基于改进的道格拉斯-普克算法确定大气激光雷达消光系数边界值

Abstract

Objective Atmospheric lidar has been widely used in horizontal scanning measurements for air pollution monitoring in recent years.The determination of the boundary value of the aerosol extinction coefficient (AEC) and the retrieval of the AEC profile are the key issues for quantitative atmospheric applications. In this work, a new method based on an improved Douglas -Peucker (DP) algorithm is proposed to find the linear region in the logarithmic lidar curve, from which the boundary value of the AEC is estimated. Combined with the classical Klett method, the AEC profile can be obtained in horizontal scanning measurements. The feasibility and performance of the improved DP algorithm has been validated through comparison studies of the AEC scanning map. MethodsThe experimental data evaluated in this work were obtained by a scanning Scheimpflug lidar (SLidar) system installed in Xianyang City, Shaanxi Province (Fig. 1), employing high power laser diodes as light sources and area image sensors as detectors.The elevation angle of the SLidar system during horizontal scanning measurements is about 3°. The scanning period is about 20 min with a rotation step of 2°. The DP algorithm has been proposed to automatically search linear regions in the logarithmic lidar signal.The DP algorithm decimates the original logarithmic lidar curve to a similar curve with fewer points through an iterative endpoint fit algorithm. Besides, the variance of the distance between the logarithmic lidar signal and the corresponding line segment is used as the threshold to replace the farthest/maximum distance threshold in the classical DP algorithm , which can be used to obtain the linear region of the logarithmic lidar curve more accurately. The slope method is then employed for the determination of the AEC boundary value in the linear region, where the atmosphere is considered to be homogeneous. With the boundary value of the AEC as the input, the AEC profile can be obtained in horizontal scanning measurements according to the Klett method. Long enough linear regions (>3500 m) with an R 2 correlation coefficient beyond 0.9999 are selected as reference signals, from which the AEC profile can be reliably obtained. By comparing with the AEC profile retrieved from the reference signal, the performances of the classical DP algorithm and the improved DP algorithm are evaluated.Results and Discussions It has been found out that the maximum distance threshold used in classical DP algorithm cannot be well adapted to different atmospheric conditions. On the other hand, the variance of the distance between the logarithmic lidar signal and the corresponding line segment, considering the deviations of all data points in the potential linear region, is more reliable for evaluating the linearity of the logarithmic lidar signal segment. According to comprehensive comparison studies, the variance threshold can be set to 1×10 -4 to obtain the optimum result under various atmospheric conditions. The improved DP algorithm based on the variance threshold is then ut...