Ground Sample Inventories
The Forest Analysis and Inventory Branch (FAIB) is responsible for coordinating and managing data collection from 3 main ground sampling programs. These programs complement each other by providing unique data needed for making sustainable forest management decisions.
More information about each program is provided in the pages below with associated sections that include links to Data Collection Standards and Reports.
Permanent Sample Plots (PSPs) are purposefully located across a gradient of different forest types and are used to support development and testing of growth-and-yield models in unmanaged stands. They also provide a long-term biological baseline for how forest stands grow and develop. The main strength of this program is that it has been operational for over 90 years with some plots having 12 re-measurements. The subjective location of plots along a gradient of forest types is needed for model development, but limits the utility in monitoring average forest condition.
Provincial Monitoring Programs include the Provincial Change Monitoring Inventory (CMI), Provincial Young Stand Monitoring (YSM) and National Forest Inventory (NFI) programs. These programs are provincial in scope and their plots are located on a standard 20 km grid or an intensification of this grid. These plots are measured at regular time intervals and use well known sampling methods. The main strengths of this program are the ease of re-measurement and statistically sound design using fixed-radius plots located at each grid intersection. It is important that these Provincial programs are distinguished from location-specific CMI and YSM plots that have been established by forest companies in the past.
To verify key spatial inventory attributes estimated during photo interpretation, temporary samples are randomly established within mapped polygons in mature stands. Comparisons of this ground data to the photo estimation attributes helps determine confidence in the inventory for TSR. The main strength of this program is the efficiency in capturing variability within a polygon with the 5-point cluster plot design and the probability proportional to size with replacement (PPSWR) plot location. Its weaknesses are that the plots are not designed to be re-measured (which is often required) and therefore have limited flexibility in the use of the data.