2015
DOI: 10.3390/rs70404112
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Toward the Estimation of Surface Soil Moisture Content Using Geostationary Satellite Data over Sparsely Vegetated Area

Abstract: Based on a novel bare surface soil moisture (SSM) retrieval model developed from the synergistic use of the diurnal cycles of land surface temperature (LST) and net surface shortwave radiation (NSSR) (Leng et al. 2014. "Bare Surface Soil Moisture Retrieval from the Synergistic Use of Optical and Thermal Infrared Data". International Journal of Remote Sensing 35: 988-1003.), this paper mainly investigated the model's capability to estimate SSM using geostationary satellite observations over vegetated area. Resu… Show more

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Cited by 13 publications
(7 citation statements)
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“…For decades, satellite-based thermal imaging cameras have been extensively used to monitor vegetation and crop conditions on a regional scale [4], estimate energy fluxes and soil moisture [5][6][7][8][9], detect plant water stress [10,11], predict yield [12], and monitor regional drought [13][14][15][16]. However, their usefulness in precision agriculture and small area phenotyping has been mixed due to the fact that their spatial resolution and the homogeneity of data with large pixels is typically not suitable for precision agriculture.…”
Section: Introductionmentioning
confidence: 99%
“…For decades, satellite-based thermal imaging cameras have been extensively used to monitor vegetation and crop conditions on a regional scale [4], estimate energy fluxes and soil moisture [5][6][7][8][9], detect plant water stress [10,11], predict yield [12], and monitor regional drought [13][14][15][16]. However, their usefulness in precision agriculture and small area phenotyping has been mixed due to the fact that their spatial resolution and the homogeneity of data with large pixels is typically not suitable for precision agriculture.…”
Section: Introductionmentioning
confidence: 99%
“…This disadvantage makes the SSM retrieval model inconvenience to use, especially with the geostationary satellite images. In a previous study (Leng et al, 2015), a calibration method was attempted to obtain the model coefficients over the REMEDHUS network (Spain) using combined in-situ SSM measurements and the Meteosat Second Generation (MSG) images. Although the calibrated coefficients revealed good results between estimated SSM and ground SSM measurements, the calibration process is generally complicated, and a number of in-situ SSM measurements are required.…”
Section: Introductionmentioning
confidence: 99%
“…Although initially the goal was to support algorithm development and validation of the SMOS satellite, which was indeed the case for 79 studies, many other satellite missions profited from the ISMN data, most notably ASCAT (n=45),AMSR-E (n=44), SMAP (n=39), and ESA CCI (n=22). Fortuitously, the data have also been discovered for the evaluation of soil moisture products from less used sensors, including the Chinese Feng-Yun 3B, HY-2 and Gaofen-1 satellites (Parinussa et al, 2014a(Parinussa et al, , 2018Zhao et al, 2014;Xing et al, 2017), MSG SIVIRI (Leng et al, 2015(Leng et al, , 2017, MODIS (Gumbricht et al, 2017;Gumbricht, 2018), Aquarius (González-Zamora et al, 2016), and Landsat (Zhao et al, 2017;Pradhan, 2019).…”
Section: Scientific Studiesmentioning
confidence: 99%