Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 747-749, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-747-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
23 Jun 2016
SUBTROPICAL FOREST BIOMASS ESTIMATION USING AIRBORNE LiDAR AND HYPERSPECTRAL DATA
Yong Pang and Zengyuan Li Institute of Forest Resource Information Technique, Chinese Academy of Forestry, China
Keywords: Subtropical Forest, Biomass, Airborne Lidar, Hyperspectral, Fusion Abstract. Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF’s (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.
Conference paper (PDF, 785 KB)


Citation: Pang, Y. and Li, Z.: SUBTROPICAL FOREST BIOMASS ESTIMATION USING AIRBORNE LiDAR AND HYPERSPECTRAL DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 747-749, https://doi.org/10.5194/isprs-archives-XLI-B8-747-2016, 2016.

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