Volume XLII-3/W9
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W9, 227–232, 2019
https://doi.org/10.5194/isprs-archives-XLII-3-W9-227-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W9, 227–232, 2019
https://doi.org/10.5194/isprs-archives-XLII-3-W9-227-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  25 Oct 2019

25 Oct 2019

PROCESSING JUMP POINT OF LIDAR DETECTION DATA AND INVERSING THE AEROSOL EXTINCTION COEFFICIENT

H. L. Zhang1, H. Zhao1, Y. P. Liu2, X. K. Wang2, and C. Shu2 H. L. Zhang et al.
  • 1School of Electrical and Information Engineering, North MinZu University Yinchuan 750021, China
  • 2School of Computer Science and Engineering, North MinZu University Yinchuan 750021, China

Keywords: Extinction Coefficient, Jump Point, Fitting, Interpolation, Invention Method

Abstract. For a long time, the research of the optical properties of atmospheric aerosols has aroused a wide concern in the field of atmospheric and environmental. Many scholars commonly use the Klett method to invert the lidar return signal of Mie scattering. However, there are always some negative values in the detection data of lidar, which have no actual meaning,and which are jump points. The jump points are also called wild value points and abnormal points. The jump points are refered to the detecting points that are significantly different from the surrounding detection points, and which are not consistent with the actual situation. As a result, when the far end point is selected as the boundary value, the inversion error is too large to successfully invert the extinction coefficient profile. These negative points are jump points, which must be removed in the inversion process. In order to solve the problem, a method of processing jump points of detection data of lidar and the inversion method of aerosol extinction coefficient is proposed in this paper. In this method, when there are few jump points, the linear interpolation method is used to process the jump points. When the number of continuous jump points is large, the function fitting method is used to process the jump points. The feasibility and reliability of this method are verified by using actual lidar data. The results show that the extinction coefficient profile can be successfully inverted when different remote boundary values are chosen. The extinction coefficient profile inverted by this method is more continuous and smoother. The effective detection range of lidar is greatly increased using this method. The extinction coefficient profile is more realistic. The extinction coefficient profile inverted by this method is more favorable to further analysis of the properties of atmospheric aerosol. Therefore, this method has great practical application and popularization value.