基于FY-3A遥感数据的冰岛火山灰云识别

2010年4月至5月期间冰岛艾雅法拉火山喷发造成了欧洲航空业史无前例的瘫痪以及巨大的经济损失,其严重影响再次显示,对火山灰云进行有效监测的重要性。火山灰云是由火山碎屑物及气体组成的混合物,火山碎屑物主要由直径小于2mm的岩石、矿物、火山玻璃碎片组成,火山灰云中的气体主要包括水汽、CO2、SO2、H2S、CH4、CO、HCL、HF、HBr、和NOx等。使用具有我国自主知识产权的FY-3A/VIRR数据,对此次艾雅法拉火山喷发的不同阶段选取具有典型风向变化的日期,采用分裂窗亮温差算法(SWTD)、RGB真彩色方法、中红外波段数据等进行火山灰云的识别,并将结果与冰岛地区的火山灰监测报告以及前人的研究结果进行对比研究,结果表明:火山喷发初期火山灰云中较高含量的水汽会补偿反面吸收的影响,妨碍分裂窗亮温差算法(SWTD)对火山灰云的识别,而中红外波段数据因对高温物体的敏感性,不受水汽的影响,对喷发初期较高温度的火山灰云识别效果较好;在喷发中期,火山灰云浓度较大时三种方法均表现良好,卫星图像中火山灰云的位置信息及漂移方向均非常清晰,且同气象条件相吻合,验证了识别方法的正确性。该项结果表明,具有我国自主知识产权的FY-3A数据能够达到监测火山灰云的目的,而如何更加清晰地界定火山灰云的边界位置以及更加准确的计算出火山灰云的浓度需要进一步的深入研究。

Identification of Icelandic volcanic ash cloud based on FY-3A remote sensing data

The eruption of Iceland's Eyjafjallajökull volcano in April-May 2010 resulted in an unprecedented disruption to Europe's airline industry as well as a huge economic loss. Such serious impact reminds us with vital importance to monitor ash cloud efficiently. Volcanic ash cloud is a mixture of volcanic debris and gases, with the former mainly composed of rocks, minerals and volcanic glass pieces all measuring less than 2mm in diameter, and the latter including major gases such as water vapor, CO₂, SO₂, H₂S, CH₄, CO, HCL, HF, HBr, and NOx etc. Using the FY-3A/VIRR data with China's own independent intellectual property rights, this paper attempts to identify volcanic ash cloud by adopting Split Window Temperature Difference method (SWTD), RGB nature color method and Mid-Infrared data etc. on the dates with typical wind direction changes in different phases of the Eyjafjallajökull volcanic eruption. Then, this paper makes a comparative study on the identification results with reference to the volcanic ash monitoring reports of Iceland and the research results of predecessors. The study suggests that in the preliminary stage of volcanic eruption high concentration of water vapor in volcanic ash cloud will compensate the reverse absorption and prevent the identification of volcanic ash cloud with SWTD method. Whereas Mid-Infrared data is more effective in identifying thermal volcanic ash cloud in the early volcanic eruption thanks to its sensitivity to high temperature objects to free from the influence of water vapor. In the mid and late eruption, three methods all perform well with high density of ash cloud. Satellite images clearly show the location and the drift direction of the ash cloud, which are also corresponding to the meteorological conditions. Hence, the identification methods prove to be correct. The research results indicate that FY-3A/VIRR data with our own independent intellectual property rights is capable of monitoring the ash cloud. How to define the boundary of the volcanic ash cloud more clearly and calculate the density of the volcanic ash cloud more accurately will be the focus of the further research.