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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]

Using geographically weighted regression kriging for crop yield mapping in West Africa / Muhammad Imran 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 234 - 257 Titre : Using geographically weighted regression kriging for crop yield mapping in West Africa Type de document : Article/Communication Auteurs : Muhammad Imran, Auteur ; Alfred Stein, Auteur ; Raul Zurita-Milla, Auteur Année de publication : 2015 Article en page(s) : pp 234 - 257 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] agriculture [Termes IGN] analyse de données [Termes IGN] Burkina Faso [Termes IGN] carte agricole [Termes IGN] cartographie statistique [Termes IGN] image SPOT-Végétation [Termes IGN] krigeage [Termes IGN] régression géographiquement pondérée [Termes IGN] rendement agricole [Termes IGN] sorgho (céréale) Résumé : (Auteur) Geographical information systems support the application of statistical techniques to map spatially referenced crop data. To do this in the optimal way, errors and uncertainties have to be minimized that are often associated with operations on the data. This paper applies a spatial statistical approach to upscale crop yields from the field level toward the scale of Burkina Faso. Observed yields were related to the Normalized Difference Vegetation Index derived from SPOT-VEGETATION. The objective was to quantify the uncertainties at the subsequent steps. First, we applied a point pattern analysis to examine uncertainties due to the sampling network of field surveys in the country. Second, geographically weighted regression kriging (GWRK) was applied to upscale the yield observations and to quantify the corresponding uncertainty. The proposed method was demonstrated with the mapping of sorghum yields in Burkina Faso and results were compared with those from regression kriging (RK) and kriging with external drift using a local kriging neighborhood (KEDLN). The proposed method was validated with independent yield observations obtained from field surveys. We observed that the lower uncertainty range value increased by 39%, and the upper uncertainty range value decreased by 51%, when comparing GWRK with RK and KEDLN. Moreover, GWRK reduced the prediction error variance as compared to RK (20 vs. 31) and to KEDLN (20 vs. 39). We found that climate and topography had a major impact on the country’s sorghum yields. Further, the financial ability of farmers influenced the crop management and, thus, the sorghum crop yields. We concluded that GWRK effectively utilized information present in the covariate datasets and improved the accuracies of both the regional-scale mapping of sorghum yields and was able to quantify the associated uncertainty. Numéro de notice : A2015-578 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.959522 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.959522 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77840 [article]

Geo-located community detection in Twitter with enhanced fast-greedy optimization of modularity: the case study of typhoon Haiyan / Mohamed Bakillah 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 258 - 279 Titre : Geo-located community detection in Twitter with enhanced fast-greedy optimization of modularity: the case study of typhoon Haiyan Type de document : Article/Communication Auteurs : Mohamed Bakillah, Auteur ; Ren-Yu Li, Auteur ; Steve H.L. Liang, Auteur Année de publication : 2015 Article en page(s) : pp 258 - 279 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] communauté virtuelle [Termes IGN] données issues des réseaux sociaux [Termes IGN] exploration de données géographiques [Termes IGN] géopositionnement [Termes IGN] risque naturel [Termes IGN] Twitter Résumé : (Auteur) As they increase in popularity, social media are regarded as important sources of information on geographical phenomena. Studies have also shown that people rely on social media to communicate during disasters and emergency situation, and that the exchanged messages can be used to get an insight into the situation. Spatial data mining techniques are one way to extract relevant information from social media. In this article, our aim is to contribute to this field by investigating how graph clustering can be applied to support the detection of geo-located communities in Twitter in disaster situations. For this purpose, we have enhanced the fast-greedy optimization of modularity (FGM) clustering algorithm with semantic similarity so that it can deal with the complex social graphs extracted from Twitter. Then, we have coupled the enhanced FGM with the varied density-based spatial clustering of applications with noise spatial clustering algorithm to obtain spatial clusters at different temporal snapshots. The method was experimented with a case study on typhoon Haiyan in the Philippines, and Twitter’s different interaction modes were compared to create the graph of users and to detect communities. The experiments show that communities that are relevant to identify areas where disaster-related incidents were reported can be extracted, and that the enhanced algorithm outperforms the generic one in this task. Numéro de notice : A2015-579 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.964247 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.964247 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77841 [article]

Rank-based strategies for cleaning inconsistent spatial databases / Nieves R. Brisaboa 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 280 - 304 Titre : Rank-based strategies for cleaning inconsistent spatial databases Type de document : Article/Communication Auteurs : Nieves R. Brisaboa, Auteur ; M. Andrea Rodríguez, Auteur ; Diego Seco, Auteur Année de publication : 2015 Article en page(s) : pp 280 - 304 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] cohérence des données [Termes IGN] contrainte d'intégrité [Termes IGN] données massives [Termes IGN] efficacité [Termes IGN] intégrité topologique [Termes IGN] qualité des données [Termes IGN] relation topologique [Termes IGN] révision des données Résumé : (Auteur) A spatial data set is consistent if it satisfies a set of integrity constraints. Although consistency is a desirable property of databases, enforcing the satisfaction of integrity constraints might not be always feasible. In such cases, the presence of inconsistent data may have a negative effect on the results of data analysis and processing and, in consequence, there is an important need for data-cleaning tools to detect and remove, if possible, inconsistencies in large data sets. This work proposes strategies to support data cleaning of spatial databases with respect to a set of integrity constraints that impose topological relations between spatial objects. The basic idea is to rank the geometries in a spatial data set that should be modified to improve the quality of the data (in terms of consistency). An experimental evaluation validates the proposal and shows that the order in which geometries are modified affects both the overall quality of the database and the final number of geometries to be processed to restore consistency. Numéro de notice : A2015-580 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.965711 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.965711 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77842 [article]

The decision task complexity and information acquisition strategies in GIS-MCDA / Mohammadreza Jelokhani-Niaraki 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 327 - 344 Titre : The decision task complexity and information acquisition strategies in GIS-MCDA Type de document : Article/Communication Auteurs : Mohammadreza Jelokhani-Niaraki, Auteur ; Jacek Malczewski, Auteur Année de publication : 2015 Article en page(s) : pp 327 - 344 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] acquisition de données [Termes IGN] analyse multicritère [Termes IGN] complexité [Termes IGN] outil d'aide à la décision [Termes IGN] Téhéran Résumé : (Auteur) This paper addresses the research question of how does the complexity of a decision task affect information acquisition strategies used by decision-makers in a GIS-based multicriteria decision analysis (MCDA)? It reports the results of an experimental study that investigated the effect of task complexity (information load) on information acquisition strategies in the use of a multicriteria spatial decision support system (MC-SDSS). The experiment involved the use of the MC-SDSS for online parking site selection (ranking) in District # 22 of Tehran, Iran at four levels of complexity. The complexity of the site selection task was manipulated in terms of the number of: (1) decision alternatives available to decision-makers and (2) the evaluation criteria (attributes) used to describe the alternatives. At each level of task complexity, the site selection process was carried out in two GIS-MCDA modes: individual and group (collaborative) modes. The findings demonstrate that: (1) an increase in task complexity tend to result in the use of non-compensatory decision strategies; (2) decision-makers using compensatory strategies spend more time acquiring information from decision tables than maps, and (3) the task complexity has no impact on the interaction between the map and table uses. Numéro de notice : A2015-581 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.947614 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.947614 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77843 [article]