Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRS
The accuracy of remote-sensing reflectance (<inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </m...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/20/2400 |
| _version_ | 1798018494120329216 |
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| author | Jun Li Cédric Jamet Jianhua Zhu Bing Han Tongji Li Anan Yang Kai Guo Di Jia |
| author_facet | Jun Li Cédric Jamet Jianhua Zhu Bing Han Tongji Li Anan Yang Kai Guo Di Jia |
| author_sort | Jun Li |
| collection | DOAJ |
| description | The accuracy of remote-sensing reflectance (<inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>) estimated from ocean color imagery through the atmospheric correction step is essential in conducting quantitative estimates of the inherent optical properties and biogeochemical parameters of seawater. Therefore, finding the main source of error is the first step toward improving the accuracy of <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>. However, the classic validation exercises provide only the total error of the retrieved <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>. They do not reveal the error sources. Moreover, how to effectively improve this satellite algorithm remains unknown. To better understand and improve various aspects of the satellite atmospheric correction algorithm, the error budget in the validation is required. Here, to find the primary error source from the OLCI <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>, we evaluated the OLCI <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula> product with in-situ data around the China Sea from open ocean to coastal waters and compared them with the MODIS-AQUA and VIIRS products. The results show that the performances of OLCI are comparable to those MODIS-AQUA. The average percentage difference (APD) in <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula> is lowest at 490 nm (18%), and highest at 754 nm (79%). A more detailed analysis reveals that open ocean and coastal waters show opposite results: compared to coastal waters the satellite <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula> in open seas are higher than the in-situ measured values. An error budget for the three satellite-derived <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula> products is presented, showing that the primary error source in the China Sea was the aerosol estimation and the error on the Rayleigh-corrected radiance for OLCI, as well as for MODIS and VIIRS. This work suggests that to improve the accuracy of Sentinel-3A in the coastal waters of China, the accuracy of aerosol estimation in atmospheric correction must be improved. |
| first_indexed | 2024-04-11T16:24:54Z |
| format | Article |
| id | doaj.art-d6adce1f4add46769ccc63598bac17b9 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T16:24:54Z |
| publishDate | 2019-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-d6adce1f4add46769ccc63598bac17b92022-12-22T04:14:13ZengMDPI AGRemote Sensing2072-42922019-10-011120240010.3390/rs11202400rs11202400Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRSJun Li0Cédric Jamet1Jianhua Zhu2Bing Han3Tongji Li4Anan Yang5Kai Guo6Di Jia7National Ocean Technology Center, State Oceanic Administration, Tianjin 300112, ChinaUniv. Littoral Cote d’Opale, Univ. Lille, CNRS, UMR 8187, LOG, Laboratoire d’Océanologie et de Géosciences, 62930 Wimereux, FranceNational Ocean Technology Center, State Oceanic Administration, Tianjin 300112, ChinaNational Ocean Technology Center, State Oceanic Administration, Tianjin 300112, ChinaNational Ocean Technology Center, State Oceanic Administration, Tianjin 300112, ChinaNational Ocean Technology Center, State Oceanic Administration, Tianjin 300112, ChinaNational Ocean Technology Center, State Oceanic Administration, Tianjin 300112, ChinaNational Ocean Technology Center, State Oceanic Administration, Tianjin 300112, ChinaThe accuracy of remote-sensing reflectance (<inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>) estimated from ocean color imagery through the atmospheric correction step is essential in conducting quantitative estimates of the inherent optical properties and biogeochemical parameters of seawater. Therefore, finding the main source of error is the first step toward improving the accuracy of <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>. However, the classic validation exercises provide only the total error of the retrieved <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>. They do not reveal the error sources. Moreover, how to effectively improve this satellite algorithm remains unknown. To better understand and improve various aspects of the satellite atmospheric correction algorithm, the error budget in the validation is required. Here, to find the primary error source from the OLCI <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula>, we evaluated the OLCI <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula> product with in-situ data around the China Sea from open ocean to coastal waters and compared them with the MODIS-AQUA and VIIRS products. The results show that the performances of OLCI are comparable to those MODIS-AQUA. The average percentage difference (APD) in <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula> is lowest at 490 nm (18%), and highest at 754 nm (79%). A more detailed analysis reveals that open ocean and coastal waters show opposite results: compared to coastal waters the satellite <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula> in open seas are higher than the in-situ measured values. An error budget for the three satellite-derived <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics> </math> </inline-formula> products is presented, showing that the primary error source in the China Sea was the aerosol estimation and the error on the Rayleigh-corrected radiance for OLCI, as well as for MODIS and VIIRS. This work suggests that to improve the accuracy of Sentinel-3A in the coastal waters of China, the accuracy of aerosol estimation in atmospheric correction must be improved.https://www.mdpi.com/2072-4292/11/20/2400olcimodisviirsremote-sensing reflectance (<i>r<sub>rs</sub></i>)error budgetchina sea |
| spellingShingle | Jun Li Cédric Jamet Jianhua Zhu Bing Han Tongji Li Anan Yang Kai Guo Di Jia Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRS Remote Sensing olci modis viirs remote-sensing reflectance (<i>r<sub>rs</sub></i>) error budget china sea |
| title | Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRS |
| title_full | Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRS |
| title_fullStr | Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRS |
| title_full_unstemmed | Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRS |
| title_short | Error Budget in the Validation of Radiometric Products Derived from OLCI around the China Sea from Open Ocean to Coastal Waters Compared with MODIS and VIIRS |
| title_sort | error budget in the validation of radiometric products derived from olci around the china sea from open ocean to coastal waters compared with modis and viirs |
| topic | olci modis viirs remote-sensing reflectance (<i>r<sub>rs</sub></i>) error budget china sea |
| url | https://www.mdpi.com/2072-4292/11/20/2400 |
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