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Evaluating the impact of declining tsetse fly (Glossina pallidipes) habitat in the Zambezi valley of Zimbabwe / Farai Matawa in Geocarto international, vol 35 n° 12 ([01/09/2020])
[article]
Titre : Evaluating the impact of declining tsetse fly (Glossina pallidipes) habitat in the Zambezi valley of Zimbabwe Type de document : Article/Communication Auteurs : Farai Matawa, Auteur ; Amon Murwira, Auteur ; Peter M. Atkinson, Auteur Année de publication : 2020 Article en page(s) : pp 1373 - 1384 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] biodiversité
[Termes IGN] bovin
[Termes IGN] couvert végétal
[Termes IGN] diptère
[Termes IGN] distance
[Termes IGN] distribution spatiale
[Termes IGN] forêt tropicale
[Termes IGN] habitat d'espèce
[Termes IGN] maladie parasitaire
[Termes IGN] Zambèze (fleuve)
[Termes IGN] ZimbabweRésumé : (auteur) Tsetse flies transmit trypanosomes that cause Human African Trypanosomiasis (HAT) in humans and African Animal Trypanosomiasis (AAT) in animals. Understanding historical trends in the spatial distribution of tsetse fly habitat is necessary for planning vector control measures. The objectives of this study were (i) to test for evidence of any trends in suitable tsetse fly habitat and (ii) to test whether there is an association between trypanosomiasis detected from livestock sampled in dip tanks and local tsetse habitat in the project area. Results indicate a significant decreasing trend in the amount of suitable habitat. There is no significant correlation between trypanosomiasis prevalence rates in cattle and distance from patches of suitable tsetse habitat. The observed low trypanosomiasis prevalence and the lack of dependence on suitable tsetse fly habitat can be explained by the observed decreases in suitable tsetse habitat, which themselves are due to expansion of settlement and agriculture in North Western Zimbabwe. Numéro de notice : A2020-486 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576780 Date de publication en ligne : 21/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576780 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95653
in Geocarto international > vol 35 n° 12 [01/09/2020] . - pp 1373 - 1384[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)
[article]
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 géographiqueRésumé : (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
in Computers, Environment and Urban Systems > vol 83 (September 2020) . - n° 101520[article]A lightweight ensemble spatiotemporal interpolation model for geospatial data / Shifen Cheng in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)
[article]
Titre : A lightweight ensemble spatiotemporal interpolation model for geospatial data Type de document : Article/Communication Auteurs : Shifen Cheng, Auteur ; Peng Peng, Auteur ; Feng Lu, Auteur Année de publication : 2020 Article en page(s) : pp 1849 - 1872 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] coefficient de corrélation
[Termes IGN] distance pondérée
[Termes IGN] données localisées
[Termes IGN] erreur absolue
[Termes IGN] interpolation spatiale
[Termes IGN] lissage de données
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] requête spatiotemporelleRésumé : (auteur) Missing data is a common problem in the analysis of geospatial information. Existing methods introduce spatiotemporal dependencies to reduce imputing errors yet ignore ease of use in practice. Classical interpolation models are easy to build and apply; however, their imputation accuracy is limited due to their inability to capture spatiotemporal characteristics of geospatial data. Consequently, a lightweight ensemble model was constructed by modelling the spatiotemporal dependencies in a classical interpolation model. Temporally, the average correlation coefficients were introduced into a simple exponential smoothing model to automatically select the time window which ensured that the sample data had the strongest correlation to missing data. Spatially, the Gaussian equivalent and correlation distances were introduced in an inverse distance-weighting model, to assign weights to each spatial neighbor and sufficiently reflect changes in the spatiotemporal pattern. Finally, estimations of the missing values from temporal and spatial were aggregated into the final results with an extreme learning machine. Compared to existing models, the proposed model achieves higher imputation accuracy by lowering the mean absolute error by 10.93 to 52.48% in the road network dataset and by 23.35 to 72.18% in the air quality station dataset and exhibits robust performance in spatiotemporal mutations. Numéro de notice : A2020-484 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1725016 Date de publication en ligne : 12/02/2020 En ligne : https://doi.org/10.1080/13658816.2020.1725016 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95651
in International journal of geographical information science IJGIS > vol 34 n° 9 (September 2020) . - pp 1849 - 1872[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2020091 RAB Revue Centre de documentation En réserve L003 Disponible Measuring accessibility of bus system based on multi-source traffic data / Yufan Zuo in Geo-spatial Information Science, vol 23 n° 3 (September 2020)
[article]
Titre : Measuring accessibility of bus system based on multi-source traffic data Type de document : Article/Communication Auteurs : Yufan Zuo, Auteur ; Zhiyuan Liu, Auteur ; Xiao Fu, Auteur Année de publication : 2020 Article en page(s) : pp 248 - 257 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accessibilité
[Termes IGN] approche holistique
[Termes IGN] données multisources
[Termes IGN] données spatiotemporelles
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] planification urbaine
[Termes IGN] point d'intérêt
[Termes IGN] Shenzhen
[Termes IGN] trafic routier
[Termes IGN] transport collectifRésumé : (auteur) Accessibility is a representative indicator for evaluating the supply of bus system. Traditional studies have evaluated the accessibility from different aspects. Considering the interaction among land use, bus timetable arrangement and individual factors, a more holistic accessibility measurement is proposed to combine static and dynamic characteristics from multisource traffic data. The rationale of the proposed model is verified by a case study of bus system in Shenzhen, China, which is carried out to find the spatial and temporal discrepancy of service of bus system. It is found that the adjustment of bus schedule to time-varying travel demand can affect accessibility of bus system and that Land-use development, average bus speed and bus facilities all have positive effects on accessibility of bus system. These findings provide significant reference for transport planning and policy-making. The proposed model is not limited to accessibility measuring of bus system, but also applicable to other travel modes. Numéro de notice : A2020-564 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1783189 Date de publication en ligne : 24/07/2020 En ligne : https://doi.org/10.1080/10095020.2020.1783189 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95881
in Geo-spatial Information Science > vol 23 n° 3 (September 2020) . - pp 248 - 257[article]Mining regional patterns of land use with adaptive adjacent criteria / Xinmeng Tu in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)
[article]
Titre : Mining regional patterns of land use with adaptive adjacent criteria Type de document : Article/Communication Auteurs : Xinmeng Tu, Auteur ; Zhenjie Chen, Auteur ; Beibei Wang, Auteur ; changqing Xu, Auteur Année de publication : 2020 Article en page(s) : pp 418 - 431 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] adjacence
[Termes IGN] analyse combinatoire (maths)
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatio-temporelle
[Termes IGN] changement d'utilisation du sol
[Termes IGN] Chine
[Termes IGN] construction
[Termes IGN] extraction de modèle
[Termes IGN] filtrage spatiotemporel
[Termes IGN] occupation du sol
[Termes IGN] polygone
[Termes IGN] région
[Termes IGN] relation spatiale
[Termes IGN] surface cultivée
[Termes IGN] urbanisation
[Termes IGN] utilisation du sol
[Termes IGN] variogrammeRésumé : (auteur) Land use/cover changes (LULC) are complicated and regionally diverse. When mining regional patterns, the use of a spatial relationship that is determined without considering the spatial correlation among geographical objects can lead to problematic results, e.g. mistakenly treating unrelated objects as adjacent. Additionally, traditional prevalence measures are unstable for uneven datasets such as LULC, wherein some land-use change types show small numbers and uneven quantities, and valuable rules for some land-use categories may be ignored. Therefore, we proposed a regional pattern mining method. First, we developed adaptive adjacent criteria, which can be automatically generated for each specific zone to define adjacency for better spatial-temporal mining. Then, a combinational decision model was built to improve the stability of the prevalence measure, which was used to filter out the insignificant spatial-temporal rules. Furthermore, we proposed two levels of land-use pattern mining, i.e. cluster-level mining and polygon-level mining, to first discover hot-spot areas where similar land-use change has occurred frequently and then to determine the location, frequency, and change time of rules related to different land-use activities. The proposed method was used for mining the dependence of land use and regional patterns on land-use changes. Results show that the proposed method can determine the spatial dependence between the land-use categories, as well as regional patterns of land-use changes. According to our research, the study area, Xinbei District, China, is undergoing land-use change involving rapid urbanization, extensive transportation construction, and losses of farmland. Numéro de notice : A2020-487 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1761452 Date de publication en ligne : 18/06/2020 En ligne : https://doi.org/10.1080/15230406.2020.1761452 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95655
in Cartography and Geographic Information Science > Vol 47 n° 5 (September 2020) . - pp 418 - 431[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2020051 RAB Revue Centre de documentation En réserve L003 Disponible NEAT approach for testing and validation of geospatial network agent-based model processes: case study of influenza spread / Taylor Anderson in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)PermalinkHow do species and data characteristics affect species distribution models and when to use environmental filtering? / Lukáš Gábor in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)PermalinkIncorporating behavior into animal movement modeling: a constrained agent-based model for estimating visit probabilities in space-time prisms / Rebecca W. Loraamm in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)PermalinkTourism land use simulation for regional tourism planning using POIs and cellular automata / Hong Shi in Transactions in GIS, Vol 24 n° 4 (August 2020)PermalinkComputational improvements to multi-scale geographically weighted regression / Ziqi Li in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)PermalinkCyclists' exposure to air pollution and noise in Mexico City : contribution of real-time traffic density indicators integrated into GIS / Philippe Apparicio in Revue internationale de géomatique, vol 30 n° 3-4 (juillet - décembre 2020)PermalinkIntegration of spatialization and individualization: the future of epidemic modelling for communicable diseases / Meifang Li in Annals of GIS, vol 26 n° 3 (July 2020)PermalinkMoGUS, un outil de modélisation et d'analyse comparative des trames urbaines / Dominique Badariotti in Revue internationale de géomatique, vol 30 n° 3-4 (juillet - décembre 2020)PermalinkPredictive land value modelling in Guatemala City using a geostatistical approach and Space Syntax / Jose Morales in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)PermalinkReestimating a minimum acceptable geocoding hit rate for conducting a spatial analysis / Alvaro Briz-Redon in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)Permalink