Erik Næsset

Bio: Erik Næsset is an academic researcher from Norwegian University of Life Sciences. The author has contributed to research in topics: Forest inventory & Laser scanning. The author has an hindex of 66, co-authored 267 publications receiving 17093 citations.

Determination of mean tree height of forest stands using airborne laser scanner data

Abstract: The mean tree height of forest stands is a crucial stand characteristic in forest planning. Currently, the mean tree height is determined by field measurements or by photogrammetric measurements utilizing aerial photographs. In this study, mean tree height of 36 test stands is derived from tree canopy heights measured by means of an airborne laser scanner. On the average the laser recorded 505–1070 canopy heights per stand. First, the laser mean height is computed as the arithmetic mean of the canopy heights within each stand. The laser mean height underestimates the ground truth mean height by 4.1–5.5 m. Second, a weighted mean of the laser canopy heights is computed. The individual height values are used as weights. The weighted mean height underestimates the true height by 2.1–3.6 m. Finally, the laser mean height is computed as the arithmetic mean of the largest laser values within square grid cells with cell sizes of 15–30 m. The bias of the laser estimates is in the range −0.4 m to 1.9 m. The standard deviation for differences between the laser mean heights and the ground truth mean height is 1.1–1.6 m.

Practical large-scale forest stand inventory using a small-footprint airborne scanning laser

Abstract: Mean tree height, dominant height, mean diameter, stem number, basal area and timber volume of 116 georeferenced field sample plots were estimated from various canopy height and canopy density metrics derived by means of a small-footprint laser scanner over young and mature forest stands using regression analysis. The sample plots were distributed systematically throughout a 6500 ha study area, and the size of each plot was 232.9 m2. Regressions for coniferous forest explained 60–97% of the variability in ground reference values of the six studied characteristics. A proposed practical two-phase procedure for prediction of corresponding characteristics of entire forest stands was tested. Fifty-seven test plots within the study area with a size of approximately 3740 m2 each were divided into 232.9 m2 regular grid cells. The six examined characteristics were predicted for each grid cell from the corresponding laser data using the estimated regression equations. Average values for each test plot were computed...

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Estimation and Inference in Econometrics

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