The System for Assessment of the Japanese Cedar Forest Resources Using Space Image Data

The volume of Japanese cedar (Cryptomeria japonica (Thunb. Ex L. f.) D. Don), «sugi» in Japanese) plantations was estimated by using the Japanese satellite ALOS (AVNIR-2, PRISM) to identify sugi plantations as a forest resource. We performed highly precise geometric corrections by locating ground control points (GCP) on the RPC (Rational Polynomial Coefficients) geometric correction image. DPR (Dual Partitioning Regression) was used for the topographic correction. The forest was extracted by primary classification and sugi stands by secondary classification. The overall accuracy of the primary classification was 94 % and that of the secondary classification was 89 %. Parameters effective for estimating volume per hectare were selected by multiple regression analysis between volume and average digital number of each band (band value) by a stepwise procedure. Regression equation using the reciprocal of band 4 (Near IR) value was significantly effective. We demonstrated that the area with a negative NDVI value is not a sugi forest. By identifying these areas using periodical satellite monitoring, the accuracy of the forest register can be increased and this helps facilitate the practical use of the sugi forest