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The intensity and frequency of extreme heat events are increasing globally, which has a great impact on resident health, social life, and ecosystems. Detailed knowledge of the spatial heat pattern during extreme heat events is important for coping with heat disasters. This study aimed to monitor the characteristics of the spatial pattern during the 2013 heat wave in the Yangtze River Delta (YRD), China, based on the remote sensing estimated gridded air temperature (Ta). Based on the land surface temperature (Ts), normalized difference vegetation index (NDVI), built-up area, and elevation derived from multi-source satellite data, the daily maximum air temperature (Ta_max) during the heat wave was mapped by the random forest (RF) algorithm. Based on the remotely sensed Ta, heat intensity index (HII) was calculated to measure the spatial pattern of heat during this heat wave. Results indicated that most areas in the YRD suffered from extreme heat, and the heat pattern also exhibited obvious spatial heterogeneity. Cities located in the Taihu Plain and the Hangjiahu Plain generally had high HII values. The northern plain in the YRD showed relatively lower HII values, and mountains in the southern YRD showed the lowest HII values. Heat proportion index (HPI) was calculated to qualify the overall heat intensity of each city in the YRD. Wuxi, Changzhou, and Shanghai showed the highest HPI values, indicating that the overall heat intensities in these cities were higher than others. Yancheng, Zhoushan, and Anqing ranked last. This study provides a good reference for understanding the pattern of heat during heat waves in the YRD, which is valuable for heat wave disaster prevention.

Study on the Spatial Pattern of an Extreme Heat Event by Remote Sensing: A Case Study of the 2013 Extreme Heat Event in the Yangtze River Delta, China