Leveraging Street Level Imagery for Urban Planning-Reference-Cited by-同舟云学术

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Leveraging Street Level Imagery for Urban Planning

Published:2022-02-15 Issue:3 Volume:49 Page:773-776
ISSN:2399-8083
Container-title:Environment and Planning B: Urban Analytics and City Science
language:en
Short-container-title:Environment and Planning B: Urban Analytics and City Science

Author:

Crooks Andrew¹,See Linda²

Affiliation:

1. University at Buffalo, NY, USA

2. International Institute for Applied Systems Analysis, Laxenburg, Austria

Publisher

SAGE Publications

Subject

Management, Monitoring, Policy and Law,Nature and Landscape Conservation,Urban Studies,Geography, Planning and Development,Architecture

Link

http://journals.sagepub.com/doi/pdf/10.1177/23998083221083364

Reference13 articles.

1. Exploring convolutional neural networks and spatial video for on-the-ground mapping in informal settlements

2. Measuring the size of a crowd using Instagram

3. Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States

4. Associations between the quality of street space and the attributes of the built environment using large volumes of street view pictures

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bridging the gap between pedestrian and street views for human-centric environment measurement: A GIS-based 3D virtual environment;Landscape and Urban Planning;2023-12

2. Mapping sidewalks on a neighborhood scale from street view images;Environment and Planning B: Urban Analytics and City Science;2023-09-01

3. AGDF-Net: Attention-Gated and Direction-Field-Optimized Building Instance Extraction Network;Sensors;2023-07-12

4. Global microscale walkability ratings and rankings: A novel composite indicator for 59 European city centres;Journal of Transport Geography;2023-07

5. Smart and Sentient Retail High Streets;Smart Cities;2022-11-29

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