自然资源遥感2025，Vol.37Issue(2)：148-154,7.DOI:10.6046/zrzyyg.2024054
国产多源卫片图斑智能提取平台研究与应用
An intelligent platform for extracting patches from multisource domestic satellite images and its application
摘要
Abstract
This study designed a one-stop platform for automatically extracting patches from multisource domestic satellite images based on a deep learning framework.The platform focuses primarily on critical techniques including semantic segmentation of ground objects,swarm intelligence algorithms for patch extraction,and deep feature interpretation.To address challenges in remote sensing image interpretation,such as significant color differences,vast data volumes of single images,diverse multi-channel image representations,and considerable differences in the sizes of remote sensing targets,the platform incorporates intelligent semantic segmentation and swarm intelligence algorithms for automatic patch extraction into the framework.It offers a range of customizable general and specialized models while supporting the self-training of models.With functions including large-scale data management,data annotation,model training,model testing,patch extraction,and application analysis,the platform has been successfully applied to the intelligent semantic segmentation and patch extraction of ground objects like buildings,vegetation,farmland,industrial zones,and water bodies in Taiyuan City,Shanxi Province based on multisource domestic satellite images.关键词
国产卫片/语义分割/图斑提取/遥感影像解译/深度学习/多尺度特征Key words
domestic satellite image/semantic segmentation/patch extraction/remote sensing image interpreta-tion/deep learning/multi-scale features分类
信息技术与安全科学引用本文复制引用
庞敏..国产多源卫片图斑智能提取平台研究与应用[J].自然资源遥感,2025,37(2):148-154,7.基金项目
2022山西省重点研发计划项目"山西太原城区国产卫星卫片图斑提取关键技术研究"(编号:202202010101005). （编号:202202010101005）
