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Prediction of traffic accidents hot spots using fuzzy logic and GIS / Aslam Al-Omari in Applied geomatics, vol 12 n° 2 (June 2020)
[article]
Titre : Prediction of traffic accidents hot spots using fuzzy logic and GIS Type de document : Article/Communication Auteurs : Aslam Al-Omari, Auteur ; Nawras Shatnawi, Auteur ; Taisir Khedaywi, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 149 – 161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] accident de la route
[Termes IGN] analyse spatio-temporelle
[Termes IGN] Jordanie
[Termes IGN] logique floue
[Termes IGN] modèle de simulation
[Termes IGN] pondération
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] superposition
[Termes IGN] zone à risqueRésumé : (auteur) The purpose of the current study is to predict accident hot spots in different locations using Geographic Information System (GIS) and fuzzy logic. The data used contained accident types and occurrence time. Fatality and injury were also studied with spatial-temporal analysis. Moreover, accident hot spots were predicted performing Weighted Overlay Method (WOM) and Fuzzy Overlay Method (FOM), which are widely used in decision making and alternatives analysis based on the results obtained from Analytic Hierarchy Process (AHP). Point Density (PD) method was used to verify hot spots in urban region that resulted from the mentioned two methods. Traffic accidents’ hot spots were predicted for Irbid City in Jordan using the data of the accidents that occurred between 2013 and 2015. Both WOM and FOM proved to be successful in identifying hot spots in parts of study area when verified to PD surface. Final results showed that eight hot spots were pointed out; three are road sections and five are major intersections, which were analyzed to get accident-contributing factors and suggest the proper remedies. Numéro de notice : A2020-559 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-019-00290-7 Date de publication en ligne : 03/12/2019 En ligne : https://doi.org/10.1007/s12518-019-00290-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95869
in Applied geomatics > vol 12 n° 2 (June 2020) . - pp 149 – 161[article]Suitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS / Dogus Guler in Annals of GIS, vol 26 n° 2 (April 2020)
[article]
Titre : Suitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS Type de document : Article/Communication Auteurs : Dogus Guler, Auteur ; Tahsin Yomralioglu, Auteur Année de publication : 2020 Article en page(s) : pp 169 - 189 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse multicritère
[Termes IGN] approche holistique
[Termes IGN] électricité
[Termes IGN] outil d'aide à la décision
[Termes IGN] pondération
[Termes IGN] processus de hiérarchisation analytique floue
[Termes IGN] station
[Termes IGN] système d'information géographique
[Termes IGN] véhicule électrique
[Termes IGN] zone urbaineRésumé : (auteur) Electric vehicles arouse interest since they not only contribute economies of countries in the context of dependency to oil but also support to more livable and sustainable urban areas. The location selection of electric vehicle charging stations is one of the most vital topics in order to enhance the use of electric vehicles. In this sense, the aim of this paper is to propose an approach that integrates Geographic Information System (GIS) techniques and Multi-Criteria Decision Making (MCDM) methods for finding suitable locations of the electric vehicle charging stations. In this regard, the Analytic Hierarchy Process (AHP) and the Fuzzy Analytic Hierarchy Process (FAHP) methods are used to calculate the weights of criteria. While the two different weights for each criterion are obtained by means of AHP in terms of environmental impact and accessibility, another weight for each criterion is obtained as a means of applying the FAHP. The intersection of three different suitability indexes is determined so as to achieve a holistic, credible result. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the alternative locations. The results show that the proposed approach offers a notable solution to be selected suitable charging station locations. Moreover, policymakers and administrators could benefit from these results in order to make efficient decisions for forward planning and strategies. Numéro de notice : A2020-322 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475683.2020.1737226 Date de publication en ligne : 09/03/2020 En ligne : https://doi.org/10.1080/19475683.2020.1737226 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95189
in Annals of GIS > vol 26 n° 2 (April 2020) . - pp 169 - 189[article]Unsupervised extraction of urban features from airborne lidar data by using self-organizing maps / Alper Sen in Survey review, vol 52 n° 371 (March 2020)
[article]
Titre : Unsupervised extraction of urban features from airborne lidar data by using self-organizing maps Type de document : Article/Communication Auteurs : Alper Sen, Auteur ; Baris Suleymanoglu, Auteur ; Metin Soycan, Auteur Année de publication : 2020 Article en page(s) : pp 150 - 158 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de filtrage
[Termes IGN] carte de Kohonen
[Termes IGN] classification non dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] données lidar
[Termes IGN] extraction de la végétation
[Termes IGN] extraction de points
[Termes IGN] filtre adaptatif
[Termes IGN] khi carré
[Termes IGN] pondération
[Termes IGN] réseau neuronal artificiel
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (auteur) The extraction of artificial and natural features using light detection and ranging (Lidar) data is a fundamental task in many fields of research for environmental science. In this study, the possibility of using self-organising maps (SOM), which is an unsupervised artificial neural network classification method to extract the bare earth surface and features from airborne Lidar data, was investigated for two different urban areas. The effect of the enlargement of the study area was analysed using the proposed approach. The appropriate weights of SOM inputs, which are 3D coordinates and intensity, obtained from a Lidar point cloud were determined by using Pearson's chi-squared independence test. The weighted SOM feature extraction performance was better than that of the unweighted SOM. The filtering results of SOM to separate ground and non-ground data were also compared with those obtained by the adaptive TIN filtering algorithm. Most of the non-ground features could be removed by the weighted SOM. Numéro de notice : A2020-079 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1532704 Date de publication en ligne : 12/10/2018 En ligne : https://doi.org/10.1080/00396265.2018.1532704 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94642
in Survey review > vol 52 n° 371 (March 2020) . - pp 150 - 158[article]Multi-spectral image change detection based on single-band iterative weighting and fuzzy C-means clustering / Liyuan Ma in European journal of remote sensing, vol 53 n° 1 (2020)
[article]
Titre : Multi-spectral image change detection based on single-band iterative weighting and fuzzy C-means clustering Type de document : Article/Communication Auteurs : Liyuan Ma, Auteur ; Jia Zhenhong, Auteur ; Jie Yang, Auteur ; Nikola Kasabov, Auteur Année de publication : 2020 Article en page(s) : pp 1 -13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] bruit blanc
[Termes IGN] classification floue
[Termes IGN] classification non dirigée
[Termes IGN] coefficient de corrélation
[Termes IGN] détection de changement
[Termes IGN] distance euclidienne
[Termes IGN] image multibande
[Termes IGN] itération
[Termes IGN] masque
[Termes IGN] pondérationRésumé : (auteur) In the present study, an improved iteratively reweighted multivariate alteration detection (IR-MAD) algorithm was proposed to improve the contribution of weakly correlated bands in multi-spectral image change detection. In the proposed algorithm, each image band was given a different weight through single-band iterative weighting, improving the correlation between each pair of bands. This method was used to obtain the characteristic difference in the diagrams of the band that contain more variation information. After removing Gaussian noise from each feature-difference graph, the difference graphs of each band were fused into a change-intensity graph using the Euclidean distance formula. Finally, unsupervised fuzzy C-means (FCM) clustering was used to perform binary clustering on the fused difference graphs to obtain the change detection results. By comparing the original multivariate alteration detection (MAD) algorithm, the IR-MAD algorithm and the proposed IR-MAD algorithm, which used a mask to eliminate strong changes, the experimental results revealed that the multi-spectral change detection results of the proposed algorithm are closer to the actual value and had higher detection accuracy than the other algorithms. Numéro de notice : A2020-164 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2019.1707124 Date de publication en ligne : 26/12/2020 En ligne : https://doi.org/10.1080/22797254.2019.1707124 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94831
in European journal of remote sensing > vol 53 n° 1 (2020) . - pp 1 -13[article]Impact of GPS processing on the estimation of snow water equivalent using refracted GPS signals / Ladina Steiner in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)
[article]
Titre : Impact of GPS processing on the estimation of snow water equivalent using refracted GPS signals Type de document : Article/Communication Auteurs : Ladina Steiner, Auteur ; Michael Meindl, Auteur ; Christoph Marty, Auteur ; Alain Geiger, Auteur Année de publication : 2020 Article en page(s) : pp 123 - 135 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] Alpes
[Termes IGN] altitude
[Termes IGN] antenne GPS
[Termes IGN] eau de fonte
[Termes IGN] étalonnage des données
[Termes IGN] manteau neigeux
[Termes IGN] modèle hydrographique
[Termes IGN] neige
[Termes IGN] phase GPS
[Termes IGN] pondération
[Termes IGN] réfraction
[Termes IGN] signal GPS
[Termes IGN] SuisseRésumé : (auteur) Global navigation satellite system (GNSS) antennas buried underneath a snowpack have a high potential for in situ snow water equivalent (SWE) estimation. Automated and continuous SWE quantification independent of weather conditions could enhance snow hydrological monitoring and modeling. Accurate and reliable in situ data are needed for the calibration and validation of remote sensing data and snowpack modeling. A relative bias of less than 5% is achieved using sub-snow global positioning system (GPS) antennas (GPS refractometry) during a three full seasons time period in the Swiss Alps. A systematic overview regarding the temporal reliability of the sub-snow GPS derived results is, however, missing for this emerging technique. Moreover, GPS processing impacts the results significantly. Different GPS processing parameters are therefore selected and their influence on the SWE estimation is investigated. The impact of elevation-dependent weighting, the elevation cutoff angles, and the time intervals for SWE estimation are systematically assessed. The best results are achieved using all observations with an elevation-dependent weighting scheme. Moreover, the SWE estimation performance is equally accurate for hourly SWE estimation as for lower temporal resolutions up to daily estimates. The impact of snow on the coordinate solution is furthermore evaluated. While the east and north components are not systematically influenced by the overlying snowpack, the vertical component exhibits a significant variation and strongly depends on the SWE. The biased vertical component therefore provides an additional possibility to estimate SWE. Numéro de notice : A2020-074 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2934016 Date de publication en ligne : 06/09/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2934016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94605
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 1 (January 2020) . - pp 123 - 135[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)PermalinkAnalysis of collaboration networks in OpenStreetMap through weighted social multigraph mining / Quy Thy Truong in International journal of geographical information science IJGIS, vol 33 n° 7 - 8 (July - August 2019)PermalinkHelmert-VCE-aided fast-WTLS approach for global ionospheric VTEC modelling using data from GNSS, satellite altimetry and radio occultation / Andong Hu in Journal of geodesy, vol 93 n°6 (June 2019)PermalinkA deep neural network with spatial pooling (DNNSP) for 3-D point cloud classification / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 8 (August 2018)PermalinkWeighted simplicial complex reconstruction from mobile laser scanning using sensor topology / Stéphane Guinard in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)PermalinkA novel computational knowledge-base framework for visualization and quantification of geospatial metadata in spatial data infrastructures / Gangothri Rajaram in Geoinformatica, vol 22 n° 2 (April 2018)PermalinkA novel orthoimage mosaic method using a weighted A∗ algorithm : Implementation and evaluation / Maoteng Zheng in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkIncreasing the accuracy of crowdsourced information on land cover via a voting procedure weighted by information inferred from the contributed data / Giles M. Foody in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkCut Pursuit: Fast algorithms to learn piecewise constant functions on general weighted graphs / Loïc Landrieu in SIAM Journal on Imaging Sciences, vol 10 n° 4 (November 2017)PermalinkWeighted coordinate transformation formulated by standard least-squares theory / D. Mihajlovic in Survey review, vol 49 n° 356 (November 2017)PermalinkComparison of landslide susceptibility mapping based on statistical index, certainty factors, weights of evidence and evidential belief function models / Kai Cui in Geocarto international, vol 32 n° 9 (September 2017)PermalinkInvestigation of automatic feature weighting methods (Fisher, Chi-square and Relief-F) for landslide susceptibility mapping / Emrehan Kutlug Sahin in Geocarto international, vol 32 n° 9 (September 2017)PermalinkA robust weighted total least-squares solution with Lagrange multipliers / X. Gong in Survey review, vol 49 n° 354 (September 2017)PermalinkLocal Moebius transformations applied to omnidirectional images / Leonardo Souto Ferreira in Computers and graphics, vol 68 (November 2017)PermalinkTotal variation regularized reweighted sparse nonnegative matrix factorization for hyperspectral unmixing / Wei He in IEEE Transactions on geoscience and remote sensing, vol 55 n° 7 (July 2017)PermalinkBias compensation for rational function model based on total least squares / Anzhu Yu in Photogrammetric record, vol 32 n° 157 (March - May 2017)PermalinkRobust sparse hyperspectral unmixing with ℓ2,1 norm / Yong Ma in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkDEM Fusion of elevation REST API data in support of rapid flood modelling / Heather McGrath in Geomatica, vol 70 n° 4 (December 2016)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)PermalinkA mixed weighted least squares and weighted total least squares adjustment method and its geodetic applications / Y. Zhou in Survey review, vol 48 n° 351 (October 2016)Permalink