基于GF-2影像的农村黑臭水体遥感识别与动态监测

doi:10.13474/j.cnki.11-2246.2025.0502

摘要/Abstract

摘要： 农村黑臭水体治理是实施乡村振兴战略的重要任务,而其面广、量大,且存在季节性变化,导致底数不清、周期性反臭,成为治理监管的难点。遥感监测时效性强、覆盖面广,可提高农村黑臭水体监测效率。本文以国产高分辨率卫星GF-2为数据源,首先采用DeepLabV3+语义分割方法提取农村坑塘、沟渠等细小水体,然后基于黑臭水体与正常水体的光谱曲线差异,构建多种黑臭水体识别模型,最后在新乡县、漯河市、项城市进行农村黑臭水体识别和精度验证。结果显示,基于红波段、绿波段建立的NDBWI模型具有较高的准确性和普适性。利用该模型对新乡县2022—2024年的农村黑臭水体进行的动态监测发现,2023年黑臭水体数量较上年减少60%,2024年有6.8%的轻微反弹,表明近3年新乡县农村黑臭水体治理成效显著。本文研究成果可为精准治理农村黑臭水体,推进农村人居环境整治提供有效支撑。

关键词: GF-2影像, 水体提取, 农村黑臭水体, 遥感识别, 动态监测

Abstract: The treatment of black-odor water bodies is an important task in implementing the rural revitalization strategy. However, their distribution is extensive, widespread, and shows seasonal variation, leading to unclear baseline figures and periodic odors, thus becoming a difficult point for governance and supervision. In this paper, we use GF-2 as the data source and adopt the DeepLabv3+ semantic segmentation method to extract fine water body in rural areas. We analyze the spectral curve features of black-odor water bodies and normal water bodies, and build various models to identify black-odor water bodies. We conduct precision verification in Xinxiang County, Luohe City, and Xiangcheng City,and the results show that the NDBWI model has high accuracy and universality. We use this model to dynamically monitor black-odor water bodies in Xinxiang County from 2022 to 2024. The study found that the number of black-odor water bodies in 2023 is 60% less than that in the previous year, and there is a slight rebound of 6.8% in 2024, indicating that the treatment of black-odor water bodies treatment in Xinxiang County has achieved significant results in the past three years. The research results can provide effective support for precise management of rural black-odor water bodies and the promotion of rural living environment improvement.

Key words: GF-2, water extraction, rural black-odor water bodies, remote sensing identification, dynamic monitoring

中图分类号:

P237

刘甜甜, 张明, 冯继锋, 李倩楠, 朱雨芯. 基于GF-2影像的农村黑臭水体遥感识别与动态监测[J]. 测绘通报, 2025, 0(5): 8-14.

LIU Tiantian, ZHANG Ming, FENG Jifeng, LI Qiannan, ZHU Yuxin. Remote sensing identification and dynamic monitoring of black-odor water bodies in rural areas based on GF-2 images[J]. Bulletin of Surveying and Mapping, 2025, 0(5): 8-14.

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