Descripteur
Documents disponibles dans cette catégorie (2598)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Modelling evacuation preparation time prior to floods: A machine learning approach / R. Sreejith in Sustainable Cities and Society, vol 87 (December 2022)
[article]
Titre : Modelling evacuation preparation time prior to floods: A machine learning approach Type de document : Article/Communication Auteurs : R. Sreejith, Auteur ; K.R. Sinimole, Auteur Année de publication : 2022 Article en page(s) : n° 104257 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage automatique
[Termes IGN] chronométrie
[Termes IGN] données spatiotemporelles
[Termes IGN] gestion de crise
[Termes IGN] inondation
[Termes IGN] Kerala (Inde ; état)
[Termes IGN] modèle de simulation
[Termes IGN] plan de prévention des risques
[Termes IGN] questionnaire
[Termes IGN] risque naturel
[Termes IGN] secours d'urgenceRésumé : (auteur) Flooding is a significant hazard responsible for substantial damage and risks to human life worldwide. Effective emergency evacuation to a safer location remains a concern even though the crisis can be predicted and warnings were given. During a calamity, most residents cannot quickly and securely flee. As it is crucial to start evacuation at the right time to have a safe evacuation, this study focuses on a machine learning-based model for predicting a household's evacuation preparation time in the incident of a flood. The study is based on the data collected from flood-affected people from Kerala, India, through a questionnaire. The study indicates that people's demographic, geographical and behavioural aspects, awareness of natural hazards and management are the critical components for improved emergency actions. Further, the article also analysed the characteristics of the respondents and successfully created clusters in which the respondents broadly belong, which will help the rescue team operationalize the evacuation process. Numéro de notice : A2022-819 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2022.104257 Date de publication en ligne : 14/10/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104257 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101986
in Sustainable Cities and Society > vol 87 (December 2022) . - n° 104257[article]Progressive collapse of dual-line rivers based on river segmentation considering cartographic generalization rules / Fubing Zhang in ISPRS International journal of geo-information, vol 11 n° 12 (December 2022)
[article]
Titre : Progressive collapse of dual-line rivers based on river segmentation considering cartographic generalization rules Type de document : Article/Communication Auteurs : Fubing Zhang, Auteur ; Qun Sun, Auteur ; Jingzhen Ma, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 609 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] effondrement (généralisation)
[Termes IGN] représentation multiple
[Termes IGN] rivière
[Termes IGN] segmentation
[Termes IGN] triangulation de Delaunay
[Vedettes matières IGN] GénéralisationRésumé : (auteur) Collapse is a common cartographic generalization operation in multi-scale representation and cascade updating of vector spatial data. During transformation from large- to small-scale, the dual-line river shows progressive collapse from narrow river segment to line. The demand for vector spatial data with various scales is increasing; however, research on the progressive collapse of dual-line rivers is lacking. Therefore, we proposed a progressive collapse method based on vector spatial data. First, based on the skeleton graph of the dual-line river, the narrow and normal river segments are preliminarily segmented by calculating the width of the river. Second, combined with the rules of cartographic generalization, the collapse and exaggeration priority strategies are formulated to determine the handling mode of the river segment. Finally, based on the two strategies, progressive collapse of dual-line rivers is realized by collapse and exaggeration of the river segment. Experimental results demonstrated that the progressive collapse results of the proposed method were scale-driven, and the collapse part had no burr and topology problems, whereas the remaining part was clearly visible. The proposed method can be better applied to progressive collapse of the dual-line river through qualitative and quantitative evaluation with another progressive collapse method. Numéro de notice : A2022-901 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi11120609 Date de publication en ligne : 06/12/2022 En ligne : https://doi.org/10.3390/ijgi11120609 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102285
in ISPRS International journal of geo-information > vol 11 n° 12 (December 2022) . - n° 609[article]Updating and backdating analyses for mitigating uncertainties in land change modeling: a case study of the Ci Kapundung upper water catchment area, Java Island, Indonesia / Medria Shekar Rani in International journal of geographical information science IJGIS, vol 36 n° 12 (December 2022)
[article]
Titre : Updating and backdating analyses for mitigating uncertainties in land change modeling: a case study of the Ci Kapundung upper water catchment area, Java Island, Indonesia Type de document : Article/Communication Auteurs : Medria Shekar Rani, Auteur ; Ross Cameron, Auteur ; Olaf Schrott, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2549 - 2562 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] bassin hydrographique
[Termes IGN] carte thématique
[Termes IGN] changement d'occupation du sol
[Termes IGN] Java (île de)
[Termes IGN] mise à jour
[Termes IGN] modèle de Markov
[Termes IGN] modélisation spatiale
[Termes IGN] Perceptron multicoucheRésumé : (auteur) In developing countries, data gaps are common and lead to uncertainties in land cover change analysis. This study demonstrates how to mitigate uncertainties in modeling land change in the Ci Kapundung upper water catchment area by comparing the outcomes of two simulation phases. A conventional cellular automata (CA)–Markov model was complemented with a multilayer perceptron (MLP) to project future land cover maps in the study area. The CA–Markov–MLP model results in high uncertainties in forested sites where a data gap is apparent in the input data (land cover maps and driver variables) and parameters. The results show that the model accuracy is improved from 47.90% in the first phase to 81.36% in the second phase. Both first and second phases integrate six demographic–economic and environmental drivers in the modeling, but the second phase also incorporates an updating and backdating analysis to revise the base-maps. This study suggests that uncertainties can be mitigated by linking such base-map revision process with the updating and backdating analyses using remote sensing datasets retrieved at different times. Numéro de notice : A2022-845 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2103820 Date de publication en ligne : 28/07/2022 En ligne : https://doi.org/10.1080/13658816.2022.2103820 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102076
in International journal of geographical information science IJGIS > vol 36 n° 12 (December 2022) . - pp 2549 - 2562[article]Vertical deformation and residual altimeter systematic errors around continental Australia inferred from a Kalman-based approach / Mohammad-Hadi Rezvani in Journal of geodesy, vol 96 n° 12 (December 2022)
[article]
Titre : Vertical deformation and residual altimeter systematic errors around continental Australia inferred from a Kalman-based approach Type de document : Article/Communication Auteurs : Mohammad-Hadi Rezvani, Auteur ; Christopher S. Watson, Auteur ; Matt A. King, Auteur Année de publication : 2022 Article en page(s) : n° 96 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] altimètre
[Termes IGN] Australie occidentale (Australie)
[Termes IGN] déformation verticale de la croute terrestre
[Termes IGN] données altimétriques
[Termes IGN] données marégraphiques
[Termes IGN] erreur systématique
[Termes IGN] filtre de Kalman
[Termes IGN] montée du niveau de la mer
[Termes IGN] série temporelle
[Termes IGN] variabilitéRésumé : (auteur) We further developed a space–time Kalman approach to investigate time-fixed and time-variable signals in vertical land motion (VLM) and residual altimeter systematic errors around the Australian coast, through combining multi-mission absolute sea-level (ASL), relative sea-level from tide gauges (TGs) and Global Positioning System (GPS) height time series. Our results confirmed coastal subsidence in broad agreement with GPS velocities and unexplained by glacial isostatic adjustment alone. VLM determined at individual TGs differs from spatially interpolated GPS velocities by up to ~ 1.5 mm/year, yielding a ~ 40% reduction in RMSE of geographic ASL variability at TGs around Australia. Our mission-specific altimeter error estimates are small but significant (typically within ~ ± 0.5–1.0 mm/year), with negligible effect on the average ASL rate. Our circum-Australia ASL rate is higher than previous results, suggesting an acceleration in the ~ 27-year time series. Analysis of the time-variability of altimeter errors confirmed stability for most missions except for Jason-2 with an anomaly reaching ~ 2.8 mm/year in the first ~ 3.5 years of operation, supported by analysis from the Bass Strait altimeter validation facility. Data predominantly from the reference missions and located well off narrow shelf regions was shown to bias results by as much as ~ 0.5 mm/year and highlights that residual oceanographic signals remain a fundamental limitation. Incorporating non-reference-mission measurements well on the shelf helped to mitigate this effect. Comparing stacked nonlinear VLM estimates and altimeter systematic errors with the El Niño-Southern Oscillation shows weak correlation and suggests our approach improves the ability to explore nonlinear localized signals and is suitable for other regional- and global-scale studies. Numéro de notice : A2022-897 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01680-3 Date de publication en ligne : 05/12/2022 En ligne : https://doi.org/10.1007/s00190-022-01680-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102251
in Journal of geodesy > vol 96 n° 12 (December 2022) . - n° 96[article]Automatic vectorization of fluvial corridor features on historical maps to assess riverscape changes / Samuel Dunesme in Cartography and Geographic Information Science, vol 49 n° 6 (November 2022)
[article]
Titre : Automatic vectorization of fluvial corridor features on historical maps to assess riverscape changes Type de document : Article/Communication Auteurs : Samuel Dunesme , Auteur ; Hervé Piegay, Auteur ; Sébastien Mustière , Auteur Année de publication : 2022 Projets : EUR H20'Lyon / Article en page(s) : pp 512 - 527 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] automatisation
[Termes IGN] carte ancienne
[Termes IGN] couleur (rédaction cartographique)
[Termes IGN] cours d'eau
[Termes IGN] détection de changement
[Termes IGN] Institut national de l'information géographique et forestière (France)
[Termes IGN] réseau fluvial
[Termes IGN] réseau hydrographique
[Termes IGN] vectorisationRésumé : (auteur) The vectorization of historical maps is an important scientific issue for understanding the dynamics of change recorded by territories. Historical maps are potentially an excellent source of data for characterizing river changes at large scales. The use of vectorized data is essential for such characterization, as well as for highlighting changes in the planform alignment of such reaches over time. At a regional network scale of several thousand kilometers of river, such work requires the vectorization of several hundred or even thousands of maps. This work proposes an automated vectorization procedure for the hydrographic network detailed in the cartographic resources of the IGN (the French National Mapping Agency). The ultimate goal is to use these historical maps to track the planform evolution of the elementary landscape units (water, bare banks, and riparian vegetation) that constitute river corridors at the basin network scale. The Historical Maps Vectorization Toolbox was developed to automatically vectorize river corridor objects (sediment banks, water surfaces, and vegetation polygons) with a high level of accuracy. The toolbox works with a 2-step process: first it classifies the colors detected on the map, then it reconstructs the objects of the fluvial corridor. We also demonstrate a practical use of the toolbox through measuring changes in the surface area of river networks of several hundred kilometers. Numéro de notice : A2022-604 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2022.2091661 Date de publication en ligne : 26/07/2022 En ligne : https://doi.org/10.1080/15230406.2022.2091661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102073
in Cartography and Geographic Information Science > vol 49 n° 6 (November 2022) . - pp 512 - 527[article]Features predisposing forest to bark beetle outbreaks and their dynamics during drought / M. Müller in Forest ecology and management, vol 523 (November-1 2022)PermalinkIntegrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability / Benjamin T. Gutierrez in Earth and space science, vol 9 n° 11 (November 2022)PermalinkTidal level prediction using combined methods of harmonic analysis and deep neural networks in Southern coastline of Iran / Kourosh Shahryari Nia in Marine geodesy, vol 45 n° 6 (November 2022)PermalinkFlash-flood hazard susceptibility mapping in Kangsabati River Basin, India / Rabin Chakrabortty in Geocarto international, vol 37 n° 23 ([15/10/2022])PermalinkMonitoring spatiotemporal soil moisture changes in the subsurface of forest sites using electrical resistivity tomography (ERT) / Julian Fäth in Journal of Forestry Research, vol 33 n° 5 (October 2022)PermalinkSpatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding / Faxi Yuan in Computers, Environment and Urban Systems, vol 97 (October 2022)PermalinkA comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers / Qasim Khan in Geocarto international, vol 37 n° 20 ([20/09/2022])PermalinkDevelopment of a novel hybrid multi-boosting neural network model for spatial prediction of urban flood / Amid Darabi in Geocarto international, vol 37 n° 19 ([15/09/2022])PermalinkPrediction of suspended sediment concentration using hybrid SVM-WOA approaches / Sandeep Samantaray in Geocarto international, vol 37 n° 19 ([15/09/2022])PermalinkEffect of riparian soil moisture on bacterial, fungal and plant communities and microbial decomposition rates in boreal stream-side forests / M.J. Annala in Forest ecology and management, vol 519 (September-1 2022)PermalinkExploring multi-modal evacuation strategies for a landlocked population using large-scale agent-based simulations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 36 n° 9 (September 2022)PermalinkFlood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network approach / Quoc Bao Pham in Natural Hazards, vol 113 n° 2 (September 2022)PermalinkLarge-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt / André Bertoncini in Remote sensing of environment, vol 278 (September 2022)PermalinkTowards a global seasonal and permanent reference water product from Sentinel-1/2 data for improved flood mapping / Sandro Martinis in Remote sensing of environment, vol 278 (September 2022)PermalinkComparison of PBIA and GEOBIA classification methods in classifying turbidity in reservoirs / Douglas Stefanello Facco in Geocarto international, vol 37 n° 16 ([15/08/2022])PermalinkA pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery / Sajid Ghuffar in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)PermalinkUAV-borne, LiDAR-based elevation modelling: a method for improving local-scale urban flood risk assessment / Katerina Trepekli in Natural Hazards, vol 113 n° 1 (August 2022)PermalinkUse of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand / Kiatkulchai Jitt-Aer in Natural Hazards, vol 113 n° 1 (August 2022)PermalinkMultiscale assimilation of Sentinel and Landsat data for soil moisture and Leaf Area Index predictions using an ensemble-Kalman-filter-based assimilation approach in a heterogeneous ecosystem / Nicola Montaldo in Remote sensing, vol 14 n° 14 (July-2 2022)PermalinkCartographie : Le dispositif national de suivi des bocages / Sophie Morin Pinaud in Courrier de la nature, No special 2022 ([01/07/2022])Permalink