Centre dedocumentation
scientifique

ART-RISK 3.0, a fuzzy-based platform that combine GIS and expert assessments for conservation strategies in cultural heritage / M. Moreno in Journal of Cultural Heritage, vol 55 (May - June 2022)  

Public [article]  inJournal of Cultural Heritage > vol 55 (May - June 2022) . - pp 263 - 276 Titre : ART-RISK 3.0, a fuzzy-based platform that combine GIS and expert assessments for conservation strategies in cultural heritage Type de document : Article/Communication Auteurs : M. Moreno, Auteur ; R. Ortiz, Auteur ; D. Cagigas-Muñiz, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 263 - 276 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse des risques [Termes IGN] conservation du patrimoine [Termes IGN] église [Termes IGN] Espagne [Termes IGN] gelée [Termes IGN] Inférence floue [Termes IGN] inondation [Termes IGN] intelligence artificielle [Termes IGN] logique floue [Termes IGN] monument historique [Termes IGN] patrimoine culturel [Termes IGN] risque naturel [Termes IGN] séisme [Termes IGN] système d'information géographique [Termes IGN] température de l'air Résumé : (auteur) Heritage preservation poses numerous difficulties, especially in emergency situations or during budget cuts. In these contexts, having tools that facilitate efficient and rapid management of hazards-vulnerabilities is a priority for the preventive conservation and triage of cultural assets. This paper presents the first (to the authors' knowledge) free and public availability Artificial Intelligence platform designed for conservation strategies in cultural heritage. Art-Risk 3.0 is a platform designed as a fuzzy-logic inference system that combines information from geographical information system maps with expert assessments, in order to identify the contextual threat level and the degree of vulnerability that heritage buildings present. Thanks to the possibilities that the geographic information system offers, 12 Spanish churches (11th - 16th centuries) were analyzed. The artificial intelligence platform developed makes it possible to analyze the index of hazard, vulnerability and functionality, classify buildings according to the risk in order to do a sustainable use of budgets through the rational management of preventive conservation. The data stored in the system allows identify the danger due to geotechnics, precipitation, torrential downpour, thermal oscillation, frost, earthquake and flooding. Through the use of fuzzy logic, the tool interrelates environmental conditions with 14 other variables related to structural risks and the vulnerability of buildings, which are evaluated through bibliographic search and review of photographic images. The geographic information system has identified torrential rains and thermal oscillations as the environmental threats that mostly impact heritage buildings in Spain. The results obtained highlight the Church of Santiago de Jesús as the most vulnerable building due to a lack of preventive conservation programs. These results, consistent with the inclusion of this monument on the list of heritage at risk defined by Hispania Nostra, corroborate the functionality of the model. Numéro de notice : A2022-472 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.culher.2022.03.012 Date de publication en ligne : 14/04/2022 En ligne : https://doi.org/10.1016/j.culher.2022.03.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100818 [article]

A prediction model for surface deformation caused by underground mining based on spatio-temporal associations / Min Ren in Geomatics, Natural Hazards and Risk, vol 13 n° 1 (2022)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 13 n° 1 (2022) . - pp 94 - 122 Titre : A prediction model for surface deformation caused by underground mining based on spatio-temporal associations Type de document : Article/Communication Auteurs : Min Ren, Auteur ; Guanwen Cheng, Auteur ; Wancheng Zhu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 94 - 122 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse des risques [Termes IGN] analyse spatio-temporelle [Termes IGN] Chine [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] déformation de la croute terrestre [Termes IGN] déformation de surface [Termes IGN] mine de fer [Termes IGN] modèle de simulation [Termes IGN] règle d'association Mots-clés libres : spatio-temporal association rule mining (STARM) Résumé : (auteur) Accurate predictions of the surface deformation caused by underground mining are crucial for the safe development of underground resources. Although surface deformation has been predicted by artificial intelligence (AI) methods, most AI models are established based on the relationships between surface deformation and influential factors. The lack of consideration of the deformation state transition often leads to errors in the prediction results of catastrophic deformation by conventional AI methods. In this respect, this study introduces a surface deformation prediction model based on spatio-temporal association rule mining (STARM). Surface deformation is classified as excessive deformation zone (EDZ) and hysteretic deformation zone (HDZ), representing different surface deformation stage or state. The spatio-temporal association rules between the monitored EDZ and HDZ data are then mined. A surface deformation prediction model is established according to the spatio-temporal relationship between monitored EDZ and HDZ data. The proposed model is verified based on a practical case study of the Chengchao Iron Mine in China. The data collection of the influential factors is not requisite for the proposed model. It can achieve accurate prediction of the catastrophic deformation that was characterized by deformation state transition. Numéro de notice : A2022-035 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1080/19475705.2021.2015460 Date de publication en ligne : 21/12/2021 En ligne : https://doi.org/10.1080/19475705.2021.2015460 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99359 [article]

Incorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment / Ali Azareh in Geocarto international, vol 36 n° 20 ([01/12/2021])  

Public [article]  inGeocarto international > vol 36 n° 20 [01/12/2021] . - pp 2345 - 2365 Titre : Incorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment Type de document : Article/Communication Auteurs : Ali Azareh, Auteur ; Elham Rafiei Sardooi, Auteur ; Bahram Choubin, Auteur ; Saeed Barkhori, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2345 - 2365 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse des risques [Termes IGN] analyse multicritère [Termes IGN] bassin hydrographique [Termes IGN] cartographie des risques [Termes IGN] classification floue [Termes IGN] crue [Termes IGN] gestion des risques [Termes IGN] inondation [Termes IGN] Iran [Termes IGN] logique floue [Termes IGN] risque naturel [Termes IGN] zone à risque Résumé : (auteur) Floods are among the most frequently occurring natural disasters and the costliest in terms of human life and ecosystem disturbance. Identifying areas susceptible to flooding is important for developing appropriate watershed management policies. As such, the goal of the present study was to develop an integrated framework for flood susceptibility assessment in data-scarce regions, using data from the Haraz watershed in Iran. Flood-influencing indices best suited to the identification of areas particularly prone to flooding were selected. The decision-making trial and evaluation laboratory (DEMATEL) approach was used to investigate the interdependence among criteria and to develop a network structure representative of the problem. The relative importance of different flood-influencing factors was determined using the analytical network process (ANP). A flood susceptibility map was produced using weights obtained through the ANP and fuzzy-value function (FVF) and validated using 72 available flood locations where flooding occurred between 2006 and 2018. After validating the results, fuzzy theory served to better delineate the flood susceptibility scores among the region’s sub-watersheds. Incorporating the DEMATEL-ANP approach with FVF yielded an accuracy of 89.1%, as was assessed through the area under the curve (AUC) of a receiver operating characteristics (ROC) curve. The results indicated that the strongest flood-influencing (occurrence/nonoccurrence) factors were elevation, land use, soil texture, and frequency of heavy rainstorms. The fuzzy theory showed sub-watershed C1 to be highly susceptible to flooding, and thus, most in need of flood management. Numéro de notice : A2021-833 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1695958 Date de publication en ligne : 28/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1695958 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99006 [article]

Prioritization of forest fire hazard risk simulation using Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) coupled with multicriteria decision analysis (MCDA) techniques – a comparative study analysis / Michael Stanley Peprah in Geodesy and cartography, vol 47 n° 3 (October 2021)  

Public [article]  inGeodesy and cartography > vol 47 n° 3 (October 2021) . - pp 147 - 161 Titre : Prioritization of forest fire hazard risk simulation using Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) coupled with multicriteria decision analysis (MCDA) techniques – a comparative study analysis Type de document : Article/Communication Auteurs : Michael Stanley Peprah, Auteur ; Bernard Kumi-Boateng, Auteur ; Edwin Kojo Larbi, Auteur Année de publication : 2021 Article en page(s) : pp 147 - 161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse des risques [Termes IGN] analyse multicritère [Termes IGN] cartographie des risques [Termes IGN] forêt tropicale [Termes IGN] Ghana [Termes IGN] incendie de forêt [Termes IGN] modèle de simulation [Termes IGN] prévention des risques [Termes IGN] processus de hiérarchisation analytique floue [Termes IGN] rastérisation Résumé : (auteur) Forests are important dynamic systems which are widely attracted by wild fires worldwide. Due to the complexity and non-linearity of the causative forest fire problems, employing sophisticated hybrid evolutionary algorithms is a logical task to achieve a reliable approximation of this environmental threats. This estimate will provide the outline of priority areas for preventing activities and allocation of fire fighters’ stations, seeking to minimize possible damages caused by fires. This study aims at prioritizing the forest fire risk of Wassa West district of Ghana. The study considered static causative factors such as Land use and land cover (which include forest, built-ups and settlement areas), slope, aspect, linear features (water bodies and roads) and dynamic causative factors such as wind speed, precipitation, and temperature were used. The methods employed include a Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) techniques. The fuzzy sets integrated with AHP in a decision-making algorithm using geographic information system (GIS) was used to model the fire risk in the study area. FAHP and HGRA methods were used for estimating the importance (weights) of the effective factors in forest fire modelling. Based on their modelling methods, the expert ideas were used to express the relative importance and priority of the major criteria and sub-criteria in forest fire risk in the study area. The expert ideas were analyzed based on FAHP and HGRA. The major criteria models and fire risk model were presented based on these FAHP and HGRA weights. On the other hand, the spatial data of the sub criteria were provided and assembled in GIS environment to obtain the sub-criteria maps. Each sub-criterion map was converted to raster format and it was reclassified based on risks of its classes to fire occurrence. The maps of each major criterion were obtained by weighted overlay of its sub criteria maps considering to major criterion model in GIS environment. Finally, the map of fire risk was obtained by weighted overlay of major criteria maps considering to fire risk model in GIS. The results showed that the FAHP model showed superiority than HGRA in prioritizing forest fire risk of the study area in terms of statistical analysis with a standard deviation of 0.09277 m as compared to 0.1122 m respectively. The obtained fire risk map can be used as a decision support system for predicting of the future trends in the study area. The optimized structures of the proposed models could serve as a good alternative to traditional forest predictive models, and this can be a promisingly testament used for future planning and decision making in the proposed areas. Numéro de notice : A2021-863 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.3846/gac.2021.13028 Date de publication en ligne : 17/08/2021 En ligne : https://doi.org/10.3846/gac.2021.13028 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99079 [article]

Attribution of the Australian bushfire risk to anthropogenic climate change / Geert Jan Van Oldenborgh in Natural Hazards and Earth System Sciences, vol 21 n° 3 (March 2021)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 21 n° 3 (March 2021) . - pp 941 - 960 Titre : Attribution of the Australian bushfire risk to anthropogenic climate change Type de document : Article/Communication Auteurs : Geert Jan Van Oldenborgh, Auteur ; Folmer Krikken, Auteur ; Sophie Lewis, Auteur Année de publication : 2021 Article en page(s) : pp 941 - 960 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse des risques [Termes IGN] brousse [Termes IGN] changement climatique [Termes IGN] incendie [Termes IGN] modèle météorologique [Termes IGN] planification [Termes IGN] prévention des risques [Termes IGN] série temporelle [Termes IGN] température au sol [Termes IGN] utilisation du sol Résumé : (auteur) Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically based index of fire weather, the Fire Weather Index; long-term observations of heat and drought; and 11 large ensembles of state-of-the-art climate models. We find large trends in the Fire Weather Index in the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5) since 1979 and a smaller but significant increase by at least 30 % in the models. Therefore, we find that climate change has induced a higher weather-induced risk of such an extreme fire season. This trend is mainly driven by the increase of temperature extremes. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor of 2 due to the long-term warming trend. However, current climate models overestimate variability and tend to underestimate the long-term trend in these extremes, so the true change in the likelihood of extreme heat could be larger, suggesting that the attribution of the increased fire weather risk is a conservative estimate. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season, September–February. The observations, however, show a weak drying trend in the annual mean. For the 2019/20 season more than half of the July–December drought was driven by record excursions of the Indian Ocean Dipole and Southern Annular Mode, factors which are included in the analysis here. The study reveals the complexity of the 2019/20 bushfire event, with some but not all drivers showing an imprint of anthropogenic climate change. Finally, the study concludes with a qualitative review of various vulnerability and exposure factors that each play a role, along with the hazard in increasing or decreasing the overall impact of the bushfires. Numéro de notice : A2021-395 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-21-941-2021 Date de publication en ligne : 11/03/2021 En ligne : https://doi.org/10.5194/nhess-21-941-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97684 [article]

Geomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) / Marcello Buccolini in Journal of maps, vol 16 n° 3 ([01/12/2020])  

Permalink

Large-scale stochastic flood hazard analysis applied to the Po River / A. Curran in Natural Hazards, vol 104 n° 3 (December 2020)  

Permalink

Urban flooding in Britain: an approach to comparing ancient and contemporary flood exposure / T.E. O'Shea in Natural Hazards, Vol 104 n° 1 (October 2020)  

Permalink

Fusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)  

Permalink

Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images / Wen Dai in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)  

Permalink

A space-time varying graph for modelling places and events in a network / Ikechukwu Maduako in International journal of geographical information science IJGIS, vol 33 n° 10 (October 2019)  

Permalink

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])  

Permalink

Modélisation spatio-temporelle multi-niveau à base d'ontologies pour le suivi de la dynamique en imagerie satellitaire / Fethi Ghazouani (2018)  

Permalink

Développement de méthodes et d'outils pour l'amélioration de la résilience urbaine face au risque d'inondation / Serge Lhomme (2009)

Permalink

L’Internet des objets / Pierre-Jean Benghozi (2009)  

Permalink