Automatic GNSS-enabled harvester data to evaluate productivity

Automatic GNSS-enabled harvester data to evaluate productivity

Most modern cut-to-length (CTL) machines used in forest harvesting have on-board computers that capture individual tree data and can also be coupled with global navigation satellite systems (GNSS). 

Researchers from the University of Canterbury and the University of the Sunshine Coast have used this data to study a forest harvesting operation in a Eucalyptus spp. Plantation based in Uruguay. 

The team fitted a mixed effects model to the data to evaluate harvester productivity as a function of stem diameter at breast height (DBH), species, shift (day/night), slope, and operator. A slope surface derived from a digital terrain model was overlaid with GNSS stem records and slope values were assigned to each stem using the Spatial Analyst toolbox in ArcGIS.

Results showed that DBH was the most influential variable in harvester productivity. Operator and species also had significant effects. 

The model developed constitutes the first published harvester productivity model in South America based on data automatically collected by harvesters.

Click here for source (Taylor & Francis Online)

Image Credit: Heikki Valve, Wikipedia