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Ilkka Korpela (email), Tuukka Tuomola, Timo Tokola, Bo Dahlin

Appraisal of seedling stand vegetation with airborne imagery and discrete-return LiDAR – an exploratory analysis

Korpela I., Tuomola T., Tokola T., Dahlin B. (2008). Appraisal of seedling stand vegetation with airborne imagery and discrete-return LiDAR – an exploratory analysis. Silva Fennica vol. 42 no. 5 article id 466. https://doi.org/10.14214/sf.466

Abstract

The potential for combined use of airborne discrete-return LiDAR and digital imagery in the classification and measurement of common seedling stand vegetation was examined in southern Finland (61°50’N, 24°20’E). Classification was based on spectral and textural image features in addition to geometric and radiometric features of the LiDAR. The accuracy of leaf-on, LiDAR-based terrain elevation models was tested as well as the accuracy of LiDAR in the measurement of vegetation heights. LiDAR-based canopy height and the range-normalized intensity of the LiDAR were strong explanatory variables in vegetation classification. Interspecies variation was observed in the height measurement accuracy of LiDAR for different tree, shrub and low vegetation canopies. Elevation models derived with 1–15 pulses per m2 showed an inherent noise of app. 15–25 cm, which restricts the use of LiDAR in regeneration assessment of very young stands. The spatial pattern of the competing vegetation was reproduced in classification-based raster surfaces, which could be useful in deriving meaningful treatment proposals.

Keywords
silviculture; remote sensing; forest regeneration; classification; species

Author Info
  • Korpela, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland E-mail ilkka.korpela@helsinki.fi (email)
  • Tuomola, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland E-mail tt@nn.fi
  • Tokola, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland E-mail tt@nn.fi
  • Dahlin, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland E-mail bd@nn.fi

Received 24 June 2008 Accepted 17 November 2008 Published 31 December 2008

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Available at https://doi.org/10.14214/sf.466 | Download PDF

Creative Commons License CC BY-SA 4.0

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Korpela I., Ørka H. O. et al. (2010) Tree species classification using airborne LiDAR.. Silva Fennica vol. 44 no. 2 article id 156