📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

The distribution of greenspace quantity and quality and their association with neighbourhood socioeconomic conditions in Guangzhou, China: A new approach using deep learning method and street view images (2021)

First Author: Wang R
Attributed to:  Administrative Data Research Centres 2018 funded by ESRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1016/j.scs.2020.102664

Publication URI: http://dx.doi.org/10.1016/j.scs.2020.102664

Type: Journal Article/Review

Parent Publication: Sustainable Cities and Society