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A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena / Guiming Zhang in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 33 n° 9 (September 2019) . - pp 1873 - 1893 Titre : A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena Type de document : Article/Communication Auteurs : Guiming Zhang, Auteur ; A - Xing Zhu, Auteur Année de publication : 2019 Article en page(s) : pp 1873 - 1893 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] carte thématique [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] échantillon [Termes descripteurs IGN] erreur d'échantillon [Termes descripteurs IGN] erreur de positionnement [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] habitat (nature) [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] oiseau [Termes descripteurs IGN] phénomène géographique [Termes descripteurs IGN] pondération [Termes descripteurs IGN] précision de localisation [Termes descripteurs IGN] régression logistique [Termes descripteurs IGN] representativité [Termes descripteurs IGN] science citoyenne [Termes descripteurs IGN] Wisconsin (Etats-Unis) Résumé : (auteur) Volunteered geographic information (VGI) contains valuable field observations that represent the spatial distribution of geographic phenomena. As such, it has the potential to provide regularly updated low-cost field samples for predictively mapping the spatial variations of geographic phenomena. The predictive mapping of geographic phenomena often requires representative samples for high mapping accuracy, but samples consisting of VGI observations are often not representative as they concentrate on specific geographic areas (i.e. spatial bias) due to the opportunistic nature of voluntary observation efforts. In this article, we propose a representativeness-directed approach to mitigate spatial bias in VGI for predictive mapping. The proposed approach defines and quantifies sample representativeness by comparing the probability distributions of sample locations and the mapping area in the environmental covariate space. Spatial bias is mitigated by weighting the sample locations to maximize their representativeness. The approach is evaluated using species habit suitability mapping as a case study. The results show that the accuracy of predictive mapping using weighted sample locations is higher than using unweighted sample locations. A positive relationship between sample representativeness and mapping accuracy is also observed, suggesting that sample representativeness is a valid indicator of predictive mapping accuracy. This approach mitigates spatial bias in VGI to improve predictive mapping accuracy. Numéro de notice : A2019-392 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1615071 date de publication en ligne : 10/05/2019 En ligne : https://doi.org/10.1080/13658816.2019.1615071 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93490 [article]

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Improving the quality of cartographic colour reproduction using the self-organizing map method / Mingguang Wu in Cartographic journal (the), Vol 55 n° 3 (August 2018)  

Public [article]  inCartographic journal (the) > Vol 55 n° 3 (August 2018) . - pp 273 - 284 Titre : Improving the quality of cartographic colour reproduction using the self-organizing map method Type de document : Article/Communication Auteurs : Mingguang Wu, Auteur ; A - Xing Zhu, Auteur ; Li He, Auteur Année de publication : 2018 Article en page(s) : pp 273 - 284 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes descripteurs IGN] algorithme [Termes descripteurs IGN] carte de Kohonen [Termes descripteurs IGN] carte thématique [Termes descripteurs IGN] couleur (rédaction cartographique) [Termes descripteurs IGN] couleur imprimée [Termes descripteurs IGN] qualité cartographique [Termes descripteurs IGN] représentation cartographique Résumé : (Auteur) Colour distortion, which is caused by the unavoidable mismatch between a map’s gamut and a device’s gamut, negatively affects the semiotic quality of maps. Cartographic communication often suffers from undesirable colour inconsistency. This method models cartographic colour reproduction as a constrained transform problem, namely, adapting a map’s gamut to fit a device’s gamut while preserving the semiotic quality. First, the characteristics of the map’s gamut are investigated by considering cartographic principles, and the fundamental concerns of preserving semiotic quality are proposed. Then, the self-organizing map method is introduced to iteratively optimize the cartographic colour reproduction. We implement this method and evaluate it based on a series of thematic maps. The results indicate that the proposed algorithm offers better results than two alternatives in terms of facilitating cartographic colour reproduction. Numéro de notice : A2018-519 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00087041.2017.1414106 date de publication en ligne : 18/10/2018 En ligne : https://doi.org/10.1080/00087041.2017.1414106 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91325 [article]

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Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information / Yongzhi Wang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 146 - 153 Titre : Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information Type de document : Article/Communication Auteurs : Yongzhi Wang, Auteur ; Yuqing Ma, Auteur ; A - Xing Zhu, Auteur ; Hui Zhao, Auteur ; Lixia Liao, Auteur Année de publication : 2018 Article en page(s) : pp 146 - 153 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] façade [Termes descripteurs IGN] image optique [Termes descripteurs IGN] semis de points Résumé : (Auteur) Facade features represent segmentations of building surfaces and can serve as a building framework. Extracting facade features from three-dimensional (3D) point cloud data (3D PCD) is an efficient method for 3D building modeling. By combining the advantages of 3D PCD and two-dimensional optical images, this study describes the creation of a highly accurate building facade feature extraction method from 3D PCD with a focus on structural information. The new extraction method involves three major steps: image feature extraction, exploration of the mapping method between the image features and 3D PCD, and optimization of the initial 3D PCD facade features considering structural information. Results show that the new method can extract the 3D PCD facade features of buildings more accurately and continuously. The new method is validated using a case study. In addition, the effectiveness of the new method is demonstrated by comparing it with the range image-extraction method and the optical image-extraction method in the absence of structural information. The 3D PCD facade features extracted by the new method can be applied in many fields, such as 3D building modeling and building information modeling. Numéro de notice : A2018-113 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.11.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.11.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89543 [article]

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Validity of historical volunteered geographic information: Evaluating citizen data for mapping historical geographic phenomena / Guiming Zhang in Transactions in GIS, vol 22 n° 1 (February 2018)  

Public [article]  inTransactions in GIS > vol 22 n° 1 (February 2018) . - pp 149 - 164 Titre : Validity of historical volunteered geographic information: Evaluating citizen data for mapping historical geographic phenomena Type de document : Article/Communication Auteurs : Guiming Zhang, Auteur ; A - Xing Zhu, Auteur ; Zhi‐Pang Huang, Auteur ; Guopeng Ren, Auteur ; Cheng‐Zhi Qin, Auteur ; Wen Xiao, Auteur Année de publication : 2018 Article en page(s) : pp 149 - 164 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes descripteurs IGN] cartographie historique [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] habitat animal [Termes descripteurs IGN] phénomène géographique [Termes descripteurs IGN] singe [Termes descripteurs IGN] validité des données [Termes descripteurs IGN] Yunnan (Chine) Résumé : (auteur) Studies on volunteered geographic information (VGI) have focused on examining its validity to reveal geographic phenomena in relatively recent periods. Empirical evaluation of the validity of VGI to reveal geographic phenomena in historical periods (e.g., decades ago) is lacking, although such evaluation is desirable for assessing the possibility of broadening the temporal scope of VGI applications. This article presents an evaluation of the validity of VGI to reveal historical geographic phenomena through a citizen data‐based habitat suitability mapping case study. Citizen data (i.e., sightings) of the black‐and‐white snub‐nosed monkey (Rhinopithecus bieti) were elicited from local residents through three‐dimensional (3D) geovisualization interviews in Yunnan, China. The validity of the elicited sightings to reveal the historical R. bieti distribution was evaluated through habitat suitability mapping using the citizen data in historical periods. The results of controlled experiments demonstrated that suitability maps predicted using the historical citizen data had a consistent spatial pattern (correlation above 0.60) that reflects the R. bieti distribution (Boyce index around 0.90) in areas free of significant environmental change across historical periods. This in turn suggests that citizen data have validity for mapping historical geographic phenomena. It provides supporting empirical evidence for potentially broadening the temporal scope of VGI applications. Numéro de notice : A2018-066 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12300 En ligne : https://doi.org/10.1111/tgis.12300 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89422 [article]

A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data / Guiming Zhang in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 9-10 (September - October 2017) . - pp 2068 - 2097 Titre : A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data Type de document : Article/Communication Auteurs : Guiming Zhang, Auteur ; A - Xing Zhu, Auteur ; Qunying Huang, Auteur Année de publication : 2017 Article en page(s) : pp 2068 - 2097 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] données massives [Termes descripteurs IGN] estimation par noyau [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] optimisation (mathématiques) [Termes descripteurs IGN] processeur graphique Résumé : (Auteur) Kernel density estimation (KDE) is a classic approach for spatial point pattern analysis. In many applications, KDE with spatially adaptive bandwidths (adaptive KDE) is preferred over KDE with an invariant bandwidth (fixed KDE). However, bandwidths determination for adaptive KDE is extremely computationally intensive, particularly for point pattern analysis tasks of large problem sizes. This computational challenge impedes the application of adaptive KDE to analyze large point data sets, which are common in this big data era. This article presents a graphics processing units (GPUs)-accelerated adaptive KDE algorithm for efficient spatial point pattern analysis on spatial big data. First, optimizations were designed to reduce the algorithmic complexity of the bandwidth determination algorithm for adaptive KDE. The massively parallel computing resources on GPU were then exploited to further speed up the optimized algorithm. Experimental results demonstrated that the proposed optimizations effectively improved the performance by a factor of tens. Compared to the sequential algorithm and an Open Multiprocessing (OpenMP)-based algorithm leveraging multiple central processing unit cores for adaptive KDE, the GPU-enabled algorithm accelerated point pattern analysis tasks by a factor of hundreds and tens, respectively. Additionally, the GPU-accelerated adaptive KDE algorithm scales reasonably well while increasing the size of data sets. Given the significant acceleration brought by the GPU-enabled adaptive KDE algorithm, point pattern analysis with the adaptive KDE approach on large point data sets can be performed efficiently. Point pattern analysis on spatial big data, computationally prohibitive with the sequential algorithm, can be conducted routinely with the GPU-accelerated algorithm. The GPU-accelerated adaptive KDE approach contributes to the geospatial computational toolbox that facilitates geographic knowledge discovery from spatial big data. Numéro de notice : A2017-509 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1324975 En ligne : http://dx.doi.org/10.1080/13658816.2017.1324975 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86455 [article]

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Enabling point pattern analysis on spatial big data using cloud computing: optimizing and accelerating Ripley’s K function / Guiming Zhang in International journal of geographical information science IJGIS, vol 30 n° 11-12 (November - December 2016)  

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vol 27 n° 7-8 - july - august 2013 - Digital terrain analysis and modelling [Suivi de] Geological applications of digital terrain analysis (Bulletin de International journal of geographical information science IJGIS) / Qiming Zhou

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

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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)

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An experiment using a circular neighborhood to calculate slope gradient from a DEM / X. Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 2 (February 2007)

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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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Knowledge discovery from soil maps using inductive learning / F. Qi in International journal of geographical information science IJGIS, vol 17 n° 8 (december 2003)

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