{"type": "FeatureCollection", "features": [{"id": "10.1016/j.rse.2020.112050", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:16:47Z", "type": "Journal Article", "created": "2020-08-24", "title": "Monitoring of wheat crops using the backscattering coefficient and the interferometric coherence derived from Sentinel-1 in semi-arid areas. Remote Sensing of Environment, 251, 112050.", "description": "Abstract   Radar data at C-band has shown great potential for the monitoring of soil and canopy hydric conditions of wheat crops. In this study, the C-band Sentinel-1 time series including the backscattering coefficients \u03c30 at VV and VH polarization, the polarization ratio (PR) and the interferometric coherence \u03c1 are first analyzed with the support of experimental data gathered on three plots of irrigated winter wheat located in the Haouz plain in the center of Morocco covering five growing seasons. The results showed that \u03c1 and PR are tightly related to the canopy development. \u03c1 is also sensitive to soil preparation. By contrast, \u03c30 was found to be widely linked to changes in surface soil moisture (SSM) during the first growth stages when Leaf Area Index remains moderate (", "keywords": ["[SDE] Environmental Sciences", "2. Zero hunger", "Interferometric coherence", "0211 other engineering and technologies", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "Surface soil moisture", "630", "Backscattering coefficient", "Winter wheat", "[SDE]Environmental Sciences", "Sentinel-1", "0401 agriculture", " forestry", " and fisheries", "Semi-arid region", "C-band"]}, "links": [{"href": "https://doi.org/10.1016/j.rse.2020.112050"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing%20of%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.rse.2020.112050", "name": "item", "description": "10.1016/j.rse.2020.112050", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.rse.2020.112050"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-01T00:00:00Z"}}, {"id": "10.1109/igarss.2019.8899164", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:18:39Z", "type": "Journal Article", "created": "2019-11-25", "title": "Sensitivity of Sentinel-1 Interferometric Coherence to Crop Structure and Soil Moisture", "description": "This paper investigates the sensitivity of Sentinel-1 (S-1) interferometric coherence to crop structure and near surface soil moisture (SSM) content. The study analyzes a data set collected in 2017 over the Apulian Tavoliere agricultural site (Southern Italy). The data set includes: i) in situ data over more than 600 agricultural fields monitored during the 2017 winter and spring growing seasons; ii) time-series of S-1 IW VV & VH backscatter & interferometric coherence; iii) time series of S-1 SSM maps. The temporal behavior of S-1 coherence and VH backscatter has been assessed over the monitored agricultural fields. Initial results indicate a stronger sensitivity of S-1 coherence than VH backscatter to crop geometric structure. In addition, an analysis at site scale, conducted before and after an important rain event, indicates a change of SSM from 0.18 to 0.30 m3/m3 along with a change of S-1 coherence from 0.61 to 0.53.", "keywords": ["2. Zero hunger", "crop segmentation", "crop segmentation; interferometric coherence; Sentinel-1; soil moisture", "0211 other engineering and technologies", "0202 electrical engineering", " electronic engineering", " information engineering", "Sentinel-1", "interferometric coherence", "02 engineering and technology", "soil moisture", "15. Life on land"]}, "links": [{"href": "http://xplorestaging.ieee.org/ielx7/8891871/8897702/08899164.pdf?arnumber=8899164"}, {"href": "https://doi.org/10.1109/igarss.2019.8899164"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/IGARSS%202019%20-%202019%20IEEE%20International%20Geoscience%20and%20Remote%20Sensing%20Symposium", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1109/igarss.2019.8899164", "name": "item", "description": "10.1109/igarss.2019.8899164", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1109/igarss.2019.8899164"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-07-01T00:00:00Z"}}, {"id": "10.1109/jstars.2019.2958847", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-29T16:18:40Z", "type": "Journal Article", "created": "2020-01-22", "title": "Sentinel-1 InSAR Coherence for Land Cover Mapping: A Comparison of Multiple Feature-Based Classifiers", "description": "Open AccessThis article investigates and demonstrates the suitability of the Sentinel-1 interferometric coherence for land cover and vegetation mapping. In addition, this study analyzes the performance of this feature along with polarization and intensity products according to different classification strategies and algorithms. Seven different classification workflows were evaluated, covering pixel- and object-based analyses, unsupervised and supervised classification, different machine-learning classifiers, and the various effects of distinct input features in the SAR domain\u2014interferometric coherence, backscattered intensities, and polarization. All classifications followed the Corine land cover nomenclature. Three different study areas in Europe were selected during 2015 and 2016 campaigns to maximize diversity of land cover. Overall accuracies (OA), ranging from 70% to 90%, were achieved depending on the study area and methodology, considering between 9 and 15 classes. The best results were achieved in the rather flat area of Do\u00f1ana wetlands National Park in Spain (OA 90%), but even the challenging alpine terrain around the city of Merano in northern Italy (OA 77%) obtained promising results. The overall potential of Sentinel-1 interferometric coherence for land cover mapping was evaluated as very good. In all cases, coherence-based results provided higher accuracies than intensity-based strategies, considering 12 days of temporal sampling of the Sentinel-1 A stack. Both coherence and intensity prove to be complementary observables, increasing the overall accuracies in a combined strategy. The accuracy is expected to increase when Sentinel-1 A/B stacks, i.e., six-day sampling, are considered.", "keywords": ["Teledetecci\u00f3", "550", "Interferometric coherence", "Geophysics. 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