用无人机+气体断层成像技术，精准测绘火山二氧化碳排放。
Towards Drone-based Mapping of Volcanic Gases using Gas Tomography
- 用拉格朗日模型补偿风力影响，提升气体分布重建精度。
- 实测显示传统机载传感器因气流扰动失效，远程传感成功成图。
- 适合火山监测、环境评估与灾害预警研究者参考。
火山释放大量CO2，直接影响人类生活。监测火山气体排放有助于预测喷发，并理解其对气候与环境的影响。无人机气体传感显著降低监测风险，但旋翼下洗气流会扰动气流，导致气体难以被检测。本文采用基于远程传感的气体断层成像技术，在意大利萨利内勒-德伊卡普乔钦泥火山区域验证：搭载于无人机的原位传感器因气动干扰未能检测到CO2，而开放路径传感则成功实现气体分布映射。提出一种融合拉格朗日模型的新型模型驱动气体断层重建方法，有效补偿风致平流。重建结果与人工采集的原位测量数据一致，证实该方法可克服下洗限制，实现火山排放的精确制图。
原文摘要 · Abstract (English)
Volcanoes emit large amounts of CO2, directly influencing human lives. Mapping volcanic gas emissions helps to forecast eruptions and understand the impact of volcanoes on climate and the environment. Drone-based gas sensing significantly reduces risks in volcanic monitoring but faces technical limitations when measuring gas, as rotor downwash disperses the gas plume before detection. Gas Tomography using remote gas sensing addresses this challenge. At the Salinelle dei Cappuccini mud volcanoes, we demonstrate that while drone-mounted in-situ sensors failed to detect CO2 emissions due to aerodynamic disturbance, open-path sensing successfully enabled remote gas distribution mapping. We present a novel model-based gas tomographic reconstruction approach that incorporates a Lagrangian model to compensate for wind-induced advection. The resulting gas distribution maps align with manually collected in-situ measurements, confirming that model-based gas tomography effectively overcomes downwash limitations and enables accurate mapping of volcanic emissions.
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