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1.武汉大学遥感信息工程学院,湖北 武汉,430079
2.武汉大学测绘遥感信息工程全国重点实验室,湖北 武汉,430079
3.中国科学院空天信息创新研究院遥感与数字地球全国重点实验室,北京,100094
4.武汉大学资源与环境科学学院,湖北 武汉,430079
Received:10 December 2025,
Published:05 January 2026
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李德仁,秦昆,张过,等.社会遥感地理计算的研究进展与创新[J].武汉大学学报(信息科学版),2026,51(1):1-21.
LI Deren,QIN Kun,ZHANG Guo,et al.Development and Innovation of Geo-computation for Social Remote Sensing[J].Geomatics and Information Science of Wuhan University,2026,51(1):1-21.
李德仁,秦昆,张过,等.社会遥感地理计算的研究进展与创新[J].武汉大学学报(信息科学版),2026,51(1):1-21. DOI:10.13203/j.whugis20250371
LI Deren,QIN Kun,ZHANG Guo,et al.Development and Innovation of Geo-computation for Social Remote Sensing[J].Geomatics and Information Science of Wuhan University,2026,51(1):1-21. DOI:10.13203/j.whugis20250371
遥感已经从传统的对地观测发展到既对地观测,也对人、对社会进行观测。遥感地理信息科学与技术、计算理论与方法,与社会人文科学不断交叉融合,形成了一个新的交叉学科方向——社会遥感地理计算。首先提出了社会遥感地理计算的概念及研究框架,然后系统阐述了社会遥感地理计算的学科分支及研究进展(包括遥感经济学、遥感新闻学、遥感国际关系分析、遥感战场环境监测、遥感健康环境分析等),探索了社会遥感地理计算的研究方法(包括空中视角与空间思维、时空智能、社会感知与社会计算、地理计算与社会地理计算、空间数据挖掘与夜光遥感、时空大数据与人工智能、遥感大模型与知识图谱、地理空间优化,以及相关软件工具和平台等),最后对社会遥感地理计算的关键问题和未来发展方向进行了总结和展望。
Remote sensing has evolved from traditional Earth observation to observation of both the Earth and people (society). Remote sensing and geographic information science
computational science
and social sciences are increasingly intersecting and merging
forming an innovative interdisciplinary field: Geo-computing for social remote sensing. First
we propose the concept and research framework of geo-computation for social remote sensing
and systematically elucidate the disciplinary branches of geo-computation for social remote sensing and their research progress
including remote sensing economics
remote sensing journalism
remote sensing and international relations analysis
battlefield environment remote sensing monitoring
remote sensing and health environment analysis
and so on. Second
theories and methods of geo-computation for social remote sensing are explored
including aerial perspective and spatial thinking
spatiotemporal intelligence
social sensing and social computation
geo-computation and geo-computation for social sciences
spatial data mining and nighttime light remote sensing
spatiotemporal big data and artificial intelligence
remote sensing large models and knowledge graphs
geospatial optimization
as well as software tools and platforms. Finally
the key issues and future development directions of geo-computation for social remote sensing are summarized and prospected.
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