Burned area and surface albedo products: Assessment of change consistency at global scale

Mota, Bernardo; Gobron, Nadine; Cappucci, Fabrizio; Morgan, Olivier

doi:10.1016/j.rse.2019.03.001

Cited by 12 publications

(7 citation statements)

References 35 publications

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“…By calculating the frequency of blue-sky albedo in the same range (Figure S2), the frequency of blue-sky albedo in grassland was the highest in the higher value range, while that in barren land was the highest in the lower value range. In addition, snowfall [50], overgrazing [51] and fire [52][53][54] have a great impact on the blue-sky albedo of grasslands, resulting in an increase in blue-sky albedo.…”

Section: Spatiotemporal Variation In Blue-sky Albedomentioning

confidence: 99%

Blue-Sky Albedo Reduction and Associated Influencing Factors of Stable Land Cover Types in the Middle-High Latitudes of the Northern Hemisphere during 1982–2015

et al. 2022

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Land surface albedo (LSA) directly affects the radiation balance and the surface heat budget. LSA is a key variable for local and global climate research. The complexity of LSA variations and the driving factors highlight the importance of continuous spatial and temporal monitoring. Snow, vegetation and soil are the main underlying surface factors affecting LSA dynamics. In this study, we combined Global Land Surface Satellite (GLASS) products and ERA5 reanalysis products to analyze the spatiotemporal variation and drivers of annual mean blue-sky albedo for stable land cover types in the middle-high latitudes of the Northern Hemisphere (30~90°N) from 1982 to 2015. Snow cover (SC) exhibited a decreasing trend in 99.59% of all pixels (23.73% significant), with a rate of −0.0813. Soil moisture (SM) exhibited a decreasing trend in 85.66% of all pixels (22.27% significant), with a rate of −0.0002. The leaf area index (LAI) exhibited a greening trend in 74.38% of all pixels (25.23% significant), with a rate of 0.0014. Blue-sky albedo exhibited a decreasing trend in 98.97% of all pixels (65.12% significant), with a rate of −0.0008 (OLS slope). Approximately 98.16% of all pixels (57.01% significant) exhibited a positive correlation between blue-sky albedo and SC. Approximately 47.78% and 67.38% of all pixels (17.13% and 25.3% significant, respectively) exhibited a negative correlation between blue-sky albedo and SM and LAI, respectively. Approximately 10.31%, 20.81% and 68.88% of the pixel blue-sky albedo reduction was mainly controlled by SC, SM and LAI, respectively. The decrease in blue-sky albedo north of 40°N was mainly caused by the decrease in SC. The decrease in blue-sky albedo south of 40°N was mainly caused by SM reduction and vegetation greening. The decrease in blue-sky albedo in the western Tibetan Plateau was caused by vegetation greening, SM increase and SC reduction. The results have important scientific significance for the study of surface processes and global climate change.

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Section: Spatiotemporal Variation In Blue-sky Albedomentioning

confidence: 99%

Blue-Sky Albedo Reduction and Associated Influencing Factors of Stable Land Cover Types in the Middle-High Latitudes of the Northern Hemisphere during 1982–2015

et al. 2022

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“…Satellite remote sensing is widely used as the most effective way to estimate surface albedo in large areas with long time series. Many albedo estimation algorithms [9][10][11] and global products [12][13][14][15] have been developed, which has boosted climate change research [16][17][18]. In recent years, fine spatial resolution (e.g., 10 to 50 m, hereinafter be shorted as "fineresolution") albedo estimation algorithms and datasets have been developed for fine-scale environmental monitoring and ecological applications [10,19,20], with a good potential for better understanding and quantifying energy budget in mountainous areas.…”

Section: Introductionmentioning

confidence: 99%

Landsat Snow-Free Surface Albedo Estimation Over Sloping Terrain: Algorithm Development and Evaluation

Liang

et al. 2022

IEEE Trans. Geosci. Remote Sensing

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Surface albedo plays a key role in global climate modeling as a factor controlling the energy budget. Satellite observations were utilized to estimate surface albedo at global and regional scales with good precision over flat areas. However, because topography greatly complicates radiative transfer processes, estimating the albedo of rugged terrain with satellite data remains a challenge. Additionally, albedo definitions over sloping terrain differ from that for flat areas. They include horizontal/horizontal sloped surface albedo (HHSA) and inclined/inclined sloped surface albedo (IISA). Methods for retrieving HHSA and IISA in mountains have not been wellexplored. Here, we retrieved HHSA and IISA on sloping terrain from Landsat 8 using a direct estimation algorithm. We simulated a dataset of Landsat top-of-atmosphere (TOA) reflectance and surface albedo with Discrete Anisotropic Radiative Transfer (DART) model, for variable atmospheric, vegetation, soil and topography properties. Then, we used artificial neural networks to derive an empirical relationship between TOA reflectance and surface albedo. The accuracy of our method was verified with insitu measurements: root mean squared error (RMSE) and bias equal to 0.029 and -0.010 for HHSA, and 0.023 and -0.001 for IISA, respectively. Several albedo results (HHSA, IISA, values without topographic consideration) were evaluated and compared. HHSA was found similar to albedo without topographic consideration, but IISA, considered as the "true albedo" for sloping terrain, showed large difference from them. This study demonstrated the feasibility of surface albedo estimation from Landsat TOA reflectance directly in rugged terrains and advanced our understanding of energy budget in mountains.

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“… Mota and Gobron (2017) , Mota et al (2019) proposed a framework that can be used for any combination of physically linked ECVs and we adapted the methodology to assess cross-ECV consistency between LAI and FAPAR.…”

Section: Introductionmentioning

confidence: 99%

Cross-ECV consistency at global scale: LAI and FAPAR changes

Mota

Gobron

Morgan

et al. 2021

Remote Sensing of Environment

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A framework is proposed for assessing the physical consistency between two terrestrial Essential Climate Variables (ECVs) products retrieved from Earth Observation at global scale. The methodology assessed the level of agreement between the temporal variations of Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). The simultaneous changes were classified according to their sign, magnitude and level of confidence, whereby the respective products uncertainties were taken into consideration. A set of proposed agreement metrics were used to identify temporal and spatial biases of non-coherency, non-significance, sensitivity and the overall level of agreement of the temporal changes between two ECVs. We applied the methodology using the Joint Research Center (JRC) Two-stream Inversion Package (TIP) products at 1 km, those provided by the Copernicus Global Land Service (CGLS) based on the SPOT/VGT and Proba-V at 1 km, and the MODIS MCD15A3 at 500 m. In addition, the same analysis was applied with aggregated products at a larger scale over Southern Africa. We found that the CGLS LAI and FAPAR products lacked consistency in their spatial and temporal changes and were severely affected by trends. The MCD15A3 products were characterized by the highest number of non-coherent changes between the two ECVs but temporal inconsistencies were mainly located over the eastern hemisphere. The JRC-TIP products were highly consistent. The results showed the advantages of physically-based retrieval algorithms, in both JRC-TIP and MODIS products, and indicated also that, except for MODIS over forests, aggregated products using an uncertainty-based weighted average led to higher agreement between the ECVs changes.

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Burned area and surface albedo products: Assessment of change consistency at global scale

Cited by 12 publications

References 35 publications

Blue-Sky Albedo Reduction and Associated Influencing Factors of Stable Land Cover Types in the Middle-High Latitudes of the Northern Hemisphere during 1982–2015

Blue-Sky Albedo Reduction and Associated Influencing Factors of Stable Land Cover Types in the Middle-High Latitudes of the Northern Hemisphere during 1982–2015

Landsat Snow-Free Surface Albedo Estimation Over Sloping Terrain: Algorithm Development and Evaluation

Cross-ECV consistency at global scale: LAI and FAPAR changes

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