摘要
ICESat-2(Ice,Cloud and Land Elevation Satellite-2)是世界首颗采用光子计数模式的激光测高卫星,可快速获得高精度、大尺度地面三维数据。光子探测机制使得数据中除了地面信号外,还包含大气散射等背景信号,需要通过滤波才能获得地形等信息。为分析ICESat-2背景和信号光子的分布特点及点云滤波算法的效果和适用性,本文首先选取了六种地表覆盖类型(城市、海冰、沙漠、植被、海洋及冰盖/冰川)及不同观测条件的数据,对其背景光子率进行统计分析。分析结果表明:白天观测数据的背景光子率平均为106(点/秒)数量级,远高于夜晚观测数据的背景光子率——104(点/秒)数量级,弱波束的背景光子率与强波束背景光子率相当,六种地表覆盖类型中,冰盖/冰川的背景光子率最高。然后,根据统计结果筛选出21组测高数据,并选取七种具有代表性的点云滤波对其进行去噪实验,分析精度后得出结论:改进局部密度法的去噪效果最佳,算法召回率、精准度和F值均大于0.90,算法较为稳定。最后,对所选取各滤波算法的精度、特点与适用性等性质进行了总结与分析,可为后续该数据的使用和滤波算法的选择提供参考。
ICESat-2 is the world´s first laser altimetry satellite to use photon counting technology.It provides high-precision,three-dimensional,large-scale ground data that can be obtained rapidly.Altimetry data obtained using photon detection systems generally contain ground signals and background signals,such as atmospheric scattering,which must be filtered to obtain ground information.To analyze the distribution characteristics of ICESat-2 background and signal photons and the performance of the point cloud filtering algorithm,we selected data from six types of land cover(city,sea ice,desert,vegetation,ocean and ice sheet(or glacier))in different observation conditions.A statistical analysis of the background rate was then performed.The results show that the average background rate of daytime observation data is 106 points per second,which is much higher than that of nighttime observation data(104 points per second).The background rate of the weak beam is equivalent to that of the strong beam.Among the six types of land cover,the ice sheet(or glacier)has the highest background rate.Based on the statistical results,21 datasets and seven representative point cloud filters were selected for denoising experiments.After analyzing the accuracy,we can conclude that the improved local density method with recall,accuracy,and F-measure values greater than 0.90 has the best denoising performance and is relatively stable.Finally,the performance,characteristics,and applicability of the seven filtering algorithms were summarized and analyzed.This can serve as a reference for the subsequent data use and selection of filtering algorithms.
作者
谢欢
黄佩琪
徐琪
叶丹
孙媛
栾奎峰
刘世杰
童小华
XIE Huan;HUANG Peiqi;XU Qi;YE Dan;SUN Yuan;LUAN Kuifeng;LIU Shijie;TONG Xiaohua(College of Surveying and Geo-informatics,Tongji University,Shanghai 200092,China;Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration,Shanghai 200092,China;College of Marine Sciences,Shanghai Ocean University,Shanghai 201306,China)
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2023年第5期631-643,共13页
Optics and Precision Engineering
基金
国家自然科学基金项目(No.41822106)
上海市教育发展基金会曙光计划项目(No.18SG22)。
