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A comparison of area-based forest attributes derived from airborne laser scanner, small-format and medium-format digital aerial photography

Iqbal, IA, Musk, RA, Osborn, J ORCID: 0000-0003-2278-3766, Stone, C and Lucieer, A ORCID: 0000-0002-9468-4516 2019 , 'A comparison of area-based forest attributes derived from airborne laser scanner, small-format and medium-format digital aerial photography' , International Journal of Applied Earth Observation and Geoinformation, vol. 76 , pp. 231-241 , doi: 10.1016/j.jag.2018.12.002.

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Abstract

Forest inventory operations have greatly benefitted from remotely sensed data particularly airborne laser scanning (ALS) which has become a popular technology choice for large-area forest inventories. For remote regions, for fragmented estates or for single stand-level inventories ALS may be unsuitable because of the high cost of data acquisition. Point cloud data generated from digital aerial photography (DAP) is emerging as a cost-effective alternative to ALS. In this study we compared area-based forest inventory attributes derived from point cloud datasets sourced from ALS, small-format and medium-format digital aerial photography (SFP and MFP). Non-parametric modelling approach, namely RandomForest, was employed to model forest structural attributes at both plot- and stand-levels. The results were evaluated using field data collected at 105 inventory plots. At plot-level, the maximum difference among relative RMSEs of basal area (BA), top height (Htop), stocking (N) and total stem volume (TSV) of the three datasets was 2.46%, 0.55%, 13.29% and 2.53%, respectively. At stand-level, the maximum difference among relative RMSEs of BA, Htop, N and TSV of the three datasets was 3.86%, 1.25%, 7.85% and 6.04%, respectively. This study demonstrates the robustness of DAP across different sensors, and thus informs forest managers planning data acquisition solutions to best suit their operational needs.

Item Type: Article
Authors/Creators:Iqbal, IA and Musk, RA and Osborn, J and Stone, C and Lucieer, A
Keywords: forest inventory, Pinus radiata, airborne laser scanning, digital aerial photography, photogrammetry, small-format photography, medium-format photography, image point cloud, Random Forest, remote sensing, forestry
Journal or Publication Title: International Journal of Applied Earth Observation and Geoinformation
Publisher: Elsevier BV
ISSN: 0303-2434
DOI / ID Number: 10.1016/j.jag.2018.12.002
Copyright Information:

© 2018 Elsevier B.V. All rights reserved.

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