Standardized Green View Index and Quantification of Different Metrics of Urban Green Vegetation

Yusuke Kumakoshi, Sau Yee Chan, Hideki Koizumi, Xiaojiang Li and Yuji Yoshimura
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Yusuke Kumakoshi: Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan
Sau Yee Chan: Independent Engineer, Tokyo 113-8656, Japan
Hideki Koizumi: Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan
Xiaojiang Li: Department of Geography and Urban Studies, Temple University, Philadelphia, PA 19122, USA
Yuji Yoshimura: Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan

Sustainability, 2020, vol. 12, issue 18, 1-16

Abstract: Urban greenery is considered an important factor in sustainable development and people’s quality of life in the city. To account for urban green vegetation, Green View Index (GVI), which captures the visibility of greenery at street level, has been used. However, as GVI is point-based estimation, when aggregated at an area-level by mean or median, it is sensitive to the location of sampled sites, overweighing the values of densely located sites. To make estimation at area-level more robust, this study aims to (1) propose an improved indicator of greenery visibility (standardized GVI; sGVI), and (2) quantify the relation between sGVI and other green metrics. Experiment on an hypothetical setting confirmed that bias from site location can be mitigated by sGVI. Furthermore, comparing sGVI and Normalized Difference Vegetation Index (NDVI) at the city block level in Yokohama city, Japan, we found that sGVI captures the presence of vegetation better in the city center, whereas NDVI is better at capturing vegetation in parks and forests, principally due to the different viewpoints (eye-level perception and top-down eyesight). These tools provide a foundation for accessing the effect of vegetation in urban landscapes in a more robust matter, enabling comparison on any arbitrary geographical scale.

Keywords: green view index (GVI); Google street view; normalized differential vegetation index (NDVI); satellite image; urban greenery (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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