 All right, so Matt already talked a little bit about INSAR, so I work on ground deformation monitoring from remote sensing technique, GPS and INSAR. I tend to call INSAR GPS on steroids because we get very high precision measurements of ground deformation over time. So the way INSAR works is a satellite flies over the earth, send the microwaves and basically measure the precise distance between its orbit and every pixel on the earth within a thwart. So a pixel is about 10 to 30 meter and a thwart can be about 100 kilometer wide. And when the satellite comes back, it does the same measurement, so we can measure very precisely over time how the ground has moved. So why is this important for groundwater monitoring? As Matt mentioned this morning, we are basically looking at changes in pore pressure driven by groundwater extraction, and we can have a compaction that may be elastic in aquifer systems and inelastic in the clay layers, and basically our satellite over time measure these small changes of deformation. And if we integrate many, many interferograms, we can create time series analysis where you can get the map that you're seeing there, where we have the mean deformation for a certain time span for each pixel that's color coded, and then we can track deformations through time, and we can have satellites that measure up to every eight days, also with Cosmo SkyMed. The standard right now is sent in always 12 day repeats. So every 12 day, we can measure very precisely the ground elevation. And what that led to is discovering that we have many places in the world that are experiencing land subsidence due to groundwater extraction. The fastest coastal city that has subsidence is Jakarta, that's subsiding at about 25 centimeter per year since over 15 years. It's not the fastest subsiding city, it's the fastest subsiding coastal city. So Jakarta has lost about four meter of elevation in the past 10 years. The fastest subsiding city is Mexico City at 35 centimeter per year. And we can get these measurements within SAR because we get very high level of precision at millimeter per year of ground deformation, very high spatial resolution, each pixel is about 10 to 30 meter, and we can cover hundreds of thousands of square centimeters because we have basically data of a very large area. We can do more than just looking at ground deformation by combining ground deformation with in-situ data. And this is an example of work that was done in the Silicon Valley where we use groundwater data together with deformation to estimate the storativity of the elastic skeletal specific storage. And because in SAR such as high spatial resolution and high spatial coverage, we can get this parametrization of aquifer system at the scale of an entire aquifer. So we can use the data from the deformation to its interval between wells. And depending on the temporal sampling of the in-sar we can get different kind of resolution. Where we are kind of pushing the method now is that when we have this data set we have a lot of hidden signal. Basically the deformation is the sum of different processes. And we can now use statistical methods to try to extract from this recorded signal what is elastic and what is inelastic and really get at how things change over time and what is recorded in different spatial and temporal settings. One last thing that I wanted to mention is what we've called the in-sar ads. So predicting water head changes from deformation. So what we did there was looking at combining deformation and water data for a certain time span to estimate the storativity or elastic skeletal specific storage. And let's say that we don't have this well measurements for a very long time span. We can use the deformation to predict where the well level would be based on the initial calibration if we're in an elastic setting. And we found that we can predict it at the scale of an entire aquifer with a precision of 70%. So that means that if we can't afford to have well monitoring constantly we can use ground deformation to bridge the gaps. In terms of opportunities I just wanted to point out that we're getting more and more satellites. So we're getting high repeat and global coverage. And most of the satellites now are going to have free and open access data. The big new thing will be NYSAR launched in January 2021 with a 12-day repeat everywhere on Earth with L-Band. We can now use in-sar to track water through an aquifer system and combine it with GPS that looks at surface water and make the link between what we see with surface water GPS and what we see with in-sar in groundwater to kind of get a sense of free charge of aquifer systems. And we can also use in-sar to up sample GRACE data to try to move towards fully remotely sense ground deformation measurements to basically be able to integrate GRACE at the management scale instead of having it at much larger spatial scale. The major challenge we talked about it today is that right now we're looking at changes over time and we don't really have a way to characterize how much water is in the system and how much water we can use. So I think this is still something where we need to move towards using remote sensing data to address this problem for sustainability. Thank you.