Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/14/3209 |
| _version_ | 1811307021409976320 |
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| author | Hamid Reza Mirsoleimani Mahmod Reza Sahebi Nicolas Baghdadi Mohammad El Hajj |
| author_facet | Hamid Reza Mirsoleimani Mahmod Reza Sahebi Nicolas Baghdadi Mohammad El Hajj |
| author_sort | Hamid Reza Mirsoleimani |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T08:57:09Z |
| format | Article |
| id | doaj.art-ed09695118174413903f7f67a5875e1a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T08:57:09Z |
| publishDate | 2019-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-ed09695118174413903f7f67a5875e1a2022-12-22T02:53:16ZengMDPI AGSensors1424-82202019-07-011914320910.3390/s19143209s19143209Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural NetworksHamid Reza Mirsoleimani0Mahmod Reza Sahebi1Nicolas Baghdadi2Mohammad El Hajj3Faculty of Geodesy and Geomatics Engineering & Remote Sensing Institute, K. N. Toosi University of Technology, Tehran 19667-15433, IranFaculty of Geodesy and Geomatics Engineering & Remote Sensing Institute, K. N. Toosi University of Technology, Tehran 19667-15433, IranIRSTEA, UMR TETIS, University of Montpellier, 500 rue François Breton, 34093 Montpellier cedex 5, FranceIRSTEA, UMR TETIS, University of Montpellier, 500 rue François Breton, 34093 Montpellier cedex 5, FranceThe 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.https://www.mdpi.com/1424-8220/19/14/3209bare soilssoil moistureneural networksSentinel-1calibrated IEMModified Dubois ModelIran |
| spellingShingle | Hamid Reza Mirsoleimani Mahmod Reza Sahebi Nicolas Baghdadi Mohammad El Hajj Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks Sensors bare soils soil moisture neural networks Sentinel-1 calibrated IEM Modified Dubois Model Iran |
| title | Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks |
| title_full | Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks |
| title_fullStr | Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks |
| title_full_unstemmed | Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks |
| title_short | Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks |
| title_sort | bare soil surface moisture retrieval from sentinel 1 sar data based on the calibrated iem and dubois models using neural networks |
| topic | bare soils soil moisture neural networks Sentinel-1 calibrated IEM Modified Dubois Model Iran |
| url | https://www.mdpi.com/1424-8220/19/14/3209 |
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