Centre dedocumentation
scientifique

Landslide susceptibility prediction based on image semantic segmentation / Bowen Du in Computers & geosciences, vol 155 (October 2021)  

Public [article]  inComputers & geosciences > vol 155 (October 2021) . - n° 104860 Titre : Landslide susceptibility prediction based on image semantic segmentation Type de document : Article/Communication Auteurs : Bowen Du, Auteur ; Zirong Zhao, Auteur ; Xiao Hu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] aléa [Termes IGN] apprentissage automatique [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] effondrement de terrain [Termes IGN] image captée par drone [Termes IGN] modèle de simulation [Termes IGN] prévention des risques [Termes IGN] segmentation sémantique Résumé : (auteur) Numéro de notice : A2021-683 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104860 date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104860 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98408 [article]

GIS models for vulnerability of coastal erosion assessment in a tropical protected area / Luís Russo Vieira in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 9 (September 2021) . - n° 598 Titre : GIS models for vulnerability of coastal erosion assessment in a tropical protected area Type de document : Article/Communication Auteurs : Luís Russo Vieira, Auteur ; José Guilherme Vieira, Auteur ; Isabel Marques da silva, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] Brésil [Termes IGN] érosion côtière [Termes IGN] géoréférencement [Termes IGN] mangrove [Termes IGN] modèle de simulation [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité [Termes IGN] zone intertropicale Résumé : (auteur) Coastal erosion is considered a major worldwide challenge. The vulnerability assessment of coastal areas, in relation to climate change, is a key topic of worldwide increasing interest. The integration of methodologies supported by Remote Sensing, Geographical Information Systems (GIS) and in situ monitoring has allowed a viable identification of vulnerable areas to erosion. In the present study, a model was proposed to the assessment of the estuarine system of Cananéia-Iguape (Brazil), by applying the evaluation and prediction of vulnerability models for the conservation and preservation of mangroves. Approximately 1221 Km2 were classified, with 16% of the total presenting high and very high vulnerability to erosion. Other relevant aspects, were the identification and georeferencing sites that showed strong evidence of erosion and, thus, having a huge influence on the final vulnerability scores. The obtained results led to the development of a multidisciplinary approach through the application of a prediction and description model that resulted from the adaptation of the study system from a set of implemented models for coastal regions, in order to contribute to the erosion vulnerability assessment in the mangroves ecosystems (and associated localities, municipalities and communities). Numéro de notice : A2021-685 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10090598 date de publication en ligne : 10/09/2021 En ligne : https://doi.org/10.3390/ijgi10090598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98411 [article]

Remote sensing method for extracting topographic information on tidal flats using spatial distribution features / Yang Lijun in Marine geodesy, vol 44 n° 5 (September 2021)  

Public [article]  inMarine geodesy > vol 44 n° 5 (September 2021) . - pp 408 - 431 Titre : Remote sensing method for extracting topographic information on tidal flats using spatial distribution features Type de document : Article/Communication Auteurs : Yang Lijun, Auteur ; Xiao Yao, Auteur ; Jie Jiang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 408 - 431 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] alluvion [Termes IGN] arpentage [Termes IGN] Chine [Termes IGN] distribution spatiale [Termes IGN] données topographiques [Termes IGN] extraction de données [Termes IGN] Fleuve bleu (Chine) [Termes IGN] géomorphologie locale [Termes IGN] image Landsat [Termes IGN] marée océanique [Termes IGN] modèle numérique de surface [Termes IGN] positionnement cinématique en temps réel [Termes IGN] Shanghai (Chine) [Termes IGN] vase Résumé : (Auteur) A remote sensing method combining remote sensing and ground surveying is proposed to extract tidal flat topographic information via the spatial distribution characteristics of tidal flat surface features. Based on the eastern Chongming beach of the Yangtze Estuary and Landsat-5 satellite images, this study identifies the spatial distribution characteristics of tidal flat features using field-based RTK data and spectral data. The remote sensing method for extracting the geometric and physical characteristics of linear and surface geographical elements on tidal flats and the elevation assignment method are discussed. The effectiveness of this method is verified by the quality of the resultant tidal flat DEM. The results show that the use of spatial distribution features in remote sensing images can provide rich topographic information. The DEM results have an accuracy of 0.16 m, are in line with the basic topographic patterns of tidal flats, and can describe local microscale geomorphic features. This technique solves the problem of a single topographic information source in current remote sensing measurement methods and provides technical support for detecting dynamic changes in coastal zones by using remote sensing technology. Numéro de notice : A2021-577 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2021.1925791 date de publication en ligne : 04/06/2021 En ligne : https://doi.org/10.1080/01490419.2021.1925791 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98230 [article]

Shore zone classification from ICESat-2 data over Saint Lawrence Island / Huan Xie in Marine geodesy, vol 44 n° 5 (September 2021)  

Public [article]  inMarine geodesy > vol 44 n° 5 (September 2021) . - pp 454 - 466 Titre : Shore zone classification from ICESat-2 data over Saint Lawrence Island Type de document : Article/Communication Auteurs : Huan Xie, Auteur ; Yuan Sun, Auteur ; Xiaoshuai Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 454 - 466 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Alaska (Etats-Unis) [Termes IGN] Bering, mer de [Termes IGN] données ICEsat [Termes IGN] Google Earth [Termes IGN] indicateur environnemental [Termes IGN] littoral [Termes IGN] modèle de régression [Termes IGN] photon [Termes IGN] sédiment Résumé : (Auteur) The shore zone is the most active zone in the atmosphere, hydrosphere, biosphere and lithosphere of nature, and has the environmental characteristics of both ocean and land. The ICESat-2 satellite provides height measurements of shore zone using a photon-counting LiDAR. The purpose of this study is to explore the application potential of ICESat-2 satellite data in shore zone classification. Saint Lawrence Island, Alaska, was chosen as the study area. Firstly, in this study, the upper and lower boundaries of the shore zone of the study area were extracted based on Google Earth images. The slope and width between the two boundaries were then calculated according to the formula. Secondly, six statistical indicators (standard deviation, relative standard deviation, average absolute deviation, relative average deviation, absolute median error and quartile deviation) related to the substrate and sediment classification that could reflect the characteristics of the shore zone profile were extracted, and the statistical indicators were used as input parameters of the softmax regression model for classification. Finally, the accuracy of the shore zone classification was validated using the ShoreZone classification system. The results show that, among the 246 shore zone sections in the study area, 86% (212) has been correctly classified. The results therefore indicate that ICESat-2 data can be used to support the characterization of shore zone morphology. Numéro de notice : A2021-578 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2021.1898498 date de publication en ligne : 29/03/2021 En ligne : https://doi.org/10.1080/01490419.2021.1898498 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98234 [article]

Estimation of surface deformation due to Pasni earthquake using RADAR interferometry / Muhammad Ali in Geocarto international, vol 36 n° 14 ([01/08/2021])  

Public [article]  inGeocarto international > vol 36 n° 14 [01/08/2021] . - pp 1630 - 1645 Titre : Estimation of surface deformation due to Pasni earthquake using RADAR interferometry Type de document : Article/Communication Auteurs : Muhammad Ali, Auteur ; Muhammad Shahzad, Auteur ; Majir Nazeer, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1630 - 1645 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] déformation de surface [Termes IGN] déformation verticale de la croute terrestre [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] Pakistan [Termes IGN] polarisation [Termes IGN] rapport signal sur bruit [Termes IGN] séisme [Termes IGN] série temporelle Résumé : (auteur) This study analyzed the land deformation associated with Mw 6.3 earthquake along Pasni coast, Pakistan. Post-earthquake widespread surface displacements were found using Sentinel-1 data. Pre, Co and Post-seismic images were used to investigate the deformation trends. Before the earthquake, 89.65% of Pasni land mass showed uplifting from 0.0 to 3.0 cm at 1.00 mm/day while 3.0 cm subsidence was noted in 86.36% of the land mass after the earthquake at 2.5 mm/day. However, two weeks after the earthquake, 72.9% Pasni land mass showed uplifting at an unprecedented rate of 3.3 mm/day. The maximum deformation along the Line Of Sight (LOS) direction in co-seismic time was about -4.0 cm. Azimuthal interferogram showed more complex displacement pattern with both negative and positive displacements between ±5.0 cm. Pasni is already facing many problems due to increased sea water intrusion under prevailing climatic changes and land deformation due to strong earthquakes. Numéro de notice : A2021-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1661031 date de publication en ligne : 09/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1661031 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98110 [article]

A hybrid data model for dynamic GIS: application to marine geomorphological dynamics / Younes Hamdani in International journal of geographical information science IJGIS, vol 35 n° 8 (August 2021)  

Permalink

An integrated methodology for surface soil moisture estimating using remote sensing data approach / Rida Khellouk in Geocarto international, vol 36 n° 13 ([15/07/2021])  

Permalink

Anomalous variations of air temperature prior to earthquakes / Irfan Mahmood in Geocarto international, vol 36 n° 12 ([01/07/2021])  

Permalink

DEM- and GIS-based analysis of soil erosion depth using machine learning / Kieu Anh Nguyen in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)  

Permalink

Mapping sandy land using the new sand differential emissivity index from thermal infrared emissivity data / Shanshan Chen in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)  

Permalink

Groundwater vulnerability assessment of the chalk aquifer in the northern part of France / Lahcen Zouhri in Geocarto international, vol 36 n° 11 ([15/06/2021])  

Permalink

Imaging the subsurface: How different visualizations of cross-sections affect the sense of uncertainty / Ane Bang-Kittilsen in Journal of Geovisualization and Spatial Analysis, vol 5 n° 1 (June 2021)  

Permalink

Prevention of erosion in mountain basins: A spatial-based tool to support payments for forest ecosystem services / Sandro Sacchelli in Journal of forest science, vol 67 n° 6 (July 2021)  

Permalink

Analysing the impact of climate change on hydrological ecosystem services in Laguna del Sauce (Uruguay) using the SWAT model and remote sensing data / Celina Aznarez in Remote sensing, vol 13 n°10 (May 2021)  

Permalink

Increasing efficiency of the robust deformation analysis methods using genetic algorithm and generalised particle swarm optimisation / Mehmed Batilović in Survey review, Vol 53 n° 378 (May 2021)  

Permalink