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A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers / Qasim Khan in Geocarto international, vol 37 n° 20 ([20/09/2022])
[article]
Titre : A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers Type de document : Article/Communication Auteurs : Qasim Khan, Auteur ; Muhammad Usman Liaqat, Auteur ; Mohamed Mostafa Mohamed, Auteur Année de publication : 2022 Article en page(s) : pp 5832 - 5850 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse en composantes principales
[Termes IGN] apprentissage automatique
[Termes IGN] aquifère
[Termes IGN] ArcGIS
[Termes IGN] classification bayesienne
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] eau souterraine
[Termes IGN] Emirats Arabes Unis
[Termes IGN] estimation par noyau
[Termes IGN] nitrate
[Termes IGN] vulnérabilitéRésumé : (auteur) Groundwater is more prone to contamination due to its extensive usage. Different methods are applied to study vulnerability of groundwater including widely used DRASTIC method, SI and GOD. This study proposes a novel method of mapping groundwater vulnerability using machine learning algorithms. In this study, point extraction method was used to extract point values from a grid of 646 points of seven raster layer in the Al Khatim study area of United Arab Emirates. These extracted values were classified based on nitrate concentration threshold of 50 mg/L into two classes. Machine learning models were developed, using depth to water (D), recharge (R), aquifer media (A), soil media (S), topography (T), vadose zone (I) and hydraulic conductivity (C), on the basis of nitrate class. Classified ‘groundwater vulnerability class values’ were trained using 10-fold cross-validation, using four machine learning models which were Random Forest, Support Vector Machine, Naïve Bayes and C4. 5. Accuracy showed the model developed by Random Forest gained highest accuracy of 93%. Four groundwater vulnerability maps were developed from machine learning classifiers and was compared with base method of DRASTIC index. The efficiency, accuracy and validity of machine learning based models were evaluated based on Receiver Operating Characteristics (ROC) curve and Precision-Recall curve (PRC). The results proved that machine learning is an efficient tool to access, analyze and map groundwater vulnerability. Numéro de notice : A2022-716 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2021.1923833 Date de publication en ligne : 01/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1923833 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101641
in Geocarto international > vol 37 n° 20 [20/09/2022] . - pp 5832 - 5850[article]Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine / Luis Carrasco in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)
[article]
Titre : Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine Type de document : Article/Communication Auteurs : Luis Carrasco, Auteur ; Go Fujita, Auteur ; Kensuke Kito, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 277 - 289 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] cartographie historique
[Termes IGN] détection de changement
[Termes IGN] Google Earth
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] indice de végétation
[Termes IGN] Japon
[Termes IGN] phénologie
[Termes IGN] photographie aérienne
[Termes IGN] réflectance de surface
[Termes IGN] rizière
[Termes IGN] signature spectraleRésumé : (auteur) Mapping the expansion or reduction of rice fields is fundamental for food and water security, greenhouse gas emission accounting, and environmental management. The historical mapping of rice fields with satellite images is challenging because of the limited availability of remote sensing and training data from past decades. The use of phenology-based algorithms has been proposed for mapping rice fields because they can take advantage of rice fields’ characteristic spectral signature during the transplanting phase and do not need training data. However, in order to employ phenology-based algorithms effectively for the historical rice mapping of large areas, we need to incorporate automatized methods able to deal with non-usable data (e.g., cloud cover) and with spatial inconsistencies in the number of available images for each pixel. Here we propose the combination of a pixel-based, phenological algorithm with the temporal aggregation of all available Landsat images to produce national level historical maps of rice fields in Japan from the 1980s onwards. We used temporally aggregated metrics (median, percentiles, etc.), derived from spectral indices of a large number of images within the Google Earth Engine, to minimize the issue of inconsistent image availability and reduce the effects of outliers in phenology-based algorithms. We produced seven rice field maps, for the periods 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, 2010–14, and 2015–19. The overall map accuracies ranged from 83% to 95% when validated with visually interpreted aerial photography. We detected a 23% decrease in the area of rice fields at a country level, although the changes varied greatly among prefectures. Here we present the first freely available historical rice field maps of Japan from the 1980s onwards, together with the source code, and a web application that enables the exploration of the maps and data relating to the derived rice field area changes. The application of temporal aggregation is promising for dealing with the gap-filling of large amounts of satellite data, reducing the issue of data outliers and providing an effective use of the historical Landsat archive for phenology-based crop detection algorithms. Our maps could greatly help researchers, conservationists and policymakers studying the drivers and consequences of rice field changes, and our methods could be extrapolated to map rice fields at large scales in other regions of the world. Numéro de notice : A2022-665 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.07.018 Date de publication en ligne : 08/08/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.07.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101527
in ISPRS Journal of photogrammetry and remote sensing > vol 191 (September 2022) . - pp 277 - 289[article]Parcel Manager: A parcel reshaping model incorporating design rules of residential development / Maxime Colomb in Transactions in GIS, vol 26 n° 6 (September 2022)
[article]
Titre : Parcel Manager: A parcel reshaping model incorporating design rules of residential development Type de document : Article/Communication Auteurs : Maxime Colomb , Auteur ; Cécile Tannier, Auteur ; Julien Perret , Auteur ; Paul Chapron , Auteur ; Mickaël Brasebin , Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : pp 2558 - 2597 Note générale : bibliographie
This research benefited from the financial support of the I-SITE University Bourgogne Franche-Comté as part of the project PubPrivLands.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] bâtiment
[Termes IGN] code source libre
[Termes IGN] construction
[Termes IGN] densification
[Termes IGN] figure géométrique
[Termes IGN] habitat urbain
[Termes IGN] logiciel libre
[Termes IGN] parcelle cadastrale
[Termes IGN] règle d'urbanismeRésumé : (auteur) Parcels are the smallest units of land usually considered for urban development purposes. Analyses at the parcel level allow taking into account the administrative and physical environment of buildings with accuracy (roads, surrounding buildings, local design rules for building construction). In this article, we propose a free and open source software application, namely Parcel Manager, whose aims are twofold: (1) to assess the effects of different parcel reshaping rules and planning principles on the location, the number, and the shape of reshaped parcels; and (2) to provide a basis to assess the potential for new building construction. To this end, Parcel Manager simulates a large variety of parcel reshaping processes, with or without the joint creation of new roads, and produces realistic parcel layouts that represent either infill urban developments, edge expansions, or leapfrog developments. It can be used to determine if the densification of built parcels is feasible or not, regarding planning and design rules as well as the current urban fabric. The current version of Parcel Manager only concerns the reshaping of parcels dedicated to the construction of residential buildings but not other types of buildings. Numéro de notice : A2022-577 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12970 Date de publication en ligne : 03/08/2022 En ligne : https://doi.org/10.1111/tgis.12970 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101335
in Transactions in GIS > vol 26 n° 6 (September 2022) . - pp 2558 - 2597[article]Pourquoi le rendu des zones rocheuses sur les nouvelles cartes IGN est-il si différent de l’ancien ? / Paul Courbon in XYZ, n° 172 (septembre 2022)
[article]
Titre : Pourquoi le rendu des zones rocheuses sur les nouvelles cartes IGN est-il si différent de l’ancien ? Type de document : Article/Communication Auteurs : Paul Courbon, Auteur ; Dominique Foubert, Auteur Année de publication : 2022 Article en page(s) : pp 27 - 30 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Rédaction cartographique
[Termes IGN] BD Topo
[Termes IGN] carte Top 25
[Termes IGN] carte topographique
[Termes IGN] courbe de niveau
[Termes IGN] falaise
[Termes IGN] géoportail
[Termes IGN] représentation cartographique
[Termes IGN] rocher
[Termes IGN] visualisation cartographiqueRésumé : (Auteur) La rédaction de XYZ est alertée par Paul Courbon, l'un de nos auteurs, sur le rendu des zones rocheuses sur les nouvelles cartes IGN. Il compare les anciennes cartes au 1:25000 et les nouvelles, que l’on peut également visualiser sur le Géoportail. Excès d’automatisation du dessin, mauvais choix dans les méthodes de restitution, économie des moyens en personnels, Paul essaie de comprendre pourquoi il ne retrouve plus les falaises d’antan, leurs courbes de niveau et leurs ombrages. Sollicité, Dominique Foubert, ancien topographe du service de la cartographie à l’IGN, nous déroule des pistes de réflexion liées à l’historique de la production des cartes. Effectivement, grâce à l’appui de Christophe Pécot, les souvenirs se précisent et Dominique nous explique “pourquoi et comment” on en est arrivé là. Numéro de notice : A2022-673 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Date de publication en ligne : 01/09/2022 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101637
in XYZ > n° 172 (septembre 2022) . - pp 27 - 30[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 112-2022031 RAB Revue Centre de documentation En réserve L003 Disponible Evapotranspiration mapping of cotton fields in Brazil: comparison between SEBAL and FAO-56 method / Juan Vicente Liendro Moncada in Geocarto international, Vol 37 n° 17 ([20/08/2022])
[article]
Titre : Evapotranspiration mapping of cotton fields in Brazil: comparison between SEBAL and FAO-56 method Type de document : Article/Communication Auteurs : Juan Vicente Liendro Moncada, Auteur ; Tonny José Araújo da Silva, Auteur ; Jefferson Vieira José, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 5133 - 5149 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] carte thématique
[Termes IGN] corrélation
[Termes IGN] données météorologiques
[Termes IGN] évapotranspiration
[Termes IGN] Gossypium (genre)
[Termes IGN] GRASS
[Termes IGN] image Landsat-8
[Termes IGN] Mato Grosso
[Termes IGN] modèle de Monteith
[Termes IGN] phénologie
[Termes IGN] QGIS
[Termes IGN] régression logistique
[Termes IGN] système d'information géographiqueRésumé : (auteur) The objective was to compare the evapotranspiration of cotton (Gossypium sp. L.) estimated by the SEBAL model and the FAO-56 method, throughout the phenological cycle of the plant on eight fields located in the upper area of the Rio das Mortes basin, State of Mato Grosso—Brazil. Images from the Landsat 8 satellite were used under the Geographic Information Systems environment through the capabilities of the QGIS 3.6.2 and GRASS 7.6.1 software. The reference evapotranspiration was determined by the FAO Penman–Monteith method implementing the Ref-ET software and data from the Campo Verde meteorological station of INMET—Brazil. The R software was applied to the statistical analyses of correlation and regression. The dataset of the available stages of the cotton phenological cycle shows a strong positive correlation, with approximately 68% of the evapotranspiration variation of the SEBAL model related to the estimates of the FAO-56 method. Numéro de notice : A2022-700 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1920633 Date de publication en ligne : 06/05/2021 En ligne : https://doi.org/10.1080/10106049.2021.1920633 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101559
in Geocarto international > Vol 37 n° 17 [20/08/2022] . - pp 5133 - 5149[article]Comparative analysis of real-time precise point positioning method in terms of positioning and zenith tropospheric delay estimation / Omer Faruk Atiz in Survey review, vol 55 n° 388 (January 2023)PermalinkStudy of crustal deformation in Egypt based on GNSS measurements / S.A. Younes in Survey review, vol inconnu ([01/08/2022])PermalinkUse of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand / Kiatkulchai Jitt-Aer in Natural Hazards, vol 113 n° 1 (August 2022)Permalink3D-GIS parametric modelling for virtual urban simulation using CityEngine / Ibrahim M. Badwi in Annals of GIS, vol 28 n° 3 (July 2022)PermalinkIntegration of GNSS observations with volunteered geographic information for improved navigation performance / Tarek Hassan in Journal of applied geodesy, vol 16 n° 3 (July 2022)PermalinkInvestigating the ability to identify new constructions in urban areas using images from unmanned aerial vehicles, Google Earth, and Sentinel-2 / Fahime Arabi Aliabad in Remote sensing, vol 14 n° 13 (July-1 2022)PermalinkA participatory trail web map based on open source technologies / Joshua Gore in International journal of cartography, vol 8 n° 2 (July 2022)PermalinkPolyline simplification based on the artificial neural network with constraints of generalization knowledge / Jiawei Du in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)PermalinkValidation of regional and global ionosphere maps from GNSS measurements versus IRI2016 during different magnetic activity / Ahmed Sedeek in Journal of applied geodesy, vol 16 n° 3 (July 2022)PermalinkConstraint-based evaluation of map images generalized by deep learning / Azelle Courtial in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)PermalinkEfficient calculation of distance transform on discrete global grid systems / Meysam Kazemi in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)PermalinkA geospatial workflow for the assessment of public transit system performance using near real-time data / Anastassios Dardas in Transactions in GIS, vol 26 n° 4 (June 2022)PermalinkGIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data / Wanqin He in ISPRS International journal of geo-information, vol 11 n° 6 (June 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)PermalinkNarrative cartography with knowledge graphs / Gengchen Mai in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)PermalinkPhysical modelling of Nanda Devi National Park, a natural world heritage site, from GIS data / Sanat Agrawal in Cartographica, vol 57 n° 2 (Summer 2022)PermalinkPrototypage, analyse et qualification d’une solution de photogrammétrie mobile / Guillaume Niederberger in XYZ, n° 171 (juin 2022)PermalinkCity3D: Large-scale building reconstruction from airborne LiDAR point clouds / Jin Huang in Remote sensing, vol 14 n° 9 (May-1 2022)PermalinkMulti-modal temporal attention models for crop mapping from satellite time series / Vivien Sainte Fare Garnot in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)PermalinkPerformance analysis of low-cost GNSS stations for structural health monitoring of civil engineering structures / Nicolas Manzini in Structure and Infrastructure Engineering, vol 18 n° 5 ([01/05/2022])Permalink