传统的地震统计学多局限于规则的统计范围，或是需要较多的人工干预，本文引入了基于地理信息系统的空间统计学方法，将其应用于地震空间统计中，能够高效、快速地挖掘含有地理信息的各要素之间的相互联系。本文以川滇地区2019年发生的M_L≥1.0地震数量的空间统计为例，详述了对地震数据进行空间统计的流程。统计结果表明，0.5°×0.5°是最适合该地震数据集空间统计的矩形范围，发生地震次数最多的区域位于四川盆地西南缘的威远-长宁地区，此外龙门山断裂带、龙门山断裂带与鲜水河-小江断裂系交汇处、丽江-小金河断裂沿线以及滇南地区均为地震发生次数较高的区域。此外，还利用该方法计算了2015—2019年全国各省地震能量释放情况。结果显示在该时间段内，释放地震能量总量最多的省份为四川省，新疆维吾尔自治区和西藏自治区次之，而台湾地区陆地区域、四川省、西藏自治区等地区具有较高的每万平方公里地震能量释放量和每万人地震能量承受量。并通过上述应用实例，探索了地理信息系统在地震统计领域的初步应用。

Traditional seismic statistics are usually limited to regular statistical scope, or require a lot of manual intervention somehow. To solve this problem, in this paper we introduce the spatial statistics method based on geographic information system, and apply it to seismic spatial statistics, which can efficiently and rapidly excavate the interrelation among various elements containing geographic information. Take a case-study to demonstrate the basic and detailed technological process of spatial statistics, we analyzed the seismic data(M_L ≥ 1.0) of the Sichuan and Yunnan region. The results show that 0.5°×0.5° is the most suitable scale size for this case-study, and the region with most earthquake events in 2019 is the Weiyuan-Changning region on the southwestern margin of the Sichuan Basin. In addition, the Longmenshan region, junction area of the Longmenshan fault zone and Xianshuihe-Xiaojiang fault zones, Lijiang-Xiaojinhe region, and the southern margin of the Yunnan Province have relative high rate of earthquake occurrence in 2019. Besides, we applied the method to statistically study the earthquake energy released of every province during 2015-2019. We found that the Sichuan Province has released the largest amount of seismic energy, Xinjiang and Xizang Autonomous Region has gone through the second largest amount energy. Besides the Sichuan Province, the land area of Taiwan, Sichuan Province and Xizang Autonomous Region have experienced very high seismic energy per 10⁴ square kilometers by area or per 10⁴ people by population. Through above two case-studies we show the preliminary application of GIS in the earthquake statistical analysis.

P315

地震动力学国家重点实验室开放基金项目（LED2019B08）资助