摘要
夜光遥感作为遥感应用研究的一个重要分支,能够直观地反映人类的夜间活动,具有数据易获取、覆盖范围广以及时效快等优势,在多尺度、长时间序列的城市研究方面具有广阔的应用前景。目前,基于夜光遥感数据的应用研究成果较为丰富,不少学者开展了夜光遥感数据预处理及应用潜力分析。然而,由于夜光遥感传感器存在局限性,当前多源夜光遥感数据仍存在数据间不可对比和不连续性等问题,为此许多学者开展了夜光遥感数据校正研究。近年来学者发文量不断增长,数量从几篇增加到几百篇。基于此,文章对近年来多源夜光遥感数据相互校正的研究成果进行详细梳理,从DMSP/OLS数据的校正、DMSP/OLS与NPP/VIIRS数据的相互校正、夜光遥感数据的去饱和现象以及去溢出效应共4个方面,对多源夜光遥感数据的校正研究进行了述评和前景展望。
As an important branch of remote sensing application research,nighttime light remote sensing can directly reflect human activities at night.It has the advantages of easy access,wide coverage and fast time efficiency,and has broad application prospects in multi-scale,long time series urban research.At present,the application research achievements based on the nighttime light remote sensing data are relatively rich.Many scholars have carried out pre-processing and application potential analysis of nightlight remote sensing data.However,due to the limitations of the satellite system,the current multi-source nighttime light remote sensing data still has problems such as non-comparability and discontinuity between data,and for this reason,many scholars have conducted research on the correction of nighttime light remote sensing data.The number of scholarly publications has been increasing in recent years,from a few to several hundred.Based on this,this paper presents a detailed review of recent research results on the inter-correction of multi-source nighttime light remote sensing data in recent years,reviews and prospects for the correction of multi-source night-light remote sensing data in four aspects,which are the calibration of DMSP/OLS data,the mutual calibration of DMSP/OLS and NPP/VIIRS data,the desaturation phenomenon of nightlight remote sensing data and blooming effect correction.
作者
郑渊茂
杨可欣
范孟琳
陈炳凝
何原荣
ZHENG Yuanmao;YANG Kexin;FAN Menglin;CHEN Bingning;HE Yuanrong(School of Environmental Science and Engineering,Xiamen University of Technology,Xiamen,Fujian 361024,China;Big Data Institute of Digital Natural Disaster Monitoring in Fujian,Xiamen University of Technology,Xiamen,Fujian 361024,China)
出处
《遥感信息》
CSCD
北大核心
2023年第4期1-11,共11页
Remote Sensing Information
基金
福建省自然科学基金面上项目(2022J011229)
宁夏回族自治区重点研发计划项目(2021BECO3001)
龙岩市产学研联合创新项目(2022LYF18001)
厦门理工学院高层次人才科研启动项目(YKJ22010R)。