An Approach for Downscaling SMAP Soil Moisture by Combining Sentinel-1 SAR and MODIS Data

[1]  Jong-Sen Lee,et al.  Polarimetric SAR speckle filtering and its implication for classification , 1999, IEEE Trans. Geosci. Remote. Sens..

[2]  Mahta Moghaddam,et al.  A Combined Active–Passive Soil Moisture Estimation Algorithm With Adaptive Regularization in Support of SMAP , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Jiancheng Shi,et al.  Tests of the SMAP Combined Radar and Radiometer Algorithm Using Airborne Field Campaign Observations and Simulated Data , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Yann Kerr,et al.  An RFI Index to Quantify the Contamination of SMOS Data by Radio-Frequency Interference , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[5]  Maosheng Zhao,et al.  Development of a global evapotranspiration algorithm based on MODIS and global meteorology data , 2007 .

[6]  Y. Kerr,et al.  State of the Art in Large-Scale Soil Moisture Monitoring , 2013 .

[7]  Thomas J. Jackson,et al.  Spatially enhanced passive microwave derived soil moisture: Capabilities and opportunities , 2018 .

[8]  Ahmet Emre Tekeli,et al.  Reducing False Flood Warnings of TRMM Rain Rates Thresholds over Riyadh City, Saudi Arabia by Utilizing AMSR-E Soil Moisture Information , 2017, Water Resources Management.

[9]  Dara Entekhabi,et al.  An Algorithm for Merging SMAP Radiometer and Radar Data for High-Resolution Soil-Moisture Retrieval , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Tao Han,et al.  Evaluation of Data Quality and Drought Monitoring Capability of FY-3A MERSI Data , 2010, Adv. Artif. Intell..

[11]  Adriano Camps,et al.  A Change Detection Algorithm for Retrieving High-Resolution Soil Moisture From SMAP Radar and Radiometer Observations , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Jungho Im,et al.  Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches , 2016, Environmental Earth Sciences.

[13]  Emanuele Santi,et al.  An application of the SFIM technique to enhance the spatial resolution of spaceborne microwave radiometers , 2010 .

[14]  Mehrez Zribi,et al.  Synergic Use of Sentinel-1 and Sentinel-2 Images for Operational Soil Moisture Mapping at High Spatial Resolution over Agricultural Areas , 2017, Remote. Sens..

[15]  Andreas Colliander,et al.  SMAP soil moisture improves global evapotranspiration , 2018, Remote Sensing of Environment.

[16]  Terri S. Hogue,et al.  Improving Spatial Soil Moisture Representation Through Integration of AMSR-E and MODIS Products , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Lingkui Meng,et al.  Downscaling SMAP soil moisture estimation with gradient boosting decision tree regression over the Tibetan Plateau , 2019, Remote Sensing of Environment.

[18]  Heather McNairn,et al.  Using multi-polarization C- and L-band synthetic aperture radar to estimate biomass and soil moisture of wheat fields , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[19]  Ainong Li,et al.  Performance Evaluation of the Triangle-Based Empirical Soil Moisture Relationship Models Based on Landsat-5 TM Data and In Situ Measurements , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Xin Li,et al.  Evaluation of four remote sensing based land cover products over China , 2010 .

[21]  Jie Wang,et al.  Evaluation of Satellite and Reanalysis Soil Moisture Products over Southwest China Using Ground-Based Measurements , 2015, Remote. Sens..

[22]  Seokhyeon Kim,et al.  Building a Flood-Warning Framework for Ungauged Locations Using Low Resolution, Open-Access Remotely Sensed Surface Soil Moisture, Precipitation, Soil, and Topographic Information , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[23]  Dan-Li Xi,et al.  Distribution characteristics and source analysis of dioxins in sediments and mussels from Qingdao coastal sea. , 2008, Chemosphere.

[24]  Wade T. Crow,et al.  Effect of vegetation index choice on soil moisture retrievals via the synergistic use of synthetic aperture radar and optical remote sensing , 2019, Int. J. Appl. Earth Obs. Geoinformation.

[25]  Jie Wang,et al.  Spatial Downscaling of Satellite Soil Moisture Data Using a Vegetation Temperature Condition Index , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[26]  Thomas Jagdhuber,et al.  Estimation of active-passive microwave covariation using SMAP and Sentinel-1 data , 2019, Remote Sensing of Environment.

[27]  Salah Er-Raki,et al.  Including Sentinel-1 radar data to improve the disaggregation of MODIS land surface temperature data , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[28]  Emanuele Santi,et al.  Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation , 2013 .

[29]  Irena Hajnsek,et al.  Investigation of SMAP Fusion Algorithms With Airborne Active and Passive L-Band Microwave Remote Sensing , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[30]  Philippe Richaume,et al.  Disaggregation of SMOS Soil Moisture in Southeastern Australia , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[31]  Jaroslaw Zawadzki,et al.  Soil moisture variability over Odra watershed: Comparison between SMOS and GLDAS data , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[32]  Yann Kerr,et al.  Development and Assessment of the SMAP Enhanced Passive Soil Moisture Product. , 2018, Remote sensing of environment.

[33]  José Martínez-Fernández,et al.  Integrated remote sensing approach to global agricultural drought monitoring , 2018, Agricultural and Forest Meteorology.

[34]  Jiancheng Shi,et al.  The Soil Moisture Active Passive (SMAP) Mission , 2010, Proceedings of the IEEE.

[35]  Adriano Camps,et al.  A Downscaling Approach for SMOS Land Observations: Evaluation of High-Resolution Soil Moisture Maps Over the Iberian Peninsula , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[36]  Hui Wang,et al.  Preliminary Evaluation of the SMAP Radiometer Soil Moisture Product over China Using In Situ Data , 2017, Remote. Sens..

[37]  Tongren Xu,et al.  A soil moisture estimation framework based on the CART algorithm and its application in China , 2018, Journal of Hydrology.

[38]  Yann Kerr,et al.  Downscaling SMOS-Derived Soil Moisture Using MODIS Visible/Infrared Data , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[39]  Claudia Notarnicola,et al.  Estimation of Soil Moisture in Vegetation-Covered Floodplains with Sentinel-1 SAR Data Using Support Vector Regression , 2018, PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science.

[40]  Christoph Rüdiger,et al.  Medium-Resolution Soil Moisture Retrieval Using the Bayesian Merging Method , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[41]  Minha Choi,et al.  A microwave-optical/infrared disaggregation for improving spatial representation of soil moisture using AMSR-E and MODIS products , 2012 .

[42]  José Martínez-Fernández,et al.  Satellite soil moisture for agricultural drought monitoring: Assessment of the SMOS derived Soil Water Deficit Index , 2016 .

[43]  W. Lucht,et al.  Considerations in the parametric modeling of BRDF and albedo from multiangular satellite sensor observations , 2000 .

[44]  Niko E. C. Verhoest,et al.  Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[45]  Adriano Camps,et al.  Impact of day/night time land surface temperature in soil moisture disaggregation algorithms , 2016 .

[46]  Wei Zhao,et al.  A comparison study on empirical microwave soil moisture downscaling methods based on the integration of microwave-optical/IR data on the Tibetan Plateau , 2015 .

[47]  Qian Cui,et al.  Assessment of the SMAP-Derived Soil Water Deficit Index (SWDI-SMAP) as an Agricultural Drought Index in China , 2018, Remote. Sens..

[48]  W. Wagner,et al.  Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates. , 2017, Geophysical research letters.

[49]  Dara Entekhabi,et al.  Sensitivity of Aquarius Active and Passive Measurements Temporal Covariability to Land Surface Characteristics , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[50]  Yann Kerr,et al.  A Simple Method to Disaggregate Passive Microwave-Based Soil Moisture , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[51]  Mehrez Zribi,et al.  Calibration of the Water Cloud Model at C-Band for Winter Crop Fields and Grasslands , 2017, Remote. Sens..

[52]  Jarosław Zawadzki,et al.  Comparative study of soil moisture estimations from SMOS satellite mission, GLDAS database, and cosmic-ray neutrons measurements at COSMOS station in Eastern Poland , 2016 .

[53]  Emanuele Santi,et al.  On the synergy of SMAP, AMSR2 AND SENTINEL-1 for retrieving soil moisture , 2018, Int. J. Appl. Earth Obs. Geoinformation.

[54]  T. Carlson An Overview of the “Triangle Method” for Estimating Surface Evapotranspiration and Soil Moisture from Satellite Imagery , 2007, Sensors (Basel, Switzerland).

[55]  S. Liang Narrowband to broadband conversions of land surface albedo I Algorithms , 2001 .

[56]  Leung Tsang,et al.  Soil moisture retrieval from time series multi-angular radar data using a dry down constraint , 2019, Remote Sensing of Environment.

[57]  Filipe Aires,et al.  Global downscaling of remotely sensed soil moisture using neural networks , 2018, Hydrology and Earth System Sciences.

[58]  Yingying Chen,et al.  The Evaluation of SMAP Enhanced Soil Moisture Products Using High-Resolution Model Simulations and In-Situ Observations on the Tibetan Plateau , 2018, Remote. Sens..

[59]  John S. Kimball,et al.  Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat. , 2018, Remote sensing of environment.

[60]  Ashish Sharma,et al.  A comprehensive validation of the SMAP Enhanced Level-3 Soil Moisture product using ground measurements over varied climates and landscapes , 2019, Remote Sensing of Environment.

[61]  Lian He,et al.  Investigation of SMAP Active–Passive Downscaling Algorithms Using Combined Sentinel-1 SAR and SMAP Radiometer Data , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[62]  Niko E. C. Verhoest,et al.  A review of spatial downscaling of satellite remotely sensed soil moisture , 2017 .

[63]  Emanuele Santi,et al.  Integration of microwave data from SMAP and AMSR2 for soil moisture monitoring in Italy , 2018, Remote Sensing of Environment.

[64]  Nengcheng Chen,et al.  Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive assessment using global ground-based observations , 2019, Remote Sensing of Environment.

[65]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[66]  N. Sánchez,et al.  A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression , 2018 .

[67]  Koreen Millard,et al.  Quantifying the relative contributions of vegetation and soil moisture conditions to polarimetric C-Band SAR response in a temperate peatland , 2018 .

[68]  Shusen Wang,et al.  A model for downscaling SMOS soil moisture using Sentinel-1 SAR data , 2018, Int. J. Appl. Earth Obs. Geoinformation.

[69]  Thomas J. Jackson,et al.  An Assessment of the Differences Between Spatial Resolution and Grid Size for the SMAP Enhanced Soil Moisture Product over Homogeneous Sites , 2018 .

[70]  Yann Kerr,et al.  The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle , 2010, Proceedings of the IEEE.

[71]  Wade T. Crow,et al.  Estimating Basin‐Scale Water Budgets With SMAP Soil Moisture Data , 2018, Water resources research.

[72]  Gabriel A. García,et al.  Evapotranspiration estimation using SMAP soil moisture products and bouchet complementary evapotranspiration over Southern Great Plains , 2019, Journal of Arid Environments.

[74]  George P. Petropoulos,et al.  Towards improved spatio-temporal resolution soil moisture retrievals from the synergy of SMOS and MSG SEVIRI spaceborne observations , 2016 .

[75]  B. Gao NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .

[76]  Christoph Rüdiger,et al.  DisPATCh as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and AMSR-E data in Southeastern Australia , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[77]  T. Carlson,et al.  A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover , 1994 .

[78]  Rajat Bindlish,et al.  Subpixel variability of remotely sensed soil moisture: an inter-comparison study of SAR and ESTAR , 2002, IEEE Trans. Geosci. Remote. Sens..

[79]  Adriaan A. Van de Griend,et al.  Comparison of soil moisture penetration depths for several bare soils at two microwave frequencies and implications for remote sensing , 1998 .