We present Tangible Landscape - a technology for rapidly and intuitively designing landscapes informed by geospatial modeling, analysis, and simulation. Tangible Landscape is a tangible interface powered by a geographic information system that gives 3D spatial data an interactive, physical form so that users can naturally sense and shape it. It couples a physical and a digital model of a landscape through a real-time cycle of physical manipulation, 3D scanning, spatial computation, and projected feedback. Natural 3D sketching and real-time analytical feedback should aid landscape architects in the design of high performance landscapes that account for physical and ecological processes. We conducted a series of studies to assess the effectiveness of tangible modeling for landscape architects. Landscape architecture students, academics, and professionals were given a series of fundamental landscape design tasks - topographic modeling, cut-and-fill analysis, and water flow modeling. Their performance was assessed using qualitative and quantitative methods including interviews, raster statistics, morphometric analyses, and geospatial simulation. With tangible modeling participants built more accurate models that better represented morphological features than they did with either digital or analog modeling. When tangibly modeling they worked in a rapid, iterative process informed by real-time geospatial analytics and simulations. With the aid of real-time simulations they were able to quickly understand and then manipulate how complex topography controls the flow of water.

This repository contains python scripts for reproducing the experiment in GRASS GIS and a LaTeX paper describing the experiment.

GIS data for the experiment, the results of the experiment, and instructions for reproducing the experiment are available at osf.io/82gst/.

The code in this repository is licensed under GPL v2.

The text and images in this repository are licensed under CC BY-SA 4.0. This license does not apply to logos, linked material, quotations, or reprinted images by other authors which may have different licenses.

The data and results for this experiment are available on the Open Science Framework at osf.io/82gst/ under the CC0 license.