期刊
FORESTS
卷 7, 期 11, 页码 -出版社
MDPI
DOI: 10.3390/f7110255
关键词
growth and yield; airborne laser scanning; remote sensing; enhanced forest inventory; template matching
类别
资金
- Canadian Wood Fibre Centre (CWFC) of the Canadian Forest Service, Natural Resources Canada
- Natural Sciences and Engineering Research Council of Canada (NSERC)
Accurate information on both the current stock and future growth and yield of forest resources is critical for sustainable forest management. We demonstrate a novel approach to utilizing airborne laser scanning (ALS)-derived forest stand attributes to determine future growth and yield of six attributes at a sub-stand (25 m grid cell) level of detail: dominant height (HMAX), Lorey's height (HL), quadratic mean diameter (QMD), basal area (BA), whole stem volume (V), and trees per hectare (TPH). The approach is designed to find the most appropriate matching yield curve and project the attributes to the age of 80 years. Comparisons to conventional plot-level projections resulted in relative mean differences of 13.4% (HMAX), -27.1% (HL), 18.8% (QMD), 12.0% (BA), 18.6% (V), and -17.5% (TPH). The respective relative root mean squared difference values were: 31.1%, 38.4%, 19.8%, 19.8%, 21.8%, and 38.4%. Differences were driven mostly by stand-level age and site index. The uncertainty of cell-level yield curve assignment was used to refine stand-level summaries. The novel contribution of this study is in the application of growth and yield models at the cell level, combined with the use of ALS-derived attributes to optimize yield curve selection via template matching.
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