利用无人机红外热成像技术绘制超冰川碎屑厚度图的低成本开源方法

J. Messmer, A. Groos
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引用次数: 0

摘要

摘要许多山脉都有碎屑覆盖的冰川,它们在区域水循环中发挥着重要作用。然而,由于全球只有少数几个地方可以精确观测到碎屑厚度和碎屑下冰融化率的小尺度变化,因此建立碎屑覆盖冰川的地表质量平衡、径流贡献和未来演变模型充满了不确定性。在此,我们介绍了一种用于高分辨率山地冰川热成像的定制化低成本无人飞行器(UAV),并介绍了一个完整的开源管道,该管道有助于根据辐射测量图像生成精确的地表温度和碎屑厚度图。首先,利用运动结构和多视角立体技术,从单个无人飞行器辐射图像中计算出辐射正射影像图。然后,用户特定的校准和修正程序可应用于辐射正射影像图,以考虑影响辐射测量的大气和环境因素。热能正射影像图显示了整个勘测碎片覆盖区域表面温度的明显空间变化。最后,利用将地表温度与碎片厚度联系起来的经验或逆地表能量平衡模型,并根据现场测量结果进行校准,从校正后的热正射照片中得出高分辨率碎片厚度图。我们在瑞士阿尔卑斯山的 Kanderfirn(又称 Kander Neve)进行的小规模实验结果表明,利用经验或物理模型可以高精度地绘制相对较薄的碎屑层(约 0-15 厘米)的表面温度和厚度图。在冰雪表面,绘制的表面温度与融点(0 ∼ 0 ∘C)的平均偏差为 0.6 ± 2.0 ∘C。模拟碎片厚度的均方根误差为 1.3 厘米。通过详细测绘,典型的小尺度碎片特征和碎片厚度模式变得清晰可见,而当前一代卫星的热红外传感器无法在空间上分辨这些特征和模式。所提出的方法为全面的高分辨率冰川上碎屑厚度测绘铺平了道路,并为更精确地监测碎屑覆盖的冰川并为其建模开辟了新的机会。
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A low-cost and open-source approach for supraglacial debris thickness mapping using UAV-based infrared thermography
Abstract. Debris-covered glaciers exist in many mountain ranges and play an important role in the regional water cycle. However, modelling the surface mass balance, runoff contribution and future evolution of debris-covered glaciers is fraught with uncertainty as accurate observations on small-scale variations in debris thickness and sub-debris ice melt rates are only available for a few locations worldwide. Here we describe a customised low-cost unoccupied aerial vehicle (UAV) for high-resolution thermal imaging of mountain glaciers and present a complete open-source pipeline that facilitates the generation of accurate surface temperature and debris thickness maps from radiometric images. First, a radiometric orthophoto is computed from individual radiometric UAV images using structure-from-motion and multi-view-stereo techniques. User-specific calibration and correction procedures can then be applied to the radiometric orthophoto to account for atmospheric and environmental influences that affect the radiometric measurement. The thermal orthophoto reveals distinct spatial variations in surface temperature across the surveyed debris-covered area. Finally, a high-resolution debris thickness map is derived from the corrected thermal orthophoto using an empirical or inverse surface energy balance model that relates surface temperature to debris thickness and is calibrated against in situ measurements. Our results from a small-scale experiment on the Kanderfirn (also known as Kander Neve) in the Swiss Alps show that the surface temperature and thickness of a relatively thin debris layer (ca. 0–15 cm) can be mapped with high accuracy using an empirical or physical model. On snow and ice surfaces, the mean deviation of the mapped surface temperature from the melting point (∼ 0 ∘C) was 0.6 ± 2.0 ∘C. The root-mean-square error of the modelled debris thickness was 1.3 cm. Through the detailed mapping, typical small-scale debris features and debris thickness patterns become visible, which are not spatially resolved by the thermal infrared sensors of current-generation satellites. The presented approach paves the way for comprehensive high-resolution supraglacial debris thickness mapping and opens up new opportunities for more accurate monitoring and modelling of debris-covered glaciers.
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