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Extracting knowledge from legacy maps to delineate eco-geographical regions / Lin Yang in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 250 - 272 Titre : Extracting knowledge from legacy maps to delineate eco-geographical regions Type de document : Article/Communication Auteurs : Lin Yang, Auteur ; Xinming Li, Auteur ; Qinye Yang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 250 - 272 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] carte ancienne [Termes IGN] carte climatique [Termes IGN] cartographie écologique [Termes IGN] Chine [Termes IGN] délimitation [Termes IGN] données cartographiques [Termes IGN] écorégion [Termes IGN] extraction de données [Termes IGN] logique floue [Termes IGN] sous ensemble flou [Termes IGN] zone tampon Résumé : (auteur) Legacy ecoregion maps contain knowledge on relationships between eco-region units and their environmental factors. This study proposes a method to extract knowledge from legacy area-class maps to formulate a set of fuzzy membership functions useful for regionalization. We develop a buffer zone approach to reduce the uncertainty of boundaries between eco-region units on area-class maps. We generate buffer zones with a Euclidean distance perpendicular to the boundaries, then the original eco-region units without buffer zones serve as the basic units to generate the probability density functions (PDF) of environmental variables. Then, we transform the PDFs to fuzzy membership functions for class-zones on the map. We demonstrate the proposed method with a climatic zone map of China. The results showed that the buffer zone approach effectively reduced the uncertainties of boundaries. A buffer distance of 10–15 km was recommended in this study. The climatic zone map generated based on the extracted fuzzy membership functions showed a higher spatial stratification heterogeneity (compared to the original map). Based on the fuzzy membership functions with climate data of 1961–2015, we also prepared an updated climatic zone map. This study demonstrates the prospects of using fuzzy membership functions to delineate area classes for regionalization purpose. Numéro de notice : A2021-025 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1806284 date de publication en ligne : 17/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1806284 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96692 [article]

A LiDAR aiding ambiguity resolution method using fuzzy one-to-many feature matching / Chuang Qian in Journal of geodesy, vol 94 n° 10 (October 2020)  

Public [article]  inJournal of geodesy > vol 94 n° 10 (October 2020) . - 18 p. Titre : A LiDAR aiding ambiguity resolution method using fuzzy one-to-many feature matching Type de document : Article/Communication Auteurs : Chuang Qian, Auteur ; Hongjuan Zhang, Auteur ; Wenzhuo Li, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] analyse comparative [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] estimation de position [Termes IGN] GPS assisté pour la navigation (technologies) [Termes IGN] logique floue [Termes IGN] positionnement cinématique en temps réel [Termes IGN] précision du positionnement [Termes IGN] résolution d'ambiguïté Résumé : (auteur) Despite the high-precision performance of GNSS real-time kinematic (RTK) in many cases, large noises in pseudo-range measurements or harsh signal environments still impact float ambiguity estimation in kinematic localization, which leads to ambiguity-fixed failure and worse positioning results. To improve RTK ambiguity resolution (AR) performance further, multi-sensor fusion technique is a feasible option. Light detection and ranging (LiDAR)-based localization is a good complementary method to GNSS. Tight integration of GNSS RTK and LiDAR adds new information to satellite measurements, thus improving float ambiguity estimation and then improving integer AR. In this work, a LiDAR aiding single-frequency single-epoch GPS + BDS RTK was proposed and investigated by theoretical analysis and performance assessment. Considering LiDAR-based localization failure because of ambiguous and repetitive landmarks, a fuzzy one-to-many feature-matching method was proposed to find a series of sequences including all possible relative positions to landmarks. Then, the standard RTK method was tightly combined with the possible positions from each sequence to find the most accurate position estimation. Experimental results proved the superiority of our method over the standard RTK method in all aspects of success rate, fixed rate and positioning accuracy. In specific, our method achieved centimeter-level position accuracy with 100% fixed rate in the urban environment, while the standard GPS + BDS RTK obtained decimeter-level accuracy with 26.84% fixed rate. In the high occlusion environment, our method had centimeter-level accuracy with a fixed rate of 96.31%, comparing a meter-level accuracy and a fixed rate of 7.65% of standard GPS + BDS RTK method. Numéro de notice : A2020-649 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01426-z date de publication en ligne : 25/11/2020 En ligne : https://doi.org/10.1007/s00190-020-01426-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96082 [article]

Prediction of traffic accidents hot spots using fuzzy logic and GIS / Aslam Al-Omari in Applied geomatics, vol 12 n° 2 (June 2020)  

Public [article]  inApplied geomatics > vol 12 n° 2 (June 2020) . - pp 149 – 161 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 d'analyse hiérarchique [Termes IGN] superposition [Termes IGN] zone à risque Résumé : (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 [article]

Estimation of metabolic flows of urban environment based on fuzzy expert knowledge / Igor Patrakeyev in Geodesy and cartography, vol 46 n° 1 (January 2020)  

Public [article]  inGeodesy and cartography > vol 46 n° 1 (January 2020) . - pp 8 – 16 Titre : Estimation of metabolic flows of urban environment based on fuzzy expert knowledge Type de document : Article/Communication Auteurs : Igor Patrakeyev, Auteur ; Victor Ziborov, Auteur ; Oleksii Mikhno, Auteur Année de publication : 2020 Article en page(s) : pp 8 – 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information [Termes IGN] aménagement durable [Termes IGN] croissance urbaine [Termes IGN] environnement [Termes IGN] logique floue [Termes IGN] système d'information urbain [Termes IGN] système expert flou [Termes IGN] Ukraine [Termes IGN] ville [Termes IGN] zone urbaine Résumé : (auteur) The quality and comfort of the urban environment serve as one of the most important factors for ensuring the competitiveness of municipalities, regions and countries. The quality of the urban environment is determined by the qual-ity of its three components: anthropogenic, natural and social environment. The main problem of assessing the state of the urban environment is the fragmentation of methodological approaches and adequate tools for assessing the qualitative state of the urban environment. This objectively makes it difficult for municipal authorities to use this assessment as an ele-ment in the system of urban planning decision making. We have developed an intelligent information system to provide an assessment of potential, real and lost opportunities of the urban environment using fuzzy expert knowledge. This system operates in the conditions of using non-numeric, inaccurate and incomplete information to ensure the management of sustainable city development. The system for assessing the potential, real and lost opportunities of the urban environment is based on the use of fuzzy logic equations. It allows to evaluate the effectiveness of metabolic transformations of each subsystem of the urban environment. Numéro de notice : A2020-221 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Article DOI : 10.3846/gac.2020.8560 date de publication en ligne : 27/02/2020 En ligne : https://doi.org/10.3846/gac.2020.8560 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94926 [article]

Saliency-guided deep neural networks for SAR image change detection / Jie Geng in IEEE Transactions on geoscience and remote sensing, Vol 57 n° 10 (October 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 57 n° 10 (October 2019) . - pp 7365 - 7377 Titre : Saliency-guided deep neural networks for SAR image change detection Type de document : Article/Communication Auteurs : Jie Geng, Auteur ; Xiaorui Ma, Auteur ; Xiaojun Zhou, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 7365 - 7377 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse d'image orientée objet [Termes IGN] classification floue [Termes IGN] classification non dirigée [Termes IGN] classification par réseau neuronal [Termes IGN] détection de changement [Termes IGN] échantillonnage d'image [Termes IGN] extraction de traits caractéristiques [Termes IGN] filtre de déchatoiement [Termes IGN] image radar moirée [Termes IGN] logique floue [Termes IGN] occupation du sol [Termes IGN] saillance [Termes IGN] télédétection en hyperfréquence Mots-clés libres : hierarchical fuzzy C-means clustering (HFCM) Résumé : (auteur) Change detection is an important task to identify land-cover changes between the acquisitions at different times. For synthetic aperture radar (SAR) images, inherent speckle noise of the images can lead to false changed points, which affects the change detection performance. Besides, the supervised classifier in change detection framework requires numerous training samples, which are generally obtained by manual labeling. In this paper, a novel unsupervised method named saliency-guided deep neural networks (SGDNNs) is proposed for SAR image change detection. In the proposed method, to weaken the influence of speckle noise, a salient region that probably belongs to the changed object is extracted from the difference image. To obtain pseudotraining samples automatically, hierarchical fuzzy C-means (HFCM) clustering is developed to select samples with higher probabilities to be changed and unchanged. Moreover, to enhance the discrimination of sample features, DNNs based on the nonnegative- and Fisher-constrained autoencoder are applied for final detection. Experimental results on five real SAR data sets demonstrate the effectiveness of the proposed approach. Numéro de notice : A2019-536 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2913095 date de publication en ligne : 19/05/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2913095 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94154 [article]

A fuzzy formal concept analysis-based approach to uncovering spatial hierarchies among vague places extracted from user-generated data / Xiaoyu Wu in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)  

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Computing with cognitive spatial frames of reference in GIS / Simon Scheider in Transactions in GIS, vol 22 n° 5 (October 2018)  

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Référencement spatial indirect : modélisation à base de relations et d'objets spatiaux vagues / Mattia Bunel (2018) 

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Snapshot and continuous points-based trajectory search / Shuyao Qi in Geoinformatica [en ligne], vol 21 n° 4 (October - December 2017)  

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Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data / Luliang Tang in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)  

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Ensemble adaptive tile prefetching using fuzzy logic / Mehmet Fatih Uluat in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

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Foundations of Fuzzy Logic and Semantic Web Languages / Umberto Straccia (2014)  

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Slope analysis of fuzzy surfaces / J. Caha in Transactions in GIS, vol 16 n° 5 (October 2012)  

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Modélisation d'un SIG archéologique et développement d'outils d'analyse prenant en compte l'imperfection de l'information : retour des projets SIGRem et ArchéoChamp / Eric Desjardin in Revue internationale de géomatique, vol 22 n° 3 (septembre - novembre 2012)

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A fuzzy index for detecting spatiotemporal outliers / George Grekousis in Geoinformatica, vol 16 n° 3 (July 2012)  

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