Propagating the errors of initial forest variables through stand- and tree-level growth simulators |
| |
| Authors: | Antti Mäkinen Markus Holopainen Annika Kangas Jussi Rasinmäki |
| |
| Institution: | (1) Department of Forest Resource Management, University of Helsinki, Latokartanonkaari 7, 00014 Helsinki, Finland |
| |
| Abstract: | Developments in the field of remote sensing have led to various cost-efficient forest inventory methods at different levels
of detail. Remote-sensing techniques such as airborne laser scanning (ALS) and digital photogrammetry are becoming feasible
alternatives for providing data for forest planning. Forest-planning systems are used to determine the future harvests and
silvicultural operations. Input data errors affect the forest growth projections and these effects are dependent on the magnitude
of the error. Our objective in this study was to determine how the errors typical to different inventory methods affect forest
growth projections at individual stand level during a planning period of 30 years. Another objective was to examine how the
errors in input data behave when different types of growth simulators are used. The inventory methods we compared in this
study were stand-wise field inventory and single-tree ALS. To study the differences between growth models, we compared two
forest simulators consisting of either distance-independent tree-level models or stand-level models. The data in this study
covered a 2,000-ha forest area in southern Finland, including 240 sample plots with individually measured trees. The analysis
was conducted with Monte Carlo simulations. The results show that the tree-level simulator is less sensitive to errors in
the input data and that by using single-tree ALS data, more precise growth projections can be obtained than using stand-wise
field inventory data. |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
