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Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis / Kai Zhang in Sustainable Cities and Society, vol 78 (March 2022)
[article]
Titre : Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis Type de document : Article/Communication Auteurs : Kai Zhang, Auteur ; Zhen Qian, Auteur ; Yue Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage profond
[Termes IGN] cartographie du bruit
[Termes IGN] Chine
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] distribution spatiale
[Termes IGN] image Streetview
[Termes IGN] lutte contre le bruit
[Termes IGN] milieu urbain
[Termes IGN] OpenStreetMap
[Termes IGN] planification urbaine
[Termes IGN] pollution acoustique
[Termes IGN] trafic routier
[Termes IGN] ville durableRésumé : (auteur) Road noise barriers (RNBs) are important urban infrastructures to relieve the harm of traffic noise pollution for citizens. Therefore, obtaining the spatial distribution characteristics of RNBs, such as precise positions and mileage, can be of great help for obtaining more accurate urban noise maps and assessing the quality of the urban living environment for sustainable urban development. However, an effective and efficient method for identifying RNBs and acquiring their attributes in large areas is scarce. This study constructs an ensemble classification model (ECM) to automatically identify RNBs at the city level based on Baidu Street View (BSV). Firstly, the bootstrap sampling method is proposed to build a street view image-based train set, where the effect of imbalanced categories of samples was reduced by adding confusing negative samples. Secondly, two state-of-the-art deep learning models, ResNet and DenseNet, are ensembled to construct an ECM based on the bagging framework. Finally, a post-processing method has been proposed based on geospatial analysis to eliminate street view images (SVIs) that are misclassified as RNBs. This study takes Suzhou, China as the study area to validate the proposed method. The model achieved an accuracy and F1-score of 0.98 and 0.90, respectively. The total mileage of the RNBs in Suzhou was 178,919 m. The results demonstrated the performance of the proposed RNBs identification framework. The significance of obtaining RNBs attributes for accelerating sustainable urban development has been demonstrated through the case of photovoltaic noise barriers (PVNBs). Numéro de notice : A2022-241 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.scs.2021.103598 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1016/j.scs.2021.103598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100167
in Sustainable Cities and Society > vol 78 (March 2022) . - n° 103598[article]Visual vs internal attention mechanisms in deep neural networks for image classification and object detection / Abraham Montoya Obeso in Pattern recognition, vol 123 (March 2022)
[article]
Titre : Visual vs internal attention mechanisms in deep neural networks for image classification and object detection Type de document : Article/Communication Auteurs : Abraham Montoya Obeso, Auteur ; Jenny Benois-Pineau, Auteur ; Mireya S. García Vázquez, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 108411 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse visuelle
[Termes IGN] apprentissage profond
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] oculométrie
[Termes IGN] saillance
[Termes IGN] segmentation sémantique
[Termes IGN] visualisation de donnéesRésumé : (auteur) The so-called “attention mechanisms” in Deep Neural Networks (DNNs) denote an automatic adaptation of DNNs to capture representative features given a specific classification task and related data. Such attention mechanisms perform both globally by reinforcing feature channels and locally by stressing features in each feature map. Channel and feature importance are learnt in the global end-to-end DNNs training process. In this paper, we present a study and propose a method with a different approach, adding supplementary visual data next to training images. We use human visual attention maps obtained independently with psycho-visual experiments, both in task-driven or in free viewing conditions, or powerful models for prediction of visual attention maps. We add visual attention maps as new data alongside images, thus introducing human visual attention into the DNNs training and compare it with both global and local automatic attention mechanisms. Experimental results show that known attention mechanisms in DNNs work pretty much as human visual attention, but still the proposed approach allows a faster convergence and better performance in image classification tasks. Numéro de notice : A2022-197 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.patcog.2021.108411 Date de publication en ligne : 12/11/2021 En ligne : https://doi.org/10.1016/j.patcog.2021.108411 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99988
in Pattern recognition > vol 123 (March 2022) . - n° 108411[article]Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])
[article]
Titre : Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques Type de document : Article/Communication Auteurs : Saman Javadi, Auteur ; Seied Mehdy Hashemy Shahdany, Auteur ; Hashemy Shahdany, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1160-1182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] aquifère
[Termes IGN] arsenic
[Termes IGN] cartographie des risques
[Termes IGN] contamination
[Termes IGN] eau souterraine
[Termes IGN] Iran
[Termes IGN] logique floue
[Termes IGN] nitrate
[Termes IGN] pollution des eaux
[Termes IGN] vulnérabilitéRésumé : (auteur) This study proposes a new approach to establish a multi-parameter risk mapping method by employing the K-Means clustering technique. Accordingly, spatial assessment of arsenic (As), nitrate (NO3) and total dissolved solids (TDS) were carried out based on the type of land use to estimate contamination potential in an aquifer. Since risk mapping is always associated with the occurrence probability of a phenomenon, pollution occurrence probability was then obtained using the fuzzy C-means clustering. The results reveal that NO3 and As contamination levels increase from the first cluster (C1), covers 22.3% of the aquifer, to C5 encompassing 35.1% of the aquifer devoted to extensive industrial and agricultural activities. Fuzzy clustering results show that the pollution occurrence probability in each aquifer cell varied from less than 30 to more than 90%. Moreover, the results show, industrial and agricultural land uses cover about 70% of the areas with high risk of contamination. Numéro de notice : A2022-396 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1778099 Date de publication en ligne : 23/06/2020 En ligne : https://doi.org/10.1080/10106049.2020.1778099 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100690
in Geocarto international > vol 37 n° 4 [15/02/2022] . - pp 1160-1182[article]Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery / Donato Morresi in Remote sensing of environment, vol 269 (February 2022)
[article]
Titre : Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery Type de document : Article/Communication Auteurs : Donato Morresi, Auteur ; Raffaella Marzano, Auteur ; Emanuele Lingua, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112800 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] cartographie des risques
[Termes IGN] détection de changement
[Termes IGN] forêt alpestre
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] incendie de forêt
[Termes IGN] phénologie
[Termes IGN] Piémont (Italie)
[Termes IGN] réflectance spectrale
[Termes IGN] risque naturel
[Termes IGN] variation saisonnière
[Termes IGN] zone sinistréeRésumé : (auteur) Deriving burn severity from multispectral satellite data is a widely adopted approach to infer the degree of environmental change caused by fire. Burn severity maps obtained by thresholding bi-temporal indices based on pre- and post-fire Normalized Burn Ratio (NBR) can vary substantially depending on temporal constraints such as matched acquisition and optimal seasonal timing. Satisfying temporal requirements is crucial to effectively disentangle fire and non-fire induced spectral changes and can be particularly challenging when only a few cloud-free images are available. Our study focuses on 10 wildfires that occurred in mountainous areas of the Piedmont Region (Italy) during autumn 2017 following a severe and prolonged drought period. Our objectives were to: (i) generate reflectance composites using Sentinel-2 imagery that were optimised for seasonal timing by embedding spatial patterns of long-term land surface phenology (LSP); (ii) produce and validate burn severity maps based on the modelled relationship between bi-temporal indices and field data; (iii) compare burn severity maps obtained using either a pair of cloud-free Sentinel-2 images, i.e. paired images, or reflectance composites. We proposed a pixel-based compositing algorithm coupling the weighted geometric median and thematic spatial information, e.g. long-term LSP metrics derived from the MODIS Collection 6 Land Cover Dynamics Product, to rank all the clear observations available in the growing season. Composite Burn Index data and bi-temporal indices exhibited a strong nonlinear relationship (R2 > 0.85) using paired images or reflectance composites. Burn severity maps attained overall classification accuracy ranging from 76.9% to 83.7% (Kappa between 0.61 and 0.72) and the Relative differenced NBR (RdNBR) achieved the best results compared to other bi-temporal indices (differenced NBR and Relativized Burn Ratio). Improvements in overall classification accuracy offered by the calibration of bi-temporal indices with the dNBR offset were limited to burn severity maps derived from paired images. Reflectance composites provided the highest overall classification accuracy and differences with paired images were significant using uncalibrated bi-temporal indices (4.4% to 5.2%) while they decreased (2.8% to 3.2%) when we calibrated bi-temporal indices derived from paired images. The extent of the high severity category increased by ~19% in burn severity maps derived from reflectance composites (uncalibrated RdNBR) compared to those from paired images (calibrated RdNBR). The reduced contrast between healthy and burnt conditions associated with suboptimal seasonal timing caused an underestimation of burnt areas. By embedding spatial patterns of long-term LSP metrics, our approach provided consistent reflectance composites targeted at a specific phenological stage and minimising non-fire induced inter-annual changes. Being independent from the multispectral dataset employed, the proposed pixel-based compositing approach offers new opportunities for operational change detection applications in geographic areas characterised by persistent cloud cover. Numéro de notice : A2022-095 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112800 Date de publication en ligne : 22/11/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112800 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99534
in Remote sensing of environment > vol 269 (February 2022) . - n° 112800[article]Maps, volunteered geographic information (VGI) and the spatio-discursive construction of nature / Juan Astaburuaga in Digital Geography and Society, vol 3 (2022)
[article]
Titre : Maps, volunteered geographic information (VGI) and the spatio-discursive construction of nature Type de document : Article/Communication Auteurs : Juan Astaburuaga, Auteur ; Michael E. Martin, Auteur ; Agnieszka Leszczynski, Auteur ; JC Gaillard, Auteur Année de publication : 2022 Article en page(s) : n° 100029 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse du discours
[Termes IGN] cartographie collaborative
[Termes IGN] données localisées des bénévoles
[Termes IGN] gestion de la vie sauvage
[Termes IGN] milieu naturel
[Termes IGN] Patagonie
[Termes IGN] représentation mentale
[Vedettes matières IGN] CartologieRésumé : (auteur) This paper interrogates the role that spatial media such as maps and Volunteered Geographic Information (VGI) play in the construction and mobilisation of representations of nature. Drawing on poststructural political ecology, critical cartography, and GIScience, this article engages maps and VGI as discursive mechanisms that solidify and convey meanings and representations of nature tied to broader strategies of commodification. Particularly, we explore how spatial media reproduces and legitimises discursive strategies that rationalise the reconciliation of economic development and conservation through nature-based tourism by producing new ways of nature commodification. Drawing on evidence from Patagonia-Aysén, Chile, this paper examines the intersections between the discourse of nature encoded within institutional tourist maps and advertisements, and within the VGI platform for travellers, TripAdvisor. This illustrative case shows, firstly, how tourist maps and advertisements have contributed to normalising a discursive construction of nature as pristine, grandiose, sublime and wild that has not only secured aesthetics as ontological qualities of nature, but also as embedded values that protect ‘nature’ as a commodity to consume. Secondly, our findings evidence that TripAdvisor emerges out of this context as content that mobilises individual perceptions of and narratives about Patagonian nature that is already mediated by this dominant discourse. This dynamic suggests that VGI constitutes a new form of discursive power that digitally reproduces and mobilises a dominant discourse of nature, (re)producing what we term ‘discursive digital nature’. Numéro de notice : A2022-140 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.diggeo.2022.100029 Date de publication en ligne : 22/01/2022 En ligne : https://doi.org/10.1016/j.diggeo.2022.100029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99772
in Digital Geography and Society > vol 3 (2022) . - n° 100029[article]Assessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India / Rajib Mitra in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkPermalinkPermalinkCartographie dynamique de la topographie de l'océan de surface par assimilation de données altimétriques / Florian Le Guillou (2022)PermalinkLa cartographie au service de la diffusion des connaissances de l’Inventaire du Patrimoine culturel de la Région Bretagne / Elise Frank (2022)PermalinkCIME: Context-aware geolocation of emergency-related posts / Gabriele Scalia in Geoinformatica, vol 26 n° 1 (January 2022)PermalinkCombining a class-weighted algorithm and machine learning models in landslide susceptibility mapping: A case study of Wanzhou section of the Three Gorges Reservoir, China / Huijuan Zhang in Computers & geosciences, vol 158 (January 2022)PermalinkContributions of multi-temporal airborne LiDAR data to mapping carbon stocks and fluxes in tropical forests / Claudia Milena Huertas Garcia (2022)PermalinkDetection and biomass estimation of phaeocystis globosa blooms off Southern China from UAV-based hyperspectral measurements / Xue Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkDétection des prairies de fauche et estimation des périodes de fauche par télédétection / Emma Seneschal (2022)PermalinkPermalinkForest fire susceptibility assessment using Google Earth engine in Gangwon-do, Republic of Korea / Yong Piao in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkPermalinkA GIS-based landslide susceptibility mapping and variable importance analysis using artificial intelligent training-based methods / Pengxiang Zhao in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkGuidelines for standardizing the design of tactile maps: A review of research and best practice / Jakub Wabiński in Cartographic journal (the), vol 59 n° 3 (August 2022)PermalinkHarmonisation de la production cartographique dans le cadre des Programmes d’Actions de Prévention des Inondations / Nils Deslandes (2022)PermalinkIdentifying map users with eye movement data from map-based spatial tasks: user privacy concerns / Hua Liao in Cartography and Geographic Information Science, vol 49 n° 1 (January 2022)PermalinkImproving urban land cover mapping with the fusion of optical and SAR data based on feature selection strategy / Qing Ding in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)PermalinkInteractive HGIS platform union of Lublin (1569): A geomatic solution for discovering the Jagiellonian heritage of the city / Jakub Kuna in Journal of Cultural Heritage, vol 53 (January–February 2022)PermalinkIntroduction à la géomatique pour le statisticien : quelques concepts et outils innovants de gestion, traitement et diffusion de l’information spatiale / François Sémécurbe (2022)PermalinkJahresbericht 2021 des Bundesamtes für Kartographie und Geodäsie / Bundesamt für Kartographie und Geodäsie (2022)PermalinkPermalinkPermalinkPermalinkModalités et rythmes d'évolution des falaises des Vaches Noires (Normandie, France) : caractérisation et quantification des dynamiques hydrogravitaires par approches multi-scalaires / Thomas Roulland (2022)PermalinkLe radar révèle des montagnes cachées / Laurent Polidori in Géomètre, n° 2198 (janvier 2022)PermalinkRéappropriation de la donnée spatiale de la Communauté d’Agglomération de Coulommiers Pays de Brie / Mathieu Defaye (2022)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkThe use of volunteer geographic information for producing and maintaining authoritative land use and land cover data / Ana-Maria Olteanu-Raimond (2022)PermalinkThree-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation / Massimiliano Alvioli in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkTowards urban flood susceptibility mapping using data-driven models in Berlin, Germany / Omar Seleem in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkUrban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images / Xiao Li in Cartography and Geographic Information Science, vol 49 n° 1 (January 2022)PermalinkUtilisations multiples de FME pour automatiser les traitements d’une collectivité / Emma Bolmin (2022)PermalinkA 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)PermalinkEvaluating narrative in geoportals for territorial public policies / Luis Manuel Batista in Cartographica, vol 56 n° 4 (Winter 2021)PermalinkExplorer par la carte l’espace pendant le confinement: Une expérimentation de cartographie sensible / Laurence Jolivet in Revue des Politiques Sociales et Familiales, n° 141 ([01/12/2021])PermalinkA GIS-remote sensing approach for forest fire risk assessment: case of Bizerte region, Tunisia / Salwa Saidi in Applied geomatics, vol 13 n° 4 (December 2021)PermalinkGIS to identify exposed shoreline sectors to wave impacts: case of El Tarf coast / Abdeldjalil Goumrasa in Applied geomatics, vol 13 n° 4 (December 2021)PermalinkIncorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment / Ali Azareh in Geocarto international, vol 36 n° 20 ([01/12/2021])PermalinkParticle swarm optimization based water index (PSOWI) for mapping the water extents from satellite images / Mohammad Hossein Gamshadzaei in Geocarto international, vol 36 n° 20 ([01/12/2021])PermalinkA semantics-based trajectory segmentation simplification method / Minshi Liu in Journal of Geovisualization and Spatial Analysis, vol 5 n° 2 (December 2021)PermalinkEvaluation of watershed soil erosion hazard using combination weight and GIS: a case study from eroded soil in Southern China / Shifa Chen in Natural Hazards, vol 109 n° 2 (November 2021)PermalinkInteractive maps for the production of knowledge and the promotion of participation from the perspective of communication, journalism, and digital humanities / Pedro Molina Rodríguez-Navas in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)PermalinkA method of extracting high-accuracy elevation control points from ICESat-2 altimetry data / Binbin Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)PermalinkA novel cotton mapping index combining Sentinel-1 SAR and Sentinel-2 multispectral imagery / Lan Xun in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)PermalinkPotential flood hazard zone mapping based on geomorphologic considerations and fuzzy analytical hierarchy model in a data scarce West African basin / Olabanji Aladejana in Geocarto international, vol 36 n° 19 ([01/11/2021])PermalinkTidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region / Paulo Victor N. Araújo in Natural Hazards and Earth System Sciences, vol 21 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)PermalinkTraditional communities and mental maps: Dialogues between local knowledge and cartography from the socioenvironmental atlas of Lençóis Maranhenses, Brazil / Benedito Souza Filho in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)PermalinkComplexity-based matching between image resolution and map scale for multiscale image-map generation / Qian Peng in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)PermalinkDeep-learning-based burned area mapping using the synergy of Sentinel-1&2 data / Qi Zhang in Remote sensing of environment, vol 264 (October 2021)PermalinkEpistemological thoughts on the success of maps and the role of cartography / David Fairbairn in International journal of cartography, vol 7 n° 3 (October 2021)PermalinkExtracting 3D indoor maps with any shape accurately using building information modeling data / Qi Qiu in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)PermalinkFlood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model / Gaurav Talukdar in Natural Hazards, vol 109 n° 1 (October 2021)PermalinkGeomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques / Peter G. Chirico in Journal of maps, vol 17 n° 4 (October 2021)PermalinkLoosening the grid: topology as the basis for a more inclusive GIS / L. Westerveld in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)PermalinkA methodology for producing realistic hill-shading map based on shaded relief map, digital orthophotographic map fusion and IHS transformation / Hongyun Zeng in Annals of GIS, vol 27 n° 4 (October 2021)PermalinkPrioritization of forest fire hazard risk simulation using Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) coupled with multicriteria decision analysis (MCDA) techniques – a comparative study analysis / Michael Stanley Peprah in Geodesy and cartography, vol 47 n° 3 (October 2021)PermalinkSpatial thinking in cartography teaching for schoolchildren / Sonia Maria Vanzella Castellar in International journal of cartography, vol 7 n° 3 (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)PermalinkA web GIS-based integration of 3D digital models with linked open data for cultural heritage exploration / Ikrom Nishanbaev in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)PermalinkAutomatic building detection with polygonizing and attribute extraction from high-resolution images / Samitha Daranagama in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)PermalinkDeveloping reliably distinguishable color schemes for legends of natural resource taxonomy-based maps / Virgil Vlad in Cartography and Geographic Information Science, Vol 48 n° 5 (September 2021)PermalinkEvaluating the potential of cybercartography in facilitating indigenous self-determination: A case study with the Hupačasath first nation / Dexter Robson in Cartographica, vol 56 n° 3 (Fall 2021)PermalinkA learning-based approach to automatically evaluate the quality of sequential color schemes for maps / Taisheng Chen in Cartography and Geographic Information Science, Vol 48 n° 5 (September 2021)PermalinkOptimising 2-parameter Lambert Conformal Conic projections for ground-to-grid distortions / Sergio Baselga in Survey review, Vol 53 n° 380 (September 2021)PermalinkProtection naturelle contre la submersion, apport de l'intelligence artificielle / Antoine Mury in Cartes & Géomatique, n° 245-246 (septembre - décembre 2021)PermalinkSearching for an optimal hexagonal shaped enumeration unit size for effective spatial pattern recognition in choropleth maps / Izabela Karsznia in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)PermalinkThe accuracy of urban maps in Spain through GIS: The example of Burgos from the nineteenth to the twentieth century / Barbara Polo-Martin in Cartographica, vol 56 n° 3 (Fall 2021)PermalinkThe willingness of volonteers to report changes on topographic maps / Mihaela Triglav Cekada in Geodetski vestnik, vol 65 n° 3 (September - November 2021)PermalinkA typification method for linear building groups based on stroke simplification / Xiao Wang in Geocarto international, vol 36 n° 15 ([15/08/2021])PermalinkRapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning / Xin Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkUnsupervised representation high-resolution remote sensing image scene classification via contrastive learning convolutional neural network / Fengpeng Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 8 (August 2021)PermalinkApplying planetary mapping methods to submarine environments: onshore-offshore geomorphology of Christiana-Santorini-Kolumbo Volcanic Group, Greece / Alexandra E. Huff in Journal of maps, vol 17 n° 3 (July 2021)PermalinkEvaluating the suitability of multi-scale terrain attribute calculation approaches for seabed mapping applications / Benjamin Misiuk in Marine geodesy, vol 44 n° 4 (July 2021)PermalinkLa géovisualisation de données massives sur le Web : entre avancées technologiques et évolutions cartographiques / Boris Mericskay in Mappemonde, n° 131 (juillet 2021)PermalinkSpatio-temporal-spectral observation model for urban remote sensing / Zhenfeng Shao in Geo-spatial Information Science, vol 24 n° 3 (July 2021)PermalinkThe spread of the Mercator projection in Western European and United States cartography / Michele Abee in Cartographica, vol 56 n° 2 (Summer 2021)PermalinkUsing machine learning to map Western Australian landscapes for mineral exploration / Thomas Albrecht in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)PermalinkEye tracking research in cartography: Looking into the future / Vassilios Krassanakis in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)PermalinkReconsidering movement and exposure: Towards a more dynamic health geography / Malcolm Campbell in Geography compass, vol 15 n° 6 (June 2021)PermalinkEmotional cartography as a window into children's well-being: Visualizing the felt geographies of place / Andrew Steger in Emotion, Space and Society, vol 39 (May 2021)PermalinkEvaluating PPGIS usability in a multi-national field study combining qualitative surveys and eye-tracking / Mona Bartling in Cartographic journal (the), vol 58 n° 2 (May 2021)PermalinkFlood risk mapping using uncertainty propagation analysis on a peak discharge: case study of the Mille Iles River in Quebec / Jean-Marie Zokagoa in Natural Hazards, vol 107 n° 1 (May 2021)PermalinkGénération automatique de courbes de niveaux dans les zones de plateaux karstiques / Guillaume Touya in Cartes & Géomatique, n° 243-244 (mars - juin 2021)PermalinkLearning from multimodal and multitemporal earth observation data for building damage mapping / Bruno Adriano in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)PermalinkMapping and quantification of the dwarf eelgrass Zostera noltii using a random forest algorithm on a SPOT 7 satellite image / Salma Benmokhtar in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)PermalinkWhat is the difference between augmented reality and 2D navigation electronic maps in pedestrian wayfinding? / Weihua Dong in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)PermalinkDecision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping / Jiadi Yin in Remote sensing, vol 13 n° 8 (April-2 2021)PermalinkAn analysis of the spatial and temporal distribution of large‐scale data production events in OpenStreetMap / A. Yair Grinberger in Transactions in GIS, Vol 25 n° 2 (April 2021)PermalinkEvolution of the beaches in the regional Park of Salinas and Arenales of San Pedro del Pinatar (Southeast of Spain) (1899–2019) / Daniel Ibarra-Marinas in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)Permalink