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A Comparative Study of Carbon Absorption Measurement Using Hyperspectral Image and High Density LiDAR Data in Geojedo

  • Received : 2017.04.05
  • Accepted : 2017.08.21
  • Published : 2017.08.31

Abstract

This paper aims to study a method to estimate precise carbon absorption by quantification of forest information that uses accurate LiDAR data, hyperspectral image. To estimate precise carbon absorption value by using spatial data, a problem was found out of carbon absorption value estimation method with statistical method, which is already existed method, and then offered optimized carbon absorption estimation method with spatial information by analyzing with methods of compare digital aerial photogrammetry and LiDAR data. It turned out possible Precise classification and quantification in case of using LiDAR and hyperspectral image. Various classification of tree species was possible with use of LiDAR and hyperspectral image. Classification of hyperspectral image was matched in general with field survey and Mahalanobis distance classification method. Precise forest resources could be extracted using high density LiDAR data. Compared with existing method, 19.7% in forest area, 19.2% in total carbon absorption, 0.9% in absorption per unit area of difference created, and improvement was found out to be estimated precisely in international code.

Keywords

References

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