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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]Flood monitoring by integration of remote sensing technique and multi-criteria decision making method / Hadi Farhadi in Computers & geosciences, vol 160 (March 2022)
[article]
Titre : Flood monitoring by integration of remote sensing technique and multi-criteria decision making method Type de document : Article/Communication Auteurs : Hadi Farhadi, Auteur ; Ali Esmaeily, Auteur ; Mohammad Najafzadeh, Auteur Année de publication : 2022 Article en page(s) : n° 105045 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse multicritère
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] Electre
[Termes IGN] image Sentinel-MSI
[Termes IGN] inondation
[Termes IGN] Iran
[Termes IGN] Matlab
[Termes IGN] rapport signal sur bruit
[Termes IGN] surveillance hydrologiqueRésumé : (auteur) Traditional methodologies of flood monitoring are generally time-consuming and demanding tasks. In most cases, there is no possibility of flood monitoring in large areas. Due to the major drawbacks of conventional methods in flood detection of large districts, Remote Sensing (RS) has been efficiently employed as the best solution owing to its being synoptic view and cost-effective methodologies. One of the most challenging issues in RS technologies is choosing the optimal spectral bands to detect changes in the natural environment. In this research, Elimination and Choice Expressing Reality (ELECTRE), as one of the most widely used Multi-Criteria Decision Making (MCDM) techniques, was applied to select the optimal bands of Sentinel-2 satellite images for detection of flood-affected areas. For this purpose, the decision-making method was implemented during ten options and six criteria. The properties of the Sentinel-2 satellite images consisted of ten bands (with 10 and 20m spatial resolutions) and the criteria are the signal to noise ratio (SNR) related to sensor, standard deviation, variance, the SNR related to the bands, spatial resolution, and wavelength. Afterward, the ELECTRE technique was used to select six optimal bands among ten bands. The ELECTRE algorithm was programmed in MATLAB programming language that could make decisions with multiple options and multiple criteria. Furthermore, the Support Vector Machine (SVM) classification method, as one of the most powerful Machine Learning (ML) models, has been applied to classify the water bodies related to before and after the flood. According to the results of optimal bands classification, Overall Accuracy (OA) and Kappa Coefficient (KC) for the pre-flood classification were 93.65 percent and 0.923, respectively, and for the post-flood classification, the OA and KC values were 94.52 percent and 0.935 respectively. In the case of before and after flooding, the results of classification model for optimal bands had more accuracy levels in comparison with those obtained by original bands. Generally, it was found that the ELECTRE technique for selecting the best bands of Sentinel-2 satellite images and detection of flood-affected areas, in a short period of time with high accuracy, offers remarkable and consistent results. Numéro de notice : A2022-175 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2022.105045 Date de publication en ligne : 29/01/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105045 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99814
in Computers & geosciences > vol 160 (March 2022) . - n° 105045[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)
[article]
Titre : Assessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India Type de document : Article/Communication Auteurs : Rajib Mitra, Auteur ; Piu Saha, Auteur ; Jayanta Das, Auteur Année de publication : 2022 Article en page(s) : pp 2183 - 2226 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse des risques
[Termes IGN] analyse multicritère
[Termes IGN] Bengale-Occidental (Inde ; état)
[Termes IGN] carte thématique
[Termes IGN] cartographie des risques
[Termes IGN] inondation
[Termes IGN] modélisation spatiale
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] risque naturelRésumé : (auteur) Floods have received global significance in contemporary times due to their destructive behavior, which may wreak tremendous ruin on infrastructure and civilization. The present research employed an integration of the Geographic information system (GIS) and Analytical Hierarchy Process (AHP) method for identifying the flood susceptibility zonation (FSZ), flood vulnerability zonation (FVZ), and flood risk zonation (FRZ) of the humid subtropical Uttar Dinajpur district in India. The study combined a large number of thematic layers (N = 12 for FSZ and N = 9 for FVZ) to achieve reliable accuracy and included the multicollinearity analysis of these variables to overcome the issues related to highly correlated variables. According to the findings, 27.04, 15.62, and 4.59% of the area were classified as medium, high, and very high FRZ, respectively. The ROC-AUC, MAE, MSE, and RMSE of the model exhibited a good prediction accuracy of 0.73, 0.15, 0.16, and 0.21, respectively. The performance of the AHP model has been evaluated using sensitivity analyses. It also highly recommends that persistent improvement in this subject, such as sensitivity studies on modifying criteria thresholds, changing the relative significance of criteria, and changing the desired matrix, will permit GIS and MCDA to be progressively adapted to real hazard-management issues. Numéro de notice : A2022-885 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475705.2022.2112094 En ligne : https://doi.org/10.1080/19475705.2022.2112094 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102211
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 2183 - 2226[article]CIME: Context-aware geolocation of emergency-related posts / Gabriele Scalia in Geoinformatica, vol 26 n° 1 (January 2022)
[article]
Titre : CIME: Context-aware geolocation of emergency-related posts Type de document : Article/Communication Auteurs : Gabriele Scalia, Auteur ; Chiara Francalanci, Auteur ; Barbara Pernici, Auteur Année de publication : 2022 Article en page(s) : pp 125 - 157 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] cartographie d'urgence
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] exploration de données
[Termes IGN] géolocalisation
[Termes IGN] géoréférencement
[Termes IGN] Grande-Bretagne
[Termes IGN] implémentation (informatique)
[Termes IGN] inondation
[Termes IGN] New York (Etats-Unis ; ville)
[Termes IGN] prise en compte du contexte
[Termes IGN] tempête
[Termes IGN] TwitterRésumé : (auteur) Information extracted from social media has proven to be very useful in the domain of emergency management. An important task in emergency management is rapid crisis mapping, which aims to produce timely and reliable maps of affected areas. During an emergency, the volume of emergency-related posts is typically large, but only a small fraction is relevant and help rapid mapping effectively. Furthermore, posts are not useful for mapping purposes unless they are correctly geolocated and, on average, less than 2% of posts are natively georeferenced. This paper presents an algorithm, called CIME, that aims to identify and geolocate emergency-related posts that are relevant for mapping purposes. While native geocoordinates are most often missing, many posts contain geographical references in their metadata, such as texts or links that can be used by CIME to filter and geolocate information. In addition, social media creates a social network and each post can be enhanced with indirect information from the post’s network of relationships with other posts (for example, a retweet can be associated with other geographical references which are useful to geolocate the original tweet). To exploit all this information, CIME uses the concept of context, defined as the information characterizing a post both directly (the post’s metadata) and indirectly (the post’s network of relationships). The algorithm was evaluated on a recent major emergency event demonstrating better performance with respect to the state of the art in terms of total number of geolocated posts, geolocation accuracy and relevance for rapid mapping. Numéro de notice : A2022-204 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-021-00446-x Date de publication en ligne : 28/07/2021 En ligne : https://doi.org/10.1007/s10707-021-00446-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100011
in Geoinformatica > vol 26 n° 1 (January 2022) . - pp 125 - 157[article]
Titre : Etude de la propagation de l’onde de crue du bassin versant de la Save Type de document : Mémoire Auteurs : Emma Bonzom, Auteur Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2022 Importance : 44 p. Format : 21 x 30 cm Note générale : bibliographie
Rapport de stage de Master 1 GéomatiqueLangues : Français (fre) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse de données
[Termes IGN] bassin hydrographique
[Termes IGN] cartographie thématique
[Termes IGN] crue
[Termes IGN] inondation
[Termes IGN] modèle de régression
[Termes IGN] QGIS
[Termes IGN] R (langage)
[Termes IGN] régression linéaire
[Termes IGN] rivièreIndex. décimale : M1GEO Mémoires de Master 1 Géomatique Résumé : (auteur) Mon stage de fin de première année du cycle du Master Géomatique à l’ENSG s’est déroulé au sein du syndicat de gestion de la Save et de ses affluents. C’est un organisme public qui protège et aménage les masses d’eau du bassin versant de la Save grâce à leur compétence GEMAPI (Gestion des Milieux Aquatiques et de Prévention des Inondations). J’ai été accueillie par une technicienne de rivière référente prévention des inondations. Le syndicat cherchait un stagiaire capable de réaliser une étude sur la propagation de l’onde de crue du bassin versant de la Save afin de renforcer leurs connaissances de l’aléa inondation sur leur territoire. Il faut estimer le temps de propagation de l’onde entre chaque station hydrométrique du bassin versant. Ce rapport retrace comment à partir de tableaux au format CSV de données hydrométriques, cette étude a été réalisée en deux grands axes : la visualisation et l’analyse statistique des données. Je me suis servie pour cette étude sur l’onde de crue de QGIS, PostgreSQL, Python et R. Cette mission au sein du syndicat de rivière m’a donnée la possibilité de mettre en application concrète mes connaissances acquises à l’école au service de la gestion de l’environnement, plus précisément la gestion des milieux aquatiques. Note de contenu : Introduction
1- Visualisation des données des stations hydrométriques
2- Analyse statistique des données géographiques
3- Travail annexe pour le syndicat de gestion de la rivière Save
ConclusionNuméro de notice : 24029 Affiliation des auteurs : non IGN Nature : Mémoire masters divers Organisme de stage : Syndicat de gestion de la Save et de ses affluents Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101833 Documents numériques
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