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

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Remote Sensing of Environment Pub Date : 2024-09-19 DOI:10.1016/j.rse.2024.114407
Shuai Gao , Xiaoyang Zhang , Hankui K. Zhang , Yu Shen , David P. Roy , Weile Wang , Crystal Schaaf
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引用次数: 0

摘要

地球静止业务环境卫星-R 系列(GOES-R)上的高级基线成像仪(ABI)传感器拓宽了全球植被监测的应用范围,因为与以前的地球静止和当前的极轨传感系统相比,它们具有更高的时间分辨率(5-15 分钟)和适当的空间分辨率(0.5-1 公里)。值得注意的是,与传统的地球同步实用环境卫星和中分辨率成像分光仪(MODIS)和可见光红外成像辐射计套件(VIIRS)等极地轨道传感器的观测数据相比,ABI 陆面气候学(LSP)无云观测数据的可用性更高,因此其量化能力可能会得到改善。地球静止卫星以固定的视角几何图形和不断变化的太阳几何图形感知位置,因此能捕捉到各向异性表面上明显的时间反射率变化。通过应用双向反射分布函数(BRDF)模型来调整或预测新的太阳几何图形和固定视图几何图形的反射率,可以减少这些反射率变化。经验和半经验 BRDF 模型在预测用于参数化模型的观测数据中未发现的角度所获得的反射率时,或在太阳和观测方向重合的热点感应条件下所获得的反射率时,效果较差。因此,使用固定的太阳几何图形,甚至是当地太阳正午时的几何图形,可能会因太阳位置的昼夜变化和季节变化以及热点感应条件的发生而产生误差。本文提出了一种基于恒定散射角(CSA)准则的新的太阳几何定义,正如我们所证明的,它可减少太阳几何变化对反射率和用于低纬度植被指数量化的衍生植被指数的影响。CSA 标准与 Ross-Thick-Li-Sparse (RTLS) BRDF 模型一起应用于 GOES-16 (2018 年 1 月 1 日至 2020 年 12 月 31 日)和 GOES-17 (2019 年 1 月 1 日至 2020 年 12 月 31 日)获取的北美 ABI 表面反射率数据,以归一化太阳几何 BRDF 影响并生成 3 天双波段增强植被指数 (EVI2) 时间序列。与当地太阳正午几何相比,CSA 标准可减少太阳几何反射率和 EVI2 时间序列伪差。此外,还介绍了与同期 VIIRS NBAR(Nadir BRDF 调整反射率)EVI2 时间序列的比较,以说明 CSA 标准的功效。最后,经 CSA 调整的 EVI2 时间序列所产生的 LSP 结果与基于 PhenoCam 的观测结果非常吻合,在植被成熟、衰老和休眠日期的启动方面没有明显的系统性偏差,而经当地太阳正午调整的 EVI2 时间序列则存在约 10 天的偏差。
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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.

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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.
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