Multisource data evaluation of heat risk in Shanghai

Impact of high temperatures on natural ecology and human life is becoming increasingly serious．How to accurately quantify and evaluate urban heat risk has become a major focus. In this study, remote sensing data, socio-economic data, natural ecological data and other multi-source data were analyzed to develop a heat risk assessment index system and heat risk evaluation model from 4 dimensions (hazard, exposure, vulnerability and adaptability)．The distribution characteristics of heat risk level and spatial heterogeneity rules were examined, risk spatial regions and disaster types across Shanghai were identified．The 4-dimensional indices showed significant spatial agglomeration in Shanghai: heat hazard index gradually decreased from southwest to northeast and then increased; the three indices of heat exposure, vulnerability and adaptability all showed "center-periphery" characteristics．The heat risk in Shanghai was found to be mainly at low and moderate levels, gradually decreasing from southwest to northeast and then increasing, with significant spatial agglomeration．Hottest spots were found in northeast and southwest of Shanghai, coldest spots were concentrated in the east．The highest value in heat risk index (HRI : 1.80) was found in Changning District in central city, the lowest value (0.55) in Pudong New District．The area proportion of different disaster causing types was: two-dimensional leading type (45.89%) > single dimensional leading type (29.32%) > triple dimensional leading type (13.97%) > comprehensive leading type (8.66%). Regarding the area proportion of different disaster causing types, the largest area was the leading type of hazard and insufficient adaptability (16.10%), the smallest was the leading type of vulnerability (0.13%)．This study provides reference for more scientific prediction and early warning of heat disaster, and for measures and schemes of disaster prevention and mitigation．