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Titre : Systems mapping: How to build and use causal models of systems Type de document : Monographie Auteurs : Peter Barbrook-Johnson, Auteur ; Alexandra S. Penn, Auteur Editeur : Springer Nature Année de publication : 2022 Autre Editeur : Palgrave Macmillan (Londres, New York, ...) Importance : 186 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-031-01919-7 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] approche participative
[Termes IGN] carte cognitive
[Termes IGN] carte heuristique
[Termes IGN] cartographie dynamique
[Termes IGN] diagramme
[Termes IGN] représentation cartographique
[Termes IGN] représentation mentale
[Termes IGN] réseau bayesienRésumé : (éditeur) This open access book explores a range of new and older systems mapping methods focused on representing causal relationships in systems. In a practical manner, it describes the methods and considers the differences between them; describes how to use them yourself; describes how to choose between and combine them; considers the role of data, evidence, and stakeholder opinion; and describes how they can be useful in a range of policy and research settings. This book provides a key starting point and general-purpose resource for understanding complex adaptive systems in practical, actionable, and participatory ways. The book successfully meets the growing need in a range of social, environmental, and policy challenges for a richer more nuanced, yet actionable and participatory understanding of the world. The authors provide a clear framework to alleviate any confusion about the use of appropriate terms and methods, enhance the appreciation of the value they can bring, and clearly explain the differences between approaches and the resulting outputs of mapping processes and analysis. Note de contenu : Introduction
1- Rich pictures
2- Theory of change diagrams
3- Causal loop diagrams
4- Participatory systems mapping
5- Fuzzy cognitive mapping
6- Bayesian belief networks
7- System dynamics
8- What data and evidence can you build system maps from?
9- Running systems mapping workshops
10- Comparing, choosing, and combining systems mapping methods
ConclusionNuméro de notice : 24095 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie DOI : 10.1007/978-3-031-01919-7 En ligne : https://doi.org/10.1007/978-3-031-01919-7 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102569
Titre : Télédétection et modélisation spatiale : Applications à la surveillance et au contrôle des maladies liées aux moustiques Type de document : Monographie Auteurs : Annelise Tran, Éditeur scientifique ; Eric Daudé, Éditeur scientifique ; Thibault Catry, Éditeur scientifique Editeur : Versailles : Quae Année de publication : 2022 Importance : 148 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-2-7592-3629-9 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse multicritère
[Termes IGN] cartographie des risques
[Termes IGN] distribution spatiale
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multibande
[Termes IGN] image Terra-MODIS
[Termes IGN] maladie parasitaire
[Termes IGN] maladie tropicale
[Termes IGN] modélisation spatiale
[Termes IGN] Normalized Difference Water Index
[Termes IGN] surveillance sanitaire
[Termes IGN] température de l'air
[Termes IGN] TRMMRésumé : (éditeur) Mosquitoes are vectors of many disease-causing agents, such as malaria, dengue, chikungunya and yellow fever. According to the World Health Organisation, they cause several hundred thousand deaths each year. They are also the cause of zoonoses, such as Rift Valley fever and West Nile fever. In this context, there is a great need for operational tools to guide surveillance and control actions, both in the South - tropical and subtropical areas are the most affected by mosquito-borne diseases - and in the North, where the establishment of new species such as the tiger mosquito increases the risk of disease emergence. Earth observation imagery is of great interest to meet these needs: the spatial distribution and temporal dynamics of mosquitoes are influenced by climatic (temperature, precipitation, humidity) and environmental (availability of water areas, vegetation) variables, indicators of which can be derived from satellite imagery. Many recent studies have developed innovative methods combining remote sensing and spatial modelling to predict the spatial and temporal dynamics of mosquito vectors and associated diseases. Beyond the feasibility study, some of these methods have led to tools and processing chains that are now operational and used by public health actors and vector control operators. This book, intended for students and researchers as well as public health actors, presents a summary of this research work and these tools. Note de contenu : Introduction générale
Partie I- Informations spatiales pour la surveillance des moustiques vecteurs et des maladies associées
1- Liens entre moustiques vecteurs et environnement : apport des méthodes de télédétection satellite
2- Indices spectraux et classifications d’images multispectrales pour la cartographie du risque vectoriel
3- Estimation des températures de l’air à partir d’images satellite et de stations météorologiques
4- Du recensement au bâtiment : génération de populations synthétiques
5- Texture des images satellite et caractérisation des milieux urbains favorables aux moustiques vecteurs
Partie II- Analyser et prédire l’effet de variables environnementales sur la distribution et la dynamique des moustiques vecteurs
6- Modèles basés sur les données : cartographier la distribution spatiale des vecteurs
7- Modèles fondés sur les connaissances : exemple d’un outil d’évaluation multicritère pour la santé publique
8- Arbocarto : un modèle mécaniste fondé sur le cycle de vie des moustiques Aedes
9- Simulation spatiale du risque de propagation de la dengue à partir de modèles comportementaux vecteurs et hôtes
Conclusion générale et perspectivesNuméro de notice : 24096 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.35690/978-2-7592-3629-9 En ligne : https://doi.org/10.35690/978-2-7592-3629-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102570 The use of volunteer geographic information for producing and maintaining authoritative land use and land cover data / Ana-Maria Olteanu-Raimond (2022)
Titre : The use of volunteer geographic information for producing and maintaining authoritative land use and land cover data : EuroSDR and LandSense Workshop, November 24th - 25th 2020, Online Conference Type de document : Actes de congrès Auteurs : Ana-Maria Olteanu-Raimond , Auteur ; Joep Crompvoets, Auteur ; Inian Moorthy, Auteur ; Clément Mallet , Auteur ; Bénédicte Bucher , Auteur Editeur : Dublin : European Spatial Data Research EuroSDR Année de publication : 2022 Collection : EuroSDR Workshop report Projets : Landsense / Raimond, Ana-Maria Conférence : VGI4LULC 2020, The use of volunteer geographic information for producing and maintaining authoritative land use and land cover data 24/11/2020 25/11/2020 online OA Proceedings Importance : 40 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] approche participative
[Termes IGN] cartographie collaborative
[Termes IGN] collecte de données
[Termes IGN] Corine Land Cover
[Termes IGN] détection de changement
[Termes IGN] données localisées des bénévoles
[Termes IGN] intégration de données
[Termes IGN] occupation du sol
[Termes IGN] OpenStreetMap
[Termes IGN] science citoyenne
[Termes IGN] utilisation du solRésumé : (éditeur) The report refers to the workshop that was organized on behalf of EuroSDR and the LandSense project (24-25 November 2020). LandSense aims to build a citizen observatory for Land Use and Land Cover (LULC) monitoring by proposing innovate technologies for data collection, change detection, data quality assessment and offering tools and systems to empower different communities (e.g., private companies, Non Governmental Organisation, National Mapping Agencies, research, public authorities) to monitor and report on LULC. The workshop was co-organized by the LASTIG laboratory of the University Gustave Eiffel and IGN-ENSG, the French National Mapping agency (Ana-Maria Olteanu-Raimond, Clément Mallet, Bénédicte Bucher), the Katholieke Universiteit Leuven (Joep Crompvoets), the International Institute for Applied Systems Analysis (Inian Moorthy) and EuroSDR. Note de contenu : INTRODUCTION GENERALE
1. Introduction
1.1 Land Use and Land Cover data: specificities and challenges
1.2 VGI and citizen science for LULC monitoring
2. Session 1: Use of VGI for LULC data production
2.1 National Land Cover and Land Use Information System of Spain (SIOSE)- Coordination,
production, maintenance and VGI
2.2 A fusion data approach for integrating VGI to update and enrich authoritative LULC data
2.3 OpenStreetMap for Earth Observation (OSM4EO) land use application and benchmark
2.4 Using OpenStreetMap as a data source for training classifiers to generate LULC maps
3. Session 2: Data collection and validation
3.1 A mapping prototype for land use mapping by land users
3.2 A mobile application for collecting snow data in support to satellite remote sensing
3.3 Global land cover monitoring, validation and participation: experiences from several case studies
4. Session 3: Sustainability
4.1 Crowdsourcing reference data collection for land cover and land use mapping: Findings from Picture Pile and FotoquestGo
4.2 Land Cover Monitoring System with Sentinel-Hub and Python Machine Learning Library eo-learn. Is it possible to build a fast and cost-effective LCMS?
4.3 Regular monitoring of landscape changes with Copernicus data- The German land cover change detection service
4.4 Authentication as a Service - A LandSense contribution to improve the FAIR principle in Citizen Science
5. ConclusionNuméro de notice : 28680 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Actes nature-HAL : DirectOuvrColl/Actes DOI : sans En ligne : http://www.eurosdr.net/sites/default/files/uploaded_files/eurosdr_vgi4lulc.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99973 Three-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation / Massimiliano Alvioli in Geomatics, Natural Hazards and Risk, vol 13 (2022)
[article]
Titre : Three-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation Type de document : Article/Communication Auteurs : Massimiliano Alvioli, Auteur ; Ada De Mateo, Auteur ; Raffaele Castaldo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2712 - 2736 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] éboulement
[Termes IGN] île
[Termes IGN] Italie
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] pente
[Termes IGN] risque naturel
[Termes IGN] roche
[Termes IGN] séisme
[Termes IGN] semis de points
[Termes IGN] surveillance géologique
[Termes IGN] vulnérabilitéRésumé : (auteur) Ischia Island is a volcano-tectonic horst in the Phlegrean Volcanic District, Italy. We investigated rockfalls in Ischia using STONE, a three-dimensional model for simulating trajectories for given detachment locations of blocks. We propose methodological advances regarding the use of high-resolution LiDAR elevation data, the localization of possible detachments sources, and the inclusion of scenario-based seismic shaking as a trigger for rockfalls. We demonstrated that raw LiDAR data are useful to distinguish areas covered by tall vegetation, allowing realistic simulation of trajectories. We found that the areas most susceptibile to rockfalls are located along the N, N-W and S-W steep flanks of Mt. Epomeo, the S and S-W coast, and the sides of some steep exposed hydrographic channels located in the southern sector of the island. A novel procedure for dynamic activation of sources depending on ground shaking, in the event of an earthquake, helped inferring a seismically-triggered source map and the corresponding rockfall trajectories, for a scenario with 475 y return time. Thus, we obtained preliminary rockfall suceptibility in Ischia both in a “static” (trigger-independent) scenario, and in a seismic shaking triggering scenario. They must not be considered a risk map, but a starting point for a detailed field analysis. Numéro de notice : A2022-874 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : https://doi.org/10.1080/19475705.2022.2131472 Date de publication en ligne : 09/10/2022 En ligne : https://doi.org/10.1080/19475705.2022.2131472 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102172
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 2712 - 2736[article]Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany / Omar Seleem in Geomatics, Natural Hazards and Risk, vol 13 (2022)
[article]
Titre : Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany Type de document : Article/Communication Auteurs : Omar Seleem, Auteur ; Georgy Ayzel, Auteur Année de publication : 2022 Article en page(s) : pp 1640 - 1662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Berlin
[Termes IGN] cartographie des risques
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] inondation
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] vulnérabilitéRésumé : (auteur) Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available. Numéro de notice : A2022-457 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/19475705.2022.2097131 Date de publication en ligne : 12/07/2022 En ligne : https://doi.org/10.1080/19475705.2022.2097131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101257
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 1640 - 1662[article]Urban 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)Permalink