Abstract
Remote sensing using unmanned aerial vehicle (UAV) -borne
sensors is currently a highly interesting approach for
the estimation of forest characteristics. 3D remote
sensing data from airborne laser scanning or digital
stereo photogrammetry enable highly accurate estimation
of forest variables related to the volume of growing
stock and dimension of the trees, whereas recognition of
tree species dominance and proportion of different tree
species has been a major complication in remote
sensing-based estimation of stand variables. In this
study the use of UAV-borne hyperspectral imagery was
examined in combination with a high-resolution
photogrammetric canopy height model in estimating forest
variables of 298 sample plots. Data were captured from
eleven separate test sites under weather conditions
varying from sunny to cloudy and partially cloudy. Both
calibrated hyperspectral reflectance images and
uncalibrated imagery were tested in combination with a
canopy height model based on RGB camera imagery using the
k-nearest neighbour estimation method. The results
indicate that this data combination allows accurate
estimation of stand volume, mean height and diameter: the
best relative RMSE values for those variables were 22.7%,
7.4% and 14.7%, respectively. In estimating volume and
dimension-related variables, the use of a calibrated
image mosaic did not bring significant improvement in the
results. In estimating the volumes of individual tree
species, the use of calibrated hyperspectral imagery
generally brought marked improvement in the estimation
accuracy; the best relative RMSE values for the volumes
for pine, spruce, larch and broadleaved trees were 34.5%,
57.2%, 45.7% and 42.0%, respectively.
Original language | English |
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Article number | 7721 |
Journal | Silva Fennica |
Volume | 51 |
Issue number | 5 |
DOIs | |
Publication status | Published - 1 Jan 2017 |
MoE publication type | A1 Journal article-refereed |
Keywords
- aerial imagery
- digital photogrammetry
- forest inventory
- hyperspectral imaging
- radiometric calibration
- stereo-photogrammetric canopy modelling
- UAVs
- OtaNano