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冰川冻土 ›› 2022, Vol. 44 ›› Issue (3): 1100-1108.doi: 10.7522/j.issn.1000-0240.2022.0102

• 冰冻圈技术 • 上一篇    

基于延时数字摄影测量的积雪过程4D监测技术研究

刘俊峰1(), 陈仁升1,2, 韩春坛1, 郭淑海1, 刘章文1, 王学良1,3, 卿文武4   

  1. 1.中国科学院 西北生态环境资源研究院, 甘肃 兰州 730000
    2.西北大学, 陕西 西安 710127
    3.甘肃省水文站, 甘肃 兰州 730000
    4.兰州大学, 甘肃 兰州 730000
  • 收稿日期:2021-07-06 修回日期:2021-11-01 出版日期:2022-06-25 发布日期:2022-08-27
  • 作者简介:刘俊峰,副研究员,主要从事寒区水文观测研究工作. E-mail: liujfzyou@lzb.ac.cn
  • 基金资助:
    国家重点研发计划项目(2019YFC1510500);国家自然科学基金项目(41877163);中国科学院“百人计划”项目(Y729G01002)

Snow surface monitoring from 4D structure from motion photogrammetry

Junfeng LIU1(), Rensheng CHEN1,2, Chuntan HAN1, Shuhai GUO1, Zhangwen LIU1, Xueliang WANG1,3, Wenwu QING4   

  1. 1.Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
    2.Northwest University, Xi’an 710127, China
    3.Gansu Hydrological Stations, Lanzhou 730000, China
    4.Lanzhou University, Lanzhou 730000, China
  • Received:2021-07-06 Revised:2021-11-01 Online:2022-06-25 Published:2022-08-27

摘要:

为实现4D(时间+空间)多目标、高精度的积雪监测,本次试验研究采用单台相机延时拍摄结合运动结构重建算法(Structure from motion,SfM),分别获取了祁连山黑河上游站裸露山坡坡面尺度单次降雪的雪深、逐日积雪空间分布和面积,以及祁连山八一冰川1.5 m×1.5 m的斑块尺度全年雪深及雪面特征数据。坡面尺度积雪观测研究表明:本方法可以准确获取积雪分布信息,但其雪深空间分布获取精度较差。斑块尺度雪深监测研究表明:本方法能够很好地获取连续的雪面特征信息和雪深,且获取雪深与SR50观测雪深的绝对误差小于3.4 cm。在不同季节,本方法对积雪监测能力略有差异:春季快速积累期雪面纹理少,照片组对齐并获取点云数据和DEM数据的成功率较低,而冬季和消融季雪面纹理丰富,相应的对齐成功率比例和精度较高。本研究表明基于单台相机的4D摄影测量方法能够实现小范围、连续、高精度、多目标的积雪监测,未来应用前景广泛。

关键词: 4D摄影测量, SfM算法, 积雪面积, 雪深, 积雪分布

Abstract:

In order to achieve 4D (time+space) multi-objective and high-precision snow monitoring, a single-camera time-lapse Structure-from-Motion (SfM) photogrammetry setup was build-up and tested at two different places of Qilian Mountains. The one test was performed to estimate snow depth, snow cover area and their distribution on slope scale at Qilian Alpine station. Another experiments was carried out next to the August-one glacier to monitor snow-surface depth and snow-surface features at plot-scale. At slope scale, the 4D SfM photogrammetry is capable to acquire snow cover area with high accuracy. Yet the accuracy of 4D SfM photogrammetry derived snow depth was poor at slop scale. At plot-scale, the 4D SfM photogrammetry can obtain continuous snow surface characteristic information and snow depth well. The absolute error between the 4D SfM photogrammetry estimated and the SR50 observed snow depth was less than 3.4 cm. The 4D SfM photogrammetry performance varies with the variation of surface condition in different season. The best performance was reached with snow surface features were abundant in winter and in melt season. It is hard for 4D SfM photogrammetry to capture high precision and alignment achievement in spring. Our results suggest that 4D SfM photogrammetry can achieve long-term, continual, multi-objective and high-precision monitor of plot scale snow processes.

Key words: 4D SfM photogrammetry, structure from motion, snow covered area, snow depth, snow distribution

中图分类号: 

  • P426.63+5