Research article - Peer-reviewed, 2013
Change detection of mountain birch using multi-temporal ALS point clouds
Nyström, Mattias; Holmgren, Johan; Olsson, HåkanAbstract
The use of multi-temporal laser scanner data is potentially an efficient method for monitoring of vegetation changes, for example, at the alpine treeline. Methods for relative calibration of multi-temporal airborne laser scanning (ALS) data sets and detection of experimental changes of tree cover in the forest–tundra ecotone was tested in northern Sweden (68° 20′ N, 19° 01′ E). Trees were either partly or totally removed on 6 m radius sample plots to simulate two classes of biomass change. Histogram matching was successfully used to calibrate the laser metrics from the two data sets and sample plots were then classified into three change classes. The proportion of vegetation returns from the canopy was the most important explanatory variable, which provided an overall accuracy of 88%. The classification accuracy was clearly dependent on the density of the forest.Keywords
airborne laser scanning; lidar; vegetation; histogram matching; change detection; multi-temporal; forestPublished in
Remote Sensing Letters2013, volume: 4, number: 2, pages: 190-199
Publisher: Taylor & Francis
Authors' information
Swedish University of Agricultural Sciences, Department of Forest Resource Management
Swedish University of Agricultural Sciences, Department of Forest Resource Management
Swedish University of Agricultural Sciences, Department of Forest Resource Management
UKÄ Subject classification
Forest Science
Publication Identifiers
DOI: https://doi.org/10.1080/2150704X.2012.714087
URI (permanent link to this page)
https://res.slu.se/id/publ/78553