Hyperspectral Remote Sensing in Urban Environments

This book is intended to provide a detailed perspective on techniques and challenges in detecting urban materials using hyperspectral data including systematic perspective on spectral properties of the materials and methods. It adopts process chain approach in describing the topic and explains image processing steps from reflectance calibration to final insights. The objective of the book is to provide in-depth information on hyperspectral remote sensing of urban materials covering global case studies as applicable.

Features

Covers the complete processing chain of hyperspectral data specifically in urban environments
Gives more information about the mapping and classification of urban scenes
Includes information from basic imaging spectroscopy to advanced methods such as deep learning for imaging spectroscopy
Reviews detailed spectral characteristics of urban materials commonly found in world cities
Discusses advanced supervised methods such as deep learning with a due focus on hyperspectral data analysis
This book is aimed at professionals and graduate students in Hyperspectral Imaging, Urban Remote Sensing, and Hyperspectral Image Processing.