ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 77–81, 2018
https://doi.org/10.5194/isprs-annals-IV-3-77-2018
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 77–81, 2018
https://doi.org/10.5194/isprs-annals-IV-3-77-2018

  23 Apr 2018

23 Apr 2018

ESTIMATION OF FOREST BIOMASS BASED ON MULITI-SOURCE REMOTE SENSING DATA SET – A CASE STUDY OF SHANGRI-LA COUNTY

Wanwan Feng1,2, Leiguang Wang2, Junfeng Xie3, Cairong Yue1, Yalan Zheng1, and Longhua Yu1 Wanwan Feng et al.
  • 1Southwest Forestry University, Faculty of Forestry, Kunming 650224, China
  • 2Southwest Forestry University, Big data and Artificial Intelligence Research Institute, Kunming 650224, China
  • 3Satellite Surveying and Mapping Application Centre, Beijing 100048, China

Keywords: Texture, Regression model, Shangri-La county, Multi-source data, Forest biomass estimation

Abstract. Forest biomass is an important indicator for the structure and function of forest ecosystems, and an accurate assessment of forest biomass is crucial for understanding ecosystem changes. Remote sensing has been widely used for inversion of biomass. However, in mature or over-mature forest areas, spectral saturation is prone to occur. Based on existing research, this paper synthesizes domestic high resolution satellites, ZY3-01 satellites, and GLAS14-level data from space-borne Lidar system, and other data set. Extracting texture and elevation features respectively, for the inversion of forest biomass. This experiment takes Shangri-La as the research area. Firstly, the biomass in the laser spot was calculated based on GLAS data and other auxiliary data, DEM, the second type inventory of forest resources data and the Shangri-La vector boundary data. Then, the regression model was established, that is, the relationship between the texture factors of ZY3-01 and biomass in the laser spot. Finally, by using this model and the forest distribution map in Shangri-La, the biomass of the whole area is obtained, which is 1.3972 × 108t.