Linking within stand variability to timber growth characteristics for site-specific forest management

The adoption of precision agriculture technologies and site-specific management has been limited in the forest industry. Geographic information systems (GIS) and remote sensed imagery have been used in forest management, but at a landscape scale, typically to prescribe and schedule treatments for a diverse collection of relatively large tracts. Individual stands have traditionally been treated uniformly based on their most prevalent characteristics. Sub-stand variability has most often been studied as something for which an efficient inventory sampling strategy can compensate, not as being suggestive of a treatment regime to maximize revenue or ecological benefits. This paper develops a method to generate a site-specific database using ground-based and LiDAR data to estimate individual tree volume to create a timber yield map. Tree diameter at breast height (DBH) was hand measured for each tree across a 3.6 ha site and then LiDAR data was used to estimate individual tree height. Tree location and elevation across the site were determined using a total station. Random tree height measurements were collected and correlated to the LiDAR data (R ²=0.57) while the DBH and height for each tree were then used to compute individual tree volume. Finally, management zones were developed based upon the timber yield map to illustrate how database could be used for site-specific management.