Mapping site index and age by linking a time series of canopy height models with growth curves

Site index (SI) is one of the main measures of forest productivity in North America. For monospecific even-age stands, it is defined as the height of dominant trees at a given reference age or presented as an age–height curve. SI normally reflects the overall effect of all the environmental parameters that determine height growth locally. However, measuring SI can only be achieved though field observations and is, for this reason, limited to sample plots. In this study, we propose a new method for quantifying and mapping SI and age based on known age–height curves and time series of canopy height models (CHMs) produced using digital photogrammetry and lidar. Digital surface models (DSMs) are created by applying an automated stereo-matching algorithm to scanned aerial photographs. The canopy height is obtained by subtracting the lidar ground elevations from the DSM. Using aerial photographs covering the 1945–2003 interval and a recent lidar coverage, CHMs could be reconstructed retrospectively for a period of over 58 years. Regionally calibrated age–height curves were fitted to observations that were extracted cell-wise from the historical CHMs to estimate SI and age values for all undisturbed locations. Results demonstrate that SI and age of jack pine (Pinus banksiana [Lamb.]) stands can be quantified respectively with an average bias of 0.76 m (2.41 m root mean squared error, RMSE) and 1.86 years (7 years RMSE). The method can be used to produce quasi-continuous maps of SI and age and to estimate productivity in a spatially explicit way.