基于不同采样策略的武义县滑坡易发性评价对比分析

周孙超 ,  宋腾蛟 ,  沈腾泽 ,  蔡宗佑

自然灾害学报 ›› 2026, Vol. 35 ›› Issue (3) : 48 -62.

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自然灾害学报 ›› 2026, Vol. 35 ›› Issue (3) : 48 -62. DOI: 10.13577/j.jnd.2026.0305
专题: 自然灾害风险防范与应急响应

基于不同采样策略的武义县滑坡易发性评价对比分析

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Comparative analysis of landslide susceptibility evaluation in Wuyi County based on different sampling strategies

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摘要

滑坡是一种常见的地质灾害,影响地区经济的发展,危害人民的生命安全。本文以浙江省金华市武义县为例,利用GIS平台提取高程、坡度、坡向等13种环境因子,通过信息量法分析各个环境因子对滑坡灾害的影响,基于信息量值生成滑坡易发性图并由此划分出易发性等级区域,根据不同采集策略从极低易发区、低易发区采集不同比例的非滑坡样本点,形成数据集,训练小龙虾算法(crayfish optimization algorithm,COA)耦合反向传播(back propagation,BP)神经网络模型(COA-BP),通过准确率、模型内部权重影响分析、滑坡易发性评价精度分析,对不同采样策略进行评价。结果表明,滑坡灾害发生区间与人类活动区间重合,测试集准确率与训练集准确率不存在强关系,不同采样策略以及样本量比例对模型内部权重影响不同,并且权重的正负性也不能定性,1∶4不处理样本的采样策略在该地区综合采样能力最佳,为当地防灾减灾提供一定的参考。

Abstract

Landslides are a common geological hazard that impacts economic development and endangers people’s lives. This paper takes Wuyi County, Jinhua City, Zhejiang Province as an example. Using a GIS platform, 13 environmental factors, including elevation, slope, and aspect, are extracted. The impact of each environmental factor on landslide hazards is analyzed using the information content method. A landslide susceptibility map is generated based on the information content values, and susceptibility levels are delineated. Different proportions of non-landslide sample points are collected from extremely low-susceptibility and low-susceptibility areas according to different collection strategies to form a dataset. A crayfish algorithm coupled with a back propagation (COA-BP) neural network model is trained. Different sampling strategies are evaluated through accuracy, internal model weight influence analysis, and landslide susceptibility assessment accuracy analysis. The results show that the landslide hazard occurrence area overlaps with the human activity area. There is no strong correlation between the accuracy of the test set and the accuracy of the training set. Different sampling strategies and sample size ratios have different impacts on the internal model weights, and the positive or negative nature of the weights cannot be qualitatively interpreted. The 1∶4 sampling strategy with no sample processing has the best overall sampling capability in this area, providing a certain reference for local disaster prevention and mitigation.

关键词

小龙虾算法 / BP神经网络 / 采样策略 / 滑坡易发性评价 / 信息量法

Key words

crayfish algorithm / BP neural network / sampling strategy / evaluation of landslide susceptibility / information value

引用本文

引用格式 ▾
周孙超,宋腾蛟,沈腾泽,蔡宗佑. 基于不同采样策略的武义县滑坡易发性评价对比分析[J]. 自然灾害学报, 2026, 35(3): 48-62 DOI:10.13577/j.jnd.2026.0305

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基金资助

吉林省科技发展计划项目(YDZJ202501ZYTS563)

吉林省教育厅科学研究项目(JJKH20190874KJ)

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