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Detecting land use and land cover change on Barbuda before and after the Hurricane Irma with respect to potential land grabbing: A combined volunteered geographic information and multi sensor approach / Andreas Rienow in International journal of applied Earth observation and geoinformation, vol 108 (April 2022)
[article]
Titre : Detecting land use and land cover change on Barbuda before and after the Hurricane Irma with respect to potential land grabbing: A combined volunteered geographic information and multi sensor approach Type de document : Article/Communication Auteurs : Andreas Rienow, Auteur ; Jan Schweighöfer, Auteur ; Torben Dedring, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102732 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] anthropisation
[Termes IGN] Antilles (îles des)
[Termes IGN] carte thématique
[Termes IGN] changement d'occupation du sol
[Termes IGN] détection de changement
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] éclairage public
[Termes IGN] image Sentinel
[Termes IGN] image Terra-MODIS
[Termes IGN] occupation du sol
[Termes IGN] OpenStreetMap
[Termes IGN] tempête
[Termes IGN] utilisation du solRésumé : (auteur) Two months after the hurricanes Irma and Maria hit Barbuda, the construction of a new international airport led to accusations of degrading the Codrington Lagoon National Park and contravening the conventions of the Ramsar Program. Scientists have analyzed the aftermath with respect to historical legacies, disaster capitalism, manifestation of climate injustices and green gentrification. The main objective of this study was to quantify and allocate land use and land cover change (LULCC) in Barbuda before and after the 2017 Hurricane disasters. Remote sensing data and volunteered geographic information were analyzed to detect the potential changes in natural LULC so that human activities and the emergence of artificial surfaces could be detected. Human-induced LULCC occurred at different sites on the island, with decreased activities in Codrington, but increased and continued activities at Coco and Palmetto Points. With an accuracy of 97.1 %, we estimated a total increase of vegetated areas by 6.56 km2, and a simultaneous slight increase in roads and buildings with a total length of 249.67 km and a total area of 1.43 km2. The vegetation condition itself depict a steady decrease since 2017. New hotspots of human activity emerged on the island in the Codrington Lagoon National Park. Numéro de notice : A2022-233 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102732 Date de publication en ligne : 02/03/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102732 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100123
in International journal of applied Earth observation and geoinformation > vol 108 (April 2022) . - n° 102732[article]Human movement patterns of different racial-ethnic and economic groups in U.S. top 50 populated cities: What can social media tell us about isolation? / Meiliu Wu in Annals of GIS, vol 28 n° 2 (April 2022)
[article]
Titre : Human movement patterns of different racial-ethnic and economic groups in U.S. top 50 populated cities: What can social media tell us about isolation? Type de document : Article/Communication Auteurs : Meiliu Wu, Auteur ; Qunying Huang, Auteur Année de publication : 2022 Article en page(s) : pp 161 - 183 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données socio-économiques
[Termes IGN] Etats-Unis
[Termes IGN] ethnie
[Termes IGN] migration humaine
[Termes IGN] mobilité territoriale
[Termes IGN] sociologie
[Termes IGN] TwitterRésumé : (auteur) Many studies have proven that human movement patterns are strongly impacted by individual socioeconomic and demographic background. While many efforts have been made on exploring the influences of age and gender on movement patterns using social media, this study aims to analyse and compare the movement patterns among different racial-ethnic and economic groups using social media (i.e. geotagged tweets) from the U.S. top 50 populated cities. Results show that there are significant differences in number of activity zones and median travel distance across cities and demographic groups, and that power-laws tend to be captured in both spatial and demographic aspects. Additionally, the analysis of outbound-city travels demonstrates that some cities have slightly stronger interaction with others, and that economically disadvantaged populations and racial-ethnic minorities are more restricted in long distance travels, indicating that their spatial mobility is more limited to the local scale. Lastly, an economically-segregated movement pattern is discovered – upper-class neighbourhoods are mostly visited by the upper-class, while lower-class neighbourhoods are mainly accessed by the lower-class – but some racial-ethnic groups can diversify this segregated pattern in the local scale. Numéro de notice : A2022-501 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2022.2026471 Date de publication en ligne : 22/01/2022 En ligne : https://doi.org/10.1080/19475683.2022.2026471 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100998
in Annals of GIS > vol 28 n° 2 (April 2022) . - pp 161 - 183[article]Mining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction / Jincai Huang in Transactions in GIS, vol 26 n° 2 (April 2022)
[article]
Titre : Mining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction Type de document : Article/Communication Auteurs : Jincai Huang, Auteur ; Yunfei Zhang, Auteur ; Min Deng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 735 - 754 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Vedettes matières IGN] Géomatique
[Termes IGN] base de données routières
[Termes IGN] carrefour
[Termes IGN] carte routière
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] données routières
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] information sémantique
[Termes IGN] intégration de données
[Termes IGN] navigation automobile
[Termes IGN] vitesse
[Termes IGN] Wuhan (Chine)Résumé : (auteur) The road map is a fundamental part of a spatial data infrastructure (SDI), and is widely applied in navigation, smart transportation, and mobile location services. Recently, with the ubiquity of positioning devices, crowdsourced trajectories have become a significant data resource for road map construction and updating. However, existing trajectory-based methods mainly place emphasis on extracting road geometry features and may ignore continuous updating of road semantic information. Hence, we propose a divide-and-conquer method to construct a spatial-semantic road map by incorporating multiple data sources (e.g., crowdsourced trajectories and geo-tagged data). The proposed method divides road map construction into two sub-tasks, road structure reconstruction and road attributes inference. The road structure reconstruction process starts to partition raw trajectory data into different cliques of roadways and road intersections, and then extracts various targeted road structures by analyzing the turning modes in different trajectory cliques. The road attributes inference process aims to infer three pieces of crucial semantic information about road speeds, turning rules, and road names from crowdsourced trajectories and geo-tagged data. The case studies in Wuhan were examined to illustrate that the proposed method can construct a routable road map with enhanced geometric structures and rich semantic information, providing a beneficial data solution for car navigation and SDI update. Numéro de notice : A2022-364 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12879 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.1111/tgis.12879 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100583
in Transactions in GIS > vol 26 n° 2 (April 2022) . - pp 735 - 754[article]Modular multi-dimensional tool for emergency evacuation including location-based social network data / Ilil Blum Shem-Tov in Journal of location-based services, vol 16 n° 1 (March 2022)
[article]
Titre : Modular multi-dimensional tool for emergency evacuation including location-based social network data Type de document : Article/Communication Auteurs : Ilil Blum Shem-Tov, Auteur ; Shlomo Bekhor, Auteur Année de publication : 2022 Article en page(s) : pp 54 - 75 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] distribution spatiale
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] origine - destination
[Termes IGN] réseau social géodépendant
[Termes IGN] secours d'urgence
[Termes IGN] téléphone intelligentRésumé : (auteur) This paper presents the concept of a modular multi-dimensional tool (MMDT) for evacuation planning models. The goal of MMDT is to propose alternative route and destination locations that can be evaluated and compared to one another. The proposed tool can represent a very large number of scenarios and its strength is in its modularity and efficiency. The MMDT can be applied using both conventional evacuation models and decentralised personalised evacuation models based on Location-Based Social Networks (LBSN) to reduce overall evacuation times. Large-scale test cases using anonymous LBSN data illustrate the MMDT on several scenarios. Results indicate a significant reduction in evacuation times when using decentralised personal evacuation. Numéro de notice : A2022-389 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17489725.2021.1990422 Date de publication en ligne : 16/11/2021 En ligne : https://doi.org/10.1080/17489725.2021.1990422 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100679
in Journal of location-based services > vol 16 n° 1 (March 2022) . - pp 54 - 75[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)
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Titre : Discovering transition patterns among OpenStreetMap feature classes based on the Louvain method Type de document : Article/Communication Auteurs : Yijiang Zhao, Auteur ; Wentao Yang, Auteur ; Yizhi Liu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 236 - 258 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] Açores, archipel des
[Termes IGN] algorithme glouton
[Termes IGN] données localisées des bénévoles
[Termes IGN] étiquette
[Termes IGN] géobalise
[Termes IGN] Indiana (Etats-Unis)
[Termes IGN] OpenStreetMap
[Termes IGN] réseau routierRésumé : (auteur) Numerous studies have shown that OpenStreetMap (OSM) data can achieve high positional quality. However, the thematic attributes of OSM objects can be modified several times, which has a large impact on semantic heterogeneity. Identifying transition patterns within OSM feature classes is an important preliminary step for the tag recommendation algorithm, which can reduce the number of modifications and enhance the efficiency of OSM data updates. In this article, we propose an approach for discovering transition patterns among OSM feature classes. We first produced the transition matrix of feature classes and then developed a graph. Next, the Louvain method for community detection was utilized to cluster the feature classes. OSM data from Indiana, USA, and the Azores, Portugal, were used for our experiments. Some transition patterns were discovered: (1) many feature classes with the most transitions are the same in both datasets and most transitions occur in road-related feature classes; (2) people tend to tag general classes if they are unsure of the specific classes of tagged objects; and (3) most class transitions occurred as a result of volunteers improving the specificity and precision of feature classes. Moreover, consistently confusing concept pairs were identified. Numéro de notice : A2022-178 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12843 Date de publication en ligne : 08/10/2021 En ligne : https://doi.org/10.1111/tgis.12843 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99835
in Transactions in GIS > vol 26 n° 1 (February 2022) . - pp 236 - 258[article]GazPNE: 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)PermalinkNovel model for predicting individuals’ movements in dynamic regions of interest / Xiaoqi Shen in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkAnnotation sémantique pour la géolocalisation d'entités spatiales dans des tweets / Gaëtan Caillaut (2022)PermalinkAutomated construction of a French Entity Linking dataset to geolocate social network posts in the context of natural disasters / Gaëtan Caillaut (2022)PermalinkCIME: Context-aware geolocation of emergency-related posts / Gabriele Scalia in Geoinformatica, vol 26 n° 1 (January 2022)PermalinkContextual location recommendation for location-based social networks by learning user intentions and contextual triggers / Seyyed Mohammadreza Rahimi in Geoinformatica, vol 26 n° 1 (January 2022)PermalinkGenerating geographical location descriptions with spatial templates: a salient toponym driven approach / Mark M. Hall in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)PermalinkA semantics-based trajectory segmentation simplification method / Minshi Liu in Journal of Geovisualization and Spatial Analysis, vol 5 n° 2 (December 2021)PermalinkAnalytics of location-based big data for smart cities: Opportunities, challenges, and future directions / Haosheng Huang in Computers, Environment and Urban Systems, vol 90 (November 2021)PermalinkPoint-of-interest (POI) data validation methods: An urban case study / Lih Wei Yeow in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)Permalink