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Use of UAV Photogrammetric Data for Estimation of Biophysical Properties in Forest Stands Under Regeneration

Norwegian Institute for Bioeconomy Research (NIBIO); Division of Forest and Forest Resources; National Forest Inventory. Høgskoleveien 8, 1433 Ås, Norway
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Remote Sens. 2019, 11(3), 233; https://doi.org/10.3390/rs11030233
Received: 18 December 2018 / Revised: 17 January 2019 / Accepted: 22 January 2019 / Published: 23 January 2019
(This article belongs to the Special Issue 3D Point Clouds in Forests)
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Abstract

The objective of this study was to assess the use of unmanned aerial vehicle (UAV) data for modelling tree density and canopy height in young boreal forests stands. The use of UAV data for such tasks can be beneficial thanks to the high resolution and reduction of the time spent in the field. This study included 29 forest stands, within which 580 clustered plots were measured in the field. An area-based approach was adopted to which random forest models were fitted using the plot data and the corresponding UAV data and then applied and validated at plot and stand level. The results were compared to those of models based on airborne laser scanning (ALS) data and those from a traditional field-assessment. The models based on UAV data showed the smallest stand-level R M S E values for mean height (0.56 m) and tree density (1175 trees ha−1). The R M S E of the tree density using UAV data was 50% smaller than what was obtained using ALS data (2355 trees ha−1). Overall, this study highlighted that the use of UAVs for the inventory of forest stands under regeneration can be beneficial both because of the high accuracy of the derived data analytics and the time saving compared to traditional field assessments. View Full-Text
Keywords: unmanned aerial vehicle; forest inventory; stands under regeneration; tree density; airborne laser scanning unmanned aerial vehicle; forest inventory; stands under regeneration; tree density; airborne laser scanning
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Puliti, S.; Solberg, S.; Granhus, A. Use of UAV Photogrammetric Data for Estimation of Biophysical Properties in Forest Stands Under Regeneration. Remote Sens. 2019, 11, 233.

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