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  • 1
    Publication Date: 2014-11-01
    Description: Forest compartments are usually delineated according to artificial or natural boundaries and usually include portions of different strata. While volume estimation of each stratum can be performed from field plots located within each stratum, volume estimation in portions of the stratum may be problematic owing to the small number (or even the absence) of plots falling in those portions. If upper canopy heights from airborne laser scanning are available at the pixel level for the whole survey area, these data are used as auxiliary information. A ratio model presuming a proportional relationship between transformed heights (e.g., power of heights) and volumes at the pixel level is adopted to guide estimation. From this model, the volume within any portion of the survey area is estimated as the proportionality factor estimate multiplied by the total of transformed heights in that portion. This estimator is considered from the model-based, design-based, and hybrid perspectives. Variances and their estimators are derived under the three approaches together with the corresponding confidence intervals. The volume estimator and the variance estimators are checked from the design-based point of view by a simulation study performed on a real forest in northwestern Italy. An application to a public forest estate in the same zone is performed.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
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  • 2
    Publication Date: 2015-04-01
    Description: LiDAR-based techniques to estimate forest variables at the stand level require accurate calibration through ground truth data. One purpose of this study was to verify whether angle count samples can be used as suitable ground truth to calibrate LiDAR-based models for timber volume estimation. Volume data were acquired on the ground for 79 plots in the Latemar forest (province of Bolzano, Italian Alps). A simple linear regression model, using the sum of all of the tree canopy heights in the plot as the explanatory variable, was adopted. As angle count samples have no fixed area, three different methods to approximate their size were compared. The angle count sample area can be properly approximated by visual assessment of the tree size classes and by callipering the largest tree in the plot. The results show that angle count sampling can be an efficient solution to calibrate LiDAR-based models: they produced fair estimates at the plot level (relative root mean square error (RMSE), 26.6%) that were better than fixed-radius plot estimates with full callipering (RMSE, 29.7%). Estimate uncertainty at increasingly large forest stand areas was also calculated by means of a simulation procedure. It showed that low uncertainty (standard error of estimate = approximately 2%) could be reached at a forest compartment level (19 ha on average).
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
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