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Deep Learning for Remote Sensing Images with Open Source Software
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. Deep Learning for Remote Sensing Images with Open Source Software 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 a...
Signal and Image Processing for Remote Sensing
Advances in signal and image processing for remote sensing have been tremendous in recent years. The progress has been particularly significant with the use of deep learning based techniques to solve remote sensing problems. These advancements are the focus of this third edition of Signal and Image Processing for Remote Sensing. It emphasizes the use of machine learning approaches for the extraction of remote sensing information. Other topics include change detection in remote sensing and compressed sensing. With 19 new chapters written by world leaders in the field, this book provides an authoritative examination and offers a unique point of view on signal and image processing. Features Inc...
On the Logics of Planetary Computing
A new breed of low Earth orbit satellites is making planetary-scale observation and analysis ubiquitous. This book explores how this condition feeds spatially explicit artificial intelligence, GeoAI, in redefining the study of landscapes, and how it impacts one particular land dispute in the Alas Mertajati in Central Bali, Indonesia. This book combines scholarship from the humanities and engineering to forge a novel way of presenting planetary computing in its GeoAI vernacular. From data collection to model evaluation, the book describes how multi-spectral, high-resolution satellite data and machine learning algorithms respond to uncommon land cover conditions, including sustainable land car...
Deep Learning for Remote Sensing Images with Open Source Software
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. Deep Learning for Remote Sensing Images with Open Source Software 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 a...
QGIS and Generic Tools
These four volumes present innovative thematic applications implemented using the open source software QGIS. These are applications that use remote sensing over continental surfaces. The volumes detail applications of remote sensing over continental surfaces, with a first one discussing applications for agriculture. A second one presents applications for forest, a third presents applications for the continental hydrology, and finally the last volume details applications for environment and risk issues.
QGIS et outils génériques
Cet ouvrage débute la série Utilisation de QGIS en télédétection qui vise à faciliter l’appropriation et l’utilisation opérationnelle du système d’information géographique (SIG) QGIS (Quantum Geographic Information System) dans le domaine de la télédétection. Ce volume définit le principe de fonctionnement de QGIS et des librairies fondamentales les plus fréquemment utilisées en traitement d’images et en géomatique : GDAL, GRASS, SAGA et OTB. Il présente ainsi de nombreuses fonctionnalités qui seront mises en oeuvre dans de nombreux cas pratiques de télédétection et en analyse spatiale. Porté par des scientifiques de haut niveau de technicité, QGIS et outils génériques s'adresse aux étudiants (masters, écoles d’ingénieurs, doctorat), aux ingénieurs et aux chercheurs qui utilisent déjà des systèmes d’information géographique. En plus des textes, les lecteurs auront accès aux données et outils qui permettent la réalisation intégrale de toutes les démarches scientifiques décrites ainsi qu’aux copies d’écran de chaque fenêtre qui illustre les manipulations nécessaires à la réalisation des applications.
