摘要
本文利用深度学习解译技术,建立自然资源样本库,构建地物分类模型,实现遥感影像自然资源信息自动提取,并对解译结果进行精度评价。结果表明,基于深度学习技术的解译效果较为理想,能提升解译精度和效率,为建立高效、完善的自然资源遥感监测服务体系提供了先进的技术手段。
Deep learning interpretation technology is used to establish a natural resource sample database,construct the feature classification model,realize automatic extraction of natural resource information from remote sensing images,and evaluate the accuracy of interpretation results in this paper.The results show that the deep learning technology can create an ideal effect and greatly improve the interpretation accuracy and efficiency,provide advanced technical method for the establishment of efficient and perfect remote sensing monitoring service system of natural resources.
作者
叶萍萍
YE Pingping(Gansu Province Basic Geographic Information Center,Lanzhou,Gansu 730000,China)
出处
《测绘技术装备》
2023年第1期36-40,共5页
Geomatics Technology and Equipment
关键词
深度学习
遥感影像
自然资源监测
信息提取
deep learning
remote sensing images
natural resources monitoring
information extraction