Airborne Laser Scanning Outperforms the Alternative 3D Techniques in Capturing Variation in Tree Height and Forest Density in Southern Boreal Forests

Authors

  • Mikko Vastaranta University of Eastern Finland http://orcid.org/0000-0001-6552-9122
  • Tuomas Yrttimaa University of Eastern Finland
  • Ninni Saarinen University of Eastern Finland
  • Xiaowei Yu Finnish Geospatial Research Institute, National Land Survey, Finland
  • Mika Karjalainen Finnish Geospatial Research Institute, National Land Survey, Finland
  • Kimmo Nurminen Finnish Geospatial Research Institute, National Land Survey, Finland
  • Kirsi Karila Finnish Geospatial Research Institute, National Land Survey, Finland
  • Ville Kankare University of Helsinki, Finland
  • Ville Luoma University of Helsinki, Finland
  • Jiri Pyörälä University of Helsinki, Finland
  • Samuli Junttila University of Helsinki, Finland
  • Topi Tanhuanpää University of Helsinki, Finland
  • Harri Kaartinen Finnish Geospatial Research Institute, National Land Survey, Finland
  • Antero Kukko Finnish Geospatial Research Institute, National Land Survey, Finland
  • Eija Honkavaara Finnish Geospatial Research Institute, National Land Survey, Finland
  • Anttoni Jaakkola Finnish Geospatial Research Institute, National Land Survey, Finland
  • Xinlian Liang Finnish Geospatial Research Institute, National Land Survey, Finland
  • Yunsheng Wang Finnish Geospatial Research Institute, National Land Survey, Finland
  • Matti Vaaja Canadian Forest Service (Pacific Forestry Centre), Canada
  • Hannu Hyyppä Aaalto University, Finland
  • Masato Katoh Shinshu University, Japan
  • Michael A. Wulder Canadian Forest Service (Pacific Forestry Centre), Canada
  • Markus Holopainen University of Helsinki, Finland
  • Juha Hyyppä Finnish Geospatial Research Institute, National Land Survey, Finland

Abstract

The objective of this study is to better understand the relationship between forest structure and point cloud features generated from certain airborne and space borne sensors.  Point cloud features derived from airborne laser scanning (ALS), aerial imagery (AI), WorldView-2 imagery (WV2), TerraSAR-X, and Tandem-X (TDX) data were classified as features characterizing vegetation height and density as well as variation in vegetation height. Correlations between these features and field-measured attributes describing forest structure were investigated at plot scale. Basal area (G) was used as a proxy for forest density whereas maximum tree height (Hmax) and standard deviation in tree height (Hstd) were used to correspond height-related point cloud features. In the analyses, field observations from 364 sample plots (16 m × 16 m) located in southern Finland were used. Even though ALS was found to be the most accurate data source in characterizing forest structure, AI, WV2, and TDX were also capable of characterizing forest height at plot scale with correlation coefficients higher than 0.80. However, ALS was the only data source capable of providing separate features for characterizing also the variation in tree height and forest density. Features related to vegetation height, generated from the other data sources besides ALS, also provided highest correlation with the forest density and variation in height, in addition to Hmax. Due to these more diverse characterization capabilities, forest structural attributes can be predicted more accurately by using ALS, also in the areas where the relation between the attributes of interest is not solely dependent on height, compared to the other investigated 3D remote sensing data sources.

Keywords: airborne laser scanning; lidar; photogrammetry; radargrammetry; interferometry; tree; mapping

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Published

2018-12-31

How to Cite

Vastaranta, M., Yrttimaa, T., Saarinen, N., Yu, X., Karjalainen, M., Nurminen, K., Karila, K., Kankare, V., Luoma, V., Pyörälä, J., Junttila, S., Tanhuanpää, T., Kaartinen, H., Kukko, A., Honkavaara, E., Jaakkola, A., Liang, X., Wang, Y., Vaaja, M., Hyyppä, H., Katoh, M., Wulder, M. A., Holopainen, M., & Hyyppä, J. (2018). Airborne Laser Scanning Outperforms the Alternative 3D Techniques in Capturing Variation in Tree Height and Forest Density in Southern Boreal Forests. Baltic Forestry, 24(2), 268–277. Retrieved from https://balticforestryojs.lammc.lt/ojs/index.php/BF/article/view/226

Issue

Vol. 24 No. 2 (2018): Baltic Forestry

Section

Remote Sensing Technology

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