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Le radar révèle des montagnes cachées / Laurent Polidori in Géomètre, n° 2198 (janvier 2022)

Public [article]  inGéomètre > n° 2198 (janvier 2022) . - pp 17 - 17 Titre : Le radar révèle des montagnes cachées Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2022 Article en page(s) : pp 17 - 17 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] altimétrie satellitaire par radar [Termes IGN] Biomass [Termes IGN] longueur d'onde [Termes IGN] représentation du relief [Termes IGN] télédétection en hyperfréquence [Termes IGN] traitement d'image radar Résumé : (Auteur) Un radar embarqué sur satellite peut voir des reliefs cachés par l’eau, la forêt, le sable ou la glace. Numéro de notice : A2022-060 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/01/2022 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99401 [article]

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063-2022011	SL	Revue	Centre de documentation	Revues en salle	En circulation Exclu du prêt

Improving soil moisture retrieval from GNSS-interferometric reflectometry: parameters optimization and data fusion via neural network / Yajie Shi in International Journal of Remote Sensing IJRS, vol 42 n° 23 (1-10 December 2021)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 42 n° 23 (1-10 December 2021) Titre : Improving soil moisture retrieval from GNSS-interferometric reflectometry: parameters optimization and data fusion via neural network Type de document : Article/Communication Auteurs : Yajie Shi, Auteur ; Chao Ren, Auteur ; Zhiheng Yan, Auteur ; Jianmin Lai, Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] fusion de données [Termes IGN] humidité du sol [Termes IGN] optimisation (mathématiques) [Termes IGN] réflectométrie par GNSS [Termes IGN] réseau neuronal artificiel Résumé : (auteur) Soil moisture is a vital surface physical quantity in studying the earth’s ecology. It plays a crucial role in the hydrological cycle, crop yield estimation, and ecological monitoring. Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technology inversion to obtain high accuracy soil moisture is a hot topic of current research. However, due to the limited available sites, it’s difficult to obtain an extensive and continuous range of soil moisture based on this technique. It is necessary to build algorithms for encryption based on known sites’ data, combined with the corresponding geographic environmental elements. This paper extracted the surface environmental factors affecting soil moisture using high-precision optical remote sensing images. The contribution of each surface environmental element to the soil moisture inversion was analysed using back propagation (BP) neural network optimized by the genetic algorithm (GA). Based on this, ten surface environmental elements (latitude and longitude information, precipitation, temperature, land cover type, normalized difference vegetation index (NDVI), elevation, slope, slope direction, and shading) were identified as critical factors, and a multi-data fusion soil moisture inversion model was constructed. The results showed that the constructed model could better describe the relationship between soil moisture and these elements, and the Pearson correlation coefficient R reached 0.8724, and the RMSE was 0.0346 cm3 cm−3. GNSS-IR technology provides an effective technical means for inversing soil moisture over a large area with high spatial and temporal resolution. Numéro de notice : A2021-786 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01431161.2021.1988186 Date de publication en ligne : 24/10/2021 En ligne : https://doi.org/10.1080/01431161.2021.1988186 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98972 [article]

La modélisation des eaux / Michel Kasser in Géomètre, n° 2197 (décembre 2021)

Public [article]  inGéomètre > n° 2197 (décembre 2021) . - pp 41 - 41 Titre : La modélisation des eaux Type de document : Article/Communication Auteurs : Michel Kasser, Auteur Année de publication : 2021 Article en page(s) : pp 41 - 41 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] altimétrie par radar [Termes IGN] image SWOT [Termes IGN] océanographie dynamique [Termes IGN] océanographie spatiale [Termes IGN] précision centimétrique [Termes IGN] précision de localisation [Termes IGN] salinité [Termes IGN] surface de la mer [Termes IGN] vague [Termes IGN] variation temporelle Résumé : (Auteur) Grâce à l’altimétrie radar, il est possible de mesurer la hauteur de la surface des mers, avec des applications fortes pour la connaissance de la Terre. Numéro de notice : A2021-893 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99250 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
063-2021111	SL	Revue	Centre de documentation	Revues en salle	En circulation Exclu du prêt

A feature based change detection approach using multi-scale orientation for multi-temporal SAR images / R. Vijaya Geetha in European journal of remote sensing, vol 54 sup 2 (2021)  

Public [article]  inEuropean journal of remote sensing > vol 54 sup 2 (2021) . - pp 248 - 264 Titre : A feature based change detection approach using multi-scale orientation for multi-temporal SAR images Type de document : Article/Communication Auteurs : R. Vijaya Geetha, Auteur ; S. Kalaivani, Auteur Année de publication : 2021 Article en page(s) : pp 248 - 264 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse de groupement [Termes IGN] anisotropie [Termes IGN] chatoiement [Termes IGN] classification non dirigée [Termes IGN] classification par nuées dynamiques [Termes IGN] détection de changement [Termes IGN] filtre de Gabor [Termes IGN] image multitemporelle [Termes IGN] image radar moirée [Termes IGN] matrice de confusion [Termes IGN] transformation en ondelettes Résumé : (auteur) Excellent operation regardless of weather conditions and superior resolution independent of sensor light are the most attractive and desired features of synthetic aperture radar (SAR) imagery. This paper proposes an exclusive multi-scale with multiple orientation approach for multi-temporal SAR images. This approach integrates pre-processing and change detection. Pre-processing is performed on the SAR imagery through speckle reducing anisotropic diffusion and discrete wavelet transform. The processed speckle-free images are designed by Log-Gabor filter bank in terms of multi-scale with multiple orientations. The maximum magnitude of multiple orientations is concatenated to obtain feature-based scale representation. Each scale is dealt with multiple orientations and is compared by band-wise subtraction to retrieve difference image (DI) coefficient. The series of the difference coefficients from each scale are add-on together to estimate a DI. Thus, the resultant image of multi-scale orientation gives perception of detailed information with specific contour. Constrained k-means clustering algorithm is preferred to achieve change and un-change map. Performance of the proposed approach is validated on three real SAR image datasets. The effective change detection is examined by using confusion matrix parameters. Experimental results are described to show the efficacy of the proposed approach. Numéro de notice : A2021-819 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.1759457 Date de publication en ligne : 12/06/2020 En ligne : https://doi.org/10.1080/22797254.2020.1759457 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98924 [article]

Persistent scatterer interferometry for Pettimudi (India) landslide monitoring using Sentinel-1A images / Hari Shankar in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 11 (November 2021) . - pp 853 - 862 Titre : Persistent scatterer interferometry for Pettimudi (India) landslide monitoring using Sentinel-1A images Type de document : Article/Communication Auteurs : Hari Shankar, Auteur ; Arijit Roy, Auteur ; Prakash Chauhan, Auteur Année de publication : 2021 Article en page(s) : pp 853 - 862 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] déformation de la croute terrestre [Termes IGN] effondrement de terrain [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] Inde [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] précipitation [Termes IGN] risque naturel [Termes IGN] série temporelle [Termes IGN] surveillance géologique Résumé : (Auteur) The continuous monitoring of land surface movement over time is of paramount importance for assessing landslide triggering factors and mitigating landslide hazards. This research focuses on measuring horizontal and vertical surface displacement due to a devastating landslide event in the west-facing slope of the Rajamala Hills, induced by intense rainfall. The landslide occurred in Pettimudi, a tea-plantation village of the Idukki district in Kerala, India, on August 6–7, 2020. The persistent-scatterer synthetic aperture radar interferometry (PSInSAR ) technique, along with the Stanford Method for Persistent Scatterers (StaMPS), was applied to investigate the land surface movement over time. A stack of 20 Sentinel-1A single-look complex images (19 interferograms) acquired in descending passes was used for PSInSAR processing. The line-of-sight (LOS ) displacement in long time series, and hence the average LOS velocity, was measured at each measurement-point location. The mean LOS velocity was decomposed into horizontal east–west (EW ) and vertical up–down velocity components. The results show that the mean LOS, EW, and up–down velocities in the study area, respectively, range from –18.76 to +11.88, –10.95 to +6.93, and –15.05 to +9.53 mm/y, and the LOS displacement ranges from –19.60 to +19.59 mm. The displacement values clearly indicate the instability of the terrain. The time-series LOS displacement trends derived from the applied PSInSAR technique are very useful for providing valuable inputs for disaster management and the development of disaster early-warning systems for the benefit of local residents. Numéro de notice : A2021-897 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00020R3 Date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.14358/PERS.21-00020R3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99275 [article]

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Multi-objective CNN-based algorithm for SAR despeckling / Sergio Vitale in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)  

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A parameterization of the cloud scattering polarization signal derived from GPM observations for microwave fast radative transfer models / Victoria Sol Galligani in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)  

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Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations / Caglar Bayik in Natural Hazards, vol 109 n°1 (October 2021)  

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Automatic detection of inland water bodies along altimetry tracks for estimating surface water storage variations in the Congo basin / Frédéric Frappart in Remote sensing, vol 13 n° 19 (October-1 2021)  

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Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation / Peng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)  

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GPRInvNet: Deep learning-based ground-penetrating radar data inversion for tunnel linings / Bin Liu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)  

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Seawater Debye model function at L-band and its impact on salinity retrieval from Aquarius satellite data / Yiwen Zhou in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)  

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Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model / Yanan Du in International journal of applied Earth observation and geoinformation, vol 102 (October 2021)  

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Coniferous and broad-leaved forest distinguishing using L-band polarimetric SAR data / Fang Shang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

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Sentinel-1 sensitivity to soil moisture at high incidence angle and the impact on retrieval over seasonal crops / Davide Palmisano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

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