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Titre : COVID-19 pandemic, geospatial information, and community resilience : Global applications and lessons Type de document : Monographie Auteurs : Abbas Rajabifard, Éditeur scientifique ; Daniel Paez, Éditeur scientifique ; Greg Foliente, Éditeur scientifique Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2021 Importance : 544 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-1-00-318159-0 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] analyse spatiale
[Termes IGN] données localisées
[Termes IGN] épidémie
[Termes IGN] gestion de crise
[Termes IGN] image satellite
[Termes IGN] maladie virale
[Termes IGN] modélisation spatiale
[Termes IGN] OpenStreetMap
[Termes IGN] planification urbaine
[Termes IGN] réseau socialRésumé : (auteur) Geospatial information plays an important role in managing location dependent pandemic situations across different communities and domains. Geospatial information and technologies are particularly critical to strengthening urban and rural resilience, where economic, agricultural, and various social sectors all intersect. Examining the United Nations' SDGs from a geospatial lens will ensure that the challenges are addressed for all populations in different locations. This book, with worldwide contributions focused on COVID-19 pandemic, provides interdisciplinary analysis and multi-sectoral expertise on the use of geospatial information and location intelligence to support community resilience and authorities to manage pandemics. Note de contenu : 1- Setting the scene
2- Technical and technico-social solutions
3- Regional, country and local applications
4- Stakeholder perspectives
5- The futur directionNuméro de notice : 28628 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.1201/9781003181590 En ligne : https://doi.org/10.1201/9781003181590 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99578
Titre : Developing graphics frameworks with Python and OpenGL Type de document : Guide/Manuel Auteurs : Lee Stemkoski, Auteur ; Michael Pascale, Auteur Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2021 Importance : 345 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-1-00-318137-8 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Langages informatiques
[Termes IGN] image 3D
[Termes IGN] interface de programmation
[Termes IGN] OpenGL
[Termes IGN] processeur graphique
[Termes IGN] programmation informatique
[Termes IGN] Python (langage de programmation)
[Termes IGN] scène 3D
[Termes IGN] texture d'image
[Termes IGN] transformation géométriqueRésumé : (éditeur) Developing Graphics Frameworks with Python and OpenGL shows you how to create software for rendering complete three-dimensional scenes. The authors explain the foundational theoretical concepts as well as the practical programming techniques that will enable you to create your own animated and interactive computer-generated worlds. You will learn how to combine the power of OpenGL, the most widely adopted cross-platform API for GPU programming, with the accessibility and versatility of the Python programming language. Topics you will explore include generating geometric shapes, transforming objects with matrices, applying image-based textures to surfaces, and lighting your scene. Advanced sections explain how to implement procedurally generated textures, postprocessing effects, and shadow mapping. In addition to the sophisticated graphics framework you will develop throughout this book, with the foundational knowledge you will gain, you will be able to adapt and extend the framework to achieve even more spectacular graphical results. Note de contenu : 1- Introduction to computer graphics
2- Introduction to Pygame and OpenGL
3- Matrix algebra and transformations
4- A scene graph framework
5- Textures
6- Light and shadowNuméro de notice : 28306 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Manuel DOI : 10.1201/9781003181378 En ligne : https://doi.org/10.1201/9781003181378 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98077
Titre : Cartography : visualization of geospatial data Type de document : Guide/Manuel Auteurs : Menno-Jan Kraak, Auteur ; Ferjan J. Ormeling, Auteur Mention d'édition : Fourth edition Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2020 Importance : 245 p. ISBN/ISSN/EAN : 978-1-138-61395-9 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie
[Termes IGN] géostatistique
[Termes IGN] géovisualisation
[Termes IGN] outil d'aide à la décision
[Termes IGN] système d'information géographique
[Termes IGN] visualisation cartographiqueIndex. décimale : 39.00 Cartographie - généralités - Cartologie Résumé : (Editeur) This Fourth Edition of Cartography: Visualization of Geospatial Data serves as an excellent introduction to general cartographic principles. It is an examination of the best ways to optimize the visualization and use of spatiotemporal data. Fully revised, it incorporates all the changes and new developments in the world of maps, such as OpenStreetMap and GPS (Global Positioning System) based crowdsourcing, and the use of new web mapping technology and adds new case studies and examples. Now printed in colour throughout, this edition provides students with the knowledge and skills needed to read and understand maps and mapping changes and offers professional cartographers an updated reference with the latest developments in cartography.
Written by the leading scholars in cartography, this work is a comprehensive resource, perfect for senior undergraduate and graduate students taking courses in GIS (geographic information system) and cartography.
New in This Edition:
- Provides an excellent introduction to general cartographic visualization principles through full-colour figures and images
- Addresses significant changes in data sources, technologies and methodologies, including the movement towards more open data sources and systems for mapping
- Includes new case studies and new examples for illustrating current trends in mapping
- Provides a societal and institutional framework in which future mapmakers are likely to operate, based on UN global development sustainability goalsNote de contenu : 1. Geographical Information Science and Maps
2. Data Acquisition
3. Map Characteristics
4. GIS Applications: Which Map to Use?
5. Map Design and Production
6. Topography
7. Statistical Mapping
8. Mapping Time
9. Maps at Work: Presenting and Using Geospatial Data in Maps and Atlases
10. Maps at Work: Analysis and Geovisualization
11. Cartography at Work: Maps as Decision ToolsNuméro de notice : 26840 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Manuel Accessibilité hors numérique : Accessible via le SUDOC (sur demande au cdos) Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101359
Titre : Deep learning for remote sensing images with open source software Type de document : Guide/Manuel Auteurs : Rémi Cresson, Auteur Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2020 Importance : 164 p. Présentation : Nombreuses illustrations en couleur ISBN/ISSN/EAN : 978-0-367-85848-3 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] image radar
[Termes IGN] image Sentinel
[Termes IGN] jeu de données localisées
[Termes IGN] Orfeo Tool Box
[Termes IGN] QGIS
[Termes IGN] restauration d'image
[Termes IGN] segmentation sémantiqueIndex. décimale : 35.20 Traitement d'image Résumé : (Editeur) In today’s world, deep learning source codes and a plethora of open access geospatial images are readily available and easily accessible. However, most people are missing the educational tools to make use of this resource.This book is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches detailed in this book are generic and can be adapted to suit many different applications for remote sensing image processing, including landcover mapping, forestry, urban studies, disaster mapping, image restoration, etc. Written with practitioners and students in mind, this book helps link together the theory and practical use of existing tools and data to apply deep learning techniques on remote sensing images and data.
Specific Features of this Book:
- The first book that explains how to apply deep learning techniques to public, free available data (Spot-7 and Sentinel-2 images, OpenStreetMap vector data), using open source software (QGIS, Orfeo ToolBox, TensorFlow)
- Presents approaches suited for real world images and data targeting large scale processing and GIS applications
- Introduces state of the art deep learning architecture families that can be applied to remote sensing world, mainly for landcover mapping, but also for generic approaches (e.g. image restoration)
- Suited for deep learning beginners and readers with some GIS knowledge. No coding knowledge is required to learn practical skills.
- Includes deep learning techniques through many step by step remote sensing data processing exercises.Note de contenu : Introduction
1. Backgrounds
2. Patch Based Classification
3. Semantic Segmentation
4. Image RestorationNuméro de notice : 26551 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Manuel DOI : sans Accessibilité hors numérique : Accessible via le SUDOC (sur demande au cdos) Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97864
Titre : Atlas of remote sensing of the Wenchuan earthquake : Cas- Project Team of Remote Sensing for Wenchuan Earthquake Type de document : Monographie Auteurs : Huadong Guo, Auteur Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2019 Importance : 259 p. Format : 26 x 28 cm ISBN/ISSN/EAN : 978-1-4398-1674-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse du paysage
[Termes IGN] carte géologique
[Termes IGN] détection de changement
[Termes IGN] dommage matériel
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] image Radarsat
[Termes IGN] image satellite
[Termes IGN] impact sur l'environnement
[Termes IGN] réseau routier
[Termes IGN] séisme
[Termes IGN] Setchouan (Chine)
[Termes IGN] zone urbaineRésumé : (éditeur) In May 12, 2008, the Wenchuan County earthquake caused devastating loss of human life and property. Applying all the remote sensing technology available, the Chinese Academy of Sciences immediately launched into action, making full use of its state-of-the-art facilities, remote sensing planes, and satellites to amass invaluable optical and radar data. This unprecedented use of comprehensive remote sensing techniques provided accurate, up to the minute information for disaster management and has left us with a visually stunning and beautiful record that is as much a scientific achievement as it is an artistic one. Based on the accumulated data and images collected by the Project Team of Remote Sensing Monitoring and Assessment of the Wenchuan Earthquake, Atlas of Remote Sensing of the Wenchuan Earthquake documents the events as they happened in real time. The book covers the disaster from six aspects: geological, barrier lakes, collapsed buildings, damaged roads, destroyed farmland and forests, and demolished infrastructure. It also demonstrates that the Dujiangyan Irrigation Project, which has been standing for 2000 years, remains fully functioning, and keeps the Chengdu Plain operating optimally even after the earthquake. Translated into English for the first time, the Atlas presents a pictorial summation of this unique project. It chronicles the event with over 280 before and after color images from a range of perspectives. This volume dramatically demonstrates the value of remote sensing for understanding how an earthquake unfolds and the potential of remote sensing in helping coordinate emergency relief. A pictorial record of events as they unfolded, this book provides a systematic documentation of earthquake damage that can be used to prepare for future seismic events. Note de contenu : 1- Remote sensing data
2- Geological disaster
3- Barrier lakes
4- Collapsed buildings
5- Damaged roads
6- Destroyed farmlands and forests
7- Demolished infrastructure
8- Civilization perseveresNuméro de notice : 25917 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie En ligne : https://library.oapen.org/handle/20.500.12657/40124 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96100 Land Resources Monitoring, Modeling, and Mapping with Remote Sensing, ch. 17. Optical remote sensing of tree and stand heights / Sylvie Durrieu (2015)
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