A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy
Effective soil salinity monitoring is crucial for sustainable land management in arid regions. Most current studies face limitations by relying solely on single-source data. This study presents a novel three-dimensional (3D) optical-radar feature space model combining Gaofen-3 polarimetric synthetic...
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2025-06-01
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| Series: | Agronomy |
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| author | Ilyas Nurmemet Yilizhati Aili Yang Xiang Aihepa Aihaiti Yu Qin Bilali Aizezi |
| author_facet | Ilyas Nurmemet Yilizhati Aili Yang Xiang Aihepa Aihaiti Yu Qin Bilali Aizezi |
| author_sort | Ilyas Nurmemet |
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| description | Effective soil salinity monitoring is crucial for sustainable land management in arid regions. Most current studies face limitations by relying solely on single-source data. This study presents a novel three-dimensional (3D) optical-radar feature space model combining Gaofen-3 polarimetric synthetic aperture radar (SAR) and Sentinel-2 multispectral data for China’s Yutian Oasis. The random forest (RF) feature selection algorithm identified three optimal parameters: Huynen_vol (volume scattering component), RVI_Freeman (radar vegetation index), and NDSI (normalized difference salinity index). Based on the interactions of these three optimal features within the 3D feature space, we constructed the Optical-Radar Salinity Inversion Model (ORSIM). Subsequent validation using measured soil electrical conductivity (EC) data (May–June 2023) demonstrated strong model performance, with ORSIM achieving R<sup>2</sup> = 0.75 and RMSE = 7.57 dS/m. Spatial analysis revealed distinct salinity distribution patterns: (1) Mildly salinized areas clustered in the central oasis region, and (2) severely salinized zones predominated in northern low-lying margins. This spatial heterogeneity strongly correlated with local topography-higher elevation (south) to desert depression (north) gradient. The 3D feature space approach advances soil salinity monitoring by overcoming traditional 2D limitations while providing an accurate, transferable framework for arid ecosystem management. Furthermore, this study significantly expands the application potential of SAR data in soil salinization research. |
| format | Article |
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| institution | DOAJ |
| issn | 2073-4395 |
| language | English |
| publishDate | 2025-06-01 |
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| series | Agronomy |
| spelling | doaj-art-85cea2d756ea4218804f6668f82465162025-08-20T02:45:49ZengMDPI AGAgronomy2073-43952025-06-01157159010.3390/agronomy15071590A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data SynergyIlyas Nurmemet0Yilizhati Aili1Yang Xiang2Aihepa Aihaiti3Yu Qin4Bilali Aizezi5College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, ChinaCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, ChinaEffective soil salinity monitoring is crucial for sustainable land management in arid regions. Most current studies face limitations by relying solely on single-source data. This study presents a novel three-dimensional (3D) optical-radar feature space model combining Gaofen-3 polarimetric synthetic aperture radar (SAR) and Sentinel-2 multispectral data for China’s Yutian Oasis. The random forest (RF) feature selection algorithm identified three optimal parameters: Huynen_vol (volume scattering component), RVI_Freeman (radar vegetation index), and NDSI (normalized difference salinity index). Based on the interactions of these three optimal features within the 3D feature space, we constructed the Optical-Radar Salinity Inversion Model (ORSIM). Subsequent validation using measured soil electrical conductivity (EC) data (May–June 2023) demonstrated strong model performance, with ORSIM achieving R<sup>2</sup> = 0.75 and RMSE = 7.57 dS/m. Spatial analysis revealed distinct salinity distribution patterns: (1) Mildly salinized areas clustered in the central oasis region, and (2) severely salinized zones predominated in northern low-lying margins. This spatial heterogeneity strongly correlated with local topography-higher elevation (south) to desert depression (north) gradient. The 3D feature space approach advances soil salinity monitoring by overcoming traditional 2D limitations while providing an accurate, transferable framework for arid ecosystem management. Furthermore, this study significantly expands the application potential of SAR data in soil salinization research.https://www.mdpi.com/2073-4395/15/7/1590soil salinityfeature spaceGaofen-3Sentinel-2polarization decomposition |
| spellingShingle | Ilyas Nurmemet Yilizhati Aili Yang Xiang Aihepa Aihaiti Yu Qin Bilali Aizezi A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy Agronomy soil salinity feature space Gaofen-3 Sentinel-2 polarization decomposition |
| title | A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy |
| title_full | A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy |
| title_fullStr | A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy |
| title_full_unstemmed | A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy |
| title_short | A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy |
| title_sort | three dimensional feature space model for soil salinity inversion in arid oases polarimetric sar and multispectral data synergy |
| topic | soil salinity feature space Gaofen-3 Sentinel-2 polarization decomposition |
| url | https://www.mdpi.com/2073-4395/15/7/1590 |
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