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GIS-based spatial landslide distribution analysis of district Neelum, AJ&K, Pakistan / Shah Naseer in Natural Hazards, vol 106 n° 1 (March 2021)
[article]
Titre : GIS-based spatial landslide distribution analysis of district Neelum, AJ&K, Pakistan Type de document : Article/Communication Auteurs : Shah Naseer, Auteur ; Tanveer Ul Haq, Auteur ; Abdullah Khan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 965 - 989 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] ArcGIS
[Termes IGN] distribution spatiale
[Termes IGN] effondrement de terrain
[Termes IGN] fréquence
[Termes IGN] Google Earth
[Termes IGN] lit majeur
[Termes IGN] modèle numérique de surface
[Termes IGN] Pakistan
[Termes IGN] réseau hydrographique
[Termes IGN] réseau routier
[Termes IGN] sismicitéRésumé : (auteur) The Landslide happens in mountainous regions due to the catastrophe of slope through intensive rain and seismicity. The Himalayas is one of the susceptible parts of the world in the perspective of slope catastrophe hazard; i.e., Mass Movement, especially Neelum valley is considerable destruction of community infrastructure, highway, and critically disturbed the tourism segment. Landslide is a common and recurrent phenomenon in the northern mountainous terrain of Pakistan such as District Neelum. After the 2005 Kashmir earthquake, the importance of landslide investigation is increasing. The purpose of this research is to establish a brief landslide inventory and to determine the relationship of landslides with causative factors by spatial distribution analysis. With the aid of Google Earth imageries and field visits, a total of 618 landslides were identified in the study area of 3621 km. These landslide localities compared with causative factors. Finally, distribution maps are generated and analyse their feature class through Digital Elevation Model and ArcGIS. Landslide intensity is calculated in terms of landslide concentration. Landslide concentration (LC) is significantly found very high in slope gradient less than 30 (1.21) and the first 100 m zone around the road network (15.06). A bit higher landslide frequency is noted in east orienting slopes. In the first 100 m, zone road network and drainage networks are 83.49% and 62.78% of the total landslide occurs having LC value 4.6, respectively. The analysis shows that the steep slopes, an area closer to the road network, drainage network, barren lands, and Quaternary alluvium of loose material are more susceptible to landslides. In addition, a landslide classification map is also prepared on the basis of field observation that shows that debris slides are more dominating. Numéro de notice : A2021-420 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-021-04502-5 Date de publication en ligne : 21/01/2021 En ligne : https://doi.org/10.1007/s11069-021-04502-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97770
in Natural Hazards > vol 106 n° 1 (March 2021) . - pp 965 - 989[article]Landslide susceptibility mapping and assessment using geospatial platforms and weights of evidence (WoE) method in the indian Himalayan region: Recent developments, gaps, and future directions / Amit Batar in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)
[article]
Titre : Landslide susceptibility mapping and assessment using geospatial platforms and weights of evidence (WoE) method in the indian Himalayan region: Recent developments, gaps, and future directions Type de document : Article/Communication Auteurs : Amit Batar, Auteur ; Teiji Watanabe, Auteur Année de publication : 2021 Article en page(s) : n° 114 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse bivariée
[Termes IGN] analyse de sensibilité
[Termes IGN] bassin hydrographique
[Termes IGN] cartographie des risques
[Termes IGN] effondrement de terrain
[Termes IGN] géomorphologie locale
[Termes IGN] Google Earth
[Termes IGN] Himalaya
[Termes IGN] Inde
[Termes IGN] inventaire
[Termes IGN] système d'information géographique
[Termes IGN] théorème de BayesRésumé : (auteur) The Himalayan region and hilly areas face severe challenges due to landslide occurrences during the rainy seasons in India, and the study area, i.e., the Rudraprayag district, is no exception. However, the landslide related database and research are still inadequate in these landslide-prone areas. The main purpose of this study is: (1) to prepare the multi-temporal landslide inventory map using geospatial platforms in the data-scarce environment; (2) to evaluate the landslide susceptibility map using weights of evidence (WoE) method in the Geographical Information System (GIS) environment at the district level; and (3) to provide a comprehensive understanding of recent developments, gaps, and future directions related to landslide inventory, susceptibility mapping, and risk assessment in the Indian context. Firstly, 293 landslides polygon were manually digitized using the BHUVAN (Indian earth observation visualization) and Google Earth® from 2011 to 2013. Secondly, a total of 14 landslide causative factors viz. geology, geomorphology, soil type, soil depth, slope angle, slope aspect, relative relief, distance to faults, distance to thrusts, distance to lineaments, distance to streams, distance to roads, land use/cover, and altitude zones were selected based on the previous study. Then, the WoE method was applied to assign the weights for each class of causative factors to obtain a landslide susceptibility map. Afterward, the final landslide susceptibility map was divided into five susceptibility classes (very high, high, medium, low, and very low classes). Later, the validation of the landslide susceptibility map was checked against randomly selected landslides using IDRISI SELVA 17.0 software. Our study results show that medium to very high landslide susceptibilities had occurred in the non-forest areas, mainly scrubland, pastureland, and barren land. The results show that medium to very high landslide susceptibilities areas are in the upper catchment areas of the Mandakini river and adjacent to the National Highways (107 and 07). The results also show that landslide susceptibility is high in high relative relief areas and shallow soil, near thrusts and faults, and on southeast, south, and west-facing steep slopes. The WoE method achieved a prediction accuracy of 85.7%, indicating good accuracy of the model. Thus, this landslide susceptibility map could help the local governments in landslide hazard mitigation, land use planning, and landscape protection. Numéro de notice : A2021-233 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10030114 Date de publication en ligne : 27/02/2021 En ligne : https://doi.org/10.3390/ijgi10030114 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97228
in ISPRS International journal of geo-information > vol 10 n° 3 (March 2021) . - n° 114[article]
Titre : Artificial neural networks in agriculture Type de document : Monographie Auteurs : Sebastian Kujawa, Éditeur scientifique ; Gniewko Niedbała, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 283 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-3-0365-1579-3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture
[Termes IGN] apprentissage profond
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par réseau neuronal récurrent
[Termes IGN] couvert végétal
[Termes IGN] déformation temporelle dynamique (algorithme)
[Termes IGN] détection d'arbres
[Termes IGN] Google Earth
[Termes IGN] image à haute résolution
[Termes IGN] phénologie
[Termes IGN] réseau neuronal artificiel
[Termes IGN] surveillance agricoleRésumé : (éditeur) Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible. Note de contenu : 1- Plant and weed identifier robot as an agroecological tool using artificial neural networks for image identification
2- Oil palm tree detection and health classification on high-resolution imagery using deep learning
3- Average degree of coverage and coverage unevenness coefficient as parameters for spraying quality assessment
4- The relationship between soil electrical parameters and compaction of Sandy Clay Loam soil
5- Evaluation of convolutional neural networks’ hyperparameters with transfer learning to determine sorting of Ripe Medjool dates
6- Mapping paddy rice using weakly supervised long short-term memory network with time series sentinel optical and SAR images
7- Time series prediction with artificial neural networks: An analysis using Brazilian soybean production
8- Machine learning for plant breeding and biotechnology
9- A hybrid CFS filter and RF-RFE wrapper-based feature extraction for enhanced agricultural crop yield prediction modeling
10- Crop growth stage GPP-driven spectral model for evaluation of cultivated land quality using GA-BPNN
11- Corn grain yield estimation from vegetation indices, canopy cover, plant density, and a neural network using multispectral and RGB images acquired with unmanned aerial vehicles
12- Modeling the dynamic response of plant growth to root zone temperature in hydroponic Chili pepper plant using neural networks
13- ANN-based continual classification in agriculture
14- Application of artificial neural networks to analyze the concentration of ferulic acid, deoxynivalenol, and nivalenol in winter wheat grain
15- Neural visual detection of grain weevil (sitophilus granarius L.)Numéro de notice : 28624 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-1579-3 En ligne : https://doi.org/10.3390/books978-3-0365-1579-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99553
Titre : Spatial dataset search: Building a dedicated knowledge graph Type de document : Article/Communication Auteurs : Mehdi Zrhal , Auteur ; Bénédicte Bucher , Auteur ; Marie-Dominique Van Damme , Auteur ; Fayçal Hamdi , Auteur Editeur : AGILE Alliance Année de publication : 2021 Projets : 1-Pas de projet / Conférence : AGILE 2021, 24th AGILE Conference on Geographic Information Science 19/07/2021 22/07/2021 Aurora Colorado - Etats-Unis OA Proceedings Importance : 5 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] découverte de connaissances
[Termes IGN] données massives
[Termes IGN] données ouvertes
[Termes IGN] graphe
[Termes IGN] INSPIRE
[Termes IGN] jeu de données localisées
[Termes IGN] précision sémantique
[Termes IGN] recherche d'information géographique
[Termes IGN] requête spatiale
[Termes IGN] réseau sémantique
[Termes IGN] ressources web
[Termes IGN] service web géographique
[Termes IGN] terminologie
[Termes IGN] web des données
[Termes IGN] web sémantique géolocaliséRésumé : (auteur) A growing number of spatial datasets are published every year. These can usually be found in dedicated web portals with different structures and specificities. However, finding the dataset that fits user needs is a real challenge as prior knowledge of these portals is needed to retrieve it efficiently. In this article, we present the problem of spatial dataset search and how the use of a geographic Knowledge Graph could improve it. A proposed direction for future work, ex-tending these contributions, is then presented. Numéro de notice : C2021-008 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/agile-giss-2-43-2021 En ligne : https://doi.org/10.5194/agile-giss-2-43-2021 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97855 Florence: A web-based grammar of graphics for making maps and learning cartography / Ate Poorthuis in Cartographic perspectives, n° 96 (December 2020)
[article]
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] GéovisualisationRésumé : (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
in Cartographic perspectives > n° 96 (December 2020) . - pp 32 - 50[article]Infrastructure of the spatial information in the European Community (INSPIRE) based on examples of Italy and Poland / Marek Ogryzek in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)PermalinkTowards a new generation of digital cartography: The development of neocartography and the geoweb / Marina Tavra in Cartographica, vol 55 n° 4 (Winter 2020)PermalinkThe influence of web maps and education on adolescents’ global-scale cognitive map / Lieselot Lapon in Cartographic journal (the), Vol 57 n° 3 (August 2020)PermalinkInspire : un investissement rapidement rentabilisé / Anonyme in Géomètre, n° 2182 (juillet - août 2020)PermalinkIntegrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images / Wen Dai in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)PermalinkData scale as cartography: a semi-automatic approach for thematic web map creation / Auriol Degbelo in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)PermalinkCreation of inspirational Web Apps that demonstrate the functionalities offered by the ArcGIS API for JavaScript / Arthur Genet (2020)PermalinkDéveloppement d’outils ad-hoc open source pour des applications Web cartographiques / Bruno Verchère (2020)PermalinkPermalinkInitiatives for Providing Data and Tools for Research and Education: EuroSDR survey / Bénédicte Bucher (2020)PermalinkPermalinkPermalinkRapport d'activité 2019 de l'Institut National de l'Information Géographique et Forestière IGN / Institut national de l'information géographique et forestière (2012 -) (2020)PermalinkBertin’s graphic variables and online map makers: an empirical study of maps produced by prosumers and cartographers / Natalia Ipatow in Cartographica, vol 54 n° 4 (Winter 2019)PermalinkA two-scale approach for estimating forest aboveground biomass with optical remote sensing images in a subtropical forest of Nepal / Upama A. Koju in Journal of Forestry Research, vol 30 n° 6 (December 2019)PermalinkMultiple-view geospatial comparison using web-based virtual globes / Liangfeng Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkBridging open source tools and geoportals for interactive spatial data analytics / Bing She in Geo-spatial Information Science, vol 22 n° 3 (August 2019)PermalinkAnalysis of free image-based modelling systems applied to support topographic measurements / José Miguel Caldera-Cordero in Survey review, vol 51 n° 367 (July 2019)PermalinkMultiscale cartographic visualization of harmonized datasets / Peter Kunz in International journal of cartography, vol 5 n° 2-3 (July - November 2019)PermalinkA bevy of area-preserving transforms for map projection designers / Daniel "daan" Strebe in Cartography and Geographic Information Science, vol 46 n° 3 (May 2019)Permalink