Intercomparison of Landsat albedo retrieval techniques and evaluation against in situ measurements across the US SURFRAD network

Franch, B.; Vermote, Éric; Claverie, Martin

doi:10.1016/j.rse.2014.07.019

Cited by 59 publications

(67 citation statements)

References 35 publications

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“…Considerable effort has been devoted to extracting prior BRDF knowledge from historical BRDF data based on land cover or the NDVI [13,14]. Studies have proved that linking the surface reflectance anisotropy to land cover or the NDVI may be useful for extracting prior BRDF knowledge from the historical BRDF product, which can improve the retrieval of land surface albedo.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Extracting Prior BRDF from MODIS BRDF Data

et al. 2016

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Abstract:Many previous studies have attempted to extract prior reflectance anisotropy knowledge from the historical MODIS Bidirectional Reflectance Distribution Function (BRDF) product based on land cover or Normalized Difference Vegetation Index (NDVI) data. In this study, the feasibility of the method is discussed based on MODIS data and archetypal BRDFs. The BRDF is simplified into six archetypal BRDFs that represent different reflectance anisotropies. Five-year time series of MODIS BRDF data over three tiles are classified into six BRDF archetype classes according to the Anisotropy Flat indeX (AFX). The percentage of each BRDF archetype class in different land cover classes or every 0.1-NDVI interval is determined. Nadir BRDF-Adjusted Reflectances (NBARs) and NDVIs simulated from different archetypal BRDFs and the same multi-angular observations are compared to MODIS results to study the effectiveness of the method. The results show that one land cover type, or every 0.1-NDVI interval, contains all the potential BRDF shapes and that one BRDF archetypal class makes up no more than 40% of all data. Moreover, the differences between the NBARs and NDVIs simulated from different archetypal BRDFs are insignificant. In terms of the archetypal BRDF method and MODIS BRDF product, this study indicates that the land cover or NDVI is not necessarily related to surface reflectance anisotropy.

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Section: Discussionmentioning

confidence: 99%

Analysis of Extracting Prior BRDF from MODIS BRDF Data

et al. 2016

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“…Limited by the low revisiting frequency of medium-resolution data, the temporal composite method developed for coarse-resolution data (e.g., [25]) cannot be applied without enough angular samples of surface BRDF. To overcome this limitation, a few algorithms have been developed through using ancillary information on surface BRDF to normalize the surface reflectance after atmospheric correction to obtain surface albedo, which relies on concurrent high-quality coarse-resolution data and is particularly effective for dense vegetation [23,26]. Particularly for HJ data, Gao et al [27] refined the algorithm originally proposed by Shuai et al [22] using the surface BRDF information from coarse-resolution products and land cover maps to convert surface reflectance to albedo.…”

Section: Introductionmentioning

confidence: 99%

Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach

Liang

Wang

et al. 2015

Remote Sensing

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Abstract:Monitoring surface albedo at medium-to-fine resolution (<100 m) has become increasingly important for medium-to-fine scale applications and coarse-resolution data evaluation. This paper presents a method for estimating surface albedo directly using top-of-atmosphere reflectance. This is the first attempt to derive surface albedo for both snow-free and snow-covered conditions from medium-resolution data with a single approach. We applied this method to the multispectral data from the wide-swath Chinese HuanJing (HJ) satellites at a spatial resolution of 30 m to demonstrate the feasibility of this data for surface albedo monitoring over rapidly changing surfaces. Validation against ground measurements shows that the method is capable of accurately estimating surface albedo over both snow-free and snow-covered surfaces with an overall root mean square error (RMSE) of 0.030 and r-square (R 2 ) of 0.947. The comparison between HJ albedo estimates and the Moderate Resolution Imaging Spectral Radiometer (MODIS) albedo product suggests that the HJ data and proposed algorithm can generate robust albedo estimates over various land cover types with an RMSE of 0.011-0.014. The accuracy of HJ albedo estimation improves with the increase in view zenith angles, which further demonstrates the unique advantage of wide-swath satellite data in albedo estimation.

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“…Finally, the albedo at Landsat spatial resolution for each pixel, α oli pxl (θ s , λ), is retrieved following [15]: 550 , aer.phys λ )α ws (λ) (9) where α bs (θ, λ) is the black-sky albedo and α ws (λ) is the white-sky albedo. The Snet 6SV (θ s , τ 550 , aer.phys λ ) is the ratio of the diffuse albedo on the total component of solar radiation simulated by the 6SV model at Landsat acquisition time (solar zenith angle θ s ), with the aerosol optical thickness at 550 nm of the Cairo AERONET station and considering the microphysical properties of the aerosol, aer.phys λ , as downloaded from AERONET stations in Cairo and El Farafra and referring to the aerosol basic components (dust-like, water-soluble, oceanic and soot [25]).…”

Section: Albedomentioning

confidence: 99%

“…Consequently, concerning the monitoring of ecosystems or the study of the energy exchange at the surface in the shortwave domain, remote sensing applications require the accurate simulation of the radiative effects of the aerosol on the shortwave net radiation, R n.sw , available at the ground level for energy exchange between the surface and atmosphere [15]. Mira et al [5] highlight the role of the surface albedo for R n.sw retrieval using remote sensing data.…”

Section: Introductionmentioning

confidence: 99%

“…These models provide an accurate simulation of the solar radiation through the Earth-atmosphere coupled system by solving the radiative transfer equation [26,28]. If a ground station of the the AERONET worldwide network [29] is within the remote sensing image, the atmospheric correction can exploit the inverse products of the station by representing the microphysical properties of the aerosol [30,31], which improve the accuracy of the simulated radiative effects due to the aerosol [15,32,33]. The surface reflectance can thus be completely and accurately derived.…”

Section: Introductionmentioning

confidence: 99%

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Effect of the Aerosol Type Selection for the Retrieval of Shortwave Ground Net Radiation: Case Study Using Landsat 8 Data

et al. 2016

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This paper discusses the aerosol radiative effects involved in the accuracy of shortwave net radiation, R n.sw , with sw ∈ (400-900) nm, retrieved by the Operational Land Imager (OLI), the new generation sensor of the Landsat mission. Net radiation is a key parameter for the energy exchange between the land and atmosphere; thus, R n.sw retrieval from space is under investigation by exploiting the increased spatial resolution of the visible and near-infrared OLI data. We adopted the latest version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) atmospheric radiative transfer model implemented in the atmospheric correction algorithm (OLI Atmospherically-Corrected Reflectance Imagery (OLI@CRI)) developed specifically for OLI data. The values of R n.sw were obtained by varying the microphysical properties of the aerosol during the OLI@CRI retrieval of both the OLI surface reflectance, ρ oli pxl , and the incoming solar irradiance at the surface. The analysis of the aerosol effects on the R n.sw was carried out on a spectrally-homogeneous desert area located in the southwestern Nile Delta. The results reveal that the R n.sw available for energy exchange between the land and atmosphere reduces the accuracy (NRMSE 14%) when the local aerosol microphysical properties are not considered during the processing of space data. Consequently, these findings suggest that the aerosol type should be considered for variables retrieved by satellite observations concerning the energy exchange in the natural ecosystems, such as Photosynthetically-Active Radiation (PAR). This will also improve the accuracy of land monitoring and of solar energy for power generation when space data are used.

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Intercomparison of Landsat albedo retrieval techniques and evaluation against in situ measurements across the US SURFRAD network

Cited by 59 publications

References 35 publications

Analysis of Extracting Prior BRDF from MODIS BRDF Data

Analysis of Extracting Prior BRDF from MODIS BRDF Data

Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach

Effect of the Aerosol Type Selection for the Retrieval of Shortwave Ground Net Radiation: Case Study Using Landsat 8 Data

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