With urbanization as a global phenomenon, there is a need for data
and information about these terrains. Urban remote sensing
techniques provide critical physical input and intelligence for
preparing base maps, formulating planning proposals, and monitoring
implementations. Likewise these methodologies help with
understanding the biophysical properties, patterns, and process of
urban landscapes, as well as mapping and monitoring urban land
cover and spatial extent. Advanced sensor technologies and image
processing methodologies such as deep learning, data mining, etc.,
facilitate the wide applications of remote sensing technology in
urban areas. This book presents advanced image processing methods
and algorithms focused on three very important roots of urban
remote sensing: 3D urban modelling using different remotely sensed
data, urban orthophotomap generation, and urban feature extraction,
which are also today's real challenges in high resolution remote
sensing. Data generated by remote sensing, with its repetitive and
synoptic viewing and multispectral capabilities, constitutes a
powerful tool for mapping and monitoring emerging changes in the
city's urban core, as well as in peripheral areas. Features:
Provides advances in emerging methods and algorithms in image
processing and technology Uses algorithms and methodologies for
handling high-resolution imagery from a ground sampling distance
(GSD) less than 1.0 meter Focuses on 3D urban modelling,
orthorectification methodologies, and urban feature extraction
algorithms from high-resolution remotely sensed imagery
Demonstrates how to apply up-to-date techniques to the problems
identified and how to analyze research results Presents methods and
algorithms for monitoring, analyzing, and modeling urban growth,
urban planning, and socio-economic developments In this book,
readers are provided with valuable research studies and
applications-oriented chapters in areas such as urban trees, soil
moisture mapping, city transportation, urban remote sensing big
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