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Discovering co-location patterns in multivariate spatial flow data / Jiannan Cai in International journal of geographical information science IJGIS, vol 36 n° 4 (April 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 4 (April 2022) . - pp 720 - 748 Titre : Discovering co-location patterns in multivariate spatial flow data Type de document : Article/Communication Auteurs : Jiannan Cai, Auteur ; Mei-Po Kwan, Auteur Année de publication : 2022 Article en page(s) : pp 720 - 748 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse bivariée [Termes IGN] analyse de groupement [Termes IGN] analyse univariée [Termes IGN] autocorrélation spatiale [Termes IGN] Chicago (Illinois) [Termes IGN] co-positionnement [Termes IGN] données de flux [Termes IGN] données socio-économiques [Termes IGN] dynamique spatiale [Termes IGN] enquête [Termes IGN] exploration de données géographiques [Termes IGN] migration pendulaire [Termes IGN] origine - destination [Termes IGN] voisinage (relation topologique) Résumé : (auteur) Spatial flow co-location patterns (FCLPs) are important for understanding the spatial dynamics and associations of movements. However, conventional point-based co-location pattern discovery methods ignore spatial movements between locations and thus may generate erroneous findings when applied to spatial flows. Despite recent advances, there is still a lack of methods for analyzing multivariate flows. To bridge the gap, this paper formulates a novel problem of FCLP discovery and presents an effective detection method based on frequent-pattern mining and spatial statistics. We first define a flow co-location index to quantify the co-location frequency of different features in flow neighborhoods, and then employ a bottom-up method to discover all frequent FCLPs. To further establish the statistical significance of the results, we develop a flow pattern reconstruction method to model the benchmark null hypothesis of independence conditioning on univariate flow characteristics (e.g. flow autocorrelation). Synthetic experiments with predefined FCLPs verify the advantages of our method in terms of correctness over available alternatives. A case study using individual home-work commuting flow data in the Chicago Metropolitan Area demonstrates that residence- or workplace-based co-location patterns tend to overestimate the co-location frequency of people with different occupations and could lead to inconsistent results. Numéro de notice : A2022-256 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1980217 Date de publication en ligne : 20/09/2021 En ligne : https://doi.org/10.1080/13658816.2021.1980217 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100229 [article]

Mapping trajectories and flows: facilitating a human-centered approach to movement data analytics / Somayeh Dodge in Cartography and Geographic Information Science, vol 48 n° 4 (July 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 4 (July 2021) . - pp 353 - 375 Titre : Mapping trajectories and flows: facilitating a human-centered approach to movement data analytics Type de document : Article/Communication Auteurs : Somayeh Dodge, Auteur ; Evgeny Noi, Auteur Année de publication : 2021 Article en page(s) : pp 353 - 375 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse visuelle [Termes IGN] données de flux [Termes IGN] interaction humain-espace [Termes IGN] origine - destination [Termes IGN] trajectoire (véhicule non spatial) [Termes IGN] trajet (mobilité) [Termes IGN] visualisation cartographique [Vedettes matières IGN] Géovisualisation Résumé : (auteur) This paper argues for a “human-centered” approach to knowledge discovery from movement data through the use of visualization and mapping. As movement data becomes more available and diverse in dimension and resolution, mapping becomes particularly important in the exploratory analysis of movement trajectories and for capturing patterns and structures in large origin-destination flow data sets. Movement phenomena (e.g. ranging from micro-movements of humans and animals to macro-level mobility, to migration flows, to spread of viruses) are complex dynamic processes which are realized in a multidimensional location-time-context space. This paper provides a comprehensive overview of various visualization techniques for mapping movement through the lens of cartography and with a special focus on the “human user” (e.g. data scientist, analyst, domain expert, etc.). We systematically characterize and categorize available techniques based on their visual specifications and functional capacities for human control, map-interaction, and design flexibility. These elements are beneficial to enhance the user’s capacities for map reasoning and knowledge discovery. Trends and gaps in the literature on movement visualization over the past 10 years are discussed. Our review suggests that future research should focus more on the role of the “human” in the development of human-centered visual analytic and exploratory tools, while providing functionalities for mapping uncertainty and protecting individual privacy in knowledge discovery of movement. These tools should be guided by a cartographic framework and visual principles specifically pertinent to movement. Numéro de notice : A2021-446 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1913763 Date de publication en ligne : 21/05/2021 En ligne : https://doi.org/10.1080/15230406.2021.1913763 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97853 [article]

Exemplaires(1)

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The role of net ecosystem productivity and of inventories in climate change research: the need for “net ecosystem productivity with harvest”, NEPH / E.D. Schulze in Forest ecosystems, vol 8 (2021)  

Public [article]  inForest ecosystems > vol 8 (2021) . - n° 15 (2021) Titre : The role of net ecosystem productivity and of inventories in climate change research: the need for “net ecosystem productivity with harvest”, NEPH Type de document : Article/Communication Auteurs : E.D. Schulze, Auteur ; Riccardo Valentini, Auteur ; Olivier Bouriaud , Auteur Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : n° 15 (2021) Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bilan du carbone [Termes IGN] calcul de flux [Termes IGN] changement climatique [Termes IGN] données de flux [Termes IGN] écosystème forestier [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] productivité biologique [Termes IGN] puits de carbone [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Background : There is an urgent need for quantifying the terrestrial carbon sink in the context of global carbon emissions. However, neither the flux measurements, nor the national wood balances fulfil this purpose. In this discussion article we point at various shortcomings and necessary improvements of these approaches in order to achieve a true quantification of the carbon exchange of land surfaces. Results : We discuss the necessity of incorporating all lateral fluxes, but mainly the export of biomass by harvest, into the flux balance and to recognize feedbacks between management and fluxes to make flux measurements compatible with inventories. At the same time, we discuss the necessity that national reports of wood use need to fully recognize the use of wood for energy use. Both approaches of establishing an ecosystem carbon balance, fluxes and inventories, have shortcomings. Conclusions : Including harvest and feedbacks by management appears to be the main requirement for the flux approach. A better quantification of wood use for bioenergy seems a real need for integrating the national wood balances into the global carbon cycle. Numéro de notice : A2021-497 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s40663-021-00294-z Date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.1186/s40663-021-00294-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97975 [article]

Impact of extreme weather events on urban human flow: A perspective from location-based service data / Zhenhua Chen in Computers, Environment and Urban Systems, vol 83 (September 2020)  

Public [article]  inComputers, Environment and Urban Systems > vol 83 (September 2020) . - n° 101520 Titre : Impact of extreme weather events on urban human flow: A perspective from location-based service data Type de document : Article/Communication Auteurs : Zhenhua Chen, Auteur ; Zhaoya Gong, Auteur ; Yang Shan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 101520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cyclone [Termes IGN] données de flux [Termes IGN] phénomène climatique extrême [Termes IGN] plan de déplacement urbain [Termes IGN] planification urbaine [Termes IGN] point d'intérêt [Termes IGN] population urbaine [Termes IGN] Shenzhen [Termes IGN] système d'information géographique Résumé : (auteur) This study investigates the impact of extreme weather events on urban human flow disruptions using location-based service data obtained from Baidu Map. Utilizing the 2018 Typhoon Mangkhut as an example, the spatial and temporal variations of urban human flow patterns in Shenzhen are examined using GIS and spatial flow analysis. In addition, the variation of human flow by different urban functions (e.g. transport, recreational, institutional, commercial and residential related facilities) is also examined through an integration of flow data and point-of-interest (POI) data. The study reveals that urban flow patterns varied substantially before, during, and after the typhoon. Specifically, urban flows were found to have reduced by 39% during the disruption. Conversely, 56% of flows increased immediately after the disruption. In terms of functional variation, the assessment reveals that fundamental urban functions, such as industrial (work) and institutional - (education) related trips experienced less disruption, whereas the typhoon event appears to have a relatively larger negative influence on recreational related trips. Overall, the study provides implications for planners and policy makers to enhance urban resilience to disasters through a better understanding of the urban vulnerability to disruptive events. Numéro de notice : A2020-699 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2020.101520 Date de publication en ligne : 07/07/2020 En ligne : https://doi.org/10.1016/j.compenvurbsys.2020.101520 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96253 [article]

An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data / Xiaogang Guo in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 2 (February 2020) Titre : An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data Type de document : Article/Communication Auteurs : Xiaogang Guo, Auteur ; Zhijie Xu, Auteur ; Jianqin Zhang, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] classification par nuées dynamiques [Termes IGN] distance euclidienne [Termes IGN] données de flux [Termes IGN] données vectorielles [Termes IGN] erreur moyenne quadratique [Termes IGN] origine - destination [Termes IGN] Pékin (Chine) [Termes IGN] regroupement de données [Termes IGN] taxi [Termes IGN] trafic routier [Termes IGN] zone urbaine Résumé : (auteur) Origin-destination (OD) flow pattern mining is an important research method of urban dynamics, in which OD flow clustering analysis discovers the activity patterns of urban residents and mine the coupling relationship of urban subspace and dynamic causes. The existing flow clustering methods are limited by the spatial constraints of OD points, rely on the spatial similarity of geographical points, and lack in-depth analysis of high-dimensional flow characteristics, and therefore it is difficult to find irregular flow clusters. In this paper, we propose an OD flow clustering method based on vector constraints (ODFCVC), which defines OD flow event point and OD flow vector to express the spatial location relationship and geometric flow behavior characteristics of OD flow. First, the OD flow vector coordinate system is normalized by the Euclidean distance-based OD flow event point spatial clustering, and then the OD flow clusters with similar flow patterns are mined using adjusted cosine similarity-based OD flow vector feature clustering. The transformation of OD data from point set space to vector space is realized by constraining the vector coordinate system and vector similarity through two-step clustering, which simplifies the calculation of high-dimensional similarity of OD flow and helps mining representative OD flow clusters in flow space. Due to the OD flow cluster property, the k-means algorithm is selected as the basic clustering logic in the two-step clustering method, and a sum of squared error perceptually important points algorithm considering silhouette coefficients (SSEPIP) is adopted to automatically extract the optimal cluster number without defining any parameters. Tested by origin-destination flow data in Beijing, China, new traffic flow communities based on traffic hubs are obtained by using the ODFCVC method, and irregular traffic flow clusters (including cluster mode, divergence mode, and convergence mode) with representative travel trends are found. Numéro de notice : A2020-114 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9020128 Date de publication en ligne : 22/02/2020 En ligne : https://doi.org/10.3390/ijgi9020128 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94720 [article]

Method for the analysis and visualization of similar flow hotspot patterns between different regional groups / Haiping Zhang in ISPRS International journal of geo-information, vol 7 n° 8 (August 2018)  

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Deep learning based vehicular mobility models for intelligent transportation systems / Jian Zhang (2018)  

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D'une cartographie de flux à une cartographie du mouvement : aspects sémiologiques / Françoise Bahoken in Cartes & Géomatique, n° 229-230 (septembre 2016 - février 2017)

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Contribution à la cartographie d’une matrice de flux / Françoise Bahoken (2016)  

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Développement d’un outil de webmapping pour l’optimisation de l’offre de soins en dialyse / Clémentine Chasles (2016) 

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Traçabilité d'une pollution dans le réseau d'assainissement de la ville de Lausanne / Frédéric Ducry in Géomatique suisse, vol 112 n° 10 (octobre 2014)

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Mapping large spatial flow data with hierarchical clustering / Xi Zhu in Transactions in GIS, vol 18 n° 3 (June 2014)  

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La construction d'une matrice de flux à partir de traces de téléphones portables / Françoise Bahoken in Cartes & Géomatique, n° 217 (septembre 2013)    

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