scholarly journals GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during DRAGON-NE Asia 2012 campaign

2015 ◽  
Vol 8 (9) ◽  
pp. 9565-9609 ◽  
Author(s):  
M. Choi ◽  
J. Kim ◽  
J. Lee ◽  
M. Kim ◽  
Y. Je Park ◽  
...  
Keyword(s):  
Optical Properties ◽  
Land Surface ◽  
Pearson Correlation ◽  
Ocean Color ◽  
Single Scattering ◽  
Surface Reflectance ◽  
Robotic Networks ◽  
Deep Blue ◽  
Aerosol Retrieval ◽  
Highly Correlated

Abstract. The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorology Satellites (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm over ocean and land together with validation results during the DRAGON-NE Asia 2012 campaign. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type from selected aerosol models in calculating AOD. Assumed aerosol models are compiled from global Aerosol Robotic Networks (AERONET) inversion data, and categorized according to AOD, FMF, and SSA. Nonsphericity is considered, and unified aerosol models are used over land and ocean. Different assumptions for surface reflectance are applied over ocean and land. Surface reflectance over the ocean varies with geometry and wind speed, while surface reflectance over land is obtained from the 1–3 % darkest pixels in a 6 km × 6 km area during 30 days. In the East China Sea and Yellow Sea, significant area is covered persistently by turbid waters, for which the land algorithm is used for aerosol retrieval. To detect turbid water pixels, TOA reflectance difference at 660 nm is used. GOCI YAER products are validated using other aerosol products from AERONET and the MODIS Collection 6 aerosol data from "Dark Target (DT)" and "Deep Blue (DB)" algorithms during the DRAGON-NE Asia 2012 campaign from March to May 2012. Comparison of AOD from GOCI and AERONET gives a Pearson correlation coefficient of 0.885 and a linear regression equation with GOCI AOD =1.086 × AERONET AOD – 0.041. GOCI and MODIS AODs are more highly correlated over ocean than land. Over land, especially, GOCI AOD shows better agreement with MODIS DB than MODIS DT because of the choice of surface reflectance assumptions. Other GOCI YAER products show lower correlation with AERONET than AOD, but are still qualitatively useful.

scholarly journals GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

2016 ◽  
Vol 9 (3) ◽  
pp. 1377-1398 ◽  
Author(s):  
Myungje Choi ◽  
Jhoon Kim ◽  
Jaehwa Lee ◽  
Mijin Kim ◽  
Young-Je Park ◽  
...  
Keyword(s):  
Optical Properties ◽  
East Asia ◽  
Global Analysis ◽  
Pearson Correlation ◽  
Ocean Color ◽  
Northeast Asia ◽  
Single Scattering ◽  
The Yellow Sea ◽  
Deep Blue ◽  
Aerosol Retrieval

Abstract. The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks – Northeast Asia 2012 campaign (DRAGON-NE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox–Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD  =  1.083  ×  AERONET AOD − 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

scholarly journals Theoretical Uncertainty Analysis of Satellite Retrieved Aerosol Optical Depth Associated with Surface Albedo and Aerosol Optical Properties

2021 ◽  
Vol 13 (3) ◽  
pp. 344
Author(s):  
Jingting Huang ◽  
William Patrick Arnott ◽  
James C. Barnard ◽  
Heather A. Holmes
Keyword(s):  
Optical Properties ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Asymmetry Parameter ◽  
Surface Albedo ◽  
Single Scattering ◽  
Critical Surface ◽  
Surface Reflectance ◽  
Aerosol Optical Properties ◽  
Aerosol Retrieval

Deriving aerosol optical depth (AOD) from space-borne observations is still challenging due to uncertainties associated with sensor calibration drift, cloud screening, aerosol type classification, and surface reflectance characterization. As an initial step to understanding the physical processes impacting these uncertainties in satellite AOD retrievals, this study outlines a theoretical approach to estimate biases in the satellite aerosol retrieval algorithm affected by surface albedo and prescribed aerosol optical properties using a simplified radiative transfer model with a traditional error propagation approach. We expand the critical surface reflectance concept to obtain the critical surface albedo (CSA), critical single scattering albedo (CSSA), and critical asymmetry parameter (CAP). The top-of-atmosphere (TOA) reflectance is not sensitive to significant variability in aerosol loading (AOD) at the critical value; thus, the AOD cannot be determined. Results show that 5% bias in surface albedo (A), single scattering albedo (SSA), or asymmetry parameter (g) lead to large retrieved AOD errors, especially high under conditions when A, SSA, or g are close to their critical values. The results can be useful for future research related to improvements of satellite aerosol retrieval algorithms and provide a preliminary framework to analytically quantify AOD uncertainties from satellite retrievals.

scholarly journals Retrieval of spectral aerosol optical thickness over land using ocean color sensors MERIS and SeaWiFS

2010 ◽  
Vol 3 (3) ◽  
pp. 2107-2164 ◽  
Author(s):  
W. von Hoyningen-Huene ◽  
J. Yoon ◽  
M. Vountas ◽  
L. G. Istomina ◽  
G. Rohen ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Vegetation Index ◽  
Single Scattering ◽  
Aerosol Optical Thickness ◽  
Visible Range ◽  
Surface Reflectance ◽  
Spectral Determination ◽  
Aerosol Retrieval ◽  
Phase Functions

Abstract. For the determination of aerosol optical thickness (AOT) Bremen AErosol Retrieval (BAER) has been developed. Method and main influences on the aerosol retrieval are described together with validation and results. The retrieval separates the spectral aerosol reflectance from surface and Rayleigh path reflectance for the shortwave range of the measured spectrum of top-of-atmosphere reflectance less than 0.670 μm. The advantage of MERIS (Medium Resolution Imaging Spectrometer on ENVISAT) and SeaWiFS (Sea viewing Wide Fiels Sensor on OrbView-2) observations are the existence of several spectral channels in the blue and visible range enabling the spectral determination of AOT in 7 (or 6) channels (0.412–0.670 μm) and additionally channels in the NIR, which can be used to characterize the surface properties. A dynamical spectral surface reflectance model for different surface types is used to obtain the spectral surface reflectance for this separation. Normalized differential vegetation index (NDVI), taken from the satellite observations, is the model input. Further surface BRDF is considered by the Raman-Pinty-Verstraete (RPV) model. Spectral AOT is obtained from aerosol reflectance using look-up-tables, obtained from radiative transfer calculations with given aerosol phase functions and single scattering albedos either from aerosol models, given by OPAC or from experimental campaigns. Validations of the obtained AOT retrieval results with AERONET data over Europe gave a preference for experimental phase functions derived from almucantar measurements. Finally long-term observations of SeaWiFS have been investigated for trends in AOT.

scholarly journals Retrieval of aerosol optical depth over land based on a time series technique using MSG/SERIVI data

2012 ◽  
Vol 12 (2) ◽  
pp. 4031-4071 ◽  
Author(s):  
L. Mei ◽  
Y. Xue ◽  
G. de Leeuw ◽  
T. Holzer-Popp ◽  
J. Guang ◽  
...  
Keyword(s):  
Time Series ◽  
Detailed Analysis ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Optimal Solution ◽  
Single Scattering ◽  
Asymmetry Factor ◽  
Surface Reflectance ◽  
Deep Blue ◽  
Aerosol Type

Abstract. A novel approach for the joint retrieval of aerosol optical depth (AOD) and surface reflectance, using Meteosat Second Generation – Spinning Enhanced Visible and Infrared Imagers (MSG/SEVIRI) observations in two solar channels, is presented. The retrieval is based on a time series (TS) technique, which makes use of the two visible bands at 0.6 μm and 0.8 μm in three orderly scan times (15 min interval between two scans) to retrieve the AOD over land. Using the radiative transfer equation for plane-parallel atmospheres two coupled differential equations for the upward and downward fluxes are derived. The boundary conditions for the upward and downward fluxes at the top and at the bottom of the atmosphere are used in these equations to provide an analytic solution for the surface reflectance. To derive these fluxes, the aerosol single scattering albedo (SSA) and asymmetry factor are required to provide a solution. These are provided from a set of six pre-defined aerosol types with the SSA and asymmetry factor (g). We assume one aerosol type for a grid of 1° × 1° and the surface reflectance changes little between two consequent scans. A k approximation was used in the inversion to find the best solution of atmospheric properties and surface reflectance. The algorithm makes use of numerical minimisation routines to obtain the optimal solution of atmospheric properties and surface reflectance by selection of the most suitable aerosol type from pre-defined sets. Also, it is assumed that the surface reflectance is little influenced by aerosol scattering at 1.6 μm and therefore the ratio of surface reflectances in the solar band for two consequent scans can be well-approximated by the ratio of the reflectances at 1.6 μm. A further assumption is that the surface reflectance varies only slightly over a period of 30 min. A detailed analysis of the retrieval results show that it is suitable for AOD retrieval over land. Six Aerosol Robotic Network (AERONET) sites with different surface types were used for detailed analysis and 42 other AERONET sites were used for validation. From 445 collocations representing stable and homogeneous aerosol type, we found that >75% of MSG-retrieved AOD values compared to AERONET observed values with an error envelope of ±0.05 ± 0.15τ and a high correlation (R > 0.86). The AOD datasets derived using the TS method with SEVIRI data was also compared with collocated AOD products derived from the NASA TERRA and AQUA MODIS data using the dark dense vegetation (DDV) method and the Deep Blue algorithms. Using the TS method, AOD could be retrieved for more pixels than with the NASA Deep Blue algorithm. The AOD values derived compare favourably.

The improved thin cloud detection using BRDF model based background reflectance from GOCI geostationary satellite imagery

2020 ◽  
Author(s):  
Jong-Min Yeom ◽  
Hye-Won Kim ◽  
Jeongho Lee ◽  
Seonyoung Park ◽  
Sangcherl Lee
Keyword(s):  
Land Surface ◽  
Ocean Color ◽  
Detection Algorithm ◽  
Land Application ◽  
Surface Reflectance ◽  
Cloud Detection ◽  
Land Area ◽  
Spectral Bands ◽  
Thin Cloud ◽  
Cloud Mask

<p>In this study, the improved algorithm of thin cloud detection for geostationary ocean color imager (GOCI) satellite was developed to classify the thin cloud area over land area. The new cloud mask approach of GOCI satellite is required to expand its ocean dedicated application to other applications such for vegetation in land or aerosol optical properties (AOPs) in atmosphere due to its attractive shortwave wavelength bands of ocean color sensors. However, when trying to apply the advantages of the ocean color bands to the land area, only visible spectral bands of GOCI make it difficult to expand the land application the other way due to its limitation of cloud detection for relatively bright land surface. Furthermore, the geostationary of GOCI satellite has highly sensitive to geometry location of sun, meaning that high effective (Bidirectional Reflectance Distribution Function) BRDF effects make it also difficult to detect cloud mask in land surface due to its anisotropically scattered surface reflectance. In this paper, cloud mask algorithm of GOCI is proposed to consider those limitations by mainly using background surface reflectance from BRDF model. Therefore, minimum difference in reflectance between TOA and land as baseline of clear atmosphere and background surface reflectance underneath cloud were estimated from BRDF model. In conclusion, our new thin cloud detection is effectively detect the thin cloud over land surface area under limited ocean color bands of GOCI. The improved thin cloud detection algorithm of GOCI will be not only useful for following on instruments such as GOCI-II of Geo-KOMPSAT-2B and Sentinel 3 Ocean and Land Color Instrument (OLCL), but also applicable for existing geostationary satellites such as Geo-KOMPSAT-2A AMI, Himawari, and GOES-R as alternative cloud masking approach.</p>

scholarly journals Spatial distribution of dust's optical properties over the Sahara and Asia inferred from Moderate Resolution Imaging Spectroradiometer

2013 ◽  
Vol 13 (21) ◽  
pp. 10827-10845 ◽  
Author(s):  
M. Yoshida ◽  
J. M. Haywood ◽  
T. Yokohata ◽  
H. Murakami ◽  
T. Nakajima
Keyword(s):  
Optical Properties ◽  
Spatial Distribution ◽  
Single Scattering ◽  
Surface Reflectance ◽  
Carbonaceous Aerosols ◽  
Dust Aerosols ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Earth’S Climate

Abstract. There is great uncertainty regarding the role of mineral dust aerosols in Earth's climate system. One reason for this uncertainty is that the optical properties of mineral dust, such as its single scattering albedo (the ratio of scattering to total extinction), are poorly constrained because ground observations are limited to a few locations and satellite standard products are not available due to the excessively bright surface of the desert in the visible wavelength, which makes robust retrievals difficult. Here, we develop a method to estimate the spatial distributions of the aerosol single scattering albedo (ω0) and optical depth (τa), with daily 1°×1° spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as model simulations of radiative transfer. This approach is based on the "critical surface reflectance" method developed in the literature, which estimates ω0 from the top of the atmospheric radiance. We estimate the uncertainties in ω0 over the Sahara (Asia) to be approximately 0.020 and 0.010 (0.023 and 0.017) for bands 9 and 1, respectively, while the uncertainty in τa is approximately 0.235 and 0.228 (0.464 and 0.370) for bands 9 and 1, respectively. The 5–95% range of the spatial distribution of ω0 over the Sahara (Asia) is approximately 0.90–0.94 and 0.96–0.99 (0.87–0.94 and 0.89–0.97) for bands 9 and 1, respectively, and that of τa over the Sahara (Asia) is approximately 0.8–1.4 and 0.8–1.7 (0.7–2.0 and 0.7–1.9) for bands 9 and 1, respectively. The results for the Sahara indicate a good correlation between ω0 and the surface reflectance, and between ω0 and τa. However, the relationships between ω0, τa, and surface reflectance are less clear in Asia than in the Sahara, and the ω0 values are smaller than those in the Sahara. The regions with small ω0 values are consistent with the regions where coal-burning smoke and carbonaceous aerosols are reported to be transported in previous studies. Because the coal-burning and carbonaceous aerosols are known to be more absorptive and have smaller ω0 values than dust aerosols, our results indicate that the dust aerosols in Asia are contaminated by these anthropogenic aerosols. The spatial distribution of dust optical properties obtained in our work could be useful in understanding the role of dust aerosols in Earth's climate system, most likely through future collaboration with regional and global modelling studies.

scholarly journals Spatial distribution of dust's optical properties over the Sahara and Asia inferred from Moderate Resolution Imaging Spectroradiometer

2012 ◽  
Vol 12 (12) ◽  
pp. 31107-31151
Author(s):  
M. Yoshida ◽  
J. M. Haywood ◽  
B. T. Johnson ◽  
H. Murakami ◽  
T. Nakajima
Keyword(s):  
Optical Properties ◽  
Single Scattering ◽  
Spatial Distributions ◽  
Surface Reflectance ◽  
Carbonaceous Aerosols ◽  
Dust Aerosols ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Earth’S Climate

Abstract. There is a great deal of uncertainty surrounding the role of mineral dust aerosols in the earth's climate system. One reason for this uncertainty is that the optical properties of mineral dust, such as its single scattering albedo (the ratio of scattering to total extinction), are poorly understood because ground observations are limited to several locations and the satellite standard products are not available due to the excessively bright surface of the desert in the visible wavelength. We develop a method in this paper to estimate the spatial distributions of the aerosol single scattering albedo (ω0) and optical depth (τa), with daily 1 degree latitude and 1 degree longitude resolution, using data from Moderate Resolution Imaging Spectroradiometer (MODIS), as well as model simulations of radiative transfer. This approach is based on the "critical surface reflectance" method developed in the literature, which estimates ω0 from the top of the atmospheric radiance. We confirm that the uncertainties in our estimation of ω0 and τa are suitably minor and that the characteristic spatial distributions estimated over the Sahara and Asia are significant. The results for the Sahara indicate good correlation between ω0 and the surface reflectance and between ω0 and τa. Therefore, ω0 is determined mainly by the mineral composition of surface dust and/or the optical depth of airborne dust in the Sahara. On the other hand, the relationships between ω0, τa, and the surface reflectance are less clear in Asia than in the Sahara, and the values of ω0 are smaller than those in the Sahara. The regions with small ω0 values are consistent with the regions where coal-burning smoke and carbonaceous aerosols are thought to be transported, as reported in previous studies. Because the coal-burning and carbonaceous aerosols are known to be more absorptive and have smaller ω0 values than dust aerosols, our results indicate that the dust aerosols in Asia are contaminated by these anthropogenic aerosols. The spatial distribution of dust optical properties obtained in our work could be useful in understanding the roles of dust aerosols in the earth's climate system, most likely through future collaboration with regional and global modelling studies.

scholarly journals Measurement-based climatology of aerosol direct radiative effect, its sensitivities, and uncertainties from a background southeast U.S. site

2017 ◽  
Author(s):  
James P. Sherman ◽  
Allison McComiskey
Keyword(s):  
Optical Properties ◽  
Ground Truth ◽  
Single Scattering ◽  
Surface Reflectance ◽  
Radiative Effect ◽  
Aerosol Optical Properties ◽  
Clear Sky ◽  
Aerosol Loading ◽  
Measurement Uncertainties ◽  
Seasonal Dependence

Abstract. Aerosol optical properties measured at Appalachian State University's co-located NASA AERONET and NOAA ESRL aerosol network monitoring sites over a nearly four-year period (June 2012 thru February 2016) are used, along with satellite-based surface reflectance measurements, to study the seasonal variability of diurnally averaged clear sky aerosol direct radiative effect (DRE) and radiative efficiency (RE) at the top-of-atmosphere (TOA) and at the surface. Aerosol chemistry and loading at the Appalachian State site are likely representative of the background southeast U.S. (SE U.S.), home to high summertime aerosol loading and one of only a few regions not to have warmed during the 20th century. This study is the first multi-year ground truth DRE study in the SE U.S., using aerosol network data products that are often used to validate satellite-based aerosol retrievals. The study is also the first in the SE U.S. to quantify DRE uncertainties and sensitivities to aerosol optical properties and surface reflectance, including their seasonal dependence. Median DRE for the study period is −2.9 W m−2 at the TOA and −6.1 Wm−2 at the surface. Monthly median and monthly mean DRE at the TOA (surface) are −1 to −2 W m−2 (−2 to −3 W m−2) during winter months and −5 to −6 W m−2 (−10 W m−2) during summer months. The DRE cycles follow the annual cycle of aerosol optical depth (AOD), which is 9 to 10 times larger in summer than in winter. Aerosol RE is anti-correlated with DRE, with winter values 1.5 to 2 times more negative than summer values. Due to the large seasonal dependence of aerosol DRE and RE, we quantify the sensitivity of DRE to aerosol optical properties and surface reflectance, using a calendar day representative of each season (21 December for winter; 21 March for spring, 21 June for summer, and 21 September for fall). We use these sensitivities along with measurement uncertainties of aerosol optical properties and surface reflectance to calculate DRE uncertainties. Aerosol DRE at both the TOA and surface is most sensitive to changes in AOD, followed (in order) by single-scattering albedo (ω0), scattering asymmetry parameter (g), and surface reflectance (R). One exception is under the high summertime aerosol loading conditions, when sensitivity of TOA DRE to ω0 is comparable to that of AOD. While DRE sensitivity to AOD varies by only ~ 25 to 30 % with season, DRE sensitivity to ω0, g, and R vary by factors of 10 to 20 with season. Since the measurement uncertainties of AOD, ω0, g, and R are comparable at Appalachian State, their relative contributions to DRE uncertainty are roughly proportional to their (seasonally dependent) DRE sensitivity values, which suggests that the seasonal dependence of DRE uncertainty must be accounted for. Clear sky aerosol DRE uncertainty at the TOA (surface) ranges from 0.44 W m−2 (0.73 W m−2) for December to 0.90 W m−2 (1.3 W m−2) for June. Expressed as a fraction of DRE computed using monthly median aerosol optical properties and surface reflectance, the DRE uncertainties at TOA (surface) are 16 to 20 % (12 to 20 %) for March, June, and September and 48 % (49 %) for December. The relatively low DRE uncertainties are largely due to the low uncertainty in AOD measured by AERONET. Use of satellite-based AOD measurements by MODIS in the DRE calculations increases DRE uncertainties by a factor of 2.5 to 5 and DRE uncertainties are dominated by AOD uncertainty for all seasons.

scholarly journals Retrieval and Uncertainty Analysis of Land Surface Reflectance Using a Geostationary Ocean Color Imager

2022 ◽  
Vol 14 (2) ◽  
pp. 360
Author(s):  
Kyeong-Sang Lee ◽  
Eunkyung Lee ◽  
Donghyun Jin ◽  
Noh-Hun Seong ◽  
Daeseong Jung ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
Surface Properties ◽  
Spatial Resolution ◽  
Zenith Angle ◽  
Land Surface ◽  
Solar Zenith Angle ◽  
Ocean Color ◽  
Surface Reflectance ◽  
Temporal And Spatial

Land surface reflectance (LSR) is well known as an essential variable to understand land surface properties. The Geostationary Ocean Color Imager (GOCI) be able to observe not only the ocean but also the land with the high temporal and spatial resolution thanks to its channel specification. In this study, we describe the land atmospheric correction algorithm and present the quality of results through comparison with Moderate Resolution Imaging Spectroradiometer (MODIS) and in-situ data for GOCI-II. The GOCI LSR shows similar spatial distribution and quantity with MODIS LSR for both healthy and unhealthy vegetation cover. Our results agreed well with in-situ-based reference LSR with a high correlation coefficient (>0.9) and low root mean square error (<0.02) in all 8 GOCI channels. In addition, seasonal variation according to the solar zenith angle and phenological dynamics in time-series was well presented in both reference and GOCI LSR. As the results of uncertainty analysis, the estimated uncertainty in GOCI LSR shows a reasonable range (<0.04) even under a high solar zenith angle over 70°. The proposed method in this study can be applied to GOCI-II and can provide continuous satellite-based LSR products having a high temporal and spatial resolution for analyzing land surface properties.

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