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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)  

Public [article]  inApplied geomatics > vol 12 n° 4 (December 2020) . - 23 p. Titre : Application of various strategies and methodologies for landslide susceptibility maps on a basin scale: the case study of Val Tartano, Italy Type de document : Article/Communication Auteurs : Vasil Yordanov, Auteur ; Maria Antonia Brovelli, Auteur Année de publication : 2020 Article en page(s) : 23 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse de sensibilité [Termes IGN] cartographie des risques [Termes IGN] cartographie géomorphologique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] effondrement de terrain [Termes IGN] figuré linéaire [Termes IGN] indice de risque [Termes IGN] inventaire [Termes IGN] Lombardie [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de terrain [Termes IGN] modèle statistique [Termes IGN] régression logistique Résumé : (auteur) Landslide susceptibility mapping is a crucial initial step in risk mitigation strategies. Landslide hazards are widely spread all over the world and, as such, mapping the relevant susceptibility levels is in constant research and development. As a result, numerous modelling techniques and approaches have been adopted by scholars, implementing these models at different scales and with different terrains, in search of the best-performing strategy. Nevertheless, a direct comparison is not possible unless the strategies are implemented under the same environmental conditions and scenarios. The aim of this work is to implement three statistical-based models (Statistical Index, Logistic Regression, and Random Forest) at the basin scale, using various scenarios for the input datasets (terrain variables), training samples and ratios, and validation metrics. A reassessment of the original input data was carried out to improve the model performance. In total, 79 maps were obtained using different combinations with some highly satisfactory outcomes and others that are barely acceptable. Random Forest achieved the highest scores in most of the cases, proving to be a reliable modelling approach. While Statistical Index passes the evaluation tests, most of the resulting maps were considered unreliable. This research highlighted the importance of a complete and up-to-date landslide inventory, the knowledge of local conditions, as well as the pre- and post-analysis evaluation of the input and output combinations. Numéro de notice : A2020-695 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00344-1 Date de publication en ligne : 09/11/2020 En ligne : https://doi.org/10.1007/s12518-020-00344-1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96244 [article]

Automatic building footprint extraction from UAV images using neural networks / Zoran Kokeza in Geodetski vestnik, vol 64 n° 4 (December 2020 - February 2021)  

Public [article]  inGeodetski vestnik > vol 64 n° 4 (December 2020 - February 2021) . - pp 545 - 561 Titre : Automatic building footprint extraction from UAV images using neural networks Type de document : Article/Communication Auteurs : Zoran Kokeza, Auteur ; Miroslav Vujasinović, Auteur ; Miro Govedarica, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 545 - 561 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] cartographie cadastrale [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] détection du bâti [Termes IGN] empreinte [Termes IGN] image à haute résolution [Termes IGN] image captée par drone [Termes IGN] image RVB [Termes IGN] modèle numérique de surface [Termes IGN] orthoimage [Termes IGN] zone d'intérêt Résumé : (Auteur) Up-to-date cadastral maps are crucial for urban planning. Creating those maps with the classical geodetic methods is expensive and time-consuming. Emerge of Unmanned Aerial Vehicles (UAV) made a possibility for quick acquisition of data with much more details than it was possible before. The topic of the research refers to the challenges of automatic extraction of building footprints on high-resolution orthophotos. The objectives of this study were as follows: (1) to test the possibility of using different publicly available datasets (Tanzania, AIRS and Inria) for neural network training and then test the generalisation capability of the model on the Area Of Interest (AOI); (2) to evaluate the effect of the normalised digital surface model (nDSM) on the results of neural network training and implementation. Evaluation of the results shown that the models trained on the Tanzania (IoU 36.4%), AIRS (IoU 64.4%) and Inria (IoU 7.4%) datasets doesn't satisfy the requested accuracy to update cadastral maps in study area. Much better results are achieved in the second part of the study, where the training of the neural network was done on tiles (256x256) of the orthophoto of AOI created from data acquired using UAV. A combination of RGB orthophoto with nDSM resulted in a 2% increase of IoU, achieving the final IoU of over 90%. Numéro de notice : A2020-777 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.15292/geodetski-vestnik.2020.04.545-561 Date de publication en ligne : 26/10/2020 En ligne : http://www.geodetski-vestnik.com/en/2020-4 Format de la ressource électronique : URL bulletin Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96706 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
139-2020041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Florence: A web-based grammar of graphics for making maps and learning cartography / Ate Poorthuis in Cartographic perspectives, n° 96 (December 2020)  

Public [article]  inCartographic perspectives > n° 96 (December 2020) . - pp 32 - 50 Titre : Florence: A web-based grammar of graphics for making maps and learning cartography Type de document : Article/Communication Auteurs : Ate Poorthuis, Auteur ; Lucas van der Zee, Auteur ; Grace Guo, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 32 - 50 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cartographie par internet [Termes IGN] conception cartographique [Termes IGN] formation [Termes IGN] géovisualisation [Termes IGN] implémentation (informatique) [Termes IGN] représentation cartographique [Termes IGN] sémiologie graphique [Termes IGN] visualisation cartographique [Termes IGN] visualisation de données [Termes IGN] web mapping [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Online, web-based cartography workflows use a dizzying variety of software suites, libraries, and programming languages. This proliferation of mapmaking technologies, often developed from a software engineering rather than a cartographic foundation, creates a series of challenges for cartography education, research, and practice. To address these challenges, we introduce a JavaScript-based open-source framework for web-based cartography and data visualization. It is built on top of existing open web standards that are already in intensive use for online mapmaking today, but provides a framework that is firmly based on cartographic and visualization theory rather than software engineering concepts. Specifically, we adopt concepts from Bertin’s Semiology of Graphics and Wilkinson’s Grammar of Graphics to create a language with a limited number of core concepts and verbs that are combined in a declarative style of “writing” visualizations. In this paper, we posit a series of design guidelines that have informed our approach, and discuss how we translate these tenets into a software implementation and framework with specific use cases and examples. We frame the development of the software and the discussion specifically in the context of the use of such tools in cartography education. With this framework, we hope to provide an example of a software for web-based data visualization that is in sync with cartographic theories and objectives. Such approaches allow for potentially greater cartographic flexibility and creativity, as well as easier adoption in cartography courses. Numéro de notice : A2021-123 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.14714/CP96.1645 Date de publication en ligne : 02/12/2020 En ligne : https://doi.org/10.14714/CP96.1645 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99306 [article]

Geomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) / Marcello Buccolini in Journal of maps, vol 16 n° 3 ([01/12/2020])  

Public [article]  inJournal of maps > vol 16 n° 3 [01/12/2020] . - pp 10 - 18 Titre : Geomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) Type de document : Article/Communication Auteurs : Marcello Buccolini, Auteur ; Cristiano Carabella, Auteur ; Giorgio Paglia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 10 - 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] 1:5.000 [Termes IGN] analyse des risques [Termes IGN] archipel [Termes IGN] cartographie géologique [Termes IGN] données de terrain [Termes IGN] géologie locale [Termes IGN] géomorphologie locale [Termes IGN] Italie [Termes IGN] morphométrie Résumé : (auteur) The 2019 Geomorphological Field Camp at San Domino Island (Tremiti Islands, Southern Adriatic Sea) is the result of geological and geomorphological field work activities carried out by a group of students attending the Geomorphological field mapping course of the Master’s Degree in Geological Science and Technology (University of Chieti-Pescara). The main map (1:5000 scale) was obtained through an integrated approach that incorporates morphometric analysis, geological and geomorphological field mapping, and geomorphological profiles drawing. Activities were carried out by all students, divided into six working groups of three to four persons each. The field camp and field work activities made it possible to produce a detailed thematic map, as a scientific tool to depict the San Domino Island landscape, and to outline some geomorphological issues in terms of possible constraints to landscape evolution, geomorphological processes distribution, and natural hazard assessment. Numéro de notice : A2020-816 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/17445647.2020.1831979 Date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1080/17445647.2020.1831979 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96982 [article]

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, vol 77 n° 4 (December 2020)  

Public [article]  inAnnals of Forest Science > vol 77 n° 4 (December 2020) . - 18 p. Titre : The utility of fused airborne laser scanning and multispectral data for improved wind damage risk assessment over a managed forest landscape in Finland Type de document : Article/Communication Auteurs : Ranjith Gopalakrishnan, Auteur ; Petteri Packalen, Auteur ; Veli-Pekka Ikonen, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] cartographie des risques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Finlande [Termes IGN] forêt [Termes IGN] forêt boréale [Termes IGN] image multibande [Termes IGN] modèle de simulation [Termes IGN] risque naturel [Termes IGN] tempête [Termes IGN] vent [Termes IGN] zone à risque Résumé : (auteur) Key message: The potential of airborne laser scanning (ALS) and multispectral remote sensing data to aid in generating improved wind damage risk maps over large forested areas is demonstrated. This article outlines a framework to generate such maps, primarily utilizing the horizontal structural information contained in the ALS data. Validation was done over an area in Eastern Finland that had experienced sporadic wind damage. Context: Wind is the most prominent disturbance element for Finnish forests. Hence, tools are needed to generate wind damage risk maps for large forested areas, and their possible changes under planned silvicultural operations. Aims: (1) How effective are ALS-based forest variables (e.g. distance to upwind forest stand edge, gap size) for identifying high wind damage risk areas? (2) Can robust estimates of predicted critical wind speeds for uprooting of trees be derived from these variables? (3) Can these critical wind speed estimates be improved using wind multipliers, which factor in topography and terrain roughness effects? Methods: We first outline a framework to generate several wind damage risk–related parameters from remote sensing data (ALS + multispectral). Then, we assess if such parameters have predictive power. That is, whether they help differentiate between damaged and background points. This verification exercise used 42 wind damaged points spread over a large area. Results: Parameters derived from remote sensing data are shown to have predictive power. Risk models based on critical wind speeds are not that robust, but show potential for improvement. Conclusion: Overall, this work described a framework to get several wind risk–related parameters from remote sensing data. These parameters are shown to have potential in generating wind damage risk maps over large forested areas. Numéro de notice : A2020-629 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00992-8 Date de publication en ligne : 09/10/2020 En ligne : https://doi.org/10.1007/s13595-020-00992-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96045 [article]

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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Cadastral development in Norway: the need for improvement / Leiv Bjarte Mjøs in Survey review, vol 52 n° 375 (November 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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Modalflow: cross-origin flow data visualization for urban mobility / Ignacio Pérez-Messina in Algorithms, vol 13 n° 11 (November 2020)  

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A multi-scale representation model of polyline based on head/tail breaks / Pengcheng Liu in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)  

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Soil erosion assessment using RUSLE model and its validation by FR probability model / Amiya Gayen in Geocarto international, vol 35 n° 15 ([01/11/2020])  

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Topographic connection method for automated mapping of landslide inventories, study case: semi urban sub-basin from Monterrey, Northeast of México / Nelly L. Ramirez Serrato in Geocarto international, vol 35 n° 15 ([01/11/2020])  

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