Influence of the correction method of CHM-based Individual Tree Detection results on the estimation of forest stand characteristics

Information on stand characteristics is of great importance for forest inventory, management and conservation. For more than two decades, Airborne Laser Scanning (ALS) data have enabled remotely sensed estimation of forest stand attributes. Two main approaches are used to estimate biometric forest attributes using Airborne Laser Scanning (ALS): the area-based approach (ABA) and individual tree detection (ITD). So far, the ABA method has been much more com- monly used in forestry, as it requires only point cloud metrics. However, with the requirement for precise height information and the development of ITD methods, it is increasingly used to estimate tree biometric characteristics and stand attributes. With this in mind, this study assessed the impact of an ITD correction method based on the Canopy Height Model (CHM) on the estimation of forest characteristics such as tree density and average tree height. The three- -step correction method first classifies erroneous segments from ITD methods, which are then refined. In this study, two ITD methods were tested and their results subsequently corrected on a diverse forest area within Bialowieza Forest in Poland. In general, more accurate estimates of stand attributes were obtained using the Local ITD method developed in this study area, while correction procedure produced greater improvement using the basic ITD method, which is a marker-controlled watershed with a kernel size of five pixels (MCWS 5x5). Both ITD meth- ods were reliable for estimating tree density for deciduous trees. The correction worked most reliably for estimating tree density with both methods for the area consisted of deciduous trees, while it was most reliable for estimating average tree height with the Local method for the deciduous trees and with the MCWS 5x5 for the conifers. The results indicate that correction improved ITD estimates of stand characteristics, but this varied with species groups, tree height and amount of height variation. Therefore, further development of ITD methods is advisable, as estimating stand attributes using ALS at the individual tree level offers possibilities for improved forest management.