Forest Site Evaluation Based on GIS and Kriging

Abstract

Forest site evaluation is required by forestry production and is also the basis on which forest cultivation, management and planning, and forest yield prediction can be made. Thus, it is very important to develop new methods for quickly and accurately evaluate forest sites and estimate forest site indices with small samples of field data. Based on the existing forest inventory data, this paper demonstrated a forest site evaluation method by integrating geographic information system (GIS) and a spatial interpolation method-kriging in geostatistics. This method was based on spatial autocorrelation of forest height. As an example, this method was applied to evaluation of Chinese fir sites in Fengshushan tree farm, Jiangxi Province of China. The obtained results show that the spatial autocorrelation of Chinese fir site index can be quantified using spherical model and the ratio of nugget variance to sill variance is 66.15%, which indicates a moderate degree of spatial autocorrelation. Moreover, based on the sample data, Kriging can accurately reproduce the spatial distribution and variability of Chinese fir site index and result in site index map. By cross-validation, the obtained average error between the observed and predicted values and mean standard error of predictions for Chinese fir site index are close to zero. The root mean square error (RMSE) and average standard error are also relatively small and the standardized RMSE is close to one unit. In addition, this method provides a useful tool for forest management, predicting Chinese fir site index, and identifying the appropriate area for Chinese fir reforestation.