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Determination of building flood risk maps from LiDAR mobile mapping data / Yu Feng in Computers, Environment and Urban Systems, vol 93 (April 2022)
[article]
Titre : Determination of building flood risk maps from LiDAR mobile mapping data Type de document : Article/Communication Auteurs : Yu Feng, Auteur ; Qing Xiao, Auteur ; Claus Brenner, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101759 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] bâtiment
[Termes IGN] cartographie d'urgence
[Termes IGN] cartographie des risques
[Termes IGN] classification semi-dirigée
[Termes IGN] détection d'objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] façade
[Termes IGN] infiltration
[Termes IGN] inondation
[Termes IGN] modèle de simulation
[Termes IGN] prévention des risques
[Termes IGN] risque naturel
[Termes IGN] segmentation sémantiqueRésumé : (auteur) With increasing urbanization, flooding is a major challenge for many cities today. Based on forecast precipitation, topography, and pipe networks, flood simulations can provide early warnings for areas and buildings at risk of flooding. Basement windows, doors, and underground garage entrances are common places where floodwater can flow into a building. Some buildings have been prepared or designed considering the threat of flooding, but others have not. Therefore, knowing the heights of these facade openings helps to identify places that are more susceptible to water ingress. However, such data is not yet readily available in most cities. Traditional surveying of the desired targets may be used, but this is a very time-consuming and laborious process. Instead, mobile mapping using LiDAR (light detection and ranging) is an efficient tool to obtain a large amount of high-density 3D measurement data. To use this method, it is required to extract the desired facade openings from the data in a fully automatic manner. This research presents a new process for the extraction of windows and doors from LiDAR mobile mapping data. Deep learning object detection models are trained to identify these objects. Usually, this requires to provide large amounts of manual annotations.
In this paper, we mitigate this problem by leveraging a rule-based method. In a first step, the rule-based method is used to generate pseudo-labels. A semi-supervised learning strategy is then applied with three different levels of supervision. The results show that using only automatically generated pseudo-labels, the learning-based model outperforms the rule-based approach by 14.6% in terms of F1-score. After five hours of human supervision, it is possible to improve the model by another 6.2%. By comparing the detected facade openings' heights with the predicted water levels from a flood simulation model, a map can be produced which assigns per-building flood risk levels. Thus, our research provides a new geographic information layer for fine-grained urban emergency response. This information can be combined with flood forecasting to provide a more targeted disaster prevention guide for the city's infrastructure and residential buildings. To the best of our knowledge, this work is the first attempt to achieve such a large scale, fine-grained building flood risk mapping.Numéro de notice : A2022-196 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101759 Date de publication en ligne : 01/02/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101759 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99964
in Computers, Environment and Urban Systems > vol 93 (April 2022) . - n° 101759[article]Flood 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)
[article]
Titre : Flood mapping using multi-temporal Sentinel-1 SAR images: A case study—Inaouene watershed from Northeast of Morocco Type de document : Article/Communication Auteurs : Brahim Benzougagh, Auteur ; Pierre-Louis Frison , Auteur ; Sarita Gajbhiye Meshram, Auteur ; Larbi Boudad, Auteur ; Abdallah Dridri, Auteur ; Driss Sadkaoui, Auteur ; Khalid Mimich, Auteur ; Khaled Mohamed Khedher, Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : pp 1481 - 1490 Note générale : bibliographie
This research work was supported by the Deanship of Scientific Research at King Khalid University under Grant number RGP. 2/173/42.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bassin hydrographique
[Termes IGN] cartographie des risques
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] inondation
[Termes IGN] Maroc
[Termes IGN] plan de prévention des risques
[Termes IGN] prévention des risques
[Termes IGN] risque naturelRésumé : (auteur) Natural disasters like floods are happening worldwide. Due to their negative impact on different social, economic and environmental aspects need to monitor and map these phenomena have increased. In fact, to access the zones affected by the flood, we use open source remote sensing (RS) images acquired by optical and radar sensors. Furthermore, we present a method using Sentinel-1 images; we suggest applying Ground Range Detected (GRD) images. For this purpose, pre-processed built and provided by the European Space Agency (ESA), preserved by free software Sentinel Application Platform (SNAP) for data extraction around appropriate demand. Moreover, the principal objective of this article is to assess the capability of Sentinel-1 Synthetic Aperture Radar (SAR) images in order to visualize flood areas in the Inaouene watershed located in north-eastern of Morocco. The origin of this natural hazard is the combination of natural and anthropogenic factors that makes the watershed vulnerable with a sub-annual frequency. The results of this work help decision-makers and managers in the field of natural risk management and land-use planning to implement a strategy and action plan for the protection of the populations and the environment against the negative impact of floods. Numéro de notice : A2022-580 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.1007/s40996-021-00683-y Date de publication en ligne : 18/06/2021 En ligne : https://doi.org/10.1007/s40996-021-00683-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99581
in Iranian Journal of Science and Technology - Transactions of Civil Engineering > vol 46 n° 2 (April 2022) . - pp 1481 - 1490[article]A 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)
[article]
Titre : A user-centric optimization of emergency map symbols to facilitate common operational picture Type de document : Article/Communication Auteurs : Tomasz Opach, Auteur ; Jan Ketil Rød, Auteur Année de publication : 2022 Article en page(s) : pp 134 - 153 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique
[Termes IGN] cartographie d'urgence
[Termes IGN] entretien d'enquête
[Termes IGN] Norvège
[Termes IGN] représentation cartographique
[Termes IGN] secours d'urgence
[Termes IGN] sémiologie graphique
[Termes IGN] symbole graphique
[Termes IGN] utilisateur
[Termes IGN] visualisation cartographiqueRésumé : (auteur) Common operational understanding among engaged emergency responders is facilitated through shared operational pictures during crisis situations. Sharing is typically achieved through interactive tools, either desktop or web-based, in which map displays play an essential role. That role can be further strengthened if (1) agreed emergency symbols that are used in map-based interactive tools are sufficient to encode multifaceted operational information visually; and (2) the symbols are legible and meaningful for the diverse users of those tools. The authors revisited official emergency map symbols in use in Norway and reconsidered them against current requirements. To this end, they first conducted several meetings with stakeholders to elicit adequate revision requirements. Next, the reconsideration included the extension of the symbol set, symbol modification, and grouping. After the reconsideration, emergency management officers and specialists were interviewed. The interviews confirmed the agreement with the symbol categorization, extension of the symbols, and their modifications. The interviewees also made numerous suggestions to be considered in a follow-up study. Moreover, two concepts – symbol standardization and symbol harmonization – were proposed. Numéro de notice : A2022-137 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1994469 Date de publication en ligne : 13/12/2021 En ligne : https://doi.org/10.1080/15230406.2021.1994469 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99758
in Cartography and Geographic Information Science > vol 49 n° 2 (March 2022) . - pp 134 - 153[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2022021 RAB Revue Centre de documentation En réserve L003 Disponible Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])
[article]
Titre : Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques Type de document : Article/Communication Auteurs : Saman Javadi, Auteur ; Seied Mehdy Hashemy Shahdany, Auteur ; Hashemy Shahdany, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1160-1182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] aquifère
[Termes IGN] arsenic
[Termes IGN] cartographie des risques
[Termes IGN] contamination
[Termes IGN] eau souterraine
[Termes IGN] Iran
[Termes IGN] logique floue
[Termes IGN] nitrate
[Termes IGN] pollution des eaux
[Termes IGN] vulnérabilitéRésumé : (auteur) This study proposes a new approach to establish a multi-parameter risk mapping method by employing the K-Means clustering technique. Accordingly, spatial assessment of arsenic (As), nitrate (NO3) and total dissolved solids (TDS) were carried out based on the type of land use to estimate contamination potential in an aquifer. Since risk mapping is always associated with the occurrence probability of a phenomenon, pollution occurrence probability was then obtained using the fuzzy C-means clustering. The results reveal that NO3 and As contamination levels increase from the first cluster (C1), covers 22.3% of the aquifer, to C5 encompassing 35.1% of the aquifer devoted to extensive industrial and agricultural activities. Fuzzy clustering results show that the pollution occurrence probability in each aquifer cell varied from less than 30 to more than 90%. Moreover, the results show, industrial and agricultural land uses cover about 70% of the areas with high risk of contamination. Numéro de notice : A2022-396 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1778099 Date de publication en ligne : 23/06/2020 En ligne : https://doi.org/10.1080/10106049.2020.1778099 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100690
in Geocarto international > vol 37 n° 4 [15/02/2022] . - pp 1160-1182[article]Mapping 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)
[article]
Titre : Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery Type de document : Article/Communication Auteurs : Donato Morresi, Auteur ; Raffaella Marzano, Auteur ; Emanuele Lingua, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112800 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] cartographie des risques
[Termes IGN] détection de changement
[Termes IGN] forêt alpestre
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] incendie de forêt
[Termes IGN] phénologie
[Termes IGN] Piémont (Italie)
[Termes IGN] réflectance spectrale
[Termes IGN] risque naturel
[Termes IGN] variation saisonnière
[Termes IGN] zone sinistréeRésumé : (auteur) Deriving burn severity from multispectral satellite data is a widely adopted approach to infer the degree of environmental change caused by fire. Burn severity maps obtained by thresholding bi-temporal indices based on pre- and post-fire Normalized Burn Ratio (NBR) can vary substantially depending on temporal constraints such as matched acquisition and optimal seasonal timing. Satisfying temporal requirements is crucial to effectively disentangle fire and non-fire induced spectral changes and can be particularly challenging when only a few cloud-free images are available. Our study focuses on 10 wildfires that occurred in mountainous areas of the Piedmont Region (Italy) during autumn 2017 following a severe and prolonged drought period. Our objectives were to: (i) generate reflectance composites using Sentinel-2 imagery that were optimised for seasonal timing by embedding spatial patterns of long-term land surface phenology (LSP); (ii) produce and validate burn severity maps based on the modelled relationship between bi-temporal indices and field data; (iii) compare burn severity maps obtained using either a pair of cloud-free Sentinel-2 images, i.e. paired images, or reflectance composites. We proposed a pixel-based compositing algorithm coupling the weighted geometric median and thematic spatial information, e.g. long-term LSP metrics derived from the MODIS Collection 6 Land Cover Dynamics Product, to rank all the clear observations available in the growing season. Composite Burn Index data and bi-temporal indices exhibited a strong nonlinear relationship (R2 > 0.85) using paired images or reflectance composites. Burn severity maps attained overall classification accuracy ranging from 76.9% to 83.7% (Kappa between 0.61 and 0.72) and the Relative differenced NBR (RdNBR) achieved the best results compared to other bi-temporal indices (differenced NBR and Relativized Burn Ratio). Improvements in overall classification accuracy offered by the calibration of bi-temporal indices with the dNBR offset were limited to burn severity maps derived from paired images. Reflectance composites provided the highest overall classification accuracy and differences with paired images were significant using uncalibrated bi-temporal indices (4.4% to 5.2%) while they decreased (2.8% to 3.2%) when we calibrated bi-temporal indices derived from paired images. The extent of the high severity category increased by ~19% in burn severity maps derived from reflectance composites (uncalibrated RdNBR) compared to those from paired images (calibrated RdNBR). The reduced contrast between healthy and burnt conditions associated with suboptimal seasonal timing caused an underestimation of burnt areas. By embedding spatial patterns of long-term LSP metrics, our approach provided consistent reflectance composites targeted at a specific phenological stage and minimising non-fire induced inter-annual changes. Being independent from the multispectral dataset employed, the proposed pixel-based compositing approach offers new opportunities for operational change detection applications in geographic areas characterised by persistent cloud cover. Numéro de notice : A2022-095 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112800 Date de publication en ligne : 22/11/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112800 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99534
in Remote sensing of environment > vol 269 (February 2022) . - n° 112800[article]Assessment 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)PermalinkA GIS-based landslide susceptibility mapping and variable importance analysis using artificial intelligent training-based methods / Pengxiang Zhao in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkHarmonisation de la production cartographique dans le cadre des Programmes d’Actions de Prévention des Inondations / Nils Deslandes (2022)PermalinkModalités et rythmes d'évolution des falaises des Vaches Noires (Normandie, France) : caractérisation et quantification des dynamiques hydrogravitaires par approches multi-scalaires / Thomas Roulland (2022)PermalinkPermalinkPermalink