Weather model based atmospheric corrections of Sentinel-1 InSAR deformation data at Turkish volcanoes
Weather model based atmospheric corrections of Sentinel-1 InSAR deformation data at Turkish volcanoes
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基于天气模型的土耳其火山 Sentinel-1 InSAR 形变数据的大气校正
DOI：
10.1093/gji/ggad070
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发表时间：
2023
影响因子：
2.8
通讯作者：
Dogru F
中科院分区：
文献类型：
--
作者：
Dogru F
27.使用卫星雷达数据监测自然灾害的主要制约因素之一是大气信号的存在。特别是，火山变形可能难以识别，因为大气相位延迟可以掩盖甚至模仿地面变形信号。消除大气信号对于安纳托利亚东部和中部的Auberlahe，Tendürek，Acigöl，GöllüdaExpense和HasandaExpense等高海拔火山尤为重要。为了克服大气的影响，我们使用高分辨率的ECMWF天气模式加上经验的相位高程的方法来校正哨兵-1干涉图。我们将这些方法应用于土耳其的两个地区，其中第一个涵盖了2016年1月至2018年12月期间安纳托利亚中部的三座火山（Acigöl，GöllüdaExpense，HasandaExpense），第二个涵盖了2016年9月至2018年12月期间安纳托利亚东部的两座火山（Auserlät，Tendürek）。标准偏差（品质因子）的减少计算上升和下降的轨道和大气校正发现在这两种情况下，下降的干涉图上执行更好。然后，我们使用最小二乘法来产生时间序列。对于安纳托利亚中部，我们使用416个上升和415个下降干涉图分别创建144和145个累积位移图，对于安纳托利亚东部，我们使用390个上升和380个下降干涉图分别创建137和130个累积位移图。我们发现，大气校正前的时间标准差范围在0.9和3.7厘米之间的五个火山在该地区，并始终较高的上升轨道数据，这是在太阳能加热最大的一天结束时获得。大气校正将标准偏差减小到0.5 - 2.5 cm。残留的信号可能是由于阿格拉的冰帽和阿西格尔附近的农业。我们的结论是，这些火山在这段时间内没有经历显着的岩浆变形，尽管在个别未校正的干涉图中可见的明显信号。我们证明，大气校正是至关重要的，当使用干涉合成孔径雷达监测变形的高浮雕火山在干旱的大陆性气候，如土耳其。
One of the main constraints on the use of satellite radar data for monitoring natural hazards is the existence of atmospheric signals. In particular, volcanic deformation can be difficult to identify because atmospheric phase delays can mask or even mimic ground deformation signals. Eliminating atmospheric signals is particularly crucial for high-relief volcanoes such as Ağrı, Tendürek, Acigöl, Göllüdağ and Hasandağ in the Eastern and Central Anatolia. To overcome the atmospheric effects, we use high-resolution ECMWF weather models coupled with an empirical phase-elevation approach for correcting Sentinel-1 interferograms. We apply these methods to two areas of Turkey, the first of which covers three volcanoes in Central Anatolia (Acigöl, Göllüdağ, Hasandağ) between January 2016 and December 2018 and the second covers two volcanoes in Eastern Anatolia (Ağrı, Tendürek) between September 2016 and December 2018. The reduction in standard deviation (quality factor) is calculated for both ascending and descending tracks and the atmospheric corrections are found to perform better on descending interferograms in both cases. Then, we use a least-squares approach to produce a time-series. For Central Anatolia, we used 416 ascending and 415 descending interferograms to create 144 and 145 cumulative displacement maps, respectively, and for Eastern Anatolia, we used 390 ascending and 380 descending interferograms to produce 137 and 130 cumulative displacement maps, respectively. We find that the temporal standard deviation before atmospheric corrections ranges between 0.9 and 3.7 cm for the five volcanoes in the region and is consistently higher on ascending track data, which is acquired at the end of the day when solar heating is greatest. Atmospheric correction reduces the standard deviation to 0.5–2.5 cm. Residual signals might be due to the ice-cap at Ağrı and agriculture near Acigöl. We conclude that these volcanoes did not experience significant magmatic deformation during this time period, despite the apparent signals visible in individual uncorrected interferograms. We demonstrate that atmospheric corrections are vital when using InSAR for monitoring the deformation of high-relief volcanoes in arid continental climates such as Turkey.