Описание: This book presents an introductory overview of spatial data analysis methods and geoinformation analysis techniques. Each chapter introduces the related theory, explains how to interpret metrics outputs, and provides worked examples using ArcGIS and GeoDa. This is a valuable resource for graduate students and researchers analyzing geospatial data.
Автор: Alberto Refice; Annarita D`Addabbo; Domenico Capol Название: Flood Monitoring through Remote Sensing ISBN: 3319639587 ISBN-13(EAN): 9783319639581 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is an overview of current state of the art about monitoring of inundation events through remote sensing. A complete approach to efficient and precise flood monitoring requires multiple fields of expertise, from image processing to hydrologic monitoring. This volume details the latest remote sensing techniques for flood monitoring and mapping, including use of optical data from geostationary sensors and LEO spacecraft, synthetic aperture radar (SAR) data analysis, and data fusion. Detailed case studies from a variety of subject experts illustrate these tools and techniques. Accurate monitoring of flood events is increasingly necessary to gain insight about both causes and remedies. Floods are one of the most destructive hazards to the human populations, they can occur practically everywhere on the Earth surface, and each year cause considerable harm and damage to infrastructures. The recent Flood directive in European Countries is contributing to a more quantitative approach to flood hazard and risk evaluation.
Автор: Ramsay William Название: Remote Sensing: Monitoring, Modeling and Applications ISBN: 1682865568 ISBN-13(EAN): 9781682865569 Издательство: Неизвестно Цена: 21885.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With more than 100 leading global contributors, this book is the most comprehensive documentation of the scientific and methodological advances that have taken place in understanding remote sensing data, methods, and applications over last 50 years. In a very practical way the book demonstrates the experience, utility, methods and models used in
Описание: This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences.
Автор: Prasad S. Thenkabail Название: Hyperspectral remote sensing of vegetation / ISBN: 1138066257 ISBN-13(EAN): 9781138066250 Издательство: Taylor&Francis Рейтинг: Цена: 76560.00 р. Наличие на складе: Поставка под заказ.
Описание: The second edition includes extensive discussions on data processing and how to implement data processing mechanisms in a standard, fast, and efficient manner. Written by global experts, each chapter focuses on specific applications, reviews existing "state-of-art" knowledge, highlights the advances made, and provides guidance for data usage.
Описание: Part of a series of manuals covering the range of applications of remotely sensed imagery, this volume addresses the use of this technology in natural resource management and environmental monitoring. It covers terrestrial ecosystems, aquatic ecosystems, and agriculture ecosystems, as well as future directions in technology and research.
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