Modelling tree size diversity from airborne laser scanning using canopy height models with image texture measures

By I. Özdemir, Daniel N. M. Donoghue. 2013

59 citations recorded by the source corpus.

Abstract The aim of this study is to investigate the relationships between the plot-level tree size diversity and variables derived from airborne laser scanning (ALS) data, which is a type of LiDAR measurement. We conducted a study using forest stands with a range of managed and near-natural stands with a broad range of species. 33 Plots that represent the forest stand variety in the study area were sampled; within each plot four biophysical variables were measured by ground-based methods, these were height (TH), diameter at breast height (DBH), crown length (CL), and crown width (CW). The resultant tree size diversity was parameterised as Lmoments (t) statistics and compared with both point-based and grid-based laser scanning diversity variables. Point-based measures included the ratios of the Percentile means (P99/P25, P99/P50, P99/75, and P99/P90), Coefficient of variation, Skewness, Kurtosis, and Lmoments (t). The grid-based texture measures derived from the ALS Canopy Height Models (CHMs) included first-order texture, Standard Deviation of Grey Levels (SDGL), and three second-order texture measures, including Contrast, Entropy and Correlation. Furthermore, we tested the influence of scale by analysing the effect of grid cell sizes when generating CHMs from the raw point cloud ALS data. Using linear regression analysis, we show that the grid-based texture measures are superior predictors of tree height diversity than the point-based metrics. Sixty percent of the variance in the tree height diversity and 51% of the variance in the DBH Diversity were explained by the SDGL and Correlation texture measures, respectively (p

Subfields: Environmental Engineering, Insect Science, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/951367f8fcae89695c768e0235d0aaf0d8fd92c4

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In Environmental Engineering

In Insect Science

In Nature and Landscape Conservation

Citations in the corpus

Practical guidelines for choosing GLCM textures to use in landscape classification tasks over a range of moderate spatial scales (2017, background): “Its utility has been corroborated for high spatial resolution as well as moderate resolution images (Ozdemir and Karnieli 2011; Murray, Lucieer, and Williams 2010; Ozdemir and Donaghue 2013; Rabia and Terribile 2013).”
Comparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves (2014, background): “The attention has recently been turned to studying tree size inequality by L-moments, especially with regards to their relations with ALS datasets (Ozdemir and Donoghue, 2013; Valbuena et al., 2013b).”