LiDAR remote sensing can be considered a key instrument for studies related to quantifying the vegetation structure. We utilised LiDAR metrics to estimate plot-scale structural parameters of subtropical rainforest and eucalypt-dominated open forest in topographically dissected landscape in north-eastern Australia. This study is considered an extreme application of LiDAR technology for structurally complex subtropical forests in complex terrain. A total of 31 LiDAR metrics of vegetation functional parameters were examined. Multiple linear regression models were able to explain 62% of the variability associated with basal area, 66% for mean diameter at breast height, 61% for dominant height and 60% for foliage projective cover in subtropical rainforest. In contrast, mean height (adjusted r² = 0.90) and dominant height (adjusted r² = 0.81) were predicted with highest accuracy in the eucalypt-dominated open canopy forest. Nevertheless, the magnitude of error for predicting structural parameters of vegetation was much higher in subtropical rainforest than those documented in the literature. Our findings reinforce that obtaining accurate LiDAR estimates of vegetation structure is a function of the complexity of horizontal and vertical structural diversity of vegetation.
Ediriweera, S, Pathirana, S, Danaher, T & Nichols, D 2014, 'Lidar remote sensing of structural properties of subtropical rainforest and eucalypt forest in complex terrain in north-eastern Australia', Journal of Tropical Forest Science, vol. 26, no. 3, pp. 397-408.
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