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利用哨兵1A/B卫星对2015年至2022年中国广东省的非构造地质灾害进行监测

Non-Tectonic Geohazards of Guangdong Province, China, Monitored Using Sentinel-1A/B from 2015 to 2022.

作者信息

Liu Jincang, Fu Zhenhua, Zhou Lipeng, Feng Guangcai, Wang Yilin, Luo Wulinhong

机构信息

Surveying and Mapping Institute Lands and Resource Department of Guangdong Province, Guangzhou 510630, China.

The Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Guangzhou 510670, China.

出版信息

Sensors (Basel). 2024 Aug 22;24(16):5449. doi: 10.3390/s24165449.

Abstract

Guangdong Province, home to 21 cities and a permanent population of 127.06 million people, boasts the largest provincial economy in China, contributing 11.76% to the national GDP in 2023. However, it is prone to geological hazards due to its geological conditions, extreme weather, and extensive human activities. Geohazards not only endanger lives but also hinder regional economic development. Monitoring surface deformation regularly can promptly detect geological hazards and allow for effective mitigation strategies. Traditional ground subsidence monitoring methods are insufficient for comprehensive surveys and rapid monitoring of geological hazards in the whole province. Interferometric Synthetic Aperture Radar (InSAR) technology using satellite images can achieve wide-area geohazard monitoring. However, current geological hazard monitoring in Guangdong Province based on InSAR technology lacks regional analysis and statistics of surface deformation across the entire province. Furthermore, such monitoring fails to analyze the spatial-temporal characteristics of surface deformation and disaster evolution mechanisms by considering the local geological features. To address these issues, current work utilizes Sentinel-1A/B satellite data covering Guangdong Province from 2015 to 2022 to obtain the wide-area surface deformation in the whole province using the multi-temporal (MT) InSAR technology. Based on the deformation results, a wide-area deformation region automatic identification method is used to identify the surface deformation regions and count the deformation area in each city of Guangdong Province. By analyzing the results, we obtained the following findings: (1) Using the automatic identification algorithm we identified 2394 deformation regions. (2) Surface subsidence is concentrated in the delta regions and reclamation areas; over a 4 cm/year subsidence rate is observed in the hilly regions of northern Guangdong, particularly in mining areas. (3) Surface deformation is closely related to geological structures and human activities. (4) Sentinel-1 satellite C-band imagery is highly effective for wide-area geological hazard monitoring, but has limitations in monitoring small-area geological hazards. In the future, combining the high-spatial-temporal-resolution L-band imagery from the NISAR satellite with Sentinel-1 imagery will allow for comprehensive monitoring and early warning of geological hazards, achieving multiple geometric and platform perspectives for geological hazard monitoring and management in Guangdong Province. The findings of this study have significant reference value for the monitoring and management of geological disasters in Guangdong Province.

摘要

广东省下辖21个城市,常住人口1.2706亿,是中国省级经济体量最大的省份,2023年对全国GDP的贡献率达11.76%。然而,由于其地质条件、极端天气和广泛的人类活动,该省容易发生地质灾害。地质灾害不仅危及生命,还阻碍区域经济发展。定期监测地表变形能够及时发现地质灾害并制定有效的减灾策略。传统的地面沉降监测方法不足以对全省的地质灾害进行全面调查和快速监测。利用卫星图像的干涉合成孔径雷达(InSAR)技术可以实现广域地质灾害监测。然而,目前广东省基于InSAR技术的地质灾害监测缺乏对全省地表变形的区域分析和统计。此外,这种监测未能结合当地地质特征分析地表变形的时空特征和灾害演化机制。为解决这些问题,当前工作利用2015年至2022年覆盖广东省的哨兵-1A/B卫星数据,采用多时相(MT)InSAR技术获取全省广域地表变形情况。基于变形结果,运用广域变形区域自动识别方法识别地表变形区域并统计广东省各城市的变形面积。通过分析结果,我们得到以下发现:(1)使用自动识别算法,我们识别出2394个变形区域。(2)地面沉降集中在三角洲地区和围垦区;粤北山区沉降速率超过4厘米/年,特别是在矿区。(3)地表变形与地质构造和人类活动密切相关。(4)哨兵-1卫星C波段图像对广域地质灾害监测非常有效,但在监测小面积地质灾害方面存在局限性。未来,将NISAR卫星的高时空分辨率L波段图像与哨兵-1图像相结合,将能够对地质灾害进行全面监测和预警,实现对广东省地质灾害监测和管理的多几何和平台视角。本研究结果对广东省地质灾害的监测和管理具有重要参考价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f1e5/11359379/ac98fb174bd8/sensors-24-05449-g001.jpg

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