NISAR Science Team Meeting - Town Hall and Data Access Webinar

0:01 Speaker 1: So welcome. My name is Paul Rosen.

0:03 Speaker 2: I'm the project scientist for NISAR, and it's been a while since we've had a town hall. We had to miss the last town hall in October because of the government shutdown, and the previous one was before launched. There's a lot that has happened since the last town hall. Thank you all for joining. I do apologize to those online for the late notice that required that you had to rearrange your schedules at the last minute, and for those who are listening to this after the fact on the recorded version of it, I apologize to you for not giving you enough time to coordinate attending.

0:44 Speaker 2: But hopefully you'll get all the information you need about the status of NISAR today, the fantastic products that we're producing, the fantastic products were about to release all of you, and also how to access those through a data access webinar immediately following the town hall, So thank you all for joining. I thought I would hand it over. I'll just show you the agenda here briefly. We'll just start with a very short welcome from me as I've already done, and then hand it over to Torreston Marcus, the NASA Headquarters Program Scientist for NISAR.

1:17 Speaker 2: Then we'll have a brief project status from our deputy project manager, Wendy Edelstein, followed by a product status briefing by Hairesh Fatahi, the algorithm development lead.

1:29 Speaker 1: And then we'll have a.

1:30 Speaker 2: Brief data release plan discussion and Q and A in the remaining time should there be any. Right after that, at twelve thirty to one thirty Pacific time, we will begin the Data Access webinar Frontzmeyer from ASF will be leading that, primarily giving the briefing that there may be others who contribute. So that's the agenda for today. So Turstan, would you like to say a few words?

1:58 Speaker 1: Yeah, thank you, Paul.

1:59 Speaker 3: I if we try to s screen of his works would be pretty easy. And I assume you can see my screen. Yes, all right, perfect, So welcome to the to this town hall. And you know my name is Thruston Marcus. As Paul already said, I'm the new NISA Program Scientist at NASA Headquarters, and I'm assisted by two deputies by Craig Ferguson and Amanda white Person. I think both of them are online as well and adjacent to me or next to me or whatever you want to call it. We have also for NICA a program Applications Lead at NASA Headquarters, and that person is Shannon McLane.

2:46 Speaker 1: Mm hmm.

2:48 Speaker 3: I cannot start to talk about NICA without thanking Gerald Barden and Mitra for their work to help making Nicer what it is. Gerald was the former Nicer Program Scientists through commissioning, and so was Mitra who was the former Nicer Program Executive through commissioning, and then you know, things were handed over to a new PE and a new p PS. These are very exciting times. This is just the phenomenal image which is just extremely beautiful. And this is like a false color image and has mergantires I think is age H and and green is VH polarization.

3:33 Speaker 3: And what it shows it shows crevasses in Antarctica and it's absolutely stunning. And to give you a little bit more context of where this is, it's a it's a couple of ice streams on the near the Emory Ice Shelf in in Antarctica. And you see you know, Antarctica at the lower left there and then you see the Nicer image laid in and then you see the blow up on the right, which I just showed, and it's just stunning, beautingful and imagining that you know, all these little white lines that look like part of an eye are crevassus.

4:10 Speaker 3: And the reason why I'm showing this particular image is because just last week Karen Saint Germain, my boss, or the head of Earth Sciences at NASA, soh this image, this very image is very slight in fact to management, to NASA management. So NYSA is at the forefront of everyone here. It's a big mission, it's a flagship mission, and it's super super exciting. So the other exciting part is that just a few weeks ago that's for the US scientists only, really is an announcement of opportunity came out to write proposals to be on the NISA Data Applications and Research Research and Technology Team.

4:59 Speaker 3: It was formerly known as a science and Application Teams.

5:03 Speaker 1: Now it became a so called DART.

5:05 Speaker 3: The Data Applications, Research and Technology Team did this announcement that is on the street. You can read it, you can look at it, and hopefully you write proposals because we really want to maximize the science and the applications that is coming out of an isan. This is a two step proposal process, and the reason is we want to be more efficient, want to reduce the burden for proposals as well as for the review panels. So in step one we only requested three page short you know, synopsis of what you plan to propose.

5:41 Speaker 3: We will send you a discouragement or encouragement to write a full proposal, and then you know, you can write full the full proposals. Just a few comments about this. As Paul already announced and as you will see throughout you know this town hall, a large set of nicer data will be made publicly available to support proposal development, and you know we will talk more about it as a data access webinar. There was some some people already went in onto inspires and looked at the cover page and see and then then you know, try to figure out how to do submit my three pager.

6:22 Speaker 3: There was some confusion about the program specific data on the endspier's cover page and that is modified and that should be all clarified. It's probably already revised by now, if if not, it will be sometime this afternoon. If you do not plan to submit a proposal, but are willing to be a reviewer of proposals. Please volunteer. We always need proposals. This is a big car and so we always need uh, you know, panelists to help assess assess all the We'll put the as I said here, I will put the link into the chat in just a second, So I don't want to take much time.

7:08 Speaker 3: I'm just a bureaucrat. NICA is a flagship mission at exhilarating times. It truly is. It's a truly, you know, multidisciplinary mission. We should talk so much about system signs et cetera, Earth system signs, and nica's right there in the middle of it being a truly multidisciplinary mission. It's also the first mission where the data are archived and distributed slowly in the cloud environment. This is you know, challenging for us, but it also provides new opportunities. People don't need a supercomputer to work on the data, and they don't need to download terabytes of data.

7:46 Speaker 3: You basically have all the data, all the nicer data, at your fingertips. And they're not only nicer data. As we move, as NASA moves more and more data into your cloud environment, and so does EISA, you pretty much have all the data from all missions at your fingertips without needing a monster computer.

8:06 Speaker 4: So this.

8:08 Speaker 3: Having the data in archivet and distributed in the cloud environment and doing science in the cloud environment will transform the way we do science.

8:17 Speaker 1: And similarly, you know, we.

8:20 Speaker 3: Are embracing open science and open source science, and this will be transforming the way we will collaborate. It will transform scientific progress. We do not need to reinvent the reel anymore because if somebody has solved something or has learned how to read in data or to analyze data in a specific way, has written a paper about it, not only will the paper be available, but also the data and the code will be available as well. So I think it will really transform, you know, as I said before, a progress and collaboration.

8:53 Speaker 3: And then the other thing is artificial intelligent and intelligent and machine learning is becoming. You know, we will see how this will in the next you know, decade or so, we'll transform our science. And NISA is right there in the middle of it, as I said, as a flagship mission, being part of this whole change and transformation of science. And that's really all I wanted to say real quick. I don't want to take too much of your time because NISA is very exciting and people want to see data. I want to see more interesting things.

9:29 Speaker 3: Thank you, Paul, great, Thank you so much.

9:33 Speaker 2: Torsten, very inspirational and I think we're all looking forward to hearing more about the mission and the products today. And we'll circle back to you at the end in the Q and A before we go onto the data access webinar.

9:47 Speaker 1: Thank you certainly.

9:49 Speaker 2: Thank you all right, So next up we will have a project status from Wendy Edelstein.

10:02 Speaker 5: Good afternoon. I'm Wendy Ettlesey and the deputy project manager for NISAR, and it's my pleasure to be here. It is a very exciting time. I've been on this project for a long time, over ten years, and so it's great to be at this position. So I wanted to give you a summary of the last time, as Paul said, is before launch. So I wanted to at least remind everyone you know that we launched successfully, a spectacular launch in July thirtieth, twenty twenty five. Many of you were there in person, some of you weren't, but as you can see that it had the full contingent, it had VIPs from NASA, had the science team and the project team.

10:41 Speaker 5: It was a really exciting time. We also had the Joint Operations team both JPL at JPL and at Israel's. Yeah, so there was a team up at out at Istrak which is the mission operations facility in Bangalore, and we also had a team at JPL. We had the successful deployment of the antenna, which was a really important part of the first early phase of commissioning. That happened on August fifteenth, and many of you have may have not seen the picture on the far right, but that is an actual photo image photograph taken in space from the Worldview satellite part of viaconcon via Core satellite that was actually taken of the Nice satellite shortly after the intenna deployment.

11:28 Speaker 5: That we got the image on the twenty fifth in October, but I think the actual image was taken just after the deployment, so it was actually a very cool verification that the system deployed as expected. So then you know, that was the beginning of commissioning. We went through a series of activities to check out the spacecraft, the payloads, get our into our orbit, science reference orbit, do the calibration of the intent, all that happened again in the commissioning period. We ended our commissioning with a celebratory activity in India.

11:59 Speaker 5: It was called the Nice Our one hundred Day event. It was sponsored by a variety of programmatic and technical folks, including the science team, and this was just a way to celebrate the first hundred days in orbit. It was also the opportunity to release the formally release the first images of the LSR and the SR image data. So that was an exciting time. And then once we got to this point, we're kind of not completely done with commissioning, but we were mostly done. So here's our project status.

12:31 Speaker 5: So since that time, since early November, we've been in the science reference orbit. We've been operating our routine science using our daily observation plans. We had our post launch Assessive Assessment Review called PILAR. That was our official NASA gate to say hey, you can move forward to the science phase. You're done with commissioning. That happened on December fourth, and then we officially transitioned into our calval period into the science phase at the end of December December two, so essentially the beginning of this year, the spacecraft and all and all the payloads are healthy, they're operating nominally.

13:09 Speaker 5: The spacecraft resources have been.

13:13 Speaker 6: Nominal.

13:14 Speaker 5: There's been no degradation or anything unexpected. The maneuver has been phenomenal. The navigation team has done a great time with the orbit maneuvers and we have been staying in the orbit diamond one hundred percent of the time. They've also calculated that it's probably probably about fifteen years of propellant left, so if we continue on at this rate, about fifteen years of propellant. The LSR itself is the temperatures and voltages are nominal. They've collected over fourteen and eighty hours of data so far as of last week, and the SDS has been processing and delivering all the data through the cloud products to the ASF and the JACK.

13:55 Speaker 5: They've exceeded their thirty five tier bits of data every day. The YES has produced over seven hundred and fifty thousand images and I think you all know that in January a sample set of products was delivered to the public so that you can start understanding how to use the data and prepare for the next bigger release. And then THEDS team have made a lot of different improvements to their ground processing algorithms and the processor so that the science data is ready to be released and that they're preparing for the full production.

14:31 Speaker 5: So looking ahead, and I know Paul will talk about this when he at the end here, but just wanted to say, we're now that the calval phase is coming to a completion at the end of May, and next week or so, or maybe this week, very soon we're going to be releasing the first one hundred thousand images or granules to the community to support that ROSES call that you just heard about. And then in June, we'll be preparing to move forward with full low latency public distribution of all the global data so that you can all have all of it all the time.

15:06 Speaker 5: And then finally there's going to be a reprocessing activity starting in around September October timeframe that will be reprocessing all the data that they've gotten since October of twenty twenty five, since we started just when we finish commissioning activities until till June, when we have all the updates in our processors built in, so that will be a reprocessing effort. So that's what's to come. I'll hand it over, but thank you very much. I'm really excited about you know what nice hours done and you know how beautiful the results are and I can't wait to see what.

15:40 Speaker 4: Kind of breakthroughs it makes.

15:41 Speaker 5: Thank you very much.

15:47 Speaker 1: Thank you, Wendy. Very great to hear. It's too bad we don't have two.

15:52 Speaker 2: Of those reflectors, but that's okay, we'll live with it, okay. Next up is Harashmatahi to talk about the products, and this is your presentation.

16:10 Speaker 1: Hopefully that's sharing.

16:14 Speaker 6: Okay, all right, well everybody, I'm representing the algorithm team and the project for giving you a status and the where we are with the ls R science products, so for for supporting the roses that Paul and Thurstan mentioned as well as Wendy. Our science team identified a collection of the targets that they want to use for colveral activities. We have intersected those with the observations database and we have selected around for for one thousand raw data observations. As you see on the right side, that tells you the heat map of the r clcs that we have we are about to release very soon, and Paul, we'll talk about the schedule there from ascending and descending, so a lot of data is coming more than half a petabyte data is processed ready to go more than one hundred thousand granules.

17:26 Speaker 6: Just a reminder that the the besides the raw data, we are of course producing a lot of different products. The ranged after single or complex, the traditional imagery is there. I wanted to remind the user community that we are operating in two many different modes. The constant PRF which you see on the left side is used for small percentage of the observations. Wherever that we have quad hole and the majority of the observation is their PRF which you see on the right side. So the constant PRF you may end up with gaps in the data.

18:02 Speaker 6: And that's the characteristic capture data sets

18:08 Speaker 6: for this release that is coming, we have processed, as I said, more than one hundred thousand granules. Here is a mosaic of the cycle eight of the backs cutter images for this release. It is definitely spectacular that we see this mosaic coming together. Even though the calibration is not fully done. The antenna pattern correction is not still in place, and a few other calibration activities is going on as we are still in the middle of the calvall. However, from this mosaic. It confirms that the system is robust and without any adjustment really frame to frame or track to track.

18:51 Speaker 6: The backscutter's uniform represents what we would have expected over this region. The of the focusing looking at the corner reflectors is very satisfactory. We already have the common delay for geolocation in place. That's a rough estimate, but already has gotten us very close to almost perfect geolocation. For forty megahers we see an average around one meter geolocation errors, five meters for twenty megahers data and fifteen meters for five macare data. So for next releases we will account for those as well and the geolocation will get better.

19:36 Speaker 6: Looking at the focusing quality ISLR and PSLR is very satisfactory, and the azmolocation is really great. Looking at the radiometry and looking at the basically measured RCS versus predicted the upscull factor over different corner reflectors in Oklahoma, lask UH, and Rosamond. We see very interestingly that over of course, over Alaska, which is the more scattered on the right side, the imosphere is giving us a hard time. Amosphere is very high and very active right now. That that definitely impacts the focusing.

20:19 Speaker 6: Over Rosamond, we don't have a wide range of elevation to look at elevation angles. Therefore, you see that it's very less less scattered. Over Oklahoma, which is our main calibration site for the corner reflectors, we see very small variation of one to two TB. You see an outlier around minus four over there. That's because they are actually in the outside of the fully focused data. So this is without antenna pattern correction. The variation is about what we expect. This is this is good news for all of us.

21:00 Speaker 6: Nice are they?

21:02 Speaker 4: Also?

21:02 Speaker 6: Our instrument has received only pulses and that allows us to estimate the power of the noise of the system that that comes basically operationally. For these data sets that we are about to release, we took a look at how how is that performing? Very satisfactory for most of the moods that we have five maguers to any four dmagahs, they are roughly around minus twenty eight minus twenty nine dB noise power, which is great. Seventy seven megahers is slightly higher. That is expected to some good extent.

21:37 Speaker 6: Over all this and our we have we are we are discussing within the project to improve the s an R for seventy seven megaherts. Further, all right, what are you guys gonna get Besides the raw data you're gonna get, as I said, arranged after single or complex imagery r SLC, you're gonna get geo coded a SALC and geocodeed covariance. So geocoded the SALTC is just simply the geo coded version of the SELC imagery the postings depending on the mode for our SELC, you see that usually it's five meters five meters in asimoth and in range it depends on the bandwidth we have it from around one and a half meters to twenty five meters depending on the modes.

22:24 Speaker 6: For geocoded. The SALC we have comparable to the r SLC, but that's not anymore in range doubler. It's on the X and y or coordinates of the projection system, which is either UTM or polar Stereographic and geocodeed covariance is the product that is going to have a lot of users in the application community because this is already corrected for the topography and terrain packs. Cutter is removed and as you see in this figure, hopefully that shows that the topography is removed. Looking at the g COOV for the Walpole data for this data release, we have the coverage that you seeing this plot and if we're zooming over US and India again similar to the previous mosaica that I showed very nicely and very uniform.

23:19 Speaker 6: What may stand out to many of you are those bright dots and yes they are radio frequency interference. So one thing that I would like the users to start getting used to is yes, we are operating an elebent radar and that that definitely increases the possibility of seeing RFI. We have a plan to deal with that, and I have one slide at least on that one, the geo coded unwrapped unwrapped interfrogram that is made globally over solid earth and chrios field regions. The product is really comprehensive.

23:58 Speaker 6: It's not only the phase but also interformetric coherence in an stf FI file the wrapped and unwrapped layers. We have anospheric phase in the layer as well. In the same product, we have tropospherical layer from CMWF solid earth tide and comprehensive metadata. They are produced at eighty meter posting and ground for this release. Again, if you look at the mosaic of the interfrometric coherence, it is very promising because the coherence looks about what we would have expected for this system. It's high in middle latitudes over texas I was looking, it's around zero point eighty five.

24:45 Speaker 6: As you go along to higher latitudes, yes, it decreases because of the precipitation and significant atmosphere activity these days. You see of course water bodies and tain rages and vegetation. I'm sure many of you are aware how impacts coherence and that all makes sense. So overall this is good news and confirms the quality of the products. As I already mentioned, we are at the high peak of ionospheric activities. Going forward, it should calm down and come down, but right now it's high. And if we look at these products that we are about to release.

25:29 Speaker 6: This is just one example somewhere in Africa, around a few thousand kilometer long. The top is interfrometry. It's just inter program itself. At the second plot is the estimated amospheric phase. So as you see majority of the phase that we see here is really a inosphere, probably more than ninety five percent, and we have been able to successfully estimate it at these long wavelengths. Another example again firms that the intraformetric phase is heavily heavily dominated by ionosphere. We would like to remind the users and get your attention that we are still doing cal well.

26:13 Speaker 6: There are caveats in the data. The anosphetic phase seems very robust at long wavelengths, but zooming in and looking at the details, there are artifacts in the data in the layers of the ionosphere that some of it, most of it is really known to us, and we have plans to improve. There is subswats, There is valid data mask in the input products that needs to be improved. I have one slight anta. There is r AFI that makes the phase noisier and that amplifies when you do anospheric phase estimation. That's another sort of artifact.

26:50 Speaker 6: There is the correlation itself, so all those limitations may result into artifacts in the ionospheric phase layer. So users needs to pay attention enough. Of course, the filtering. Unfortunately, the dimension of the filtering is not appropriate for the posting that we have too.

27:10 Speaker 4: Late to fix that.

27:11 Speaker 6: One for this release, but we will we will make that very clear in the release notes. So those smaller streaks as in aligned with range direction is actually filter filtering artifacts. We have products also over Cressfield regions, Antarctica and Greenland. Again, atmosphere is high. Over there is not only high, but the main challenge that is significantly variable and that shows up as streaks in the atmosphere in the coherence makes ins are a little bit more difficult, but still there is a lot of interesting signal to to look at in the inter release products in both interfrometry as well as remember that for for cryosphere regions, not over the entire globe, but for Chrissield regions, we have pixel offset products.

28:06 Speaker 6: We call it range doubler offsets are off and geocoded version of those which is geocoded offsets. Here I'm showing one example that the slant range offsets and long track offsets overlaid on an existing velocity field from chreosphere colleagues nicely shows that how the range offsets on the right side the top row basically captures the velocity of the ice sheets and of course the asimus offsets are impacted by the atmosphere. Solomasture product is the only Level three product that the project is making.

28:43 Speaker 6: Our science team have been very busy to make this product work. The colval is not done, but already we are seeing really exciting examples of how the product eventually would look like. Here is one from my science color. On the left is what ins A what nice are did and on the right side is SMAP and the two are very consistent. So this is really exciting that eventually solve monsture product.

29:14 Speaker 4: Will get there.

29:16 Speaker 6: Here's another example of the sol moisture. I believe this is an animation if it would work. Basically it shows that how zoom into some of the sol measure products shows that how the irrigation is captured. Actually with this product already, so this is very exciting. But again disclaimer, this product is under heavy calibration right now. The team is are doing their best to to improve the product and did recommendation from science team is to focus on the top level baseline sol moisture layer in the product.

29:54 Speaker 6: All right, some of the issues that I would like at least a couple to highlight. Again, we are doing calvoll. The valid mask in the data is not one hundred percent valid itself. So what do I mean by that. If you look at the top left plot that's an our sel C plot, you see at the edges we have dark regions, which means that the partially focused data and if we have masks coming with the data, which is supposed to mask out those dark regions, but unfortunately right now with the release products, that that mask is not correct.

30:33 Speaker 6: Of course, the edhed case is understood and we already have fix in place for future release. So that's something for you in the community. If you are using these products to be aware of RFI, you will see it in the products. So here is one example in the release that we are about to make. The RFI is not mitigated, so you will see RFI in the data. Of course, the project has been in investing in mitigating our of FI in the last few years and we are making good progress. Here is example of the progress.

31:07 Speaker 6: The backscutter that you see high power URIFI after mitigation and the I'm sorry I don't have labels, but basically the high power URIFI and then after medication is on the right side, significantly improved, low power URIFI and again significantly improved after correction, but again the products are not corrected for URFI, and of course it impacts interfrometry as well. There is one insur inter program that has RFI in it and very noisy. After our FIE mitigation, it is improved significantly, So that's something to come later.

31:43 Speaker 6: And some disclaimers. I don't know, Paul how much I have time, but probably too much for you guys to go over it. I just want to make sure that you are all aware that we are again in the middle of the cold wall, and there are caveats with the data, and we had a way. We will document it in a release note. Take a look at them, and we do believe that still with those covees, the products are going to be useful for the community. Thank you,

32:21 Speaker 6: Thank you Harash.

32:22 Speaker 2: Yes, Harash's team has worked very hard and of course they would like to release the data after it's absolutely perfect, but given the call to the community for proposals and the need for the community to look at some data, we felt this was a good point. The data are quite good as they are. There are some caveats as you see here, but I think you'll find them very useful.

32:48 Speaker 1: Did you want to say anything about this. Okay, there is.

32:51 Speaker 2: Going to be a data user God. You're going to hear more about that in the data access in the data access session after this, and that will give you more insights into the issues with the data. All right, so let's go back to the other partition quickly. We are running out of time formally in this session, but it's one contiguous session, so we can just keep moving on.

33:21 Speaker 2: So the data release plan this will go very quickly. So you saw already the table on the left hand side of all the various products product granules that are planned to be released. We're actually discussing with the cryo team about adding a few more to this to give them a little bit more depth in time and in space. And you can see the breakdown in terms of volume for the various products. I actually can't read it on my little screen here, but the by far the largest volume products of the GSLC the geocoded single look complex images and the range Doppler ALC single look complex images.

34:03 Speaker 2: But you can see there's quite a few granules in every category spanning space and time.

34:09 Speaker 1: So it should be.

34:10 Speaker 2: Very helpful for you to be able to create some sample science products for proposals and just.

34:17 Speaker 1: For getting used to the value of these data sets.

34:23 Speaker 2: So we do have on the nice our website already access to a map, an RGIS webmap and a KMZ download that will tell you what is being planned, so all those granules, where they are and what the time depth is in terms of the plan. Since we have just finished the processing, we haven't been able to compare what actually came out of the processor with the plan, but as soon as we do that assessment, we will update this particular website with the actual granules that are there that will allow you to see exactly what you have act us to.

35:00 Speaker 2: And of course the data will be shortly at the Alaska Satellite Facility and you can use the Vertex interface there for accessing it. As you'll hear about in the next in the next hour, so once it's going to take about a week to populate the entire data set at ASF, we'll start sending the data tomorrow and over the next week you'll see the archive filling and the data will be marked as uncalibrated there so you won't confuse it for fully calibrated data. And as Haresh mentioned or actually I think it was I can't remember who mentioned it, but we will have release notes that will describe.

35:46 Speaker 1: These known features that Harash mentioned there.

35:50 Speaker 2: The science team has been meeting for the last couple of days and has been providing feedback and inputs onto what exactly we should say about the characteristics of the data and the data release plan. So that's all I want to say about data release. But I think we should have a few minutes for questions. I know questions have been coming in over the chat, but we can have a few minutes for additional questions.

36:17 Speaker 1: And Tourus doesn't is.

36:18 Speaker 2: On the phone to answer questions about the proposal process and its relation to the data. So I'll just pause as somebody looking, Is there people in the room?

36:30 Speaker 1: I think.

36:32 Speaker 2: Pretty much what's going on? Are there questions online that are coming in? Okay, question about the SPAN data release. So Israel is working hard on s band data. We had a briefing from them in the science team meeting earlier today which showed some very impressive results. The calibration process for the S band system is a little bit more complicated than it is for the L system because they have twice as many tr modules and the actual physical characteristics of those makes the calibration a little bit more challenging.

37:09 Speaker 2: They have their own schedule for the release of data. They've told us that in the next few weeks they'll be releasing some sample products similar to what we released back in January, and then sometime thereafter will be a larger data release, but they haven't specified the schedule for that yet, so just stay.

37:28 Speaker 1: Tuned for that.

37:29 Speaker 2: The place to get those data are at the Bundi console and France will talk about that in the next hour. Okay, The question is are the S and L band data acquired at nearly the same time. The answer to that question is that they are acquired at exactly the same time when we acquire both.

38:00 Speaker 1: Wavelengths.

38:01 Speaker 2: So the observation plan calls for blanket coverage of Indian the surrounding areas, blanket coverage of Antarctica and Greenland on either ascending or descending, and sporadic coverage around the world for calibration, validation sites and other science sites. Whenever we turn on S band, generally speaking, L band is on at the same time in those locations. There are a few places around the world, primarily ocean targets, where it's spand only, but generally speaking it's simultaneous acquisition of LNS men.

38:47 Speaker 4: Yeah.

38:48 Speaker 2: So the answer the question was will data before November twenty twenty.

38:52 Speaker 1: Five be made available? I think the answer is yes. We need to.

38:59 Speaker 2: Discus us how we go about doing that. There was a few technical issues on board before November that makes some of the data not so useful, So obviously we're not going to be releasing those data sets, but other data sets.

39:13 Speaker 1: Will be useful.

39:14 Speaker 2: The nominal release releasable date would be mid October, so it would be an extra thirty days roughly of data that we could add to it. I think the answer to that question is yes. We need to do a full assessment of all the data issues between October and November. So after the calibration phase, we will begin what we call forward processing of the data. That's what Wendy mentioned as a low latency processing. All the acquisitions over the entire land and ice covered surfaces of the Earth, plus the ocean areas that we have in our plan, not the full oceans, but the ocean areas we have in the plan.

40:00 Speaker 2: Those will be forward processed from that point on with the latest available software and placed in the deck within several days. Depend the latency depends on the product, and that will be going forward from that point on. Then after that, at a later time, we'll be reprocessing the data that was acquired from the beginning of the mission up until that forward processing time begins, and the late the cadence is every twelve days. We take data on the ascending and on the descending parts of the orbit, so we get effectively on average, six day sampling of the globe.

40:44 Speaker 2: Everywhere we have observations in our plan. Prediction is always a difficult word. I would say, let's not say that, but certainly so to be a little bit less a little bit more descriptive. We have a twelve day cadence, so natural disasters generally have a faster evolution time than that. So it's very difficult to predict something that is changing rapidly when you only sample it every twelve days. So prediction is not an easy thing to do with a single satellite. If you don't see it in the plan that's on the web, then it will not be released before the step two proposal phase.

41:48 Speaker 1: Anything else.

41:56 Speaker 2: We do not have any level one or Level two requirements on snow in particular. We do know that NASA is extremely interested in the potential of NICs are for measuring snow water equivalent. We have people on the team here working on it, and I know the community.

42:14 Speaker 1: Has working groups in this area.

42:16 Speaker 2: So I suspect I mean, maybe Touristen can comment or on that.

42:24 Speaker 1: He's still there, Turston.

42:29 Speaker 3: Yes, I am just trying to find my window here and I'm looking at the Chad.

42:33 Speaker 1: Yeah.

42:33 Speaker 3: No, you know, snow later of super interest to the community and to call it wide open in a way for the nice the Nice and Science team or DOT team call.

42:46 Speaker 1: Thank you. Mm hmm.

42:49 Speaker 2: Maybe one or two more questions. Yes, So the data is the question is can proposals focus on India. I don't want to speak for NASA, but the data sets are going to be global data sets. There will be many over India. So if the science calls on studying India, I would guess there would be those kinds of proposals would be welcome. Tourstin Anny, Yeah, I mean.

43:42 Speaker 3: We evaluate a panel will evaluate a scientific merit of any proposal. It's not just United States.

43:51 Speaker 2: Correct, thank you, not correct, but you know what I mean, That's what I expected.

43:57 Speaker 1: The answer to me, thank you.

44:00 Speaker 2: What we want more in the regional.

44:10 Speaker 1: That's a good question.

44:11 Speaker 2: Most of the ones that we've identified as large blobs of RFI seem to be FAA airport radars.

44:21 Speaker 1: We have not looked at weather radars.

44:22 Speaker 2: The frequencies of weather radars tend to be different from LBAN, so I'm not sure that they would interact with our our system. Okay, that's good. For questions, this link will be open. You can keep putting them in the chat and we'll answer them as time goes on during the data access webinar. So I'll hand it over now to Franzmeyer, who will talk about the data access Okay.

44:50 Speaker 4: So I know now that data are going to be coming. You're all clamoring to find out how to get your hands on these data sets. So this where presentation is going to walk you through a few items. First of all, the main ones that I'm going to talk about are items two, three, and four, which is how to find and access nice, nicer data sets at various resources where they are available, search clients, et cetera. And how to do it through a graphical user interface and through command line, and then also where to work with data sets and how to work.

45:25 Speaker 7: With these data sets.

45:29 Speaker 4: And I'll start out also talking about a Nicer Data user Guide, which was mentioned a few times already. This is a really handy resource that's available to you that summarizes most of what's in this talk today, but will also in the future give you updates to what's available right now. So as toolkits around nice are growing over time, the Nicer Data User Guide will capture these new developments that make them available to you. So maybe I'll start with that real quick, so please if you can, if you are at your browser, bookmark this page.

46:08 Speaker 4: Nicerdocs dot ASF, dot Alaska dot edu can also be found following this QR code. I should also mention these slides will be made available after the talk, so the links that are embedded there are also useful for you when you just go to the PDF of the slide deck. The Nicer Data User Guide is put together by the Nicer Project in collaboration with ASF, and highlights tools and services developed by those two teams, but also stuff that's available in the broader community and is meant to be sort of the one stop shop for nicer data access and usage, but also a growing sort of resource, a living document that will grow over time, and we will add new information to this user guide as time goes on.

47:00 Speaker 4: So bookmark this page. I think it's going to come in handy down the road. It's going to tell you something about NISA in general, what data products are available, where you can find the data you know, what tools are available to work with the data set, and so on.

47:17 Speaker 4: So the first topic also covered in the User Guy that I want to talk through is how can you find and access NISER data sets now and how you will be able to access them in the future. We have somebody that's trying to do full screen awesome now you should all be seeing it full screen. So what I'm going to walk you through is three different sort of access patterns for NISA data. The first one is using map based sort of graphic user interface based searches. There's two services available through NASA Earth Data Search and ASF's Vertex platform that you may have experienced in the past.

47:56 Speaker 4: And I also will talk about Boniti, which is an Israel service that will provide you access to all of the s band data sets from NYSA and also some airband data sets that have ISRAE interest. In addition to these graphical user interfaces, you also have ways to search and discover NISA data sets more programmatically through Python interfaces like a data search and ASEF search and so on. And then lastly, I'm going to talk about direct bucket access. So the NISA data sets that NASA is holding are available in the AWS cloud in a NASA owned storage bucket storage device there.

48:40 Speaker 4: But NASA has worked with the community on making this data set accessible to the community. So if you are interested in working in the cloud and accessing data sets streaming them directly from the bucket, there are some ways to do this, and I'm going to talk about that briefly. So first things first, if you want to access the NASA held NYSER data, you're required to create an Earth Data log in a short edl. This Earth Data Logins give you access to all of NASA data holdings, not just NYSA, but all of the data sets that NASA holds in its archives.

49:21 Speaker 4: It's very easy and free to create an account. It's used to sort of get some information on how data sets are used in track usage. Very simple to create. If you want to create your Earth Data login, there's a QR codes here on the bottom that you can follow, or you can follow this link that's embedded in the document. And again you don't have to do this now. You can click on that link later once you have access to the slide deck. Once you have an account, you can use one of two web based interfaces for searching for nicer data.

49:56 Speaker 4: The first one is Earth Data Search. Will have a short vi here in a sect that walk you through how to find nicer data through Earth Data Search. Earth Data Search is a web application that was developed by the NASA Earth Science Data and Information System or short is this. It allows you to search all of NASA's Earth science data holdings in one unified interface, and so that can have some advantages if you want to find SAR data sets alongside optical images or other data products that you want to use for your research.

50:31 Speaker 4: And so in this slide that follows correct short from ASEF is going to give you a short introduction on how to access data a nicer data through earth Data Search.

50:45 Speaker 4: We play this.

50:48 Speaker 8: Earth Data Search is a web application developed by NASA's Earth Science Data and Information System. It allows users to search, compare, visualized, and access all of NASA's Earth Science Data. Earth Data Search can be found at search dot earth Data dot NASA dot gov. While earth Data Search allows anyone to explore its catalog without authentication, in order to actually download or otherwise access the available data, one must sign in using an earth Data log in account, so.

51:13 Speaker 7: We'll begin there.

51:14 Speaker 8: To sign in, simply click the login button in the upperright corner of the page, and you'll be presented with a screen that allows you to enter your credentials. If you don't already have an earth Data log in account, you may create one by clicking register for a profile and following and provided instructions. Creating an earth Data Login profile is free and provides unified access to NASA's Perth Science Catalog. Now that we've registered or signed in using our earth Data log In credentials, let's go find some nice our data.

51:40 Speaker 7: Earth Data Search is based on.

51:41 Speaker 8: Collections, so assuming that we have a specific nice Our product in mind, it'll help to know the short name for the collection we want. The nice Our user guide includes these values as a handy reference to access that. We'll go to nisardshdocks dot ASF dot Alaska dot edu. Expand the accessing nicear Data section in the table of contents and select Earth Data Search. Here we can see a list of all the various nice art collections available. We'll copy the level three soil moisture collection name, return to Earth Data Search and paste that into the search field.

52:10 Speaker 8: Then we click search and are presented with that specific collection. If we want to know more about the collection, we can click the info icon, which gives us the more detailed description of the products, including temporal and spatial extents, relevant science keywords, and more.

52:24 Speaker 7: Going back one page and.

52:25 Speaker 8: Clicking on the collection itself, we can view a list of granules within that collection. For now, this collection only includes one single granule. Clicking on that granule will zoom to it on the map. Let's go back to the main Earth Data search page one last time. If we want to explore the catalog more organically, we can simply click browse all Earth Science Data and then begin applying filters as needed.

52:45 Speaker 7: There are many ways one could drill down to nice our data.

52:48 Speaker 8: One way is to start by selecting the Alaska Satellite Facility as the provider, and then under the platform category selecting space based platforms than Earth observation satellites, and lastly, nice are itself. This will lead to all the same collections listed in the nice our user guide. If we want to view the granules within a collection, we just click on the collection itself and there we are. Of course, accessing the data is a critical step, so let's take a look at that. Going back to the Level three Soy Moisture collection.

53:15 Speaker 8: In order to download a granule, click on the download icon for that granule, and in the download files dialogue that appears, select the product you want. If you're already signed in, your download will start immediately. If you're not signed in, you'll be prompted to do so, and then your download will continue as requested. In addition to downloading the files directly, you may also notice a second tab on the download dialogue that provides information for AWSS three direct access. Clicking this tab provides useful information such as the appropriate AWS region bucket prefixes and helpful links for making use of this approach.

53:46 Speaker 8: In addition to downloading single granules, earth that a search provides mechanisms for managing multiple downloads in bulk. Be sure to explore all these various access methods to find the one that best fits your needs.

53:59 Speaker 4: You greg for this intro to THEATA search so Earth Data Search has mentioned gives you access to all of NASA's data holdings in one platform. The Alaska Setup Facility also has long operated its own search and discovery interface called Vertex the four Star users. The advantage of first Vertex is that it's streamline for Star focused usage patterns, so in addition to just finding data, it also provides tailored access patterns such as searching by baseline, you know, building an s bus search and so on.

54:35 Speaker 4: It also has bulk download support that's available. It has some handy features that can make you move easily from a web based platform to a Python based search that'll show you in a second. And there's also on demand processing capabilities that are built into Vertex that will be available for NYSAR as time passes. On the QR cotea gets you to the again to the place in the user had handbook that the data use a hand guide where you can find information about Vertex, And on the next slide, Greg is going to give you us give us a little rundown on how to use Vertex and how it's different to a data search.

55:23 Speaker 8: Vertex is the Alaska Satellite Facilities Web based portal for working with ns OUR data as well as other SAR products.

55:29 Speaker 7: Because it is focused on.

55:30 Speaker 8: Our data, ASF is able to breenline and tune vertext to more effective please support the needs of the SAR community. This helps experienced users minimize the time it takes to find the data they need, and also allows ASF to provide guidance to newer users who may need help finding appropriate data products for their use case. Vertex is available at search dot asf Alaska dot edu. It provides several different search features, including geospatial and temporal searches, as well as a variety of nice our specific filters.

56:09 Speaker 8: For this example, we'll be working with the geographic search option. We'll select NICSAR from the dataset menu, and if we want, we can immediately click search to view the latest nice our data.

56:19 Speaker 7: Most likely, though, we'll want to apply more filters.

56:21 Speaker 8: Let's start by constraining our search to a geographic region for clarity. First, I'll clear the search to define an area of interest. I'll start by selecting the type of shape I want to draw. A couple clicks on the map, and we have our region defined. Vertex provides drawing tools for a number of geometry types, and you can upload geospatial files as well. Next, let's take a look at some of the other filters available. We'll click filters next to the search button and that'll open a panel with a number of options.

56:45 Speaker 8: Of course, you'll notice the option to paste in a WKT string or upload a geospatial file at the top.

56:51 Speaker 7: Below that we see the temporal filters.

56:53 Speaker 8: We can apply an overall date range here, and if we want, we can also apply a seasonal filter using this handy wheel that lets us specify a season start and end. This season will be applied in addition to the overall date range if one is defined.

57:05 Speaker 7: Next up, we have the product filters.

57:07 Speaker 8: This is extremely handy if you're looking for a specific type of science product, such as the level two GSLC or g CoV. Multiple selections are allowed, and making no selection here implies all options are included. Following that, we can see a variety of observational filters covering properties such as polarization, flight direction, and more. Same rules apply here. As above, Multiple selections are allowed, and selecting none implies no filtering is applied on that property. Lastly, we have the track in frame filters which allow you to specify tracks and frames you're interested in or all of these filter categories.

57:36 Speaker 8: There's a documentation link that will open our Vertex User Manual to the appropriate section, providing more information about the filters in question. Having applied the filters we want, let's take a look at those search results. Across the bottom of the screen, you'll see three columns. This leftmost column includes a list of scenes. Each of these scenes represents a location in time and may include multiple products depending on your active filters. Selecting the scene from this list will change the information displayed in the other columns.

58:00 Speaker 8: The second column provides more detailed information about the selected search result, such as the track and frame, as well as citation information and a browser image. Additionally, if the scene can be used with the SPASS or Baseline tools, you can click those buttons to explore options for interferometric and time series analysis. Lastly, the right most column provides a list of each of the files associated with this scene. From here, specific files can be downloaded directly or added to the download que for bulk download operations.

58:25 Speaker 8: To download data immediately, just click the download icon next to the file you want. If you already signed in using your Earth Data log in account, the download begin immediately, otherwise you'll be prompted to sign in or register first.

58:36 Speaker 7: If instead, you want to queue the file.

58:38 Speaker 8: For downloading later, click the card icon to add the file to your queue.

58:41 Speaker 1: Queue.

58:42 Speaker 8: Files can be viewed by clicking the downloads icon near the top of the screen.

58:45 Speaker 7: From there, several.

58:46 Speaker 8: Options are available, including our in browser bulk download manager if you're using Chrome. We hope this helps you get started with nice our data through Vertex, and as always, our user support team is standing by to help if you have any questions.

59:00 Speaker 4: Thanks again to Greg for making this video. This was very fast, of course for everybody, but it's worth reminding everybody that the recording of this presentation will be available so you can rewatch this as you go through Vertex and try to find the data sets you're most interested in.

59:19 Speaker 4: So this concludes sort of the NASA based web based services available to discover SAR data sets, but they're also services available and tools available for more programmatic search for folks that'd like to search from command line or are writing Python scripts, et cetera to find data sets a more larger scale and automatically. So there's two different tools available that can use. One of them is a package called earth Access, which is a Python package that somebody else was sharing their documents with us, so Earth Data Searches.

59:57 Speaker 4: That is a Python package that you can use to search for and download or stream NASA's NASA Earth Science data, not just nicear but also nice are We via Python. It is an open source package that is developed by the community and is developing highly active, so there's a lot of development going on right now. So whatever you see now in earth Access, there's going to be more functionality available for NICAR as nicer data sets become more broadly available. It is installable through PIP and Conda and an open source package that's available on guitub and the QR code gets you again to the Nicer Data user Guide with more information on how to use this package.

1:00:49 Speaker 4: On the data use Guide, there is also a link to notebooks and to information to several examples on how you can use earth Data Search to earth access to to discover nicer data sets and work with nicer data sets. There's a box that's highlighted here for now, there's some additional settings that need to be applied to earth Access to streamline the discovery of nicer data. We expect that to change as more nicer data sets become available. Again. For more information, please look at the Nicer Data user Guide to find out how to utilize earth access.

1:01:32 Speaker 4: AF also has a Python package called ASF search, which provides the same features that Greg presented that are available through Vertex through a more command line interface and for a programmatic search that includes of course discovery of data sets, subsetting of your search results, but also things like s bus search and baseline searches that you I talked about earlier. It's very easy to actually move from a Vertex web based search to a Python script. I'm going to show you that on another slide.

1:02:07 Speaker 4: And also ASF search is available via Pipe and Conda for for easy install. And again the QR code gets you to more instructions about to how to work with ASF search on the Nicer Data user Guide. There's also notebooks linked with several common commonly used ways of how people tend to search for data sets and nicer data sets, so check those out. There's some examples in there to help you find for instance, CHICOV products, upset, g COF products and so on. So work through that notebook and look at that notebook for more instructions.

1:02:49 Speaker 4: As mentioned earlier, it is fairly straightforward to move from a web based search within the Vertex client web client and two or more programmatic search using ASEF search. So if you've been on Vertex and you found the data sets that you're interested in, you can follow that those instructions the three steps shown here to export your search as a little Python snippet that you can run on command line to download these data sets via your command command line interface. Lastly, there is also access direct bucket access available two nicer data sets.

1:03:35 Speaker 4: Oh sorry that there's a notebook that helps you understand how you use as search to access data sets directly in the cloud, and also there's a QR code linked to that. There are some examples that are shown here, is like load a single product in Python, load multiple products at once to do and then also load time series of products using ASF search. If you want to work with data sets directly in the cloud, there are also notebooks available that are linked here that show you how the you know what the access patterns are to get yourself going with direct cloud based access and streaming data sets.

1:04:18 Speaker 4: Directly from the AWLS bucket. So these are the resources available through NASA at this current stage. Again as a reminder, as more and more such resources become available, keep checking in in the in the data in the Nicer Data user Guide. Those those resources will be made available and accessible through the user guide to you. Some nicer data sets, especially the spand data sets, will not be available through NASA, but will be available through ISRA and isra's Earth Observation Data Hub Bonniti.

1:05:00 Speaker 4: Boniti gives you access to nicer data sets of course, but a range of optical and radar data sets dating back to nineteen eighty eight through a unified platform and nicer data says here will be made available free and open through Buniti as required by the Open Data Policy of the Indian Space the Indian Space Open Data Policy, So all of SPEN data for NICSAR in some airbent data of Israel interest will be available through Bonniti. Boniti offers a sort of a sequence of different services that can use to explore and work with nicer data sets.

1:05:47 Speaker 4: It starts out with the web based interface for search and discovery that's shown on top. There is an API based search available through Bonniti API that lets use search and discover data sets through command line interface. And then there are services like Visa which allows you to visualize nicer data sets in a web browser, Code Lab which is a Jupiter notebook type setup that sits next to the archive and lets you work with data sets directly at the archive. And then their Geo raster Craft service, which is an on demand service that lets you run pre developed workflows on data sets such as NICAR.

1:06:31 Speaker 4: So you're going to give you a little bit of information on each of these services on the next slides. So first, if you're interested in discovering israel held nicer data sets, I recommend you start with the Nicer Information page that Israel has put together the link on the slide. Again, you will have access to these slides and can follow this link gets you to the starting page which gives you information about NAR, the ocquisition plan and the data policy, the data availability and the latest news for available data through Israel.

1:07:07 Speaker 4: On this page is also a link that then gets you to the web based data access and data search client. So there's a link that's shown down here that gets you to that web based interface and there you will be able to then search for NISA data sets, discover nice data sets and download them. So specifically, folks interested in spend data that's definitely a useful resource, and folks that are interested for the joint mode observations available specifically over India should also try out Buniti as a resource.

1:07:45 Speaker 4: You also will have to authenticate with Buniti similar to NASA. Also, Israe has an authentication service that is being used. So the steps are to first register with the service and then start discoverings nicer data sets through your web based platform. Also on Israel's side, these search clients, the search services that are available through the web based interface are also available through command line through the Boniti API. Also there authentication is required, but then you can search for data sets, subset data sets to the data sets you actually need and want, and then it facilitates data download through the API.

1:08:34 Speaker 4: So that allows you to build discovery of SPN nicer data sets into your more programmatic searches. So in addition to these the search and discovery and download of data sets, there are services are available through ISRAE that allow you to visualize images. So Vista showing you on a left hand side is a way to visualize data sets directly in a browser. There is a URL that can follow on this slide. And then code lab, which is shown on the right is the stupid and notebook platform that allows you to work with data sets directly at the archive without necessary necessitating download of data to your local machine.

1:09:16 Speaker 4: So also here's a link available that you can follow to find out more. So this is how to discover data sets. Maybe a conclude with this one slide on where to work with nicer data. Really, the message hopefully that you got from the previous slides is that NASA and Israel are both interested in meeting you where you are most comfortable. So we are trying to facilitate your work on your local machine by providing very high volume and high bandwidth download capabilities and sophisticated discovery capabilities.

1:09:52 Speaker 4: But we also want to work your facilitate your work in the cloud. If you're interested in migrating your workflows into the cloud. If that's something you're curious about but you don't have a lot of experience with, there's two communities that you can contact for help. The ASF Open Science Lab team can help you with getting started with work moving into the cloud. They provide, similar to what I showed on the previous slide, a Jupiter Hub based environment that sits right next to the archive and is also populated with a lot of already established workflows that may get you started quickly with your work with nyser data.

1:10:33 Speaker 4: Also, I want to mention the NASA openscapes community. Openscapes mission is really to help people jumpstart their migration into the cloud. Linked here is the website for open Scapes with additional information about how they can help you and contact information also on the website. So as you think about potentially migrating into the cloud, these are two communities that you can connect with to help you get used to this idea. Now that you know how to discover data sets, I want to show you a few tools that are available and a few access patterns available that allow you to then work with these data sets for a variety of applications.

1:11:19 Speaker 4: I'm going to start out with reaching out to the GIS community, so there's going to be a few slides on how to work with nicer data sets in QGIS and RGIS. Then we'll migrate more to the community that uses tools like ICE and GMTSR and then to sort of folks that are familiar with Python based data analysis. So first two QGIS, we have a short video I think by Brandy Downs. Is that correct. She's going to walk you through how you can access and visualize and work with nicer data sets in QGIS.

1:11:58 Speaker 9: Hi everyone, I'm Brandy Downs in the nice Our project science team at JPL, and I'm going to walk through a demo of how to load and view two nice Our data products and QGIS. So we'll start with the g code data and then we'll also do the complex value GSLC data product. So QGIS doesn't know how to read the spatial reference information from nice R HDF five files. If you just try to load in a nice Our HGF five file directly into QGIS as is, it will either crash or it will load it to add zero zero long because it doesn't know what the coordinate reference system is.

1:12:35 Speaker 9: So to fix this, we have to tell QGIS to use g Doll's net CDF driver, and there are a couple of ways to do that, but the way that I'll show you have to go to layer AD layer, add roster layer and then find the gCO file and then in this cell, go to the very beginning and just type in net CDF and that just tells QGI use the net CDF driver no matter what the file extension is. So click on AD and then it gives you all of the layers that.

1:13:08 Speaker 4: Can be added.

1:13:10 Speaker 9: So I'm going to choose frequency B because that's a lot smaller than the frequency A data. But typically you would probably want to work with frequency A, but I'm choosing frequency b. Hh AD layers clothes and then if we zoom to the layer, it does look like it's correctly GEO referenced. However, it is quite dark, and so we're just going to adjust the symbology to this cumulative countcut so that it will map the min and max to the second and the ninety eighth percentile of the pixel values. So that will eliminate a lot of the out layers from view.

1:13:48 Speaker 9: So that's it. That's the g COVE data. So next we'll do the GSLC product. QGAS does not have a native way of handling complex valued data, so to get around that, there's a couple of things we can do. You can use g'll translate to extract the amplitude and phase and save them separately to geotips. But if you don't want to save separate files, you can do it this way. So you got to layer AD layer AD roster layer the same way as we did it for the g cove and the GSLC file. Now we need to specify a few additional parameters beyond just the net CDF to the beginning and to the end of the file path, and those are.

1:14:34 Speaker 7: Here listed here.

1:14:36 Speaker 9: So if we want the amplitude data, we need to specify derive subdata set amplitude and then the net CDF driver, and then at the end we need to specify the exact subdata set name. So I'm going to grab this. I'll be that to the beginning, and then to find the subdata set name, I just use ged all info. So I'm already in the direct three where my files are. To git all info all one word based in the file name, and that will print a list of all of the subdata set names. Then you can find what you're looking for, which is frequency bahh.

1:15:16 Speaker 9: And you want to grab everything from the colon onward and that goes at the end of the filepath.

1:15:25 Speaker 4: So add that.

1:15:27 Speaker 9: Close Okay, again that comes up quite dark. So we'll just adjust the symbology.

1:15:38 Speaker 4: And there is.

1:15:39 Speaker 9: The HH amplitude data from the GSLC file. I'll just rename that and then likewise we can add the phase data in the same way. It saved all of the inputs we had already put for the amplitude. So all we have to change is this phase and there's the phase data, so rename that. So we have the g COVEHH data, the GSLC HH amplitude, and the GSLC hhphase.

1:16:18 Speaker 4: Thank you, Brandy. So this covers the usage of QGIS. I'm going to get back to that in a little bit in a few seconds, so stay tuned if you have more interested in QGIS. A lot of the community, at least in the United States and probably also internationally, is a heavy user of RGIS pro, and the nicer data format is supported in RGS pro. Now there was support added in version three point four point zero, so make sure that you're running a version of RGIS that is that or later, so it's available since November of twenty twenty four.

1:16:56 Speaker 4: There's more information if you follow that QR code on the top right. Especially there's a tutorial available that you can follow to work with data sets in rgis pro. It's also linked in this link on this slide. On the next slide, we'll have Heidi Christensen from the Alaska Sellie Facility walk us through usage patterns of nicer data and rgis pro.

1:17:33 Speaker 10: One way to add nicer data to your rgis pro project is to clickly add data menu, select multi dimensional data and navigate to your nice our data set. Click on it to view the variables and select the ones you want to add to your map. I'll add both polarizations as multidimensional rasters.

1:18:01 Speaker 7: Each variable is added.

1:18:02 Speaker 10: As its own layer and you can see the full file name, including the path to that variable. There are many tools for working with imagery that can be used within nyser data sets. For example, you can change the symbology all, select a gray scale and adjusts the stretch.

1:18:35 Speaker 10: You can apply different raster functions, including some raster functions that are specific to SAR. I'll apply a Speckel filter.

1:18:56 Speaker 10: While there are many things that you can do with the HDF five variables, some analysis workflows may require a geotif, or you may find that an easier format to work with. In general, and you can export the variables as geotifs either the original product or if you have applied raster functions and you want to start with that, you can also export.

1:19:19 Speaker 7: That as a raster.

1:19:22 Speaker 10: When you export the data, you have the option to clip it to an area of interest. So I'm going to add that area of interest and I'll export my speckle filtered image be a file name. I'll put it as a TIFF file using the same coordinate system and as the HDF fly variable and setting my clipping geometry to my area of interest, can adjust the symbology and I now have a subset ciotip.

1:20:21 Speaker 4: For my area of interest. Thank you Heidi for this intro to how to use nice data sets in our GIS. So this is for the GIS community and sort of the two big GIS platforms that are around. If you are more a SAR data user and experienced star data user that has worked with open source SAR processing software in the past, I should note that you can use ICE three, which is a JPL released open source SAR focused software package that's of a level. ICE three is like your perfect way to work with nice data sets more because ICE three is the engine behind NYSA.

1:21:07 Speaker 4: All of the data processing, the operational data processing for NICAR is done with ICE three. So it allows you using the software package, allows you to replicate the exact data products you would get from the operational processor, and it allows you to make modifications to that operational workflow. You know, process at a different resolution, use a different DM.

1:21:28 Speaker 1: Et cetera.

1:21:29 Speaker 4: So's it's the perfect way how to customize your data products on your machine using the exact same process that is also behind nicer. In addition to that, another software package, open source software package that the community is familiar with is GMTSR, and this software package is also ready to consume nicer data sets. There have been many examples already to use some of the early release data to create in the paragrams using gm TSAR. So there's a que here that gets you to the website and to a download link and an install link.

1:22:05 Speaker 4: And so please encourage you to also look into GMC GMTSAR as an option.

1:22:13 Speaker 4: Beyond those two open source packages that are partly NASA supported, there's a growing list of additional resources available in the community. A number of the commercial SAR software providers are working on integrating nicer data sets into their solutions, and the project here at JPL has been in communication with Google earth Engine Google and the Google Earth Engine team and discussing their interest in integrating nicer data sets also into ge.

1:22:47 Speaker 4: If you are more familiar with working in Python environments and want to find utilities that let you explore nicer data sets easily through Python, sort ready to use n nice R products in Python. There's some utilities provided by the HDF five group that are listed here, such as ISDHDF, HDF five, HD five and HDF py h five py packages. They allow you to sort of visualize metadata, explore the data content, and do some Python based processing on nicer data sets. Again, there's a QR code here that gets you to the HDF five group website with additional information.

1:23:35 Speaker 4: There's also a visualization service called h five web that allows you to view metadata and raster layers in a web browser. It can read up to about five thousand by five thousand pixel sized data sets, and it can also be instantiated from a Jupiter hub. So if you're using a service like open Science Lab for instance, or others such Jupiter ob services, you can install h five web into your Jupiter lab to visualize data sets there. Lastly, the team at JPR has been working on a nicer driver for g doll that's available now through a separate channel called the nicer Forge channel.

1:24:22 Speaker 4: So there's information on here and how you can install this driver to your local machine, which then makes GDR look like it understands nicer data sets. Natively, there is an effort going on right now to integrate this driver into the official g doll release, which then would make also working with nicer data sets in platforms like q GAS a little more a little easier and streamline that analysis pattern as well. So that the team is working on that integration right now, and we'll let you know on the Data user Guide once that usage pattern and the GED integration is completed.

1:25:07 Speaker 4: JPL is also a couple of other software packages available that you can use with nyser data sets. One of them is a package called Plant, which includes a collection of tools that were developed by JPL for the use with remote sensing data. It was developed with a radar use case in mind, but is broader than radar and can help you work with remote sensing data sets in general. It's meant to take outputs that you get from the project and analyze them further such as subsetting them, mosaching them, applying, applying masks to data sets, et cetera.

1:25:44 Speaker 4: So there's some examples of usage patterns that can use with Plant and the QR code in the corner, as well as the link in the in this slide gets you to the repository where you can download and install Plan from guitub.

1:26:02 Speaker 4: There's also an integration between Plant and ice plant ICE three which is useful for folks that are not as familiar with the with handling data sets in ICE three. ICE three requires a lot of information to know how to process data sets correctly that need to be configured in the configuration configuration file. If you're not as familiar with these configuration files, Plant the Plant ice integration can help you with that. So Plant will help you pre populate these configuration files that make the usage of some nice ICE three utilities a little more straightforward for folks that are not as familiar with ICE three as a package.

1:26:46 Speaker 4: So, as mentioned, there's a currently already a growing number of software tools available that help you work with nicer data sets. We expect the number of tools to expand quickly as more nice, nice data sets are being released, so stay tuned for the Nicer Data use Guide user guide to get the latest and most up to date information on these tools. Lastly, I want to talk about the Acquisition Plan. Paul Rosen already presented this earlier, so there's a web based version of the acquisition plan available built as an RGIS experience.

1:27:24 Speaker 4: So if you follow this QR code or the link underneath it, you get to that website. It will show you what kind of data and what kind of acquisition modes are available in different places of the world once the full release of data sets becomes available, and you can filter then by different acquisition types. In this RGIS webmap, one thing, for instance, you can visualize. You can look at the coverage of spand data. These are the data sets that are specifically available through israe's Booniti platform and you see information here.

1:28:02 Speaker 4: You see various places throughout the world, but heavily the areas of India and around India, the Antarctic and Greenland are covered heavily in s band. That leads me back to a follow up on my earliest slides on the ISRAE data holdings. I shall mention that the Elbent data Israel will hold are reprocessed so they are different slightly than the data sets you get through NASA and our reprocessed to align most optimally with the spend data collects that they are collected with simultaneously, so it's interesting maybe to check out.

1:28:41 Speaker 4: So these data sets will be available through both platforms. Through Vertex are the NASA released alban data sets, and through Bonniti you'll get the Israel released data sets that you can analyze together and compare to compare to each other.

1:29:00 Speaker 4: I want to finish up with some additional information that you might find interesting. First of all, again pointing out and the Nicer Data Use Guide, which is the first QR code you're listed on the bottom. There's also Earth Data Forum, so if you have questions about nicer data access or you know working with nicer data sets in general, please we want to point you to the Earth Data Forum, which is NASA's forum where you can bring your questions. There will be eventually a tab that you can click on that says nicer specifically, so that your question is directed to the right people to answer them.

1:29:40 Speaker 4: But asf and also the JPL team, I'm monitoring UH the Earth Data Forum for your questions related to NISA, and of course ASF AS will be the host and we'll be managing all of the nicer data sets in our user support team at ASF is you know waiting for your question and are giddy to help you out with all your questions about NISAR. So this third QR code gets you to contact information at ASEF and please feel free to direct all your questions toward us. Lastly, there's going to be a slew of upcoming events and training events that will help you more with accessing and working with nicer data sets.

1:30:24 Speaker 4: There's a large list shown on the slide that you can browse through in the recording or in the slide deck that you will be made available to you. So there's a number of events that are coming up. They don't all have dates yet at this point, but again we'll make them available through the use guide. It will be available through the Nicer website once those are announced. So stay tuned for all of these opportunities training opportunities linked to NISA coming up in the coming days and months. And with that, I want to thank you for your attention.

1:30:58 Speaker 4: Again. If you have further questions, please use any of the links that are provided at the end to get in touch. There might be a chance for answering some questions in chat now, and then the recording of this session is going to be made available to you for rewatching. Thank you very much. Do we want to do some questions? Are there any open questions we need to address now? Yes, there will be. It will be identifiable who process the data? Yes? Answer okay, excellent, So most questions were answered, and I thank you for attention, and again don't forget to get in touch if you have further questions.

1:32:07 Speaker 4: In the future. Product the soy moisture product and I'm looking at poor ros and why mensering. This is the only Level three product that is going to be produced by the project. There will be additional Level three products coming through other resources. For instance, the JPL Opera project is going to create a displacement product and I think a vertical landmotion product based on NISAR in addition to the soil moasture product. And there is probably other sources of Level three that will come in the future, provided through different resources.

1:32:51 Speaker 4: On the ATBD notebooks will be made available for open Science lab. There is an effort that's going on to make them more deductical. Deductible is that the right word, make them easier to use and understand for folks that are new tw SAR and we will have trainings on these at b DS. There's some interest in taking some of these workflows and make them turn them into an on demand service that you can just run dependent on funding. So there's broad interest in the community to make those available. So I should repeat those questions.

1:33:44 Speaker 4: So any help for the HG five files files that are very large. Yes, ASF is working on a subsetting service that will be available for nicer data sets to help users that don't need the full frame and don't need the full data volume that the full frame brings. So there will be a subsetting service available in the near future. Yeah, and there are also options through g doll and the earlier presented the planned IC three package, which also can facilitate some of that subsetting. Yeah, and so the wad All Bright, the ASF director, also mentioned that, as you saw in Greg Short's presentation about Vertex, for instance, you don't always have to download the full content of the h G five.

1:34:45 Speaker 4: You can also download individual elements of that data product to reduce download volumes. Okay, well, we'll answer the remaining questions offline and otherwise you can always email us. Thank you very much, Thank.

1:35:07 Speaker 2: You Franz and everybody who put all so much work into putting that presentation together.

1:35:13 Speaker 1: It was very informative.

1:35:14 Speaker 2: And I hope you enjoy the data once they are released starting tomorrow. That concludes this town hall and Data Access webinar. Thank you all for attending online and in person, and we look forward to your feedback once you start looking at these data.

1:35:33 Speaker 1: Thank you and have a good day.