Atmospheric Correction Over Coastal Turbid Waters of Bay of Bengal Using OCEANSAT-I Ocean Colour Monitor (OCM) Data

Space-borne ocean-colour remote sensor-detected radiance is heavily contaminated by solar radiation backscattered by the atmospheric air molecules and aerosols. Hence, the first step in ocean-colour data processing is the removal of this atmospheric contribution from the sensor-detected radiance to enable detection of optically active oceanic constituents e.g. chlorophyll-a, suspended sediment etc. In standard atmospheric correction procedure for OCEANSAT-1 Ocean Colour Monitor (OCM) data, NIR bands centered at 765 and 865 nm wavelengths were used for aerosol characterization. Due to high absorption by water molecules, ocean surface in these two wavelengths acts as dark background, therefore, sensor detected radiance can be assumed to have major contribution from atmospheric scattering. For coastal turbid waters this assumption of dark surface fails due to the presence of highly scattering sediments which causes sufficient water-leaving radiance in NIR bands and lead to over-estimation of aerosol radiance resulting in negative water leaving radiance for λ < 700 nm. In the present study, for the turbid coastal waters in the northern Bay of Bengal, the concept of spatial homogeneity of aerosol and water leaving reflectance has been applied to perform atmospheric correction of OCAEANSAT-1 OCM data. The results of the turbid water atmospheric correction have also been validated using in-situ measured water-leaving radiance. Comparison of satellite derived water-leaving radiance for five coastal stations with in-situ measured radiance spectra, indicates an improvement over the standard atmospheric correction algorithm giving physically realistic and positive values. Root Mean Square Error (RMSE) between the in-situ measured and satellite derived water leaving radiance for wavelengths 412 nm, 443 nm, 490 nm, 512 nm and 555 nm was found to be 1.11, 0.718, 0.575, 0.611 and 0.651%, respectively, using standard atmospheric correction procedure. By the use of spatial homogeneity concept, this error was reduced to 0.125, 0.173, 0.176, 0.225, and 0.290 and the correlation coefficient arrived at 0.945, which is an improvement over the standard atmospheric correction procedure.     

扩展多波长偏振测量的太阳—天空辐射计观测网

太阳辐射和大气气溶胶的地基遥感观测在气候变化、大气环境和对地观测等领域有重要意义。结合多波长偏振测量技术在气溶胶观测中的应用,本文介绍了在中国典型区域建立的太阳—天空辐射计观测网SONET(Sunsky radiometer Oberservation NETwork)。主要内容包括:(1)多波长偏振太阳—天空辐射计的参数、基本原理和功能,以及据此建立的中国区域太阳—天空辐射计观测网及其站点的基本情况;(2)太阳直射、太阳主平面和平纬圈几何条件下,太阳—天空辐射和偏振的观测模式及其测量参数;(3)针对气溶胶、水汽等大气成分观测发展的太阳直射辐射、天空光辐亮度、线偏振度等观测量的定标和数据处理方法,并给出在晴朗和灰霾等天气下的SONET观测结果示例;(4)基于在SONET典型站点连续的较长期遥感观测,初步建立了城市、乡村和灰霾情况下的整层大气气溶胶参数模型。在扩展多波长偏振测量的基础上,SONET还发展了自动观测、快速数据处理、定期标定和维护等观测网运行关键技术,可为典型大气气溶胶模型构建、卫星气溶胶产品反演和验证、大气环境遥感监测等应用提供支撑。     

基于葵花-8卫星大气产品的地表下行短波辐射计算

地表下行短波辐射DSSR(Downward Surface Shortwave Radiation)的准确估算在气候变化研究和地表太阳能估算等领域具有重要作用。新一代静止气象卫星葵花-8(Himawari-8)具有高达10 min的对地观测能力,为DSSR近实时估算提供了新机遇。然而,日本宇宙航空研究开发机构(JAXA)对外公开的葵花-8辐射产品中,没有将其反演的云、气溶胶产品作为DSSR的输入参数,从而没有形成一整套的DSSR估算算法流程,缺乏产品输出的一致性。大气中的云、气溶胶是DSSR的重要影响因子,本文重点考虑云、气溶胶对太阳辐射的影响,基于大气辐射传输模式RSTAR构建了DSSR查找表,开发了DSSR的快速计算方法,进而将JAXA葵花-8二级云、气溶胶产品(光学厚度,粒子有效半径等)作为快速化计算方法的输入参量,计算得到了DSSR。通过与JAXA葵花-8二级DSSR产品(JAXA DSSR)对比,发现两者具有很好的空间一致性。为了进一步评价本文的DSSR计算精度,分别选取了陆地(Yonsei)和海洋(0n_165e)的观测数据验证了2016年4、7、10和12月本文计算的DSSR和同时期的JAXA DSSR产品,验证结果显示两者的DSSR在两个观测站点均具有非常高的相关性(全天空、晴空和云天条件下的相关系数R均大于0.88)。在两个站点云天条件下的验证结果中,考虑了云相态并在冰云模型中使用了非球形冰晶粒子(六棱柱)来计算DSSR,获得了比JAXA DSSR更小的偏差。本文提出的快速化计算方法能快速准确地计算DSSR,可为计算地表辐射收支等研究提供重要数据支撑。     

中国北方地区春季气溶胶光学特性地基遥感研究

基于中国北方地区地基太阳直接/散射辐射计观测,分析了2001年春季气溶胶光学厚度、尺度和吸收特性。沙尘期间,气溶胶光学厚度显著升高,而尺度上升,粗粒子浓度显著增加,大气气溶胶表现出中性或异常消光特征。除沙尘活动之外,中国华北地区人为排放也是导致气溶胶光学厚度偏高的一个重要原因。中国沙尘源区气溶胶单次散射反照率小于以往观测和模式结果。北京和香河两地气溶胶光学厚度、Angstrom指数和尺度谱基本相似,说明华北地区人为排放与沙尘活动类似,也表现出区域尺度的特点。由于沙尘气溶胶与人为排放气溶胶相比,折射指数实部偏大、虚部偏小,从而北京地区沙尘期间单次散射反照率明显大于非沙尘期间,特别是在近红外波段,说明沙尘活动不仅可以通过增加气溶胶光学厚度,同时也通过改变气溶胶物理、辐射特性来影响下游地区的气溶胶辐射强迫。     

The ADV/ASV AATSR aerosol retrieval algorithm: current status and presentation of a full-mission AOD dataset

An advanced along-track scanning radiometer (AATSR) global multi-year aerosol retrieval algorithm is described. Over land, the AATSR dual-view (ADV) algorithm utilizes the measured top of the atmosphere (TOA) reflectance in both the nadir and forward views to decouple the contributions of the atmosphere and the surface to retrieve aerosol properties. Over ocean, the AATSR single-view (ASV) algorithm minimizes the discrepancy between the measured and modelled TOA reflectances in one of the views to retrieve the aerosol information using an ocean reflectance model. Necessary steps to process global, multi-year aerosol information are presented. These include cloud screening, the averaging of measured reflectance, and post-processing. Limitations of the algorithms are also discussed. The main product of the aerosol retrieval is the aerosol optical depth (AOD) at visible/near-infrared wavelengths. The retrieved AOD is validated using data from the surface-based AERONET and maritime aerosol network (MAN) sun photometer networks as references. The validation shows good agreement with the reference (r?=?0.85, RMSE?=?0.09 over land; r?=?0.83, RMSE?=?0.09 at coasts and r?=?0.96, RMSE?=?0.06 over open ocean). The results of the aerosol retrievals are presented for the full AATSR mission years 2002–2012 with seasonally averaged time series for selected regions.     

Description of a New Method for Retrieving the Aerosol Optical Thickness from Satellite Remotely Sensed Imagery Using the Maximum Contrast Value and Darkest Pixel Approach

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative remotely sensed imagery and quantitative data, such as aerosol optical depth which is the basic unknown parameter for any atmospheric correction method in the pre‐processing of satellite imagery. This article presents a new method for retrieving aerosol optical thickness directly from satellite remotely sensed imagery for short wavelength bands in which atmospheric scattering is the dominant contribution to the at‐satellite recorded signal. The method is based on the determination of the aerosol optical thickness through the application of the contrast tool (maximum contrast value), the radiative transfer calculations and the ‘tracking’ of the suitable darkest pixel in the scene. The proposed method that needs no a‐priori information has been applied to LANDSAT‐5 TM, LANDSAT‐7 ETM+, SPOT‐5 and IKONOS data of two different geographical areas: West London and Cyprus. The retrieved aerosol optical thickness values show high correlations with in‐situ visibility data acquired during the satellite overpass. Indeed, for the West London area a logarithmic regression was fitted for relating the determined aerosol optical thickness with the in‐situ visibility values. A high correlation coefficient (r²= 0.82; p= 0.2) was found. Plots obtained from Tanre et al. (1979, 1990) and Forster (1984 ) were reproduced and estimates for these areas were generated with the proposed method so as to compare the results. The author's results show good agreement with Forster's aerosol optical thickness vs. visibility results and a small deviation from Tanre's model estimates.     

Assessment of satellite ocean color products of MERIS,MODIS and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea)

The validation of satellite ocean-color products is an important task of ocean-color missions. The uncertainties of these products are poorly quantified in the Yellow Sea (YS) and East China Sea (ECS), which are well known for their optical complexity and turbidity in terms of both oceanic and atmospheric optical properties. The objective of this paper is to evaluate the primary ocean-color products from three major ocean-color satellites, namely the Moderate Resolution Imaging Spectroradiometer (MODIS), Medium Resolution Imaging Spectrometer (MERIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Through match-up analysis with in situ data, it is found that satellite retrievals of the spectral remote sensing reflectance R_rs(λ) at the blue-green and green bands from MERIS, MODIS and SeaWiFS have the lowest uncertainties with a median of the absolute percentage of difference (APD_m) of 15–27% and root-mean-square-error (RMS) of 0.0021–0.0039 sr⁻¹, whereas the R_rs(λ) uncertainty at 412 nm is the highest (APD_m 47–62%, RMS 0.0027–0.0041 sr⁻¹). The uncertainties of the aerosol optical thickness (AOT) τ_a, diffuse attenuation coefficient for downward irradiance at 490 nm K_d(490), concentrations of suspended particulate sediment concentration (SPM) and Chlorophyll a (Chl-a) were also quantified. It is demonstrated that with appropriate in-water algorithms specifically developed for turbid waters rather than the standard ones adopted in the operational satellite data processing chain, the uncertainties of satellite-derived properties of K_d(490), SPM, and Chl-a may decrease significantly to the level of 20–30%, which is true for the majority of the study area. This validation activity advocates for (1) the improvement of the atmosphere correction algorithms with the regional aerosol optical model, (2) switching to regional in-water algorithms over turbid coastal waters, and (3) continuous support of the dedicated in situ data collection effort for the validation task.     

Retrieval of Brown Carbon based on the aerosol complex refractive indices in the winter of Wuhan

Abstract

The impact of Brown Carbon (BrC) to aerosol light absorption has been paid more attention recently and there are a large number of studies showing that the influence of BrC on radiative forcing should not be ignored. BrC also acts as an important component of haze pollution which is occurring frequently in Wuhan, China. Therefore, it is essential to estimate their optical properties, composition, and mass concentration. Considering most haze pollution happens during the coldest time, we retrieved BrC columnar content during winter in Wuhan for the first time. Our method bases on the fact that BrC showed the strong spectral dependence on UV-light absorption. Using this method, we found that BrC makes up the small proportions of total aerosol volume (less than 10%). In the winter of 2011, we retrieved the daily-averaged columnar-integrated mass concentration of BrC on clear day is 4.353 mg/m² while that of haze day is 12.750 mg/m². According to the sensitivity study, we found that the results highly relied on the assumed aerosol refractive index. To reduce the uncertainty of this approach, we need to gain a better understanding of the temporal variability of the radiation absorbing components of these aerosols in the future.     

极地区域气溶胶地基遥感观测及分析

依据全球气溶胶自动观测网在极地区域的观测,对以下问题进行了讨论:(1)温度订正在极地气溶胶光学厚度观测中的重要性及订正方法;(2)在极地进行仪器常数标定的可行性分析及温度效应的影响;(3)利用天空散射光观测反演气溶胶微物理和光学特性参数(粒子谱分布、散射相函数、复折射指数、单次散射反照率等)时,关于观测几何选择的问题,以及针对极地区域气溶胶特性的初步反演结果。这些研究可以为中国未来在两极地区开展基于自动太阳-天空辐射计的气溶胶地基遥感观测提供参考,为极地区域气溶胶卫星遥感及气候效应评估等研究提供重要支撑。     

基于MODIS数据的上海市气溶胶厚度研究

基于6S传输模型,本文利用中分辨率成像光谱仪（MODIS）数据并结合较新的NASA的V5．2气溶胶业务反演算法,以上海市MODIS数据为研究数据源,结合晴朗天气（晴朗且无云或云稀薄）与AERONET发布的探测日（即发布AOD探测值日期）选取8组MODISLIB数据集,对其进行气溶胶厚度反演。同时将反演结果与AERONET架设在太湖区域点（31N,120E）的太阳光度观测的光学厚度进行验证。结果表明：V5．2反演算法结果与观测值呈现相同的变化趋势,反演值与观测值误差不大,在气溶胶光学厚度反演中具有较好的应用。     

Impact of aerosols on terrestrial gross primary productivity in North China using an improved boreal ecosystem productivity simulator with satellite-based aerosol optical depth

ABSTRACT

Atmospheric aerosols can alter the direct and diffuse components of global solar radiation, which further influences terrestrial gross primary productivity (GPP) via photosynthesis. To investigate the impact of aerosols on GPP, GPP is modeled using the Boreal Ecosystem Productivity Simulator (BEPS) under two aerosol scenarios (S1& S2) over cropland and grassland ecosystems in the highly polluted North China. In S1, the aerosol-effect is not considered and an original empirical method is used when estimating direct and diffuse solar radiation in BEPS. In S2, BEPS is improved by a new empirical method which incorporates the impact of aerosols using the remote sensing-based aerosol optical depth (AOD). Results suggest that aerosols can reduce GPP of the sunlit leaves by decreasing direct solar radiation, but increase GPP of the shaded leaves by increasing diffuse solar radiation. The impact of aerosols on GPP is more significant over the cropland ecosystem (p < 0.05) with a more complex canopy structure during the peak period of the growing season. Furthermore, an AOD value of 0.3–0.6 with a diffuse fraction (the fraction of diffuse solar radiation in global solar radiation) around 30-40% can largely increase total GPP over the cropland ecosystem. The study improves the accuracy of GPP modeling using BEPS by highlighting the aerosol-effect on GPP via solar radiation over highly polluted regions.

Abbreviations: gross primary productivity (GPP); aerosol optical depth (AOD); boreal ecosystem productivity simulator (BEPS)     

In Situ Time Series Estimation of Downwelling Diffuse Attenuation Coefficient at Southern Bay of Bengal

The present study is aimed to determine the bio-optical characteristics of oceanic waters during South west monsoon in Bay of Bengal using hyperspectral radiometer. The variability of diffuse attenuation coefficient, K_d(λ), with chlorophyll a showed a good relation at shorter wavelengths, indicating the effect of phytoplankton on K_d(λ). The determination coefficient, R² at 412, 443, 490 and 555 nm were greater than 0.931. A good linear relation between K_d(490) and K_d(λ) was observed at shorter wavelengths. These relationships of K_d(λ) provides a platform to study the underwater light field during Southwest monsoon in Bay of Bengal.     

大气水汽的红外遥感

本文讨论了利用差分吸收法来遥感大气中的水汽。水汽透过率用辐射计测量，水汽含量由我们自行编制的红外辐射大气透过率计算程序计算。在此同时还观测了气象参数，以确定光路上的水汽含量。结果表明，水汽长度的计算值和测量值非常吻合，回归曲线的相关系数达０．９７，均方根偏差为０．０１５ｇ／ｃｍ２。文中最后讨论误差来源和改善精度的途径，并指出对其它气体分子的吸收和气溶胶的消光进行修正的必要性。     

航空遥感数据典型自然下垫面偏振特性分析

对于航空航天大气偏振遥感来说,下垫面偏振辐射噪声影响扣除至关重要。本文基于航空偏振遥感数据,探讨了典型自然下垫面对可见光及短波红外波段偏振敏感性。研究发现,在可见光波段与短波红外(2250 nm)波段,植被下垫面偏振反射率线性拟合斜率都接近1,相关系数大于0.95,表明植被偏振反射率对光谱波段不敏感。比较分析了平静水面和存在耀光水面在670 nm和2250 nm两波段的偏振特性,存在耀光的水面其偏振反射率大约是平静水面的3倍。此外,在实验室测量了红砂土和河沙土的偏振反射率,偏振反射率随波段的改变量很小,其与波段的线性拟合斜率仅为10-5量级,说明两者的偏振反射率对波段很不敏感。因此,利用典型自然下垫面在可见和短波红外波段的偏振反射特性,将能够有效进行地气解耦,提高大气偏振遥感精度。     

Estimation of higher chlorophylla concentrations using field spectral measurement and HJ-1A hyperspectral satellite data in Dianshan Lake,China

Based on in situ water sampling and field spectral measurements in Dianshan Lake, a semi-analytical three-band algorithm was used to estimate Chlorophylla (Chla) content in case II waters. The three bands selected to estimate Chla for high concentrations included 653, 691 and 748 nm. An equation, based on the difference in reciprocal reflectance between 653 and 691 nm, multiplied by reflectance at 748 nm as [R_rs⁻¹(653) − R_rs⁻¹ (691)] R_rs(748), explained 85.57% of variance in Chla concentration with a root mean square error (RMSE) of <6.56 mg/m³. In order to test the utility of this model with satellite data, HJ-1A Hyperspectral Imager (HSI) data were analyzed using comparable wavelengths selected from the in situ data [B₆₇⁻¹(656) − B₈₀⁻¹(716)] B₈₇(753). This model accounted for 84.3% of Chla variation, estimating Chla concentrations with an RMSE of <4.23 mg/m³. The results illustrate that, based on the determined wavelengths, the spectrum-based model can achieve a high estimation accuracy and can be applied to hyperspectral satellite imagery especially for higher Chla concentration waters.     

Evaluation of a three-band model for estimating chlorophyll-a concentration in tidal reaches of the Pearl River Estuary, China

Accurate assessment of phytoplankton chlorophyll-a (Chla) concentration in turbid waters by means of remote sensing was challenging due to the optical complexity of turbid waters. Recently, a conceptual model containing reflectance in three spectral bands in the red and near-infrared range of the spectrum was suggested for retrieving Chla concentrations in turbid productive waters. The objective of this paper was to evaluate the performance of this three-band model to estimate Chla concentration in the Pearl River Estuary (PRE), China. Reflectance spectra of surface water and water samples were collected concurrently. The samples contained variable Chla (4.80-92.60 mg/m³) and total suspended solids (0.4-55.2 mg/L dry wt). Colored dissolved organic matter (CDOM) absorption at 400 nm was 0.40-1.41 m⁻¹; turbidity ranged from 4 to 25 NTU (Nephelometric Turbidity Units). The three-band model was spectrally calibrated by iterative and least-square linear regression methods to select the optimal spectral bands for the most accurate Chla estimation. Strong linear relationships (R²=0.81, RMSE=1.4 mg/m³, N=32) were established between measured Chla and the levels obtained from the calibrated three-band model [R⁻¹(684)-R⁻¹(690)]×R(718), where R(λ) was the reflectance at wavelength λ. The calibrated three-band model was independently validated (R²=0.9521, RMSE=6.44 mg/m³, N=16) and applied to retrieve Chla concentrations from the calibrated EO-1 Hyperion reflectance data in the PRE on December 21, 2006. The EO-1 Hyperion-derived Chla concentrations were further validated using synchronous in situ data collected on the same day (R²=0.64, RMSE=2 mg/m³, N=9). The spatial tendency of Chla distribution mapping by Hyperion showed gradually increased concentrations of Chla farther from the river mouths (although decreasing from east to west), which were disturbed by the combination of river outlets and tidal current in Lingding Bay of the PRE. This observation conformed to previous observations and studies, and could reasonably be explained by geographical changes. Also, results indicated that the slope of the three-band regression line decreased as the Chla concentration increased, resulting in the first sensitive band of the three-band model to move towards short wavelengths. These findings validated the rationale behind the conceptual model and demonstrated the robustness of this algorithm for Chla retrieval from in situ data and the Hyperion satellite sensor in turbid estuarine waters of the PRE, China.     

海洋激光雷达反演水体光学参数

研制了一套船载海洋激光雷达,用于探测海水光学参数垂直廓线。2017年8月,该系统在黄海海域进行了实验测量。在准单次散射模型中引入原位测量的光学参数,实现了理想激光雷达回波信号的模拟,并将该理想信号与系统响应函数卷积后精确复现了实验的激光雷达信号。采用Fernald后向迭代积分法(简称Fernald法),比较了不同水体悬浮物激光雷达比下反演的激光雷达衰减系数α与原位漫射衰减系数Kd的差别。基于停航时标定的水体悬浮物激光雷达比,采用Fernald法获得了走航时的激光雷达衰减系数。进一步地,提出一种基于米散射激光雷达数据和原位测量的后向散射数据的融合算法,模拟了高光谱分辨率激光雷达(HSRL)反演α的过程,并将其与Fernald法进行了比较。实验结果表明,自研的海洋激光雷达能够有效探测海水光学参数,基于合适的水体悬浮物激光雷达比的Fernald法可以有效应用于米散射激光雷达的反演,未来无需假设的HSRL在海水光学参数探测领域具有更大的优势。     

偏振激光雷达探测大气—水体光学参数廓线

激光雷达在上层水体垂直廓线的遥感中展现出巨大优势。本文研制了一套高垂直分辨率的实时探测偏振激光雷达,提出了一种基于偏振激光雷达回波信号的反演算法,采用Fernald理论和多次散射原理反演非均匀大气—水体的衰减和退偏光学产品,以高效稳定地处理偏振激光雷达实验数据。展示了一个中国内陆水体激光雷达探测实例,观测到了两次气溶胶积聚现象和一次水体浑浊现象。对实验数据的分析表明,退偏比主要由前向多次散射和后向单次散射产生的退偏两部分组成。当多次散射强度较大时,退偏比的变化主要取决于多次前向散射退偏;反之,则主要依赖于单次后向散射退偏。     

Incorporating dynamic factors for improving a GIS‐based solar radiation model

Solar radiation has been a major input to agricultural, hydrological, and ecological modeling. However, solar radiation is usually influenced by three groups of dynamic factors: sun–earth position, terrain, and atmospheric effects. Therefore, an integrated approach to accurately consider the impacts of those dynamic factors on solar radiation is essential to estimate solar radiation over rugged terrain. In this study, a spatial and temporal gap‐filling algorithm was proposed to obtain a seamless daily MODIS albedo dataset. A 1 km‐resolution digital elevation model was used to model the impact of local topography and shading by surrounding terrain on solar radiation. A sunshine‐based model was adopted to simulate radiation under the influence of clouds. A GIS‐based solar radiation model that incorporates albedo, shading by surrounding terrain, and variations in cloudiness was used to address the spatial variability of these factors in mountainous terrain. Compared with other independent solar radiation products, our model generated a more reliable solar radiation product over rugged terrain, with an R² of 0.88 and an RMSE of 2.55 MJ m^?2 day^?1. The improved solar radiation products and open source app can be used further in practice or scientific research.     

Estimation of Seasonal Sun-Induced Fluorescence Dynamics of Indian Tropical Deciduous Forests using SCOPE and Sentinel-2 MSI

This paper presents a new approach to estimate spatial Sun-Induced Fluorescence (SIF) using the empirical relationship between simulated Canopy Chlorophyll Concentration (CCC) and simulated SIF. PROSAIL model [PROpriétésSPECTrales (PROSPECT) and Scattering by Arbitrarily Inclined Leaves (SAIL) models] was used to simulate CCC. CCC maps were generated through an Automated Radiative Transfer Model Operator (ARTMO) using the PROSAIL model and Sentinel-2 Multi-Spectral Imager (MSI) imagery. The Soil Canopy Observation, Photochemistry, and Energy fluxes (SCOPE) model was used to simulate SIF emitted at 740 nm (SIF₇₄₀), at 760 nm (SIF₇₆₀), and top of canopy (SIF_TOC) (640-850 nm). The SCOPE model, configured with the specification of the Sentinel-2 sensor, simulates SIF within the spectrum range of 640-850 nm. A non-linear logarithmic relationship (R²>0.9, p < 0.05) was observed between simulated SIF and simulated CCC. Simulated CCC was linearly related to observed CCC with R² 0.88, 0.92 and 0.89 and RMSE = 0.04, 0.17 and 0.09 gm/m² at p < 0.05 for summer, post-monsoon and early winter respectively. Whereas, the simulated CCC did not capture the full range of CCC variability for the post-monsoon season. Simulated SIF (SIF₇₆₀) was well correlated with SIF from Orbiting Carbon Observatory-2 (OCO-2) satellite with R² 0.68, 0.73 and 0.73 (RMSE = <1 W/m²/sr/μm, p < 0.05) for the month of summer (April), pre-monsoon (May) and early winter season (November) respectively. Temporal SIF_TOC effectively captured the seasonal variability associated with the phenology of deciduous tree species. Among various Sentinel-2 MSI derived VIs, Red Edge NDVI (RENDVI) exhibited maximum sensitivity with SIF (highest monthly average R²> 0.6, p < 0.05). The spatial SIF would serve as an useful link between airborne /satellite derived SIF and in-situ fluorescence measurements to understand multiscale SIF variability of terrestrial vegetation.