Obtaining plotwise mean height and volume growth in boreal forests using multi-temporal laser surveys and various change detection techniques

This study used high-density multitemporal laser scanner datasets acquired at different dates between 1998 and 2003 to estimate the tree mean height and volume growth at plot level in a boreal forest. Thirty-three sample plots were established in a mixed, multiple-storey forest in Kalkkinen, 130 km north of Helsinki, Finland. Plotwise attributes, such as mean height, basal area and volume, were estimated from field measurements. Laser datasets were collected with a TopoSys laser scanner in 1998, 2000 and 2003 with a nominal point density on the target of 10points/m(2). Three techniques were used to derive predictors for growth estimation: a method based on individual tree top differencing, digital surface model (DSM) differencing and canopy height distribution differencing. The regression models were developed for mean height growth and volume growth using the single best predictor derived from each method and selected predictors from all methods. Best-subset technique was used for predictor selection. The best results were obtained for mean height growth (adjusted R-2 value of 0.86 and standard deviation of residuals of 0.15m) using the individual tree top differencing method. The corresponding values for volume growth were 0.58 and 8.39 m(3) ha(-1) (35.7%) respectively, using DSM differencing. Combined use of the three techniques yielded a better result for volume growth (adjusted R-2=0.75) but did not improve the estimation for mean height growth. The results indicated that it is possible to determine forest mean height and volume growth with an acceptable accuracy using multitemporal laser scanning. This information could be used in growth model development and in determination of forest growth using strip-based sampling as part of large-area forest inventories, such as the national forest inventory.