2009
DOI: 10.1016/j.foreco.2009.06.016
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A semi-variogram approach for estimating stems per hectare in Eucalyptus grandis plantations using discrete-return lidar height data

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Cited by 30 publications
(23 citation statements)
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“…Also, tree height estimates may be underestimated because laser pulses are not always reflected from treetops, particularly for trees with smaller crown diameters or conically shaped crowns, whereby the laser pulse may detect the sides of the tree instead of the treetop [7,8]. One of the main advantages of airborne laser scanning (ALS) is that it covers large areas, but costs can be relatively high and lower point densities tend to limit tree detection accuracy, according to [9]. In contrast, terrestrial laser scanning (TLS) produces very high point densities and fills the gap between tree-scale manual measurements and large-scale airborne LiDAR measurements by providing a large amount of precise information on various forest structural parameters [6,10,11].…”
Section: Introductionmentioning
confidence: 99%
“…Also, tree height estimates may be underestimated because laser pulses are not always reflected from treetops, particularly for trees with smaller crown diameters or conically shaped crowns, whereby the laser pulse may detect the sides of the tree instead of the treetop [7,8]. One of the main advantages of airborne laser scanning (ALS) is that it covers large areas, but costs can be relatively high and lower point densities tend to limit tree detection accuracy, according to [9]. In contrast, terrestrial laser scanning (TLS) produces very high point densities and fills the gap between tree-scale manual measurements and large-scale airborne LiDAR measurements by providing a large amount of precise information on various forest structural parameters [6,10,11].…”
Section: Introductionmentioning
confidence: 99%
“…Falkowski et al [4] have found up to a 95% agreement rate when inferring forest inventory classes from lidar data. Stem density calculation over Eucalyptus stands using discrete return lidar [5] showed the feasibility of using lidar for management of such types of plantations. Korpela et al [6] did an extensive study using lidar for estimating single tree position, diameter, height and relative volume, finding a 4.7% error on height estimation, 2% and 10% respectively for commission and omission errors of stem position detection, and 20% error on stem diameter estimation.…”
Section: Introductionmentioning
confidence: 99%
“…There are various established approaches to model validation, e.g., validation based on an independent test data set and cross-validation procedures, also called leave-one-out methods. Ideally, validation based on independently gathered data is highly recommended, but is often expensive and time consuming (Tesfamichael et al 2009).…”
Section: Discussionmentioning
confidence: 99%