Refining the potential visual exposure index for the assessment of residential visual privacy: a three-dimensional study

ABSTRACT

Residential visual privacy is an important issue in modern society. This paper proposes an improved Potential Visual Exposure Index (I-PVEI) to evaluate the privacy risks of visual exposure along building facades in a dense residential environment. Compared with the PVEI indicator, the proposed method introduces the observer’s view direction based on visual perception and applies a weighting scheme to construct the I-PVEI. To validate the I-PVEI, a case study with a neighborhood located at the center of Kowloon, Hong Kong, was evaluated. The results demonstrate: (1) Potential observers from building and pedestrian levels had different impacts on the neighborhood, resulting in different I-PVEI distribution patterns on the building facades; (2) Although significant changes of I-PVEI value could be found across building facades, I-PVEI values always presented a uniform change trend on the same façade; (3) The quantitative indicator can perceive subtle privacy risks of openings located at the corner of the building, which was overlooked by the PVEI. The results indicate that the proposed I-PVEI can be an optional indicator for the assessment of residential visual privacy in urban planning and building design.

Graphical Abstract

KEYWORDS:

• Visual privacy
• Improved Potential Visual Exposure Index (I-PVEI)
• visual perception
• distribution patterns
• quantitative model

Acknowledgments

The authors would like to thank the anonymous reviewers and editors for their valuable comments. We are also thankful for The Hong Kong Government (Planning Department and Lands Department) for providing the datasets.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Highlights

• An Improved Potential Visual Exposure Index (I-PVEI) for the assessment of residential visual privacy is proposed.

• The level of visual privacy does not consistently increase as the floor rises, and residents living on the middle floor may suffer the most serious.

• Although significant changes of I-PVEI value could be found across building facades, the I-PVEI values always presented a steady change pattern on the same façade.

• The I-PVEI can be an optional indicator for the quantitative assessment of visual privacy.

Author Contributions

Conceptualization, Bo Wu; methodology, He Zheng and Jinmu Zhang; investigation, Jinbiao Yan and Heyi Wei; software, He Zheng; resources, Xianhua Zhang; writing original draft preparation, He Zheng; writing review and editing, Bo Wu and He Zheng; visualization, Heyi Wei and Jinbiao Yan; supervision, Bo Wu; All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Publicly available datasets were analyzed in this study. 3D Photo-realistic Model dataset can be found here: [https://www.pland.gov.hk/pland_en/info_serv/3D_models/download.htm]. 3D Pedestrian Network dataset can be found here: [https://geodata.gov.hk/gs/view-dataset?uuid=201eaaee-47d6-42d0-ac81-19a430f63952&sidx=0#]. iB1000 datasets can be found here: [https://www.hkmapservice.gov.hk/OneStopSystem/map-search?product=OSSCatB&series=iB1000&locale=en].

Additional information

Funding

This work was supported by Natural Science Foundation of China [grant numbers 41961055 and 31860233]; and The National Key Research and Development Program of China [grant number 2018YFE0207800]; and The Science and technology research project of Education Department of Jiangxi Province [grant number GJJ214915].

Notes on contributors

He Zheng

He Zheng is currently a Ph.D. candidate at Jiangxi Normal University, and he is also a lecture at Jiangxi College of Applied Technology. His research interests include 3D modeling, quantitative assessment of building environment and urban sustainability.

Bo Wu

Bo Wu is a Professor at Jiangxi Normal University. His research interests include spatiotemporal big data analysis, remote sensing image processing and building information modeling.

Jinmu Zhang

Jinmu Zhang is a Senior engineer at Jiangxi Normal University. Her research interests include civil engineering and building information modeling.

Jinbiao Yan

Jinbiao Yan is a Ph.D. candidate at Jiangxi Normal University. His research interests include spatiotemporal big data analysis, geographic information system and 3D modeling.

Heyi Wei

Heyi Wei is a lecture and founding director of Geodesign Research Centre at Jiangxi Normal University. His research interests include the Geodesign, Digital Simulation, GIS＆RS in Landscape Architecture.