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<span style="margin:0px; font-size:12pt; color:rgb(0,0,0)"><b><span style="margin:0px; font-size:14pt"><span style="margin:0px; font-size:12pt; font-family:"Calibri Light","Helvetica Light",sans-serif; box-sizing:border-box"><span style="margin:0px; color:black!important; font-size:16pt">The
many, many eyes in the sky: Remote sensing products and their application to ground failure monitoring and modeling</span><span style="margin:0px; color:black!important">
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<div style="margin:0px; font-size:12pt; color:rgb(0,0,0)"><span style="margin:0px; font-family:"Calibri Light","Helvetica Light",sans-serif">Speaker:</span><span style="margin:0px"><span style="margin:0px; font-family:"Calibri Light","Helvetica Light",sans-serif"><span>
</span></span></span><span style="margin:0px; font-family:"Calibri Light","Helvetica Light",sans-serif"><b>Paula Burgi</b></span><span style="margin:0px; font-family:"Calibri Light","Helvetica Light",sans-serif">,</span><br>
<span style="margin:0px; font-family:"Calibri Light","Helvetica Light",sans-serif"> USGS,</span><span style="margin:0px; font-family:"Calibri Light","Helvetica Light",sans-serif"> GHSC</span></div>
<div style="margin:0px; font-size:12pt; color:rgb(0,0,0)"><span style="margin:0px; font-family:"Calibri Light","Helvetica Light",sans-serif">Location: online/virtual</span><br>
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<span style="margin:0px; font-size:12pt; font-family:"Calibri Light","Helvetica Light",sans-serif">Date/Time: Tuesday (<b>TOMORROW</b>), February 8th, 2022, 10–11am MST</span></div>
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<span style="margin:0px; font-size:12pt; font-family:"Calibri Light","Helvetica Light",sans-serif">Abstract:
</span><span style="color:rgb(0,0,0); font-family:Calibri,Arial,Helvetica,sans-serif; font-size:12pt">With the exponential increase in earth-observing satellites and other remote sensing systems in the last several decades, remote sensing data has provided
unprecedented insight into a wide range of earth properties and processes. But, it can be difficult to sift through this enormous trove of data to find the most relevant or useful data for a particular application. In the first part of this talk, I will give
an overview of the available remote sensing data that is relevant to geologic hazards, and in particular, ground failure. I will discuss the differences between observation systems, including active and passive observation, data gathering schemes, and signal
bandwidth(s), followed by a discussion of the different types of signals we can extract from these observation systems. One such signal is soil moisture, and in the second part of this talk, I will discuss the different methods for extracting soil moisture
information from remote sensing data. I will focus on one type of satellite observation method: Interferometric Synthetic Aperture Radar (InSAR), which is increasingly used by earth scientists for a diverse suite of applications, in large part due to its high
spatial resolution, rapidly growing catalog of imagery, and increasingly open data policies. I present a method to invert a dataset derived from a measure of InSAR data quality, known as coherence, that separates different causes of data quality variation
over time and in hyper-arid regions where little to no vegetation is present. One product of this inversion is a relative soil moisture metric at each data point in time, and I compare this metric with a variety of other remote sensing and data assimilation
soil moisture products over the southern Arabian Peninsula following two extreme rain events in 2018. I also examine the impact soil moisture has on the interferometric phase, impacts of spatial averaging on phase (triplet phase closure), and simultaneously
collected dual polarization data. In the final part of this talk, I will revisit the bigger picture, and discuss the possibility of incorporating remotely-sensed soil moisture products into earthquake-triggered ground failure models.
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<span style="margin:0px; font-size:12pt; font-family:"Calibri Light","Helvetica Light",sans-serif"><span style="margin:0px">Bio:<span> </span></span>Paula Burgi is a Mendenhall Fellow with the USGS Geologic Hazards Science Center in Golden, CO, where she is
working with the ground failure team to help improve earthquake-triggered ground failure models by incorporating remote sensing and other geospatial datasets. She got her PhD from Cornell University in 2021, where her research focused on characterizing the
impact of land surface change (e.g., forest loss, soil moisture change) on InSAR and other remote sensing datasets. Paula got her B.A. in geological sciences and astronomy from Smith College in 2014, followed by two years as a research assistant at the Earth
Observatory of Singapore. There, she focused on re-analyzing industry-collected seismic reflection data characterize fault geometry and gain insight into earthquake hazards in Nepal and Bangladesh. In her free time, Paula likes to partake in all winter-related
activities, admire bugs of all shapes and sizes, and go on food adventures.</span></p>
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<span style="margin:0px"><span style="margin:0px; font-size:12pt; font-family:"Calibri Light","Helvetica Light",sans-serif; color:rgb(50,49,48)">GHSC Seminar Committee:</span><span style="margin:0px; font-size:12pt; color:rgb(50,49,48)"><span style="margin:0px; font-family:"Calibri Light","Helvetica Light",sans-serif"> </span></span><span style="margin:0px; font-size:12pt; font-family:"Calibri Light","Helvetica Light",sans-serif; color:rgb(50,49,48)">Oliver
Boyd <olboyd@usgs.gov>, Josh Rigler <erigler@usgs.gov>, Francis Rengers <frengers@usgs.gov></span></span></p>
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