测绘通报 ›› 2026, Vol. 0 ›› Issue (10): 21-27.doi: 10.13474/j.cnki.11-2246.2026.1003

• 滑坡灾害识别 • 上一篇    

顾及地表形变特征的滑坡易发性WOA-BP评价模型

陈兰兰1,2,3, 黄浩4, 陈欣悦4, 孙晓玉4, 肖海平4, 万俊辉4   

  1. 1. 赣南科技学院低空技术与工程学院, 江西 赣州 341000;
    2. 赣州市智能建造重点实验室, 江西 赣州 341000;
    3. 赣州市古建筑修复与保护技术创新中心, 江西 赣州 341000;
    4. 江西理工大学低空技术学院, 江西 赣州 341000
  • 收稿日期:2026-01-12 发布日期:2026-11-06
  • 通讯作者: 肖海平。E-mail:415562281@qq.com
  • 作者简介:陈兰兰(1981—),女,硕士,副教授,主要研究方向为边坡稳定性分析与监测。E-mail:707598180@qq.com
  • 基金资助:
    国家自然科学基金(42361012);江西省自然科学基金(20212BAB204030)

Landslide susceptibility evaluation model based on WOA-BP considering surface deformation features

Chen Lanlan1,2,3, Huang Hao4, Chen Xinyue4, Sun Xiaoyu4, Xiao Haiping4, Wan Junhui4   

  1. 1. School of Low-Altitude Technology and Engineering, Gannan University of Science and Technology, Ganzhou 341000, China;
    2. Ganzhou Key Laboratory of Intelligent Construction, Ganzhou 341000, China;
    3. Ganzhou Technology Innovation Center of Architectural Heritage Conservation and Restoration, Ganzhou 341000, China;
    4. School of AirSpace Technology, Jiangxi University of Science and Technology, Ganzhou 341000, China
  • Received:2026-01-12 Published:2026-11-06

摘要: [目的] 滑坡是一种分布广、频率高、破坏性强的地质灾害,其易发性评价对灾害预警和风险防控具有重要意义。考虑到传统评价方法存在的仅依赖静态因子、忽略地表形变特征、模型精度不高等问题,本文提出了一种顾及DInSAR地表形变特征的WOA-BP滑坡易发性评价方法。[方法] 以贵州省德江县为研究对象,基于Sentinel-1A卫星升轨数据,采用DInSAR技术提取研究区的地表形变特征,并结合历史滑坡数据及10个静态因子,实现滑坡易发性评价。[结果] 研究结果表明,对比BP、LSTM、SVM与RF 4种模型,WOA-BP模型的AUC值提升至0.800,预测精度至少提高10.19%。[结论] 本文所提顾及地表形变特征的WOA-BP模型相比仅考虑静态因子的评价方法,纠正近30.9个百分点的误分类区域,可有效提升滑坡易发性评价的可靠性,为滑坡易发性准确评价提供新方法。

关键词: DInSAR技术, 地表形变特征, WOA-BP模型, 滑坡发性评价

Abstract: [Purposes] Landslides are widely distributed,frequent,and highly destructive geological disasters,and evaluating their susceptibility is crucial for disaster early warning and risk management.This paper proposes a WOA-BP landslide susceptibility evaluation model that incorporates DInSAR surface deformation features to address the limitations of traditional methods that only rely on static factors and neglect surface deformation characteristics. [Methods] Using Dejiang county,Guizhou province as the study area,the DInSAR technology based on Sentinel-1A satellite ascending data is employed to extract surface deformation features,combined with historical landslide data and 10 static factors,to evaluate landslide susceptibility. [Findings] The results show that compared to BP,LSTM,SVM,and RF models,the WOA-BP model's AUC value improves to 0.800,and its prediction accuracy increases by at least 10.19%. [Conclusions] The proposed model,which includes surface deformation features,effectively corrects nearly 30.9 percentage points of misclassified areas,significantly improving the reliability of landslide susceptibility evaluation and providing a new method for accurate landslide susceptibility assessment.

Key words: DInSAR technology, surface deformation features, WOA-BP model, landslide susceptibility evaluation

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