Generating citywide street cross-sections using aerial LiDAR and detailed street plan

•Utilized LiDAR and precise street datasets to generate 0.5 Million cross-sections.•Calculation of detailed cross-section statistics.•Integration of shadow information with the cross-sections.•Generation of generic street categories and calculation of Enclosure. Precise information on spatial config...

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Vydané v:Sustainable cities and society Ročník 96; s. 104673
Hlavní autori: Verma, Deepank, Mumm, Olaf, Carlow, Vanessa Miriam
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.09.2023
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ISSN:2210-6707
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Abstract •Utilized LiDAR and precise street datasets to generate 0.5 Million cross-sections.•Calculation of detailed cross-section statistics.•Integration of shadow information with the cross-sections.•Generation of generic street categories and calculation of Enclosure. Precise information on spatial configurations of urban spaces, such as streets, is essential for investigating complex interrelationships between the quality of life, livability, and mobility. Street cross-sections can be central for such research as they depict the allocation of urban space by detailing the streetscape's layout and dimensions, including driveways, sidewalks, bikepaths, median strips, trees, adjoining buildings and open spaces, and shadows. However, creating an accurate description of the real world as a three-dimensional representation and translation into cross-sections is challenging due to the requirement of multiple data sources, such as road layouts with widths, height information, and, optionally, high-resolution aerial imagery. Without such datasets, the cross-section drawings are limited to manual measurements, which are difficult to extend to a city scale. This study aims to develop a method to automatically generate street cross-sections for the entire city of Berlin based on an aerial Lidar dataset and a city street plan. The study also includes shadows as a part of the sections and utilizes the Lidar dataset to generate solar radiation maps. Approximately 0.5 million cross-sections are generated with detailed information regarding the width and placement of the street elements. The details of the cross-sections are further processed to find generic street compositions, understand the influence of shadows on walkways and bikepaths, and calculate the enclosure.
AbstractList •Utilized LiDAR and precise street datasets to generate 0.5 Million cross-sections.•Calculation of detailed cross-section statistics.•Integration of shadow information with the cross-sections.•Generation of generic street categories and calculation of Enclosure. Precise information on spatial configurations of urban spaces, such as streets, is essential for investigating complex interrelationships between the quality of life, livability, and mobility. Street cross-sections can be central for such research as they depict the allocation of urban space by detailing the streetscape's layout and dimensions, including driveways, sidewalks, bikepaths, median strips, trees, adjoining buildings and open spaces, and shadows. However, creating an accurate description of the real world as a three-dimensional representation and translation into cross-sections is challenging due to the requirement of multiple data sources, such as road layouts with widths, height information, and, optionally, high-resolution aerial imagery. Without such datasets, the cross-section drawings are limited to manual measurements, which are difficult to extend to a city scale. This study aims to develop a method to automatically generate street cross-sections for the entire city of Berlin based on an aerial Lidar dataset and a city street plan. The study also includes shadows as a part of the sections and utilizes the Lidar dataset to generate solar radiation maps. Approximately 0.5 million cross-sections are generated with detailed information regarding the width and placement of the street elements. The details of the cross-sections are further processed to find generic street compositions, understand the influence of shadows on walkways and bikepaths, and calculate the enclosure.
ArticleNumber 104673
Author Carlow, Vanessa Miriam
Mumm, Olaf
Verma, Deepank
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Keywords Street composition
Shadows
Street cross-sections
Generic Street categories
Enclosure
Aerial LiDAR
Language English
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Snippet •Utilized LiDAR and precise street datasets to generate 0.5 Million cross-sections.•Calculation of detailed cross-section statistics.•Integration of shadow...
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StartPage 104673
SubjectTerms Aerial LiDAR
Enclosure
Generic Street categories
Shadows
Street composition
Street cross-sections
Title Generating citywide street cross-sections using aerial LiDAR and detailed street plan
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