Volume IV-4/W4
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W4, 255-258, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W4-255-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W4, 255-258, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W4-255-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  13 Nov 2017

13 Nov 2017

USING AIRBORNE LIDAR DATA FOR ASSESSMENT OF FOREST FIRE FUEL LOAD POTENTIAL

M. İnan1, E. Bilici2, and A. E. Akay2 M. İnan et al.
  • 1Istanbul University, Faculty of Forestry, Department of Surveying and Cadastre, Istanbul, Turkey
  • 2Bursa Technical University, Faculty of Forestry, 16310 Yıldırım, Bursa, Turkey

Keywords: LIDAR, Forestry, Voxel Point Cloud Segmentation, Forest Fire Risk, Fuel Load Potential

Abstract. Forest 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 Bahceköy Forest Enterprise Directorate that composed of mixed deciduous forest structure.