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Mapping territorial vulnerability to wildfires: A participative multi-criteria analysis / Miguel Rivière in Forest ecology and management, vol 539 (July-1 2023)
[article]
Titre : Mapping territorial vulnerability to wildfires: A participative multi-criteria analysis Type de document : Article/Communication Auteurs : Miguel Rivière, Auteur ; Jonathan Lenglet, Auteur ; Adrien Noirault, Auteur ; et al., Auteur Année de publication : 2023 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse multicritère
[Termes IGN] cartographie des risques
[Termes IGN] incendie de forêt
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] Rhône-Méditerranée-Corse
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du sol
[Termes IGN] vulnérabilitéNuméro de notice : A2023-216 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1016/j.foreco.2023.121014 Date de publication en ligne : 22/04/2023 En ligne : https://doi.org/10.1016/j.foreco.2023.121014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103146
in Forest ecology and management > vol 539 (July-1 2023)[article]Automating the external placement of symbols for point features in situation maps for emergency response / Sven Gedicke in Cartography and Geographic Information Science, Vol 50 n° 4 (June 2023)
[article]
Titre : Automating the external placement of symbols for point features in situation maps for emergency response Type de document : Article/Communication Auteurs : Sven Gedicke, Auteur ; Lukas Arzoumanidis, Auteur ; Jan‐Henrik Haunert, Auteur Année de publication : 2023 Article en page(s) : pp 385 - 402 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme du recuit simulé
[Termes IGN] cartographie d'urgence
[Termes IGN] optimisation (mathématiques)
[Termes IGN] placement automatique des signes conventionnels
[Termes IGN] programmation linéaireRésumé : (auteur) In this article, we address the time-critical work of emergency services in the field of disaster and emergency response. Aiming at saving valuable human and time resources during emergency operations, we present one exact and one heuristic approach for the automatic placement of tactical symbols in situation maps. Such maps are used to establish situational awareness and to convey mission-relevant information to emergency personnel. Usually, the information is communicated through the visualization of descriptive symbols which are predominantly placed in a manual process. We automate this process based on an established map layout used by emergency services in Germany that distributes the symbols to the map boundaries. Following general principles and observations from existing literature, we formalize the symbol placement as an optimization problem. We take into account the relevance of tactical symbols as well as short and crossing-free leaders and allow the grouped representation of symbols of similar semantics and spatially close map locations. In experiments with real-world data, we determine a balance between the optimization criteria and show that our heuristic generates high-quality results in less than a second. In an assessment by an expert, we get confirmation that our maps are suitable for use in emergency scenarios. Numéro de notice : A2023-234 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2023.2213446 Date de publication en ligne : 20/06/2023 En ligne : https://doi.org/10.1080/15230406.2023.2213446 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103592
in Cartography and Geographic Information Science > Vol 50 n° 4 (June 2023) . - pp 385 - 402[article]A spatial distribution: Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil / Jiawei Liu in Science of the total environment, vol 859 n° 1 (February 2023)
[article]
Titre : A spatial distribution: Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil Type de document : Article/Communication Auteurs : Jiawei Liu, Auteur ; Hou Kang, Auteur ; Wendong Tao, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 160112 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse en composantes principales
[Termes IGN] autocorrélation spatiale
[Termes IGN] cartographie des risques
[Termes IGN] Chine
[Termes IGN] distribution spatiale
[Termes IGN] métal lourd
[Termes IGN] pollution des sols
[Termes IGN] risque de pollution
[Termes IGN] traçabilitéRésumé : (auteur) With the rapid development of urbanization, heavy metal pollution of soil has received great attention. Over-enrichment of heavy metals in soil may endanger human health. Assessing soil pollution and identifying potential sources of heavy metals are crucial for prevention and control of soil heavy metal pollution. This study introduced a spatial distribution - principal component analysis (SD-PCA) model that couples the spatial attributes of soil pollution with linear data transformation by the eigenvector-based principal component analysis. By evaluating soil pollution in the spatial dimension it identifies the potential sources of heavy metals more easily. In this study, soil contamination by eight heavy metals was investigated in the Lintong District, a typical multi-source urban area in Northwest China. In general, the soils in the study area were lightly contaminated by Cr and Pb. Pearson correlation analysis showed that Cr was negatively correlated with other heavy metals, whereas the spatial autocorrelation analysis revealed that there was strong association in the spatial distribution of eight heavy metals. The aggregation forms were more varied and the correlation between Cr contamination and other heavy metals was lower. The aggregation forms of Mn and Cu, Zn and Pb, on the other hand, were remarkably comparable. Agriculture was the largest pollution source, contributing 65.5 % to soil pollution, which was caused by the superposition of multiple heavy metals. Additionally, traffic and natural pollution sources contributed 17.9 % and 11.1 %, respectively. The ability of this model to track pollution of heavy metals has important practical significance for the assessment and control of multi-source soil pollution. Numéro de notice : A2023-009 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scitotenv.2022.160112 Date de publication en ligne : 11/11/2022 En ligne : https://doi.org/10.1016/j.scitotenv.2022.160112 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102115
in Science of the total environment > vol 859 n° 1 (February 2023) . - n° 160112[article]A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level / Laxmi Gupta in Journal of maps, vol 18 n° 2 (February 2023)
[article]
Titre : A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level Type de document : Article/Communication Auteurs : Laxmi Gupta, Auteur ; Jagabandhu Dixit, Auteur Année de publication : 2023 Article en page(s) : 33 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse multicritère
[Termes IGN] cartographie des risques
[Termes IGN] eau de surface
[Termes IGN] Inde
[Termes IGN] inondation
[Termes IGN] planification
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] ruissellement
[Termes IGN] système d'information géographique
[Termes IGN] vulnérabilitéRésumé : (auteur) Floods are frequently occurring events in the Assam region due to the presence of the Brahmaputra River and the heavy monsoon period. An efficient and reliable methodology is utilized to prepare a GIS-based flood risk map for the Assam region, India. At the regional and administrative level, the flood hazard index (FHI), flood vulnerability index (FVI), and flood risk index (FRI) are developed using multi-criteria decision analysis (MCDA) – analytical hierarchy process (AHP). The selected indicators define the topographical, geological, meteorological, drainage characteristics, land use land cover, and demographical features of Assam. The results show that more than 70%, 57.37%, and 50% of the total area lie in moderate to very high FHI, FVI, and FRI classes, respectively. The proposed methodology can be applied to identify high flood risk zones and to carry out effective flood risk management and mitigation strategies in vulnerable areas. Numéro de notice : A2023-054 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2060329 Date de publication en ligne : 19/04/2022 En ligne : https://doi.org/10.1080/10106049.2022.2060329 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102387
in Journal of maps > vol 18 n° 2 (February 2023) . - 33 p.[article]Simplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area / David Marín-García in Sustainable Cities and Society, vol 88 (January 2023)
[article]
Titre : Simplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area Type de document : Article/Communication Auteurs : David Marín-García, Auteur ; Juan Rubio-Gómez-Torga, Auteur ; Manuel Duarte-Pinheiro, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104251 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] acquisition de données
[Termes IGN] Andalousie
[Termes IGN] apprentissage automatique
[Termes IGN] bassin hydrographique
[Termes IGN] bâtiment
[Termes IGN] cartographie des risques
[Termes IGN] coefficient de corrélation
[Termes IGN] dommage matériel
[Termes IGN] évaluation des paramètres
[Termes IGN] image à haute résolution
[Termes IGN] modèle de simulation
[Termes IGN] zone inondableRésumé : (auteur) Flooding due to overflowing rivers affects the construction elements of many buildings. Although significant progress has been made in predicting this damage, there is still a need to continue studying this issue. For this reason, the main goal of this research focuses on finding out if, based on a small dataset of cases of a given area, it is possible to predict at least three degrees of affectation in buildings, considering only three environmental factors (minimum distance from the river, unevenness and possible water communication). To meet this goal, the methodological approach followed considers scientific literature review and collection and analysis of a small dataset from 101 buildings that have been affected by floods in the Guadalquivir River basin (Andalusia. Spain). After analyzing this data, algorithms based on machine learning (ML) are applied to predict the degree of affection. The results, analysis and conclusions indicate that, if the study focuses on a specific area and similar buildings, using a correlation matrix and ML algorithms such as the "Decision Tree" with cross-validation, around 90% can be achieved in the "Recall" and "Precision" of "High-Level-Affection" class, and an “Accuracy” around 80% in general. Numéro de notice : A2023-006 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2022.104251 Date de publication en ligne : 15/10/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104251 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102093
in Sustainable Cities and Society > vol 88 (January 2023) . - n° 104251[article]Establishing a GIS-based evaluation method considering spatial heterogeneity for debris flow susceptibility mapping at the regional scale / Shengwu Qin in Natural Hazards, vol 114 n° 3 (December 2022)PermalinkHybrid XGboost model with various Bayesian hyperparameter optimization algorithms for flood hazard susceptibility modeling / Saeid Janizadeh in Geocarto international, vol 37 n° 25 ([01/12/2022])PermalinkGraph neural networks with constraints of environmental consistency for landslide susceptibility evaluation / Haowei Zeng in International journal of geographical information science IJGIS, vol 36 n° 11 (November 2022)PermalinkMachine learning and landslide studies: recent advances and applications / Faraz S. Tehrani in Natural Hazards, vol 114 n° 2 (November 2022)PermalinkFlash-flood hazard susceptibility mapping in Kangsabati River Basin, India / Rabin Chakrabortty in Geocarto international, vol 37 n° 23 ([15/10/2022])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])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)PermalinkDetection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM / Jiehua Cai in Engineering Geology, vol 305 (August 2022)PermalinkA comparison of three multi-criteria decision-making models in mapping flood hazard areas of Northeast Penang, Malaysia / Rofiat Bunmi Mudashiru in Natural Hazards, vol 112 n° 3 (July 2022)PermalinkLandslide susceptibility assessment considering spatial agglomeration and dispersion characteristics: A case study of Bijie City in Guizhou Province, China / Kezhen Yao in ISPRS International journal of geo-information, vol 11 n° 5 (May 2022)PermalinkDetermination of building flood risk maps from LiDAR mobile mapping data / Yu Feng in Computers, Environment and Urban Systems, vol 93 (April 2022)PermalinkFlood mapping using multi-temporal Sentinel-1 SAR images: A case study—Inaouene watershed from Northeast of Morocco / Brahim Benzougagh in Iranian Journal of Science and Technology - Transactions of Civil Engineering, vol 46 n° 2 (April 2022)PermalinkA user-centric optimization of emergency map symbols to facilitate common operational picture / Tomasz Opach in Cartography and Geographic Information Science, vol 49 n° 2 (March 2022)PermalinkMulti-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkMapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery / Donato Morresi in Remote sensing of environment, vol 269 (February 2022)PermalinkAssessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India / Rajib Mitra in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkPermalinkCIME: Context-aware geolocation of emergency-related posts / Gabriele Scalia in Geoinformatica, vol 26 n° 1 (January 2022)PermalinkCombining a class-weighted algorithm and machine learning models in landslide susceptibility mapping: A case study of Wanzhou section of the Three Gorges Reservoir, China / Huijuan Zhang in Computers & geosciences, vol 158 (January 2022)PermalinkForest fire susceptibility assessment using Google Earth engine in Gangwon-do, Republic of Korea / Yong Piao in Geomatics, Natural Hazards and Risk, vol 13 (2022)Permalink