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Simulation of dispersion effects by considering interactions of pedestrians and bicyclists using an agent space model / Mingwei Liu in Computers, Environment and Urban Systems, vol 91 (January 2022)
[article]
Titre : Simulation of dispersion effects by considering interactions of pedestrians and bicyclists using an agent space model Type de document : Article/Communication Auteurs : Mingwei Liu, Auteur ; Tinggui Chen, Auteur ; Chiaki Matunaga, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101725 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] agent (intelligence artificielle)
[Termes IGN] bicyclette
[Termes IGN] comportement
[Termes IGN] cycliste
[Termes IGN] direction
[Termes IGN] interaction spatiale
[Termes IGN] modèle de dispersion
[Termes IGN] modèle orienté agent
[Termes IGN] navigation pédestre
[Termes IGN] piéton
[Termes IGN] sécurité
[Termes IGN] vitesse
[Termes IGN] zone urbaineRésumé : (auteur) As the number of bicyclists in urban areas continues to increase, the need to realistically model the movement and interactions of bicyclists in mixed urban traffic is rapidly gaining importance. Therefore, this paper presents an agent space model (ASM) to elucidate the movements of bicyclists and pedestrians on shared roads. The ASM model, via simulation, particularly illustrates the dispersion phenomenon observed for non-motorized road users. The mutual interactions and diverse bicyclist and pedestrian properties were also incorporated into this model. The mutual interactions were realised through agent spaces of different sizes in conflict and overtaking behaviours for the following combinations: bicyclist-to-pedestrian, bicyclist-to-bicyclist, pedestrian-to-bicyclist, and pedestrian-to-pedestrian, which were obtained through experiments. The hypothesis test indicated that different agent spaces exist for different types of interactions. The experimental data were used to obtain several variables that describe the elements of road user agent spaces, including longitudinal and lateral distances and the dynamic relationship between the longitudinal distance and speed. The simulation results indicated that with an increase in the number of pedestrians, the maximum capacity decreased and the dispersion degree increased. The following psychological and physiological factors affect the degree of dispersion of bicyclists: travelling speed, reaction time, intensity, probability of selecting the head-on direction, and probability of selecting the right-hand direction. In addition, lane formation was observed in all simulations. The results also demonstrated that dedicated bicycle lanes will significantly reduce the dispersion degree. Moreover, the safety and efficiency effects of different forms of bicycle lanes were analysed from the perspective of the degree of dispersion. The simulation results can provide specific guidelines for understanding the causes of phenomena such as dispersion and lane formation, as well as for studying the traffic dynamics, effects of dedicated bicycle lanes, and macroscopic characteristics according to different bicyclist-pedestrian ratios. Numéro de notice : A2021-826 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101725 Date de publication en ligne : 20/10/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101725 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98947
in Computers, Environment and Urban Systems > vol 91 (January 2022) . - n° 101725[article]Spatial distribution of lead (Pb) in soil: a case study in a contaminated area of the Czech Republic / Nicolas Francos in Geomatics, Natural Hazards and Risk, vol 13 (2022)
[article]
Titre : Spatial distribution of lead (Pb) in soil: a case study in a contaminated area of the Czech Republic Type de document : Article/Communication Auteurs : Nicolas Francos, Auteur ; Asa Gholizadeh, Auteur ; Eyal Ben-Dor, Auteur Année de publication : 2022 Article en page(s) : pp 610 - 620 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] autocorrélation spatiale
[Termes IGN] contamination
[Termes IGN] distribution spatiale
[Termes IGN] image infrarouge
[Termes IGN] interpolation spatiale
[Termes IGN] krigeage
[Termes IGN] plomb
[Termes IGN] qualité du sol
[Termes IGN] République TchèqueRésumé : (auteur) For decades, the Příbram district in the Czech Republic has been affected by industrial and mining activities, which are the main sources of heavy metal pollutants and negatively affect soil quality. A recent study examined visible–near-infrared (VNIR), shortwave-infrared (SWIR), and X-ray fluorescence (XRF) spectroscopy to model soil lead (Pb) content in a selected area located in Příbram. Following that study, and using the data, we examined the spatial distribution of Pb content in the soil, with a combination of traditional techniques (Moran’s I, hotspot analysis, and Kriging). One of the novel points of this work is the use of the Getis–Ord hotspot analysis before the execution of Kriging interpolation to better emphasize clustering patterns. The results indicated that Pb was a spatially dependent soil property and through extensive in-situ sampling, it was possible to generate an accurate interpolation model. The high-Pb hotspots coincided with topographic obstacles that were modeled using topographic profiles extracted from Google Earth, indicating that Pb content does not always exhibit a direct relationship with topographic height as a result of runoff, due to the contribution of topographic steps. This observation provides a new perspective on the relationship between Pb content and topographic patterns. Numéro de notice : A2022-872 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475705.2022.2039786 Date de publication en ligne : 23/02/2022 En ligne : https://doi.org/10.1080/19475705.2022.2039786 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102166
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 610 - 620[article]Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany / Omar Seleem in Geomatics, Natural Hazards and Risk, vol 13 (2022)
[article]
Titre : Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany Type de document : Article/Communication Auteurs : Omar Seleem, Auteur ; Georgy Ayzel, Auteur Année de publication : 2022 Article en page(s) : pp 1640 - 1662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Berlin
[Termes IGN] cartographie des risques
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] inondation
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] vulnérabilitéRésumé : (auteur) Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available. Numéro de notice : A2022-457 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/19475705.2022.2097131 Date de publication en ligne : 12/07/2022 En ligne : https://doi.org/10.1080/19475705.2022.2097131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101257
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 1640 - 1662[article]Building fuzzy areal geographical objects from point sets / Jifa Guo in Transactions in GIS, vol 25 n° 6 (December 2021)
[article]
Titre : Building fuzzy areal geographical objects from point sets Type de document : Article/Communication Auteurs : Jifa Guo, Auteur ; Shihong Du, Auteur Année de publication : 2021 Article en page(s) : pp 3067 - 3087 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse comparative
[Termes IGN] habitat animal
[Termes IGN] habitat d'espèce
[Termes IGN] objet flou
[Termes IGN] objet géographique zonal
[Termes IGN] réserve naturelleRésumé : (Auteur) Representations of fuzzy geographic objects and analyses of their spatial relationships have received considerable attention in the GIS and spatial database domains over the past 30 years. However, building fuzzy geographical objects from real data is still a challenge. Simple fuzzy areal object models are too restrictive for many applications, and general fuzzy areal models may not be restrictive enough; as a result, the extent of fuzzy regions that satisfy the relevant conditions may be too large to affect the location description and spatial analysis. A condition by which the number of cores is not greater than one is added for the general object model, and an operable method for constructing fuzzy objects from the point set is proposed. Two peak and pass sets are determined for the membership surface by the fuzzy morphometric analysis method. The first set is used to initially divide the footprint of the fuzzy surface into smaller subfootprints, and the second set is used to merge insignificant fuzzy objects with their nearest significant fuzzy objects; thus, unreasonable division is avoided. Cross-validation is adopted to evaluate the generated fuzzy objects. An experiment is provided to verify the effectiveness of the proposed method. Numéro de notice : A2021-933 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12808 Date de publication en ligne : 10/10/2021 En ligne : https://doi.org/10.1111/tgis.12808 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99454
in Transactions in GIS > vol 25 n° 6 (December 2021) . - pp 3067 - 3087[article]A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping / Khalil Valizadeh Kamran in Applied geomatics, vol 13 n° 4 (December 2021)
[article]
Titre : A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping Type de document : Article/Communication Auteurs : Khalil Valizadeh Kamran, Auteur ; Bakhtiar Feizizadeh, Auteur ; Behnam Khorrami, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 837 - 851 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de sensibilité
[Termes IGN] apprentissage automatique
[Termes IGN] cartographie des risques
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] effondrement de terrain
[Termes IGN] fonction de base radiale
[Termes IGN] Iran
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] occupation du sol
[Termes IGN] pente
[Termes IGN] risque naturel
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (auteur) Landslides are among the most destructive natural hazards with severe socio-economic ramifications all around the world. Understanding the critical combination of geoenvironmental factors involved in the occurrence of landslides can mitigate the adverse impacts ascribed to them. Among the several scenarios for studying and investigating this phenomenon, landslide susceptibility mapping (LSM) is the most prominent method. Applying the machine learning (ML) algorithms integrated with the geographic information systems (GIS) has become a trending means for accurate and rapid landslide mapping practices in the scientific community. Support vector machine (SVM) has been the most commonly applied ML algorithm for LSM in recent years. The current study aims to implement different SVM kernel functions including polynomial kernel function (PKF) (degree 1 to 5), radial basis function (RBF), sigmoid, and linear kernels, for a GIS-based LSM over the Tabriz Basin (TB). To this end, a total number of 9 conditioning parameters being involved in the occurrence of the landslide events were determined and utilized. The LSM maps of the TB were generated based on the different SVM kernels and were statistically validated according to the landslide inventory. The findings revealed that the polynomial-degree-2 (PKF-2) model (AUC = 0.9688) outperforms the rest of the utilized kernels. According to the SLM map generated through PKF-2, the northernmost parts of the TB are extremely susceptible to slope failures than the rest; therefore, the developmental policies over these parts have to be taken into account with privileged priority to hinder any humanitarian as well as environmental catastrophes. Numéro de notice : A2021-858 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s12518-021-00393-0 Date de publication en ligne : 28/08/2021 En ligne : https://doi.org/10.1007/s12518-021-00393-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99066
in Applied geomatics > vol 13 n° 4 (December 2021) . - pp 837 - 851[article]Incorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment / Ali Azareh in Geocarto international, vol 36 n° 20 ([01/12/2021])PermalinkModeling transit-assisted hurricane evacuation through socio-spatial networks / Yan Yang in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)PermalinkA topology-based graph data model for indoor spatial-social networking / Mahdi Rahimi in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)PermalinkUnderstanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models / Tong Zhang in Transactions in GIS, vol 25 n° 6 (December 2021)PermalinkUsing textual volunteered geographic information to model nature-based activities: A case study from Aotearoa New Zealand / Ekaterina Egorova in Journal of Spatial Information Science (JoSIS), n° 23 (2021)PermalinkAnalytics of location-based big data for smart cities: Opportunities, challenges, and future directions / Haosheng Huang in Computers, Environment and Urban Systems, vol 90 (November 2021)PermalinkCalibration of cellular automata urban growth models from urban genesis onwards - a novel application of Markov chain Monte Carlo approximate Bayesian computation / Jingyan Yu in Computers, Environment and Urban Systems, vol 90 (November 2021)PermalinkA comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area / Myung-Jin Jun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkGIS-based study on the environmental sensitivity to pollution and susceptibility to eutrophication in Burullus Lake, Egypt / Muhammad A. El-Alfy in Marine geodesy, vol 44 n° 6 (November 2021)PermalinkIdentifying surface urban heat island drivers and their spatial heterogeneity in China’s 281 cities: An empirical study based on multiscale geographically weighted regression / Lu Niu in Remote sensing, vol 13 n° 21 (November-1 2021)PermalinkMultiscale geographically and temporally weighted regression with a unilateral temporal weighting scheme and its application in the analysis of spatiotemporal characteristics of house prices in Beijing / Zhi Zhang in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkA quantitative comparison of regionalization methods / Orhun Aydun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkA spatial model of cognitive distance in cities / Ed Manley in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkSpatially–encouraged spectral clustering: a technique for blending map typologies and regionalization / Levi John Wolf in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkA topic model based framework for identifying the distribution of demand for relief supplies using social media data / Ting Zhang in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkEvaluating urban intensity through a city information model - intermediate results from an action research project / Adeline Deprêtre in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol VIII-4/W2-2021 ([07/10/2021])PermalinkAnthropogenic degradation of dunes within a city: a disappearing feature of the cultural landscape of Toruń (Poland) / Pawel Molewski in Journal of maps, vol 17 n° 4 (October 2021)PermalinkImpact of travel time uncertainties on modeling of spatial accessibility: a comparison of street data sources / Yan Lin in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)PermalinkUrban geomorphology of a historical city straddling the Tanaro River (Alessandria, NW Italy) / Andrea Mandarino in Journal of maps, vol 17 n° 4 (October 2021)PermalinkAssessment and prediction of urban growth for a mega-city using CA-Markov model / Veerendra Yadav in Geocarto international, vol 36 n° 17 ([15/09/2021])Permalink