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Forests 2014, 5(5), 936-951; doi:10.3390/f5050936

Analysis of the Influence of Plot Size and LiDAR Density on Forest Structure Attribute Estimates

Geo-Environmental Cartography and Remote Sensing Group, Department of Cartographic Engineering, Geodesy and Photogrammetry, Universitat Politècnica de València, Camino de Vera, s/n, Valencia 46022, Spain
Integrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
School of Forestry, Technical University of Madrid, Ciudad Universitaria s/n, Madrid 28040, Spain
Author to whom correspondence should be addressed.
Received: 1 January 2014 / Revised: 3 March 2014 / Accepted: 13 May 2014 / Published: 16 May 2014
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This paper assesses the combined effect of field plot size and LiDAR density on the estimation of four forest structure attributes: volume, total biomass, basal area and canopy cover. A total of 21 different plot sizes were considered, obtained by decreasing the field measured plot radius value from 25 to 5 m with regular intervals of 1 m. LiDAR data densities were simulated by randomly removing LiDAR pulses until reaching nine different density values. In order to avoid influence of the digital terrain model spatial resolution, eight different resolutions were considered (from 0.25 to 2 m grid size) and tested. A set of per-plot LiDAR metrics was extracted for each parameter combination. Prediction models of forest attributes were defined using forward stepwise ordinary least-square regressions. Results show that the highest R2 values are reached by combining large plot sizes and high LiDAR data density values. However, plot size has a greater effect than LiDAR point density. In general, minimum plot areas of 500–600 m2 are needed for volume, biomass and basal area estimates, and of 300–400 m2 for canopy cover. Larger plot sizes do not significantly increase the accuracy of the models, but they increase the cost of fieldwork. View Full-Text
Keywords: forest inventory; LiDAR; plot size; data density; forest structure; forest attributes; remote sensing forest inventory; LiDAR; plot size; data density; forest structure; forest attributes; remote sensing

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Ruiz, L.A.; Hermosilla, T.; Mauro, F.; Godino, M. Analysis of the Influence of Plot Size and LiDAR Density on Forest Structure Attribute Estimates. Forests 2014, 5, 936-951.

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