Geography

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    Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach
    (MDPI, 2015-05-04) He, Tao; Liang, Shunlin; Wang, Dongdong; Chen, Xiaona; Song, Dan-Xia; Jiang, Bo
    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 (R2) 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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    A Mapping Framework to Characterize Land Use in the Sudan-Sahel Region from Dense Stacks of Landsat Data
    (MDPI, 2019-03-16) Sedano, Fernando; Molini, Vasco; Azad, M. Abdul Kalam
    We developed a land cover and land use mapping framework specifically designed for agricultural systems of the Sudan-Sahel region. The mapping approach extracts information from inter- and intra-annual vegetation dynamics from dense stacks of Landsat 8 images. We applied this framework to create a 30 m spatial resolution land use map with a focus on agricultural landscapes of northern Nigeria for 2015. This map provides up-to-date information with a higher level of spatial and thematic detail resulting in a more precise characterization of agriculture in the region. The map reveals that agriculture is the main land use in the region. Arable land represents on average 52.5% of the area, higher than the reported national average for Nigeria (38.4%). Irrigated agriculture covers nearly 2.2% of the total area, reaching nearly 20% of the cultivated land when traditional floodplain agriculture systems are included, above the reported national average (0.63%). There is significant variability in land use within the region. Cultivated land in the northern section can reach values higher than 75%, most land suitable for agriculture is already under cultivation and there is limited land for future agricultural expansion. Marginal lands, not suitable for permanent agriculture, can reach 30% of the land at lower altitudes in the northeast and northwest. In contrast, the southern section presents lower land use intensity that results in a complex landscape that intertwines areas farms and larger patches of natural vegetation. This map improves the spatial detail of existing sources of LCLU information for the region and provides updated information of the current status of its agricultural landscapes. This study demonstrates the feasibility of multi temporal medium resolution remote sensing data to provide detailed and up-to-date information about agricultural systems in arid and sub arid landscapes of the Sahel region.
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    Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach
    (Multidisciplinary Digital Publishing Institute (MDPI), 2015-05-04) He, Tao; Liang, Shunlin; Wang, Dongdong; Chen, Xiaona; Song, Dan-Xia; Jiang, Bo
    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 (R2) 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.