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Termes IGN > sciences naturelles > sciences de la Terre et de l'univers > géosciences > géographie physique > hydrographie > hydrographie de surface > bassin hydrographique
bassin hydrographiqueSynonyme(s)Bassin-versant Bassin versantVoir aussi |
Documents disponibles dans cette catégorie (452)



Etendre la recherche sur niveau(x) vers le bas
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)
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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)
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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]Assessment of groundwater potential using multi-criteria decision analysis and geoelectrical surveying / Marzieh Shabani in Geo-spatial Information Science, vol 25 n° 4 (December 2022)
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Titre : Assessment of groundwater potential using multi-criteria decision analysis and geoelectrical surveying Type de document : Article/Communication Auteurs : Marzieh Shabani, Auteur ; Zohreh Masoumi, Auteur ; Abolfazl Rezaei, Auteur Année de publication : 2022 Article en page(s) : pp 600 - 618 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse multicritère
[Termes IGN] analyse spatiale
[Termes IGN] bassin hydrographique
[Termes IGN] carte thématique
[Termes IGN] développement durable
[Termes IGN] eau souterraine
[Termes IGN] gestion de l'eau
[Termes IGN] Iran
[Termes IGN] processus de hiérarchisation analytiqueRésumé : (auteur) A precise map of the dispersion of the groundwater potential across each watershed can help decision-makers to exert optimal water management in each region. In this research, the potential of groundwater resources in both the Zanjanrood Catchment and the Tarom Region, located in the northwest of Iran, has been studied. Seven effective criteria including slope, land-use, drainage density, spring density, lithology, lineament density, and rainfall are considered. Criteria were first weighted using the Analytical Hierarchical Process (AHP) method and then overlaid by the Technique for Order Preferences by Similarity to Ideal (TOPSIS) model. Finally, the spatial zoning map of groundwater potential was obtained in four categories. A sensitivity analysis was performed to determine the influence of each criterion on the obtained map. The model was verified using both the spatial distribution of the high-discharged production wells and the geophysical-based geoelectric field surveys. The results indicate that the high-discharged wells (>40 l/s) in both regions are dispersed predominantly in the very good zone and, in several cases, in the good zone. Besides, the results from the two-dimensional models of resistivity and induced polarization of geoelectrical field survey are inappropriate agreement with those from the TOPSIS method. Notably, there is no suitable potential zone of groundwater in the surrounding highlands to be used in the future for drinking purposes since the highlands water supply is a strategic supply for drinking. The strategies employed in this study, the results of GIS modeling, and the geoelectrical analysis can be considered for sustainable development of similar arid and semi-arid areas since groundwater is considered as the main supplier of water in such regions. Numéro de notice : A2022-891 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10095020.2022.2069052 Date de publication en ligne : 10/05/2022 En ligne : https://doi.org/10.1080/10095020.2022.2069052 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102238
in Geo-spatial Information Science > vol 25 n° 4 (December 2022) . - pp 600 - 618[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)
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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]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)
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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]Development 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])
PermalinkA GIS-based approach for identification of optimum runoff harvesting sites and storage estimation: a study from Subarnarekha-Kangsabati Interfluve, India / Manas Karmakar in Applied geomatics, vol 14 n° 2 (June 2022)
PermalinkAssessing surface drainage conditions at the street and neighborhood scale: A computer vision and flow direction method applied to lidar data / Cheng-Chun Lee in Computers, Environment and Urban Systems, vol 93 (April 2022)
PermalinkCharacterizing stream morphological features important for fish habitat using airborne laser scanning data / Spencer Dakin Kuiper in Remote sensing of environment, vol 272 (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)
PermalinkAssessment and mapping soil water erosion using RUSLE approach and GIS tools: Case of Oued el-Hai watershed, Aurès West, Northeastern of Algeria / Aida Bensekhria in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)
PermalinkUsing vertices of a triangular irregular network to calculate slope and aspect / Guanghui Hu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)
PermalinkPermalinkModélisations des écoulements fluviaux adaptées aux observations spatiales et assimilations de données altimétriques / Thibault Malou (2022)
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