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作 者:刘同文[1,2] 徐进达 薛立明 LIU Tongwen;XU Jinda;XUE Liming(Shandong GEO-Surveying&Mapping Institute,Jinan Shandong 250002,China;Big Data Center of Shandong Provincial Bureau of Geology&Mineral Resources,Jinan Shandong 250002,China)
机构地区:[1]山东省地质测绘院,山东济南250002 [2]山东省地矿局大数据中心,山东济南250002
出 处:《北京测绘》2023年第12期1581-1584,共4页Beijing Surveying and Mapping
摘 要:如何融合云计算、大数据、人工智能等先进技术手段,开展对遥感大数据的研究,进行遥感影像智能化处理,为空间智能应用提供更加精准、高效的数据支撑已成为必然,并具有广泛的应用前景。本文介绍了遥感大数据基本特征及研究现状,并运用深度神经网络等算法进行特征提取和目标识别,提出一种基于遥感大数据的智能监测方法,该方法结合了遥感技术和人工智能算法,通过对地表和大气信息的获取、分类和分析,实现了对城市环境、自然资源和生态系统的全面监测和管理。此外,开发了一套基于云计算和分布式处理的智能监测平台,该平台支持灵活的数据集成、可视化展示和实时预警功能,并已成功应用于城市的监测和管理任务中。It is inevitable to integrate advanced technologies such as cloud computing,big data,and artificial intelligence to study remote sensing big data,perform intelligent processing of remote sensing images,and provide more accurate and efficient data support for intelligent spatial applications,with broad application prospects.This paper introduced the basic features and research status of remote sensing big data and used algorithms such as deep neural networks for feature extraction and target recognition.An intelligent monitoring method based on remote sensing big data was proposed,which combined remote sensing technology and artificial intelligence algorithms to comprehensively monitor and manage urban environments,natural resources,and ecological systems through the acquisition,classification,and analysis of surface and atmospheric information.In addition,an intelligent monitoring platform based on cloud computing and distributed processing was developed,which had flexible data integration,visualization,and real-time warning functions,and it has been successfully applied in urban monitoring and management tasks.
分 类 号:P237[天文地球—摄影测量与遥感]
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