Visualizing forest landscapes using public data sources

Three-dimensional (3-D) visualizations of forest landscapes are quantitative ecological information-based techniques that can be used to visualize forest structure, dynamics, landscape transformations and regional plans. Visualizing forests and landscapes with limited ground observations are often the primary challenge for quality animations. Conducting stand-level field surveys over a large forest area is time consuming, labor-intensive and expensive. An alternative is to use existing public datasets. We used the Forest Inventory and Analysis (FIA) database and other existing vegetation data, classified Landsat TM imagery, measurements of tree architecture and Forest Vegetation Simulator (FVS) to visualize a forest landscape in the Washburn District of the Chequamegon National Forest (CNF) in northern Wisconsin to generate useful information for resource management at multiple scales. Realistic images for tree species were designed using the Tree Professional 5 software package. Empirical models were developed to calculate necessary information such as tree height and stand density from DBH, basal area and species composition. The 3-D visualizations were developed at stand and landscape levels within Visual Nature Studio 2.01. Different perspectives of the forest and landscape were visualized through zooming, variable latitudes and flying through. Potential applications of these animations are discussed within a context of alternative management of forests and landscapes (e.g., fire and harvesting), public education and decision-making processes. Results from our study demonstrate that public datasets are suitable for visualizing the dynamics of forests and landscapes, although precisely visualizing forest history is still challenging. It is appropriate to use FIA data for stand level visualization and existing vegetation data for landscape scale visualization. With these different public data sources, forests can be visualized at levels varying from a single stand to the landscape/regional level. © 2005 Elsevier B.V. All rights reserved.