Prediction of vegetation structure from LIDAR and multispectral satellite data in a topographically complex landscape, Eastern Australia
نویسندگان
چکیده
Measures of forest structure provide an important indication of productivity, health and the growth stage of a forest. Using traditional field-based approaches, extraction of such structural parameters is often time consuming and labour intensive. Remote sensing is a cost effective technique for mapping and interpreting some features of vegetation; and LiDAR provides highly accurate measurements in the vertical and horizontal planes of vegetation structure that can approximate field measurements. In this study, we integrated LiDAR and Landsat TM to model the variation of biophysical parameters of a topographically complex landscape. Focusing on eucalyptus-dominated open forests in eastern Australia, this study provides an insight into how integrating small-footprint LiDAR and Landsat data can be used to develop models to assess vegetation structural attributes. This study demonstrates that fundamental forest structure attributes can be modelled with current remote sensing technologies.
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