Journal
INTERNATIONAL JOURNAL OF REMOTE SENSING
Volume 31, Issue 5, Pages 1175-1192Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/01431160903380649
Keywords
-
Funding
- research council FORMAS
- company Prevista A/S
Ask authors/readers for more resources
Individual tree crown segmentation from airborne laser scanning (ALS) data often fails to detect all trees depending on the forest structure. This paper presents a new method to produce tree lists consistent with unbiased estimates at area level. First, a tree list with height and diameter at breast height (DBH) was estimated from individual tree crown segmentation. Second, estimates at plot level were used to create a target distribution by using a k-nearest neighbour (k-NN) approach. The number of trees per field plot was rescaled with the estimated stem volume for the field plot. Finally, the initial tree list was calibrated using the estimated target distribution. The calibration improved the estimates of the distributions of tree height (error index (EI) from 109 to 96) and DBH (EI from 99 to 93) in the tree list. Thus, the new method could be used to estimate tree lists that are consistent with unbiased estimates from regression models at field plot level.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available