Retrieval of terrain surface elevation in mountainous areas with ICESat-2/ATLAS

IF 11.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Remote Sensing of Environment Pub Date : 2025-05-27 DOI:10.1016/j.rse.2025.114823

Yanli Zhang , Pan Zhao , Xin Li , Bisheng Yang , Jun Zhao , Jiazheng Hu , Qi Wei , Kegong Li , Mingliang He

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引用次数: 0

Abstract

Land elevation data are indispensable for topographic mapping and geological disaster monitoring. However, the existing ICESat-2/ATL08 (V04) product has a coarse resolution (≥100 m) and is characterized by high uncertainty in mountainous areas; thus, it cannot be used to describe terrain relief characteristics accurately. In this study, a new method for extracting terrain surface elevation is proposed, which uses a local statistical denoising algorithm for mountainous areas (LSDAMA) based on the raw georeferenced photon product ICESat-2/ATL03. Coarse denoising is based on performing histogram thresholding, and refined denoising is based on local slope fitting; the process of performing coarse denoising twice and then refined denoising not only improves the removal effect for noise photons but also increases the signal photon retention rate in mountainous areas. Additionally, the estimation accuracy of the terrain surface elevation can be improved by setting rectangular dynamic windows along the fitted slope direction. Using the Babao River Basin in the Qilian Mountains as the research area, a total of 137 validation points from 777 GPS CORS in 40 quadrats and UAV LiDAR measurements were used to verify the accuracy. The results showed that the terrain surface elevations estimated by the LSDAMA are more accurate than those estimated by the ATL08 official products, especially in mountainous areas with slopes greater than 20°. The root mean square error (RMSE) of the LSDAMA decreased from 2.72 m for the ATL08 product to 0.60 m, and the mean deviation (MBE) decreased from −1.27 to 0.04 m. Additionally, the LSDAMA greatly improved the signal photon retention rate and reduced the interval between adjacent elevation points from 100 m for the ATL08 product to 2–7 m; this reduced interval can be used to describe the terrain fluctuation characteristics in detail, thus providing reliable basic data for monitoring terrain surface elevation changes in mountainous areas.

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基于ICESat-2/ATLAS的山区地表高程反演

土地高程数据是地形测绘和地质灾害监测必不可少的数据。然而，现有的ICESat-2/ATL08 （V04）产品分辨率较粗（≥100 m），在山区具有较高的不确定性；因此，它不能准确地描述地形起伏特征。本文提出了一种基于原始地理参考光子产品ICESat-2/ATL03的山区局部统计去噪算法（LSDAMA）提取地表高程的新方法。粗去噪基于执行直方图阈值，精细去噪基于局部斜率拟合；采用两次粗去噪再进行精细去噪的方法，不仅提高了噪声光子的去除效果，而且提高了山区信号光子的保留率。此外，在拟合的坡向上设置矩形动态窗口可以提高地形表面高程的估计精度。以祁连山八宝河流域为研究区，利用40个样方的777个GPS CORS和无人机激光雷达测量数据共137个验证点对其精度进行验证。结果表明，LSDAMA估算的地形表面高程比ATL08官方产品估算的地形表面高程更准确，特别是在坡度大于20°的山区。LSDAMA的均方根误差（RMSE）由ATL08产品的2.72 m下降到0.60 m，平均偏差（MBE）由- 1.27下降到0.04 m。此外，LSDAMA极大地提高了信号光子保留率，并将相邻高程点之间的间隔从ATL08产品的100 m缩短到2-7 m；这一缩减区间可以较为详细地描述地形起伏特征，为山区地表高程变化监测提供可靠的基础数据。

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来源期刊

Remote Sensing of Environment 环境科学-成像科学与照相技术

CiteScore

25.10

自引率

8.90%

发文量

455

审稿时长

53 days

期刊介绍： Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.