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Vol 44 n° 5 - September 2017 - Special content sections: pointed innovations; bicycle mapping (Bulletin de Cartography and Geographic Information Science)
[n° ou bulletin]
est un bulletin de Cartography and Geographic Information Science / Cartography and geographic information society (1999 -)
Titre : Vol 44 n° 5 - September 2017 - Special content sections: pointed innovations; bicycle mapping Type de document : Périodique Année de publication : 2017 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] carte thématique
[Termes IGN] cartographie collaborative
[Termes IGN] données localisées des bénévolesNuméro de notice : 032-201705 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Numéro de périodique En ligne : http://www.tandfonline.com/toc/tcag20/44/5?nav=tocList Format de la ressource électronique : URL Sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=28805 [n° ou bulletin]Contient
- Point grid map : a new type of thematic map for statistical data associated with geographic points / Mengjie Zhou in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
- BinSq : visualizing geographic dot density patterns with gridded maps / Alvin Chua in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
- Crowdsourcing a cyclist perspective on suggested recreational paths in real-world networks / Kevin Baker in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
- An empirical evaluation of three elevation change symbolization methods along routes in bicycle maps / Annina Brügger in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
- Assessing professional benefits of GIS certification / Adam J. Mathews in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2017051 RAB Revue Centre de documentation En réserve L003 Disponible Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data / Timo P Pitkänen in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
[article]
Titre : Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data Type de document : Article/Communication Auteurs : Timo P Pitkänen, Auteur ; Niina Käyhkö, Auteur Année de publication : 2017 Article en page(s) : pp 150 - 161 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse diachronique
[Termes IGN] arbre (flore)
[Termes IGN] boisement naturel
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité des points
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur de classification
[Termes IGN] image Landsat
[Termes IGN] orthoimage
[Termes IGN] prairie
[Termes IGN] structure de données localiséesRésumé : (Auteur) Mapping structural changes in vegetation dynamics has, for a long time, been carried out using satellite images, orthophotos and, more recently, airborne lidar acquisitions. Lidar has established its position as providing accurate material for structure-based analyses but its limited availability, relatively short history, and lack of spectral information, however, are generally impeding the use of lidar data for change detection purposes. A potential solution in respect of detecting both contemporary vegetation structures and their previous trajectories is to combine lidar acquisitions with optical remote sensing data, which can substantially extend the coverage, span and spectral range needed for vegetation mapping. In this study, we tested the simultaneous use of a single low-density lidar data set, a series of Landsat satellite frames and two high-resolution orthophotos to detect vegetation succession related to grassland overgrowth, i.e. encroachment of woody plants into semi-natural grasslands. We built several alternative Random Forest models with different sets of variables and tested the applicability of respective data sources for change detection purposes, aiming at distinguishing unchanged grassland and woodland areas from overgrown grasslands. Our results show that while lidar alone provides a solid basis for indicating structural differences between grassland and woodland vegetation, and orthophoto-generated variables alone are better in detecting successional changes, their combination works considerably better than its respective parts. More specifically, a model combining all the used data sets reduces the total error from 17.0% to 11.0% and omission error of detecting overgrown grasslands from 56.9% to 31.2%, when compared to model constructed solely based on lidar data. This pinpoints the efficiency of the approach where lidar-generated structural metrics are combined with optical and multitemporal observations, providing a workable framework to identify structurally oriented and dynamically organized landscape phenomena, such as grassland overgrowth. Numéro de notice : A2017-513 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.05.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.05.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86459
in ISPRS Journal of photogrammetry and remote sensing > vol 130 (August 2017) . - pp 150 - 161[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt A relative evaluation of random forests for land cover mapping in an urban area / Di Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 8 (August 2017)
[article]
Titre : A relative evaluation of random forests for land cover mapping in an urban area Type de document : Article/Communication Auteurs : Di Shi, Auteur ; Xiaojun Yang, Auteur Année de publication : 2017 Article en page(s) : pp 541 - 552 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] objet géographique complexe
[Termes IGN] occupation du sol
[Termes IGN] Perceptron multicouche
[Termes IGN] zone urbaineRésumé : (auteur) Random forests as a novel ensemble learning algorithm have significant potential for land cover mapping in complex areas but have not been sufficiently tested by the remote sensing community relative to some more popular pattern classifiers. In this research, we implemented random forests as a pattern classifier for land cover mapping from a satellite image covering a complex urban area, and evaluated the performance relative to several popular classifiers including Gaussian maximum likelihood (GML), multi-layer-perceptron networks (MLP), and support vector machines (SVM). Each classifier was carefully configured with the parameter settings recommended by recent literature, and identical training data were used in each classification. The accuracy of each classified map was further evaluated using identical reference data. Random forests were slightly more accurate than SVM and MLP but significantly better than GML in the overall map accuracy. Random forests and support vector machines generated almost identical overall map accuracy, but the former produced a smaller standard deviation of categorical accuracies, suggesting its better overall capability in classifying both homogeneous and heterogeneous land cover classes. Random forests have shown its robustness due to the most accurate classification on the whole, relatively balanced performance across all land cover categories, and relatively easier to implement. These findings should help promote the use of random forests for land cover classification in complex areas. Numéro de notice : A2017-435 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.14358/PERS.83.8.541 En ligne : https://doi.org/10.14358/PERS.83.8.541 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86339
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 8 (August 2017) . - pp 541 - 552[article]Developing detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor / Abel Chemura in Geocarto international, vol 32 n° 7 (July 2017)
[article]
Titre : Developing detailed age-specific thematic maps for coffee (Coffea arabica L.) in heterogeneous agricultural landscapes using random forests applied on Landsat 8 multispectral sensor Type de document : Article/Communication Auteurs : Abel Chemura, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2017 Article en page(s) : pp 759 - 776 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte agricole
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] Coffea arabica
[Termes IGN] cultures
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] image multibande
[Termes IGN] précision de la classification
[Termes IGN] rayonnement proche infrarougeRésumé : (Auteur) Coffee is a commodity of international trade significance, and its value chain can benefit from age-specific thematic maps. This study aimed to assess the potential of Landsat 8 OLI to develop these maps. Using field-collected samples with the random forest classifier, splitting coffee into three age classes (Scheme A) was compared with running the classification with one compound coffee class (Scheme B). Higher overall classification accuracy was obtained in Scheme B (90.3% for OLI and 86.8% for ETM+) than in Scheme A (86.2% for OLI and 81.0% for ETM+). The NIR band of OLI was the most important band in intra-class discrimination of coffee. Landsat 8 OLI mapped area closely matched farm records (R2 = 0.88) compared to that of Landsat 7 ETM+ (R2 = 0.78). It was concluded that Landsat 8 OLI data can be used to produce age-specific thematic maps in coffee production areas although disaggregating coffee classes reduces overall accuracy. Numéro de notice : A2017-454 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1178812 Date de publication en ligne : 03/05/2016 En ligne : http://dx.doi.org/10.1080/10106049.2016.1178812 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86374
in Geocarto international > vol 32 n° 7 (July 2017) . - pp 759 - 776[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2017071 RAB Revue Centre de documentation En réserve L003 Disponible Domains of uncertainty visualization research: a visual summary approach / Jennifer Smith Mason in Cartography and Geographic Information Science, Vol 44 n° 4 (July 2017)
[article]
Titre : Domains of uncertainty visualization research: a visual summary approach Type de document : Article/Communication Auteurs : Jennifer Smith Mason, Auteur ; David Retchless, Auteur ; Alexander Klippel, Auteur Année de publication : 2017 Article en page(s) : pp 296 - 309 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique
[Termes IGN] carte heuristique
[Termes IGN] carte synthétique
[Termes IGN] classification
[Termes IGN] incertitude des données
[Termes IGN] interface web
[Termes IGN] visualisationRésumé : (auteur) The inherent uncertainty of geospatial data has engendered a critical research agenda addressing all facets of uncertainty visualization due to the communicative efficiency of graphical representation. To organize this broad research area, we have reviewed literature on geospatial uncertainty visualization and systematically and iteratively classified research in this field. Upon creating a classification, we developed several visual summaries over time, refining the classification and subsequent graphic as new relevant topics emerged. This visual summary extends current existing approaches to taxonomies by allowing users a quick visual overview of relevant topics in a research area at a glance. For each research paper on uncertainty visualization, this classification can be used to visually represent which domains are covered. In order to ensure that the visual summary approach and the corresponding domains developed in this article can be used reliably, we performed an inter-rater agreement task. The high agreement reveals that the domains in the classification that were identified are intuitive and can lead to objective, reproducible classifications (visual summaries) of research papers. In future research, we plan to refine the visual classification/summary approach by providing guided classification via a web interface to visually classify the entire body of literature on geospatial uncertainty visualization and visually explore any trends in research topics, how they have changed over the years, and identify sparser topics that still need to be addressed. Numéro de notice : A2017-223 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2016.1154804 En ligne : http://dx.doi.org/10.1080/15230406.2016.1154804 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85104
in Cartography and Geographic Information Science > Vol 44 n° 4 (July 2017) . - pp 296 - 309[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2017041 RAB Revue Centre de documentation En réserve L003 Disponible Fusion of RADARSAT-2 and multispectral optical remote sensing data for LULC extraction in a tropical agricultural area / Mohamed Barakat A. Gibril in Geocarto international, vol 32 n° 7 (July 2017)PermalinkMap the gap: alternative visualisations of geographic knowledge production / Margath Walker in Geo: Geography and Environment, vol 4 n°2 (July 2017)PermalinkSafe separation distance score : a new metric for evaluating wildland firefighter safety zones using lidar / Michael J. Campbell in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)PermalinkSuperresolution for UAV images via adaptive multiple sparse representation and its application to 3-D reconstruction / Muhammad Haris in IEEE Transactions on geoscience and remote sensing, vol 55 n° 7 (July 2017)PermalinkPermalinkDIOGEN, a multi-level oriented model for cartographic generalization / Adrien Maudet in International journal of cartography, vol 3 n° 1 (June 2017)PermalinkMonitoring mangrove biomass change in Vietnam using SPOT images and an object-based approach combined with machine learning algorithms / Lien T.H. Pham in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)PermalinkNatura 2000 protected habitats, Massaciuccoli Lake (northern Tuscany, Italy) / Daniele Viciani in Journal of maps, vol 13 n° 2 ([01/06/2017])PermalinkViCTOr : paysage virtuel pour explorer les dynamiques de la VIticulture et de la Consommation en TouRaine / Etienne Delay in Cybergeo, European journal of geography, n° 2017 ([01/06/2017])PermalinkInvestigating the potential of deep neural networks for large-scale classification of very high resolution satellite images / Tristan Postadjian in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-1/W1 (May 2017)PermalinkAn ontology-driven multi-agent system for nautical chart generalization / Jingya Yan in Cartography and Geographic Information Science, Vol 44 n° 3 (May 2017)PermalinkDescription formelle de trajectoire de navigation en environnement maritime côtier / Wissame Laddada in Revue internationale de géomatique, vol 27 n° 2 (avril - juin 2017)PermalinkMapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)PermalinkMapping spatial distribution of forest age in China / Yuan Zhang in Earth and space science, vol 4 n° 3 (March 2017)PermalinkAgricultural cropland mapping using black-and-white aerial photography, Object-Based Image Analysis and Random Forests / M.F.A. Vogels in International journal of applied Earth observation and geoinformation, vol 54 (February 2017)PermalinkDelineation of groundwater potential zones using remote sensing and GIS-based data-driven models / Samira Ghorbani Nejad in Geocarto international, vol 32 n° 2 (February 2017)PermalinkIntegrating elevation data and multispectral high-resolution images for an improved hybrid Land Use/Land Cover mapping / Mirco Sturari in European journal of remote sensing, vol 50 n° 1 (2017)PermalinkAnalyse et cartographie des sentiments dans des récits de vie de migrants / Catherine Dominguès (2017)PermalinkAnalyse de séries temporelles d’images Sentinel et intégration de connaissances pour la classification en milieu agricole / Simon Bailly (2017)PermalinkPermalinkCartographie de l'occupation des sols à partir de séries temporelles d'images satellitaires à hautes résolutions : identification et traitement des données mal étiquetées / Charlotte Pelletier (2017)PermalinkLe commentaire de carte topographique / Camille Tiano (2017)PermalinkContributions méthodologiques pour la caractérisation des milieux par imagerie optique et lidar / Nesrine Chehata (2017)PermalinkPermalinkLa géomatique comme aide à la décision dans le domaine de la santé / Lise Le Lann (2017)PermalinkLearning-based spatial-temporal superresolution mapping of forest cover with MODIS images / Yihang Zhang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)PermalinkPermalinkLes prairies de l’estuaire de la Loire : étude de la dynamique de la végétation de 1982 à 2014 / Mathieu Le Dez in Mappemonde, n° 119 (janvier 2017)PermalinkRéalisation d’une carte de synthèse nationale des continuités écologiques régionales / Lucille Billon (2017)PermalinkRefonte de l’intranet cartographique dynamique du Parc national de la Guadeloupe / Anthony Clet (2017)PermalinkSols artificialisés et processus d’artificialisation des sols : déterminants, impacts et leviers d’action / Béatrice Béchet (2017)PermalinkSVM et réseaux neuronaux convolutifs pour la classification de scènes urbaines / Amaury Zarzelli (2017)PermalinkTélédétection pour l'observation des surfaces continentales, Volume 3. Observation des surfaces continentales par télédétection 1 / Nicolas Baghdadi (2017)PermalinkAssessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas / Charlotte Pelletier in Remote sensing of environment, vol 187 (15 December 2016)PermalinkAn iterative interpolation deconvolution algorithm for superresolution land cover mapping / Feng Ling in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkCartographie de la dynamique de terroirs villageois à l’aide d’un drone dans les aires protégées de la République démocratique du Congo / Jean Semeki Ngabinzeke in Bois et forêts des tropiques, n° 330 (4e trimestre 2016)PermalinkSymbolize map distortion with inscribed circles in polygons / Shipeng Sun in International journal of cartography, vol 2 n° 2 (December 2016)PermalinkUrban damage level mapping based on scattering mechanism investigation using fully polarimetric SAR Data for the 3.11 East Japan earthquake / Si-Wei Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkAssimilation of SMOS retrievals in the land information system / Clay B. Blankenship in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)PermalinkA new climatology of maximum and minimum temperature (1951–2010) in the Spanish mainland: a comparison between three different interpolation methods / D. Peña-Angulo in International journal of geographical information science IJGIS, vol 30 n° 11-12 (November - December 2016)PermalinkAméliorer la perception du réalisme dans la géovisualisation du littoral : Utilisation de données spatiotemporelles hétérogènes / Antoine Masse in Revue internationale de géomatique, vol 26 n° 4 (octobre - décembre 2016)PermalinkCHP toolkit : case study of LAIe sensitivity to discontinuity of canopy cover in fruit plantations / Karolina D. Fieber in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkEstimating forest species abundance through linear unmixing of CHRIS/PROBA imagery / S. Stagakis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkInteractive map to illustrate seat distributions of political party support levels : a web GIS application / Yifei Chen in Cartographica, vol 51 n° 3 (Fall 2016)PermalinkMapping of land cover in northern California with simulated hyperspectral satellite imagery / Matthew L. Clark in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)Permalink