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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (4) : 122-129     DOI: 10.6046/zrzyyg.2022292
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Assessing the susceptibility of slope geological hazards based on multi-source heterogeneous data: A case study of Longgang District, Shenzhen City
WANG Ning1(), JIANG Decai1,2,3, ZHENG Xiangxiang1,2,4, ZHONG Chang1,5()
1. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000,China
4. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
5. College of Intelligence Science and Technology,National University of Defense Technology, Changsha 410073, China
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Abstract  

This study aims to investigate the fundamental facts concerning slope geological hazards in Longgang District, Shenzhen City, as well as the distributions of disaster-prone zones in the district. Based on the multi-source remote sensing satellite data, this study interpreted the slope geological hazards using the expert interpretation method on a geological hazard interpretation platform. Furthermore, some interpreted geological hazards were verified through field verification combined with Baidu Street View data. Finally, the distributions of zones susceptible to slope geological hazards in Longgang District were determined using the information value method, with the slope height, slope gradient, rainfall, surface lithology, and land cover as assessment factors. Additionally, existing geological hazard sites were superimposed with the susceptibility assessment results for analysis, yielding completely consistent results. This confirms the effectiveness of the method used in this study for assessing the susceptibility of slope geological hazards, as well as the accuracy of remote sensing interpretation of slope geological hazards.
Keywords identification of geological hazards      time-series InSAR      susceptibility assessment      information value model     
ZTFLH:  TP79  
Issue Date: 21 December 2023
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Ning WANG
Decai JIANG
Xiangxiang ZHENG
Chang ZHONG
Cite this article:   
Ning WANG,Decai JIANG,Xiangxiang ZHENG, et al. Assessing the susceptibility of slope geological hazards based on multi-source heterogeneous data: A case study of Longgang District, Shenzhen City[J]. Remote Sensing for Natural Resources, 2023, 35(4): 122-129.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022292     OR     https://www.gtzyyg.com/EN/Y2023/V35/I4/122
Fig.1  Technical route for evaluating the susceptibility of slope geological hazards
序号 类型 光学影像特征
1 滑坡 影像上表现为圈椅状地形、双沟同源、坡体后部出现平台洼地,与周围河流阶地、构造平台或与风化差异平台不一致的大平台地形,“大肚子”斜坡、不正常河流弯道等
2 崩塌 影像上一般呈现白色调或者浅色调,在崩塌体上部色调较亮,下部亮度稍微较暗;对于新发生的崩塌,呈现出新鲜的结构面,对光谱具有加强的反射能力,使得影像呈浅色调
3 泥石流 影像具有树枝状、痕状冲沟,植被镶嵌其中,呈条状或者零星状,真彩色影像中颜色为绿、紫红相间,绿色植被部分似突起的“山脊”
4 不稳定斜坡 无明显特征,主要参考InSAR形变监测数据
Tab.1  Optical image characteristics of geological hazards
Fig.2  SBAS-InSAR processing
传感器名称 成像模式 轨道方向 波长/cm 分辨率(Az×Rg)①/m 入射角/(°) 获取日期
Sentinel-1A TOPS模式 升轨 5.6 13.9×3.7 38.94 20181016—20191210
20190812—20200830
Tab.2  Basic parameters of Sentinel-1A dataset
Fig.3  InSAR monitoring of surface deformation and interpretation results of slope geological hazards
Fig.4  Slope geological hazard interpretation platform
Fig.5  Distribution of slope geological hazards by optical remote sensing interpretation
Fig.6  Street view verification of slope geological hazards
Fig.7  Field verification of slope geological hazards
坡高分档/m 面积/ km2 隐患点数/个 信息量值 坡度分档/度 面积/km2 隐患点数/个 信息量值
[0,30] 130.51 2 -2.57 [0,5] 148.07 3 -1.60
(30,50] 188.85 7 -1.15 (5,10] 104.88 10 -0.15
(50,70] 43.11 13 1.01 (10,15] 55.70 12 0.67
(70,100] 10.87 12 2.31 (15,20] 39.50 9 0.70
(100,120] 5.09 6 2.46 (20,25] 22.26 6 0.80
>120 10.07 3 1.08 (25,30] 11.60 2 0.54
土地覆被 面积/km2 隐患点数/个 信息量值 (30, 90) 6.46 1 0.43
耕地 2.93 2 1.88 地表岩性 面积/km2 隐患点数/个 信息量值
林地 69.68 13 0.51 土体 99.67 8 -0.35
草地 18.75 6 0.72 坚硬的块状岩组 83.52 3 -1.02
灌木林 60.51 5 -0.44 坚硬的层状岩组 8.04 3 0.90
人造地表 226.15 17 -0.31 坚硬的碎屑岩岩组 41.76 2 -1.43
水体 — — -1.50 较坚硬的块状岩组 73.87 18 0.82
降雨量/mm 面积/km2 隐患点数/个 信息量值 较坚硬的碎屑岩岩组 68.19 9 0.27
[1 588, 1 732] 23.59 1 -0.86 较软的块状岩组 2.03 0 -1.50
(1 732, 1 808] 93.58 7 -0.45 较软的层状岩组 3.77 0 -1.50
(1 808, 1 872] 111.14 10 -0.21 较软的碎屑岩岩组 6.85 0 -1.50
(1 872, 1 946] 135.93 17 0.15
(1 946, 2 071] 23.54 8 1.08
Tab.3  Information content calculation results
Fig.8  Assessment results of slope geological hazards
低易发区 中易发区 高易发区 极高易发区 总计
已发灾害
数量/个		 1 8 26 4 39
面积/km2 136.53 107.07 129.50 17.55 390.65
面积占
比/%		 34.95 27.41 33.15 4.49 100
Tab.4  Statistics on the area of susceptible zones and the distribution of occurred disasters
Fig.9  Distribution of slope geological hazards
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