Use of multi-spectral imagery and LiDar data to quantify compositional and structural characteristics of vegetation in red-cockaded woodpecker (Picoides borealis) habitat in North Carolina

Author

Joelle Marie Carney

Issuing Body

Mississippi State University

Advisor

Evans, David

Committee Member

Roberts, Scott

Committee Member

Grado, Stephen

Date of Degree

8-8-2009

Document Type

Graduate Thesis - Open Access

Major

Forestry

Degree Name

Master of Science

College

College of Forest Resources

Department

Department of Forestry

Abstract

This study evaluated habitat parameters for the red-cockaded woodpecker (RCW; Picoides borealis) on three tracts in Hoke County, North Carolina. Multi-spectral imagery was used to classify shadow, non-vegetation, herbaceous, hardwoods, and loblolly and longleaf pine trees. Field data were collected for image classification training and validation. Overall classification accuracy for separating hardwood from pine trees, was 80.8%. When separating longleaf (Pinus palustris Mill.) and loblolly (Pinus taeda L.) pine from hardwoods the accuracy was 73.7%. Field-based height/diameter relationships were applied to LiDAR-identified trees to predict diameter classes. Due to differences in management regimes and site conditions, each tract had different majority pine diameter classes. Average height, diameter, basal area, and stem density per plot were reported from matched, unmatched, and total LiDAR trees to field trees. Differences between the height, diameter, basal area, and stem density values occurred between the matched and unmatched LiDAR- and field-identified trees.

URI

https://hdl.handle.net/11668/15314

Recommended Citation

Carney, Joelle Marie, "Use of multi-spectral imagery and LiDar data to quantify compositional and structural characteristics of vegetation in red-cockaded woodpecker (Picoides borealis) habitat in North Carolina" (2009). Theses and Dissertations. 4871.
https://scholarsjunction.msstate.edu/td/4871