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Retours d'expérience de la mise en place d'une plateforme collaborative pour le suivi de l'usage du sol / Ana-Maria Olteanu-Raimond in Cartes & Géomatique, n° 247-248 (mars-juin 2022)
[article]
Titre : Retours d'expérience de la mise en place d'une plateforme collaborative pour le suivi de l'usage du sol Type de document : Article/Communication Auteurs : Ana-Maria Olteanu-Raimond , Auteur ; Marie-Dominique Van Damme , Auteur ; Laurence Jolivet , Auteur Année de publication : 2022 Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie Article en page(s) : pp 65 - 67 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données d'occupation du sol
[Termes IGN] changement d'utilisation du sol
[Termes IGN] données localisées des bénévoles
[Termes IGN] information géographique
[Termes IGN] plateforme collaborative
[Termes IGN] Toulouse
[Termes IGN] utilisation du solRésumé : (Auteur) [Résumé de l'intervention faite à Florence lors de la conférence de l'ACI en décembre 2021] La cartographie et le suivi de l'usage du sol (US) à une échelle spatiale et temporelle fine nécessitent beaucoup d'efforts. Des approches de détection de changement s'appuient sur la télédétection (Lu et al., 2014), cependant l'information d'usage n'est pas nécessairement en lien avec l'information de couverture du sol et elle n'est pas triviale. Un intérêt considérable s'est porté sur l'information géographique volontaire (ou volunteered geographic information) (Goodchild, 2007) comme une source de données alternative (Fonte et al., 2013) ; Fritz et al., 2015). L'objectif de cet article est de discuter des retours d'expérience suite à une initiative en information géographique volontaire pour collecter des observations sur des changements et des usages du sol ciblés (par exemple activité en carrière, usage et nombre d'étages d'un bâtiment, construction en cours), ceci afin de mettre à jour et d'enrichir des bases de données d'usage du sol institutionnelles produites par l'IGN. Numéro de notice : A2022-677 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101895
in Cartes & Géomatique > n° 247-248 (mars-juin 2022) . - pp 65 - 67[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 021-2022011 SL Revue Centre de documentation Revues en salle Disponible Road network generalization method constrained by residential areas / Zheng Lyu in ISPRS International journal of geo-information, vol 11 n° 3 (March 2022)
[article]
Titre : Road network generalization method constrained by residential areas Type de document : Article/Communication Auteurs : Zheng Lyu, Auteur ; Qun Sun, Auteur ; Jingzhen Ma, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 159 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] 1:50.000
[Termes IGN] carte routière
[Termes IGN] connexité (topologie)
[Termes IGN] corrélation
[Termes IGN] programmation par contraintes
[Termes IGN] quartier
[Termes IGN] réseau routier
[Termes IGN] voisinage (relation topologique)
[Termes IGN] zone (aménagement du territoire)
[Vedettes matières IGN] GénéralisationRésumé : (auteur) Residential areas and road networks have a strong geographical correlation. The development of a single geographical feature could destroy the geographical correlation. It is necessary to establish collaborative generalization models suitable for multiple features. However, existing road network generalization methods for mapping purposes do not fully consider residential areas. Compared with road networks, residential areas have a higher priority in cartographic generalization. In this regard, this study proposes a road network generalization method constrained by residential areas. First, the roads and settlements obtained from clustering residential areas were classified. Next, the importance of the settlements was evaluated and certain settlements were selected as the control features. Subsequently, a geographical network with the settlements as the nodes was built, and the traffic paths between adjacent settlements were searched. Finally, redundant paths between the settlements were simplified, and the visual continuity and topological connectivity were checked. The data of a 1:50,000 road network and residential areas were used as the experimental data. The experimental results demonstrated that the proposed method preserves the overall structure and relative density characteristics of the road network, as well as the geographical correlation between the road network and residential areas. Numéro de notice : A2022-184 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11030159 Date de publication en ligne : 22/02/2022 En ligne : https://doi.org/10.3390/ijgi11030159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99890
in ISPRS International journal of geo-information > vol 11 n° 3 (March 2022) . - n° 159[article]Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis / Kai Zhang in Sustainable Cities and Society, vol 78 (March 2022)
[article]
Titre : Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis Type de document : Article/Communication Auteurs : Kai Zhang, Auteur ; Zhen Qian, Auteur ; Yue Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage profond
[Termes IGN] cartographie du bruit
[Termes IGN] Chine
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] distribution spatiale
[Termes IGN] image Streetview
[Termes IGN] lutte contre le bruit
[Termes IGN] milieu urbain
[Termes IGN] OpenStreetMap
[Termes IGN] planification urbaine
[Termes IGN] pollution acoustique
[Termes IGN] trafic routier
[Termes IGN] ville durableRésumé : (auteur) Road noise barriers (RNBs) are important urban infrastructures to relieve the harm of traffic noise pollution for citizens. Therefore, obtaining the spatial distribution characteristics of RNBs, such as precise positions and mileage, can be of great help for obtaining more accurate urban noise maps and assessing the quality of the urban living environment for sustainable urban development. However, an effective and efficient method for identifying RNBs and acquiring their attributes in large areas is scarce. This study constructs an ensemble classification model (ECM) to automatically identify RNBs at the city level based on Baidu Street View (BSV). Firstly, the bootstrap sampling method is proposed to build a street view image-based train set, where the effect of imbalanced categories of samples was reduced by adding confusing negative samples. Secondly, two state-of-the-art deep learning models, ResNet and DenseNet, are ensembled to construct an ECM based on the bagging framework. Finally, a post-processing method has been proposed based on geospatial analysis to eliminate street view images (SVIs) that are misclassified as RNBs. This study takes Suzhou, China as the study area to validate the proposed method. The model achieved an accuracy and F1-score of 0.98 and 0.90, respectively. The total mileage of the RNBs in Suzhou was 178,919 m. The results demonstrated the performance of the proposed RNBs identification framework. The significance of obtaining RNBs attributes for accelerating sustainable urban development has been demonstrated through the case of photovoltaic noise barriers (PVNBs). Numéro de notice : A2022-241 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.scs.2021.103598 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1016/j.scs.2021.103598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100167
in Sustainable Cities and Society > vol 78 (March 2022) . - n° 103598[article]Simulation of future forest and land use/cover changes (2019–2039) using the cellular automata-Markov model / Hasan Aksoy in Geocarto international, vol 37 n° 4 ([15/02/2022])
[article]
Titre : Simulation of future forest and land use/cover changes (2019–2039) using the cellular automata-Markov model Type de document : Article/Communication Auteurs : Hasan Aksoy, Auteur ; Sinan Kaptan, Auteur Année de publication : 2022 Article en page(s) : pp 1183 - 1202 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] automate cellulaire
[Termes IGN] classification dirigée
[Termes IGN] détection de changement
[Termes IGN] gestion forestière
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-TM
[Termes IGN] modèle de Markov
[Termes IGN] occupation du sol
[Termes IGN] surface cultivée
[Termes IGN] surface forestière
[Termes IGN] Turquie
[Termes IGN] utilisation du solRésumé : (auteur) This study aimed to simulate and assess forest cover and land use/land cover (LULC) changes between 2019 and 2039 using the cellular automata-Markov model. The performance of the model was evaluated by comparing the 2019 simulation map with the 2019 supervised classified map, and it was found to be reliable, with a similarity rate of 85.43%. The LULC analysis and estimates were carried out for a total of six classes: coniferous, broad-leaf, mixed forest, settlement, water and agriculture. Between 1999 and 2019, the areas of total forest increased by 17.4%, settlement by 84.6% and water by 20.1%, whereas the agriculture area decreased by 33.2%. According to 2019‒2039 land use/cover simulation results, there were decreases of 2.4% in total forest area and 3.7% in residential and water surface areas, but a 6.9% decrease in the agriculture class. Tracking these changes will contribute to decision making and strategy development efforts of forest planners and managers. Numéro de notice : A2022-397 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1778102 Date de publication en ligne : 22/06/2020 En ligne : https://doi.org/10.1080/10106049.2020.1778102 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100691
in Geocarto international > vol 37 n° 4 [15/02/2022] . - pp 1183 - 1202[article]Application of catastrophe theory to spatial analysis of groundwater potential in a sub-humid tropical region: a hybrid approach / Laishram Kanta Singh in Geocarto international, vol 37 n° 3 ([01/02/2022])
[article]
Titre : Application of catastrophe theory to spatial analysis of groundwater potential in a sub-humid tropical region: a hybrid approach Type de document : Article/Communication Auteurs : Laishram Kanta Singh, Auteur ; Madan K. Jha, Auteur ; V.M. Chowdary, Auteur Année de publication : 2022 Article en page(s) : pp 700 - 719 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse multicritère
[Termes IGN] analyse spatiale
[Termes IGN] couche thématique
[Termes IGN] drainage
[Termes IGN] eau souterraine
[Termes IGN] gestion de l'eau
[Termes IGN] Inde
[Termes IGN] pondération
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] zone tropicale humideRésumé : (auteur) Geospatial techniques and Multi-Criteria Decision Analysis (MCDA) play a crucial role in the planning and management of land and water resources. GIS-based MCDA technique "Catastrophe theory" has been recently proposed for evaluating groundwater potential. However, the major limitation of "Catastrophe theory" is that only quantitative factors/thematic layers can be used for assessing groundwater potential, though qualitative factors are equally important. To overcome this inherent limitation, a novel GIS-based MCDA approach named "Hybrid Catastrophe" technique is proposed in this study. The "Hybrid Catastrophe" technique integrates the original "Catastrophe theory" with the "Analytic Hierarchy Process (AHP)" to take into account both qualitative and quantitative thematic layers for assessing groundwater potential, thereby improving the reliability and versatility of the original Catastrophe technique. The applicability of "Hybrid Catastrophe" technique is demonstrated through a case study wherein 8 influential thematic layers (both quantitative and qualitative) were considered for assessing groundwater potential. The four quantitative layers were assigned weights based on the "Catastrophe theory" and the remaining four qualitative layers were assigned weights based on the "AHP theory". These thematic layers were integrated in GIS to delineate groundwater potential zones. The "Hybrid Catastrophe" technique yields four groundwater potential zones in the study area: (i) "very good" (covering 16% of the study area), (ii) "good" (54%), (iii) "moderate" (29%) and (iv) "poor" (1%) and its accuracy was found to be 77% that is reasonably high. The proposed "Hybrid Catastrophe" technique is versatile and it can be successfully applied to other parts of the world for evaluating groundwater potential at diverse spatial scales irrespective of agro-climatic, hydrologic and hydrogeologic conditions. Numéro de notice : A2022-343 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1737970 Date de publication en ligne : 11/03/2020 En ligne : https://doi.org/10.1080/10106049.2020.1737970 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100524
in Geocarto international > vol 37 n° 3 [01/02/2022] . - pp 700 - 719[article]Discovering transition patterns among OpenStreetMap feature classes based on the Louvain method / Yijiang Zhao in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkGazPNE: annotation-free deep learning for place name extraction from microblogs leveraging gazetteer and synthetic data by rules / Xuke Hu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)PermalinkGenerating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network / Da He in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)PermalinkGisGCN: a visual graph-based framework to match geographical areas through time / Margarita Khokhlova in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)PermalinkQuantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data / Tianyu Hu in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)PermalinkQuickly locating POIs in large datasets from descriptions based on improved address matching and compact qualitative representations / Ruozhen Cheng in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkRaw GIS to 3D road modeling for real-time traffic simulation / Yacine Amara in The Visual Computer, vol 38 n° 1 (January 2022)Permalink3D modeling of urban area based on oblique UAS images - An end-to-end pipeline / Valeria-Ersilia Oniga in Remote sensing, vol 14 n° 2 (January-2 2022)PermalinkSemantic segmentation of land cover from high resolution multispectral satellite images by spectral-spatial convolutional neural network / Ekrem Saralioglu in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkPermalink