This book is intended to provide a detailed perspective on techniques and challenges in detecting urban materials using hyperspectral data including a systematic perspective on the spectral properties of the materials and methods. It adopts a 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.