首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >A method to automatically determine sea level for referencing snow freeboards and computing sea ice thicknesses from NASA IceBridge airborne LIDAR
【24h】

A method to automatically determine sea level for referencing snow freeboards and computing sea ice thicknesses from NASA IceBridge airborne LIDAR

机译:一种自动确定海平面以参考干雪板并从NASA IceBridge机载LIDAR计算海冰厚度的方法

获取原文
获取原文并翻译 | 示例
           

摘要

The NASA IceBridge flights have obtained critical observations for Earth's polar ice since ICESat stopped collecting data in 2009. This study develops an automatic method in processing IceBridge Airborne Topographic Mapper (ATM) altimeter L1B data (one elevation per 3-4. m horizontally) to derive a local sea level height for referencing snow freeboards and then computing sea ice thicknesses. Four 30-km L1B profiles (A, B, C and D) flown on October 21, 2009 over the Bellingshausen Sea in Antarctica are selected. The local sea level reference is first obtained by visual examination of ATM L1B heights over leads or thin ice identified on images simultaneously acquired from the Digital Mapping System camera (called manual selection). This sea level reference is then used as ground truth to validate sea level heights derived by automatic calculations using five thresholds of 2%, 1%, 0.5%, 0.2% and 0.1% of the lowest L1B data. The L1B_0.2% method gives a similar sea level height as from the L1B manual selection, by mean (absolute) difference of -0.01 (0.06) m. The sea level heights demonstrate a near linear gradient of 0.01. m/km to 0.03. m/km within each ~. 30-km L1B profile along the flight track from section A to D. The resulting mean snow freeboards are 0.59. m, 0.67. m, 0.53. m, and 0.60. m on sections A, B, C and D, respectively. Three empirical equations and the buoyancy equation (with zero ice freeboard assumption) all give similar statistics in ice thickness estimation with mean ice thicknesses of 1.91. m for section A, 2.16. m for B, 1.76. m for C, and 1.94. m for D. The sea level over leads cannot be accurately resolved from the ATM L2 data (~. 60. m x 80. m horizontal averaging). However, by using a sea level reference obtained from the L1B data, the ATM L2 data can achieve reasonable ice thickness estimates with mean absolute difference of only 0.10. m compared to thickness derived from the L1B data.
机译:自从ICESat在2009年停止收集数据以来,NASA IceBridge航班已经获得了对地球极地冰的关键观测结果。这项研究开发了一种自动方法来处理IceBridge机载地形测绘仪(ATM)高度计L1B数据(水平每3-4。m高程)到推导当地的海平面高度,以参考干雪板,然后计算海冰厚度。选择了2009年10月21日在南极贝灵斯豪森海上飞行的四个30公里L1B剖面(A,B,C和D)。首先通过目视检查从数字测绘系统相机同时获取的图像上识别出的导线或稀薄的冰上的ATM L1B高度,来获得本地海平面参考(称为手动选择)。然后将此海平面参考用作地面真相,以验证使用最低L1B数据的2%,1%,0.5%,0.2%和0.1%的五个阈值通过自动计算得出的海平面高度。 L1B_0.2%方法的平均海平面高度与手动选择L1B的海平面高度相似,均值(绝对)差为-0.01(0.06)m。海平面高度显示出接近0.01的线性梯度。 m / km至0.03。每米以内m / km。从A区到D区的飞行轨迹为30公里的L1B剖面。所得平均降雪干度为0.59。 m,0.67。 m,0.53。 m和0.60 m分别位于A,B,C和D部分。三个经验方程式和浮力方程式(假设干冰高度为零)在平均冰厚为1.91的冰厚估计中都给出了相似的统计数据。 m代表A节2.16。 B的m,1.76。 C为1.94。 D处的m。无法从ATM L2数据(〜。60. m x 80. m水平平均)中准确解析出导线上方的海平面。但是,通过使用从L1B数据获得的海平面参考,ATM L2数据可以实现合理的冰厚估计,平均绝对差仅为0.10。 m与从L1B数据得出的厚度相比。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号