Shuai Gao , Xiaoyang Zhang , Hankui K. Zhang , Yu Shen , David P. Roy , Weile Wang , Crystal Schaaf
{"title":"用于 GOES-R ABI 反射率时间序列归一化的新的恒定散射角太阳几何定义,以支持陆地表面物候学研究","authors":"Shuai Gao , Xiaoyang Zhang , Hankui K. Zhang , Yu Shen , David P. Roy , Weile Wang , Crystal Schaaf","doi":"10.1016/j.rse.2024.114407","DOIUrl":null,"url":null,"abstract":"<div><p>The Advanced Baseline Imager (ABI) sensors on the Geostationary Operational Environment Satellite-R series (GOES-R) broaden the application of global vegetation monitoring due to their higher temporal (5–15 min) and appropriate spatial (0.5–1 km) resolution compared to previous geostationary and current polar-orbiting sensing systems. Notably, ABI Land Surface Phenology (LSP) quantification may be improved due to the greater availability of cloud-free observations as compared to those from legacy GOES satellite generations and from polar-orbiting sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS). Geostationary satellites sense a location with a fixed view geometry but changing solar geometry and consequently capture pronounced temporal reflectance variations over anisotropic surfaces. These reflectance variations can be reduced by application of a Bidirectional Reflectance Distribution Function (BRDF) model to adjust or predict the reflectance for a new solar geometry and a fixed view geometry. Empirical and semi-empirical BRDF models perform less effectively when used to predict reflectance acquired at angles not found in the observations used to parameterize the model, or acquired under hot-spot sensing conditions when the solar and viewing directions coincide. Consequently, using a fixed solar geometry or even the geometry at local solar noon may introduce errors due to diurnal and seasonal variations in the position of the sun and the incidence of hot-spot sensing conditions. In this paper, a new solar geometry definition based on a Constant Scattering Angle (CSA) criterion is presented that, as we demonstrate, reduces the impacts of solar geometry changes on reflectance and derived vegetation indices used for LSP quantification. The CSA criterion is used with the Ross-Thick-Li-Sparse (RTLS) BRDF model applied to North America ABI surface reflectance data acquired by GOES-16 (1 January 2018 to 31 December 2020) and GOES-17 (1 January 2019 to 31 December 2020) to normalize solar geometry BRDF effects and generate 3-day two-band Enhanced Vegetation Index (EVI2) time series. Compared to the local solar noon geometry, the CSA criterion is shown to reduce solar geometry reflectance and EVI2 time series artifacts. Further, comparison with contemporaneous VIIRS NBAR (Nadir BRDF-Adjusted Reflectance) EVI2 time series is also presented to illustrate the efficacy of the CSA criterion. Finally, the CSA-adjusted EVI2 time series are shown to produce LSP results that agree well with PhenoCam-based observations, with no obvious systematic bias in onsets of vegetation maturity, senescence, and dormancy dates compared to about 10-day bias found with local solar noon adjusted EVI2 time series.</p></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"315 ","pages":"Article 114407"},"PeriodicalIF":11.1000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new constant scattering angle solar geometry definition for normalization of GOES-R ABI reflectance times series to support land surface phenology studies\",\"authors\":\"Shuai Gao , Xiaoyang Zhang , Hankui K. Zhang , Yu Shen , David P. Roy , Weile Wang , Crystal Schaaf\",\"doi\":\"10.1016/j.rse.2024.114407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The Advanced Baseline Imager (ABI) sensors on the Geostationary Operational Environment Satellite-R series (GOES-R) broaden the application of global vegetation monitoring due to their higher temporal (5–15 min) and appropriate spatial (0.5–1 km) resolution compared to previous geostationary and current polar-orbiting sensing systems. Notably, ABI Land Surface Phenology (LSP) quantification may be improved due to the greater availability of cloud-free observations as compared to those from legacy GOES satellite generations and from polar-orbiting sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS). Geostationary satellites sense a location with a fixed view geometry but changing solar geometry and consequently capture pronounced temporal reflectance variations over anisotropic surfaces. These reflectance variations can be reduced by application of a Bidirectional Reflectance Distribution Function (BRDF) model to adjust or predict the reflectance for a new solar geometry and a fixed view geometry. Empirical and semi-empirical BRDF models perform less effectively when used to predict reflectance acquired at angles not found in the observations used to parameterize the model, or acquired under hot-spot sensing conditions when the solar and viewing directions coincide. Consequently, using a fixed solar geometry or even the geometry at local solar noon may introduce errors due to diurnal and seasonal variations in the position of the sun and the incidence of hot-spot sensing conditions. In this paper, a new solar geometry definition based on a Constant Scattering Angle (CSA) criterion is presented that, as we demonstrate, reduces the impacts of solar geometry changes on reflectance and derived vegetation indices used for LSP quantification. The CSA criterion is used with the Ross-Thick-Li-Sparse (RTLS) BRDF model applied to North America ABI surface reflectance data acquired by GOES-16 (1 January 2018 to 31 December 2020) and GOES-17 (1 January 2019 to 31 December 2020) to normalize solar geometry BRDF effects and generate 3-day two-band Enhanced Vegetation Index (EVI2) time series. Compared to the local solar noon geometry, the CSA criterion is shown to reduce solar geometry reflectance and EVI2 time series artifacts. Further, comparison with contemporaneous VIIRS NBAR (Nadir BRDF-Adjusted Reflectance) EVI2 time series is also presented to illustrate the efficacy of the CSA criterion. Finally, the CSA-adjusted EVI2 time series are shown to produce LSP results that agree well with PhenoCam-based observations, with no obvious systematic bias in onsets of vegetation maturity, senescence, and dormancy dates compared to about 10-day bias found with local solar noon adjusted EVI2 time series.</p></div>\",\"PeriodicalId\":417,\"journal\":{\"name\":\"Remote Sensing of Environment\",\"volume\":\"315 \",\"pages\":\"Article 114407\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2024-09-19\",\"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/S0034425724004334\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425724004334","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}
A new constant scattering angle solar geometry definition for normalization of GOES-R ABI reflectance times series to support land surface phenology studies
The Advanced Baseline Imager (ABI) sensors on the Geostationary Operational Environment Satellite-R series (GOES-R) broaden the application of global vegetation monitoring due to their higher temporal (5–15 min) and appropriate spatial (0.5–1 km) resolution compared to previous geostationary and current polar-orbiting sensing systems. Notably, ABI Land Surface Phenology (LSP) quantification may be improved due to the greater availability of cloud-free observations as compared to those from legacy GOES satellite generations and from polar-orbiting sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS). Geostationary satellites sense a location with a fixed view geometry but changing solar geometry and consequently capture pronounced temporal reflectance variations over anisotropic surfaces. These reflectance variations can be reduced by application of a Bidirectional Reflectance Distribution Function (BRDF) model to adjust or predict the reflectance for a new solar geometry and a fixed view geometry. Empirical and semi-empirical BRDF models perform less effectively when used to predict reflectance acquired at angles not found in the observations used to parameterize the model, or acquired under hot-spot sensing conditions when the solar and viewing directions coincide. Consequently, using a fixed solar geometry or even the geometry at local solar noon may introduce errors due to diurnal and seasonal variations in the position of the sun and the incidence of hot-spot sensing conditions. In this paper, a new solar geometry definition based on a Constant Scattering Angle (CSA) criterion is presented that, as we demonstrate, reduces the impacts of solar geometry changes on reflectance and derived vegetation indices used for LSP quantification. The CSA criterion is used with the Ross-Thick-Li-Sparse (RTLS) BRDF model applied to North America ABI surface reflectance data acquired by GOES-16 (1 January 2018 to 31 December 2020) and GOES-17 (1 January 2019 to 31 December 2020) to normalize solar geometry BRDF effects and generate 3-day two-band Enhanced Vegetation Index (EVI2) time series. Compared to the local solar noon geometry, the CSA criterion is shown to reduce solar geometry reflectance and EVI2 time series artifacts. Further, comparison with contemporaneous VIIRS NBAR (Nadir BRDF-Adjusted Reflectance) EVI2 time series is also presented to illustrate the efficacy of the CSA criterion. Finally, the CSA-adjusted EVI2 time series are shown to produce LSP results that agree well with PhenoCam-based observations, with no obvious systematic bias in onsets of vegetation maturity, senescence, and dormancy dates compared to about 10-day bias found with local solar noon adjusted EVI2 time series.
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.