摘要
近年来,卫星遥感定量产品逐渐成为我国行业应用的重要输入,广泛服务自然资源、生态环境、气象、海洋和地球系统研究等领域。尽管各类遥感卫星数量急速增长,但是由于不同卫星系统的数据格式、处理方法和应用领域存在差异,遥感数据的广泛使用受到严重制约。为了降低遥感数据的使用门槛,文章按照遥感信息模型与数据工程模型,提出具有数据方块(Data Square,DS)形式的标准化遥感定量产品。在统一的地理格网框架下,对多源时空数据进行规格化组织,以观测对象几何、辐射、分类、理化生参数等4种控制样本的数据方块作为相对真值约束,面向不同星座、卫星、遥感器在不同时间和地点获取的数据方块集合开展合成产品生产,形成时、空间一致的遥感标准定量产品和编码,并开展应用示范。通过对比当前常见的“分析即用数据”(Analysis Ready Data,ARD)模型和标准化处理方法,利用文章提出的卫星遥感定量产品标准化技术,可从不同观测时刻、角度和方式提升数据的全面性、准确性和可靠性,促进不同星座间的数据互补,为“百星百用”的遥感工业化愿景提供技术支撑。
Recently,quantitative products of space-borne remote sensing have gradually become important inputs for various applications in China,widely serving fields such as meteorology,oceanography,natural resources,ecological environment,and Earth system research.Although the rapid growth in the number of remote sensing satellites,the widespread use of remote sensing data is severely restricted due to their differences in data formats,processing methods,and application fields of different satellite systems.To reduce the threshold for using remote sensing data,we proposed a standardized data product model based on Data Square(DS)according to the remote sensing information model and data engineering model.The multi-source spatio-temporal data are normalized and organized under a unified geographic grid framework from the perspectives of data product levels,observation methods,and product attributes.Four types of control samples,namely geometric,radiometric,classification,and parametric,are applied for the relative truth constraints of data squares.Synthetic product production is carried out for data square collections acquired by different constellations,satellites,and remote sensors at different times and locations,forming spatio-temporally consistent remote sensing standard quantitative products and file codes.The advantages and disadvantages of the proposed models are further investigated for the existing Analysis Ready Data(ARD)models in the space-borne remote sensing,providing technical support for the vision of universal application across multiple satellites.
作者
吴俣
余涛
占玉林
郑利娟
王更科
谢东海
米晓飞
张丽丽
王春梅
刘川
臧文乾
黄祥志
郭颜铭
王宝玉
李娟
WU Yu;YU Tao;ZHAN Yulin;ZHENG Lijuan;WANG Gengke;XIE Donghai;MI Xiaofei;ZHANG Lili;WANG Chunmei;LIU Chuan;ZANG Wenqian;HUANG Xiangzhi;GUO Yanming;WANG Baoyu;LI Juan(School of Earth System Science,Tianjin University,Tianjin 300072,China;Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China;Demonstration Center for Spaceborne Remote Sensing,China National Space Administration,Beijing 100101,China;Land Satellite Remote Sensing Application Center,MNR,Beijing 100048,China;College of Resource Environment and Tourism,Capital Normal University,Beijing 100048,China;Zhongke Xingtong(Langfang)Information Technology Co.,Ltd.,Langfang 065000,China;Langfang Research and Development Center for Spatial Information Technology,Langfang 065099,China)
出处
《航天返回与遥感》
北大核心
2025年第4期27-37,共11页
Spacecraft Recovery & Remote Sensing
基金
国家重点研发计划(2022YFB3902200)
国家自然科学基金(42071318)
国防基础科研计划项目(JCKY2020908B001)。
关键词
卫星遥感
标准定量产品
分析即用数据
数据方块
相对真值
space-borne remote sensing
standard quantitative products
Analysis Ready Data(ARD)
Data Square(DS)
relative truth
