Q
Qi Gao
Researcher at Centre national de la recherche scientifique
Publications - 32
Citations - 716
Qi Gao is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Computer science & Geology. The author has an hindex of 7, co-authored 14 publications receiving 414 citations. Previous affiliations of Qi Gao include Spanish National Research Council & University of Toulouse.
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Journal ArticleDOI
Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution
TL;DR: Two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m, based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell.
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Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters.
Safa Bousbih,Safa Bousbih,Mehrez Zribi,Zohra Lili-Chabaane,Nicolas Baghdadi,Mohammad El Hajj,Qi Gao,Qi Gao,Bernard Mougenot +8 more
TL;DR: The results reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness, and shows that the radar signal strength decreases when the vegetation parameters increase.
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Retrieving surface soil moisture at high spatio-temporal resolution from a synergy between Sentinel-1 radar and Landsat thermal data: A study case over bare soil
Abdelhakim Amazirh,Olivier Merlin,Salah Er-Raki,Qi Gao,Vincent Rivalland,Yoann Malbeteau,Yoann Malbeteau,Said Khabba,Maria Jose Escorihuela +8 more
TL;DR: In this paper, an innovative synergistic method combining Sentinel-1 (S1) microwave and Landsat 7/8 (L7/8) thermal data was presented to help calibrate radar-based retrieval approaches to supervising surface soil moisture (SM) changes in various conditions.
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Irrigation Mapping Using Sentinel-1 Time Series at Field Scale
TL;DR: The methodology for irrigation mapping using SAR data is proposed, which makes it applicable to all areas, even with frequent cloud cover, but this method may be less robust when irrigation is less dominated to soil moisture change.
Journal ArticleDOI
Soil Moisture and Irrigation Mapping in A Semi-Arid Region, Based on the Synergetic Use of Sentinel-1 and Sentinel-2 Data
Safa Bousbih,Mehrez Zribi,Mohammad El Hajj,Nicolas Baghdadi,Zohra Lili-Chabaane,Qi Gao,Pascal Fanise +6 more
TL;DR: This paper presents a technique for the mapping of soil moisture and irrigation, at the scale of agricultural fields, based on the synergistic interpretation of multi-temporal optical and Synthetic Aperture Radar (SAR) data (Sentinel-2 and Sentinel-1).