地质通报2026，Vol.45Issue(5)：885-899,15.DOI:10.12097/gbc.2024.05.007
基于卷积神经网络的生态地质环境评价方法
Eco-geological environment evaluation method based on Convolutional Neural Network
摘要
Abstract
[Objective]The eco-geological environment is closely related to the development of human society.Scientific evaluation of the eco-geological environment can deepen our understanding of environmental conditions and promote social and economic development.However,traditional evaluation methods fail to fully capture the key characteristics of the eco-geological environment such as nonlinearity and spatial autocorrelation,which easily lead to problems such as discontinuous evaluation results,abrupt grade jumps and lack of gradual transition and biased identification of extreme environments.This study aims to construct a deep learning evaluation method suitable for complex eco-geological systems to improve evaluation rationality and spatial continuity.[Methods]The subject region under investigation is Anji County,Zhejiang Province.Seventeen evaluation indicators including vegetation coverage,land use and slope were selected to construct a three-subsystem evaluation system of ecological,geological and livable environments.Evaluation label maps were produced by expert scoring,and a Convolutional Neural Network(CNN)model was built for training and evaluation.Finally,the evaluation results were compared with the comprehensive index method and random forest method for verification.[Results]The excellent and good areas of eco-geological environment in Anji County account for 95.57%.The ecologically excellent areas are concentrated in forest land,the geologically weak areas are high-prone areas of disasters,and the livable excellent areas are mainly plain gentle zones.[Conclusions]The method proposed in this paper can reasonably identify extreme eco-geological environments and effectively eliminate evaluation faults and incoherence of adjacent plots.Compared with conventional evaluation methods such as the comprehensive index method and random forest,the CNN model can better characterize the nonlinear relationships and spatial autocorrelation features of eco-geological systems.The findings of this study provide scientific support for the sustainable development in Anji County,and also offer a methodological reference for eco-geological environment assessment in analogous regions.关键词
生态地质环境/深度学习/卷积神经网络/浙江省安吉县Key words
eco-geological environment/deep learning/Convolutional Neural Network/Anji County,Zhejiang Province分类
天文与地球科学引用本文复制引用
朱振翔,鲁晨妍,陈丽,郐开富,章孝灿,黄智才..基于卷积神经网络的生态地质环境评价方法[J].地质通报,2026,45(5):885-899,15.基金项目
浙江省人民政府项目《自然资源调查监测关键技术研究与应用-自然资源卫星遥感综合监测关键技术研究与应用》(编号:2025C02052) Supported by Zhejiang Province Leading Project(No.2025C02052) （编号:2025C02052）
