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

0:08 Speaker 2: while since we've had a town hall. We had to

0:10 Speaker 2: miss the last town hall in October because of the

0:15 Speaker 2: government shutdown, and the previous one was before launched. There's

0:19 Speaker 2: a lot that has happened since the last town hall.

0:23 Speaker 2: Thank you all for joining. I do apologize to those

0:26 Speaker 2: online for the late notice that required that you had

0:30 Speaker 2: to rearrange your schedules at the last minute, and for

0:32 Speaker 2: those who are listening to this after the fact on

0:36 Speaker 2: the recorded version of it, I apologize to you for

0:40 Speaker 2: not giving you enough time to coordinate attending. But hopefully

0:44 Speaker 2: you'll get all the information you need about the status

0:47 Speaker 2: of NISAR today, the fantastic products that we're producing, the

0:51 Speaker 2: fantastic products were about to release all of you, and

0:55 Speaker 2: also how to access those through a data access webinar

0:58 Speaker 2: immediately following the town hall, So thank you all for joining.

1:02 Speaker 2: I thought I would hand it over. I'll just show

1:04 Speaker 2: you the agenda here briefly. We'll just start with a

1:08 Speaker 2: very short welcome from me as I've already done, and

1:11 Speaker 2: then hand it over to Torreston Marcus, the NASA Headquarters Program

1:16 Speaker 2: Scientist for NISAR. Then we'll have a brief project status

1:20 Speaker 2: from our deputy project manager, Wendy Edelstein, followed by a

1:24 Speaker 2: 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

1:34 Speaker 2: the remaining time should there be any. Right after that,

1:38 Speaker 2: at twelve thirty to one thirty Pacific time, we will

1:42 Speaker 2: begin the Data Access webinar Frontzmeyer from ASF will be

1:46 Speaker 2: leading that, primarily giving the briefing that there may be

1:50 Speaker 2: others who contribute. So that's the agenda for today. So Turstan,

1:54 Speaker 2: 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

2:02 Speaker 3: would be pretty easy. And I assume you can see

2:06 Speaker 3: my screen. Yes, all right, perfect, So welcome to the

2:12 Speaker 3: to this town hall. And you know my name is

2:14 Speaker 3: Thruston Marcus. As Paul already said, I'm the new NISA

2:18 Speaker 3: Program Scientist at NASA Headquarters, and I'm assisted by two

2:23 Speaker 3: deputies by Craig Ferguson and Amanda white Person. I think

2:29 Speaker 3: both of them are online as well and adjacent to

2:33 Speaker 3: me or next to me or whatever you want to

2:35 Speaker 3: call it. We have also for NICA a program Applications

2:39 Speaker 3: 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

2:51 Speaker 3: Barden and Mitra for their work to help making Nicer

2:57 Speaker 3: what it is. Gerald was the former Nicer Program Scientists

3:02 Speaker 3: through commissioning, and so was Mitra who was the former

3:06 Speaker 3: Nicer Program Executive through commissioning, and then you know, things

3:10 Speaker 3: were handed over to a new PE and a new

3:13 Speaker 3: p PS. These are very exciting times. This is just

3:19 Speaker 3: the phenomenal image which is just extremely beautiful. And this

3:24 Speaker 3: is like a false color image and has mergantires I

3:28 Speaker 3: think is age H and and green is VH polarization.

3:33 Speaker 3: And what it shows it shows crevasses in Antarctica and

3:38 Speaker 3: it's absolutely stunning. And to give you a little bit

3:41 Speaker 3: more context of where this is, it's a it's a

3:44 Speaker 3: couple of ice streams on the near the Emory Ice

3:47 Speaker 3: Shelf in in Antarctica. And you see you know, Antarctica

3:52 Speaker 3: at the lower left there and then you see the

3:55 Speaker 3: Nicer image laid in and then you see the blow

3:57 Speaker 3: up on the right, which I just showed, and it's

4:00 Speaker 3: just stunning, beautingful and imagining that you know, all these

4:04 Speaker 3: little white lines that look like part of an eye

4:09 Speaker 3: are crevassus. And the reason why I'm showing this particular

4:13 Speaker 3: image is because just last week Karen Saint Germain, my boss,

4:18 Speaker 3: or the head of Earth Sciences at NASA, soh this image,

4:22 Speaker 3: this very image is very slight in fact to management,

4:27 Speaker 3: to NASA management. So NYSA is at the forefront of

4:31 Speaker 3: everyone here. It's a big mission, it's a flagship mission,

4:35 Speaker 3: and it's super super exciting. So the other exciting part

4:41 Speaker 3: is that just a few weeks ago that's for the

4:44 Speaker 3: US scientists only, really is an announcement of opportunity came

4:49 Speaker 3: out to write proposals to be on the NISA Data

4:56 Speaker 3: Applications and Research Research and Technology Team. It was formerly

5:00 Speaker 3: 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

5:10 Speaker 3: that is on the street. You can read it, you

5:13 Speaker 3: can look at it, and hopefully you write proposals because

5:16 Speaker 3: we really want to maximize the science and the applications

5:20 Speaker 3: that is coming out of an isan. This is a

5:24 Speaker 3: two step proposal process, and the reason is we want

5:27 Speaker 3: to be more efficient, want to reduce the burden for

5:30 Speaker 3: proposals as well as for the review panels. So in

5:35 Speaker 3: step one we only requested three page short you know,

5:39 Speaker 3: synopsis of what you plan to propose. We will send

5:42 Speaker 3: you a discouragement or encouragement to write a full proposal,

5:46 Speaker 3: and then you know, you can write full the full proposals.

5:52 Speaker 3: Just a few comments about this. As Paul already announced

5:55 Speaker 3: and as you will see throughout you know this town hall,

6:00 Speaker 3: a large set of nicer data will be made publicly

6:03 Speaker 3: available to support proposal development, and you know we will

6:07 Speaker 3: talk more about it as a data access webinar. There

6:11 Speaker 3: was some some people already went in onto inspires and

6:15 Speaker 3: looked at the cover page and see and then then

6:19 Speaker 3: you know, try to figure out how to do submit

6:21 Speaker 3: my three pager. There was some confusion about the program

6:24 Speaker 3: specific data on the endspier's cover page and that is

6:28 Speaker 3: modified and that should be all clarified. It's probably already

6:33 Speaker 3: revised by now, if if not, it will be sometime

6:39 Speaker 3: this afternoon. If you do not plan to submit a proposal,

6:44 Speaker 3: but are willing to be a reviewer of proposals. Please volunteer.

6:49 Speaker 3: We always need proposals. This is a big car and

6:52 Speaker 3: so we always need uh, you know, panelists to help

6:58 Speaker 3: assess assess all the We'll put the as I said here,

7:02 Speaker 3: I will put the link into the chat in just

7:04 Speaker 3: 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

7:13 Speaker 3: exhilarating times. It truly is. It's a truly, you know,

7:17 Speaker 3: multidisciplinary mission. We should talk so much about system signs

7:20 Speaker 3: et cetera, Earth system signs, and nica's right there in

7:24 Speaker 3: the middle of it being a truly multidisciplinary mission. It's

7:29 Speaker 3: also the first mission where the data are archived and

7:32 Speaker 3: distributed slowly in the cloud environment. This is you know,

7:36 Speaker 3: challenging for us, but it also provides new opportunities. People

7:40 Speaker 3: don't need a supercomputer to work on the data, and

7:43 Speaker 3: they don't need to download terabytes of data. You basically

7:47 Speaker 3: have all the data, all the nicer data, at your fingertips.

7:52 Speaker 3: And they're not only nicer data. As we move, as

7:54 Speaker 3: NASA moves more and more data into your cloud environment,

7:57 Speaker 3: and so does EISA, you pretty much have all the

8:01 Speaker 3: data from all missions at your fingertips without needing a

8:04 Speaker 3: monster computer.

8:06 Speaker 4: So this.

8:08 Speaker 3: Having the data in archivet and distributed in the cloud

8:11 Speaker 3: environment and doing science in the cloud environment will transform

8:15 Speaker 3: 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

8:24 Speaker 3: will be transforming the way we will collaborate. It will

8:27 Speaker 3: transform scientific progress. We do not need to reinvent the

8:32 Speaker 3: reel anymore because if somebody has solved something or has

8:36 Speaker 3: learned how to read in data or to analyze data

8:38 Speaker 3: in a specific way, has written a paper about it,

8:42 Speaker 3: not only will the paper be available, but also the

8:45 Speaker 3: data and the code will be available as well. So

8:47 Speaker 3: I think it will really transform, you know, as I

8:50 Speaker 3: said before, a progress and collaboration. And then the other

8:54 Speaker 3: thing is artificial intelligent and intelligent and machine learning is becoming.

9:00 Speaker 3: You know, we will see how this will in the

9:03 Speaker 3: next you know, decade or so, we'll transform our science.

9:07 Speaker 3: And NISA is right there in the middle of it,

9:11 Speaker 3: as I said, as a flagship mission, being part of

9:13 Speaker 3: this whole change and transformation of science. And that's really

9:19 Speaker 3: all I wanted to say real quick. I don't want

9:21 Speaker 3: to take too much of your time because NISA is

9:24 Speaker 3: very exciting and people want to see data. I want

9:26 Speaker 3: to see more interesting things. Thank you, Paul, great, Thank

9:32 Speaker 3: you so much.

9:33 Speaker 2: Torsten, very inspirational and I think we're all looking forward

9:37 Speaker 2: to hearing more about the mission and the products today.

9:41 Speaker 2: And we'll circle back to you at the end in

9:43 Speaker 2: the Q and A before we go onto the data

9:46 Speaker 2: access webinar.

9:47 Speaker 1: Thank you certainly.

9:49 Speaker 2: Thank you all right, So next up we will have

9:52 Speaker 2: a project status from Wendy Edelstein.

10:02 Speaker 5: Good afternoon. I'm Wendy Ettlesey and the deputy project manager

10:06 Speaker 5: for NISAR, and it's my pleasure to be here. It

10:08 Speaker 5: is a very exciting time. I've been on this project

10:11 Speaker 5: for a long time, over ten years, and so it's

10:14 Speaker 5: great to be at this position. So I wanted to

10:17 Speaker 5: give you a summary of the last time, as Paul said,

10:20 Speaker 5: is before launch. So I wanted to at least remind

10:23 Speaker 5: everyone you know that we launched successfully, a spectacular launch

10:27 Speaker 5: in July thirtieth, twenty twenty five. Many of you were

10:30 Speaker 5: there in person, some of you weren't, but as you

10:32 Speaker 5: can see that it had the full contingent, it had

10:35 Speaker 5: 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

10:44 Speaker 5: Joint Operations team both JPL at JPL and at Israel's. Yeah,

10:48 Speaker 5: so there was a team up at out at Istrak

10:51 Speaker 5: which is the mission operations facility in Bangalore, and we

10:56 Speaker 5: also had a team at JPL. We had the successful

10:59 Speaker 5: deployment of the antenna, which was a really important part

11:02 Speaker 5: of the first early phase of commissioning. That happened on

11:05 Speaker 5: August fifteenth, and many of you have may have not

11:09 Speaker 5: seen the picture on the far right, but that is

11:12 Speaker 5: an actual photo image photograph taken in space from the

11:16 Speaker 5: Worldview satellite part of viaconcon via Core satellite that was

11:23 Speaker 5: 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,

11:31 Speaker 5: but I think the actual image was taken just after

11:34 Speaker 5: the deployment, so it was actually a very cool verification

11:37 Speaker 5: that the system deployed as expected. So then you know,

11:41 Speaker 5: that was the beginning of commissioning. We went through a

11:43 Speaker 5: series of activities to check out the spacecraft, the payloads,

11:47 Speaker 5: get our into our orbit, science reference orbit, do the

11:51 Speaker 5: calibration of the intent, all that happened again in the

11:54 Speaker 5: commissioning period. We ended our commissioning with a celebratory activity

11:58 Speaker 5: in India. It was called the Nice Our one hundred

12:01 Speaker 5: Day event. It was sponsored by a variety of programmatic

12:06 Speaker 5: and technical folks, including the science team, and this was

12:10 Speaker 5: just a way to celebrate the first hundred days in orbit.

12:13 Speaker 5: It was also the opportunity to release the formally release

12:16 Speaker 5: the first images of the LSR and the SR image data.

12:21 Speaker 5: So that was an exciting time. And then once we

12:23 Speaker 5: got to this point, we're kind of not completely done

12:26 Speaker 5: with commissioning, but we were mostly done. So here's our

12:30 Speaker 5: project status. So since that time, since early November, we've

12:35 Speaker 5: been in the science reference orbit. We've been operating our

12:38 Speaker 5: routine science using our daily observation plans. We had our

12:41 Speaker 5: post launch Assessive Assessment Review called PILAR. That was our

12:45 Speaker 5: official NASA gate to say hey, you can move forward

12:47 Speaker 5: to the science phase. You're done with commissioning. That happened

12:51 Speaker 5: on December fourth, and then we officially transitioned into our

12:56 Speaker 5: calval period into the science phase at the end of

12:59 Speaker 5: December December two, so essentially the beginning of this year,

13:04 Speaker 5: the spacecraft and all and all the payloads are healthy,

13:07 Speaker 5: they're operating nominally. 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

13:21 Speaker 5: been phenomenal. The navigation team has done a great time

13:24 Speaker 5: with the orbit maneuvers and we have been staying in

13:26 Speaker 5: the orbit diamond one hundred percent of the time. They've

13:29 Speaker 5: also calculated that it's probably probably about fifteen years of

13:33 Speaker 5: propellant left, so if we continue on at this rate,

13:35 Speaker 5: about fifteen years of propellant. The LSR itself is the

13:39 Speaker 5: temperatures and voltages are nominal. They've collected over fourteen and

13:44 Speaker 5: eighty hours of data so far as of last week,

13:48 Speaker 5: and the SDS has been processing and delivering all the

13:51 Speaker 5: 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.

13:58 Speaker 5: The YES has produced over seven hundred and fifty thousand

14:02 Speaker 5: images and I think you all know that in January

14:07 Speaker 5: a sample set of products was delivered to the public

14:10 Speaker 5: so that you can start understanding how to use the

14:13 Speaker 5: data and prepare for the next bigger release. And then

14:18 Speaker 5: THEDS team have made a lot of different improvements to

14:22 Speaker 5: their ground processing algorithms and the processor so that the

14:26 Speaker 5: science data is ready to be released and that they're

14:29 Speaker 5: preparing for the full production. So looking ahead, and I

14:33 Speaker 5: know Paul will talk about this when he at the

14:36 Speaker 5: end here, but just wanted to say, we're now that

14:38 Speaker 5: the calval phase is coming to a completion at the

14:42 Speaker 5: end of May, and next week or so, or maybe

14:45 Speaker 5: this week, very soon we're going to be releasing the

14:48 Speaker 5: first one hundred thousand images or granules to the community

14:51 Speaker 5: to support that ROSES call that you just heard about.

14:54 Speaker 5: And then in June, we'll be preparing to move forward

14:58 Speaker 5: with full low latency public distribution of all the global

15:03 Speaker 5: data so that you can all have all of it

15:06 Speaker 5: all the time. And then finally there's going to be

15:08 Speaker 5: a reprocessing activity starting in around September October timeframe that

15:14 Speaker 5: will be reprocessing all the data that they've gotten since

15:17 Speaker 5: October of twenty twenty five, since we started just when

15:20 Speaker 5: we finish commissioning activities until till June, when we have

15:25 Speaker 5: all the updates in our processors built in, so that

15:28 Speaker 5: will be a reprocessing effort. So that's what's to come.

15:32 Speaker 5: I'll hand it over, but thank you very much. I'm

15:34 Speaker 5: really excited about you know what nice hours done and

15:36 Speaker 5: you know how beautiful the results are and I can't

15:39 Speaker 5: 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

15:51 Speaker 1: we don't have two.

15:52 Speaker 2: Of those reflectors, but that's okay, we'll live with it, okay.

15:59 Speaker 2: Next up is Harashmatahi to talk about the products, and

16:07 Speaker 2: 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

16:25 Speaker 6: and the project for giving you a status and the

16:28 Speaker 6: where we are with the ls R science products, so

16:35 Speaker 6: for for supporting the roses that Paul and Thurstan mentioned

16:40 Speaker 6: as well as Wendy. Our science team identified a collection

16:46 Speaker 6: of the targets that they want to use for colveral activities.

16:52 Speaker 6: We have intersected those with the observations database and we

16:57 Speaker 6: have selected around for for one thousand raw data observations.

17:04 Speaker 6: As you see on the right side, that tells you

17:07 Speaker 6: the heat map of the r clcs that we have

17:10 Speaker 6: we are about to release very soon, and Paul, we'll

17:12 Speaker 6: talk about the schedule there from ascending and descending, so

17:16 Speaker 6: a lot of data is coming more than half a

17:19 Speaker 6: petabyte data is processed ready to go more than one

17:23 Speaker 6: hundred thousand granules. Just a reminder that the the besides

17:30 Speaker 6: the raw data, we are of course producing a lot

17:33 Speaker 6: of different products. The ranged after single or complex, the

17:36 Speaker 6: traditional imagery is there. I wanted to remind the user

17:40 Speaker 6: community that we are operating in two many different modes.

17:44 Speaker 6: The constant PRF which you see on the left side

17:48 Speaker 6: is used for small percentage of the observations. Wherever that

17:52 Speaker 6: we have quad hole and the majority of the observation

17:55 Speaker 6: is their PRF which you see on the right side.

17:58 Speaker 6: So the constant PRF you may end up with gaps

18:01 Speaker 6: in the data. And that's the characteristic capture data sets

18:08 Speaker 6: for this release that is coming, we have processed, as

18:12 Speaker 6: I said, more than one hundred thousand granules. Here is

18:15 Speaker 6: a mosaic of the cycle eight of the backs cutter

18:19 Speaker 6: images for this release. It is definitely spectacular that we

18:25 Speaker 6: see this mosaic coming together. Even though the calibration is

18:29 Speaker 6: not fully done. The antenna pattern correction is not still

18:33 Speaker 6: in place, and a few other calibration activities is going

18:36 Speaker 6: on as we are still in the middle of the calvall. However,

18:40 Speaker 6: from this mosaic. It confirms that the system is robust

18:45 Speaker 6: and without any adjustment really frame to frame or track

18:50 Speaker 6: to track. The backscutter's uniform represents what we would have

18:55 Speaker 6: expected over this region. The of the focusing looking at

19:01 Speaker 6: the corner reflectors is very satisfactory. We already have the

19:06 Speaker 6: common delay for geolocation in place. That's a rough estimate,

19:12 Speaker 6: but already has gotten us very close to almost perfect geolocation.

19:19 Speaker 6: For forty megahers we see an average around one meter

19:23 Speaker 6: geolocation errors, five meters for twenty megahers data and fifteen

19:28 Speaker 6: meters for five macare data. So for next releases we

19:32 Speaker 6: will account for those as well and the geolocation will

19:35 Speaker 6: get better. Looking at the focusing quality ISLR and PSLR

19:40 Speaker 6: is very satisfactory, and the azmolocation is really great. Looking

19:48 Speaker 6: at the radiometry and looking at the basically measured RCS

19:53 Speaker 6: versus predicted the upscull factor over different corner reflectors in Oklahoma,

19:59 Speaker 6: lask UH, and Rosamond. We see very interestingly that over

20:05 Speaker 6: of course, over Alaska, which is the more scattered on

20:07 Speaker 6: the right side, the imosphere is giving us a hard time.

20:14 Speaker 6: Amosphere is very high and very active right now. That

20:17 Speaker 6: that definitely impacts the focusing. Over Rosamond, we don't have

20:21 Speaker 6: a wide range of elevation to look at elevation angles. Therefore,

20:28 Speaker 6: you see that it's very less less scattered. Over Oklahoma,

20:33 Speaker 6: which is our main calibration site for the corner reflectors,

20:39 Speaker 6: we see very small variation of one to two TB.

20:42 Speaker 6: You see an outlier around minus four over there. That's

20:45 Speaker 6: because they are actually in the outside of the fully

20:49 Speaker 6: focused data. So this is without antenna pattern correction. The

20:53 Speaker 6: variation is about what we expect. This is this is

20:56 Speaker 6: good news for all of us. Nice are they?

21:02 Speaker 4: Also?

21:02 Speaker 6: Our instrument has received only pulses and that allows us

21:06 Speaker 6: to estimate the power of the noise of the system

21:10 Speaker 6: that that comes basically operationally. For these data sets that

21:15 Speaker 6: we are about to release, we took a look at

21:18 Speaker 6: how how is that performing? Very satisfactory for most of

21:22 Speaker 6: the moods that we have five maguers to any four dmagahs,

21:25 Speaker 6: they are roughly around minus twenty eight minus twenty nine

21:29 Speaker 6: dB noise power, which is great. Seventy seven megahers is

21:33 Speaker 6: slightly higher. That is expected to some good extent. Over

21:37 Speaker 6: all this and our we have we are we are

21:40 Speaker 6: discussing within the project to improve the s an R

21:43 Speaker 6: for seventy seven megaherts. Further, all right, what are you

21:48 Speaker 6: guys gonna get Besides the raw data you're gonna get,

21:51 Speaker 6: as I said, arranged after single or complex imagery r SLC,

21:57 Speaker 6: you're gonna get geo coded a SALC and geocodeed covariance.

22:00 Speaker 6: So geocoded the SALTC is just simply the geo coded

22:05 Speaker 6: version of the SELC imagery the postings depending on the

22:10 Speaker 6: mode for our SELC, you see that usually it's five

22:13 Speaker 6: meters five meters in asimoth and in range it depends

22:17 Speaker 6: on the bandwidth we have it from around one and

22:20 Speaker 6: 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,

22:28 Speaker 6: but that's not anymore in range doubler. It's on the

22:32 Speaker 6: X and y or coordinates of the projection system, which

22:37 Speaker 6: is either UTM or polar Stereographic and geocodeed covariance is

22:43 Speaker 6: the product that is going to have a lot of

22:44 Speaker 6: users in the application community because this is already corrected

22:49 Speaker 6: for the topography and terrain packs. Cutter is removed and

22:54 Speaker 6: as you see in this figure, hopefully that shows that

22:57 Speaker 6: the topography is removed. Looking at the g COOV for

23:03 Speaker 6: the Walpole data for this data release, we have the

23:06 Speaker 6: coverage that you seeing this plot and if we're zooming

23:11 Speaker 6: over US and India again similar to the previous mosaica

23:16 Speaker 6: that I showed very nicely and very uniform. What may

23:20 Speaker 6: stand out to many of you are those bright dots

23:24 Speaker 6: and yes they are radio frequency interference. So one thing

23:28 Speaker 6: that I would like the users to start getting used

23:32 Speaker 6: to is yes, we are operating an elebent radar and

23:36 Speaker 6: that that definitely increases the possibility of seeing RFI. We

23:40 Speaker 6: have a plan to deal with that, and I have

23:43 Speaker 6: one slide at least on that one, the geo coded

23:47 Speaker 6: unwrapped unwrapped interfrogram that is made globally over solid earth

23:53 Speaker 6: and chrios field regions. The product is really comprehensive. It's

23:58 Speaker 6: not only the phase but also interformetric coherence in an

24:01 Speaker 6: stf FI file the wrapped and unwrapped layers. We have

24:05 Speaker 6: anospheric phase in the layer as well. In the same product,

24:10 Speaker 6: we have tropospherical layer from CMWF solid earth tide and

24:17 Speaker 6: comprehensive metadata. They are produced at eighty meter posting and

24:20 Speaker 6: ground for this release. Again, if you look at the

24:26 Speaker 6: mosaic of the interfrometric coherence, it is very promising because

24:33 Speaker 6: the coherence looks about what we would have expected for

24:37 Speaker 6: this system. It's high in middle latitudes over texas I

24:43 Speaker 6: was looking, it's around zero point eighty five. As you

24:45 Speaker 6: go along to higher latitudes, yes, it decreases because of

24:50 Speaker 6: the precipitation and significant atmosphere activity these days. You see

24:56 Speaker 6: of course water bodies and tain rages and vegetation. I'm

25:02 Speaker 6: sure many of you are aware how impacts coherence and

25:06 Speaker 6: that all makes sense. So overall this is good news

25:10 Speaker 6: and confirms the quality of the products. As I already mentioned,

25:16 Speaker 6: we are at the high peak of ionospheric activities. Going forward,

25:20 Speaker 6: it should calm down and come down, but right now

25:24 Speaker 6: it's high. And if we look at these products that

25:27 Speaker 6: we are about to release. This is just one example

25:32 Speaker 6: somewhere in Africa, around a few thousand kilometer long. The

25:36 Speaker 6: top is interfrometry. It's just inter program itself. At the

25:41 Speaker 6: second plot is the estimated amospheric phase. So as you

25:45 Speaker 6: see majority of the phase that we see here is

25:48 Speaker 6: really a inosphere, probably more than ninety five percent, and

25:51 Speaker 6: we have been able to successfully estimate it at these

25:55 Speaker 6: long wavelengths. Another example again firms that the intraformetric phase

26:02 Speaker 6: is heavily heavily dominated by ionosphere. We would like to

26:08 Speaker 6: remind the users and get your attention that we are

26:12 Speaker 6: still doing cal well. There are caveats in the data.

26:15 Speaker 6: The anosphetic phase seems very robust at long wavelengths, but

26:20 Speaker 6: zooming in and looking at the details, there are artifacts

26:23 Speaker 6: in the data in the layers of the ionosphere that

26:27 Speaker 6: some of it, most of it is really known to us,

26:29 Speaker 6: and we have plans to improve. There is subswats, There

26:35 Speaker 6: is valid data mask in the input products that needs

26:39 Speaker 6: to be improved. I have one slight anta. There is

26:42 Speaker 6: r AFI that makes the phase noisier and that amplifies

26:46 Speaker 6: 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

26:54 Speaker 6: result into artifacts in the ionospheric phase layer. So users

26:59 Speaker 6: needs to pay attention enough. Of course, the filtering. Unfortunately,

27:03 Speaker 6: the dimension of the filtering is not appropriate for the

27:08 Speaker 6: 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

27:14 Speaker 6: that very clear in the release notes. So those smaller

27:18 Speaker 6: streaks as in aligned with range direction is actually filter

27:23 Speaker 6: filtering artifacts. We have products also over Cressfield regions, Antarctica

27:30 Speaker 6: and Greenland. Again, atmosphere is high. Over there is not

27:37 Speaker 6: only high, but the main challenge that is significantly variable

27:42 Speaker 6: and that shows up as streaks in the atmosphere in

27:46 Speaker 6: the coherence makes ins are a little bit more difficult,

27:50 Speaker 6: but still there is a lot of interesting signal to

27:53 Speaker 6: to look at in the inter release products in both

27:56 Speaker 6: interfrometry as well as remember that for for cryosphere regions,

28:01 Speaker 6: not over the entire globe, but for Chrissield regions, we

28:04 Speaker 6: have pixel offset products. We call it range doubler offsets

28:08 Speaker 6: are off and geocoded version of those which is geocoded offsets.

28:13 Speaker 6: Here I'm showing one example that the slant range offsets

28:17 Speaker 6: and long track offsets overlaid on an existing velocity field

28:22 Speaker 6: from chreosphere colleagues nicely shows that how the range offsets

28:27 Speaker 6: on the right side the top row basically captures the

28:33 Speaker 6: velocity of the ice sheets and of course the asimus

28:35 Speaker 6: offsets are impacted by the atmosphere. Solomasture product is the

28:41 Speaker 6: only Level three product that the project is making. Our

28:44 Speaker 6: science team have been very busy to make this product work.

28:47 Speaker 6: The colval is not done, but already we are seeing

28:50 Speaker 6: really exciting examples of how the product eventually would look like.

28:57 Speaker 6: Here is one from my science color. On the left

29:02 Speaker 6: is what ins A what nice are did and on

29:05 Speaker 6: the right side is SMAP and the two are very consistent.

29:11 Speaker 6: 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

29:19 Speaker 6: is an animation if it would work. Basically it shows

29:23 Speaker 6: that how zoom into some of the sol measure products

29:26 Speaker 6: shows that how the irrigation is captured. Actually with this

29:30 Speaker 6: product already, so this is very exciting. But again disclaimer,

29:34 Speaker 6: this product is under heavy calibration right now. The team

29:39 Speaker 6: is are doing their best to to improve the product

29:43 Speaker 6: and did recommendation from science team is to focus on

29:48 Speaker 6: the top level baseline sol moisture layer in the product.

29:54 Speaker 6: All right, some of the issues that I would like

29:58 Speaker 6: at least a couple to highlight. Again, we are doing calvoll.

30:03 Speaker 6: The valid mask in the data is not one hundred

30:07 Speaker 6: percent valid itself. So what do I mean by that.

30:11 Speaker 6: If you look at the top left plot that's an

30:13 Speaker 6: our sel C plot, you see at the edges we

30:16 Speaker 6: have dark regions, which means that the partially focused data

30:22 Speaker 6: and if we have masks coming with the data, which

30:25 Speaker 6: is supposed to mask out those dark regions, but unfortunately

30:28 Speaker 6: right now with the release products, that that mask is

30:32 Speaker 6: not correct. Of course, the edhed case is understood and

30:35 Speaker 6: we already have fix in place for future release. So

30:39 Speaker 6: that's something for you in the community. If you are

30:42 Speaker 6: using these products to be aware of RFI, you will

30:46 Speaker 6: see it in the products. So here is one example

30:50 Speaker 6: in the release that we are about to make. The

30:53 Speaker 6: RFI is not mitigated, so you will see RFI in

30:56 Speaker 6: the data. Of course, the project has been in investing

31:00 Speaker 6: in mitigating our of FI in the last few years

31:02 Speaker 6: and we are making good progress. Here is example of

31:06 Speaker 6: the progress. The backscutter that you see high power URIFI

31:11 Speaker 6: after mitigation and the I'm sorry I don't have labels,

31:15 Speaker 6: but basically the high power URIFI and then after medication

31:18 Speaker 6: is on the right side, significantly improved, low power URIFI

31:24 Speaker 6: and again significantly improved after correction, but again the products

31:27 Speaker 6: are not corrected for URFI, and of course it impacts

31:31 Speaker 6: interfrometry as well. There is one insur inter program that

31:35 Speaker 6: has RFI in it and very noisy. After our FIE mitigation,

31:39 Speaker 6: 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

31:46 Speaker 6: have time, but probably too much for you guys to

31:50 Speaker 6: go over it. I just want to make sure that

31:52 Speaker 6: you are all aware that we are again in the

31:55 Speaker 6: middle of the cold wall, and there are caveats with

31:58 Speaker 6: the data, and we had a way. We will document

32:02 Speaker 6: it in a release note. Take a look at them,

32:06 Speaker 6: and we do believe that still with those covees, the

32:09 Speaker 6: 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

32:26 Speaker 2: they would like to release the data after it's absolutely perfect,

32:30 Speaker 2: but given the call to the community for proposals and

32:35 Speaker 2: the need for the community to look at some data,

32:37 Speaker 2: we felt this was a good point. The data are

32:40 Speaker 2: quite good as they are. There are some caveats as

32:43 Speaker 2: 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

32:53 Speaker 2: hear more about that in the data access in the

32:57 Speaker 2: data access session after this, and that will give you

33:01 Speaker 2: more insights into the issues with the data. All right,

33:05 Speaker 2: so let's go back to the other partition quickly. We

33:09 Speaker 2: are running out of time formally in this session, but

33:12 Speaker 2: 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.

33:24 Speaker 2: So you saw already the table on the left hand

33:27 Speaker 2: side of all the various products product granules that are

33:31 Speaker 2: planned to be released. We're actually discussing with the cryo

33:35 Speaker 2: team about adding a few more to this to give

33:38 Speaker 2: them a little bit more depth in time and in space.

33:42 Speaker 2: And you can see the breakdown in terms of volume

33:46 Speaker 2: for the various products. I actually can't read it on

33:49 Speaker 2: my little screen here, but the by far the largest

33:52 Speaker 2: volume products of the GSLC the geocoded single look complex

33:57 Speaker 2: 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

34:06 Speaker 2: 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

34:14 Speaker 2: 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

34:26 Speaker 2: access to a map, an RGIS webmap and a KMZ

34:32 Speaker 2: download that will tell you what is being planned, so

34:36 Speaker 2: all those granules, where they are and what the time

34:39 Speaker 2: depth is in terms of the plan. Since we have

34:42 Speaker 2: just finished the processing, we haven't been able to compare

34:45 Speaker 2: what actually came out of the processor with the plan,

34:48 Speaker 2: but as soon as we do that assessment, we will

34:50 Speaker 2: update this particular website with the actual granules that are

34:55 Speaker 2: there that will allow you to see exactly what you

34:59 Speaker 2: have act us to. And of course the data will

35:01 Speaker 2: be shortly at the Alaska Satellite Facility and you can

35:05 Speaker 2: use the Vertex interface there for accessing it. As you'll

35:08 Speaker 2: hear about in the next in the next hour, so

35:14 Speaker 2: once it's going to take about a week to populate

35:17 Speaker 2: the entire data set at ASF, we'll start sending the

35:22 Speaker 2: data tomorrow and over the next week you'll see the

35:27 Speaker 2: archive filling and the data will be marked as uncalibrated

35:32 Speaker 2: there so you won't confuse it for fully calibrated data.

35:36 Speaker 2: And as Haresh mentioned or actually I think it was

35:41 Speaker 2: I can't remember who mentioned it, but we will have

35:43 Speaker 2: 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

35:53 Speaker 2: of days and has been providing feedback and inputs onto

35:57 Speaker 2: what exactly we should say about the characteristics of the

36:00 Speaker 2: data and the data release plan. So that's all I

36:05 Speaker 2: want to say about data release. But I think we

36:07 Speaker 2: should have a few minutes for questions. I know questions

36:12 Speaker 2: have been coming in over the chat, but we can

36:15 Speaker 2: 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

36:23 Speaker 2: and its relation to the data. So I'll just pause

36:28 Speaker 2: 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

36:36 Speaker 2: are coming in? Okay, question about the SPAN data release.

36:44 Speaker 2: So Israel is working hard on s band data. We

36:47 Speaker 2: had a briefing from them in the science team meeting

36:49 Speaker 2: earlier today which showed some very impressive results. The calibration

36:55 Speaker 2: process for the S band system is a little bit

36:58 Speaker 2: more complicated than it is for the L system because

37:01 Speaker 2: they have twice as many tr modules and the actual

37:05 Speaker 2: physical characteristics of those makes the calibration a little bit

37:08 Speaker 2: more challenging. They have their own schedule for the release

37:12 Speaker 2: of data. They've told us that in the next few

37:15 Speaker 2: weeks they'll be releasing some sample products similar to what

37:18 Speaker 2: we released back in January, and then sometime thereafter will

37:23 Speaker 2: be a larger data release, but they haven't specified the

37:26 Speaker 2: 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

37:32 Speaker 2: console and France will talk about that in the next hour. Okay,

37:46 Speaker 2: The question is are the S and L band data

37:49 Speaker 2: acquired at nearly the same time. The answer to that

37:53 Speaker 2: question is that they are acquired at exactly the same

37:56 Speaker 2: time when we acquire both.

38:00 Speaker 1: Wavelengths.

38:01 Speaker 2: So the observation plan calls for blanket coverage of Indian

38:05 Speaker 2: the surrounding areas, blanket coverage of Antarctica and Greenland on

38:11 Speaker 2: either ascending or descending, and sporadic coverage around the world

38:17 Speaker 2: for calibration, validation sites and other science sites. Whenever we

38:21 Speaker 2: turn on S band, generally speaking, L band is on

38:25 Speaker 2: at the same time in those locations. There are a

38:28 Speaker 2: few places around the world, primarily ocean targets, where it's

38:32 Speaker 2: 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

38:52 Speaker 2: twenty twenty.

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

38:56 Speaker 1: We need to.

38:59 Speaker 2: Discus us how we go about doing that. There was

39:02 Speaker 2: a few technical issues on board before November that makes

39:07 Speaker 2: some of the data not so useful, So obviously we're

39:09 Speaker 2: not going to be releasing those data sets, but other

39:12 Speaker 2: data sets.

39:13 Speaker 1: Will be useful.

39:14 Speaker 2: The nominal release releasable date would be mid October, so

39:20 Speaker 2: it would be an extra thirty days roughly of data

39:24 Speaker 2: that we could add to it. I think the answer

39:25 Speaker 2: to that question is yes. We need to do a

39:27 Speaker 2: full assessment of all the data issues between October and November.

39:35 Speaker 2: So after the calibration phase, we will begin what we

39:40 Speaker 2: call forward processing of the data. That's what Wendy mentioned

39:43 Speaker 2: as a low latency processing. All the acquisitions over the

39:49 Speaker 2: entire land and ice covered surfaces of the Earth, plus

39:53 Speaker 2: the ocean areas that we have in our plan, not

39:57 Speaker 2: the full oceans, but the ocean areas we have in

39:59 Speaker 2: the plan. Those will be forward processed from that point

40:04 Speaker 2: on with the latest available software and placed in the

40:07 Speaker 2: deck within several days. Depend the latency depends on the product,

40:12 Speaker 2: and that will be going forward from that point on.

40:16 Speaker 2: Then after that, at a later time, we'll be reprocessing

40:20 Speaker 2: the data that was acquired from the beginning of the

40:23 Speaker 2: mission up until that forward processing time begins, and the

40:29 Speaker 2: late the cadence is every twelve days. We take data

40:32 Speaker 2: on the ascending and on the descending parts of the orbit,

40:37 Speaker 2: so we get effectively on average, six day sampling of

40:42 Speaker 2: the globe. Everywhere we have observations in our plan. Prediction

40:55 Speaker 2: is always a difficult word. I would say, let's not

40:58 Speaker 2: say that, but certainly so to be a little bit

41:04 Speaker 2: less a little bit more descriptive. We have a twelve

41:08 Speaker 2: day cadence, so natural disasters generally have a faster evolution

41:13 Speaker 2: time than that. So it's very difficult to predict something

41:17 Speaker 2: that is changing rapidly when you only sample it every

41:20 Speaker 2: twelve days. So prediction is not an easy thing to

41:24 Speaker 2: do with a single satellite. If you don't see it

41:36 Speaker 2: in the plan that's on the web, then it will

41:40 Speaker 2: 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

41:59 Speaker 2: requirements on snow in particular. We do know that NASA

42:04 Speaker 2: is extremely interested in the potential of NICs are for

42:09 Speaker 2: measuring snow water equivalent. We have people on the team

42:12 Speaker 2: 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

42:20 Speaker 2: 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

42:31 Speaker 3: 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

42:38 Speaker 3: community and to call it wide open in a way

42:41 Speaker 3: for the nice the Nice and Science team or DOT

42:43 Speaker 3: team call.

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

42:49 Speaker 2: Maybe one or two more questions. Yes, So the data

43:18 Speaker 2: is the question is can proposals focus on India. I

43:23 Speaker 2: don't want to speak for NASA, but the data sets

43:25 Speaker 2: are going to be global data sets. There will be

43:27 Speaker 2: many over India. So if the science calls on studying India,

43:32 Speaker 2: I would guess there would be those kinds of proposals

43:38 Speaker 2: would be welcome. Tourstin Anny, Yeah, I mean.

43:42 Speaker 3: We evaluate a panel will evaluate a scientific merit of

43:45 Speaker 3: any proposal. It's not just United States.

43:51 Speaker 2: Correct, thank you, not correct, but you know what I mean,

43:56 Speaker 2: 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

44:16 Speaker 2: 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,

44:25 Speaker 2: so I'm not sure that they would interact with our

44:29 Speaker 2: our system. Okay, that's good. For questions, this link will

44:36 Speaker 2: be open. You can keep putting them in the chat

44:38 Speaker 2: and we'll answer them as time goes on during the

44:40 Speaker 2: data access webinar. So I'll hand it over now to Franzmeyer,

44:45 Speaker 2: who will talk about the data access Okay.

44:50 Speaker 4: So I know now that data are going to be coming.

44:54 Speaker 4: You're all clamoring to find out how to get your

44:57 Speaker 4: hands on these data sets. So this where presentation is

45:00 Speaker 4: going to walk you through a few items. First of all,

45:05 Speaker 4: the main ones that I'm going to talk about are

45:06 Speaker 4: items two, three, and four, which is how to find

45:11 Speaker 4: and access nice, nicer data sets at various resources where

45:14 Speaker 4: they are available, search clients, et cetera. And how to

45:17 Speaker 4: do it through a graphical user interface and through command line,

45:21 Speaker 4: and then also where to work with data sets and

45:25 Speaker 4: 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

45:33 Speaker 4: user Guide, which was mentioned a few times already. This

45:36 Speaker 4: is a really handy resource that's available to you that

45:39 Speaker 4: summarizes most of what's in this talk today, but will

45:43 Speaker 4: also in the future give you updates to what's available

45:47 Speaker 4: right now. So as toolkits around nice are growing over time,

45:52 Speaker 4: the Nicer Data User Guide will capture these new developments

45:57 Speaker 4: that make them available to you. So maybe I'll start

45:59 Speaker 4: with that real quick, so please if you can, if

46:04 Speaker 4: you are at your browser, bookmark this page. Nicerdocs dot ASF,

46:09 Speaker 4: dot Alaska dot edu can also be found following this

46:13 Speaker 4: QR code. I should also mention these slides will be

46:16 Speaker 4: made available after the talk, so the links that are

46:18 Speaker 4: embedded there are also useful for you when you just

46:22 Speaker 4: go to the PDF of the slide deck. The Nicer

46:25 Speaker 4: Data User Guide is put together by the Nicer Project

46:29 Speaker 4: in collaboration with ASF, and highlights tools and services developed

46:34 Speaker 4: by those two teams, but also stuff that's available in

46:37 Speaker 4: the broader community and is meant to be sort of

46:41 Speaker 4: the one stop shop for nicer data access and usage,

46:46 Speaker 4: but also a growing sort of resource, a living document

46:51 Speaker 4: that will grow over time, and we will add new

46:55 Speaker 4: information to this user guide as time goes on. So

47:01 Speaker 4: bookmark this page. I think it's going to come in

47:03 Speaker 4: handy down the road. It's going to tell you something

47:06 Speaker 4: about NISA in general, what data products are available, where

47:09 Speaker 4: you can find the data you know, what tools are

47:12 Speaker 4: available to work with the data set, and so on.

47:17 Speaker 4: So the first topic also covered in the User Guy

47:20 Speaker 4: that I want to talk through is how can you

47:22 Speaker 4: find and access NISER data sets now and how you

47:26 Speaker 4: will be able to access them in the future. We

47:28 Speaker 4: have somebody that's trying to do full screen awesome now

47:32 Speaker 4: you should all be seeing it full screen. So what

47:35 Speaker 4: I'm going to walk you through is three different sort

47:38 Speaker 4: of access patterns for NISA data. The first one is

47:42 Speaker 4: using map based sort of graphic user interface based searches.

47:48 Speaker 4: There's two services available through NASA Earth Data Search and

47:52 Speaker 4: 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

47:59 Speaker 4: Israel service that will provide you access to all of

48:03 Speaker 4: the s band data sets from NYSA and also some

48:07 Speaker 4: airband data sets that have ISRAE interest. In addition to

48:12 Speaker 4: these graphical user interfaces, you also have ways to search

48:17 Speaker 4: and discover NISA data sets more programmatically through Python interfaces

48:21 Speaker 4: like a data search and ASEF search and so on.

48:24 Speaker 4: And then lastly, I'm going to talk about direct bucket access.

48:28 Speaker 4: So the NISA data sets that NASA is holding are

48:32 Speaker 4: available in the AWS cloud in a NASA owned storage

48:38 Speaker 4: bucket storage device there. But NASA has worked with the

48:42 Speaker 4: community on making this data set accessible to the community.

48:45 Speaker 4: So if you are interested in working in the cloud

48:48 Speaker 4: and accessing data sets streaming them directly from the bucket,

48:52 Speaker 4: there are some ways to do this, and I'm going

48:54 Speaker 4: to talk about that briefly. So first things first, if

49:00 Speaker 4: you want to access the NASA held NYSER data, you're

49:06 Speaker 4: required to create an Earth Data log in a short edl.

49:11 Speaker 4: This Earth Data Logins give you access to all of

49:14 Speaker 4: NASA data holdings, not just NYSA, but all of the

49:18 Speaker 4: data sets that NASA holds in its archives. It's very

49:21 Speaker 4: easy and free to create an account. It's used to

49:25 Speaker 4: sort of get some information on how data sets are

49:28 Speaker 4: used in track usage. Very simple to create. If you

49:32 Speaker 4: want to create your Earth Data login, there's a QR

49:36 Speaker 4: codes here on the bottom that you can follow, or

49:39 Speaker 4: you can follow this link that's embedded in the document.

49:42 Speaker 4: And again you don't have to do this now. You

49:44 Speaker 4: can click on that link later once you have access

49:46 Speaker 4: to the slide deck. Once you have an account, you

49:51 Speaker 4: can use one of two web based interfaces for searching

49:55 Speaker 4: for nicer data. The first one is Earth Data Search.

49:59 Speaker 4: Will have a short vi here in a sect that

50:00 Speaker 4: walk you through how to find nicer data through Earth

50:04 Speaker 4: Data Search. Earth Data Search is a web application that

50:08 Speaker 4: was developed by the NASA Earth Science Data and Information

50:12 Speaker 4: System or short is this. It allows you to search

50:17 Speaker 4: all of NASA's Earth science data holdings in one unified interface,

50:23 Speaker 4: and so that can have some advantages if you want

50:25 Speaker 4: to find SAR data sets alongside optical images or other

50:28 Speaker 4: data products that you want to use for your research.

50:31 Speaker 4: And so in this slide that follows correct short from

50:34 Speaker 4: ASEF is going to give you a short introduction on

50:37 Speaker 4: 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

50:51 Speaker 8: Earth Science Data and Information System. It allows users to search, compare, visualized,

50:56 Speaker 8: and access all of NASA's Earth Science Data. Earth Data

50:59 Speaker 8: Search can be found at search dot earth Data dot

51:01 Speaker 8: NASA dot gov. While earth Data Search allows anyone to

51:04 Speaker 8: explore its catalog without authentication, in order to actually download

51:08 Speaker 8: or otherwise access the available data, one must sign in

51:11 Speaker 8: 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

51:16 Speaker 8: upperright corner of the page, and you'll be presented with

51:18 Speaker 8: a screen that allows you to enter your credentials. If

51:21 Speaker 8: you don't already have an earth Data log in account,

51:23 Speaker 8: you may create one by clicking register for a profile

51:26 Speaker 8: and following and provided instructions. Creating an earth Data Login

51:29 Speaker 8: profile is free and provides unified access to NASA's Perth

51:32 Speaker 8: Science Catalog. Now that we've registered or signed in using

51:36 Speaker 8: our earth Data log In credentials, let's go find some

51:38 Speaker 8: 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

51:43 Speaker 8: product in mind, it'll help to know the short name

51:46 Speaker 8: for the collection we want. The nice Our user guide

51:48 Speaker 8: includes these values as a handy reference to access that.

51:51 Speaker 8: We'll go to nisardshdocks dot ASF dot Alaska dot edu.

51:56 Speaker 8: Expand the accessing nicear Data section in the table of

51:59 Speaker 8: contents and select Earth Data Search. Here we can see

52:02 Speaker 8: a list of all the various nice art collections available.

52:05 Speaker 8: We'll copy the level three soil moisture collection name, return

52:07 Speaker 8: 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.

52:14 Speaker 8: If we want to know more about the collection, we

52:16 Speaker 8: can click the info icon, which gives us the more

52:17 Speaker 8: detailed description of the products, including temporal and spatial extents,

52:21 Speaker 8: 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

52:27 Speaker 8: of granules within that collection. For now, this collection only

52:30 Speaker 8: includes one single granule. Clicking on that granule will zoom

52:33 Speaker 8: to it on the map. Let's go back to the

52:35 Speaker 8: main Earth Data search page one last time. If we

52:38 Speaker 8: want to explore the catalog more organically, we can simply

52:41 Speaker 8: click browse all Earth Science Data and then begin applying

52:44 Speaker 8: filters as needed.

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

52:47 Speaker 7: our data.

52:48 Speaker 8: One way is to start by selecting the Alaska Satellite

52:50 Speaker 8: Facility as the provider, and then under the platform category

52:54 Speaker 8: selecting space based platforms than Earth observation satellites, and lastly,

52:58 Speaker 8: nice are itself. This will lead to all the same

53:01 Speaker 8: collections listed in the nice our user guide. If we

53:04 Speaker 8: want to view the granules within a collection, we just

53:06 Speaker 8: click on the collection itself and there we are. Of course,

53:09 Speaker 8: accessing the data is a critical step, so let's take

53:11 Speaker 8: a look at that. Going back to the Level three

53:14 Speaker 8: Soy Moisture collection. In order to download a granule, click

53:17 Speaker 8: on the download icon for that granule, and in the

53:19 Speaker 8: download files dialogue that appears, select the product you want.

53:22 Speaker 8: If you're already signed in, your download will start immediately.

53:25 Speaker 8: If you're not signed in, you'll be prompted to do so,

53:27 Speaker 8: and then your download will continue as requested. In addition

53:30 Speaker 8: to downloading the files directly, you may also notice a

53:33 Speaker 8: second tab on the download dialogue that provides information for

53:35 Speaker 8: AWSS three direct access. Clicking this tab provides useful information

53:40 Speaker 8: such as the appropriate AWS region bucket prefixes and helpful

53:44 Speaker 8: links for making use of this approach. In addition to

53:47 Speaker 8: downloading single granules, earth that a search provides mechanisms for

53:50 Speaker 8: managing multiple downloads in bulk. Be sure to explore all

53:53 Speaker 8: these various access methods to find the one that best

53:55 Speaker 8: fits your needs.

53:59 Speaker 4: You greg for this intro to THEATA search so Earth

54:03 Speaker 4: Data Search has mentioned gives you access to all of

54:06 Speaker 4: NASA's data holdings in one platform. The Alaska Setup Facility

54:11 Speaker 4: also has long operated its own search and discovery interface

54:15 Speaker 4: called Vertex the four Star users. The advantage of first

54:20 Speaker 4: Vertex is that it's streamline for Star focused usage patterns,

54:26 Speaker 4: so in addition to just finding data, it also provides

54:29 Speaker 4: tailored access patterns such as searching by baseline, you know,

54:33 Speaker 4: building an s bus search and so on. It also

54:36 Speaker 4: has bulk download support that's available. It has some handy

54:41 Speaker 4: features that can make you move easily from a web

54:44 Speaker 4: based platform to a Python based search that'll show you

54:48 Speaker 4: in a second. And there's also on demand processing capabilities

54:52 Speaker 4: that are built into Vertex that will be available for

54:57 Speaker 4: NYSAR as time passes. On the QR cotea gets you

55:01 Speaker 4: to the again to the place in the user had

55:06 Speaker 4: handbook that the data use a hand guide where you

55:10 Speaker 4: can find information about Vertex, And on the next slide,

55:13 Speaker 4: Greg is going to give you us give us a

55:15 Speaker 4: little rundown on how to use Vertex and how it's

55:18 Speaker 4: different to a data search.

55:23 Speaker 8: Vertex is the Alaska Satellite Facilities Web based portal for

55:26 Speaker 8: 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

55:35 Speaker 8: to more effective please support the needs of the SAR community.

55:40 Speaker 8: This helps experienced users minimize the time it takes to

55:42 Speaker 8: find the data they need, and also allows ASF to

55:45 Speaker 8: provide guidance to newer users who may need help finding

55:47 Speaker 8: appropriate data products for their use case. Vertex is available

55:51 Speaker 8: at search dot asf Alaska dot edu. It provides several

56:03 Speaker 8: different search features, including geospatial and temporal searches, as well

56:06 Speaker 8: as a variety of nice our specific filters. For this example,

56:10 Speaker 8: we'll be working with the geographic search option. We'll select

56:13 Speaker 8: NICSAR from the dataset menu, and if we want, we

56:15 Speaker 8: 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

56:24 Speaker 8: for clarity. First, I'll clear the search to define an

56:27 Speaker 8: area of interest. I'll start by selecting the type of

56:29 Speaker 8: shape I want to draw. A couple clicks on the map,

56:31 Speaker 8: and we have our region defined. Vertex provides drawing tools

56:35 Speaker 8: for a number of geometry types, and you can upload

56:37 Speaker 8: geospatial files as well. Next, let's take a look at

56:40 Speaker 8: some of the other filters available. We'll click filters next

56:42 Speaker 8: to the search button and that'll open a panel with

56:44 Speaker 8: a number of options. Of course, you'll notice the option

56:47 Speaker 8: to paste in a WKT string or upload a geospatial

56:49 Speaker 8: 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

56:55 Speaker 8: we want, we can also apply a seasonal filter using

56:57 Speaker 8: this handy wheel that lets us specify a season start

57:00 Speaker 8: and end. This season will be applied in addition to

57:02 Speaker 8: 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

57:09 Speaker 8: type of science product, such as the level two GSLC

57:12 Speaker 8: or g CoV. Multiple selections are allowed, and making no

57:14 Speaker 8: selection here implies all options are included. Following that, we

57:18 Speaker 8: can see a variety of observational filters covering properties such

57:21 Speaker 8: as polarization, flight direction, and more. Same rules apply here.

57:24 Speaker 8: As above, Multiple selections are allowed, and selecting none implies

57:27 Speaker 8: no filtering is applied on that property. Lastly, we have

57:30 Speaker 8: the track in frame filters which allow you to specify

57:32 Speaker 8: tracks and frames you're interested in or all of these

57:35 Speaker 8: filter categories. There's a documentation link that will open our

57:38 Speaker 8: Vertex User Manual to the appropriate section, providing more information

57:41 Speaker 8: about the filters in question. Having applied the filters we want,

57:44 Speaker 8: let's take a look at those search results. Across the

57:46 Speaker 8: bottom of the screen, you'll see three columns. This leftmost

57:49 Speaker 8: column includes a list of scenes. Each of these scenes

57:51 Speaker 8: represents a location in time and may include multiple products

57:54 Speaker 8: depending on your active filters. Selecting the scene from this

57:57 Speaker 8: list will change the information displayed in the other columns.

58:00 Speaker 8: The second column provides more detailed information about the selected

58:03 Speaker 8: search result, such as the track and frame, as well

58:05 Speaker 8: as citation information and a browser image. Additionally, if the

58:09 Speaker 8: scene can be used with the SPASS or Baseline tools,

58:11 Speaker 8: you can click those buttons to explore options for interferometric

58:14 Speaker 8: and time series analysis. Lastly, the right most column provides

58:17 Speaker 8: a list of each of the files associated with this scene.

58:20 Speaker 8: From here, specific files can be downloaded directly or added

58:23 Speaker 8: to the download que for bulk download operations. To download

58:26 Speaker 8: data immediately, just click the download icon next to the

58:28 Speaker 8: file you want. If you already signed in using your

58:30 Speaker 8: Earth Data log in account, the download begin immediately, otherwise

58:34 Speaker 8: 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

58:40 Speaker 8: file to your queue.

58:41 Speaker 1: Queue.

58:42 Speaker 8: Files can be viewed by clicking the downloads icon near

58:44 Speaker 8: 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

58:49 Speaker 8: if you're using Chrome. We hope this helps you get

58:52 Speaker 8: started with nice our data through Vertex, and as always,

58:54 Speaker 8: our user support team is standing by to help if

58:56 Speaker 8: you have any questions.

59:00 Speaker 4: Thanks again to Greg for making this video. This was

59:03 Speaker 4: very fast, of course for everybody, but it's worth reminding

59:07 Speaker 4: everybody that the recording of this presentation will be available

59:11 Speaker 4: so you can rewatch this as you go through Vertex

59:14 Speaker 4: 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

59:22 Speaker 4: services available to discover SAR data sets, but they're also

59:28 Speaker 4: services available and tools available for more programmatic search for

59:31 Speaker 4: folks that'd like to search from command line or are

59:34 Speaker 4: writing Python scripts, et cetera to find data sets a

59:38 Speaker 4: more larger scale and automatically. So there's two different tools

59:43 Speaker 4: available that can use. One of them is a package

59:45 Speaker 4: called earth Access, which is a Python package that somebody

59:53 Speaker 4: 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

1:00:01 Speaker 4: search for and download or stream NASA's NASA Earth Science data,

1:00:07 Speaker 4: not just nicear but also nice are We via Python.

1:00:12 Speaker 4: It is an open source package that is developed by

1:00:16 Speaker 4: the community and is developing highly active, so there's a

1:00:20 Speaker 4: lot of development going on right now. So whatever you

1:00:23 Speaker 4: see now in earth Access, there's going to be more

1:00:25 Speaker 4: functionality available for NICAR as nicer data sets become more

1:00:29 Speaker 4: broadly available. It is installable through PIP and Conda and

1:00:36 Speaker 4: an open source package that's available on guitub and the

1:00:39 Speaker 4: QR code gets you again to the Nicer Data user

1:00:43 Speaker 4: 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

1:00:54 Speaker 4: to notebooks and to information to several examples on how

1:00:59 Speaker 4: you can use earth Data Search to earth access to

1:01:03 Speaker 4: to discover nicer data sets and work with nicer data sets.

1:01:08 Speaker 4: There's a box that's highlighted here for now, there's some

1:01:12 Speaker 4: additional settings that need to be applied to earth Access

1:01:16 Speaker 4: to streamline the discovery of nicer data. We expect that

1:01:20 Speaker 4: to change as more nicer data sets become available. Again.

1:01:23 Speaker 4: For more information, please look at the Nicer Data user

1:01:27 Speaker 4: Guide to find out how to utilize earth access. AF

1:01:32 Speaker 4: also has a Python package called ASF search, which provides

1:01:36 Speaker 4: the same features that Greg presented that are available through

1:01:42 Speaker 4: Vertex through a more command line interface and for a

1:01:46 Speaker 4: programmatic search that includes of course discovery of data sets,

1:01:49 Speaker 4: subsetting of your search results, but also things like s

1:01:54 Speaker 4: bus search and baseline searches that you I talked about earlier.

1:02:00 Speaker 4: It's very easy to actually move from a Vertex web

1:02:03 Speaker 4: based search to a Python script. I'm going to show

1:02:06 Speaker 4: you that on another slide. And also ASF search is

1:02:09 Speaker 4: available via Pipe and Conda for for easy install. And

1:02:13 Speaker 4: again the QR code gets you to more instructions about

1:02:17 Speaker 4: to how to work with ASF search on the Nicer

1:02:24 Speaker 4: Data user Guide. There's also notebooks linked with several common

1:02:30 Speaker 4: commonly used ways of how people tend to search for

1:02:33 Speaker 4: data sets and nicer data sets, so check those out.

1:02:37 Speaker 4: There's some examples in there to help you find for instance,

1:02:41 Speaker 4: CHICOV products, upset, g COF products and so on. So

1:02:45 Speaker 4: work through that notebook and look at that notebook for

1:02:48 Speaker 4: more instructions. As mentioned earlier, it is fairly straightforward to

1:02:55 Speaker 4: move from a web based search within the Vertex client

1:02:59 Speaker 4: web client and two or more programmatic search using ASEF search.

1:03:04 Speaker 4: So if you've been on Vertex and you found the

1:03:06 Speaker 4: data sets that you're interested in, you can follow that

1:03:10 Speaker 4: those instructions the three steps shown here to export your

1:03:14 Speaker 4: search as a little Python snippet that you can run

1:03:18 Speaker 4: on command line to download these data sets via your

1:03:22 Speaker 4: command command line interface. Lastly, there is also access direct

1:03:30 Speaker 4: bucket access available two nicer data sets. Oh sorry that

1:03:36 Speaker 4: there's a notebook that helps you understand how you use

1:03:42 Speaker 4: as search to access data sets directly in the cloud,

1:03:46 Speaker 4: and also there's a QR code linked to that. There

1:03:49 Speaker 4: are some examples that are shown here, is like load

1:03:52 Speaker 4: a single product in Python, load multiple products at once

1:03:58 Speaker 4: to do and then also load time series of products

1:04:01 Speaker 4: using ASF search. If you want to work with data

1:04:07 Speaker 4: sets directly in the cloud, there are also notebooks available

1:04:09 Speaker 4: that are linked here that show you how the you

1:04:12 Speaker 4: know what the access patterns are to get yourself going

1:04:16 Speaker 4: with direct cloud based access and streaming data sets. Directly

1:04:19 Speaker 4: from the AWLS bucket. So these are the resources available

1:04:26 Speaker 4: through NASA at this current stage. Again as a reminder,

1:04:30 Speaker 4: as more and more such resources become available, keep checking

1:04:33 Speaker 4: in in the in the data in the Nicer Data

1:04:37 Speaker 4: user Guide. Those those resources will be made available and

1:04:43 Speaker 4: accessible through the user guide to you. Some nicer data sets,

1:04:50 Speaker 4: especially the spand data sets, will not be available through NASA,

1:04:54 Speaker 4: but will be available through ISRA and isra's Earth Observation

1:04:59 Speaker 4: Data Hub Bonniti. Boniti gives you access to nicer data

1:05:04 Speaker 4: sets of course, but a range of optical and radar

1:05:09 Speaker 4: data sets dating back to nineteen eighty eight through a

1:05:12 Speaker 4: unified platform and nicer data says here will be made

1:05:15 Speaker 4: available free and open through Buniti as required by the

1:05:21 Speaker 4: Open Data Policy of the Indian Space the Indian Space

1:05:26 Speaker 4: Open Data Policy, So all of SPEN data for NICSAR

1:05:31 Speaker 4: in some airbent data of Israel interest will be available

1:05:35 Speaker 4: through Bonniti. Boniti offers a sort of a sequence of

1:05:41 Speaker 4: different services that can use to explore and work with

1:05:46 Speaker 4: nicer data sets. It starts out with the web based

1:05:49 Speaker 4: interface for search and discovery that's shown on top. There

1:05:52 Speaker 4: is an API based search available through Bonniti API that

1:05:57 Speaker 4: lets use search and discover data sets through command line interface.

1:06:00 Speaker 4: And then there are services like Visa which allows you

1:06:03 Speaker 4: to visualize nicer data sets in a web browser, Code

1:06:07 Speaker 4: Lab which is a Jupiter notebook type setup that sits

1:06:12 Speaker 4: next to the archive and lets you work with data

1:06:14 Speaker 4: sets directly at the archive. And then their Geo raster

1:06:19 Speaker 4: Craft service, which is an on demand service that lets

1:06:23 Speaker 4: 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

1:06:32 Speaker 4: information on each of these services on the next slides.

1:06:37 Speaker 4: So first, if you're interested in discovering israel held nicer

1:06:43 Speaker 4: data sets, I recommend you start with the Nicer Information

1:06:46 Speaker 4: page that Israel has put together the link on the slide. Again,

1:06:51 Speaker 4: you will have access to these slides and can follow

1:06:53 Speaker 4: this link gets you to the starting page which gives

1:06:57 Speaker 4: you information about NAR, the ocquisition plan and the data policy,

1:07:01 Speaker 4: the data availability and the latest news for available data

1:07:06 Speaker 4: through Israel. On this page is also a link that

1:07:11 Speaker 4: then gets you to the web based data access and

1:07:15 Speaker 4: data search client. So there's a link that's shown down

1:07:18 Speaker 4: here that gets you to that web based interface and

1:07:21 Speaker 4: there you will be able to then search for NISA

1:07:25 Speaker 4: data sets, discover nice data sets and download them. So specifically,

1:07:29 Speaker 4: folks interested in spend data that's definitely a useful resource,

1:07:34 Speaker 4: and folks that are interested for the joint mode observations

1:07:38 Speaker 4: available specifically over India should also try out Buniti as

1:07:43 Speaker 4: a resource. You also will have to authenticate with Buniti

1:07:50 Speaker 4: similar to NASA. Also, Israe has an authentication service that

1:07:57 Speaker 4: is being used. So the steps are to first register

1:08:00 Speaker 4: with the service and then start discoverings nicer data sets

1:08:04 Speaker 4: through your web based platform. Also on Israel's side, these

1:08:11 Speaker 4: search clients, the search services that are available through the

1:08:15 Speaker 4: web based interface are also available through command line through

1:08:18 Speaker 4: the Boniti API. Also there authentication is required, but then

1:08:23 Speaker 4: you can search for data sets, subset data sets to

1:08:28 Speaker 4: the data sets you actually need and want, and then

1:08:30 Speaker 4: it facilitates data download through the API. So that allows

1:08:36 Speaker 4: you to build discovery of SPN nicer data sets into

1:08:40 Speaker 4: your more programmatic searches. So in addition to these the

1:08:45 Speaker 4: search and discovery and download of data sets, there are

1:08:48 Speaker 4: services are available through ISRAE that allow you to visualize images.

1:08:53 Speaker 4: So Vista showing you on a left hand side is

1:08:56 Speaker 4: a way to visualize data sets directly in a browser.

1:09:00 Speaker 4: There is a URL that can follow on this slide.

1:09:03 Speaker 4: And then code lab, which is shown on the right

1:09:06 Speaker 4: is the stupid and notebook platform that allows you to

1:09:08 Speaker 4: work with data sets directly at the archive without necessary

1:09:12 Speaker 4: necessitating download of data to your local machine. So also

1:09:17 Speaker 4: here's a link available that you can follow to find

1:09:21 Speaker 4: out more. So this is how to discover data sets.

1:09:26 Speaker 4: Maybe a conclude with this one slide on where to

1:09:29 Speaker 4: work with nicer data. Really, the message hopefully that you

1:09:32 Speaker 4: got from the previous slides is that NASA and Israel

1:09:36 Speaker 4: are both interested in meeting you where you are most comfortable.

1:09:40 Speaker 4: So we are trying to facilitate your work on your

1:09:43 Speaker 4: local machine by providing very high volume and high bandwidth

1:09:48 Speaker 4: download capabilities and sophisticated discovery capabilities. But we also want

1:09:53 Speaker 4: to work your facilitate your work in the cloud. If

1:09:56 Speaker 4: you're interested in migrating your workflows into the cloud. If

1:10:00 Speaker 4: that's something you're curious about but you don't have a

1:10:02 Speaker 4: lot of experience with, there's two communities that you can

1:10:06 Speaker 4: contact for help. The ASF Open Science Lab team can

1:10:12 Speaker 4: help you with getting started with work moving into the cloud.

1:10:16 Speaker 4: They provide, similar to what I showed on the previous slide,

1:10:20 Speaker 4: a Jupiter Hub based environment that sits right next to

1:10:23 Speaker 4: the archive and is also populated with a lot of

1:10:27 Speaker 4: already established workflows that may get you started quickly with

1:10:31 Speaker 4: your work with nyser data. Also, I want to mention

1:10:35 Speaker 4: the NASA openscapes community. Openscapes mission is really to help

1:10:40 Speaker 4: people jumpstart their migration into the cloud. Linked here is

1:10:45 Speaker 4: the website for open Scapes with additional information about how

1:10:50 Speaker 4: they can help you and contact information also on the website.

1:10:54 Speaker 4: So as you think about potentially migrating into the cloud,

1:10:59 Speaker 4: these are two communities that you can connect with to

1:11:02 Speaker 4: help you get used to this idea. Now that you

1:11:08 Speaker 4: know how to discover data sets, I want to show

1:11:11 Speaker 4: you a few tools that are available and a few

1:11:13 Speaker 4: access patterns available that allow you to then work with

1:11:16 Speaker 4: these data sets for a variety of applications. I'm going

1:11:20 Speaker 4: to start out with reaching out to the GIS community,

1:11:24 Speaker 4: so there's going to be a few slides on how

1:11:25 Speaker 4: to work with nicer data sets in QGIS and RGIS.

1:11:29 Speaker 4: Then we'll migrate more to the community that uses tools

1:11:34 Speaker 4: like ICE and GMTSR and then to sort of folks

1:11:38 Speaker 4: that are familiar with Python based data analysis. So first

1:11:45 Speaker 4: two QGIS, we have a short video I think by

1:11:48 Speaker 4: Brandy Downs. Is that correct. She's going to walk you

1:11:51 Speaker 4: through how you can access and visualize and work with

1:11:54 Speaker 4: nicer data sets in QGIS.

1:11:58 Speaker 9: Hi everyone, I'm Brandy Downs in the nice Our project

1:12:00 Speaker 9: science team at JPL, and I'm going to walk through

1:12:03 Speaker 9: a demo of how to load and view two nice

1:12:05 Speaker 9: Our data products and QGIS. So we'll start with the

1:12:09 Speaker 9: g code data and then we'll also do the complex

1:12:12 Speaker 9: value GSLC data product. So QGIS doesn't know how to

1:12:16 Speaker 9: read the spatial reference information from nice R HDF five files.

1:12:21 Speaker 9: If you just try to load in a nice Our

1:12:23 Speaker 9: HGF five file directly into QGIS as is, it will

1:12:28 Speaker 9: either crash or it will load it to add zero

1:12:31 Speaker 9: zero long because it doesn't know what the coordinate reference

1:12:34 Speaker 9: system is. So to fix this, we have to tell

1:12:38 Speaker 9: QGIS to use g Doll's net CDF driver, and there

1:12:42 Speaker 9: are a couple of ways to do that, but the

1:12:44 Speaker 9: way that I'll show you have to go to layer

1:12:47 Speaker 9: AD layer, add roster layer and then find the gCO

1:12:52 Speaker 9: file and then in this cell, go to the very

1:12:55 Speaker 9: beginning and just type in net CDF and that just

1:12:59 Speaker 9: tells QGI use the net CDF driver no matter what

1:13:02 Speaker 9: the file extension is. So click on AD and then

1:13:07 Speaker 9: 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

1:13:13 Speaker 9: lot smaller than the frequency A data. But typically you

1:13:16 Speaker 9: would probably want to work with frequency A, but I'm

1:13:19 Speaker 9: choosing frequency b. Hh AD layers clothes and then if

1:13:25 Speaker 9: we zoom to the layer, it does look like it's

1:13:28 Speaker 9: correctly GEO referenced. However, it is quite dark, and so

1:13:32 Speaker 9: we're just going to adjust the symbology to this cumulative

1:13:38 Speaker 9: countcut so that it will map the min and max

1:13:41 Speaker 9: to the second and the ninety eighth percentile of the

1:13:44 Speaker 9: pixel values. So that will eliminate a lot of the

1:13:46 Speaker 9: out layers from view. So that's it. That's the g

1:13:50 Speaker 9: COVE data. So next we'll do the GSLC product. QGAS

1:13:56 Speaker 9: does not have a native way of handling complex valued data,

1:14:00 Speaker 9: so to get around that, there's a couple of things

1:14:03 Speaker 9: we can do. You can use g'll translate to extract

1:14:07 Speaker 9: the amplitude and phase and save them separately to geotips.

1:14:11 Speaker 9: But if you don't want to save separate files, you

1:14:14 Speaker 9: can do it this way. So you got to layer

1:14:17 Speaker 9: AD layer AD roster layer the same way as we

1:14:20 Speaker 9: did it for the g cove and the GSLC file.

1:14:25 Speaker 9: Now we need to specify a few additional parameters beyond

1:14:28 Speaker 9: just the net CDF to the beginning and to the

1:14:31 Speaker 9: 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

1:14:38 Speaker 9: specify derive subdata set amplitude and then the net CDF driver,

1:14:44 Speaker 9: and then at the end we need to specify the

1:14:46 Speaker 9: exact subdata set name. So I'm going to grab this.

1:14:50 Speaker 9: I'll be that to the beginning, and then to find

1:14:55 Speaker 9: the subdata set name, I just use ged all info.

1:14:58 Speaker 9: So I'm already in the direct three where my files are.

1:15:02 Speaker 9: To git all info all one word based in the

1:15:06 Speaker 9: file name, and that will print a list of all

1:15:09 Speaker 9: of the subdata set names. Then you can find what

1:15:13 Speaker 9: you're looking for, which is frequency bahh. And you want

1:15:17 Speaker 9: to grab everything from the colon onward and that goes

1:15:22 Speaker 9: 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

1:15:32 Speaker 9: 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

1:15:45 Speaker 9: rename that and then likewise we can add the phase

1:15:49 Speaker 9: data in the same way. It saved all of the

1:15:52 Speaker 9: inputs we had already put for the amplitude. So all

1:15:55 Speaker 9: we have to change is this phase and there's the

1:16:02 Speaker 9: phase data, so rename that. So we have the g

1:16:08 Speaker 9: 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.

1:16:23 Speaker 4: I'm going to get back to that in a little

1:16:25 Speaker 4: bit in a few seconds, so stay tuned if you

1:16:29 Speaker 4: have more interested in QGIS. A lot of the community,

1:16:34 Speaker 4: at least in the United States and probably also internationally,

1:16:37 Speaker 4: is a heavy user of RGIS pro, and the nicer

1:16:41 Speaker 4: data format is supported in RGS pro. Now there was

1:16:45 Speaker 4: support added in version three point four point zero, so

1:16:48 Speaker 4: make sure that you're running a version of RGIS that

1:16:51 Speaker 4: is that or later, so it's available since November of

1:16:55 Speaker 4: twenty twenty four. There's more information if you follow that

1:16:59 Speaker 4: QR code on the top right. Especially there's a tutorial

1:17:04 Speaker 4: available that you can follow to work with data sets

1:17:08 Speaker 4: in rgis pro. It's also linked in this link on

1:17:12 Speaker 4: this slide. On the next slide, we'll have Heidi Christensen

1:17:16 Speaker 4: from the Alaska Sellie Facility walk us through usage patterns

1:17:21 Speaker 4: of nicer data and rgis pro.

1:17:33 Speaker 10: One way to add nicer data to your rgis pro

1:17:35 Speaker 10: project is to clickly add data menu, select multi dimensional

1:17:40 Speaker 10: data and navigate to your nice our data set. Click

1:17:46 Speaker 10: on it to view the variables and select the ones

1:17:49 Speaker 10: you want to add to your map. I'll add both

1:17:52 Speaker 10: 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

1:18:05 Speaker 10: file name, including the path to that variable. There are

1:18:12 Speaker 10: many tools for working with imagery that can be used

1:18:15 Speaker 10: within nyser data sets. For example, you can change the

1:18:19 Speaker 10: 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

1:18:40 Speaker 10: 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

1:18:58 Speaker 10: the HDF five variables, some analysis workflows may require a geotif,

1:19:03 Speaker 10: or you may find that an easier format to work with.

1:19:05 Speaker 10: In general, and you can export the variables as geotifs

1:19:10 Speaker 10: either the original product or if you have applied raster

1:19:16 Speaker 10: functions and you want to start with that, you can

1:19:19 Speaker 10: 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

1:19:25 Speaker 10: clip it to an area of interest. So I'm going

1:19:28 Speaker 10: to add that area of interest and I'll export my

1:19:32 Speaker 10: speckle filtered image be a file name. I'll put it

1:19:45 Speaker 10: as a TIFF file using the same coordinate system and

1:19:48 Speaker 10: as the HDF fly variable and setting my clipping geometry

1:19:53 Speaker 10: to my area of interest, can adjust the symbology and

1:20:19 Speaker 10: I now have a subset ciotip.

1:20:21 Speaker 4: For my area of interest. Thank you Heidi for this

1:20:28 Speaker 4: intro to how to use nice data sets in our GIS.

1:20:34 Speaker 4: So this is for the GIS community and sort of

1:20:37 Speaker 4: the two big GIS platforms that are around. If you

1:20:41 Speaker 4: are more a SAR data user and experienced star data

1:20:45 Speaker 4: user that has worked with open source SAR processing software

1:20:50 Speaker 4: in the past, I should note that you can use

1:20:53 Speaker 4: ICE three, which is a JPL released open source SAR

1:20:58 Speaker 4: focused software package that's of a level. ICE three is

1:21:01 Speaker 4: like your perfect way to work with nice data sets

1:21:04 Speaker 4: more because ICE three is the engine behind NYSA. All

1:21:07 Speaker 4: of the data processing, the operational data processing for NICAR

1:21:11 Speaker 4: is done with ICE three. So it allows you using

1:21:15 Speaker 4: the software package, allows you to replicate the exact data

1:21:18 Speaker 4: products you would get from the operational processor, and it

1:21:22 Speaker 4: allows you to make modifications to that operational workflow. You know,

1:21:26 Speaker 4: 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

1:21:34 Speaker 4: products on your machine using the exact same process that

1:21:37 Speaker 4: is also behind nicer. In addition to that, another software package,

1:21:42 Speaker 4: open source software package that the community is familiar with

1:21:46 Speaker 4: is GMTSR, and this software package is also ready to

1:21:49 Speaker 4: consume nicer data sets. There have been many examples already

1:21:53 Speaker 4: to use some of the early release data to create

1:21:56 Speaker 4: in the paragrams using gm TSAR. So there's a que

1:22:00 Speaker 4: here that gets you to the website and to a

1:22:03 Speaker 4: download link and an install link. And so please encourage

1:22:07 Speaker 4: 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,

1:22:18 Speaker 4: there's a growing list of additional resources available in the community.

1:22:22 Speaker 4: A number of the commercial SAR software providers are working

1:22:26 Speaker 4: on integrating nicer data sets into their solutions, and the

1:22:31 Speaker 4: project here at JPL has been in communication with Google

1:22:35 Speaker 4: earth Engine Google and the Google Earth Engine team and

1:22:39 Speaker 4: 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

1:22:53 Speaker 4: and want to find utilities that let you explore nicer

1:22:57 Speaker 4: data sets easily through Python, sort ready to use n

1:23:02 Speaker 4: nice R products in Python. There's some utilities provided by

1:23:07 Speaker 4: the HDF five group that are listed here, such as ISDHDF,

1:23:13 Speaker 4: HDF five, HD five and HDF py h five py packages.

1:23:19 Speaker 4: They allow you to sort of visualize metadata, explore the

1:23:22 Speaker 4: data content, and do some Python based processing on nicer

1:23:26 Speaker 4: data sets. Again, there's a QR code here that gets

1:23:29 Speaker 4: 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

1:23:39 Speaker 4: allows you to view metadata and raster layers in a

1:23:42 Speaker 4: web browser. It can read up to about five thousand

1:23:45 Speaker 4: by five thousand pixel sized data sets, and it can

1:23:49 Speaker 4: also be instantiated from a Jupiter hub. So if you're

1:23:53 Speaker 4: using a service like open Science Lab for instance, or

1:23:56 Speaker 4: others such Jupiter ob services, you can install h five

1:24:02 Speaker 4: web into your Jupiter lab to visualize data sets there. Lastly,

1:24:10 Speaker 4: the team at JPR has been working on a nicer

1:24:14 Speaker 4: driver for g doll that's available now through a separate

1:24:19 Speaker 4: channel called the nicer Forge channel. So there's information on

1:24:24 Speaker 4: here and how you can install this driver to your

1:24:27 Speaker 4: local machine, which then makes GDR look like it understands

1:24:32 Speaker 4: nicer data sets. Natively, there is an effort going on

1:24:36 Speaker 4: right now to integrate this driver into the official g

1:24:39 Speaker 4: doll release, which then would make also working with nicer

1:24:43 Speaker 4: data sets in platforms like q GAS a little more

1:24:46 Speaker 4: a little easier and streamline that analysis pattern as well.

1:24:52 Speaker 4: So that the team is working on that integration right now,

1:24:56 Speaker 4: and we'll let you know on the Data user Guide

1:25:00 Speaker 4: 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

1:25:11 Speaker 4: that you can use with nyser data sets. One of

1:25:13 Speaker 4: them is a package called Plant, which includes a collection

1:25:17 Speaker 4: of tools that were developed by JPL for the use

1:25:20 Speaker 4: with remote sensing data. It was developed with a radar

1:25:24 Speaker 4: use case in mind, but is broader than radar and

1:25:28 Speaker 4: can help you work with remote sensing data sets in general.

1:25:32 Speaker 4: It's meant to take outputs that you get from the

1:25:35 Speaker 4: project and analyze them further such as subsetting them, mosaching them, applying,

1:25:42 Speaker 4: applying masks to data sets, et cetera. So there's some

1:25:45 Speaker 4: examples of usage patterns that can use with Plant and

1:25:48 Speaker 4: the QR code in the corner, as well as the

1:25:50 Speaker 4: link in the in this slide gets you to the

1:25:54 Speaker 4: 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

1:26:05 Speaker 4: three which is useful for folks that are not as

1:26:09 Speaker 4: familiar with the with handling data sets in ICE three.

1:26:15 Speaker 4: ICE three requires a lot of information to know how

1:26:18 Speaker 4: to process data sets correctly that need to be configured

1:26:22 Speaker 4: in the configuration configuration file. If you're not as familiar

1:26:25 Speaker 4: with these configuration files, Plant the Plant ice integration can

1:26:29 Speaker 4: help you with that. So Plant will help you pre

1:26:32 Speaker 4: populate these configuration files that make the usage of some

1:26:36 Speaker 4: nice ICE three utilities a little more straightforward for folks

1:26:39 Speaker 4: that are not as familiar with ICE three as a package. So,

1:26:47 Speaker 4: as mentioned, there's a currently already a growing number of

1:26:51 Speaker 4: software tools available that help you work with nicer data sets.

1:26:55 Speaker 4: We expect the number of tools to expand quickly as

1:26:58 Speaker 4: more nice, nice data sets are being released, so stay

1:27:02 Speaker 4: tuned for the Nicer Data use Guide user guide to

1:27:05 Speaker 4: get the latest and most up to date information on

1:27:08 Speaker 4: these tools. Lastly, I want to talk about the Acquisition Plan.

1:27:13 Speaker 4: Paul Rosen already presented this earlier, so there's a web

1:27:18 Speaker 4: based version of the acquisition plan available built as an

1:27:23 Speaker 4: RGIS experience. So if you follow this QR code or

1:27:26 Speaker 4: the link underneath it, you get to that website. It

1:27:30 Speaker 4: will show you what kind of data and what kind

1:27:33 Speaker 4: of acquisition modes are available in different places of the

1:27:37 Speaker 4: world once the full release of data sets becomes available,

1:27:42 Speaker 4: and you can filter then by different acquisition types. In

1:27:46 Speaker 4: this RGIS webmap, one thing, for instance, you can visualize.

1:27:51 Speaker 4: You can look at the coverage of spand data. These

1:27:54 Speaker 4: are the data sets that are specifically available through israe's

1:27:58 Speaker 4: Booniti platform and you see information here. You see various

1:28:03 Speaker 4: places throughout the world, but heavily the areas of India

1:28:07 Speaker 4: and around India, the Antarctic and Greenland are covered heavily

1:28:11 Speaker 4: in s band. That leads me back to a follow

1:28:14 Speaker 4: up on my earliest slides on the ISRAE data holdings.

1:28:18 Speaker 4: I shall mention that the Elbent data Israel will hold

1:28:22 Speaker 4: are reprocessed so they are different slightly than the data

1:28:27 Speaker 4: sets you get through NASA and our reprocessed to align

1:28:32 Speaker 4: most optimally with the spend data collects that they are

1:28:36 Speaker 4: 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.

1:28:44 Speaker 4: Through Vertex are the NASA released alban data sets, and

1:28:49 Speaker 4: through Bonniti you'll get the Israel released data sets that

1:28:53 Speaker 4: 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

1:29:04 Speaker 4: you might find interesting. First of all, again pointing out

1:29:09 Speaker 4: and the Nicer Data Use Guide, which is the first

1:29:12 Speaker 4: QR code you're listed on the bottom. There's also Earth

1:29:15 Speaker 4: Data Forum, so if you have questions about nicer data

1:29:18 Speaker 4: access or you know working with nicer data sets in general,

1:29:24 Speaker 4: please we want to point you to the Earth Data Forum,

1:29:27 Speaker 4: which is NASA's forum where you can bring your questions.

1:29:31 Speaker 4: There will be eventually a tab that you can click

1:29:34 Speaker 4: on that says nicer specifically, so that your question is

1:29:37 Speaker 4: directed to the right people to answer them. But asf

1:29:42 Speaker 4: and also the JPL team, I'm monitoring UH the Earth

1:29:45 Speaker 4: Data Forum for your questions related to NISA, and of

1:29:49 Speaker 4: course ASF AS will be the host and we'll be

1:29:52 Speaker 4: managing all of the nicer data sets in our user

1:29:56 Speaker 4: support team at ASF is you know waiting for your

1:29:59 Speaker 4: question and are giddy to help you out with all

1:30:02 Speaker 4: your questions about NISAR. So this third QR code gets

1:30:05 Speaker 4: you to contact information at ASEF and please feel free

1:30:08 Speaker 4: to direct all your questions toward us. Lastly, there's going

1:30:15 Speaker 4: to be a slew of upcoming events and training events

1:30:19 Speaker 4: that will help you more with accessing and working with

1:30:23 Speaker 4: nicer data sets. There's a large list shown on the

1:30:26 Speaker 4: slide that you can browse through in the recording or

1:30:30 Speaker 4: in the slide deck that you will be made available

1:30:33 Speaker 4: to you. So there's a number of events that are

1:30:35 Speaker 4: coming up. They don't all have dates yet at this point,

1:30:39 Speaker 4: but again we'll make them available through the use guide.

1:30:42 Speaker 4: It will be available through the Nicer website once those

1:30:44 Speaker 4: are announced. So stay tuned for all of these opportunities

1:30:47 Speaker 4: training opportunities linked to NISA coming up in the coming

1:30:52 Speaker 4: days and months. And with that, I want to thank

1:30:57 Speaker 4: you for your attention. Again. If you have further questions,

1:31:00 Speaker 4: please use any of the links that are provided at

1:31:02 Speaker 4: the end to get in touch. There might be a

1:31:04 Speaker 4: chance for answering some questions in chat now, and then

1:31:08 Speaker 4: the recording of this session is going to be made

1:31:10 Speaker 4: available to you for rewatching. Thank you very much. Do

1:31:23 Speaker 4: we want to do some questions? Are there any open

1:31:32 Speaker 4: questions we need to address now? Yes, there will be.

1:31:42 Speaker 4: It will be identifiable who process the data? Yes? Answer okay, excellent,

1:31:59 Speaker 4: So most questions were answered, and I thank you for attention,

1:32:01 Speaker 4: and again don't forget to get in touch if you

1:32:04 Speaker 4: have further questions. In the future. Product the soy moisture

1:32:13 Speaker 4: product and I'm looking at poor ros and why mensering.

1:32:15 Speaker 4: This is the only Level three product that is going

1:32:18 Speaker 4: to be produced by the project. There will be additional

1:32:22 Speaker 4: Level three products coming through other resources. For instance, the

1:32:27 Speaker 4: JPL Opera project is going to create a displacement product

1:32:32 Speaker 4: and I think a vertical landmotion product based on NISAR

1:32:36 Speaker 4: in addition to the soil moasture product. And there is

1:32:40 Speaker 4: probably other sources of Level three that will come in

1:32:43 Speaker 4: the future, provided through different resources. On the ATBD notebooks

1:32:55 Speaker 4: will be made available for open Science lab. There is

1:32:57 Speaker 4: an effort that's going on to make them more deductical.

1:33:02 Speaker 4: Deductible is that the right word, make them easier to

1:33:06 Speaker 4: use and understand for folks that are new tw SAR

1:33:09 Speaker 4: and we will have trainings on these at b DS.

1:33:12 Speaker 4: There's some interest in taking some of these workflows and

1:33:15 Speaker 4: make them turn them into an on demand service that

1:33:20 Speaker 4: you can just run dependent on funding. So there's broad

1:33:24 Speaker 4: interest in the community to make those available. So I

1:33:41 Speaker 4: should repeat those questions. So any help for the HG

1:33:46 Speaker 4: five files files that are very large. Yes, ASF is

1:33:53 Speaker 4: working on a subsetting service that will be available for

1:33:56 Speaker 4: nicer data sets to help users that don't need the

1:33:59 Speaker 4: full frame and don't need the full data volume that

1:34:03 Speaker 4: the full frame brings. So there will be a subsetting

1:34:05 Speaker 4: service available in the near future. Yeah, and there are

1:34:13 Speaker 4: also options through g doll and the earlier presented the

1:34:19 Speaker 4: planned IC three package, which also can facilitate some of

1:34:23 Speaker 4: that subsetting. Yeah, and so the wad All Bright, the

1:34:33 Speaker 4: ASF director, also mentioned that, as you saw in Greg

1:34:37 Speaker 4: Short's presentation about Vertex, for instance, you don't always have

1:34:41 Speaker 4: 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

1:34:50 Speaker 4: to reduce download volumes. Okay, well, we'll answer the remaining

1:35:01 Speaker 4: questions offline and otherwise you can always email us. Thank

1:35:04 Speaker 4: you very much, Thank.

1:35:07 Speaker 2: You Franz and everybody who put all so much work

1:35:10 Speaker 2: 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

1:35:17 Speaker 2: released starting tomorrow. That concludes this town hall and Data

1:35:23 Speaker 2: Access webinar. Thank you all for attending online and in person,

1:35:28 Speaker 2: and we look forward to your feedback once you start

1:35:31 Speaker 2: looking at these data.

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