Ordinary Least Squares, we quantitatively analyzed the relationships between LST to POI, Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (MNDWI) at 500 m, 1 000 m and 2 000 m scales, then further distinguished the relative importance of variables to LST. The results show that: (1) POI is significantly positively correlated with LST and the correlation coefficient increases with the increase of scale at three scales. NDVI and MNDWI are significantly negatively correlated with LST. The correlation coefficient between NDVI and LST decreases with the increase of scale. The correlation coefficient between MNDWI and LST increases with the increase of scale. (2)The thermal field in Wuhan is the result of the joint action of natural ecological environment and human activities; (3) The interpretation of LST by POI occupies a large relative weight and is the most important factor in the formation of thermal field. The results show that POI has the greatest relative contribution to the interpretation of LST, in the study of urban thermal field influencing factors, POI can be used to reflect the intensity of human activity and has a good complement to remote sensing information.

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