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  • Articles  (3)
  • Architecture, Civil Engineering, Surveying  (3)
  • 1
    Publication Date: 2017-12-02
    Description: Remote Sensing, Vol. 9, Pages 1247: Estimating Land Surface Temperature from Feng Yun-3C/MERSI Data Using a New Land Surface Emissivity Scheme Remote Sensing doi: 10.3390/rs9121247 Authors: Xiangchen Meng Jie Cheng Shunlin Liang Land surface temperature (LST) is a key parameter for a wide number of applications, including hydrology, meteorology and surface energy balance. In this study, we first proposed a new land surface emissivity (LSE) scheme, including a lookup table-based method to determine the vegetated surface emissivity and an empirical method to derive the bare soil emissivity from the Global LAnd Surface Satellite (GLASS) broadband emissivity (BBE) product. Then, the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis data and the Feng Yun-3C/Medium Resolution Spectral Imager (FY-3C/MERSI) precipitable water vapor product were used to correct the atmospheric effects. After resolving the land surface emissivity and atmospheric effects, the LST was derived in a straightforward manner from the FY-3C/MERSI data by the radiative transfer equation algorithm and the generalized single-channel algorithm. The mean difference between the derived LSE and field-measured LSE over seven stations is approximately 0.002. Validation of the LST retrieved with the LSE determined by the new scheme can achieve an acceptable accuracy. The absolute biases are less than 1 K and the STDs (RMSEs) are less than 1.95 K (2.2 K) for both the 1000 m and 250 m spatial resolutions. The LST accuracy is superior to that retrieved with the LSE determined by the commonly used Normalized Difference Vegetation Index (NDVI) threshold method. Thus, the new emissivity scheme can be used to improve the accuracy of the LSE and further the LST for sensors with broad spectral ranges such as FY-3C/MERSI.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI Publishing
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  • 2
    Publication Date: 2018-03-20
    Description: Remote Sensing, Vol. 10, Pages 474: Evaluating Eight Global Reanalysis Products for Atmospheric Correction of Thermal Infrared Sensor—Application to Landsat 8 TIRS10 Data Remote Sensing doi: 10.3390/rs10030474 Authors: Xiangchen Meng Jie Cheng Global reanalysis products have been widely used for correcting the atmospheric effects of thermal infrared data, but their performances have not been comprehensively evaluated. In this paper, we evaluate eight global reanalysis products (NCEP/FNL; NCEP/DOE Reanalysis2; MERRA-3; MERRA-6; MERRA2-3; MERRA2-6; JRA-55; and ERA-Interim) commonly used in the atmospheric correction of Landsat 8 TIRS10 data by referencing global radiosonde observations collected from 163 stations. The atmospheric parameters (atmospheric transmittance, upward radiance, and downward radiance) simulated with MERRA-6 and ERA-Interim were accurate than those simulated with other reanalysis products for different water vapor contents and surface elevations. When global reanalysis products were applied to retrieve land surface temperature (LST) from simulated Landsat 8 TIRS10 data, ERA-Interim and MERRA-6 were accurate than other reanalysis products. The overall LST biases and RMSEs between the retrieved LSTs and LSTs that were used to generate the top-of-atmosphere radiances were less than 0.2 K and 1.09 K, respectively. When eight reanalysis products were used to estimate LSTs from thirty-two Landsat 8 TIRS10 images covering the Heihe River basin in China, the various reanalysis products showed similar validation accuracies for LSTs with low water vapor contents. The biases ranged from 0.07 K to 0.24 K, and the STDs (RMSEs) ranged from 1.93 K (1.93 K) to 2.02 K (2.04 K). Considering the above evaluation results, MERRA-6 and ERA-Interim are recommended for thermal infrared data atmospheric corrections.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI Publishing
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  • 3
    Publication Date: 2015-05-31
    Description: Vegetative filter strips (VFS) can effectively trap sediment in overland flow, but little information is available on its performance in controlling high-concentration sediment and the runoff hydraulics in VFS. Flume experiments were conducted to investigate the sediment deposition, hydraulics of overland flow and their relationships in simulating VFS under a great range of sediment concentrations with four levels of vegetation cover (bare slope and 4, 11 and 17%) and two flow rates (15 and 30 L min −1 ). Sediment concentrations varied from 30 to 400 kg m −3 and slope gradient was 9°. Both the deposited sediment load and deposition efficiency in VFS increased as the vegetation cover increased. Sediment concentration had a positive effect on the deposited load but no effect on deposition efficiency. A lower flow rate corresponded to greater deposition efficiency but had little effect on deposited load. Flow velocities decreased as vegetation cover increased. Sediment concentration had a negative effect on the mean velocity but no effect on surface velocity. Hydraulic resistance increased as the vegetation cover and sediment concentration increased. Sediment deposition efficiency had a much more pronounced relationship with overland flow hydraulics compared with deposited load, especially with the mean flow velocity, and there was a power relationship between them. Flow regime also affected the sediment deposition efficiency, and the efficiency was much higher under subcritical than supercritical flow. The results will be useful for the design of VFS and the control of sediment flowing into rivers in areas with serious soil erosion.
    Print ISSN: 0885-6087
    Electronic ISSN: 1099-1085
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by Wiley-Blackwell
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