摘要
Abstract
With the successful launch and operation of the Ice,Cloud,and Land Elevation Satellite-2(ICESat-2),obtaining detailed terrain information of the Earth's surface has become possible.However,noise interference in photon data poses challenges for data applications.This paper proposed an accurate extraction method for ICESat-2 photon signal based on two-layer density-based spatial clustering of applications with noise(DBSCAN),aimed at improving the accuracy of ground elevation and vegetation height extraction from ICESat-2 data.The two-layer DBSCAN algorithm performs rough and pre-cise extraction of photon signals through two separate DBSCAN clustering processes.Experimental results show that this algorithm maintains high denoising performance under different terrain conditions,with F1 scores consistently exceeding 89％,demonstrating strong adaptability to terrain changes.Compared to traditional methods,the two-layer DBSCAN algo-rithm has advantages in extraction accuracy,allowing for more precise extraction of signal photons and maintaining high extraction precision even in the presence of significant noise interference.The two-layer DBSCAN algorithm enables the extraction of signal photons in complex scenarios,providing accurate photon data for applications such as high-precision ter-rain mapping and glacier thickness measurement.关键词
冰、云和陆地高程卫星2号(ICESat-2)/光子数据去噪/基于密度的带有噪声的空间聚类(DBSCAN)算法/聚类/激光雷达Key words
Ice,Cloud,and Land Elevation Satellite-2(ICESat-2)/photon data denoising/density-based spatial clustering of applications with noise(DBSCAN)/Clustering/light laser detection and ranging(LiDAR)分类
天文与地球科学
