Updating residual stem volume estimates using ALS- and UAV-acquired stereo-photogrammetric point clouds

References

• Adams, T., C. Brack, T. Farrier, and R. Brownlie. 2011. “So You Want to Use Lidar? - A Guide on How to Use Liddar in Forestry.” New Zeland Journal of Forestry 55 (4): 19–23.
   Google Scholar
• Aguilar, F. J., and J. P. Mills. 2008. “Accuracy Assessment of Lidar-Derived Digital Elevation Models.” The Photogrammetric Record 23 (122): 148–169. doi:10.1111/phor.2008.23.issue-122.
   Web of Science ®Google Scholar
• Bollandsås, O. M., T. G. Gregoire, E. Næsset, and B.-H. Øyen. 2013. “Detection of Biomass Change in a Norwegian Mountain Forest Area Using Small Footprint Airborne Laser Scanner Data.” Statistical Methods & Applications 22 (1): 113–129. doi:10.1007/s10260-012-0220-5.
   Web of Science ®Google Scholar
• Cao, L., N. C. Coops, J. L. Innes, S. R. J. Sheppard, L. Fu, H. Ruan, and G. She. 2016. “Remote Sensing of Environment Estimation of Forest Biomass Dynamics in Subtropical Forests Using Multi-Temporal Airborne Lidar Data.” Remote Sensing of Environment 178: 158–171. doi:10.1016/j.rse.2016.03.012.
   Web of Science ®Google Scholar
• Dandois, J. P., and E. C. Ellis. 2010. “Remote Sensing of Vegetation Structure Using Computer Vision.” Remote Sensing 2 (4): 1157–1176. doi:10.3390/rs2041157.
   Web of Science ®Google Scholar
• Dawson, R., H. Armleder, B. Bings, and D. Peel. 2007. Management Strategy for Mule Deer Winter Ranges in the Cariboo-Chilcotin Part 1a: Management Plan for Shallow and Moderate Snowpack Zones 2007. Vancouver: British Columbia Ministry of Forests and Range.
   Google Scholar
• Day, K. J. 2007. Management and Working Plan #3. Williams Lake, BC: UBC Alex Fraser Research Forest.
   Google Scholar
• Ferraz, A., C. Mallet, and N. Chehata. 2014. “Large Scale Road Network Extraction in Forested Moutainous Areas Using Airborne Laser Scanning Data.” In 2014 IEEE Geoscience and Remote Sensing Symposium, 4315–4318. doi:10.1109/IGARSS.2014.6947444.
   Google Scholar
• Gobakken, T., O. M. Bollandsås, and E. Næsset. 2015. “Comparing Biophysical Forest Characteristics Estimated from Photogrammetric Matching of Aerial Images and Airborne Laser Scanning Data.” Scandinavian Journal of Forest Research 30 (1): 73–86. doi:10.1080/02827581.2014.961954.
   Web of Science ®Google Scholar
• Grenzdörffer, G., A. Engel, and B. Teichert. 2008. “The Photogrammetric Potential of Low-Cost UAVs in Forestry and Agriculture.” International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences 31 (B3): 1207–1214.
   Google Scholar
• Hall, R. J., R. T. Morton, and R. N. Nesby. 1989. “A Comparison of Existing Models for DBH Estimation from Large-Scale Photos.” The Forestry Chronicle 65 (2): 114–120. doi:10.5558/tfc65114-2.
   Web of Science ®Google Scholar
• Holmgren, J. 2004. “Prediction of Tree Height, Basal Area and Stem Volume in Forest Stands Using Airborne Laser Scanning.” Scandinavian Journal of Forest Research 19 (6): 543–553. doi:10.1080/02827580410019472.
   Web of Science ®Google Scholar
• Jaakkola, A., J. Hyyppä, A. Kukko, X. Yu, H. Kaartinen, M. Lehtomäki, and Y. Lin. 2010. “A Low-Cost Multi-Sensoral Mobile Mapping System and Its Feasibility for Tree Measurements.” ISPRS Journal of Photogrammetry and Remote Sensing 65 (6): 514–522. doi:10.1016/j.isprsjprs.2010.08.002.
   Web of Science ®Google Scholar
• Koh, L. P., and S. A. Wich. 2012. “Dawn of Drone Ecology: Low-Cost Autonomous Aerial Vehicles for Conservation.” Tropical Conservation Science 5 (2): 121–132.
   Web of Science ®Google Scholar
• Koot, C., K. Day, S. Ewen, and D. Skea. 2015. Harvesting on Mule Deer Winter Range under General Wildlife Measures for Shallow & Moderate Snowpack Zones: Approach and Lessons Learned following a Second Harvest Entry after 30 Years. Williams Lake, BC: UBC Alex Fraser Research Forest. June.
   Google Scholar
• Lim, K., P. Treitz, P. Treitz, M. Wulder, B. St-Onge, and M. Flood. 2003. “LiDAR Remote Sensing of Forest Structure.” Progress in Physical Geography 27 (1): 88–106. doi:10.1191/0309133303pp360ra.
   Web of Science ®Google Scholar
• Lisein, J., M. Pierrot-Deseilligny, S. Bonnet, and P. Lejeune. 2013. “A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery.” Forests 4 (4): 922–944. doi:10.3390/f4040922.
   Web of Science ®Google Scholar
• Maltamo, M., K. Eerikäinen, J. Pitkänen, J. Hyyppä, and M. Vehmas. 2004. “Estimation of Timber Volume and Stem Density Based on Scanning Laser Altimetry and Expected Tree Size Distribution Functions.” Remote Sensing of Environment 90 (3): 319–330. doi:10.1016/j.rse.2004.01.006.
   Web of Science ®Google Scholar
• Maltamo, M., T. Tokola, and M. Lehikoinen. 2003. “Estimating Stand Characteristics by Combining Single Tree Pattern Recognition of Digital Video Imagery and a Theoretical Diameter Distribution Model.” Forest Science 49 (1): 98–109.
   Web of Science ®Google Scholar
• Næsset, E. 2004. “Accuracy of Forest Inventory Using Airborne Laser Scanning: Evaluating the First Nordic Full-Scale Operational Project.” Scandinavian Journal of Forest Research 19 (6): 554–557. doi:10.1080/02827580410019544.
   Web of Science ®Google Scholar
• Näsi, R., E. Honkavaara, P. Lyytikäinen-Saarenmaa, M. Blomqvist, P. Litkey, T. Hakala, N. Viljanen, T. Kantola, T. Tanhuanpää, and M. Holopainen. 2015. “Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level.” Remote Sensing 7 (11): 15467–15493. doi:10.3390/rs71115467.
   Web of Science ®Google Scholar
• Nilsson, M. 1996. “Estimation of Tree Heights and Stand Volume Using an Airborne Lidar System.” Remote Sensing of Environment 56 (1): 1–7. doi:10.1016/0034-4257(95)00224-3.
   Web of Science ®Google Scholar
• Økseter, R., O. M. Bollandsås, T. Gobakken, and E. Næsset. 2015. “Modeling and Predicting Aboveground Biomass Change in Young Forest Using Multi-Temporal Airborne Laser Scanner Data.” Scandinavian Journal of Forest Research 30 (5): 458–469. doi:10.1080/02827581.2015.1024733.
   Web of Science ®Google Scholar
• Rahlf, J., J. Breidenbach, S. Solberg, E. Næsset, and R. Astrup. 2014. “Remote Sensing of Environment Comparison of Four Types of 3D Data for Timber Volume Estimation.” Remote Sensing of Environment 155: 325–333. doi:10.1016/j.rse.2014.08.036.
   Web of Science ®Google Scholar
• Reutebuch, S. E., H. Andersen, R. J. Mcgaughey, and L. Forest. 2005. “Light Detection and Ranging (LIDAR): An Emerging Tool for Multiple Resource Inventory.” Journal of Forestry 103 (6): 286–292. doi:10.1080/01431160500396493.
   Web of Science ®Google Scholar
• Tang, L., G. Shao, and R. P. A. Á. Forest. 2015. “Drone Remote Sensing for Forestry Research and Practices.” Journal of Forestry Research 26 (4): 791–797. doi:10.1007/s11676-015-0088-y.
   Web of Science ®Google Scholar
• Tao, W., Y. Lei, and P. Mooney. 2011. “Dense Point Cloud Extraction from UAV Captured Images in Forest Area.” In ICSDM 2011 - Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, 389–392. doi:10.1109/ICSDM.2011.5969071.
   Google Scholar
• Tompalski, P., N. C. Coops, J. C. White, and M. A. Wulder. 2014. “Forest Ecology and Management Simulating the Impacts of Error in Species and Height upon Tree Volume Derived from Airborne Laser Scanning Data.” Forest Ecology and Management 327: 167–177. doi:10.1016/j.foreco.2014.05.011.
   Web of Science ®Google Scholar
• Tomppo, E., T. Gschwantner, M. Lawrence, and R. E. McRoberts. 2010. National Forest Inventories Pathways for Common Reporting. Springer Netherlands. doi:10.1007/978-90-481-3233-1.
   Google Scholar
• Vastaranta, M., M. A. Wulder, J. C. White, A. Pekkarinen, S. Tuominen, C. Ginzler, V. Kankare, M. Holopainen, J. Hyyppä, and H. Hyyppä. 2013. “Airborne Laser Scanning and Digital Stereo Imagery Measures of Forest Structure: Comparative Results and Implications to Forest Mapping and Inventory Update.” Canadian Journal of Remote Sensing 39 (5): 382–395. doi:10.5589/m13-046.
   Web of Science ®Google Scholar
• Wallace, L., A. Lucieer, C. Watson, and D. Turner. 2012. “Development of a UAV-Lidar System with Application to Forest Inventory.” Remote Sensing 4 (12): 1519–1543. doi:10.3390/rs4061519.
   Web of Science ®Google Scholar
• Wang, Z., R. Boesch, and C. Ginzler. 2007. “Color and LIDAR Data Fusion: Application to Automatic Forest Boundary Delineation in Aerial Images.” International Archives of Photogrammetry Remote Sensing and Spatial Information Science 36 (1): W51.
   Google Scholar
• White, J., C. Stepper, P. Tompalski, N. Coops, and M. Wulder. 2015. “Comparing ALS and Image-Based Point Cloud Metrics and Modelled Forest Inventory Attributes in a Complex Coastal Forest Environment.” Forests 6 (10): 3704–3732. doi:10.3390/f6103704.
   Web of Science ®Google Scholar
• White, J., M. Wulder, A. Varhola, M. Vastaranta, N. Coops, B. Cook, D. Pitt, and M. Woods. 2013. “A Best Practices Guide for Generating Forest Inventory Attributes from Airborne Laser Scanning Data Using an Area-Based Approach.” The Forestry Chronicle 89 (6): 722–723. doi:10.5558/tfc2013-132.
   Web of Science ®Google Scholar
• White, J., M. Wulder, M. Vastaranta, N. Coops, D. Pitt, and M. Woods. 2013. “The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning.” Forests 4 (3): 518–536. doi:10.3390/f4030518.
   Web of Science ®Google Scholar
• Wulder, M. A., C. W. Bater, N. C. Coops, T. Hilker, and J. C. White. 2008. “The Role of LiDAR in Sustainable Forest Management.” The Forestry Chronicle 84 (6): 807–826. doi:10.5558/tfc84807-6.
   Web of Science ®Google Scholar
• Zhang, J., G. Sohn, and M. Brédifb. 2013. “Single Tree Detection from Airbone Laser Scanning Data: A Stochastic Approach.” ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences 1 (1): 41–46. doi:10.5194/isprsannals-II-3-W1-41-2013.
   Google Scholar