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Regionalization of flood magnitudes using the ecological attributes of watersheds / Bahman Jabbarian Amiri in Geocarto international, vol 35 n° 9 ([01/07/2020])
[article]
Titre : Regionalization of flood magnitudes using the ecological attributes of watersheds Type de document : Article/Communication Auteurs : Bahman Jabbarian Amiri, Auteur ; Bahareh Baheri, Auteur ; Nicola Fohrer, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 917 - 933 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] bassin hydrographique
[Termes IGN] Caspienne, mer
[Termes IGN] crue
[Termes IGN] débit
[Termes IGN] estimation quantitative
[Termes IGN] humidité du sol
[Termes IGN] inondation
[Termes IGN] modèle de simulation
[Termes IGN] occupation du sol
[Termes IGN] prévention des risques
[Termes IGN] régionalisation (segmentation)
[Termes IGN] ressources en eau
[Termes IGN] utilisation du sol
[Termes IGN] zone inondableRésumé : (auteur) Estimating flood discharge at ungauged sites is a significant challenge facing water resources planners and engineers during the planning and design of hydraulic structures, managing flood prone zones, and operating artificial waterbodies. Developing more robust models to improve the reliability of flood discharge estimations is thus very useful. The role of ecological attributes including land use/land cover (LULC), hydrologic soil groups (HSG), and watershed physical characteristics (area, main stream length, average slope), and watershed shape coefficients (form, compactness, circularity, and elongation) in explaining the overall variation in flood magnitude in 39 watersheds, located in the southern basin of the Caspian Sea, was investigated. As the LULC and HSG were found to play a significant role in explaining total variation (40–89%) in flood magnitudes, their inclusion in the estimation of flood magnitudes can provide more reliable estimates of flood risk and magnitude. Numéro de notice : A2020-428 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1552321 Date de publication en ligne : 07/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1552321 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95494
in Geocarto international > vol 35 n° 9 [01/07/2020] . - pp 917 - 933[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020091 RAB Revue Centre de documentation En réserve L003 Disponible A web-based spatial decision support system for monitoring the risk of water contamination in private wells / Yu Lan in Annals of GIS, vol 26 n° 3 (July 2020)
[article]
Titre : A web-based spatial decision support system for monitoring the risk of water contamination in private wells Type de document : Article/Communication Auteurs : Yu Lan, Auteur ; Wenwu Tang, Auteur ; Samantha Dye, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 293 - 309 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] arsenic
[Termes IGN] base de données localisées
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] contamination
[Termes IGN] eau souterraine
[Termes IGN] interpolation spatiale
[Termes IGN] krigeage
[Termes IGN] pollution des eaux
[Termes IGN] prévention des risques
[Termes IGN] puits
[Termes IGN] santé
[Termes IGN] surveillance sanitaire
[Termes IGN] système d'aide à la décision
[Termes IGN] système d'information géographique
[Termes IGN] WebSIGRésumé : (auteur) Long-term exposure to contaminated water can cause health effects, such as cancer. Accurate spatial prediction of inorganic compounds (e.g. arsenic) and pathogens in groundwater is critical for water supply management. Ideally, environmental health agencies would have access to an early warning system to alert well owners of risks of such contamination. The estimation and dissemination of these risks can be facilitated by the combination of Geographic Information Systems and spatial analysis capabilities – i.e., spatial decision support system (SDSS). However, the use of SDSS, especially web-based SDSS, is rare for spatially explicit studies of drinking water quality of private wells. In this study, we introduce the interactive Well Water Risk Estimation(iWWRE), a web-based SDSS to facilitate the monitoring of water contamination in private wells across Gaston County, North Carolina (US). Our system implements geoprocessing web services and generates dynamic spatial analysis results based on a database of private wells. Environmental health scientists using our system can conduct fine-grained spatial interpolation on 1) a particular type of contaminant such as arsenic, 2) on various subsets through a temporal query. Visuals consist of an estimation map, cross validation information, Kriging variance and contour lines that delineate areas with maximum contaminant levels (MCL), as set by the US Environmental Protection Agency (EPA). Our web-based SDSS was developed jointly with environmental health specialists who found it particularly critical for the monitoring of local contamination trends, and a useful tool to reach out to private well users in highly elevated contaminated areas. Numéro de notice : A2020-583 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1798508 Date de publication en ligne : 30/07/2020 En ligne : https://doi.org/10.1080/19475683.2020.1798508 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95905
in Annals of GIS > vol 26 n° 3 (July 2020) . - pp 293 - 309[article]Analysis of dam deformation with robust weight functions / Berkant Konakoglu in Geodetski vestnik, vol 64 n° 2 (June - August 2020)
[article]
Titre : Analysis of dam deformation with robust weight functions Type de document : Article/Communication Auteurs : Berkant Konakoglu, Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Slovène (slv) Descripteur : [Vedettes matières IGN] Topographie moderne
[Termes IGN] barrage
[Termes IGN] déformation d'édifice
[Termes IGN] données GNSS
[Termes IGN] méthode robuste
[Termes IGN] surveillance d'ouvrage
[Termes IGN] surveillance géologique
[Termes IGN] TurquieRésumé : (auteur)Civil engineering structures (e.g., bridges, dams) are exposed to deformation under the influence of various factors such as water level changes, landslides, tectonic phenomena, etc. These deformations must be periodically monitored. Various deformation analysis approaches have been developed to describe the behaviour of a structure or natural process. The most significant task in deformation analysis is to correctly classify whether the points are stable or unstable. In this study, various robust weight functions for determination of stable/unstable points were applied to the Deriner Dam using GNSS (Global Navigation Satellite System) data measured over four different periods. The robust weight functions examined included the Andrews, Beaton−Tukey, Cauchy, Danish, Fair, German−McClure, Hampel, Huber, L1, and L1−L2. Test results were evaluated, and the performances of the different deformation analysis methods were determined. It was concluded that the horizontal deformations based on GNSS data determined by these robust weight functions were in good agreement with each other, except for the L1−L2. The results of all approaches were also compared with the results of the θ2–Criteria method. According to the results obtained, although the θ2–Criteria and the robust methods yielded nearly similar results, the results of the θ2–Criteria method were thought to be more reliable. Numéro de notice : A2020-404 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.15292/geodetski-vestnik.2020.02.198-213 Date de publication en ligne : 12/06/2020 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2020.02.198-213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95457
in Geodetski vestnik > vol 64 n° 2 (June - August 2020) . - 16 p.[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 139-2020021 RAB Revue Centre de documentation En réserve L003 Disponible Data-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India / Subrata Mondal in Geocarto international, Vol 35 n° 8 ([01/06/2020])
[article]
Titre : Data-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India Type de document : Article/Communication Auteurs : Subrata Mondal, Auteur ; Sujit Mandal, Auteur Année de publication : 2020 Article en page(s) : pp 818 - 856 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] anthropisation
[Termes IGN] cartographie des risques
[Termes IGN] effondrement de terrain
[Termes IGN] géomorphologie locale
[Termes IGN] Himalaya
[Termes IGN] lithologie
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surveillance hydrologique
[Termes IGN] théorie de Dempster-Shafer
[Termes IGN] vulnérabilitéRésumé : (auteur) In the present study, data-driven evidential belief function model (belief function) was employed to generate landslides susceptibility index map of Darjeeling Himalaya considering 15 landslide causative factors, which grouped into six categories, i.e. geomorphological factors (elevation, aspect, slope, curvature), lithological factors (geology, soil, lineament density, distance to lineament), hydrologic factors (drainage density, distance to drainage, stream power index, topographic wetted index), triggering factor (rainfall), protective factor (normalized differential vegetation index) and anthropogenic factor (land use and land cover). Total 2079 landslide locations were mapped and randomly divided it into training datasets (70% landslide locations) and validation datasets (30% landslide locations). The resultant susceptibility map was divided into five different susceptibility zones i.e. very low, low, moderate, high and very high which covered 5.60%, 25.65%, 34.47%, 24.67% and 9.61% area respectively of the Darjeeling Himalaya. Receiver operating characteristics curve suggested that 80.20% prediction accuracy of the prepared map whereas frequency ratio plot indicated towards the ideal landslides susceptibility index map. Numéro de notice : A2020-274 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10106049.2018.1544288 Date de publication en ligne : 13/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1544288 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95059
in Geocarto international > Vol 35 n° 8 [01/06/2020] . - pp 818 - 856[article]Hydrogeology of the western Po plain (Piedmont, NW Italy) / Domenico Antonio De Luca in Journal of maps, vol 16 n° 2 ([01/06/2020])
[article]
Titre : Hydrogeology of the western Po plain (Piedmont, NW Italy) Type de document : Article/Communication Auteurs : Domenico Antonio De Luca, Auteur ; Manuela Lasagna, Auteur ; laura Debernardi, Auteur Année de publication : 2020 Article en page(s) : pp 265 - 273 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] 1:300.000
[Termes IGN] aquifère
[Termes IGN] carte hydrogéologique
[Termes IGN] eau souterraine
[Termes IGN] gestion de l'eau
[Termes IGN] gestion des risques
[Termes IGN] lit majeur
[Termes IGN] Pô (plaine)
[Termes IGN] sédimentRésumé : (auteur) This paper describes the hydrogeological map of the western Po Plain, located in Piedmont (north-western Italy). Po plain represents a hydrogeological system of European relevance, and the Piedmont Plain is the most important groundwater reservoir of the Region. The 1:300,000 scale map was realised using previous and new data to update the knowledge of this area. The map provides information about the hydrogeological complexes and their type and degree of permeability, water table levels and depth, piezometric level fluctuation, lithostratigraphic cross-sections, thickness, and percentage of the permeable deposits between 0 and 50 m from the ground surface. All this information is essential to public administrations, stakeholders, researchers, and professionals for defining possible tools for groundwater protection and management and for planning new groundwater exploitation (i.e. municipal drinking water supplies). Numéro de notice : A2020-646 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2020.1738280 Date de publication en ligne : 18/03/2020 En ligne : https://doi.org/10.1080/17445647.2020.1738280 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96073
in Journal of maps > vol 16 n° 2 [01/06/2020] . - pp 265 - 273[article]Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkFusing 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)PermalinkIncorporating Sentinel-1 SAR imagery with the MODIS MCD64A1 burned area product to improve burn date estimates and reduce burn date uncertainty in wildland fire mapping / Kristofer Lasko in Geocarto international, vol 35 n° 6 ([01/05/2020])PermalinkShrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification / Jose Aranha in Forests, vol 11 n° 5 (May 2020)PermalinkTephra mass eruption rate from ground-based X-band and L-band microwave radars during the November 23, 2013, Etna Paroxysm / Frank S. Marzano in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkVisualizing when, where, and how fires happen in U.S. parks and protected areas / Nicole C. Inglis in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)PermalinkA citSci approach for rapid earthquake intensity mapping: a case study from Istanbul (Turkey) / Ilyas Yalcin in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)PermalinkA Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions / Shahryar K. Ahmad in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)PermalinkMonitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkAssessing the shape accuracy of coarse resolution burned area identifications / Michael L. Humber in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)Permalink