摘要
以卫星影像大数据和时空数据挖掘技术为基础,采用深度学习框架支撑,构建了面向新增建设用地遥感监测应用需求的深度学习训练平台,可智能发现自然资源督察线索,全面提高自然资源督察问题的发现能力。该技术可广泛服务于大范围、高频次的督察工作,为督察工作提供更及时客观全面的信息基础和保障。
Based on satellite image big data and spatio-temporal data mining technology,supported by deep learning framework,we constructed a deep learning training platform for the application needs of remote sensing monitoring of newly increased construction land.This platform can intelligently discover the natural resource supervision clues,and comprehensively improve the ability of the natural resource supervision.The technology can be widely used to meet the needs of largescale and high-frequency supervision work,and provide more timely,objective and comprehensive information basis and information guarantee for supervision work.
出处
《地理空间信息》
2021年第1期53-54,I0006,共3页
Geospatial Information
基金
湖北省自然资源厅科技资助项目(ZRZY2020KJ09)。
关键词
新增建设用地
自然资源督察
遥感解译
智能化提取
深度学习
newly increased construction land
natural resource supervision
remote sensing interpretation
intelligent extraction
deep learning
