基于RBF神经网络−信息量耦合模型的滑坡易发性评价

黄立鑫; 郝君明; 李旺平; 周兆叶; 贾佩钱

doi:10.16031/j.cnki.issn.1003-8035.2021.06-14

基于RBF神经网络−信息量耦合模型的滑坡易发性评价

1.
兰州理工大学土木工程学院，甘肃兰州　730050

2.
甘肃省应急测绘工程研究中心，甘肃兰州　730050

基金项目: 甘肃省高等学校产业支撑计划项目“地质灾害隐患识别、临灾预警与防治关键技术研究”(2020C-40)；甘肃省自然科学基金“附加监测数据的滑坡稳定性评价”(20JR10RA180)；甘肃省自然科学基金“黄河源区高寒灌丛变化及其影响机制研究”(20JR5RA444)

详细信息

作者简介: 黄立鑫（1994-），男，甘肃会宁人，硕士研究生，主要从事3S技术及应用研究。E-mail：1417090091@qq.com

通讯作者: 李旺平（1982-），男，甘肃天水人，副教授，主要从事3S技术及应用研究。E-mail：lwp_136@163.com

中图分类号: P642.22；P954

收稿日期: 2021-02-06

修回日期: 2021-04-05

刊出日期: 2021-12-25

Landslide susceptibility assessment by the coupling method of RBF neural network and information value: A case study in Min Xian，Gansu Province

1.
College of Civil Engineering, Lanzhou University of Technology, Lanzhou, Gansu　730050, China

2.
Emergency Mapping Engineering Research Center of Gansu, Lanzhou, Gansu　730050, China

More Information

Corresponding author: LI Wangping, lwp_136@163.com

Received Date: 06 February 2021

Revised Date: 05 April 2021

Publish Date: 25 December 2021

摘要

摘要:
滑坡易发性评价是滑坡灾害管理的基础工作，也是制定各项防灾减灾措施的重要依据。针对传统的信息量模型在评价过程中确定权重值存在准确性不高的缺点，文章提出RBF神经网络和信息量耦合模型。以甘肃省岷县为研究区，筛选坡度等9个指标因子构建了滑坡灾害易发性评价指标体系，应用RBF神经网络-信息量耦合模型（RBFNN-I）进行滑坡灾害易发性评价，利用合理性检验和ROC曲线对模型的评价结果进行精度检验。结果表明：（1）RBFNN-I模型的AUC值为0.853，相比单一的RBFNN和I模型分别提高了6.3%和9.7%，说明RBFNN-I模型具有更好的评价精度；（2）岷县滑坡灾害的极高易发区和高易发区主要分布在临潭—宕昌断裂带、洮河及其支流、闾井河和蒲麻河两侧河谷地带，距断层距离、降雨量、距道路距离和NDVI是影响岷县滑坡灾害分布的主控因子。
- 滑坡 /
- 易发性评价 /
- RBF神经网络 /
- 信息量 /
- 岷县
Abstract:
The landslide susceptibility evaluation is the basic work of landslide management, and it is also an important basis for formulating various disaster prevention and mitigation measures. In view of the low accuracy of the traditional information model in determining the weight value in the evaluation process, this paper proposes a coupling model of RBF neural network and Information value model. 9 index factors such as slope are selected to build the evaluation index system of landslide susceptibility in Min Xian of Gansu Province. The RBF neural network information value coupling model (RBFNN-I) is used to carry out the landslide hazard susceptibility evaluation. Rationality test and ROC curve are used to test the accuracy of the evaluation results of the model. The results show that: (1) the AUC value of RBFNN-I model is 0.853, which is 6.3% and 9.7% higher than that of single RBFNN and I model, respectively, indicating that RBFNN-I model has better evaluation accuracy; (2) the extremely high and high susceptible areas of landslide disasters in Min Xian are mainly distributed along Lintan-Dangchang fault zone, Tao He and its tributaries, and the valleys on both sides of Lyuning River and Puma River.
- landslide /
- susceptibility assessment /
- RBF neural network /
- information value /
- Min Xian

HTML全文

图 1 RBF神经网络结构

Figure 1.

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图 2 基于RBFNN-I模型滑坡灾害易发性评价流程图

Figure 2.

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图 3 岷县地理位置及历史滑坡点分布图

Figure 3.

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图 4

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图 4 岷县滑坡灾害易发性评价指标因子

Figure 4.

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图 5 基于RBFNN-I模型的岷县滑坡易发性评价结果图

Figure 5.

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图 6 ROC精度验证曲线

Figure 6.

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图 7 各指标因子重要性分布图

Figure 7.

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表 1 指标因子相关性检验表

Table 1. Correlation of controlling index factors

	高程	坡度	坡向	平面曲率	距断层距离	地层	降雨量	距水系距离	NDVI	距道路距离
高程	1
坡度	−0.06	1
坡向	−0.01	0.03	1
平面曲率	0.05	0.05	0.04	1
距断层距离	0.37	−0.20	0.00	0.10	1
地层	−0.32	−0.14	−0.06	0.04	−0.01	1
降雨量	0.75	−0.11	−0.01	0.09	0.19	−0.33	1
距水系距离	0.48	−0.09	0.01	−0.02	0.20	−0.13	0.25	1
NDVI	0.32	−0.08	0.00	0.04	0.35	−0.13	0.38	0.14	1
距道路距离	0.52	−0.14	−0.03	−0.01	0.17	−0.24	0.47	0.26	0.25	1

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表 2 指标因子分类等级信息量值计算表

Table 2. The classification information for index factors of landslide

指标因子	分类等级	滑坡面积/km²	滑坡面积比例A/%	分级面积/km²	分级面积比例B/%	频率比(A/B)	信息量值I
坡度/(°)	0～5	0.05	2.55	299.99	8.40	0.30	−1.20
	5～10	0.10	4.96	546.03	15.28	0.32	−1.14
	10～15	0.22	11.06	687.10	19.23	0.58	−0.54
	15～20	0.36	18.21	713.50	19.97	0.91	−0.09
	20～25	0.48	24.03	617.77	17.29	1.39	0.33
	25～30	0.40	20.25	410.29	11.48	1.76	0.57
	30～35	0.23	11.83	202.24	5.66	2.09	0.74
	35～40	0.08	4.01	72.21	2.02	1.98	0.68
	40～45	0.05	2.33	18.55	0.53	4.47	1.50
	>45	0.02	0.77	5.13	0.14	5.39	1.68
坡向	平地	0.00	0.00	1.37	0.04	0.00	0.00
	北向	0.05	2.69	452.59	12.67	0.21	−1.56
	东北	0.09	4.51	510.81	14.30	0.32	−1.14
	东向	0.28	13.97	503.66	14.10	0.99	−0.01
	东南	0.46	23.03	416.25	11.65	1.98	0.68
	南向	0.46	23.17	354.90	9.93	2.33	0.85
	西南	0.39	19.89	400.81	11.22	1.77	0.57
	西向	0.19	9.46	471.18	13.18	0.72	−0.33
	西北	0.06	3.28	461.22	12.91	0.25	−1.39
平面曲率	<−0.8	0.01	0.64	20.21	0.57	1.13	0.12
	−0.8～−0.6	0.05	2.28	43.79	1.23	1.86	0.62
	−0.6～−0.4	0.13	6.60	142.80	4.00	1.65	0.50
	−0.4～−0.2	0.31	15.84	458.93	12.85	1.23	0.21
	−0.2～0	0.58	29.18	1144.97	32.05	0.91	−0.09
	0～0.2	0.55	27.58	1010.38	28.28	0.98	−0.02
	0.2～0.4	0.24	11.93	501.62	14.04	0.85	−0.16
	0.4～0.6	0.08	4.05	171.91	4.81	0.84	−0.17
	0.6～0.8	0.03	1.32	53.27	1.49	0.89	−0.12
	>0.8	0.01	0.59	24.92	0.70	0.85	−0.16
距断层距离/km	<1	0.42	21.35	282.66	7.91	2.70	0.99
	1～2	0.36	18.02	282.74	7.91	2.28	0.82
	2～3	0.23	11.83	253.39	7.09	1.67	0.51
	3～4	0.13	6.74	198.62	5.56	1.21	0.19
	4～5	0.16	8.33	186.26	5.21	1.60	0.47
	5～6	0.19	9.60	176.83	4.95	1.94	0.66
	6～7	0.14	6.83	166.75	4.67	1.46	0.38
	7～8	0.03	1.55	124.82	3.49	0.44	−0.82
	8～9	0.02	1.23	136.00	3.81	0.32	−1.14
	9～10	0.02	1.23	95.39	2.67	0.46	−0.78
	>10	0.27	13.29	1701.76	46.73	0.29	−1.24
地层	第四系	0.47	23.67	694.20	19.43	1.22	0.20
	侏罗系	0.00	0.00	5.79	0.16	0.00	0.00
	三叠系	0.53	26.85	1195.33	33.46	0.80	−0.22
	二叠系	0.68	34.41	973.57	27.25	1.26	0.23
	石炭系	0.01	0.32	31.15	0.87	0.37	−0.99
	泥盆系	0.29	14.75	672.76	18.83	0.78	−0.25
降雨量/mm	554～571	0.32	16.02	156.72	4.39	3.65	1.29
	571～582	0.66	33.36	445.17	12.46	2.68	0.99
	582～590	0.51	25.58	595.83	16.68	1.53	0.43
	590～598	0.27	13.65	746.20	20.89	0.65	−0.43
	598～606	0.16	8.24	607.02	16.99	0.48	−0.73
	606～615	0.04	1.96	438.82	12.28	0.16	−1.83
	615～626	0.01	1.19	333.59	9.33	0.13	−2.04
	626～639	0.00	0.00	169.48	4.74	0.00	0.00
	639～659	0.00	0.00	79.96	2.24	0.00	0.00
距水系距离/km	<0.2	0.52	26.08	412.24	11.54	2.26	0.82
	0.2～0.4	0.25	12.74	395.79	11.08	1.15	0.14
	0.4～0.6	0.19	9.47	378.06	10.58	0.89	−0.12
	0.6～0.8	0.18	9.33	355.84	9.96	0.94	−0.06
	0.8～1.0	0.19	9.65	328.86	9.20	1.05	0.05
	1.0～1.2	0.18	8.88	295.52	8.27	1.07	0.07
	1.2～1.4	0.16	8.19	260.91	7.30	1.12	0.11
	1.4～1.6	0.12	6.05	225.50	6.31	0.96	−0.04
	1.6～1.8	0.03	1.41	188.56	5.28	0.27	−1.31
	1.8～2.0	0.07	3.38	153.32	4.30	0.78	−0.25
	>2.0	0.10	4.82	578.20	16.18	0.30	−1.20
NDVI	−0.75～−0.15	0.00	0.00	5.20	0.15	0.00	0.00
	−0.15～0.08	0.00	0.09	3.70	0.10	0.88	−0.13
	0.08～0.27	0.26	13.2	99.87	2.80	4.72	1.55
	0.27～0.40	0.49	24.85	158.74	4.44	5.59	1.72
	0.40～0.50	0.47	23.85	299.27	8.38	2.85	1.05
	0.50～0.60	0.39	19.66	419.73	11.75	1.67	0.51
	0.60～0.70	0.25	12.74	595.47	16.67	0.76	−0.27
	0.70～0.80	0.11	5.43	1030.79	28.84	0.19	−1.66
	0.80～1.00	0.00	0.18	960.04	26.87	0.01	−4.61
距道路距离/km	<0.2	0.46	23.40	285.40	7.99	2.93	1.08
	0.2～0.4	0.20	10.29	268.18	7.51	1.37	0.31
	0.4～0.6	0.13	6.6	252.80	7.08	0.93	−0.07
	0.6～0.8	0.16	8.28	235.52	6.59	1.26	0.23
	0.8～1.0	0.18	9.19	216.71	6.07	1.52	0.42
	1.0～1.2	0.12	6.28	202.54	5.67	1.11	0.10
	1.2～1.4	0.12	6.19	190.95	5.34	1.16	0.15
	1.4～1.6	0.12	6.14	176.72	4.95	1.24	0.22
	1.6～1.8	0.09	4.60	161.19	4.51	1.02	0.02
	1.8～2.0	0.11	5.51	146.41	4.09	1.34	0.29
	>2.0	0.27	13.52	1436.39	40.20	0.34	−1.08

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表 3 岷县滑坡灾害易发性分区合理性检验表

Table 3. Rationality test table of landslide susceptibility zone in Min Xian

模型类型	易发区等级	P/个	C_p /%	S/km²	S_p/%	R
RBFNN-I	极高易发区	308	56.10	373.70	10.41	5.39
	高易发区	175	31.88	717.96	20.00	1.59
	中易发区	51	9.29	975.40	27.17	0.34
	低易发区	15	2.73	1522.80	42.42	0.06
注：P代表各等级易发区内滑坡点的数量；C_p代表各等级易发区内的滑坡点数量的比例；S代表各等级易发区的面积； S_p代表各等级易发区面积占整个研究区总面积的比例；R代表C_p和S_p的比值。

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