Evaluation of Himawari-8/AHI land surface reflectance at mid-latitudes using LEO sensors with off-nadir observation

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Remote Sensing of Environment Pub Date : 2024-11-11 DOI:10.1016/j.rse.2024.114491
Beichen Zhang , Kazuhito Ichii , Wei Li , Yuhei Yamamoto , Wei Yang , Ram C. Sharma , Hiroki Yoshioka , Kenta Obata , Masayuki Matsuoka , Tomoaki Miura
{"title":"Evaluation of Himawari-8/AHI land surface reflectance at mid-latitudes using LEO sensors with off-nadir observation","authors":"Beichen Zhang ,&nbsp;Kazuhito Ichii ,&nbsp;Wei Li ,&nbsp;Yuhei Yamamoto ,&nbsp;Wei Yang ,&nbsp;Ram C. Sharma ,&nbsp;Hiroki Yoshioka ,&nbsp;Kenta Obata ,&nbsp;Masayuki Matsuoka ,&nbsp;Tomoaki Miura","doi":"10.1016/j.rse.2024.114491","DOIUrl":null,"url":null,"abstract":"<div><div>Land-surface reflectance (LSR) is a basic physical retrieval in terrestrial monitoring. The potential for high-frequency surface product estimation was evident in third-generation Geostationary Earth Orbit (3rd-GEO) satellites, substantially improving spectral, spatial, and temporal resolutions. Intercomparisons with LSR products from Low Earth Orbit (LEO) satellites have been employed as a common way to evaluate the LSRs of GEO satellites. However, in mid-latitude regions, comparing the LSR between two satellites is challenging due to constraints in the sun–target–sensor geometries. In this study, we proposed a method to obtain observations with consistent viewing and illumination conditions aligned with those of the Himawari-8/Advanced Himawari Imager (AHI) at mid-latitudes, by utilizing forward and backward viewing cameras from LEO sensors, such as Terra/Multi-angle Imaging SpectroRadiometer (MISR). The reflectance intercomparison revealed that the estimated AHI LSR closely matched the LSR from MISR in the red and near-infrared (NIR) bands at latitudes higher than 30°N/S during 2018–2019, with correlation coefficient (<em>r</em>) greater than 0.8 and a relative root mean square error (RRMSE) below 25 %. The data accuracy in the NIR bands was higher than in the red band, as indicated by a lower RRMSE. The correlation was also stronger in non-forested regions compared to forested areas, with higher <em>r</em> values. Additionally, screening observation pairs based on the relative azimuth angle (RAA), which assumes rotational symmetry in LSR, was examined and proved effective for GEO–LEO intercomparisons. This RAA-matching criterion enables reflectance intercomparisons across a wide longitude range at mid-latitudes, including areas like mainland China and New Zealand, where ray-matching is not applicable. The reflectance consistency demonstrated by RAA matches was comparable to that of ray matches, although the RAA-matching is constrained by timing due to the solar location. The findings from this study have potential applications for other satellites.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114491"},"PeriodicalIF":11.1000,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425724005170","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Land-surface reflectance (LSR) is a basic physical retrieval in terrestrial monitoring. The potential for high-frequency surface product estimation was evident in third-generation Geostationary Earth Orbit (3rd-GEO) satellites, substantially improving spectral, spatial, and temporal resolutions. Intercomparisons with LSR products from Low Earth Orbit (LEO) satellites have been employed as a common way to evaluate the LSRs of GEO satellites. However, in mid-latitude regions, comparing the LSR between two satellites is challenging due to constraints in the sun–target–sensor geometries. In this study, we proposed a method to obtain observations with consistent viewing and illumination conditions aligned with those of the Himawari-8/Advanced Himawari Imager (AHI) at mid-latitudes, by utilizing forward and backward viewing cameras from LEO sensors, such as Terra/Multi-angle Imaging SpectroRadiometer (MISR). The reflectance intercomparison revealed that the estimated AHI LSR closely matched the LSR from MISR in the red and near-infrared (NIR) bands at latitudes higher than 30°N/S during 2018–2019, with correlation coefficient (r) greater than 0.8 and a relative root mean square error (RRMSE) below 25 %. The data accuracy in the NIR bands was higher than in the red band, as indicated by a lower RRMSE. The correlation was also stronger in non-forested regions compared to forested areas, with higher r values. Additionally, screening observation pairs based on the relative azimuth angle (RAA), which assumes rotational symmetry in LSR, was examined and proved effective for GEO–LEO intercomparisons. This RAA-matching criterion enables reflectance intercomparisons across a wide longitude range at mid-latitudes, including areas like mainland China and New Zealand, where ray-matching is not applicable. The reflectance consistency demonstrated by RAA matches was comparable to that of ray matches, although the RAA-matching is constrained by timing due to the solar location. The findings from this study have potential applications for other satellites.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用低地轨道传感器对中纬度地区的 Himawari-8/AHI 陆面反射率进行离空观测评估
地表反射率(LSR)是陆地监测中的一项基本物理检索。第三代地球静止轨道(3rd-GEO)卫星大幅提高了光谱、空间和时间分辨率,高频地表产品估算的潜力显而易见。与低地球轨道(LEO)卫星的 LSR 产品进行相互比较是评估地球同步轨道卫星 LSR 的常用方法。然而,在中纬度地区,由于太阳-目标-传感器几何形状的限制,比较两颗卫星的 LSR 具有挑战性。在这项研究中,我们提出了一种方法,通过利用低地轨道传感器(如 Terra/多角度成像光谱辐射计)的前向和后向观测相机,在中纬度地区获得与 Himawari-8/Advanced Himawari Imager (AHI) 一致的观测和照明条件。反射比对结果显示,2018-2019年期间,在北纬30度/南纬30度以上的红外和近红外波段,估计的AHI LSR与MISR的LSR密切吻合,相关系数(r)大于0.8,相对均方根误差(RRMSE)低于25%。近红外波段的数据准确性高于红色波段,这体现在相对均方根误差(RRMSE)较低。与森林地区相比,非森林地区的相关性也更强,r 值更高。此外,还研究了基于相对方位角(RAA)的观测对筛选方法,该方法假定了 LSR 的旋转对称性,并被证明对 GEO-LEO 相互比较有效。这种相对方位角匹配标准能够在中纬度广泛的经度范围内进行反射率相互比较,包括中国大陆和新西兰等不适用射线匹配的地区。RAA 匹配所显示的反射率一致性与射线匹配不相上下,尽管 RAA 匹配受到太阳位置造成的时间限制。这项研究的结果有可能应用于其他卫星。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
期刊最新文献
Two-decade surface ozone (O3) pollution in China: Enhanced fine-scale estimations and environmental health implications Assessing lead fraction derived from passive microwave images and improving estimates at pixel-wise level Estimating anthropogenic CO2 emissions from China's Yangtze River Delta using OCO-2 observations and WRF-Chem simulations A dual-branch network for crop-type mapping of scattered small agricultural fields in time series remote sensing images From theory to hydrological practice: Leveraging CYGNSS data over seven years for advanced soil moisture monitoring
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1