Journal
CANADIAN JOURNAL OF FOREST RESEARCH
Volume 47, Issue 1, Pages 113-124Publisher
CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/cjfr-2016-0209
Keywords
site index; mean annual increment; timber productivity; remote sensing; Sierra Nevada
Categories
Funding
- U.S. Department of Agriculture
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High-resolution site index (SI) and mean annual increment (MAI) maps are desired for local forest management. We integrated field inventory, Landsat, and ecological variables to produce 30 m SI and MAI maps for the Tahoe National Forest (TNF) where different tree species coexist. We converted species-specific SI using adjustment factors. Then, the SI map was produced by (i) intensifying plots to expand the training sets to more climatic, topographic, soil, and forest reflective classes, (ii) using results from a stepwise regression to enable a weighted imputation that minimized the effects of outlier plots within classes, and (iii) local interpolation and strata median filling to assign values to pixels without direct imputations. The SI (reference age is 50 years) map had an R-2 of 0.7637, a root-mean-square error (RMSE) of 3.60, and a mean absolute error (MAE) of 3.07 m. The MAI map was similarly produced with an R-2 of 0.6882, an RMSE of 1.73, and a MAE of 1.20 m(3).ha(-1).year(-1). Spatial patterns and trends of SI and MAI were analyzed to be related to elevation, aspect, slope, soil productivity, and forest type. The 30 m SI and MAI maps can be used to support decisions on fire, plantation, biodiversity, and carbon.
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