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Conference poster2014

A comparison of forest inventories based on aerial image matching and Airborne Laser Scanning data

Bohlin, Jonas; Wallerman, Jörgen; Fransson, Johan


Forest inventories are now commonly done by Airborne Laser Scanning (ALS), especially because many countries are collecting ALS data nation-wide to produce high quality elevation data. With an accurate digital elevation model, 3D data from aerial image matching could be a more cost-effective alternative to repeated ALS acquisitions for providing updated data to forest management planning in the future. This study aims at comparing the quality of forest inventory data obtained by aerial image matching and ALS. In the study area, a mixed boreal forest situated in central Sweden, aerial images from the national acquisition program with a ground sampling distance of 0.5 m and ALS data with a point density of 1.5-2 pulses per m2 from the national ALS production were available. The aerial images were matched with three different algorithms to assess possible differences in forest information content. Two hundred field plots, located within the study area, were utilized for non-parametric prediction of forest variables using random forest. Accuracy assessment was made by leave-one-out cross-validation at plot level. The results show similar accuracy of ALS and image matching-based predictions, with ALS slightly superior. Accuracy, in terms of root mean square errors in percent of surveyed plot mean, of ALS were: 6.4% for tree height; 12.5% for tree diameter; 18.2% for basal area and 20.0% for stem volume, and of image matching: 9.5% for tree height; 15.3% for tree diameter; 21.8% for basal area and 24.8% for stem volume. Among the image matching algorithms used, SURE was found to estimate the forest variables with best accuracies. However, the other algorithms produced similar results. These results indicate that inventory data acquired by matching of aerial images have a large potential for operational use in forest management planning as a cost-effective alternative to new ALS campaigns.

Published in


ForestSAT 2014, A Bridge Between Forest Sciences, Remote Sensing and Geo-Spatial Applications