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A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping / Zhice Fang 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 321 - 347 Titre : A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping Type de document : Article/Communication Auteurs : Zhice Fang, Auteur ; Yi Wang, Auteur ; Ling Peng, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 321 - 347 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] Chine [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] pondération [Termes descripteurs IGN] régression logistique [Termes descripteurs IGN] réseau neuronal récurrent [Termes descripteurs IGN] risque naturel Résumé : (auteur) This study introduces four heterogeneous ensemble-learning techniques, that is, stacking, blending, simple averaging, and weighted averaging, to predict landslide susceptibility in Yanshan County, China. These techniques combine several state-of-the-art classifiers of convolutional neural network, recurrent neural network, support vector machine, and logistic regression in specific ways to produce reliable results and avoid problems with the model selection. The study consists of three main steps. The first step establishes a spatial database consisting of 16 landslide conditioning factors and 380 historical landslide locations. The second step randomly selects training (70% of the total) and test (30%) datasets out of grid cells corresponding to landslide and non-slide locations in the study area. The final step constructs the proposed heterogeneous ensemble-learning methods for landslide susceptibility mapping. The proposed ensemble-learning methods show higher prediction accuracy than the individual classifiers mentioned above based on statistical measures. The blending ensemble-learning method achieves the highest overall accuracy of 80.70% compared to the other ensemble-learning methods. Numéro de notice : A2021-028 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1808897 date de publication en ligne : 15/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1808897 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96704 [article]

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 descripteurs IGN] carte ancienne [Termes descripteurs IGN] carte climatique [Termes descripteurs IGN] cartographie écologique [Termes descripteurs IGN] Chine [Termes descripteurs IGN] délimitation [Termes descripteurs IGN] données cartographiques [Termes descripteurs IGN] écorégion [Termes descripteurs IGN] extraction de données [Termes descripteurs IGN] logique floue [Termes descripteurs IGN] sous ensemble flou [Termes descripteurs 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 GIS- and AHP-based approach to map fire risk: a case study of Kuan Kreng peat swamp forest, Thailand / Narissara Nuthammachot in Geocarto international, vol 36 n° 2 ([01/02/2021])  

Public [article]  inGeocarto international > vol 36 n° 2 [01/02/2021] . - pp 212 - 225 Titre : A GIS- and AHP-based approach to map fire risk: a case study of Kuan Kreng peat swamp forest, Thailand Type de document : Article/Communication Auteurs : Narissara Nuthammachot, Auteur ; Dimitris Stratoulias, Auteur Année de publication : 2021 Article en page(s) : pp 212 - 225 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] climat [Termes descripteurs IGN] forêt marécageuse [Termes descripteurs IGN] historique des données [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] outil d'aide à la décision [Termes descripteurs IGN] prévention des risques [Termes descripteurs IGN] processus d'analyse hiérarchisée [Termes descripteurs IGN] Thaïlande [Termes descripteurs IGN] tourbière Résumé : (auteur) Forest fires are abrupt transformations of the natural ecosystem and management authorities are required to take preventive measures to tackle fire events. Geographic information system (GIS) is a powerful tool for providing information with a spatial context and analytical hierarchy process (AHP) is a well-established technique for multiple criteria decision making. In this study, GIS and AHP are combined to analyse seven fire-related factors related to climate, topography and human influence. Fire risk for a peat swamp forested area in Kuan Kreng, Nakorn Sri Thammarat province, Thailand is estimated in five categories. 705 historic fire events from 2006 to 2017 are used to validate our approach. 82% of the historic fire incidents occurred within the highest fire risk class categories while only a few omission errors were recorded. The combined approach of GIS and AHP techniques can yield useful fire risk maps, which can consequently be used for future planning and management of fire prone areas. Numéro de notice : A2021-083 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1611946 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1611946 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96832 [article]

Elevation models for reproducible evaluation of terrain representation / Patrick Kennelly in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 1 (January 2021) . - pp 63 - 77 Titre : Elevation models for reproducible evaluation of terrain representation Type de document : Article/Communication Auteurs : Patrick Kennelly, Auteur ; Tom Patterson, Auteur ; Bernhard Jenny, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 63 - 77 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes descripteurs IGN] altitude [Termes descripteurs IGN] données multiéchelles [Termes descripteurs IGN] figuré du terrain [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] réalité de terrain [Termes descripteurs IGN] relief [Termes descripteurs IGN] représentation du relief [Termes descripteurs IGN] reproductibilité [Termes descripteurs IGN] visualisation de données Résumé : (auteur) This paper proposes elevation models to promote, evaluate, and compare various terrain representation techniques. Our goal is to increase the reproducibility of terrain rendering algorithms and techniques across different scales and landscapes. We introduce elevation models of varying terrain types, available to the user at no cost, with minimal common data imperfections such as missing data values, resampling artifacts, and seams. Three multiscale elevation models are available, each consisting of a set of elevation grids, centered on the same geographic location, with increasing cell sizes and spatial extents. We also propose a collection of single-scale elevation models of archetypal landforms including folded ridges, a braided riverbed, active and stabilized sand dunes, and a volcanic caldera. An inventory of 78 publications with a total of 155 renderings illustrating terrain visualization techniques guided the selection of landform types in the elevation models. The benefits of using the proposed elevation models include straightforward comparison of terrain representation methods across different publications and better documentation of the source data, which increases the reproducibility of terrain representations. Numéro de notice : A2021-719 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1830856 date de publication en ligne : 04/11/2020 En ligne : https://doi.org/10.1080/15230406.2020.1830856 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96459 [article]

How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection / Junghwan Kim in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 1 (January 2021) . - pp 2 - 20 Titre : How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection Type de document : Article/Communication Auteurs : Junghwan Kim, Auteur ; Mei-Po Kwan, Auteur ; Margaret C. Levenstein, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2 - 20 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique [Termes descripteurs IGN] cartographie thématique [Termes descripteurs IGN] confidentialité [Termes descripteurs IGN] données personnelles [Termes descripteurs IGN] droit privé [Termes descripteurs IGN] entretien d'enquête [Termes descripteurs IGN] Geomasquage [Termes descripteurs IGN] information cartographique [Termes descripteurs IGN] photo-identification [Termes descripteurs IGN] protection de la vie privée [Termes descripteurs IGN] vulnérabilité Résumé : (auteur) This research examines how people subjectively perceive the disclosure risk of a map using original data collected in an online survey with 856 participants. The results indicate that perceived disclosure risk increases as the amount of locational information displayed on a map increases. Compared to point-based maps, perceived disclosure risk is significantly lower for kernel density maps, convex hull maps, and standard deviational ellipse maps. The results also revealed that perceived disclosure risk is affected by map scale and the presence of information of other people on a map. For geomasking methods, perceived disclosure risk decreases as aggregation level increases and as relocation distance increases. However, aggregation methods (point to polygon) are more effective in preventing the re-identification of individuals when compared to relocation methods (point to point). Lastly, the perceived disclosure risk of a map that displays socially-vulnerable people is significantly higher than that of a map that displays non-vulnerable groups. Specifically, a map displaying the private locations of elementary school students has the highest perceived disclosure risk. Based on the results, a set of geoprivacy protection guidelines for mapping people’s private locations to minimize people’s perceived disclosure risk is proposed. Implications for mapping infectious diseases like the COVID-19 are also discussed. Numéro de notice : A2021-016 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1794976 date de publication en ligne : 24/08/2020 En ligne : https://doi.org/10.1080/15230406.2020.1794976 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96451 [article]

A hybrid approach for recovering high-resolution temporal gravity fields from satellite laser ranging / Anno Löcher in Journal of geodesy, vol 95 n° 1 (January 2021)  

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Toward green cartography & visualization: a semantically-enriched method of generating energy-aware color schemes for digital maps / Yangli Han in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)  

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Unmixing-based Sentinel-2 downscaling for urban land cover mapping / Fei Xu in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

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Application of various strategies and methodologies for landslide susceptibility maps on a basin scale: the case study of Val Tartano, Italy / Vasil Yordanov in Applied geomatics, vol 12 n° 4 (December 2020)  

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The utility of fused airborne laser scanning and multispectral data for improved wind damage risk assessment over a managed forest landscape in Finland / Ranjith Gopalakrishnan in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

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Towards a new generation of digital cartography: The development of neocartography and the geoweb / Marina Tavra in Cartographica, vol 55 n° 4 (Winter 2020)  

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Visualization of 3D property data and assessment of the impact of rendering attributes / Stefan Seipel in Journal of Geovisualization and Spatial Analysis, vol 4 n° 2 (December 2020)  

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Bretagne, la végétation cartographiée / Marielle Mayo in Géomètre, n° 2185 (novembre 2020)

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Landslide susceptibility mapping using Naïve Bayes and Bayesian network models in Umyeonsan, Korea / Sunmin Lee in Geocarto international, vol 35 n° 15 ([01/11/2020])  

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Mapping uncertain geographical attributes: incorporating robustness into choropleth classification design / Wangshu Mu in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)  

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