{"_buckets": {"deposit": "adef473b-417b-49c0-93fa-29f37e62d20e"}, "_deposit": {"id": "10262", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "10262"}, "status": "published"}, "_oai": {"id": "oai:soar-ir.repo.nii.ac.jp:00010262"}, "item_6_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2013-06", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "1", "bibliographicPageEnd": "15", "bibliographicPageStart": "1", "bibliographicVolumeNumber": "34", "bibliographic_titles": [{"bibliographic_title": "CROATIAN JOURNAL OF FOREST ENGINEERING"}]}]}, "item_6_description_20": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "In this study, a model to automatically design a forest road considering shallow landslides using LiDAR data was examined. 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First, in order to develop a shallow landslide risk map of the Funyu Experimental Forest, a slope stability analysis was carried out using the infinite slope stability analysis formula. The soil depth was surveyed at 167 points using simple penetration tests, and the frequency distributions of the soil depth were estimated as logarithmic normal distributions. A soil depth map of the experimental forest was made using the mode values of the lognormal distributions. Then, shallow landslide risk maps were also made for the experimental forest by a slope stability analysis using these soil depth distributions. Finally, an automatic forest road design model was developed with a LiDAR based highly accurate Digital Terrain Model (DTM) and shallow landslide risk map using cubic spline interpolation and dynamic programming. The program has capability of minimizing the earthwork costs while avoiding shallow landslide risk areas. 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