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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Algorithm for Detection of Ground and Canopy Cover in Micropulse Photon-Counting Lidar Altimeter Data in Preparation for the ICESat-2 Mission
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Algorithm for Detection of Ground and Canopy Cover in Micropulse Photon-Counting Lidar Altimeter Data in Preparation for the ICESat-2 Mission

机译：为ICESat-2任务做准备的微脉冲光子计数激光雷达高度计数据中地面和树冠覆盖的检测算法

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摘要

NASA's Ice, Cloud and Land Elevation Satellite-II (ICESat-2) mission is a decadal survey mission (2016 launch). The mission objectives are to measure land ice elevation, sea ice freeboard, and changes in these variables, as well as to collect measurements over vegetation to facilitate canopy height determination. Two innovative components will characterize the ICESat-2 lidar: 1) collection of elevation data by a multibeam system and 2) application of micropulse lidar (photon-counting) technology. A photon-counting altimeter yields clouds of discrete points, resulting from returns of individual photons, and hence new data analysis techniques are required for elevation determination and association of the returned points to reflectors of interest. The objective of this paper is to derive an algorithm that allows detection of ground under dense canopy and identification of ground and canopy levels in simulated ICESat-2 data, based on airborne observations with a Sigma Space micropulse lidar. The mathematical algorithm uses spatial statistical and discrete mathematical concepts, including radial basis functions, density measures, geometrical anisotropy, eigenvectors, and geostatistical classification parameters and hyperparameters. Validation shows that ground and canopy elevation, and hence canopy height, can be expected to be observable with high accuracy by ICESat-2 for all expected beam energies considered for instrument design (93.01%-99.57% correctly selected points for a beam with expected return of 0.93 mean signals per shot (msp), and 72.85%-98.68% for 0.48 msp). The algorithm derived here is generally applicable for elevation determination from photon-counting lidar altimeter data collected over forested areas, land ice, sea ice, and land surfaces, as well as for cloud detection.
机译：NASA的“冰，云和陆地高空人造卫星II（ICESat-2）”任务是十年测量任务（2016年发射）。任务目标是测量陆地冰的高度，海冰干舷以及这些变量的变化，以及收集植被上的测量值以方便确定树冠高度。 ICESat-2激光雷达的两个创新组件：1）通过多光束系统收集高程数据； 2）应用微脉冲激光雷达（光子计数）技术。光子计数高度计由于单个光子的返回而产生离散点的云，因此需要新的数据分析技术来确定高度并将返回的点关联到感兴趣的反射器。本文的目的是基于使用Sigma Space微脉冲激光雷达的机载观测结果，推导一种算法，该算法可以检测密集冠层下的地面并识别模拟的ICESat-2数据中的地面和冠层水平。该数学算法使用空间统计和离散数学概念，包括径向基函数，密度度量，几何各向异性，特征向量以及地统计分类参数和超参数。验证表明，对于仪器设计中考虑的所有预期束能量，ICESat-2均可以高精度观察到地面和树冠高程以及树冠高度（93.01％-99.57％正确选择了具有预期收益的梁的点）每次射击的平均信号数（msp）为0.93，0.48毫秒的72.85％-98.68％）。此处导出的算法通常适用于根据在林区，陆地冰，海冰和陆地表面上收集的光子计数激光雷达高度计数据进行的海拔确定，以及云检测。

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