Modifying the site index model of sugi planted forests in Miyazaki Prefecture considering the effects of DEM quality and scale of digital terrain analysis

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. The descriptive measures of model performance of this best model, namely R 2, adjusted R 2, and residual mean squared error, were 0.830, 0.793, and 1.522, respectively. These values indicated that the best model of this study was superior to the previous one developed using only a digital contour map based 12.5-m resolution DEM. keyword : digital elevation model, digital terrain analysis, scale problem, site index, sugi 45 J. For. Plann. 20: 45-51 (2015) relationship of site productivity of sugi with topography; moreover, they will help in developing better site productivity models for other species and regions. Topography is a key factor in representing plant responses to the environment and forest management (Takeshita et al., 1966). Site productivity, a concept used for representing a specific tree species’ growth suitability for a given site (Davis and Johnson, 1987), has been studied with respect to topography. Site index, defined as the height of the dominant trees at a specific reference age (Davis and Johnson, 1987), is the most commonly used measure of site productivity for a target species (e.g., Davis and Johnson, 1987; Hägglund, 1981; Monserud et al., 1990; Takeshita et al., 1960; Wang, 1998). Various DTA-derived indices that represent topographic features, hereinafter referred to as topographic factors, have been used to develop site index prediction models (e.g., Iverson et al., 1997; Mitsuda et al., 2007; Zushi, 2007). Here we define three points to be considered in DTA: data source, grid resolution, and search range (Wilson et al., 2000). The term “search range” will be further explained in the following section. The value of a specific topographic factor for a specific site varies with respect to these three points; therefore, these points can affect site index model performance. DEM data sources are categorized into three data structures: regular grids, triangulated irregular networks, and line vectors representing contours. Such data sources are employed to generate a raster-type DEM that can be used in DTA. Several square-grid DEM data sources with various grid resolutions have been recently published, and some of them are usually available for a site of interest in Japan. However, a square-grid DEM source consists of summarized data that has lost detailed topographic information. Contour-type DEM data sources that do not lose topographic information can be used by digitizing the contour lines of the original topographic map; however, this is time-consuming and laborintensive. Thus, it is desirable to examine the effect of DEM data source on DTA in aspects of primary data structure (Van Niel et al., 2004; Wilson et al., 2000). Scale remains an important but unsolved issue in scientific studies with spatial data, and scale problems defined by grid resolution and search range are important DTA-associated issues (Wilson et al., 2000). Determining a DEM’s optimum grid cell size to represent topographic features with respect to target physical phenomena is a common scale problem (Hutchinson and Gallant, 2000; Sharma et al., 2011). Another scale problem is the determination of the optimum range for calculating topographic factors when the geomorphological pattern influences the target process of a site. Typically, algorithms used to calculate topographic factors with raster-type DEMs require an arbitrary value as a parameter (radius or window size) to define the range for searching a geomorphological feature that influences the physical phenomenon in the subject grid cell. Here we refer to the range (a circle or rectangle) defined by the given parameter as the search range. In our previous study, we developed a site index model for sugi planted forests in Miyazaki Prefecture, Japan using DTA-derived topographic factors (Mitsuda et al., 2007). Because DEM quality and the DTA scale problem were insufficiently considered in this previous study, we sought to modify the previous site index model while accounting for these two issues. The objectives of this study were 1) to evaluate the potential modification of the site index prediction model for sugi 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. Furthermore, we attempted to ascertain the appropriate DTA scale to represent each topographic feature with respect to site productivity. MATERIALS ANDMETHODS The study site was the Tano Forest Science Station, University of Miyazaki. The university forest (spread across 502 ha) is located in a lowland (approximately 110-300 m a.s.l.) of Miyazaki Prefecture, in a warm-temperate region in southeastern Kyushu Island, Japan, where the natural vegetation is evergreen broad leaved forest. The annual mean temperature and precipitation are 16.5°C and 2800 mm, respectively. The site index data set used here is the same as that used in our previous study (Mitsuda et al., 2007). We felled the dominant tree in 18 sample sites where the stand age was greater than the reference age (40 years), and estimated the height of each dominant tree at the reference age as the site index by implementing Richards’ threeparameter equation to the height-age data set derived from stem analysis. After felling, we recorded the position of each felled tree using DGPS (Trimble, Pathfinder ProXR). Thus, we acquired 18 data sets of precisely measured site index and global position of each sample site. We used three DEM sources: 50-m and 10-m resolution square-grid DEMs published by the Japanese Geographic Survey Institute (GSI, now renamed the Geospatial Information Authority of Japan) and 10-m interval vectorized contour (hereafter, GSI50, GSI10, and CNT, respectively). Using 1:25000-scale topographic maps derived from manual stereoscopic interpretation of aerial photographs, GSI50 and GSI10 were obtained by reading the elevation on 50and 10-m grids, and these two DEM data sources were treated as points with 3D coordinates at the center of grid cells. The CNT was obtained by digitizing the contour lines of the 1:25000-scale topographic maps of the study area, which maintained complete detailed topographic information of the 1:25000-scale topographic maps, whereas point-type data source (GSI50 and GSI10) lost it. We interpolated the three data sources to yield rastertype DEMs with resolutions of 10, 12.5, 25, and 50 m by the minimum curve method that fitted a two-dimensional cubic spline surface producing a smoothly varying surface. The four resolutions were set to compare our previous research (Mitsuda et al., 2007) using three of them (12.5, 25, and 50 m resolution), and 10-m resolution square-grid DEM was newly published after the previous research. As various DEMs were used in this study, each DEM was identified by its data source and grid resolution. For example, GSI10-50 denoted a 46 Mitsuda and Ito