GFDRR Webinar

Tangible Landscape

as a tool for modeling and science communication

Helena Mitasova, Anna Petrasova, Vaclav Petras, Payam Tabrizian, Brendan Harmon, Ross Meentemeyer

North Carolina State University

The webinar is presented by the GeoForAll Laboratory at the Center for Geospatial Analytics (CGA), North Carolina State University

CGA is an interdisciplinary research and education center with focus on geospatial computing, modeling, analytics and geovisualization.

We offer MGIST professional master's degree (on-line and on-campus) and a new PhD in Geospatial Analytics launched in Fall 2018

geospatial.ncsu.edu

Authors

Helena Mitasova

Associate Director of Geovisualization

Anna Petrasova

Postdoc at CGA

Brendan Harmon

Assistant Professor
of Landscape Architecture at LSU

Vaclav Petras

Postdoc at CGA

Payam Tabrizian

PhD student
CGA/College of Design

Ross Meentemeyer

CGA Director

Motivation for Tangible Interfaces for GIS

Interaction through mouse, keyboard and display does not encourage creativity.
Manipulating computer models is not intuitive and requires specialized software and training.
Collaboration is restricted as typically only one user at a time can navigate and modify models.

The evolution of tangible geospatial interfaces

Image source: MIT Media Lab,
http://idav.ucdavis.edu/

Illuminating Clay, Tangible Geospatial Modeling System (TanGeoMS), Augmented Reality Sandbox

Ishii H., Ratti C., Piper B., Wang Y., Biderman A. and Ben-Joseph E. "Bringing clay and sand into digital design—continuous tangible user interfaces." BT technology journal 22.4 (2004): 287-299.
L. Tateosian, H. Mitasova, B. A. Harmon, B. Fogleman, K. Weaver, and R. S. Harmon, “TanGeoMS: Tangible Geospatial Modeling System,” IEEE Trans. Vis. Comput. Graph., vol. 16, no. 6, pp. 1605–12, 2010.

Tangible Landscape: real-time coupling with GIS

Tangible Landscape couples a digital and a physical model through a continuous cycle of 3D scanning, geospatial modeling, and projection.

I addressed these questions through the development and application of Tangible Landscape. The new thing Tangible Landscape brings is the real-time coupling with a full-fledged geographic information system. This means we can easily plug in and automate different analyses and geospatial workflows with real landscapes, which brings lot of flexibility. Here you can see the coupling concept - A physical model is continuously scanned by a 3D scanner, the scanned data are imported into GIS, specifically GRASS GIS, where a 3D digital elevation model is computed and a selected analysis or modeling is performed in this case contours are derived and water flow and ponding is simulated. A composite image of the selected map layers is then projected over the model. In this way the system couples the digital and physical models in a continuous cycle of scanning, modeling and projection, providing the user continuous feedback.

Tangible interactions

So we have the scan of the physical model but how do we interact with the model? Tangible geospatial modeling requires different interactions to accommodate different geospatial models and model inputs. To make Tangible Landscape flexible in this regard, we developed multiple ways to interact with the physical models, taking the advantage of both depth and color information coming from the 3D scanner. You can create vector geometries using markers which can be interpreted as points or combined into polylines. Areas of different categories can be designed with pieces of colored felt. The surface from sand is most often interpreted as topography, but it can also represent more abstract surfaces, such as cross sections of a volume or as probability or cost surface. Also, direction can be intuitively manipulated using a colored marker. To detect and interpret these tangible objects and colors, we use a combination of basic geospatial tools, such as raster algebra, more complex algorithms like traveling salesman heuristics, and also classic remote sensing techniques like image segmentation and classification.

Applications: topographic analysis

slope	erosion
landforms

Applications: visibility

Visibility and line of sight

Applications: solar analysis

Solar irradiation and cast shadows

Applications: trail planning

Optimized trail routing between waypoints based on energetics, topography, and cost maps with feedback including trail slopes and viewsheds

Applications: 3D soil moisture exploration

Application: erosion control

Sculpting a check dam to retain storm water and reduce erosion

Application: erosion control

Placing colored felt to modify land cover. Adding grass (light green) and patches of trees (darker green) changes the c-factor thus reducing erosion.

Applications: Dam break

Applications: wildfire spread

Management of emerging infectious disease through participatory modeling

Sudden Oak Death (SOD) case study
tree disease in California and Oregon
simulating disease using spatially-explicit model
workshop with expert stakeholders

Applications: urban growth

Simulation of urban growth scenarios with FUTURES model

Meentemeyer, et al. (2013), FUTURES: multilevel simulations of emerging urban–rural landscape structure using a stochastic patch-growing algorithm.

Applications: urban growth

Serious games: Termite infestation

Manage the spread of termites across a city by treating city blocks using a model of biological invasion in R

Serious games: coastal flooding

Save houses from coastal flooding by building coastal defenses
(Bald Head Island, NC)

Structured problem-solving with rules, challenging objectives, and scoring

Florence hurricane flooding

Realtime 3D rendering with Blender

Designing with Tangible Landscape

Dorothea Dix park case study:
changing landforms and hydrology

Exploring views from the park entrances

Planting trees and siting a shelter

Designing a trail and exploring views

Evaluation of design scenarios

Realism

System setup

projector, scanner, stand, computer, model, table, screen

Software architecture

Building physical 3D models

Hand sculpting from polymeric sand

Hand sculpting with difference feedback

blue → add sand, red → remove sand

3D printing

CNC routing large complex models and molds

Casting polymeric sand

Tangible Landscape for designers

Intuitive, collaborative environment for landscape design augmented with geospatial analyses.

Tangible Landscape for education

Method to improve understanding of geospatial algorithms, processes and interactions.

Tangible Landscape for communities

Platform for decision-making and science communication where people of different backgrounds can interact.

Making geospatial data and tools accessible to all

Tangible Landscape for researchers and developers

Tool for rapid generation of test data for development and evaluation of geospatial algorithms.

Creating test DEMs for landscape evolution analysis

Open source

Tangible Landscape plugin for GRASS GIS
github.com/tangible-landscape/grass-tangible-landscape

GRASS GIS module for importing data from Kinect v2
github.com/tangible-landscape/r.in.kinect

Tangible Landscape repository on Open Science Framework
osf.io/w8nr6

Resources

Tangible Landscape website: tangible-landscape.github.io
Tangible Landscape wiki:
github.com/tangible-landscape/grass-tangible-landscape/wiki
Book: Tangible Modeling with Open Source GIS, second edition