Estimating Site Index for Conifer and Mixed Conifer and Hardwood Stands Using LiDAR

Lathrop P. Leonard, California State Parks, 1111 2nd

St., Crescent City, CA 95531; (707)465-

7383; lleonard@parks.ca.gov

Daryl Van Dyke, US Fish and Wildlife Service; Quentin Stewart, Ryan Graves, and Andrew

Goldman, California State Parks

We used multi-return light detecting and ranging (LiDAR) to develop a cost-effective method for

describing forest conditions and prioritizing restoration treatments in over 20,000 hectares of

second-growth forests (7-80 years old) in Del Norte Coast Redwoods State Park (DNCRSP) and

Humboldt Redwoods State Park (HRSP). DNCRSP consists primarily of redwood and Douglas-

fir dominated forests with scattered tanoak dominated stands. Species composition in DNCRSP

has generally shifted towards Douglas-fir due to previous logging practices. The second-growth

stands of HRSP are generally dominated by both Douglas-fir and tanoak with varying amounts

of redwood. Much of HRSP was unmanaged immediately after logging which has resulted in

tanoaks dominating many sites where conifers were once abundant.

In 2009, we implemented a stratified sampling design to establish plots throughout the range of

age classes and vegetation types within the property. A key step to building a model to predict

forest metrics with LiDAR was to ensure that each fixed-radius ground plot was accurately

represented by an extracted plot LiDAR point cloud cylinder. To accomplish this, we attempted

to obtain sub-meter accuracy for all ground plot centers. We also established plots in locations

that appeared to be relatively uniform so that any LiDAR point cloud cylinder extracted within

two meters of the actual plot center would be similar.

Using Douglas-fir tree heights and stand age, we determined site index for each plot. We

compared site index to descriptive statistics developed for the corresponding LiDAR point cloud

cylinders to create regression relationships for predicting site index. The ability to develop

regression equations for single species stands as compared to mixed species stands is explored.

Site index can be a used to determine the productivity of a stand. The most productive lands

within the flight tended to be dominated by redwoods, moderate sites by Douglas-fir and the

poorest sites with tanoak. By comparing site index to current species composition, we may be

able to identify areas deficient in species present under pre-logging conditions. Knowledge of

shifts in species composition can be a tool to identify restoration needs and prioritize treatments.