A time series of detailed point clouds of an experimental planting trial were captured at regular intervals using photogrammetry techniques. Each point cloud was segmented into individual plant specimens, which were analysed to determine growth parameters. These parameters describe the approximate growth and seasonal characteristics of the subject species and can be used to inform future designs. The outcomes of these design experiments support the use of spatial data capture tools to make decisions about species selection and design in the future practice of landscape architecture.
Autor / Author: | White, Michael G.; Haeusler, M. Hank; Zeunert, Joshua |
Institution / Institution: | University of New South Wales/Australia; University of New South Wales/Australia; University of New South Wales/Australia |
Seitenzahl / Pages: | 7 |
Sprache / Language: | Englisch |
Veröffentlichung / Publication: | JoDLA – Journal of Digital Landscape Architecture, 9-2024 |
Tagung / Conference: | Digital Landscape Architecture 2024 – New Trajectories in Computational Urban Landscapes and Ecology |
Veranstaltungsort, -datum / Venue, Date: | Vienna University of Technology, Austria 05-06-24 - 07-06-24 |
Schlüsselwörter (de): | |
Keywords (en): | Landscape architecture, point clouds, planting design |
Paper review type: | Full Paper Review |
DOI: | doi:10.14627/537752056 |
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