Forest practices for mountainous areas can enhance the scenery value and function of forests. However, forest scenery management is rarely implemented except for conservation areas and public forests. In this study, we first used the viewshed analysis to extract visible and invisible zones from the surface areas of ordinary mountains in Korea, and then we used spatial aesthetic analysis to interpret the human-recognized characteristics on the visible zones of mountain scenery. Finally, based on the results of both analyses, reasonable guidelines for forest practice planning were proposed to improve the scenery of ordinary mountains. The result shows that the viewshed analysis made it possible to extract visible and invisible areas from the surface areas of ordinary mountains, and to determine the scale of zoning for forest practices to improve mountain scenery. In addition, using spatial aesthetic analysis, it was possible to explain the characteristics of mountain scenery according to distance and elevational differences between viewpoint and target, and to suggest a treatment target and direction for forest practices to improve the mountain scenery. This study is meaningful in that the viewshed and spatial aesthetic analyses were applied to evaluate the current scenery of ordinary mountains and to present guidelines for forest practice planning to promote their own scenery values.

Accurate spatial information on forest roads is important for forest management and harvest operations. This study evaluated the positional accuracy, shape similarity, and cost of three mapping techniques: GNSS (Global Navigation Satellite System) mapping, CAD file conversion (as-built drawing), and image warping. We chose five road routes within the national forest road system in the Republic of Korea and made digital road maps using each technique. We then compared map accuracy to reference maps made from field surveys. The mapping and field-survey results were compared using point-correspondence, buffering analysis, shape index, and turning function methods. The comparisons indicate that GNSS mapping is the best technique because it generated the highest accuracy (Root Mean Square Error: GNSS mapping 1.28, image warping 7.13, CAD file conversion 13.35), the narrowest buffering width for 95% of the routes overlapped (buffering width: GNSS mapping 1.5 m, image warping 18 m, CAD file conversion 24 m), highest shape similarity (shape index: GNSS mapping 19.6–28.9, image warping 7.2–10.8, CAD file conversion 6.5–7.4), and smallest area size difference in turning function analysis (GNSS mapping 2814–4949, image warping 7972–26,256, CAD file conversion 8661–27,845). However, GNSS requires more time (236 min/km) and costs more ($139.64/km) to produce a digital road map as compared to CAD file conversion (99 min/km and $40.90/km) and image warping (180 min/km and $81.84/km). Managers must decide on the trade-off between accuracy and cost while considering the demand and purpose of maps. GNSS mapping can be used for small-scale mapping or short-haul routes that require a small error range. Image warping was the lowest cost and produced low-accuracy maps, but may be suitable for large-scale mapping at the regional or national level. CAD file conversion was expected to be the most accurate method, because it converted as-built drawings to a map. However, we found that it was the least accurate method, indicating low accuracy of the as-built drawings. Efforts should be made to improve the accuracy of the as-built drawings in Korea.

Distance is one of the important factors in determining transportation cost and travel time, and it can be easily estimated by measuring the circuity of road networks. This study calculated the circuity factors to estimate the network distance for 27 forest roads (about 105 km) in South Korea. For this purpose, ridge, mid-slope, and valley roads were classified according to the construction location of the mountain slope, and the weighted and unweighted circuity factor (each 500-m section) were calculated. The average value of weighted circuity was 1.55: mid-slope roads (2.09), ridge roads (1.36), and valley roads (1.09). The average unweighted circuity factors were 1.61 for mid-slope roads, 1.21 for ridge roads, and 1.07 for valley roads. This study found that the circuity of the forest road network was most affected by the mountain terrain. In addition, the circuity factor increased with increasing network distance in the mid-slope roads but was not affected by the network distance in ridges and valleys. To improve the efficiency of transportation in the forest road network, it is important to locate the ladings and properly connect with the public road network.

Forest roads are an essential facility for sustainable forest management and protection. With advances in survey technology, such as Light Detection and Ranging, forest road maps with greater accuracy and resolution can be produced. This study produced a 3D map for establishment of a forest road inventory using a Mobile Laser Scanning (MLS) device mounted on a vehicle in four study forest roads in Korea, in order to review its precision, accuracy and efficiency based on comparisons with mapping using Total Station (TS) and Global Navigation Satellite System (GNSS). We counted the points that consist of the cloud data of the maps to determine the degree of precision density, and then compared this with 50 points at 20-m intervals on the centerlines bisecting the widths of the study forest roads. Then, we evaluated the relative positional accuracy of the MLS data based on three criteria: the total length of each forest road; the Root Mean Square Error (RMSE) obtained from coordinate values of the MLS and TS surveys compared to the GNSS survey; and the ratios of the centerlines extracted by the MLS and TS surveys overlaid to the buffer zone by the GNSS survey. Finally, we estimated the time and cost per unit length for producing the map to examine the efficiency of MLS mapping compared to the other two surveys. The results showed that the point cloud data acquired by the MLS survey on the study forest roads had very high precision and so is sufficient to produce a 3D forest road map with high-precision density and a low RMSE value. Although the equipment rental cost is somewhat high, the fact that information targeting on all spatial elements of forest roads can be obtained with a low cost of labor is a benefit when evaluating the efficiency of MLS survey and mapping. Our findings are expected to provide a quantitative assessment of both maintaining sustainable effectiveness and preventing potential environmental damage of forest roads.