Inan, M.Bilici, E.Akay, Abdullah Emin2021-03-202021-03-2020172194-90422194-9050http://doi.org/10.5194/isprs-annals-IV-4-W4-255-2017https://hdl.handle.net/20.500.12885/10314th International Workshop on Geoinformation Science / 4th ISPRS International Workshop on Multi-Dimensional and Multi-Scale Spatial Data Modeling (GeoAdvances) -- OCT 14-15, 2017 -- Karabuk Univ, Safranbolu Campus, Safranbolu, TURKEYINAN, Muhittin/0000-0001-8179-9499; Akay, Abdullah Emin/0000-0001-6558-9029Forest fire incidences are one of the most detrimental disasters that may cause long terms effects on forest ecosystems in many parts of the world. In order to minimize environmental damages of fires on forest ecosystems, the forested areas with high fire risk should be determined so that necessary precaution measurements can be implemented in those areas. Assessment of forest fire fuel load can be used to estimate forest fire risk. In order to estimate fuel load capacity, forestry parameters such as number of trees, tree height, tree diameter, crown diameter, and tree volume should be accurately measured. In recent years, with the advancements in remote sensing technology, it is possible to use airborne LIDAR for data estimation of forestry parameters. In this study, the capabilities of using LIDAR based point cloud data for assessment of the forest fuel load potential was investigated. The research area was chosen in the Istanbul Bentler series of Bahcekoy Forest Enterprise Directorate that composed of mixed deciduous forest structure.eninfo:eu-repo/semantics/openAccessLIDARForestryVoxel Point Cloud SegmentationForest Fire RiskFuel Load PotentialConference Object10.5194/isprs-annals-IV-4-W4-255-20174-4W4255258WOS:000568997100038N/AN/A