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Our objective was to evaluate potential contributions of polarimetry to soil moisture estimation during crop growing cycles using RADARSAT-2 C-band images. The research focused on wheat field data collected during Soil Moisture Active Passive Validation Experiment (SMAPVEX12) conducted in 2012 in Manitoba (Canada). A sensitivity analysis was performed to select the most relevant non-polarimetric and polarimetric variables extracted from RADARSAT-2, and statistical models were developed to estimate soil moisture. In fine, three models were developed and validated: a non-polarimetric model based on cross-polarized backscattering coefficient \u03c3HV0; a polarimetric mixed model using six polarimetric and non-polarimetric retained variables after the sensitivity analysis; and a simplified polarimetric mixed model considering only the phase difference (\u03d5HH\u2212VV) and the co-polarized backscattering coefficient \u03c3HH0. The validation reveals significant positive contributions of polarimetry. It shows that the non-polarimetric model has a much larger error (RMSE = 0.098 m3\/m3) and explains only 19% of observed soil moisture variation compared to the polarimetric mixed model, which has an error of 0.087 m3\/m3, with an explained variance of 44%. The simplified model has the lowest error (0.074 m3\/m3) and explains 53.5% of soil moisture variation.<\/jats:p>","DOI":"10.3390\/rs15204925","type":"journal-article","created":{"date-parts":[[2023,10,12]],"date-time":"2023-10-12T03:14:32Z","timestamp":1697080472000},"page":"4925","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Retrieval of Surface Soil Moisture over Wheat Fields during Growing Season Using C-Band Polarimetric SAR Data"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6992-5093","authenticated-orcid":false,"given":"Kalifa","family":"Go\u00efta","sequence":"first","affiliation":[{"name":"Centre D\u2019Applications et de Recherches en T\u00e9l\u00e9d\u00e9tection (CARTEL), D\u00e9partement de G\u00e9omatique Appliqu\u00e9e, Universit\u00e9 de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada"}]},{"given":"Ramata","family":"Magagi","sequence":"additional","affiliation":[{"name":"Centre D\u2019Applications et de Recherches en T\u00e9l\u00e9d\u00e9tection (CARTEL), D\u00e9partement de G\u00e9omatique Appliqu\u00e9e, Universit\u00e9 de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9404-0276","authenticated-orcid":false,"given":"Vincent","family":"Beauregard","sequence":"additional","affiliation":[{"name":"Centre D\u2019Applications et de Recherches en T\u00e9l\u00e9d\u00e9tection (CARTEL), D\u00e9partement de G\u00e9omatique Appliqu\u00e9e, Universit\u00e9 de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada"}]},{"given":"Hongquan","family":"Wang","sequence":"additional","affiliation":[{"name":"Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada (AAFC), Lethbridge, AB T1J 4B1, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/0022-1694(95)02965-6","article-title":"Mutual interaction of soil moisture state and atmospheric processes","volume":"184","author":"Entekhabi","year":"1996","journal-title":"J. Hydrol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1038\/nature09396","article-title":"Recent decline in the global land evapotranspiration trend due to limited moisture supply","volume":"467","author":"Jung","year":"2010","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"112162","DOI":"10.1016\/j.rse.2020.112162","article-title":"A roadmap for high-resolution satellite soil moisture applications\u2014Confronting product characteristics with user requirements","volume":"252","author":"Peng","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_4","first-page":"51","article-title":"Varying applicability of four different satellite-derived soil moisture products to global gridded crop model evaluation","volume":"48","author":"Sakai","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13717-017-0112-6","article-title":"Characterizing drought in California: New drought indices and scenario-testing in support of resource management","volume":"7","author":"Flint","year":"2018","journal-title":"Ecol. Process."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3411","DOI":"10.1038\/s41598-023-30484-4","article-title":"Interconnected hydrologic extreme drivers and impacts depicted by remote sensing data assimilation","volume":"13","author":"Lahmers","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2784","DOI":"10.1109\/TGRS.2014.2364913","article-title":"The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12): Prelaunch calibration and validation of the SMAP soil moisture algorithms","volume":"53","author":"McNairn","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.rse.2016.02.064","article-title":"Satellite soil moisture for agricultural drought monitoring: Assessment of the SMOS derived Soil Water Deficit Index","volume":"177","author":"Gumuzzio","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"6979","DOI":"10.1080\/01431161.2022.2152755","article-title":"Soil moisture estimates over sporadically flooded farmlands: Synergies and biases of remote sensing and in situ sources","volume":"43","author":"Cappelletti","year":"2022","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"6329","DOI":"10.5194\/hess-21-6329-2017","article-title":"Comparing soil moisture anomalies from multiple independent sources over different regions across the globe","volume":"21","author":"Cammalleri","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.1109\/TGRS.2012.2184548","article-title":"The SMOS Soil Moisture Retrieval Algorithm","volume":"50","author":"Kerr","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","first-page":"125","article-title":"Global SMOS Soil Moisture Retrievals from The Land Parameter Retrieval Model","volume":"45","author":"Kerr","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.advwatres.2017.09.006","article-title":"Four decades of microwave satellite soil moisture observations: Part 1. A review of retrieval algorithms","volume":"109","author":"Karthikeyan","year":"2017","journal-title":"Adv. Water Resour."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.rse.2017.03.010","article-title":"Evaluating soil moisture retrievals from ESA\u2019s SMOS and NASA\u2019s SMAP brightness temperature datasets","volume":"193","author":"Wigneron","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_15","unstructured":"O\u2019Neill, P.E., Chan, S., Njoku, E.G., Jackson, T., Bindlish, R., and Chaubell, J. (2019). SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, NASA National Snow and Ice Data Center Distributed Active Archive Center."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Portal, G., Jagdhuber, T., Vall-llossera, M., Camps, A., Pablos, M., Entekhabi, D., and Piles, M. (2020). Assessment of Multi-Scale SMOS and SMAP Soil Moisture Products across the Iberian Peninsula. Remote Sens., 12.","DOI":"10.3390\/rs12030570"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"111215","DOI":"10.1016\/j.rse.2019.111215","article-title":"Satellite surface soil moisture from SMAP, SMOS, AMSR2 and ESA CCI: A comprehensive assessment using global ground-based observations","volume":"231","author":"Ma","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Llamas, R.M., Guevara, M., Rorabaugh, D., Taufer, M., and Vargas, R. (2020). Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture Based on Geostatistical Techniques and Multiple Regression. Remote Sens., 12.","DOI":"10.3390\/rs12040665"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Liu, Y., and Yang, Y. (2022). Advances in the Quality of Global Soil Moisture Products: A Review. Remote Sens., 14.","DOI":"10.3390\/rs14153741"},{"key":"ref_20","unstructured":"Boerner, W., Mott, H., Lueneburg, E., Livingstone, C., Brisco, B., Brown, R.J., and Paterson, J.S. (1998). Polarimetry in Radar Remote Sensing: Basic and Applied Concepts, John Wiley & Sons."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1109\/TGRS.1981.350328","article-title":"Microwave Backscatter Dependence on Surface Roughness, Soil Moisture, and Soil Texture: Part III-Soil Tension","volume":"GE-19","author":"Dobson","year":"1981","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","unstructured":"Dobson, M.C., and Ulaby, F.T. (1998). Mapping Soil Moisture Distribution with Imaging Radar, John Wiley & Sons."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1029\/RS013i002p00357","article-title":"Vegetation modeled as a water cloud","volume":"13","author":"Attema","year":"1978","journal-title":"Radio Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1109\/TGRS.2003.821065","article-title":"Quantitative retrieval of soil moisture content and surface roughness from multipolarized Radar observations of bare soil surfaces","volume":"42","author":"Oh","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.rse.2010.07.011","article-title":"Soil moisture retrieval over agricultural fields from multi-polarized and multi-angular RADARSAT-2 SAR data","volume":"115","author":"Gherboudj","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Xing, M., Chen, L., Wang, J., Shang, J., and Huang, X. (2022). Soil Moisture Retrieval Using SAR Backscattering Ratio Method during the Crop Growing Season. Remote Sens., 14.","DOI":"10.3390\/rs14133210"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"113059","DOI":"10.1016\/j.rse.2022.113059","article-title":"A deep neural network based SMAP soil moisture product","volume":"277","author":"Gao","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Batchu, V., Nearing, G., and Gulshan, V. (2023). A Deep Learning Data Fusion Model using Sentinel-1\/2, SoilGrids, SMAP-USDA, and GLDAS for Soil Moisture Retrieval. J. Hydrometeorol.","DOI":"10.1175\/JHM-D-22-0118.1"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"113137","DOI":"10.1016\/j.rse.2022.113137","article-title":"An advanced change detection method for time-series soil moisture retrieval from Sentinel-1","volume":"279","author":"Zhu","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1109\/36.7709","article-title":"Radar polarimetry: Analysis tools and applications","volume":"26","author":"Evans","year":"1988","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"69","DOI":"10.5589\/m11-023","article-title":"The sensitivity of RADARSAT-2 polarimetric SAR data to corn and soybean leaf area index","volume":"37","author":"Jiao","year":"2011","journal-title":"Can. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1109\/36.485127","article-title":"A review of target decomposition theorems in radar polarimetry","volume":"34","author":"Cloude","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1109\/36.673687","article-title":"A three-component scattering model for polarimetric SAR data","volume":"36","author":"Freeman","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2383","DOI":"10.1109\/TGRS.2019.2948683","article-title":"An Incoherent Decomposition Algorithm Based on Polarimetric Symmetry for Multilook Polarimetric SAR Data","volume":"58","author":"An","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Chen, Y., Zhang, L., Zou, B., and Gu, G. (2023). Polarimetric SAR Decomposition Method Based on Modified Rotational Dihedral Model. Remote Sens., 15.","DOI":"10.3390\/rs15010101"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.rse.2017.07.008","article-title":"Comparison of different polarimetric decompositions for soil moisture retrieval over vegetation covered agricultural area","volume":"199","author":"Wang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_37","first-page":"103114","article-title":"Multi-resolution soil moisture retrievals by disaggregating SMAP brightness temperatures with RADARSAT-2 polarimetric decompositions","volume":"115","author":"Wang","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"112485","DOI":"10.1016\/j.rse.2021.112485","article-title":"Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques","volume":"261","author":"Shi","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_39","unstructured":"Natural Resources Canada (2013). Transition Guide NTDB to CanVec."},{"key":"ref_40","unstructured":"Natural Resources Canada (2016). Canadian Digital Elevation Model Product Specifications."},{"key":"ref_41","unstructured":"Lee, J.S., and Pottier, E. (2009). Polarimetric Radar Imaging from Basics to Applications, CRC Press."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3039","DOI":"10.1109\/TGRS.2008.922033","article-title":"Evaluation and Bias Removal of Multilook Effect on Entropy\/Alpha\/Anisotropy in Polarimetric SAR Decomposition","volume":"46","author":"Lee","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2081","DOI":"10.1109\/TGRS.2013.2257802","article-title":"Perturbation Analysis of Eigenvector-Based Target Decomposition Theorems in Radar Polarimetry","volume":"52","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2049","DOI":"10.1109\/TGRS.2011.2170693","article-title":"Radarsat-2 DSM Generation With New Hybrid, Deterministic, and Empirical Geometric Modeling Without GCP","volume":"50","author":"Toutin","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1551","DOI":"10.1109\/TGRS.2003.813531","article-title":"Multitemporal C-band radar measurements on wheat fields","volume":"41","author":"Mattia","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1109\/TGRS.2011.2166080","article-title":"A RADARSAT-2 quad-polarized time series for monitoring crop and soil conditions in Barrax, Spain","volume":"50","author":"Moran","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","first-page":"50","article-title":"Using multi-polarization C- and L-band synthetic aperture radar to estimate biomass and soil moisture of wheat fields","volume":"58","author":"Hosseini","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1109\/TGRS.2003.810702","article-title":"Inversion of surface parameters from polarimetric SAR","volume":"41","author":"Hajnsek","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Jagdhuber, T. (2016). An Approach to Extended Fresnel Scattering for Modeling of Depolarizing Soil-Trunk Double-Bounce Scattering. Remote Sens., 8.","DOI":"10.3390\/rs8100818"},{"key":"ref_50","unstructured":"Ulaby, F.T., Moore, R.K., and Fung, A.K. (1986). Microwave Remote Sensing: Active and Passive, Volume III\u2014Volume Scattering and Emission Theory, Advanced Systems and Applications, Artech House."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1016\/S0034-4257(01)00312-1","article-title":"The effect of soil and crop residue characteristics on polarimetric radar response","volume":"80","author":"McNairn","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2343","DOI":"10.3390\/rs6032343","article-title":"Agricultural Monitoring in Northeastern Ontario, Canada, Using Multi-Temporal Polarimetric RADARSAT-2 Data","volume":"6","author":"Cable","year":"2014","journal-title":"Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2413","DOI":"10.1109\/36.789639","article-title":"Multitemporal C- and L-band polarimetric signatures of crops","volume":"37","author":"Skriver","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1080\/15481603.2020.1857123","article-title":"Microwave-based vegetation descriptors in the parameterization of water cloud model at L-band for soil moisture retrieval over croplands","volume":"58","author":"Wang","year":"2021","journal-title":"GIScience Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"4445","DOI":"10.1109\/TGRS.2016.2542214","article-title":"Soil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data","volume":"54","author":"He","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Zhao, J., Zhang, C., Min, L., Guo, Z., and Li, N. (2022). Retrieval of Farmland Surface Soil Moisture Based on Feature Optimization and Machine Learning. Remote Sens., 14.","DOI":"10.3390\/rs14205102"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Dong, L., Wang, W., Jin, R., Xu, F., and Zhang, Y. (2023). Surface Soil Moisture Retrieval on Qinghai-Tibetan Plateau Using Sentinel-1 Synthetic Aperture Radar Data and Machine Learning Algorithms. Remote Sens., 15.","DOI":"10.3390\/rs15010153"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"155066","DOI":"10.1016\/j.scitotenv.2022.155066","article-title":"A low-cost approach for soil moisture prediction using multi-sensor data and machine learning algorithm","volume":"833","author":"Nguyen","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2251","DOI":"10.1038\/s41598-023-28939-9","article-title":"Deep learning and data fusion to estimate surface soil moisture from multi-sensor satellite images","volume":"13","author":"Singh","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Wang, H., Magagi, R., Goita, K., Jagdhuber, T., and Hajnsek, I. (2016). Evaluation of simplified polarimetric decomposition for soil moisture retrieval over vegetated agricultural fields. 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