Developing raster bands computed from LiDAR to improve forest
Fetyukova, Yuliya (2013)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe201303062255
https://urn.fi/URN:NBN:fi-fe201303062255
Tiivistelmä
This study examines the use of di erent features derived from remotely sensed
data in segmentation of forest stands. Surface interpolation methods were
applied to LiDAR points in order to represent data in the form of grayscale
images. Median and mean shift ltering was applied to the data for noise reduction.
The ability of di erent compositions of rasters obtained from LiDAR
data and an aerial image to maximize stand homogeneity in the segmentation
was evaluated. The quality of forest stand delineations was assessed by the
Akaike information criterion.
The research was performed in co-operation with Arbonaut Ltd., Joensuu,
Finland.
data in segmentation of forest stands. Surface interpolation methods were
applied to LiDAR points in order to represent data in the form of grayscale
images. Median and mean shift ltering was applied to the data for noise reduction.
The ability of di erent compositions of rasters obtained from LiDAR
data and an aerial image to maximize stand homogeneity in the segmentation
was evaluated. The quality of forest stand delineations was assessed by the
Akaike information criterion.
The research was performed in co-operation with Arbonaut Ltd., Joensuu,
Finland.