期刊文献+

志愿者民航客机夜光遥感方法与数据验证 被引量:1

Volunteered nighttime light remote sensing based on civil aviation aircraft platform
原文传递
导出
摘要 夜光遥感是遥感技术一个活跃的分支,能够反映人类社会活动的痕迹。在城市监测、经济参数评估、重大事件评估等方面有着独特的优势。近年来夜光数据的应用不断拓展,这对传统的卫星夜光遥感数据提出了更高的要求。本文基于大众遥感、志愿者遥感理念,提出了一种夜光遥感数据获取的新方法--民航客机遥感(PARS)。以长沙市为研究区域获取PARS夜光遥感影像,并将所得数据与传统卫星遥感数据作对比。结果表明,PARS捕获的夜光遥感数据在分辨率、波段及时效性上比传统方式表现得更为优秀,是一种低成本、灵活及多样化的遥感数据获取方式,具有很大的发展潜力。 As an active branch of remote sensing,nighttime light remote sensing can reflect the traces of human social activities. It has unique advantages in monitoring the city,assessing economic parameters and estimating the impact of major events. With the increasing maturity of data mining of night-light remote sensing,higher requirements are required for the traditional night-light remote sensing satellite. Based on concept of volunteered geographic information,this paper introduces a new method which is called PARS(passenger aircraft remote sensing). We capture night-light remote sensing image of Changsha using this method,and then compare the results with the traditional satellite remote sensing data. The data show that night-light remote sensing data captured by PARS has higher resolution,more bands and rapider revisit period than traditional remote sensing. To conclude,it is a low-cost,flexible and diversified remote sensing data acquisition method with great potential.
作者 宿瑞博 汪驰升 王永全 唐倩迪 SU Ruibo;WANG Chisheng;WANG Yongquan;TANG Qiandi(College of Civil And Traffic Engineering,Shenzhen University,Shenzhen 518060,China;Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Land and Resources,Shenzhen 518000,China;Guangdong Key Laboratory of Urban Informatics,School of Architecture&Urban Planning,Shenzhen University,Shenzhen 518060,China)
出处 《测绘通报》 CSCD 北大核心 2020年第4期87-90,95,共5页 Bulletin of Surveying and Mapping
基金 深圳市科创委研究项目(KQJSCX20180328093453763,JCYJ20180305125101282) 国土资源部城市土地资源监测与仿真重点实验室开放基金(KF-2018-03-004) 国家自然科学基金(41974006) 深圳大学教师启动项目(2018073)。
关键词 夜光遥感 民航客机遥感 志愿者遥感 数据验证 SFM算法 night-light remote sensing passenger aircraft remote sensing volunteered geographic information data validation SFM algorithm
  • 相关文献

参考文献12

二级参考文献125

共引文献575

同被引文献15

引证文献1

二级引证文献21

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部