{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T04:16:33Z","timestamp":1780719393017,"version":"3.54.1"},"reference-count":36,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,21]],"date-time":"2019-07-21T00:00:00Z","timestamp":1563667200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The main purpose of this study is to investigate the performance of two radar backscattering models; the calibrated integral equation model (CIEM) and the modified Dubois model (MDB) over an agricultural area in Karaj, Iran. In the first part, the performance of the models is evaluated based on the field measurement and the mentioned backscattering models, CIEM and MDB performed with root mean square error (RMSE) of 0.78 dB and 1.45 dB, respectively. In the second step, based on the neural networks (NNS), soil surface moisture is estimated using the two backscattering models, based on neural networks (NNs), from single polarization Sentinel-1 images over bare soils. The inversion results show the efficiency of the single polarized data for retrieving soil surface moisture, especially for VV polarization.<\/jats:p>","DOI":"10.3390\/s19143209","type":"journal-article","created":{"date-parts":[[2019,7,22]],"date-time":"2019-07-22T02:55:37Z","timestamp":1563764137000},"page":"3209","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":77,"title":["Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8078-1633","authenticated-orcid":false,"given":"Hamid Reza","family":"Mirsoleimani","sequence":"first","affiliation":[{"name":"Faculty of Geodesy and Geomatics Engineering &amp; Remote Sensing Institute, K. N. Toosi University of Technology, Tehran 19667-15433, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7742-3974","authenticated-orcid":false,"given":"Mahmod Reza","family":"Sahebi","sequence":"additional","affiliation":[{"name":"Faculty of Geodesy and Geomatics Engineering &amp; Remote Sensing Institute, K. N. Toosi University of Technology, Tehran 19667-15433, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9461-4120","authenticated-orcid":false,"given":"Nicolas","family":"Baghdadi","sequence":"additional","affiliation":[{"name":"IRSTEA, UMR TETIS, University of Montpellier, 500 rue Fran\u00e7ois Breton, 34093 Montpellier cedex 5, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2860-5581","authenticated-orcid":false,"given":"Mohammad","family":"El Hajj","sequence":"additional","affiliation":[{"name":"IRSTEA, UMR TETIS, University of Montpellier, 500 rue Fran\u00e7ois Breton, 34093 Montpellier cedex 5, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.catena.2005.05.007","article-title":"The application of remote-sensing data to monitoring and modelling of soil erosion","volume":"62","author":"King","year":"2005","journal-title":"Catena"},{"key":"ref_2","unstructured":"Lecomte, V., King, C., Cerdan, O., Baghdadi, N., and Bourguignon, A. 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