Ilkka Korpela, Tuukka Tuomola, Timo Tokola, Bo Dahlin. (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

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

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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.

Korpela, University of Helsinki, Dept of Forest Management, P.O. Box 27, FI-00014 University of Finland E-mail: ilkka.korpela@helsinki.fi
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

article id 283, category Research article

Ilkka Korpela, Tuukka Tuomola, Esko Välimäki. (2007). Mapping forest plots: an efficient method combining photogrammetry and field triangulation. Silva Fennica vol. 41 no. 3 article id 283. https://doi.org/10.14214/sf.283

Keywords: remote sensing; least squares adjustment; intertree positioning; spatial resection; trilateration

Abstract | View details | Full text in PDF | Author Info

Intra stand spatial information is often collected in ecological investigations, when functioning or interactions in the ecosystem are studied. Local relative accuracy is often given priority in such cases. Forest maps with accurate absolute positions in a global coordinate system are needed in remote-sensing applications for validation and calibration purposes. Establishing the absolute position is particularly difficult under a canopy as is creating undistorted coordinate systems for large plots in the forest. We present a method that can be used for the absolute mapping of point features under a canopy that is efficient for large forest plots. In this method, an undistorted network of control points is established in the forest using photogrammetric observations of treetops. These points are used for the positioning of other points, using redundant observations of interpoint distances and azimuths and a least squares adjustment. The method provides decimetre-level accuracy and only one person is required to conduct the work. An estimate of the positioning accuracy of each point is readily available in the field. We present the method, a simulation study that explores the potential of the method and results from an experiment in a mixed boreal stand in southern Finland.

Korpela, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ilkka.korpela@helsinki.fi
Tuomola, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: tt@nn.fi
Välimäki, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ev@nn.fi

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