沿海和内陆水域原位反射率的空间结构:对卫星验证的影响

Thomas M. Jordan, Stefan G. H. Simis, Nick Selmes, Giulia Sent, Federico Ienna, Victor Martinez-Vicente
{"title":"沿海和内陆水域原位反射率的空间结构:对卫星验证的影响","authors":"Thomas M. Jordan, Stefan G. H. Simis, Nick Selmes, Giulia Sent, Federico Ienna, Victor Martinez-Vicente","doi":"10.3389/frsen.2023.1249521","DOIUrl":null,"url":null,"abstract":"Validation of satellite-derived aquatic reflectance involves relating meter-scale in situ observations to satellite pixels with typical spatial resolution ∼ 10–100 m within a temporal “match-up window” of an overpass. Due to sub-pixel variation these discrepancies in measurement scale are a source of uncertainty in the validation result. Additionally, validation protocols and statistics do not normally account for spatial autocorrelation when pairing in situ data from moving platforms with satellite pixels. Here, using high-frequency autonomous mobile radiometers deployed on ships, we characterize the spatial structure of in situ R rs in inland and coastal waters (Lake Balaton, Western English Channel, Tagus Estuary). Using variogram analysis, we partition R rs variability into spatial and intrinsic (non-spatial) components. We then demonstrate the capacity of mobile radiometers to spatially sample in situ R rs within a temporal window broadly representative of satellite validation and provide spatial statistics to aid satellite validation practice. At a length scale typical of a medium resolution sensor (300 m) between 5% and 35% (median values across spectral bands and deployments) of the variation in in situ R rs was due to spatial separation. This result illustrates the extent to which mobile radiometers can reduce validation uncertainty due to spatial discrepancy via sub-pixel sampling. The length scale at which in situ R rs became spatially decorrelated ranged from ∼ 100–1,000 m. This information serves as a guideline for selection of spatially independent in situ R rs when matching with a satellite image, emphasizing the need for either downsampling or using modified statistics when selecting data to validate high resolution sensors (sub 100 m pixel size).","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial structure of in situ reflectance in coastal and inland waters: implications for satellite validation\",\"authors\":\"Thomas M. Jordan, Stefan G. H. Simis, Nick Selmes, Giulia Sent, Federico Ienna, Victor Martinez-Vicente\",\"doi\":\"10.3389/frsen.2023.1249521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Validation of satellite-derived aquatic reflectance involves relating meter-scale in situ observations to satellite pixels with typical spatial resolution ∼ 10–100 m within a temporal “match-up window” of an overpass. Due to sub-pixel variation these discrepancies in measurement scale are a source of uncertainty in the validation result. Additionally, validation protocols and statistics do not normally account for spatial autocorrelation when pairing in situ data from moving platforms with satellite pixels. Here, using high-frequency autonomous mobile radiometers deployed on ships, we characterize the spatial structure of in situ R rs in inland and coastal waters (Lake Balaton, Western English Channel, Tagus Estuary). Using variogram analysis, we partition R rs variability into spatial and intrinsic (non-spatial) components. We then demonstrate the capacity of mobile radiometers to spatially sample in situ R rs within a temporal window broadly representative of satellite validation and provide spatial statistics to aid satellite validation practice. At a length scale typical of a medium resolution sensor (300 m) between 5% and 35% (median values across spectral bands and deployments) of the variation in in situ R rs was due to spatial separation. This result illustrates the extent to which mobile radiometers can reduce validation uncertainty due to spatial discrepancy via sub-pixel sampling. The length scale at which in situ R rs became spatially decorrelated ranged from ∼ 100–1,000 m. This information serves as a guideline for selection of spatially independent in situ R rs when matching with a satellite image, emphasizing the need for either downsampling or using modified statistics when selecting data to validate high resolution sensors (sub 100 m pixel size).\",\"PeriodicalId\":198378,\"journal\":{\"name\":\"Frontiers in Remote Sensing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/frsen.2023.1249521\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frsen.2023.1249521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

卫星衍生的水生反射率的验证涉及在立交桥的时间“匹配窗口”内,将米尺度的原位观测与典型空间分辨率约10-100米的卫星像元相关联。由于亚像素的变化,这些测量尺度上的差异是验证结果不确定的来源。此外,当将来自移动平台的原位数据与卫星像素配对时,验证协议和统计通常不会考虑空间自相关性。在这里,我们使用部署在船上的高频自主移动辐射计,表征了内陆和沿海水域(巴拉顿湖、西英吉利海峡、塔霍斯河口)原位R rs的空间结构。利用变异函数分析,我们将rrs变异性划分为空间和内在(非空间)成分。然后,我们展示了移动辐射计在一个广泛代表卫星验证的时间窗口内对原位R rs进行空间采样的能力,并提供空间统计数据来帮助卫星验证实践。在典型的中等分辨率传感器(300米)的长度尺度上,5%至35%(跨光谱带和部署的中值)的原位R rs变化是由空间分离引起的。这一结果说明了移动辐射计可以通过亚像素采样减少由于空间差异造成的验证不确定性的程度。原位rrs在空间上去相关的长度尺度为~ 100-1,000 m。该信息可作为与卫星图像匹配时选择空间独立的原位R rs的指南,强调在选择数据以验证高分辨率传感器(低于100 m像素尺寸)时需要降低采样或使用修改的统计数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Spatial structure of in situ reflectance in coastal and inland waters: implications for satellite validation
Validation of satellite-derived aquatic reflectance involves relating meter-scale in situ observations to satellite pixels with typical spatial resolution ∼ 10–100 m within a temporal “match-up window” of an overpass. Due to sub-pixel variation these discrepancies in measurement scale are a source of uncertainty in the validation result. Additionally, validation protocols and statistics do not normally account for spatial autocorrelation when pairing in situ data from moving platforms with satellite pixels. Here, using high-frequency autonomous mobile radiometers deployed on ships, we characterize the spatial structure of in situ R rs in inland and coastal waters (Lake Balaton, Western English Channel, Tagus Estuary). Using variogram analysis, we partition R rs variability into spatial and intrinsic (non-spatial) components. We then demonstrate the capacity of mobile radiometers to spatially sample in situ R rs within a temporal window broadly representative of satellite validation and provide spatial statistics to aid satellite validation practice. At a length scale typical of a medium resolution sensor (300 m) between 5% and 35% (median values across spectral bands and deployments) of the variation in in situ R rs was due to spatial separation. This result illustrates the extent to which mobile radiometers can reduce validation uncertainty due to spatial discrepancy via sub-pixel sampling. The length scale at which in situ R rs became spatially decorrelated ranged from ∼ 100–1,000 m. This information serves as a guideline for selection of spatially independent in situ R rs when matching with a satellite image, emphasizing the need for either downsampling or using modified statistics when selecting data to validate high resolution sensors (sub 100 m pixel size).
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A near-real-time tropical deforestation monitoring algorithm based on the CuSum change detection method Suitability of different in-water algorithms for eutrophic and absorbing waters applied to Sentinel-2 MSI and Sentinel-3 OLCI data Sea surface barometry with an O2 differential absorption radar: retrieval algorithm development and simulation Assessment of advanced neural networks for the dual estimation of water quality indicators and their uncertainties Selecting HyperNav deployment sites for calibrating and validating PACE ocean color observations
×
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