Fr. 63.00

Street Sensing - Urban Thermal Environment Assessment Using Street View Images

English, German · Paperback / Softback

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Description

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Combining publicly available Google Street View (GSV) images with deep learning and radiative transfer models enables researchers to assess urban physical and thermal environments, especially in high-density areas. This book introduces this advanced approach, which provides large-scale, high-accuracy, and high-density measurements of street-level urban features key to understanding urban radiation balance and thermal dynamics.
By leveraging GSV images, this method directly characterizes urban streetscapes, including structural and geometric attributes, allowing for a comprehensive assessment. Moreover, the methods can be applied to any geographical location covered by GSV, making it a low-cost and effective tool for urban studies globally. This is particularly advantageous compared to traditional 3D-GIS models, which may not always be freely available or as extensive in coverage as GSV images.
Lessons from Street Sensing provide data-driven insights for urban planning and governance. The accurate mapping of street view factors and solar irradiance helps identify areas with insufficient greenery, excessive or insufficient solar exposure, and other urban environment issues. These insights can help policymakers and urban planners mitigate negative environmental impacts and improve urban living conditions.

List of contents

Chapter 1: Introduction.- Chapter 2: Theoretical background.- Chapter 3: Methodology.- Chapter 4: Spatial Patterns of Street Canyon View Factors.- Chapter 5: Spatiotemporal Patterns of Street Canyon Solar Radiation.- Chapter 6: Implementation of Urban Planning and Design at Street Level.- Chapter 7: Conclusions.

Product details

Authors Fang-Ying Gong
Publisher Springer, Berlin
 
Languages English, German
Product format Paperback / Softback
Released 21.08.2025
 
EAN 9783031920042
ISBN 978-3-0-3192004-2
No. of pages 127
Illustrations XXIX, 127 p. 48 illus., 44 illus. in color.
Series SpringerBriefs in Geography
Subjects Natural sciences, medicine, IT, technology > Technology > Structural and environmental engineering

Geographie, Deep Learning, Urban Planning, Physische Geographie und Topographie, Physical geography, Environmental Monitoring, Integrated Geography, Urban Morphology, solar radiation, street view image, view factor, street sensing

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