#7939. Examining the spatial distribution and temporal change of the green view index in New York City using Google Street View images and deep learning

October 2026publication date
Proposal available till 31-05-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Architecture;
Urban Studies;
Geography, Planning and Development;
Nature and Landscape Conservation;
Management, Monitoring, Policy and Law;
Places in the authors’ list:
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4 place - free (for sale)

More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
As an important part of the urban ecosystem, urban trees provide various benefits to urban residents. It is therefore important to examine the spatial distribution and the temporal change in urban tree canopies. Different from traditional overhead view remote sensing-based methods, street-level images, which present the most common view that people have of greenery, provide a more human-centric way to quantify street tree canopies. This study mapped and analyzed the spatial distribution and temporal change in the green view index, which represents the visibility of tree canopies along streets in New York City during the last 10 years using historical Google Street View images.
Keywords:
deep learning; environmental inequity; Google Street View; green view index; street tree canopies

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