کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8866914 | 1621196 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Development and assessment of the SMAP enhanced passive soil moisture product
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
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چکیده انگلیسی
This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E). The product distinguishes itself from the current SMAP Level 2 Passive Soil Moisture Product (L2_SM_P) in that the soil moisture retrieval is posted on a 9Â km grid instead of a 36Â km grid. This is made possible by first applying the Backus-Gilbert optimal interpolation technique to the antenna temperature (TA) data in the original SMAP Level 1B Brightness Temperature Product to take advantage of the overlapped radiometer footprints on orbit. The resulting interpolated TA data then go through various correction/calibration procedures to become the SMAP Level 1C Enhanced Brightness Temperature Product (L1C_TB_E). The L1C_TB_E product, posted on a 9Â km grid, is then used as the primary input to the current operational SMAP baseline soil moisture retrieval algorithm to produce L2_SM_P_E as the final output. Images of the new product reveal enhanced visual features that are not apparent in the standard product. Based on in situ data from core validation sites and sparse networks representing different seasons and biomes all over the world, comparisons between L2_SM_P_E and in situ data were performed for the duration of April 1, 2015-October 30, 2016. It was found that the performance of the enhanced 9Â km L2_SM_P_E is equivalent to that of the standard 36Â km L2_SM_P, attaining a retrieval uncertainty below 0.040Â m3/m3 unbiased root-mean-square error (ubRMSE) and a correlation coefficient above 0.800. This assessment also affirmed that the Single Channel Algorithm using the V-polarized TB channel (SCA-V) delivered the best retrieval performance among the various algorithms implemented for L2_SM_P_E, a result similar to a previous assessment for L2_SM_P.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 204, January 2018, Pages 931-941
Journal: Remote Sensing of Environment - Volume 204, January 2018, Pages 931-941
نویسندگان
S.K. Chan, R. Bindlish, P. O'Neill, T. Jackson, E. Njoku, S. Dunbar, J. Chaubell, J. Piepmeier, S. Yueh, D. Entekhabi, A. Colliander, F. Chen, M.H. Cosh, T. Caldwell, J. Walker, A. Berg, H. McNairn, M. Thibeault, Y. Kerr,