基于信息量模型和数据标准化的滑坡易发性评价

doi:10.12082/dqxxkx.2018.170535

摘要/Abstract

摘要：

本文以北川曲山-擂鼓片区为研究区,将坡度、坡向、高程、地层、距断层的距离、距水系的距离和距道路的距离作为该区域滑坡易发性评价因子。采用信息量模型计算了各项评价因子的信息量值,并运用4种标准化模型对信息量值进行标准化处理。各评价因子的权重由层次分析法（AHP）确定。在GIS中将权重值和各评价因子的标准化信息量值,进行叠加计算得到区域滑坡总信息量值,并基于自然断点法对其进行重分类,将研究区划分为极高易发区、高易发区、中易发区、低易发区和极低易发区5级易发区。将基于4种标准化模型和信息量模型得到的滑坡易发性评价结果进行了对比分析,结果表明：基于最值标准化信息量模型的滑坡易发性评价结果的ROC曲线下面积AUC值为0.807,高于其余模型的AUC值,说明最值标准化信息量模型的滑坡易发性评价效果最好。极高易发区面积占研究区面积的20.03%,离断层和水系较近,主要分布地层为寒武系、志留系和三迭系。研究结果可为区内滑坡风险评价和灾害防治提供参考。

关键词: 易发性评价, 信息量模型, 标准化, 滑坡, GIS

Abstract:

This paper used an information quantity model and four normalized models to assess earthquake-induced shallow landslide susceptibility in a geographic information system environment. Four normalized models are Min-Max normalization, the zero-mean normalization, the logarithmic logistic normalization and the arc-tangent function normalization. The approach was applied to the Qushan-Leigu area in the Beichuan County, Sichuan Province, where many co-seismic landslides were triggered by the Wenchuan earthquake in May 2008. Seven impact factors, the slope angle, slope aspect, geology, elevation, distance to faults, distance to rivers and distance to roads, were selected as the most important conditioning factors. To assess the shallow landslide susceptibility, a spatial database of conditioning factors and a landslide inventory map were compiled in ArcGIS using data from a topographic map, a geological map and Spot-5 imageries. The information quantity values of the conditioning factors were computed and normalized based on four normalized models. The weighted values of assessment factors were determined using the analytic hierarchy process. Five landslide susceptibility maps were developed. The performance was evaluated using the receiver operating characteristic (ROC) curve. The values of the area under the curve (AUC) for four normalized models and the information quantity model are 0.807, 0.672, 0.592, 0.615 and 0.684, respectively. A comparison of the results of the landslide susceptibility assessment and the landslide inventory indicates that the Min-Max normalization had the highest predictive performance (AUC=0.807). The landslide susceptibility index values were reclassified into five susceptibility classes using the Natural Breaks approach, namely very high, high, medium, low and very low susceptibility. The results show that the very high susceptibility zone obtained using the Min-Max normalization covers about 20% of the study area. Landslides distributed in the very high susceptibility zone are close to faults and rivers. The final landslide susceptibility map has the potential to the regional landslide risk assessment and geohazard mitigation.

Key words: susceptibility assessment, information quantity model, normalization, landslide, geographic information system (GIS)

杨根云, 周伟, 方教勇. 基于信息量模型和数据标准化的滑坡易发性评价[J]. 地球信息科学学报, 2018, 20(5): 674-683.DOI:10.12082/dqxxkx.2018.170535

YANG Genyun,ZHOU Wei,FANG Jiaoyong. Assessment of landslide Susceptibility Based on Information Quantity Model and Data Normalization[J]. Journal of Geo-information Science, 2018, 20(5): 674-683.DOI:10.12082/dqxxkx.2018.170535

图/表 9

图1

图2

表1

各评价因子的信息量值及其标准化"

影响因子	分类	信息量值	数据标准化
影响因子	分类	信息量值	最值标准化	偏差法标准化	对数Logistic标准化	反正切函数标准化
坡度/°	<15	-7.7457	0.0000	-1.2306	0.0004	-0.9183
	15~30	-5.2942	0.2047	-0.7329	0.0050	-0.8812
	30~45	-1.4247	0.5278	0.0526	0.1939	-0.6104
	45~60	1.8157	0.7984	0.7104	0.8600	0.6795
	>60	4.2304	1.0000	1.2007	0.9857	0.8522
坡向	北	0.9117	1.0000	1.2701	0.7133	0.4706
	东北	-2.0117	0.0000	-1.9781	0.1180	-0.7063
	东	-0.9869	0.3505	-0.8395	0.2715	-0.4958
	东南	-0.2583	0.5998	-0.0298	0.4358	-0.1609
	南	0.0726	0.7130	0.3378	0.5181	0.0462
	西南	0.2955	0.7892	0.5855	0.5734	0.1829
	西	-0.1371	0.6412	0.1048	0.4658	-0.0867
	西北	0.2628	0.7780	0.5491	0.5653	0.1636
距断层的距离/m	1000	-0.0228	0.8291	0.4150	0.4943	-0.0145
	2000	0.3843	1.0000	0.8986	0.5949	0.2336
	3000	-0.0229	0.8291	0.4149	0.4943	-0.0146
	4000	-0.1027	0.7956	0.3202	0.4744	-0.0651
	5000	-0.4713	0.6409	-0.1176	0.3843	-0.2804
	6000	-1.9983	0.0000	-1.9311	0.1194	-0.7046
距水系的距离/m	200	0.7238	1.0000	1.5157	0.6735	0.3989
	400	-0.8372	0.5019	0.2383	0.3021	-0.4437
	600	-1.0897	0.4213	0.0316	0.2517	-0.5273
	800	-2.0283	0.1219	-0.7365	0.1163	-0.7084
	1000	-2.4102	0.0000	-1.0490	0.0824	-0.7496
地层	寒武系	0.4548	0.8003	0.7869	0.6118	0.2717
	奥陶系	0.0000	0.6341	0.2295	0.5000	0.0000
	志留系	-0.6447	0.3986	-0.5606	0.3442	-0.3646
	泥盆系	-0.5498	0.4333	-0.4443	0.3659	-0.3200
	石炭系	-1.7359	0.0000	-1.8978	0.1498	-0.6673
	二迭系	-0.0241	0.6253	0.2000	0.4940	-0.0153
	三迭系	1.0015	1.0000	1.4569	0.7314	0.5005
	第四系	0.0000	0.6341	0.2295	0.5000	0.0000
高程/m	600~900	-1.1545	0.0000	-1.9886	0.2397	-0.5456
	900~1200	-0.0043	0.7400	-0.0058	0.4989	-0.0027
	1200~1500	0.2649	0.9131	0.4582	0.5658	0.1649
	1500~1800	0.2484	0.9025	0.4298	0.5618	0.1550
	1800~2100	0.2403	0.8973	0.4159	0.5598	0.1502
	2100~2340	0.3999	1.0000	0.6909	0.5987	0.2422
距道路的距离/m	200	0.1403	1.0000	1.4541	0.5350	0.0887
	400	-0.0376	0.4787	-0.0310	0.4906	-0.0239
	600	-0.1131	0.2576	-0.6610	0.4718	-0.0717
	800	0.0509	0.7381	0.7079	0.5127	0.0324
	1000	-0.2010	0.0000	-1.3947	0.4499	-0.1263
	>1000	-0.0427	0.4639	-0.0732	0.4893	-0.0271

表1

图3

表2

表3

表4

图4

图5

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标度	含义
1	前者和后者同样重要
3	前者比后者稍微重要
5	前者比后者明显重要
7	前者比后者强烈重要
9	前者比后者极端重要
2,4,6,8	表示上述相邻判断的中间值
倒数	假如前者与后者的重要性之比为B,那么后者与前者重要性之比为1/B

	坡度	坡向	距水系的距离	距断层的距离	地层	高程	距道路的距离	权重
坡度	1	3	2	2	2	2	3	0.2578
坡向	1/3	1	1/3	1/3	1/3	1/2	1	0.0613
距水系的距离	1/2	3	1	1/2	2	2	2	0.1637
距断层的距离	1/2	3	2	1	2	2	3	0.2115
地层	1/2	3	1/2	1/2	1	1/2	2	0.1102
高程	1/2	2	1/2	1/2	2	1	2	0.1267
距道路的距离	1/3	1	1/2	1/3	1/2	1/2	1	0.0688

	N
	1	2	3	4	5	6	7	8	9	10
RI	0	0	0.58	0.90	1.12	1.24	1.32	1.41	1.45	1.49