摘要
基于新型雷达高度计Sentienl-3波形数据构建了兰伯特冰川区域的DEM。对比分析了重心偏移算法(OCOG)、线性5-β算法、主波峰峰值算法(NPPR)等几种重跟踪算法对Sentienl-3在冰盖区域的处理效果,并提出了分区域选取最优重跟踪算法的处理方法,提高了测高值精度。采用克里金插值法获得了基于Sentinel-3波形数据的500 m分辨率S3Lam DEM,并利用ICESat-2激光测高数据验证S3Lam DEM的整体高程精度为0.682±2.998 m。与另外两种基于Cryosat-2测高数据建立的南极DEM对比结果表明,S3Lam DEM整体精度有所提升,Sentienl-3数据对高程精度的明显改善位于低坡度的内陆冰盖。结果反映了Sentienl-3高度计数据在南极冰盖测高方面的有效性和优势,这对于未来长期监测南极冰盖高程有重要意义。
Satellite radar altimeter is the main data source for obtaining DEM of the Antarctic ice sheet, and the new radar altimeter Sentienl-3 has unique advantages in Antarctic ice sheet. Based on Sentinel-3 waveform data, this paper studied the application of this new data and derived a 500 m digital elevation model for Lambert Glacier area. The effects of several retracking algorithms for the new Sentinel-3 waveform in Antarctic ice sheet were compared and analyzed, including Offset Center of Gravity method, the linear 5-beta parametric method and the Narrow Primary Peak Retracker method. A sub-regional method based on optimal retracking algorithm was proposed to improve the accuracy of measurements. Then a new DEM(S3 Lam DEM) with 500 m resolution for Lambert Glacier area was presented by kriging interpolation. The accuracy of S3 Lam DEM was assessed by ICESat-2 laser altimetry data, and the overall accuracy was 0.682±2.998 m. The comparison with two other Antarctic DEMs obtained from Cryosat-2 data shown that the accuracy of S3 Lam DEM had improved, especially in the low-slope inland ice sheet. The results reflect the effectiveness and advantages of Sentienl-3 altimeter data for mapping the Antarctic ice sheet, which can provide significant support for the long-term monitoring of Antarctic ice sheet in the future.
作者
李宋
廖静娟
张连翀
LI Song;LIAO Jingjuan;ZHANG Lianchong(Key Laboratory of Digital Earth Science,Aerospace Information Research Institution,Chinese Academy of Sciences,Beijing 100094,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《测绘科学》
CSCD
北大核心
2022年第7期104-110,142,共8页
Science of Surveying and Mapping
基金
国家自然科学基金项目(41871256)
