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Remote Sens. 2017, 9(3), 205; doi:10.3390/rs9030205

A Comparison of Stand-Level Volume Estimates from Image-Based Canopy Height Models of Different Spatial Resolutions

1
Division for Forest Management and Forestry Economics, Croatian Forest Research Institute, Trnjanska Cesta 35, Zagreb HR-10000, Croatia
2
School of Earth, Environment and Society, Bowling Green State University, 190 Overman Hall, Bowling Green, OH 43403, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Guangxing Wang, Erkki Tomppo, Dengsheng Lu, Huaiqing Zhang, Qi Chen, Lars T. Waser, Randolph H. Wynne and Prasad S. Thenkabail
Received: 8 December 2016 / Revised: 22 February 2017 / Accepted: 12 March 2017 / Published: 15 March 2017
(This article belongs to the Special Issue Digital Forest Resource Monitoring and Uncertainty Analysis)
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Abstract

Digital aerial photogrammetry has recently attracted great attention in forest inventory studies, particularly in countries where airborne laser scanning (ALS) technology is not available. Further research, however, is required to prove its practical applicability in deriving three-dimensional (3D) point clouds and canopy surface and height models (CSMs and CHMs, respectively) over different forest types. The primary aim of this study is to investigate the applicability of image-based CHMs at different spatial resolutions (1 m, 2 m, 5 m) for use in stand-level forest inventory, with a special focus on estimation of stand-level merchantable volume of even-aged pedunculate oak (Quercus robur L.) forests. CHMs are generated by subtracting digital terrain models (DTMs), derived from the national digital terrain database, from corresponding digital surface models (DSMs), derived by the process of image matching of digital aerial images. Two types of stand-level volume regression models are developed for each CHM resolution. The first model is based solely on stand-level CHM metrics, whereas in the second model, easily obtainable variables from forest management databases are included in addition to CHM metrics. The estimation accuracies of the stand volume estimates based on stand-level metrics (relative root mean square error RMSE% = 12.53%–13.28%) are similar or slightly higher than those obtained from previous studies in which stand volume estimates were based on plot-level metrics. The inclusion of stand age as an independent variable in addition to CHM metrics improves the accuracy of the stand volume estimates. Improvements are notable for young and middle-aged stands, and negligible for mature and old stands. Results show that CHMs at the three different resolutions are capable of providing reasonably accurate volume estimates at the stand level. View Full-Text
Keywords: aerial images; image matching; forest inventory; pedunculate oak (Quercus robur L.) aerial images; image matching; forest inventory; pedunculate oak (Quercus robur L.)
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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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Balenović, I.; Simic Milas, A.; Marjanović, H. A Comparison of Stand-Level Volume Estimates from Image-Based Canopy Height Models of Different Spatial Resolutions. Remote Sens. 2017, 9, 205.

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