2nd International Conference on GeoComputation

Data Visualisation for New Zealand Forestry

Alan J. Thorn

Resource Monitoring Unit
New Zealand Forest
Research Institute
Private Bag 3020, Rotorua,
New Zealand

Terry C. Daniel

Professor Psychology and Natural Renewable Resources,
University of Arizona
Environmental Perception Laboratory,
Department of Psychology
Tucson, Arizona 85721, USA

Brian Orland

Professor Landscape Architecture,
University of Illinois
Imaging Systems Laboratory,
214 Mumford Hall,
1301 West Gregory Drive,
Illinois 61801, USA

Presented at the second annual conference of GeoComputation ‘97 & SIRC ‘97, University of Otago, New Zealand, 26-29 August 1997


The New Zealand Resource Management Act emphasises, among other things, the evaluation of the effects of forestry operations, and the inclusion of those affected into the decision making process. Visual images are a useful method for displaying the effects of planned forestry activities, and are easily understood by most of the general public. While the creation of fully accurate photo-realistic images is still the domain of super computers, it is possible to come close using data visualisation techniques that have been developed for a desktop computer.

The data visualisation techniques reported in this paper focus on the creation of photo-realistic, oblique view images depicting the predicted results of alternative management activities. A Geographic Information System (GIS) is used to develop a digital terrain model of the scene. Other information from the GIS database, such as forest stand boundaries, is shown on or draped over terrain model. Biophysical models are used to ‘grow’ the trees to be placed in the landscape using software called SmartForest II. Calibrated analytical images are positioned on the terrain model to match the planned forestry activities. This creates representations that are sufficiently accurate in all dimensions, and facilitates rendering photo-realistic images. The resulting images have been used in surveys to gauge public preference of forestry options.