-
摘要:
识别地质灾害聚集的热点区及驱动力对于区域灾害预警具有重要意义。以甘肃定西地区为研究区，选取坡度、坡向、土地利用等7个评价因子，利用确定系数与逻辑回归耦合模型、空间自相关方法分析地质灾害的空间集聚特征及驱动因素。结果表明：定西地区地质灾害危险性呈现中部高，南北两侧低的特征，其主要受降水、坡向、工程岩组等因子的影响；地质灾害与降水、坡向和工程岩组的空间关系为高高聚集；地质灾害危险性存在较强的空间自相关性，在3 km的空间尺度上呈显著正相关，且随距离阈值增加而降低；距离阈值为5 km时，正相关高高聚集与低低聚集以团块的形式存在，而高低聚集与低高聚集多以零星状分布。研究可为区域地质灾害监测与防控提供参考。
Abstract:It is of great significance to identify the hot spots and driving forces of geological hazard gathering for regional disaster early warning. Dingxi region of Gansu Province is taken as a the study area. Seven factors such as slope, aspect, land use, engineering rock group and so on are selected to analyze the spatial agglomeration characteristics and driving factors of geological hazards by using coupling model of determining coefficient and logical regression and spatial autocorrelation. The results show that the sensitivity of geological hazards in Dingxi region is high in the middle region and low in the north and south region. The spatial relationship between geological hazards and precipitation, aspect and engineering rock group is high accumulation. Geological hazard sensitivity has strong spatial autocorrelation, which is significantly positive correlation in 3 km scale, and decreases with the increase of distance threshold. When the distance threshold is 5 km, the high and low aggregation areas are clustered and distributed in the form of clumps, while the high and low aggregation areas and the low and high aggregation areas are mostly scattered. The research can provide reference for regional geological hazard monitoring and control.
-
-
表 1 定西地区各个县地质灾害点数量
Table 1. Dingxi region each county geological disaster point number
滑坡/处 崩塌/处 泥石流/处 安定区 10 6 19 通渭县 22 35 2 陇西县 31 31 34 漳县 2 0 50 临洮县 23 3 20 渭源县 21 6 11 岷县 9 0 83 
下载: 导出CSV
表 2 各因子CF值计算结果
Table 2. Calculation result of CF value of each factor
评价因子 类别量 灾害点数 CF 评价因子 类别量 灾害点数 CF 坡度/(°) 0～8 108 0.124 坡向 北 31 −0.472 8～16 162 −0.051 东北 48 −0.277 16～24 103 −0.023 东 45 −0.175 >24 45 −0.050 东南 69 0.331 降水量/mm <330 26 −0.327 南 66 0.219 330～380 43 −0.420 西南 77 0.320 380～430 193 0.193 西 44 −0.000 430～480 125 0.315 西北 38 −0.140 >480 31 −0.514 距河流距离/m 0～2000 84 0.243 土地利用 林地 20 −0.535 2000～4000 63 0.208 草地 194 −0.086 4000～6000 61 0.177 湿地 5 0.655 6000～8000 49 0.108 耕地 179 0.148 8000～10000 37 −0.141 人工表面 17 0.559 >10000 131 −0.250 未利用地 4 0.498 距道路距离/m <500 79 0.337 工程岩组 侵入岩 3 −0.805 500～1000 81 0.242 喷出岩 1 −0.378 1000～1500 23 −0.027 变质岩 63 0.188 1500～2000 28 −0.129 碎屑岩 311 −0.007 2000～2500 30 0.218 碳酸岩 19 −0.250 >2500 184 −0.207 松散岩 22 0.439
下载: 导出CSV
表 3 逻辑回归分析结果
Table 3. Results of logical regression analysis
B SE Wals df sig 坡度 −3.284 1.255 6.852 1 0.009 坡向 1.506 0.313 23.199 1 0.000 降水 1.766 0.267 43.704 1 0.000 土地利用 1.305 0.433 9.092 1 0.003 工程岩组 2.458 0.606 16.444 1 0.000 距河流距离 0.940 0.940 5.368 1 0.021 距道路距离 1.110 0.393 7.981 1 0.005 常数项 0.066 0.086 0.593 1 0.441 注：B代表各因子的回归系数，SE为标准误差，Wals为卡方值，df为自由度，sig表示显著性。
下载: 导出CSV
表 4 地质灾害危险性分区统计表
Table 4. Zonal statistical table of geological hazard
敏感性等级 极高
危险区高
危险区中
危险区低
危险区极低
危险区该级别区域面积/km2 3089 4258 4590 4368 3030 占研究区面积比/% 15.98 22.02 23.74 22.59 15.67 灾害点个数 135 124 100 47 12 占灾害样本点总数比/% 32.30 29.67 23.92 11.24 2.87
下载: 导出CSV
-
[1] 唐川, 马国超. 基于地貌单元的小区域地质灾害易发性分区方法研究[J]. 地理科学,2015,35(1):91 − 98. [TANG Chuan, MA Guochao. Small regional geohazards susceptibility mapping based on geomorphic unit[J]. Scientia Geographica Sinica,2015,35(1):91 − 98. (in Chinese with English abstract)
[2] 牛全福, 陆铭, 李月锋, 等. 基于灰色关联与粗糙依赖度的甘肃兰州市区泥石流危险性评价[J]. 中国地质灾害与防治学报,2019,30(5):48 − 56. [NIU Quanfu, LU Ming, LI Yuefeng, et al. Hazard assessment of debris flow in Lanzhou City of Gansu Province based on methods of grey relation and rough dependence[J]. The Chinese Journal of Geological Hazard and Control,2019,30(5):48 − 56. (in Chinese with English abstract)
[3] 张晓东, 刘湘南, 赵志鹏, 等. 基于层次分析法的盐池县地质灾害危险性评价[J]. 国土资源遥感,2019,31(3):183 − 193. [ZHANG Xiaodong, LIU Xiangnan, ZHAO Zhipeng, et al. Geological disaster hazard assessment in Yanchi County based on AHP[J]. Remote Sensing for Land Resources,2019,31(3):183 − 193. (in Chinese with English abstract)
[4] 孙长明, 马润勇, 尚合欣, 等. 基于滑坡分类的西宁市滑坡易发性评价[J]. 水文地质工程地质,2020,47(3):173 − 181. [SUN Changming, MA Runyong, SHANG Hexin, et al. Landslide susceptibility assessment in Xining based on landslide classification[J]. Hydrogeology & Engineering Geology,2020,47(3):173 − 181. (in Chinese with English abstract)
[5] 宁娜, 马金珠, 张鹏, 等. 基于GIS和信息量法的甘肃南部白龙江流域泥石流灾害危险性评价[J]. 资源科学,2013,35(4):892 − 899. [NING Na, MA Jinzhu, ZHANG Peng, et al. Debris flow hazard assessment for the Bailongjiang river, southern Gansu[J]. Resources Science,2013,35(4):892 − 899. (in Chinese with English abstract)
[6] 刘明学, 陈祥, 杨珊妮. 基于逻辑回归模型和确定性系数的崩滑流危险性区划[J]. 工程地质学报,2014,22(6):1250 − 1256. [LIU Mingxue, CHEN Xiang, YANG Shanni. Zonation of landslide risk with logistic regression model and certainty factor[J]. Journal of Engineering Geology,2014,22(6):1250 − 1256. (in Chinese with English abstract)
[7] 许冲, 戴福初, 姚鑫, 等. 基于GIS与确定性系数分析方法的汶川地震滑坡易发性评价[J]. 工程地质学报,2010,18(1):15 − 26. [XU Chong, DAI Fuchu, YAO Xin, et al. GIS platform and certainty factor analysis method based Wenchuan earthquake-induced landslide susceptibility evaluation[J]. Journal of Engineering Geology,2010,18(1):15 − 26. (in Chinese with English abstract) doi: 10.3969/j.issn.1004-9665.2010.01.003
[8] 田春山, 刘希林, 汪佳. 基于CF和Logistic回归模型的广东省地质灾害易发性评价[J]. 水文地质工程地质,2016,43(6):154 − 161. [TIAN Chunshan, LIU Xilin, WANG Jia. Geohazard susceptibility assessment based on CF model and Logistic Regression models in Guangdong[J]. Hydrogeology & Engineering Geology,2016,43(6):154 − 161. (in Chinese with English abstract)
[9] 李慧, 王云鹏, 李岩, 等. 珠江三角洲土地利用变化空间自相关分析[J]. 生态环境学报,2011,20(12):1879 − 1885. [LI Hui, WANG Yunpeng, LI Yan, et al. A spatial autocorrelation analysis of land use change in Pearl River Delta[J]. Ecology and Environmnet,2011,20(12):1879 − 1885. (in Chinese with English abstract) doi: 10.3969/j.issn.1674-5906.2011.12.017
[10] 刘金雅, 汪东川, 孙然好, 等. 基于变化轨迹分析方法的生态用地流失空间关联研究[J]. 地理研究,2020,39(1):103 − 114. [LIU Jinya, WANG Dongchuan, SUN Ranhao, et al. Study on spatial relevance of ecological-land loss based on change trajectory analysis method[J]. Geographical Research,2020,39(1):103 − 114. (in Chinese with English abstract) doi: 10.11821/dlyj020181021
[11] 林金煌, 张岸, 邓超, 等. 闽三角城市群地质灾害敏感性评价[J]. 地球信息科学学报,2018,20(9):1286 − 1297. [LIN Jinhuang, ZHANG An, DENG Chao, et al. Sensitivity assessment of geological hazards in urban agglomeration of Fujian delta region[J]. Geo-Information Science,2018,20(9):1286 − 1297. (in Chinese with English abstract) doi: 10.12082/dqxxkx.2018.180099
[12] 中国地质环境监测院编制. 中国典型县 (市) 地质灾害易发程度分区图集 [M]. 北京: 科学出版社, 2011.
China Institute of Geological Environment Monitoring. Atlas of geological hazard susceptibility in typical counties (cities) in China [M]. Beijing: Science Press, 2011. (in Chinses)
[13] 覃伟, 徐智彬, 李东林. 渗透性与降雨强度对堆积层滑坡稳定性的影响[J]. 地质与勘探,2016,52(4):743 − 750. [QIN Wei, XU Zhibin, LI Donglin. Controls of permeability and rainfall intensity on accumulation landslide stability[J]. Geology and Prospecting,2016,52(4):743 − 750. (in Chinese with English abstract)
[14] 张欣, 王运生, 梁瑞锋. 基于GIS的小江断裂中北段滑坡灾害危险性评价[J]. 地质与勘探,2018,54(3):623 − 633. [ZHANG Xin, WANG Yunsheng, LIANG Ruifeng. Assessment of landslide hazard in the middle and northern Xiaojiang fault zone based on GIS[J]. Geology and Prospecting,2018,54(3):623 − 633. (in Chinese with English abstract)
[15] 谭玉敏, 郭栋, 白冰心, 等. 基于信息量模型的涪陵区地质灾害易发性评价[J]. 地球信息科学学报,2015,17(12):1554 − 1562. [TAN Yumin, GUO Dong, BAI Bingxin, et al. Geological hazard risk assessment based on information quantity model in Fuling district, Chongqing City, China[J]. Geo-Information Science,2015,17(12):1554 − 1562. (in Chinese with English abstract)
[16] 裴惠娟, 陈晋, 李雯, 等. 甘肃省地质灾害风险评估[J]. 灾害学,2017,32(2):97 − 102. [PEI Huijuan, CHEN Jin, LI Wen, et al. Geological disaster risk assessment in Gansu Province[J]. Journal of Catastrophology,2017,32(2):97 − 102. (in Chinese with English abstract) doi: 10.3969/j.issn.1000-811X.2017.02.017
[17] 冯磊, 孙保平, 康苗. 甘肃省定西市安定区土壤侵蚀潜在危险度评价及侵蚀背景空间分析[J]. 吉林农业科学,2012,37(4):25 − 29. [FENG Lei, SUN Baoping, KANG Miao. Appraisal and study on potential danger of soil erosion and spatial analysis on erosion background in Anding region, Dingxi City of Gansu Province[J]. Jilin Agricultural Sciences,2012,37(4):25 − 29. (in Chinese with English abstract) doi: 10.3969/j.issn.1003-8701.2012.04.010
-
图(9)
表(4)
计量
- 文章访问数: 1410
- PDF下载数: 39
- 施引文献: 0