Unmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables
Tuominen, S., Balazs, A., Saari, H., Pölönen, I., Sarkeala, J., & Viitala, R. (2015). Unmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables. Silva fennica, 49(5), Article 1348. https://doi.org/10.14214/sf.1348
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Silva fennicaAuthors
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2015In this paper we examine the feasibility of data from unmanned aerial vehicle (UAV)-borne aerial
imagery in stand-level forest inventory. As airborne sensor platforms, UAVs offer advantages cost
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but they lack range and endurance in larger areas. On the other hand, advances in the processing
of digital stereo photography make it possible to produce three-dimensional (3D) forest canopy
data on the basis of images acquired using simple lightweight digital camera sensors. In this study,
an aerial image orthomosaic and 3D photogrammetric canopy height data were derived from the
images acquired by a UAV-borne camera sensor. Laser-based digital terrain model was applied
for estimating ground elevation. Features extracted from orthoimages and 3D canopy height data
were used to estimate forest variables of sample plots. K-nearest neighbor method was used in the
estimation, and a genetic algorithm was applied for selecting an appropriate set of features for the
estimation task. Among the selected features, 3D canopy features were given the greatest weight
in the estimation supplemented by textural image features. Spectral aerial photograph features
were given very low weight in the selected feature set. The accuracy of the forest estimates based
on a combination of photogrammetric 3D data and orthoimagery from UAV-borne aerial imaging
was at a similar level to those based on airborne laser scanning data and aerial imagery acquired
using purpose-built aerial camera from the same study area.
...


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Suomen Metsätieteellinen SeuraISSN Search the Publication Forum
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