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  • Earth Resources and Remote Sensing  (2)
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  • 1
    Publication Date: 2019-07-27
    Description: Increased prevalence of weather related hazards in eastern Africa including drought, floods, hail and frost threatening agricultural productivity. Kenya is heavily dependent on agriculture for economic growth (FAO 2013); (1) Agriculture contributed 23.5% and 21.5% of GDP in 2009 and 2010 respectively, (2) Employment to half a million households of smallholders and 150,000 on large tea estates. Tea growing in Kenya depends on stability of the weather; (1) Weather is unpredictable, (2) Frost has contributed 30% of tea leaf losses, (3) Drought has contributed 14-30%, (4) The losses are experienced between January and march - frost and dry season.
    Keywords: Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN41290 , American Association of Geographers (AAG) Annual Meeting; 3-7 Apr. 201; Boston, MA; United States
    Format: application/pdf
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  • 2
    Publication Date: 2019-08-26
    Description: The Soil Moisture Active Passive (SMAP) mission is dedicated toward global soil moisture mapping. Typically, an L-band microwave radiometer has spatial resolution on the order of 36-40 km, which is too coarse for many specific hydro-meteorological and agricultural applications. With the failure of the SMAP active radar within three months of becoming operational, an intermediate (9-km) and finer (3-km) scale soil moisture product solely from the SMAP mission is no longer possible. Therefore, the focus of this study is a disaggregation of the 36-km resolution SMAP passive-only surface soil moisture (SSM) using the Soil Evaporative Efficiency (SEE) approach to spatial scales of 3-km and 9-km. The SEE was computed using thermal-infrared (TIR) estimation of surface evaporation over Continental U.S. (CONUS). The disaggregation results were compared with the 3 months of SMAP-Active (SMAP-A) and Active/Passive (AP) products, while comparisons with SMAP-Enhanced (SMAP-E), SMAP-Passive (SMAP-P), as well as with more than 180 Soil Climate Analysis Network (SCAN) stations across CONUS were performed for a 19 month period. At the 9-km spatial scale, the TIR-Downscaled data correlated strongly with the SMAP-E SSM both spatially (r = 0.90) and temporally (r = 0.87). In comparison with SCAN observations, overall correlations of 0.49 and 0.47; bias of 0.022 and 0.019 and unbiased RMSD of 0.105 and 0.100 were found for SMAP-E and TIR-Downscaled SSM across the Continental U.S., respectively. At 3-km scale, TIR-Downscaled and SMAP-A had a mean temporal correlation of only 0.27. In terms of gain statistics, the highest percentage of SCAN sites with positive gains (〉55%) was observed with the TIR-Downscaled SSM at 9-km. Overall, the TIR-based downscaled SSM showed strong correspondence with SMAP-E; compared to SCAN, and overall both SMAP-E and TIR-Downscaled performed similarly, however, gain statistics show that TIR-Downscaled SSM slightly outperformed SMAP-E.
    Keywords: Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN53221 , International Journal of Applied Earth Observation and Geoinformation (ISSN 0303-2434); 68; 92-104
    Format: application/pdf
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