Affiliation:
1. School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland.
2. Bioeconomy and Environment, Natural Resources Institute Finland, P.O. Box 68, 80100 Joensuu, Finland.
Abstract
Forest management inventories (FMIs) provide critical information, usually at the stand level, for forest management planning. A typical FMI includes (i) the delineation of the inventory area to stands by applying auxiliary information; (ii) the classification of the stands according to categorical attributes such as age, site fertility, main tree species, and stand development; and (iii) measurement, modelling, and prediction of stand attributes of interest. The emergence of wall-to-wall remote-sensing data has enabled a paradigm change in FMIs from highly subjective, visual assessments to objective, model-based inferences. Previously, optical remote-sensing data were used to complement visual assessments, especially in stand delineation and height measurements. The evolution of airborne laser scanning (ALS) has made objective estimation of forest characteristics with known accuracy possible. New optical and Lidar-based sensors and platforms will allow further improvements of accuracy. However, there are still bottlenecks related to species-specific stand attribute information in mixed stands and assessments of tree quality. Here, we concentrate on approaches and methods that have been applied in the Nordic countries in particular.
Publisher
Canadian Science Publishing
Subject
Ecology,Forestry,Global and Planetary Change
Cited by
38 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献