Predicting the Plot Volume by Tree Species Using Airborne Laser Scanning and Aerial Photographs
Abstract:Several studies have indicated that forest characteristics can be accurately predicted using airborne laser scanner (ALS) data, but there are very few studies in which species-specific forest characteristics have been estimated. This article compares two approaches for determining species-specific volumes at plot level by combining ALS data with aerial photographs. The first approach consists of two stages: (1) prediction of total volume using ALS data, and (2) assignment of this total volume to tree species by fuzzy classification and aerial photographs, in which three fuzzy classification methods were tested. In the second approach, volumes by tree species and the total volume are predicted simultaneously using a nonparametric k-most similar neighbor (k-MSN) method based on both ALS data and aerial photographs in one phase. The test area, located in Finland, consists of 463 sample plots. Species-specific volumes were estimated for pine, spruce, and the deciduous trees as a species group, total volume being the sum of the species-specific volumes. The k-MSN method produced considerably more accurate estimates for the species-specific volumes than any fuzzy classification method, the relative RMSEs for the volumes of pine, spruce, and deciduous trees being 45.50%, 61.98%, and 92.30%, respectively, and that for the total volume 23.86%.
Document Type: Research Article
Publication date: 2006-12-01
More about this publication?
- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2016 Impact Factor: 1.782 (Rank 17/64 in forestry)
Average time from submission to first decision: 62.5 days*
June 1, 2016 to Feb. 28, 2017
Also published by SAF:
Journal of Forestry
Other SAF Publications
- Submit a Paper
- Membership Information
- Author Guidelines
- Ingenta Connect is not responsible for the content or availability of external websites