The following body of work introduces a plugin that links the visual scripting language Grasshopper3D (GH) to the Google Earth Engine (GEE) in order to easily fetch geospatial information relative to various societal issues and for any geographical area under study, inside the Rhino modelling software. Aiming at expanding the field of Digital Landscape Architecture with novel content to analyse and design, it provides designers with more than thirty years of historical imagery and scientific datasets, collected in GEE on a daily basis by several institutions around the world. Leveraging the intuitiveness of the visual scripting language, it computationally empowers designers with geospatial insights without the need for any GIS skills and has been proved a successful platform for teaching purposes. Encouraging learning through application, the paper discusses three teaching experiences, which adopted the proposed tool to visualise river dynamics in time, resource-specific maps of land consumption for cities and street-sensitive accessibility maps through the additional integration of OpenStreetMap data.
Autor / Author: | Neri, Iacopo |
Institution / Institution: | University of Zurich, Zurich/Switzerland & Institute for Advanced Architecture of Catalonia, Barcelona/Spain |
Seitenzahl / Pages: | 8 |
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): | Algorithmic design and analysis Landscape, teaching digital landscape architecture, UAV imagery and Remote sensing in landscape architecture |
Paper review type: | Full Paper Review |
DOI: | doi:10.14627/537740047 |
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