融合InSAR与信息量-层次分析耦合模型的西宁市地质灾害易发性评价

doi:10.13474/j.cnki.11-2246.2023.0358

测绘通报 ›› 2023, Vol. 0 ›› Issue (12): 51-56,75.doi: 10.13474/j.cnki.11-2246.2023.0358

• 学术研究 • 上一篇

融合InSAR与信息量-层次分析耦合模型的西宁市地质灾害易发性评价

胡祥祥^1,2, 明璐璐³, 吴涛⁴, 刘宝康^1,2, 庞栋栋^1,2, 尹继鑫⁵, 宋宝⁶, 柯福阳^7,8

1. 天水师范学院资源与环境工程学院, 甘肃天水 741001;
2. 甘肃正昊地星遥感科技中心, 甘肃天水 741001;
3. 南京信息工程大学遥感与测绘工程学院, 江苏南京 210044;
4. 中共铜鼓县委组织部, 江西宜春 336200;
5. 西宁市测绘院, 青海西宁 810000;
6. 北京理工大学自动化学院, 北京 100081;
7. 南京信息工程大学软件学院, 江苏南京 210044;
8. 南京信息工程大学无锡研究院, 江苏无锡 214000

收稿日期:2023-08-21 发布日期:2024-01-08
通讯作者: 柯福阳。E-mail:ke.fuyang@qq.com
作者简介:胡祥祥(1996-),男,硕士,主要研究方向为地质灾害。E-mail:837531464@qq.com
基金资助:
江苏省自然科学基金(BK20211037);2022年度第六期江苏省“333人才”培养支持资助(BRA2022042);江苏省科技项目社发项目(BE2021622)

Evaluation of geological hazard vulnerability in Xining city based on InSAR and informativeness-hierarchical analysis coupled modeling

HU Xiangxiang^1,2, MING Lulu³, WU Tao⁴, LIU Baokang^1,2, PANG Dongdong^1,2, YIN Jixin⁵, SONG Bao⁶, KE Fuyang^7,8

1. School of Resource and Environmental Engineering, Tianshui Normal University, Tianshui 741001, China;
2. Gansu Zhenghao Satellite Remote Sensing Scvience and Technology Center, Tianshui 741001, China;
3. School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;
4. Organization Department of CPC Tonggu County Committee, Yichun 336200, China;
5. Xining Surveying and Mapping Institute, Xining 810000, China;
6. School of Automation, Beijing Institute of Technology, Beijing 100081, China;
7. School of Software, Nanjing University of Information Science & Technology, Nanjing 210044, China;
8. Wuxi Research Institute of Nanjing University of Information Engineering, Wuxi 214000, China

Received:2023-08-21 Published:2024-01-08

摘要/Abstract

摘要： 为准确高效地评估西宁市的滑坡易发区,为西宁市滑坡灾害预警及防治提供参考,本文首先采用SBAS-InSAR技术获取2018—2022年5年间西宁市地表形变信息;然后将获取的形变信息划分量级,作为易发性评价模型的一个评价因子,结合高程、坡度、地层岩性等7个评价因子,基于信息量-层次分析法耦合模型对研究区滑坡易发性进行了定量评价;最后利用已有地质灾害点数据集对评价结果进行验证。结果表明,本文所得的地质灾害易发性评价结果与已有地质灾害点的分布较为吻合,已有记录的地质灾害点聚集的区域绝大多数位于本文所划分区的中高易发区内。根据ROC曲线精度结果,耦合模型AUC值为0.91。可见,利用本文提出的方法进行灾害易发性评价是可行的,研究结果可为西宁市滑坡综合防治措施提供依据。

关键词: 信息量模型, 层次分析法, SBAS-InSAR, 易发性评价

Abstract: To accurately and efficiently evaluate the landslide susceptibility area within the territory, it provides a reference for landslide disaster warning and prevention in Xining city. In this paper, SBAS-InSAR technology is used to obtain the surface deformation information of Xining city during the five years of 2018—2022. The deformation information obtained is divided into magnitudes as an evaluation factor of the susceptibility evaluation model, which is combined with seven evaluation factors, such as elevation, slope, and stratigraphic lithology, to quantitatively evaluate the susceptibility of landslides in the study area based on the informativeness-hierarchical analysis method. Finally, the evaluation results were validated using the existing geohazard point data sets. The results show that the evaluation results of geohazard susceptibility obtained in this paper are more consistent with the distribution of existing geohazard sites, and most of the areas where the recorded geohazard sites are gathered are located in the medium-high susceptibility zone of the location delineated in this paper. According to the ROC curve accuracy results, the coupled model AUC value is 0.91.It is feasible to utilize the method proposed in this paper to carry out disaster susceptibility evaluation, and the results of the study can provide a basis for the comprehensive prevention and control measures of landslides in Xining city.

Key words: information method, analytic hierarchy process, SBAS-InSAR, susceptibility evaluation

中图分类号:

P237

胡祥祥, 明璐璐, 吴涛, 刘宝康, 庞栋栋, 尹继鑫, 宋宝, 柯福阳. 融合InSAR与信息量-层次分析耦合模型的西宁市地质灾害易发性评价[J]. 测绘通报, 2023, 0(12): 51-56,75.

HU Xiangxiang, MING Lulu, WU Tao, LIU Baokang, PANG Dongdong, YIN Jixin, SONG Bao, KE Fuyang. Evaluation of geological hazard vulnerability in Xining city based on InSAR and informativeness-hierarchical analysis coupled modeling[J]. Bulletin of Surveying and Mapping, 2023, 0(12): 51-56,75.

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融合InSAR与信息量-层次分析耦合模型的西宁市地质灾害易发性评价

Evaluation of geological hazard vulnerability in Xining city based on InSAR and informativeness-hierarchical analysis coupled modeling

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