2016
DOI: 10.1080/00049158.2016.1153770
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Development of an automated individual tree detection model using point cloud LiDAR data for accurate tree counts in a Pinus radiata plantation

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Cited by 21 publications
(29 citation statements)
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“…Then, the ITDs measure or predict treelevel variables, such as height and volume, from LiDAR data and aggregate them to obtain stand-level forest inventory results . ITD approaches have an advantage over ABAs regarding improving the prediction of species-specific forest attributes (Yao et al, 2012) and the prediction of timber assortments (Kathuria et al, 2016;Vastaranta et al, 2011;Zhang et al, 2014). Another advantage of ITCs is that they can reduce the amount of or potentially even replace the expensive fieldwork required for ABAs (Hyyppä et al, 2008;Vastaranta et al, 2012).…”
Section: Lidar Remote Sensing Technology Of Forest Inventorymentioning
confidence: 99%
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“…Then, the ITDs measure or predict treelevel variables, such as height and volume, from LiDAR data and aggregate them to obtain stand-level forest inventory results . ITD approaches have an advantage over ABAs regarding improving the prediction of species-specific forest attributes (Yao et al, 2012) and the prediction of timber assortments (Kathuria et al, 2016;Vastaranta et al, 2011;Zhang et al, 2014). Another advantage of ITCs is that they can reduce the amount of or potentially even replace the expensive fieldwork required for ABAs (Hyyppä et al, 2008;Vastaranta et al, 2012).…”
Section: Lidar Remote Sensing Technology Of Forest Inventorymentioning
confidence: 99%
“…ABAs rely on statistical principles and predict forest attributes based on parametric regression or nonparametric imputation models built between using field measured variables and features derived from LiDAR data (Kathuria et al, 2016;Naesset, 2002). For instance, in ABAs statistical features, such as percentiles of laser canopy height distribution, are used as predictors in a model-based framework to estimate forest height characteristics in a certain sampling area (e.g., raster grid cell or segment) (Nelson et al, 1988;Vastaranta et al, 2011).…”
Section: Lidar Remote Sensing Technology Of Forest Inventorymentioning
confidence: 99%
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