University of Tasmania

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Using topographic attributes to predict the density of vegetation layers in a wet eucalypt forest

journal contribution
posted on 2023-05-21, 04:30 authored by Bechu Yadav, Arko LucieerArko Lucieer, Gregory JordanGregory Jordan, Susan BakerSusan Baker
Mapping the structure of forest vegetation with field surveys or high-resolution light detection and ranging (LiDAR) data is costly. We tested whether landscape topography and underlying geology 10 could predict the vegetation density of a 19 km2 area of wet eucalypt forest at the Warra Long-Term Ecological Research Supersite, Tasmania, Australia. Using spatial layers for 12 topographic attributes derived from digital terrain models (DTMs) and a geology layer, we predicted the vegetation density of three strata with a high degree of accuracy (validation root mean square error ranged from 9.0% to 13.7%). The DTMs with 30 m resolution provided greater predictive accuracy than DTMs with higher 15 resolution. The importance of different variables depended on spatial resolution and strata. Among the predictor variables, geology generally had the highest predictive importance, followed by solar radiation. Topographic Position Index, aspect, and System for Automated Geoscientific Analyses Wetness Index had moderate importance. This study demonstrates that geological and topographic attributes can provide useful predictions for the density of vegetation layers in a tall wet sclerophyll 20 primary forest. Given the good performance of the model based on 30 m DTM resolution, the predictive power of the models could be tested on a larger geographical area using lower-density Q2 LiDAR point clouds combined with medium-resolution satellite data.


Australian Research Council

Forestry Tasmania



Publication title

Australian Forestry








School of Geography, Planning and Spatial Sciences


Taylor & Francis Australasia

Place of publication


Rights statement

© 2021 Institute of Foresters of Australia (IFA)

Repository Status

  • Restricted

Socio-economic Objectives

Assessment and management of terrestrial ecosystems