Document Type

Article

Journal/Book Title/Conference

Land

Author ORCID Identifier

Doo Hong Lee https://orcid.org/0000-0002-2976-3728

Brent Chamberlain https://orcid.org/0000-0003-1956-0828

Volume

14

Issue

3

Publisher

MDPI AG

Publication Date

3-1-2025

Journal Article Version

Version of Record

First Page

1

Last Page

37

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Abstract

Interdisciplinary research has significantly advanced our understanding, benefits, and measurements of Urban Green Space (UGS). Further, the rapid expansion of research on this topic has resulted in a diverse array of definitions, which can rely on implicit assumptions without a formal definition. This variability highlights the need for a carefully structured framework to refine and combine these definitions. This narrative review examines constructs underlying UGS, particularly focusing on the spatial aspects of how we spatially measure UGS, the measurements of UGS, and how we define exposure; the latter focuses on two methods: viewsheds and image segmentation. Our findings reveal a shift in UGS measurement focus, moving beyond simple quantification of how much green space exists, to incorporate visibility, accessibility, and availability dimensions. Furthermore, advancements in computational tools, including artificial intelligence-driven methods, now enable high-resolution visibility measurements on a city-wide scale, supporting epidemiological research and urban development. These insights aim to guide researchers and practitioners in selecting suitable methodologies and datasets, as well as explicitly defining UGS in their work through a construct-based approach.

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