How far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study

References

• Aakala, T., S. Fraver, B. J. Palik, and A. W. D’Amato. 2012. “Spatially Random Mortality in Old-growth Red Pine Forests of Northern Minnesota.” Canadian Journal of Forest Research-Review Canadian Rech. Forest 42: 899–907.
   Google Scholar
• Adams, M. B., L. Loughry, and L. Plaugher. 2004. “Experimental Forests and Ranges of the USDA Forest Service”. In USDA For. Serv. Gen. Technical Report, NE-321, 178.
   Google Scholar
• Andersen, H. E., S. E. Reutebuch, and R. J. McGaughey. 2006. “A Rigorous Assessment of Tree Height Measurements Obtained Using Airborne Lidar and Conventional Field Methods.” Canadian Journal of Remote Sensing 32 (5): 355–366. doi:10.5589/m06-030.
   Web of Science ®Google Scholar
• Bradford, J. B., and B. J. Palik. 2009. “A Comparison of Thinning Methods in Red Pine: Consequences for Stand-level Growth and Tree Diameter.” Canadian Journal of Forest Research 39: 489–496. doi:10.1139/X08-201.
   Web of Science ®Google Scholar
• Buckman, R. E. 1964. “Effects of Prescribed Burning on Hazel in Minnesota.” Ecology 45: 626–629. doi:10.2307/1936114.
   Web of Science ®Google Scholar
• Coveney, S. 2013. “Association of Elevation Error with Surface Type, Vegetation Class and Data Origin in Discrete-returns Airborne LiDAR.” International Journal of Geographical Information Science 27 (3): 467–483. doi:10.1080/13658816.2012.695794.
   Web of Science ®Google Scholar
• D’Amato, A. W., B. J. Palik, and C. C. Kern. 2010. “Growth, Yield, and Structure of Extended Rotation Pinus Resinosa Stands in Minnesota, USA.” Canadian Journal of Forest Research 40: 1000–1010. doi:10.1139/X10-041.
   Web of Science ®Google Scholar
• Dubayah, R., and J. Drake. 2000. “LiDAR Remote Sensing for Forestry Applications.” Journal of Forestry 98: 44–46.
   Web of Science ®Google Scholar
• Edson, C., and M. G. Wing. 2011. “Airborne Light Detection and Ranging (Lidar) for Individual Tree Stem Location, Height, and Biomass Measurements.” Remote Sensing 3: 2494–2528. doi:10.3390/rs3112494.
   Web of Science ®Google Scholar
• Falkowski, M. J., A. M. S. Smith, A. T. Hudak, P. E. Gessler, L. A. Vierling, and N. L. Crookston. 2006. “Automated Estimation of Individual Conifer Tee Height and Crown Diameter via Two-dimensional Spatial Wavelet Analysis of Lidar Data.” Canadian Journal of Remote Sensing 32 (2): 153–161. doi:10.5589/m06-005.
   Web of Science ®Google Scholar
• Falkowski, M. J., A. M. S. Smith, P. E. Gessler, A. T. Hudak, L. A. Vierling, and J. S. Evans. 2008. “The Influence of Conifer Forest Canopy Cover on the Accuracy of Two Individual Tree Measurement Algorithms Using Lidar Data.” Canadian Journal of Remote Sensing 34 (2): S338–S350. doi:10.5589/m08-055.
   Google Scholar
• Fraver, S., and B. J. Palik. 2012. “Stand and Cohort Structures of Old-growth Pinus Resinosa-dominated Forests of Northern Minnesota, USA.” Journal of Vegetable Science 23: 249–259. doi:10.1111/j.1654-1103.2011.01348.x.
   Web of Science ®Google Scholar
• Gatziolis, D., and H. E. Andersen. 2008. “A Guide to LIDAR Data Acquisition and Processing for the Forests of the Pacific Northwest.” In Gen. Technical Report. PNW-GTR-768. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station.
   Google Scholar
• Hinsley, S., R. Hill, D. Gaveau, and P. Bellamy. 2002. “Quantifying Woodland Structure and Habitat Quality for Birds Using Airborne Laser Scanning.” Functional Ecology 16 (6): 851–857. doi:10.1046/j.1365-2435.2002.00697.x.
   Web of Science ®Google Scholar
• Hopkinson, C., L. Chasmer, C. Young-Pow, and P. Treitz. 2004. “Assessing Forest Metrics with a Ground-based Scanning Lidar.” Canadian Journal of Forest Research 34 (3): 573–583. doi:10.1139/x03-225.
   Web of Science ®Google Scholar
• Hyyppä, H., X. Yu, J. Hyyppä, H. Kaartinen, S. Kaasalainen, E. Honkavaara, and P. Rönnholm. 2005. “Factors Affecting the Quality of DTM Generation in Forested Areas.” In ISPRS Workshop “Laser scanning 2005”. Enschede, the Netherlands.
   Google Scholar
• Latifi, H., F. E. Fassnacht, J. Müller, A. Tharani, S. Dech, and M. Heurich. 2015. “Forest Inventories by LiDAR Data: A Comparison of Single Tree Segmentation and Metric-based Methods for Inventories of A Heterogeneous Temperate Forest.” International Journal of Applied Earth Observation and Geoinformation 42: 162–174. doi:10.1016/j.jag.2015.06.008.
   Web of Science ®Google Scholar
• McRoberts, R., E. Tomppo, and E. Næsset. 2010. “Advances and Emerging Issues in National Forest Inventories.” Scandinavian Journal of Forest Research 25 (4): 368–381. doi:10.1080/02827581.2010.496739.
   Web of Science ®Google Scholar
• Means, J., S. Acker, B. Fitt, M. Renslow, L. Emerson, and C. Hendrix. 2000. “Predicting Forest Stand Characteristics with Airborne Scanning Lidar.” Photogrammetric Engineering and Remote Sensing 66 (11): 1367–1371.
   Web of Science ®Google Scholar
• Montagnoli, A., S. Fusco, M. Terzagni, A. Kirschbaum, D. Pflugmacher, W. B. Cohen, G. S. Scippa, and D. Chiatante. 2015. “Estimating Forest Aboveground Biomass by Low Density Lidar Data in Mixed Broadleaved Forests in the Italian Pre-Alps.” Forest Ecosystem 2: 10. doi:10.1186/s40663-015-0035-6.
   Web of Science ®Google Scholar
• Morsdorf, F., E. Meier, B. Kötz, K. Itten, M. Dobbertin, and B. Allgöwer. 2004. “Lidar-based Geometric Reconstruction of Boreal Type Forest Stands at Single Tree Level for Forest and Wildland Fire Management.” Remote Sensing of Environment 92 (3): 353–362. doi:10.1016/j.rse.2004.05.013.
   Web of Science ®Google Scholar
• Perala, D. A., and D. H. Alban. 1993. “Allometric Biomass Estimators for Aspen-biased Ecosystems in the Upper Great Lakes.” In Res. Pap. NC-314, 38. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station.
   Google Scholar
• Popescu, S. C. 2007. “Estimating Biomass of Individual Pine Trees Using Airborne Lidar.” Biomass and Bioenergy 31 (9): 646–655. doi:10.1016/j.biombioe.2007.06.022.
   Web of Science ®Google Scholar
• Popescu, S. C., and K. Zhao. 2008. “A Voxel-based Lidar Method for Estimating Crown Base Height for Deciduous and Pine Trees.” Remote Sensing of Environment 112 (3): 767–781. doi:10.1016/j.rse.2007.06.011.
   Web of Science ®Google Scholar
• Reitberger, J., C. Schnörr, P. Krzystek, and U. Stilla. 2009. “3D Segmentation of Single Trees Exploiting Full Waveform LIDAR Data.” ISPRS Journal of Photogrammetry and Remote Sensing 64: 561–574. doi:10.1016/j.isprsjprs.2009.04.002.
   Web of Science ®Google Scholar
• Riaño, D., F. Valladares, S. Condés, and E. Chuvieco. 2004. “Estimation of Leaf Area Index and Covered Ground from Airborne Laser Scanner (Lidar) in Two Contrasting Forests.” Agricultural and Forest Meteorology 124 (3–4): 269–275. doi:10.1016/j.agrformet.2004.02.005.
   Web of Science ®Google Scholar
• Richards, J. A. 1999. Remote Sensing Digital Image Analysis, 240. Berlin: Springer-Verlag.
   Google Scholar
• Saremi, H., L. Kumar, C. Stone, G. Melville, and R. Turner. 2014. “Sub-compartment Variation in Tree Height, Stem Diameter and Stocking in a Pinus Radiata D.” Don Plantation Examined Using Airborne LiDAR Data. Remote Sensing 6 (8): 7592–7609.
   Google Scholar
• Suratno, A., C. Seielstad, and L. Queen. 2009. “Tree Species Identification in Mixed Coniferous Forest Using Airborne Laser Scanning.” Journal of Photogrammetry and Remote Sensing 64: 683–693. doi:10.1016/j.isprsjprs.2009.07.001.
   Web of Science ®Google Scholar
• VanderSchaaf, C. L. 2012. “Mixed-Effects Height-Diameter Models for Commercially and Ecologically Important Conifers in Minnesota.” Northern Journal of Applied Forestry 29 (1): 15–20. doi:10.5849/njaf.11-005.
   Google Scholar
• Willmott, C., and K. Matsuura. 2005. “Advantages of the Mean Absolute Error (MAE) over the Root Mean Square Error (RMSE) in Assessing Average Model Performance.” Climate Research 30 (1): 79. doi: 10.3354/cr030079.
   Web of Science ®Google Scholar
• Woudenberg, S. W., B. L. Conkling, B. M. O’Connell, E. B. Lapoint, J. A. Turner, and K. L. Waddell. 2010. “The Forest Inventory and Analysis Database: Database Description and User’s Manual Version 4.0 For Phase 2..” In US For. Serv. Gen. Technical Report RMRS-GTR-245.
   Google Scholar