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Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization / Si Song in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 1-2 (January - February 2019) . - pp 134 - 154 Titre : Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization Type de document : Article/Communication Auteurs : Si Song, Auteur ; Tao Pei, Auteur ; Ting Ma, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 134 - 154 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] données localisées [Termes IGN] migration pendulaire [Termes IGN] modèle statistique [Termes IGN] optimisation par colonie de fourmis [Termes IGN] origine - destination Mots-clés libres : logarithme du rapport de vraisemblance  log likelihood ratio (LLR) Résumé : (auteur) An origin-destination (OD) flow can be defined as the movement of objects between two locations. These movements must be determined for a range of purposes, and strong interactions can be visually represented via clustering of OD flows. Identification of such clusters may be useful in urban planning, traffic planning and logistics management research. However, few methods can identify arbitrarily shaped flow clusters. Here, we present a spatial scan statistical approach based on ant colony optimization (ACO) for detecting arbitrarily shaped clusters of OD flows (AntScan_flow). In this study, an OD flow cluster is defined as a regional pair with significant log likelihood ratio (LLR), and the ACO is employed to detect the clusters with maximum LLRs in the search space. Simulation experiments based on AntScan_flow and SaTScan_flow show that AntScan_flow yields better performance based on accuracy but requires a large computational demand. Finally, a case study of the morning commuting flows of Beijing residents was conducted. The AntScan_flow results show that the regions associated with moderate- and long-distance commuting OD flow clusters are highly consistent with subway lines and highways in the city. Additionally, the regions of short-distance commuting OD flow clusters are more likely to exhibit ‘residential-area to work-area’ patterns. Numéro de notice : A2019-019 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1516287 Date de publication en ligne : 10/09/2018 En ligne : https://doi.org/10.1080/13658816.2018.1516287 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91684 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2019011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records / Zhang Liu in Transactions in GIS, vol 22 n° 2 (April 2018)  

Public [article]  inTransactions in GIS > vol 22 n° 2 (April 2018) . - pp 494 - 513 Titre : Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records Type de document : Article/Communication Auteurs : Zhang Liu, Auteur ; Ting Ma, Auteur ; Yunyan Du, Auteur ; Tao Pei, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 494 - 513 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] carte thématique [Termes IGN] cartographie des flux [Termes IGN] classification par réseau neuronal [Termes IGN] mobilité urbaine [Termes IGN] population urbaine [Termes IGN] régression [Termes IGN] téléphone intelligent [Termes IGN] trace numérique [Termes IGN] trajet (mobilité) Résumé : (Auteur) Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation. Numéro de notice : A2018-215 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12323 Date de publication en ligne : 26/02/2018 En ligne : https://doi.org/10.1111/tgis.12323 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90006 [article]

Density-based clustering for data containing two types of points / Tao Pei in International journal of geographical information science IJGIS, vol 29 n° 2 (February 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 2 (February 2015) . - pp 175 - 193 Titre : Density-based clustering for data containing two types of points Type de document : Article/Communication Auteurs : Tao Pei, Auteur ; Weiyi Wang, Auteur ; Hengcai Zhang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 175 - 193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse en composantes indépendantes [Termes IGN] classification par seuillage sur la limite la plus proche [Termes IGN] densité d'information [Termes IGN] échelle d'intensité [Termes IGN] groupe [Termes IGN] taxi [Termes IGN] transport routier Résumé : (Auteur) When only one type of point is distributed in a region, clustered points can be seen as an anomaly. When two different types of points coexist in a region, they overlap at different places with various densities. In such cases, the meaning of a cluster of one type of point may be altered if points of the other type show different densities within the same cluster. If we consider the origins and destinations (OD) of taxicab trips, the clustering of both in the morning may indicate a transportation hub, whereas clustered origins and sparse destinations (a hot spot where taxis are in short supply) could suggest a densely populated residential area. This cannot be identified by previous clustering methods, so it is worthwhile studying a clustering method for two types of points. The concept of two-component clustering is first defined in this paper as a group containing two types of points, at least one of which exhibits clustering. We then propose a density-based method for identifying two-component clusters. The method is divided into four steps. The first estimates the clustering scale of the point data. The second transforms the point data into the 2D density domain, where the x and y axes represent the local density of each type of point around each point, respectively. The third determines the thresholds for extracting the clusters, and the fourth generates two-component clusters using a density-connectivity mechanism. The method is applied to taxicab trip data in Beijing. Three types of two-component clusters are identified: high-density origins and destinations, high-density origins and low-density destinations, and low-density origins and high-density destinations. The clustering results are verified by the spatial relationship between the cluster locations and their land-use types over different periods of the day. Numéro de notice : A2015-577 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.955027 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.955027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77839 [article]

Knowledge discovery from area-class resource maps: capturing prototype effects / F. Qi in Cartography and Geographic Information Science, vol 35 n° 4 (October 2008)  

Public [article]  inCartography and Geographic Information Science > vol 35 n° 4 (October 2008) . - pp 223 - 237 Titre : Knowledge discovery from area-class resource maps: capturing prototype effects Type de document : Article/Communication Auteurs : F. Qi, Auteur ; A - Xing Zhu, Auteur ; Tao Pei, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 223 - 237 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] classification à base de connaissances [Termes IGN] exploration de données [Termes IGN] extraction de données [Termes IGN] objet géographique [Termes IGN] outil de découverte de connaissances Résumé : (Auteur) This paper presents a knowledge discovery approach to extracting knowledge from area-class resource maps. Prototype theory forms the basis of the approach which consists of two major components: (1) a scheme for organizing knowledge used in categorizing geographic entities which allows for the modeling of indeterminate boundaries and non-uniform memberships within categories; and (2) a data mining method using the Expectation Maximization (EM) algorithm for extracting such knowledge from area-class maps. A case study on knowledge discovery from a soil map demonstrates the details of the approach. The study shows that knowledge for classifying geographic entities with indeterminate boundaries is embedded in area-class maps and can be extracted through data mining; and that continuous spatial variation of geographic entities can be better modeled if the knowledge discovery process retains knowledge of within-class variations as well as transitions between classes. Copyright CaGISociety Numéro de notice : A2008-437 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1559/152304008786140533 En ligne : https://doi.org/10.1559/152304008786140533 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29506 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-08041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

An adaptive approach to selecting a flow-partition exponent for a multiple-flow-direction algorithm / C. Qin in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 21 n° 3-4 (march - april 2007) . - pp 443 - 458 Titre : An adaptive approach to selecting a flow-partition exponent for a multiple-flow-direction algorithm Type de document : Article/Communication Auteurs : C. Qin, Auteur ; A - Xing Zhu, Auteur ; Tao Pei, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 443 - 458 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] bassin hydrographique [Termes IGN] Chine [Termes IGN] flux [Termes IGN] modèle numérique de surface [Termes IGN] partition de surface [Termes IGN] système d'information géographique Résumé : (Auteur) Most multiple-flow-direction algorithms (MFDs) use a flow-partition coefficient (exponent) to determine the fractions draining to all downslope neighbours. The commonly used MFD often employs a fixed exponent over an entire watershed. The fixed coefficient strategy cannot effectively model the impact of local terrain conditions on the dispersion of local flow. This paper addresses this problem based on the idea that dispersion of local flow varies over space due to the spatial variation of local terrain conditions. Thus, the flow-partition exponent of an MFD should also vary over space. We present an adaptive approach for determining the flow-partition exponent based on local topographic attribute which controls local flow partitioning. In our approach, the influence of local terrain on flow partition is modelled by a flow-partition function which is based on local maximum downslope gradient (we refer to this approach as MFD based on maximum downslope gradient, MFD-md for short). With this new approach, a steep terrain which induces a convergent flow condition can be modelled using a large value for the flow-partition exponent. Similarly, a gentle terrain can be modelled using a small value for the flow-partition exponent. MFD-md is quantitatively evaluated using four types of mathematical surfaces and their theoretical 'true' value of Specific Catchment Area (SCA). The Root Mean Square Error (RMSE) shows that the error of SCA computed by MFD-md is lower than that of SCA computed by the widely used SFD and MFD algorithms. Application of the new approach using a real DEM of a watershed in Northeast China shows that the flow accumulation computed by MFD-md is better adapted to terrain conditions based on visual judgement. Copyright Taylor & Francis Numéro de notice : A2007-120 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810601073240 En ligne : https://doi.org/10.1080/13658810601073240 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28483 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-07021	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-07022	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A new approach to the nearest-neighbour method to discover cluster features in overlaid spatial point processes / Tao Pei in International journal of geographical information science IJGIS, vol 20 n° 2 (february 2006)  

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