Journal of Digital Landscape Architecture

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Linking Image-based Metrics to 3D Model-based Metrics for Assessment of Visual Landscape Quality

Visual landscape quality represents a potential attribute of landscapes that affects people’s perception and psychological well-being. With the perceived sensory dimensions as a conceptual framework, this study proposes methods to measure visual quality in both real environments and virtual models, using image-based metrics from computer vision techniques and 3D model-based metrics from parametric modelling techniques. Using the Clementi Woods Park in Singapore as a case study, we compared these two types of metrics using statistical methods and proposed an approach of using a regression model from empirical studies to estimate subjective preference for design scenarios and thus to evaluate the result of landscape design scenarios.

Autor / Author: Xudong, Zhang; Lin, Shengwei; Qi, Jinda; Tan, Puay Yok
Institution / Institution: National University of Singapore/Singapore; National University of Singapore/Singapore; National University of Singapore/Singapore; National University of Singapore/Singapore
Seitenzahl / Pages: 11
Sprache / Language: Englisch
Veröffentlichung / Publication: JoDLA – Journal of Digital Landscape Architecture, 8-2023
Tagung / Conference: Digital Landscape Architecture 2023 – Future Resilient Landscapes
Veranstaltungsort, -datum / Venue, Date: Dessau Campus of Anhalt University, Germany 24-05-23 - 27-05-23
Schlüsselwörter (de):
Keywords (en): Image-based metrics, 3D model-based metrics, visual landscape quality
Paper review type: Full Paper Review
DOI: doi:10.14627/537740018
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