Détail de l'auteur
Auteur A - Xing Zhu |
Documents disponibles écrits par cet auteur



Predictive mapping with small field sample data using semi‐supervised machine learning / Fei Du in Transactions in GIS, Vol 24 n° 2 (April 2020)
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Titre : Predictive mapping with small field sample data using semi‐supervised machine learning Type de document : Article/Communication Auteurs : Fei Du, Auteur ; A - Xing Zhu, Auteur ; Jing Liu, Auteur ; Lin Yang, Auteur Année de publication : 2020 Article en page(s) : pp 315 - 331 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] apprentissage semi-dirigé
[Termes descripteurs IGN] covariance
[Termes descripteurs IGN] échantillon
[Termes descripteurs IGN] modèle de simulation
[Termes descripteurs IGN] représentation cartographiqueRésumé : (Auteur) Existing predictive mapping methods usually require a large number of field samples with good representativeness as input to build reliable predictive models. In mapping practice, however, we often face situations when only small sample data are available. In this article, we present a semi‐supervised machine learning approach for predictive mapping in which the natural aggregation (clustering) patterns of environmental covariate data are used to supplement limited samples in prediction. This approach was applied to two soil mapping case studies. Compared with field sample only approaches (decision trees, logistic regression, and support vector machines), maps using the proposed approach can better capture the spatial variation of soil types and achieve higher accuracy with limited samples. A cross validation shows further that the proposed approach is less sensitive to the specific field sample set used and thus more robust when field sample data are small. Numéro de notice : A2020-174 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12598 date de publication en ligne : 04/12/2019 En ligne : https://doi.org/10.1111/tgis.12598 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94900
in Transactions in GIS > Vol 24 n° 2 (April 2020) . - pp 315 - 331[article]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)
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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 Affiliation des auteurs : non IGN 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
in International journal of geographical information science IJGIS > vol 33 n° 9 (September 2019) . - pp 1873 - 1893[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2019092 RAB Revue Centre de documentation En réserve 3L Disponible 079-2019091 SL Revue Centre de documentation Revues en salle Disponible 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)
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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 cartographiqueRésumé : (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 Affiliation des auteurs : non IGN 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
in Cartographic journal (the) > Vol 55 n° 3 (August 2018) . - pp 273 - 284[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 030-2018031 SL Revue Centre de documentation Revues en salle Disponible 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)
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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 pointsRésumé : (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 Affiliation des auteurs : non IGN 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
in ISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 146 - 153[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018051 RAB Revue Centre de documentation En réserve 3L Disponible 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)
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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 Affiliation des auteurs : non IGN 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
in Transactions in GIS > vol 22 n° 1 (February 2018) . - pp 149 - 164[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)
PermalinkEnabling 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)
Permalinkvol 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
PermalinkKnowledge discovery from area-class resource maps: capturing prototype effects / F. Qi in Cartography and Geographic Information Science, vol 35 n° 4 (October 2008)
PermalinkAn 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)
PermalinkAn 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)
PermalinkA 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)
PermalinkKnowledge 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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