In this study, suitable sites for clearcutting and reforestation were found by combining GIS thematic maps expressed by standard scores in the case of the University of Tokyo Chiba Forest. The map themes were stand age over rotation age, site quality, accessibility and slope stability, and they were combined after conversion of original units into a common scale of standard scores. Then, planted stands suitable for clearcutting and reforestation were selected considering yarding feasibility. As a result, 18 sub-compartments were selected as candidate stands that had combined scores over 50 in the combined thematic map with stand sizes over 3 ha. Finally, 6 sub-compartments passed the yarding feasibility check to see if there was any obstacle along the sky line of cable logging between the two peaks in the visible area from the neighboring yard. A standard score was useful to set several thematic maps into a common scale when they were combined and to select subcompartments almost better than an average in all aspects of thematic maps. The suggested method was flexible and could contribute to a wider use of GIS in the field of forest planning.

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The objectives of this study were 1) to modify the site index prediction model for sugi (Cryptomeria japonica) planted forests in Miyazaki Prefecture developed in a previous study and 2) to investigate the effects of quality of DEM and the scale of digital terrain analysis on the performances of site index models. The study site was the Tano Forest Science Station, University of Miyazaki. We acquired 18 data sets of site index estimated using stem analysis and global position of each sample site where a sample tree was felled. Three topographic factors,a solar radiation index, a hydrological upslope contributing area index, and a vertical topographic exposure index, were derived from DEMs generated from three data sources (10-m and 50-m interval point data with 3D coordinates and digitized contour map) and at resolutions of 10, 12.5, 25, and 50 m. Several search ranges (100, 250, 500, and 1000 m) were tested. Correlation analysis between site index and topographic factors as well as regression analysis to develop a site index prediction model using topographic factors as explanatory variables revealed that the hydrological upslope contributing area index requires DEMs generated from more informative DEM data sources (10-m interval point data and digitized contour map) and at fine resolution (10 m or 12.5 m); however, these DEMs were unsuitable for solar radiation index. DEMs generated from a less informative DEM data source (50 m interval 3D point data) and at a coarse resolution of 50 m were suitable for the solar radiation index. The effects of search ranges on topographic factors were clear for vertical topographic exposure index but not for the others. The best model developed in this study accepted the solar radiation index derived from the digital contour map based 10-m resolution DEM, the hydrological upslope contributing area index derived from the digital contour map based 12.5-m resolution DEM, and the vertical topographic exposure index derived from the 50-m interval 3D point data based 50-m resolution DEM as the explanatory variables.

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