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Stand validation of lidar forest inventory modeling for a managed southern pine forest

Journal Article · · Canadian Journal of Forest Research
 [1];  [2]
  1. USDA Forest Service Pacific Northwest Research Station, 3625 93rd Avenue SW, Olympia, WA 98512, USA; OSTI
  2. USDA Forest Service Pacific Northwest Research Station, University of Washington, P.O. Box 352100, Seattle, WA 98195-2100, USA
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We evaluated area-based approaches (ABAs) to light detection and ranging (lidar) predictions of plot- and stand-level forest attributes (tree count, height, basal area, volume, aboveground biomass, broadleaf/conifer, and diameter at breast height — “diameter”). ABA methods included post-stratification (PS), ordinary least squares (OLSs) regression, k nearest neighbors ( kNN), and random forest (RF). This study was conducted on the Savannah River Site in South Carolina, USA. Plot- and stand-level predictions were validated against fixed-radius 0.04 ha (0.1 acre) plots in 49 ≈2.0 ha (5 acre) stands. Our findings demonstrate that lidar can be incorporated operationally into forest inventory systems to provide stand-level inferences for a wide range of forest attributes. Volume predictions for specific diameter classes, however, often fared poorly (root mean squared error (RMSE) > 100%) for the methods we explored, especially for larger (less common) diameter trees. Stand-level results were consistently better than pixel-level results (10–200+ percentage points). kNN and RF performed similarly and better than OLS and PS, but RF was the most robust to model configurations, while kNN has practical advantages such as simultaneous predictions of many attributes.

Research Organization:
USDA Forest Service, Savannah River, New Ellenton, SC (United States)
Sponsoring Organization:
USDOE Office of Environmental Management (EM)
DOE Contract Number:
EM0003622
OSTI ID:
2417648
Journal Information:
Canadian Journal of Forest Research, Journal Name: Canadian Journal of Forest Research Journal Issue: 2 Vol. 53; ISSN 0045-5067
Publisher:
Canadian Science Publishing
Country of Publication:
United States
Language:
English

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