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A collection of urban and landscape computational design work

About

Autosimulacrum

[2020]


Autosimulacrum is a platform for computationally rendering speculative landscapes. The program harvests federal land cover and terrain datasets, translates the data into a 3D model populated with assets and materials, and creates photorealistic renderings along with accompanying data dashboards.

This project was supported by the Harvard University Graduate School of Design through the Irving Innovation Fellowship.



Data visualization of land cover composition across the United States; presented at three scales: national, regional, state Rendering of Mt. Hood National Forest, looking north across Trillium Lake Accompanying dashboard for Mt. Hood National Forest Rendering of Great Smoky Mountains National Park, looking southeast from Newfound Gap, TN Accompanying dashboard for Great Smoky Mountains National Park Rendering of Lumaha'i Beach, Kauai, looking east towards Hanalei Bay Accompanying dashboard for Lumaha'i Beach, Kauai Rendering of Zion Canyon, Zion National Park, looking south toward Big Bend Accompanying dashboard for Zion Canyon, Zion National Park Vegetation matrix representing all possible tree inputs; a tree is selected for a specific coordinate point based on elevation, slope, and hardiness qualifications Diagram representing Autosimulacrum's process of generating renderings