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Morisset, Australia

Saremi H.,University of New England of Australia | Kumar L.,University of New England of Australia | Turner R.,Remote Census Pty Ltd | Stone C.,Australian Department of Primary Industries and Fisheries
Trees - Structure and Function | Year: 2014

Key message: Significant relationship between tree height and ALS-derived topography was shown. Taller trees were found on slopes <10° and southerly aspects. Potential value of ALS in forest management applications was defined. Accurate information on tree height distribution can provide a better understanding of forest productivity and biomass estimation. Airborne light detection and ranging remote sensing, also known as airborne laser scanning (ALS), has proven to be an effective tool for deriving tree height information in forests. While tree height has been reported to vary in response to many environmental factors, few researchers have demonstrated the effect of topography on tree height variation using ALS data. This study investigated the relationship between tree height variation and ALS-derived topographic aspect and slope factors within two even-aged radiata pine (Pinus radiata D. Don) plantation sites in Nundle, New South Wales, Australia. A total of 447 trees was sampled from 77 plots in two plantation age classes: 193 trees from a 34-year-old site and 254 trees from a 9-year-old site. ALS height estimates were highly correlated with field heights (R 2 = 0.90 and RMSE = 0.66 for 2002 and R 2 = 0.87 and RMSE = 1.49 for 1977 sites). ALS-derived slope and aspect metrics were shown to have a significant relationship with height variation across the stands. The slope (P < 0.01) and aspect (P < 0.001) were significant in the mixed linear models. Overall taller trees were found on slopes below 10° and on southerly aspects, while shorter trees dominated steeper slopes (>20°) and on northerly aspects. However, aspect gradient appeared to have more significant effect on tree heights than slope classes. These results were further verified using an additional 2,000 randomly located trees sampled across the plantations. The study demonstrates a significant relationship between tree height variation and ALS-derived ground aspect and slope categories which may have potential benefits for improving current wood resource inventories and future productivity models. © 2014 Springer-Verlag Berlin Heidelberg. Source


Melville G.,Trangie Agricultural Research Center | Stone C.,Australian Department of Primary Industries and Fisheries | Turner R.,Remote Census Pty Ltd
New Zealand Journal of Forestry Science | Year: 2015

Background: Precision in describing plantation attributes is a key requirement for forestry managers and inventory surveys aim to extract the most precise information possible using the smallest number of plots. This paper quantifies the potential efficiencies to be gained by using Light Detection and Ranging (LiDAR) data as an aid to estimation of standing timber volume in softwood plantations. A range of inventory design and estimation methods were investigated in terms of their overall predictive efficiency. Methods: Field measurements representing four different populations from two Pinus radiata D. Don plantations in New South Wales, Australia, were used to inform statistical models which were then employed to simulate populations of inventory plots. These plots were then “surveyed” using a variety of simulated sampling strategies to quantify the benefits from using LiDAR data as auxiliary information. Model-based and design-based methods were both investigated. Survey design options included stratification and plot selection strategies; estimation options included ratio estimation and regression modelling. Results were compared in terms of the relative bias and root mean squared error of the estimates. Results: The study suggests that relative efficiencies of two-fold or better, are possible with either model-based or model-assisted estimators compared to traditional inventory surveys which use grid samples and simple design-based estimators. This would enable a halving in the required sample size for the same precision for field inventories in these plantations. Conclusion: The use of LiDAR data as an aid to survey design produces marked efficiency gains compared to traditional inventory methods. © 2015, Melville et al.; licensee Springer. Source


Saremi H.,University of New England of Australia | Kumar L.,University of New England of Australia | Turner R.,Remote Census Pty Ltd | Stone C.,Australian Department of Primary Industries and Fisheries | Melville G.,Australian Department of Primary Industries and Fisheries
GIScience and Remote Sensing | Year: 2014

The aim of this study was to determine whether diameter at breast height (DBH, at 1.3 m) and total height of radiata pine (Pinus radiata D. Don) trees showed any significant relationships with microsite estimates of solar radiation. A total of 77 plots were established in two even-aged stands of radiata in Nundle State Forest, New South Wales, Australia. Within these plots, tree DBH and height measurements were recorded and their relationships with solar radiation evaluated. Airborne light detection and ranging (LiDAR) data were processed to generate a high resolution digital elevation model (DEM), and the DEM was used for calculating the incoming solar radiation. Overall, at both study sites, taller and larger trees were found on areas with lower solar radiation, possibly due to a lower loss in soil moisture. The findings of this study suggest that LiDAR-derived DEM estimates of solar radiation are significantly correlated with DBH and height variation, and therefore suitable for use as a sub-compartment stratification variable as well as for possible inclusion in fine-scale estimates of P. radiata growth and productivity. © 2014 Taylor & Francis. Source


Saremi H.,University of New England of Australia | Kumar L.,University of New England of Australia | Turner R.,Remote Census Pty Ltd | Stone C.,Australian Department of Primary Industries and Fisheries | Melville G.,Australian Department of Primary Industries and Fisheries
Annals of Forest Science | Year: 2014

Context: Reliable information on tree stem diameter variation at local spatial scales and on the factors controlling it could potentially lead to improved biomass estimation over pine plantations.Aims: This study addressed the relationship between local topography and tree diameter at breast height (DBH) within two even-aged radiata pine plantation sites in New South Wales, Australia.Methods: A total of 85 plots were established, and 1,302 trees were sampled from the two sites. Airborne light detection and ranging (LiDAR) was used to derive slope and aspect and to link them to each individual tree.Results: The results showed a significant relationship between DBH and local topography factors. At both sites, trees on slopes below 20° and on southerly aspects displayed significantly larger DBHs than trees on steeper slopes and northerly aspects. Older trees with similar heights also exhibited a significant relationship between DBH and aspect factor, where greater DBHs were found on southerly aspects.Conclusions: The observed correlation between tree DBH and LiDAR-derived slope and aspect could contribute to the development of improved biomass estimation approaches in pine plantations. These topographical variables are easily attained with airborne LiDAR, and they could potentially improve DBH predictions in resource inventories (e.g. stand volume or biomass) and support field sampling design. © 2014, INRA and Springer-Verlag France. Source


Kathuria A.,Australian Department of Primary Industries and Fisheries | Turner R.,Remote Census Pty Ltd | Stone C.,Australian Department of Primary Industries and Fisheries | Duque-Lazo J.,University of Cordoba, Spain | West R.,University of Wollongong
Australian Forestry | Year: 2016

We develop and evaluate a new individual tree detection (ITD) algorithm to automatically locate and estimate the number of individual trees within a Pinus radiata plantation from relatively sparse airborne LiDAR point cloud data. The area of interest comprised stands covering a range of age classes and stocking levels. Our approach is based on local maxima (LM) filtering that tackles the issue of selecting the optimal search radius from the LiDAR point cloud for every potential LM using metrics derived from local neighbourhood data points; thus, it adapts to the local conditions, irrespective of canopy variability. This was achieved through two steps: (i) logistic regression model development using simulated stands composed of individual trees derived from real LiDAR point cloud data and (ii) application testing of the model using real plantation LiDAR point cloud data and geolocated, tree-level reference crowns that were manually identified in the LiDAR imagery. Our ITD algorithm performed well compared with previous studies, producing RMSE of 5.7% and a bias of only −2.4%. Finally, we suggest that the ITD algorithm can be used for accurately estimating stocking and tree mapping, which in turn could be used to derive the plot-level metrics for an area-based approach for enhancing estimates of stand-level inventory attributes based on plot imputation. © 2016 Institute of Foresters of Australia (IFA). Source

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