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Assessment of Root Zone Soil Moisture Estimations from SMAP, SMOS and MODIS Observations

Miriam Pablos, Ángel González-Zamora, Nilda Sánchez, José Martínez-Fernández
2018 Remote Sensing  
The first two were the Soil Moisture Active Passive (SMAP) and the Soil Moisture and Ocean Salinity (SMOS) L4 RZSM products.  ...  In this study, six satellite-based root zone soil moisture (RZSM) estimates from March 2015 to December 2016 were evaluated both temporally and spatially.  ...  Estimation of Root Zone Soil Moisture from SMOS-BEC and MODIS ATI Surface Soil Moisture The SWI model was used to estimate the RZSM from the SMOS-BEC and MODIS ATI SSM.  ... 
doi:10.3390/rs10070981 fatcat:dvi3qn5yj5hgdls6lgw3gy3cvm

Mapping High Spatiotemporal-Resolution Soil Moisture by Upscaling Sparse Ground-Based Observations Using a Bayesian Linear Regression Method for Comparison with Microwave Remotely Sensed Soil Moisture Products

Jian Kang, Rui Jin, Xin Li, Yang Zhang
2021 Remote Sensing  
The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2  ...  , SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI.  ...  Finally, multiple RS SM products, including the Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), Advanced Microwave Scanning Radiometer 2 (AMSR2) and Climate Change Initiative  ... 
doi:10.3390/rs13020228 fatcat:kno7wpt3jng5rnilhxaii6mzji

Very High Spatial Resolution Downscaled SMAP Radiometer Soil Moisture in the CONUS Using VIIRS/MODIS Data

Bin Fang, Venkat Lakshmi, Michael Cosh, Christopher Hain
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
sciences, specifically after the Soil Moisture Active and Passive (SMAP) was launched in 2015.  ...  Satellite remote sensing has been providing passive microwave soil moisture (SM) retrievals of a global spatial coverage and a high revisit frequency for research and applications in earth and environmental  ...  USDA is an equal opportunity provider and employer.  ... 
doi:10.1109/jstars.2021.3076026 fatcat:kamd5c36b5aq7dexnoh5hdhn7m

An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data

Bouchra Ait Hssaine, Olivier Merlin, Jamal Ezzahar, Nitu Ojha, Salah Er-raki, Said Khabba
2019 Hydrology and Earth System Sciences Discussions  
<i>f<sub>c</sub></i> data and the 1&amp;thinsp;km resolution <i>SM</i> data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh.  ...  The daily calibrated <i>&amp;alpha;<sub>PT</sub></i> ranges between 0 and 1.38 for both S1 and S2.  ...  Such a delay is attributed to the high soil moisture level in the root-zone during the maturity stage. Later in the season, α P T decreases as N DV I starts to decline 20 at the onset of senescence.  ... 
doi:10.5194/hess-2019-105 fatcat:kv7clwd32rdspegbwaxbb4s4se


R. Prajapati, D. Chakraborty, V. Kumar
2018 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Passive and Active) missions launched in 2009 and 2015 respectively, are completely dedicated for providing soil moisture at global scale  ...  Microwave remote sensing techniques have a long legacy of providing surface soil moisture estimates with reasonable accuracy.  ...  Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP).  ... 
doi:10.5194/isprs-archives-xlii-5-861-2018 fatcat:rbh4qcy75babfjrygjrnray77q

Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture dataset

Pei Zhang, Donghai Zheng, Rogier van der Velde, Jun Wen, Yijian Zeng, Xin Wang, Zuoliang Wang, Jiali Chen, Zhongbo Su
2021 Earth System Science Data  
The Tibetan Plateau observatory (Tibet-Obs) of plateau scale soil moisture and soil temperature was established 10 years ago and has been widely used to calibrate/validate satellite- and model-based soil  ...  Comparisons between four spatial upscaling methods – i.e. arithmetic averaging, Voronoi diagrams, time stability, and apparent thermal inertia – show that the arithmetic average of the monitoring sites  ...  Hassler and reviewed by Mirko Mälicke and one anonymous referee.  ... 
doi:10.5194/essd-13-3075-2021 fatcat:bzv5j3wcirb6xos2pfzpmtqwzy

Actual evapotranspiration in drylands derived from in-situ and satellite data: Assessing biophysical constraints

Monica García, Inge Sandholt, Pietro Ceccato, Marc Ridler, Eric Mougin, Laurent Kergoat, Laura Morillas, Franck Timouk, Rasmus Fensholt, Francisco Domingo
2013 Remote Sensing of Environment  
PT-JPL-daily model with a soil moisture constraint based on apparent thermal inertia, f SM-ATI offers great potential for regionalization as no field-calibrations are required and water vapor deficit estimates  ...  The novelty of this paper is the computation of a key model parameter, the soil moisture constraint, relying on the concept of apparent thermal inertia (f SM-ATI ) computed with surface temperature and  ...  The authors acknowledge helpful comments and feedback from Mads Olander Rasmussen, Hector Nieto and Simon Proud.  ... 
doi:10.1016/j.rse.2012.12.016 fatcat:o7ybjhk2bngtzeom25rvwzn7qa

Estimating Regional Soil Moisture Distribution Based on NDVI and Land Surface Temperature Time Series Data in the Upstream of the Heihe River Watershed, Northwest China

Xiao Bai, Lanhui Zhang, Chansheng He, Yi Zhu
2020 Remote Sensing  
estimate the soil moisture (0–70 cm) on a regional scale with a spatial resolution of 1 km2 and a temporal resolution of 16-d from October, 2013 to September, 2016.  ...  The correlation coefficient R of the regression equations was between 0.47 and 0.94, the RMSE was 0.03, indicating that the estimation method based on the MODIS NDVI and LST data was suitable and could  ...  Acknowledgments: We are grateful to the members of the Center for Dryland Water Resources Research and Watershed Science, Lanzhou University for their hard field work to collect and analyze the soil data  ... 
doi:10.3390/rs12152414 fatcat:65hk3mp6hvhsxnql2hnoocgw34

Soil Moisture Retrieval by Integrating TASI-600 Airborne Thermal Data, WorldView 2 Satellite Data and Field Measurements: Petacciato Case Study

Angelo Palombo, Simone Pascucci, Antonio Loperte, Antonio Lettino, Fabio Castaldi, Maria Rita Muolo, Federico Santini
2019 Sensors  
Results show a good correlation (R2 = 0.62) between the estimated ATI and the SM of the soil samples measured in the laboratory.  ...  Soil moisture (SM) plays a fundamental role in the terrestrial water cycle and in agriculture, with key applications such as the monitoring of crop growing and hydrogeological management.  ...  Several satellite missions including SMOS (Soil Moisture and Ocean Salinity, [6] ), SMAP (Soil moisture Active and Passive, [7] ), ASCAT (Advanced Scatterometer [8] ), provide SM estimates at coarse  ... 
doi:10.3390/s19071515 fatcat:bkjkf7qovbdybdvz7wlrrow2fy

Optical and Thermal Remote Sensing for Monitoring Agricultural Drought

Qiming Qin, Zihua Wu, Tianyuan Zhang, Vasit Sagan, Zhaoxu Zhang, Yao Zhang, Chengye Zhang, Huazhong Ren, Yuanheng Sun, Wei Xu, Cong Zhao
2021 Remote Sensing  
We group the methods into four categories: optical, thermal, optical and thermal, and multi-source. For each category, a concise explanation is given to show the inherent mechanisms.  ...  prediction and assessment based on deep learning and cloud computing.  ...  Additionally, PF does not rely on the crosscovariance between the surface and root-zone soil moisture.  ... 
doi:10.3390/rs13245092 fatcat:iuvq5u5hcrdclhd2oqn2qokree

Improving Soil Moisture Estimation with a Dual Ensemble Kalman Smoother by Jointly Assimilating AMSR-E Brightness Temperature and MODIS LST

Weijing Chen, Huanfeng Shen, Chunlin Huang, Xin Li
2017 Remote Sensing  
Uncertainties in model parameters can easily result in systematic differences between model states and observations, which significantly affect the accuracy of soil moisture estimation in data assimilation  ...  The results demonstrate the potential of assimilating AMSR-E TB and MODIS LST to improve the estimation of soil moisture and related parameters.  ...  data sets at the global scale, such as SSM/I (Special Sensor Microwave/Image), AMSR-E, SMOS (Soil Moisture and Ocean Salinity), SMAP (Soil Moisture Active Passive), etc.  ... 
doi:10.3390/rs9030273 fatcat:sfw3z2fdunct7eftpw3oygf6j4

Evaluation of the Airborne CASI/TASI Ts-VI Space Method for Estimating Near-Surface Soil Moisture

Lei Fan, Qing Xiao, Jianguang Wen, Qiang Liu, Yong Tang, Dongqin You, Heshun Wang, Zhaoning Gong, Xiaowen Li
2015 Remote Sensing  
were explored to improve the performance of the Ts/VI space method for estimating soil moisture (SM).  ...  The validation results show that the EF approach provides superior estimates with a lower RMSE (0.023 m 3 ·m −3 ) value and a higher correlation coefficient (0.68) than the TVDI.  ...  Soil Moisture Active Passive (SMAP) satellites [13] .  ... 
doi:10.3390/rs70303114 fatcat:m7yofojgj5hljga7vagutxrdem

Mixed pixel retrieval of soil moisture from L-band passive microwave observations

Nan Ye
Soil moisture plays a key role in the water, energy, and carbon exchanges at the interface between the atmosphere and earth surface.  ...  At such a coarse scale, non-soil targets such as surface rock, urban areas, and standing water are present within many SMOS and SMAP pixels across the world, potentially confounding the radiometric observations  ...  A fundamental difference between SMOS and SMAP is that it aims to have a spatial resolution of better than 10km for soil moisture.  ... 
doi:10.4225/03/58b3a1124bcd9 fatcat:hqxn6dvh45bbdkgwvavgy4gizi