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A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping / Zhice Fang in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 321 - 347 Titre : A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping Type de document : Article/Communication Auteurs : Zhice Fang, Auteur ; Yi Wang, Auteur ; Ling Peng, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 321 - 347 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] Chine [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] pondération [Termes descripteurs IGN] régression logistique [Termes descripteurs IGN] réseau neuronal récurrent [Termes descripteurs IGN] risque naturel Résumé : (auteur) This study introduces four heterogeneous ensemble-learning techniques, that is, stacking, blending, simple averaging, and weighted averaging, to predict landslide susceptibility in Yanshan County, China. These techniques combine several state-of-the-art classifiers of convolutional neural network, recurrent neural network, support vector machine, and logistic regression in specific ways to produce reliable results and avoid problems with the model selection. The study consists of three main steps. The first step establishes a spatial database consisting of 16 landslide conditioning factors and 380 historical landslide locations. The second step randomly selects training (70% of the total) and test (30%) datasets out of grid cells corresponding to landslide and non-slide locations in the study area. The final step constructs the proposed heterogeneous ensemble-learning methods for landslide susceptibility mapping. The proposed ensemble-learning methods show higher prediction accuracy than the individual classifiers mentioned above based on statistical measures. The blending ensemble-learning method achieves the highest overall accuracy of 80.70% compared to the other ensemble-learning methods. Numéro de notice : A2021-028 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1808897 date de publication en ligne : 15/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1808897 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96704 [article]

Analysis of shoreline changes in Vishakhapatnam coastal tract of Andhra Pradesh, India: an application of digital shoreline analysis system (DSAS) / Mirza Razi Imam Baig in Annals of GIS, vol 26 n° 4 (December 2020)  

Public [article]  inAnnals of GIS > vol 26 n° 4 (December 2020) . - pp 361 - 376 Titre : Analysis of shoreline changes in Vishakhapatnam coastal tract of Andhra Pradesh, India: an application of digital shoreline analysis system (DSAS) Type de document : Article/Communication Auteurs : Mirza Razi Imam Baig, Auteur ; Ishita Afreen Ahmad, Auteur ; Mohammad Tayyab, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 361 - 376 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Andhra Pradesh (Inde ; état) [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] érosion côtière [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] pondération [Termes descripteurs IGN] régression linéaire [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] surveillance du littoral [Termes descripteurs IGN] trait de côte Résumé : (auteur) Coastline or Shoreline calculation is one of the important factors in the finding of coastal accretion and erosion and the study of coastal morphodynamic. Coastal erosion is a tentative hazard for communities especially in coastal areas as it is extremely susceptible to increasing coastal disasters. The study has been conducted along the coast of Vishakhapatnam district, Andhra Pradesh, India with the help of multi-temporal satellite images of 1991 2001, 2011 and 2018. The continuing coastal erosion and accretion rates have been calculated using the Digital Shoreline Analysis System (DSAS). Linear regression rate (LRR), End Point Rate (EPR) and Weighted Linear Regression (WLR) are used for calculating shoreline change rate. Based on calculations the district shoreline has been classified into five categories as high and low erosion, no change and high and low accretion. Out of 135 km, high erosion occupied 5.8 km of coast followed by moderate or low erosion 46.2 km. Almost 34.7 km coastal length showed little or no change. Moderate accretion is found along 30.5 km whereas high accretion trend found around 17.8 km. The outcome of shows that erosion is prevailing in Vishakhapatnam taluk, Ankapalli taluk, Yellamanchili taluk whereas most of the Bhemunipatnam coast is accreting. Natural and manmade activities and phenomena influence the coastal areas in terms of erosion and accretion. The study could be used for further planning and development and also for disaster management authority in the decision-making process in the study area. Numéro de notice : A2020-801 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1815839 date de publication en ligne : 09/10/2020 En ligne : https://doi.org/10.1080/19475683.2020.1815839 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96724 [article]

Characterizing the spatial and temporal variation of the land surface temperature hotspots in Wuhan from a local scale / Chen Yang in Geo-spatial Information Science, vol 23 n° 4 (December 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 4 (December 2020) . - pp 327 - 340 Titre : Characterizing the spatial and temporal variation of the land surface temperature hotspots in Wuhan from a local scale Type de document : Article/Communication Auteurs : Chen Yang, Auteur ; Qingming Zhan, Auteur ; Sihang Gao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 327 - 340 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] climat urbain [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] morphologie urbaine [Termes descripteurs IGN] processus gaussien [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] Wuhan (Chine) [Termes descripteurs IGN] zonage (urbanisme) Résumé : (auteur) Land Surface Temperature (LST) derived from space-borne Thermal-infrared (TIR) sensors is a key parameter of urban climate studies. Current studies are inefficient to capture the spatial and temporal variations of LST for only one snapshot adopted at one time. Focusing on the characterization of the spatial and temporal of LST variations at local scales, the latent patterns, and morphological characteristics are extracted in this study. Technically, sixteen MODerate-resolution Imaging Spectroradiometer (MODIS) eight-day synthesized LST products (MYD11A2) in 2002, 2007, 2012, and 2017 are employed. First, the non-parametric Multi-Task Gaussian Process Model (MTGP) is used to extract the smooth and continuous Latent LST (LLST) patterns using one LST subset and its temporally adjacent images. Second, the Multi-Scale Shape Index (MSSI) is then applied to quantify the morphological characteristics at the optimal scale. Then, the LLST patterns and MSSI maps are clustered into multiple spatial categories. The specific clusters with the highest LLST and MSSI values are considered as local LLST hotspots. The Hotspots Weighted Mean Center (HSWMC) and standard deviation ellipse are adopted to further investigate the spatiotemporal change of hotspots orientation, direction, and trajectories. Results revealed that Impervious Surfaces (IS) composition is the most significant external forcing of local LST anomalies. The configuration factors (e.g., shape index, aggregation index) also have a noticeable local warming effect. This study represents a latent pattern and morphology-based framework for LST hotspots spatial and temporal variations characterization, catering to the zoning and grading strategies in urban planning. Numéro de notice : A2020-788 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1834882 date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.1080/10095020.2020.1834882 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96550 [article]

Can we characterize river corridor evolution at a continental scale from historical topographic maps? A first assessment from the comparison of four countries / J. Horacio Garcia in River Research and Applications, vol 36 n° 6 (July 2020)  

Public [article]  inRiver Research and Applications > vol 36 n° 6 (July 2020) . - pp 934 - 946 Titre : Can we characterize river corridor evolution at a continental scale from historical topographic maps? A first assessment from the comparison of four countries Type de document : Article/Communication Auteurs : J. Horacio Garcia, Auteur ; Samuel Dunesme , Auteur ; Hervé Piegay, Auteur Année de publication : 2020 Projets : EUR H20'Lyon / Article en page(s) : pp 934 - 946 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] Belgique [Termes descripteurs IGN] carte ancienne [Termes descripteurs IGN] corridor biologique [Termes descripteurs IGN] dix-neuvième siècle [Termes descripteurs IGN] forêt ripicole [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] rivière [Termes descripteurs IGN] Suisse [Termes descripteurs IGN] vectorisation Résumé : (auteur) National historical map resources are assessed in four European countries to characterize river corridor features and associated channel changes, as well as identify issues limiting or promoting geomorphic assessment procedures at a continental scale. A geomorphic audit that launches potential data for diagnosis from reach to continental scales could offer a good resource for biology and ecology managers of river authorities or government agencies and engineers. The assessment compares the resources available by country in terms of period covered, spatial scale, history and chronology, and representation of the fluvial corridor features. We then applied the Historical Maps Vectorization Toolbox, initially developed for vectorizing river corridors from French maps, to detect and extract flow channels, unvegetated bars and riparian vegetation patches from historical topographical maps. We found that (a) it is difficult to apply an audit of channel changes to the whole continental scale because map legends differ between countries due to geographic and political specificity; (b) there exists an opportunity to get assessment information in all countries at reach or national scale where map resources are available; (c) the highest potential is observed in Switzerland and Belgium where there is high quality national map coverage from the 19th century; and (d) the algorithm Historical Maps Vectorization Toolbox applied to map resources works well with any of the countries, and its widespread application is encouraging. Numéro de notice : A2020-362 Affiliation des auteurs : ENSG+Ext (2012-2019) Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1002/rra.3582 date de publication en ligne : 30/12/2019 En ligne : https://doi.org/10.1002/rra.3582 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95333 [article]

Data-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India / Subrata Mondal in Geocarto international, Vol 35 n° 8 ([01/06/2020])  

Public [article]  inGeocarto international > Vol 35 n° 8 [01/06/2020] . - pp 818 - 856 Titre : Data-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India Type de document : Article/Communication Auteurs : Subrata Mondal, Auteur ; Sujit Mandal, Auteur Année de publication : 2020 Article en page(s) : pp 818 - 856 Note générale : bibbliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] action anthropique [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] lithologie [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] surveillance hydrologique [Termes descripteurs IGN] théorie de Dempster-Shafer [Termes descripteurs IGN] vulnérabilité Résumé : (auteur) In the present study, data-driven evidential belief function model (belief function) was employed to generate landslides susceptibility index map of Darjeeling Himalaya considering 15 landslide causative factors, which grouped into six categories, i.e. geomorphological factors (elevation, aspect, slope, curvature), lithological factors (geology, soil, lineament density, distance to lineament), hydrologic factors (drainage density, distance to drainage, stream power index, topographic wetted index), triggering factor (rainfall), protective factor (normalized differential vegetation index) and anthropogenic factor (land use and land cover). Total 2079 landslide locations were mapped and randomly divided it into training datasets (70% landslide locations) and validation datasets (30% landslide locations). The resultant susceptibility map was divided into five different susceptibility zones i.e. very low, low, moderate, high and very high which covered 5.60%, 25.65%, 34.47%, 24.67% and 9.61% area respectively of the Darjeeling Himalaya. Receiver operating characteristics curve suggested that 80.20% prediction accuracy of the prepared map whereas frequency ratio plot indicated towards the ideal landslides susceptibility index map. Numéro de notice : A2020-274 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10106049.2018.1544288 date de publication en ligne : 13/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1544288 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95059 [article]

Geomorphic Change Detection Using Cost-Effective Structure-from-Motion Photogrammetry: Evaluation of Direct Georeferencing from Consumer-Grade UAS at Orewa Beach (New Zealand) / Stéphane Bertin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 5 (May 2020)  

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Le sol s'affaisse, l'eau monte [Delta du Gange-Brahmapoutre-Meghna] / Marielle Mayo in Géomètre, n° 2179 (avril 2020)

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Quantification of airborne lidar accuracy in coastal dunes (Fire Island, New York) / William J. Schmelz in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 2 (February 2019)  

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Analyse de la déformation récente dans le Grand Tunis par interférométrie radar SAR / Anis Chaabani (2019)    

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Improving the reliability of landslide susceptibility mapping through spatial uncertainty analysis: a case study of Al Hoceima, Northern Morocco / Hassane Rahali in Geocarto international, vol 34 n° 1 ([01/01/2019])  

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Investigating the accuracy of a bathymetric refraction correction on Structure from Motion photogrammetric datasets / Aelaïg Cournez (2019) 

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Mise en évidence de l’activité récente des failles du bassin de Naryn (Kyrgyzstan) à partir de données photogrammétriques Pléiades et drone : un nouvel apport pour l’aléa sismique / Aurélie Médard (2018)

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Apport des plans directeurs et de l’outil LiDAR aéroporté pour la caractérisation des impacts morphologiques de la Grande Guerre : exemple de la cote 108 (Berry‑au‑Bac, France) / Pierre Taborelli in Géomorphologie, vol. 23 n° 2 ([01/06/2017])  

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Delineation of groundwater potential zones using remote sensing and GIS-based data-driven models / Samira Ghorbani Nejad in Geocarto international, vol 32 n° 2 (February 2017)  

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Détection de l'érosion dans un bassin versant agricole par comparaison d'images multidates acquises par drone / Jonathan Lisein in Revue Française de Photogrammétrie et de Télédétection, n° 213 - 214 (janvier - avril 2017)

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