Mapping Humanity From Space: NASA’s Black Marble with Dr. Miguel Román

Cold open: three moments from the interview

0:00For a lot of people, it meant that you could track things like energy access, >> right? >> You can track disasters. And at the time, we didn't know how powerful this tool was going to be uh for many different organizations. And I put Puerto Rico on just like I do every day. I drink my cafe and I'm going to look at Puerto Rico and I had to look three times. And my hard jump because it had disappeared. Made me go on a John Deere tractor, turn on the lights, and they detected the lights from space. >> No way. >> I can show you. Guess way.

A NASA intern's question and a new weather satellite

0:50So, you've already noticed the photograph that was um that's over here. This is one of the first photos on the um Earth Observatory on the NASA website that sort of caught everyone's attention, this potential to study human activity at nighttime using satellite imagery. Um were you looking to do this or how did you even stumble upon this story? Tell me tell me what the the story is. Yeah. So, for the record, there's no NASA department dedicated to starring Hollywood lights from space. Yeah. Good. It did not not even today even though I think we should probably have one >> for sure. >> But

1:30>> we get an intern on that. >> I did. >> I did. And that's that's the wonderful thing about NASA entered. They had to ask amazing questions and that was one of the questions that came my to our office after we were doing what our job was which is we just started a new mission back in 2011 launched in 2011. data started coming in early 2012 called the Swami National Polar Orbiting Partnership which is our nation's next generation weather satellite large system took years to build and we

2:11needed a preparatory mission to make sure we're testing everything before we go into this new program that is going to be generating all sorts of measurements to track our weather to track all different trends, very important things like ozone, surface radiation, >> okay, >> through the 240s. So this was that at the moment the US were was looking under the hood of this new instrument

Calibrating the night band: the Moon and the desert

2:38and they were recruiting people fresh out of college like me saying, "Hey, calibrate this thing, which is is the data coming out of this new instrument correct? is the integrity everything about this instrument working and I was an I was I trained in as an engineer then I switch over to science so I was always kind of working around the integrity of the data yeah >> working with the instrument teams working with the science teams and trying to be a bridge and they asked me is the instrument the visible infrared imaging radiometer sweep figure it out they gave me two years so First thing

3:19you do is you ask the spacecraft team to look at the moon cuz the moon is very steady. So if they if you look at the moon every month and the moon starts looking dark, you got a problem with Uranus. >> Fair enough. Yeah. >> So we started doing that moon >> and this is literally you just point the thing at the moon. Okay. >> Right. Very stable. Problem is there's a lot of variability even though it's stable. So we needed more data. So what is the next most boring stable place on earth? Just look at any desert where there's not been any kind of source of civilization. So we picked the Saharan

3:59desert and so this picture you showed a section of the Sinai desert next to Cairo up there's you know all these places Jordan Israel and we're we're

The anomaly: Ramadan seen from space

4:11tracking how the data changes in a place where there's no clouds where the moon goes up and down up and down and suddenly so you it doesn't reach a peak and suddenly boom and we have to look at it like three or four times we're seeing pics over like the bright lights in all major metropolitan districts in this region. Why? That every research article that we had read since then told us that yes, lights do increase gradually from year to year, but it takes time. It shouldn't be from one season to the next. >> Mhm. >> And we thought the instrument was

4:52broken. >> Okay. Interesting. We thought okay the low gain stage is suff the high gain stings that detects very small ch signals would broke it wasn't broken and we knew because we had corrected two data sets and the anomaly was following the lunar calendar not the Gregoria calendar and who uses the lunar calendar right >> musloops. >> Uhhuh. And so when we looked at 2013 and 2014, the anomaly had perfectly matched against the last day of Ramadan the AA. So we were mapping Ramadan from space. The instrument was fine, but it had given us a gift. They had given us a capability to monitor humanity from

5:35space and literally culture from space.

Christmas lights, and home in Puerto Rico

5:39And so the next thing is like, well, we're US agency. Let's go get Christmas. also found Christmas lights. >> Okay. >> And that brought me back to my home of Puerto Rico because >> we're very part of Puerto Rico if you don't know, but we our Christmas are the best Christmas >> longest Christmas ever. >> Yeah. Get in the comments if you disagree. >> Yes. Let me say, you know, starts at Brad Fridays, ends in January 20 with the San Sebastian festivities. And I felt that this was an opportunity to connect with these communities. and and that was amazing. I mean the other thing is we knew that we needed to

6:20do data filtering elsewhere because snow if you think of it a snow at night very bright too. So Puerto Rico doesn't have snow but still have Christmas. So again just like the desk find an easy case study turn out beautifully. So this map you could there's a Puerto Rican map also, right? And and at the time it began to sink in that we were looking at a GMA

A new pair of glasses: all of humanity at night

6:48but it was like I told you it wasn't that wasn't our job. I I and that's where a lot of our science staff began to ask questions about hey these are very bright lights but if it's like they've given you've given us a new pair of glasses and now we can see not just that activity but we're also seeing these lowlight pieces of our geography at night >> these places that before were being you know in a way these bright lights were shadowing over the smaller light. Rural communities, communities living outside the city. That's where the big

7:30reveal was. The fact that we can see all of humanity, not just the metropolitan areas that were being that were oluding the due to contamination of the the lice oluding these other pieces of society. And that's where the data became very powerful. For a lot of people, it meant that you could track things like energy access, >> right? you can track disasters and at the time we didn't know how powerful this tool was going to be uh for many different organizations and we were just I mean we were building on our research to do that. >> Yeah, that is that is an incredible like starting story um that you were

8:10effectively just trying to calibrate this thing and then you look like to the side and then there's just like these random high frequency events that are happening. That's that's pretty cool. And then from there, you know, this is sort of the first Sojourn of of the team. This is before even the team of um Black Marble was found was was formed, right? >> You were just two at the time.

From calibration to a Black Marble team

8:32>> Yeah. So, how do you transition from like okay there's like random people doing calibration to now like there's you get like a a consortium of of scientists and your you and your colleagues who are now being recognized for the Golden Goose Awards. like how do you how do you how do you start convincing um you know people that this is something that's worth full-time scientists to work on? >> Yes, we were very blessed with a very multi-talented team that brought unique skills and different questions to to our group because if it weren't for me we will be just focusing on data filter.

9:13To me, the most important job of a NASA scientist is to create highly pristine science measurements of the Earth system. And and at the time, this has changed a lot, but at the time we would just generate the gold standard product, throw order the defense, and allow the science community to ask those questions. So in a way years later we we then evolve as an agency as an organization and now NASA scientists are doing a lot of work that crosses this boundaries crosses the boundaries around nature technology and society. >> So in a way we were pioneers

9:54>> in that new mindset of developing our science to action >> and we brought urban scientists to our team very early. Okay, cool. >> We brought people who were who had degrees from Yale in you know understanding urbanization as a process >> and instead of giving them maps of land cover to show where are the cities and where are the non-urban areas now they had something that helped describe the function >> of these places cuz you can see a building if the lights are off the building is still there during the day and so this gave a lot of um versatility ility to how what kind of questions you

10:34can ask from an urban development from an infrastructure point of view that we would never be able to do before unless you had a lot of in money to kind of literally manually count buildings and how much energy they use and everything. And we understood that we had to be careful about what we were really seeing. We've seen lights at night and yes, it's been used as a proxy of many different things, but we were always very casual in approaching that with integrity like we weren't overselling the capability and saying this is a good way to replace estimates of total electricity, >> right? >> No. >> Yeah. >> No, this is a piece that gives you better insights globally, geographically.

11:16And I think the part that we began to coales was when we hired someone who was entirely focused on apply science and that's where the community became broader because we were doing things like light pollution so monitoring dark skies but we were also doing disaster response. So we were covering the entire gamut of energy conservation, wildlife preservation, and then emergency preparedness, resilience, and all these things. And we by then we were just a team of four or five people. >> Yeah, that's that's pretty incredible.

Opening the data to the world

11:51>> And so we went back to you can't just run such an amazing capability with five people. and our NASA leaders pushed us to make it full and open to the to the world. That happened 8 years after this after this discovery. And that in fact was our biggest contribution. We we made we really embraced open science and that meant that the data was not just in a web page you know you can find it you can access it you can reproduce it from start to from from scratch and that's what it has attracted so many people from around the world that before

12:33they were just like just a handful of teams. The majority of the research produced now is produced by outside organizations. NASA still we still publish but we are seen as as as the folks that preserve the integrity of the data rep that's our main that still is why they come to NASA and ask us.

Keeping the data honest: moonlight and airglow

12:58>> Well uh so speaking of like you know preserving the data and presenting pristine data that's a big passion of yours. So I wanted to ask you just how difficult it is actually if you don't mind that we we we we like getting technical on this podcast because um you know the name is from first principles so we try to develop the process of how science is done rather than just the answers. I think the answers are certainly really cool right the fact that you can see um Muslim cities of Cairo and Aman uh fluctuating in brightness during Ramadan and it it like coincides with Eid. >> But I know where you're going with this. Do you know why it takes to get >> Exactly. Like it's a lot of work. A lot

13:38of work goes into convincing yourself that you're not being fooled because the easiest person to fool is yourself. So what I wanted to ask you um with this this is a figure from I think >> the theoretical basis document. >> Exactly. So >> which is NASA's speech for no one had he written the theory on understanding how lights interact with the sky at night since 2018. He had to create that theory from scratch. >> Exactly. So, so I wanted to ask you like so there's moonlight obviously in this figure. Um >> there's air glow. >> Yeah. Air glow is just the atmosphere glowing. >> Yes. From from precipitation electrons from the hemosphere. >> Oh wow. So interacting with

14:21>> and atmospheric chemistry happening. So every time there's a storm event you see aura >> and that becomes noise for us. But helopysicists love to go get those maps to do early warnings for potential impacts to infrastructure layer power grid. This the same data set.

One band, and why LEDs look like dimming

14:36>> Oh, it's the Wait, so hold on. So let's start from just the satellite. Okay. What are the what are the wavelengths that it's sensitive to? >> So it there's only one band. There's >> there's only one band. There's only one pancreatic one from 0.5 to 900 nanometers and it captures all the infrared visible and infrared in that >> and >> so it's just brightness. >> It's just brightness. >> Okay, that's crazy actually. So >> and and because had it been designed by someone with expertise in night time would have been done completely different including the L LED pump or 20 which a lot of the lights that we see now are transitioning to LEDs. We can't

15:17see that. Why? Because it was not built to do that. It was built to measure clouds at night for weather. This is a letter sound. >> Wait, so wait, no, now I'm jumping the gun because like So the last paper that I wanted to Yeah, we're just going for it. So the last the last figure I have is this one. This the very recent um nature paper and there you see Europe dimming, but that's because of the it's just >> because Europe is poor. It's not dimming because there's some power out. It's different because all of Europe decided to switch to LED lights in three years. >> Right. So the brightness could remain the same. >> Yes. >> Right. It's not that the brightness >> the brightness is getting worse. >> Yeah. Yeah. >> But in our data it looks like it's going down because we don't see the blue. >> Yeah. That was unclear to me. So before

Why the satellite can't see blue: one instrument, many jobs

15:59this before we did this interview um we did like a deep dive on five papers that you were co-author on and that was the last one. And it it was kind of unclear to me why the brightness would go I mean the the explanation was in the paper that you know there's policy changes and there's different types of lights but now it's very clear that it's just a single band and the thing is outside the band >> and it's not only a single band it's a single end with a narrow aperture in wavelength that we made traits at the time we needed to be more in the infrared because I I sacrifice the blue, but I gain infrared life to monitor fires and flaring.

16:40>> Okay, fair enough. Yeah. >> So, that's always the trade when you build an instrument. What do you give off and what do you gain? And at NASA, we've had to do that many, many times to help address the needs and priorities of broader science communities. You know, when we build it, this same instrument was built to measure clouds, to measure ocean color, to measure fires, to measure forests. So, by the time you build those requirements, you're talking about a $700 million instrument. And so, at the end, you add, oh, and I want to add blue LEDs. Okay, that's going to be another 2 million. Like, at some point, you got to stop, you know? So you can't just you can't what's the

17:22what's the technical reason why the band has to be like a certain width. Why can't it be a little like why why is it more expensive so much? >> It's driven by requirements. It's not it's not just this one decision. It's decisions going back to the requirements of a large swath of stakeholders across the federal community. Yeah. >> Do the Noah and NASA. They all have different customers. >> They all have different stakeholders. You've got folks who need to support weather, you know, you got and so at the time the requirement was we need to be able to see low fog and cloud in Alaska and these are the bands that allows us to optimize

18:03again that Christmas lights is not a factor. >> Yeah. Yeah. And it's about it's about weather at the end of the day. >> It's all about this is our nation's weather workhorse. >> Yeah. And so the priority is let's try the 5day forecast. If there's size that comes out of that, we'll revisit it later,

Light from every angle, and building heights

18:20>> right? Okay. And so, okay, so back to the figure, you've got moonlight that >> that um that penetrates Earth's atmosphere, hits the ground, goes back. Sometimes it goes back into the ground and then comes back cuz there's like just photons are doing weird things. >> Um there's the the air glow from the atmosphere. Then there's clouds. There's all sorts of like random crap that that photons are hitting. Yes. >> Before it hits your sensor. >> Even before we did this, we didn't know how difficult it was. So, here's another problem. >> The lights from buildings also vary by angle. >> So, it matters a lot. And that's where we accounted for that in this paper.

19:01>> Oh, wow. Okay. >> If you are in New York City, Time Square and your spacecraft is looking obliquely at 45°, you're not seeing the lights, the billboard. >> The billboard. Ah okay. >> So you have to be looking from really at across the the the liio sites. So what we call nater and so we realized that this instrument had a lot of structure in the data if you understand the directional signature the multi-angular signature because you have natural variation but you also have anthropogenic radiation going on in the mirror. >> Wow. So the biggest breakthrough between this paper and this paper was the fact

19:41that we understood that the world the light in the world also vary a lot angularly >> and we couldn't we didn't even account for that when we did >> right here you have angle from the moon you've accounted for that >> yes that we accounted for that and we basically use atmospheric correction routines from daytime and we just basically plot the sun on the moon that's that's all we did >> okay yeah fair enough >> yes because the inherent optical properties of the atmosphere is really the Okay, you have aerosols, you have molecules, so you can make some approximations and those approximations have hold now for 12 years. The biggest state-of-the-art now is trying to figure out the angular structure of artificial light. And that is very fascinating because you could relate those different

20:24modes. So even though we don't have colors, we have a lot of understanding of the architecture of the likes. And that is how we started looking at the volatility of watch because the fact that the dark the it's dark at this angle and it's bright at this angle. What does it mean? I have something I have building height, >> right? >> So it's literally I can extract building heights from the lights data. >> Yeah. Yeah. Yeah. Yeah. That that's that's that's pretty cool. >> And if I can if I can track building likes over a 40year period, I know how your country is growing. China urbanized in 20 years. They built up and they ran out of space. Who's

21:06next? India. So India is going to be the next civilization that is still building horizontally and now they're building up. Then when you Elanar Stoke, he's our she's our expert in urbanization. She came out of Karen Cosbe Yale. They're the experts. They're the ones informing mayors on how to build cities sustainably where you don't end up in a situation where you're building so fast that you're not gaining benefits from building living in cities that are more accessible or those are the questions this needs. >> Yeah. Yeah. Hopefully Los Angeles also takes note because um I I would love to to have more housing in Los Angeles. So

21:48in order to do that you need to understand the makeup of transportation, commercial, you know, housing understanding how those functions change over time. For the first time we have data sets that can help you understand that variation and you can now understand the volatility of those sectors as a result of disasters. So that's another factor that that's very unique to this. >> Yeah. Yeah. Actually, so one of the

Puerto Rico: the 2016 blackout and Hurricane Maria

22:15things that I wanted to ask you about was the big Puerto Rico paper. So, first of all, this must have been um personally a very big deal for you, right? Um how'd you how' you come across like doing this? Yeah. So I remember the day I was a gerter have my monitor 2016 September 20 the first major outage like of an entire area was a power outage that happened at the Agira power plant in Guayama that day. And with this

22:56is early black marble we were still manually downloading data. No, we weren't in the cloud like and I put Puerto Rico on just like I do every day. I drink my cafeito and I'm going to look at Puerto Rico and I had to look three times. >> And my hard job because it had disappeared. >> Yeah. And this is just after the hurricane. >> Before the hurricane. A year before the hurricane. >> Oh, before the hurricane. >> That was kind of a warning sign. >> Interesting. as the electricity system of Puerto Rico was already very vulnerable and sending us an early signal of what became the largest power outage in Puerto Rico in US history at the time which is hurricane Irma and

23:38Maria that followed each other within two weeks and the project changed forever after that. We knew what was going on. We weren't, you know, our head didn't skip at that time and rather than having a concern, it was, you know, we had a sense of urgency as an agency, not just our team. I mean, I remember being part of NASA's disaster response coordination team. We were in meetings at the White House with all our partners and other federal agencies helping understand the situation in Puerto Rico from us. >> And

24:19everything we had done prior to this was curiositydriven. It was understanding the night, understanding how to protect the night. You know, the natural patrimony that is to be able to have dark skies. Puerto Rico changed that. We we started asking different questions because of this and it wasn't not enough to just coming up with a power outage map and putting it in the front cover of Washington Post. We used to do that a lot. >> Yeah. >> But after this it wasn't enough. We we had to stay and monitor which communities were still without power for

25:00how long. And the entire project became a focus on recovery and resilience. And yeah, so we were I remember being on in calls with the army nin command in Puerto Rico and they were moving diesel power generators around the island and I got a call from a captain like sir like we're going to move we want to go to this town power. >> Uhhuh. And I was like, "Yeah, they've been without power for 60 days based on the DOE report and our nighttime nets." And we we were part of the search capacity force, the federalwide search capacity for that had not been activated since Katrina.

25:40>> Wow. >> Nowadays, there were there were folks there were a lot of female folks in Puerto Rico eating MREs for weeks. And you know, and that taught us something very important because we were here, we were in DC. It taught us that you can look at all the stuff from space, but if you can't connect with those communities and people with that knowledge, >> and that's where Black Marble evolved thanks to Puerto Rico because we began to realize that >> you can't do Earth action, Earth science to action without involving the local expertise. And you know at the time like I've grown now you know since then it's been nine

26:22years. >> Yeah. It it really it that personal connection at the time was very hard. But now it I've sort of seen how much we've learned from from these events and the world has learned. You know, the the world has become more resilient in a way because we know what happens when you have these large scale events and what how can that impact centralized electricities and you go to Puerto Rico, everybody has, you know, domestically, you know, every home now has batteries and solar power. >> Nice.

27:02>> Right. And so, and there was both local investment, federal investment going into restoring that. And you can see that in the in the data too, >> right? Really? >> Yeah. You can see that you see mount like the coffee grown mountain region of Puerto Rico, Alontas, they're they're now fully electrified with solar >> and every time there's an outlet, they're still on. >> They're still on. >> And you can see that in our anomaly course >> years later, eight years later.

A Golden Goose story: Adjuntas, La Perla and resilience

27:29>> Yeah. So, so that's like significant changes at the ground level because of um you know, I mean this is like a a classic Golden Goose story, right? You're chasing uh random holiday lights and it turns into this incredible um story where communities are changed forever. >> You know, now that I'm Frey, I love salsa music more than I used to when I was a kid. >> Okay. >> And there's this amazing singer songwriter. His name is Isma Lea. And now I every time I go to God, I have, you know, Amazon music on. I'm listening to Mayo. And he talks about this little shantita

28:09off of San Juan called La Pera. If you ever seen the video, music video of Despacito, that's right. >> Oh, okay. All right. >> Sorry. I I I do I have seen the video. Yes. And they talk about this town outside the walls, the old walls of old one about he talks about this community with dignity, you know, and it funny like it took me I had to come work at NASA to understand some of the things this man was saying that a lot of what we have learned from Black Marble are just basic things about protecting a community,

28:51right? Not everything that's important in life is the thing that shines the brightest. It's hard for me to translate that. Yeah. You know, >> um people can get hit really hard >> and they get off. That's a very American thing. You see it everywhere in hurricane torn regions, in tornado torn regions. People just build back better. They just get up. And again, the credility comes by understanding that community at a personal level. And we just came back from Puerto Rico last week. We open a an Earth information center at the local science museum. >> Okay. Nice.

29:31>> And we it was a small event. So we had to we had 50 registrations every hour. So we did 300 people, right? people from all over the island wanting to learn about black marble, wanting to learn about how can NASA data help their communities. I would have never thought, you know, we would be able to reach communities from Puerto Rico learning about what we're doing at NASA. It's just in >> that's that is that is really cool and that must have been so meaningful for you to go back to that community and >> and going back to a community where you

30:12see the outages that of places that you know streets that you have lots >> right right >> yeah it hits you

From 500 m to 30 m: Black Marble HD

30:21>> that's that's pretty cool I I did want to um one of the one of the innovations I think at least from what I read in this paper um that was kind of Like it sounded miraculous to me when I first read it. It's this figure where it shows the resolution of the of the black marble standard product which is like 500 meters. So half a kilometer by half a kilometer which okay fine that's believable to me right that it's like nighttime. You don't get a lot of photons. So >> how did how did we get here? >> Yeah. So but then it's it's completely unclear to me what data magic happened to get you to 30 m resolution. >> I can explain.

31:01>> Yeah. So that's that's why um >> this came out of that. Yeah. >> This came out of a >> Yeah. >> When we were talking to FEMA >> Mhm. >> and local communities, they're saying, "We love this. You're telling us where the lights have gone down, but your data set is so coarse. I need to get down to the house level." And I'm like, I can't help you, man. >> I can't help you. I only have, right? So, but then one of our team members say but but we have Lancet and Lancet another Noah USGS NASA mission can look at buildings at the Hector scale right you could see street

31:41lights and streets you don't know where this where those streets have street lights or not why didn't we merge those two data sets LA archive which is the the like the crown jewel of like our science is >> yeah it's it's an amazing going in >> and we're like well we know we can count on Lancet being good. >> Yeah. Because there's other guys like you and Lancad team who >> there are other big girls at that we know like oh they can get down the quality of the down to >> yeah their whole thing is quality of data. So >> so we know that if we if we can get imperous area from NASA meaning anywhere that there's cement and you make this assumption

32:23the more cement the more legs. Okay, I think it's a fair assumption. >> Fair assumption. >> Then now you can create a fused image between in that pixel anywhere where there's cement the attribute the lights of that value over that area over that region. This came out of a need because we don't have a black marble satellite at 10 m resolution. We do now thanks to NASA's uh commercial satellite data acquisition program. So we I can now this is the awesome thing about industry being part of NASA. I can now ask a company to take a picture at night and buy the data for

33:04research and the they go through a an award and then they make their satellite system available to researchers like so we have done as of last year there was a major power outage in Mississippi and our disaster response system was I want high resolution images and we detected power allergist with real real nighttime nights but between now and then we had we were basically creating a you know a a a simulated map. >> Yeah. >> And that that map does it's not SI tracer. >> Mhm. What does that mean? >> It means you can visualize it but you don't know what the values mean. It's

33:46just for situational awareness only. Nothing replaces a physical measurement. So every time that's why these maps you can see them in museum displays you can see them but analysis you still use the fire in a nearby need something of high integrity and you cannot use that assumption in purpose area lights and assume that that's going to apply everywhere >> right >> that's not the case in the across the world different countries use lights differently it that assumption only holds visually and I you know from And as a point of view is like then why are you doing it? I'm doing it because our users leave

34:27>> because a lot of our users want a 60% solution. >> Mhm. And it's good enough. >> The decisions they're making are like in and out. >> They can't wait 3 months for a science paper, you know, three years to make a decision. So we we were tailoring a solution and that required a lot of technical skill not just in building the algorithms >> but figuring out the data pipe mics to do this because it's a lot of it's there's a lot of high volume in there.

Ground truth, and a tractor seen from space

34:55>> Yeah. Okay. That makes a lot of sense though. So it's with that assumption and then you kind of do like a um you know the Beijian kind of analysis of like okay given this ground truth >> what's the probability >> that's what we typically call down scaling and in the sciences this is very common um you measure flux um different kind of fluxes um and you hel collecting flux data and then NASA satellites coming give you a big perspective and then You downscale it against that anchor and you can come up with maps of like ozone, nitrogen oxide, everything like there is it's just geostatistics.

35:38In this case, you do that but we always say buy or beware. >> It is useful as a tool. >> If you do analysis, you need to get groundbased data and collocated against the lights. And we're we're also doing that. I just came from Cornell University, one of our partners, and they took me to an experimental agricultural site, made me go on a John Deere tractor, turn on the lights, and they detected the lights from space. >> No way. >> I can show you guess ways. So imagine >> that's so few photons that doesn't make what? >> Wow. >> Because again, the sensitivity is not related to the actual support. a fire, a

36:21small fire can still be detected, but the scale at which is reported is broader because you're you're running a city, right? So, you can detect a 20,000 lumen light if you know how to shine it based on the geometry. So, John Deere has lights this way, this way, that way. We got to We had a Honda Civic next door. Couldn't detect. >> Couldn't detect that. Okay. But >> the John Deere had so many conical lines. >> Yeah. the yeah the signal or not.

Electrifying Africa: the darkest places on Earth

36:52>> Why does that mean to me? Well, if you care about electrifying Africa where the light night time signal is three times smaller than the moon contaminated signal, that's 10% of the human population right there. So from a sustainability planning point of view, if you think about 2100 demographically, Africa is going to be a large large contingent of human population. So if you want to measure those trends and how that's going to impact global economies at scale, you need to look at the darkest place in the world that are developing right now. >> Yeah. And that 10%. So you're saying because Africa, I'm guessing, is like

37:33near the equator. Moon contamination is worse. Is that the idea? >> Africa is still the last mile in terms of energy. I'm saying that Africa is still in there are countries that are still not electrified. >> Right. Okay. And so to like 10% of the global population still has no electricity. >> Oh, okay. So I'm >> I'm so you want to detect those regions, >> your data has to be of high integrity because those are very low signals. >> Mhm. And so that's why NASA expends so much effort in validating these results and understanding where's the threshold at which you can make science because if you start if if the World Bank is going

38:13to go to Africa and electrify Kotiva >> which they have they can then use black marble to assess the effectiveness of those electrification programs over years and say we made an investment of $200 million. We use black marble and now we're going to look and it still looks dark. We got a problem. >> Right. >> Right. Oh, it looks bright. Great. Can And then they begin to do assessments against okay, why did it work in this city and why it didn't work? And so you can start making really good decisions about the future investments of countries that are very, you know, that don't have access to resource. >> We can do that too as a federal government. If I can tell you where are

38:56the places that are most frequently hit by disasters that are constantly observing volatility, you can concentrate support, expertise, capital in those regions. That's that's what Earth observations offer you. It we don't make the decisions, but we're giving you a very strong information by which you can make decisions to help everyone. >> Yeah. And if the data can be trusted, then >> that's the big if. >> Yeah, >> that's the big if. Because that requires a lot of expertise and institutional muscle memory. You can't just calibrate an instrument like this and back fill it with somebody else. You need you need a team

39:39of people that does that. That's where NASA steps in because we made a commitment that data systems, data integrity is a capability that must be sustained for our nation. Just in the same way the US government has a vested interest in the GPS network. Like >> why? Because we cared you couldn't find this place if it weren't for GPS. It takes a lot of space hardware to run the GPS network and many different federal agencies own the capabilities around position navigation and timing you know about understanding you know

40:19and you know understanding changes in the atmosphere and how that impacts radioultation signals like everyone is involved in this. Black Mambbo does nighttime lies, but we are not the only agency involved in asking energy related questions or disaster related questions, you know. So, but we've been given the the distinct privilege to ask the weird questions. >> Yeah. >> The think differently about these questions. And I think that's really the proudest thing about winning this award that there were folks at NASA that believed in us even though our crazy at the time.

What the Golden Goose Award means

40:58>> Yeah. Yeah. So, I mean, I wanted to ask you, you know, now you're we're about to go to the Library of Congress um for the ceremony. What is what does winning this award mean for for you, for your team? You know, you've been working on this for what, like, uh 10 almost 15 years now? 15 years since that um the Ramadan photo at least. It's been a long time. >> I'm sure you didn't start expecting to win an award. I don't think anyone does. Um, but but what does it mean that that you're you're getting recognized like this? >> I think it validates something that our leaders at NASA have

41:38been saying for a long time, which is we have given we have produced a very amazing capabilities, not just black marble, but earth science in general, the fleet of NASA satellites. And we're going through this evolution because now one of our leaders says we're part of a broader ecosystem where you know there are many different actors and the thing about being part of the ecosystem is you don't no longer control the ecosystem. And it's a huge success story that our nation made a big bet around investing in Earth observations

42:22back in the '9s and ' 80s, you know, and different administrations came in and said, "Let's do a big B. Let's understand Earth as a system. >> Let's build large observatories the size of school buses. >> Let's deploy. Let's try to get all the and now we have all this data pride into the next chapter of us if our our next big bet which is AI and and and you know digit digital moanization all this we have we're one of the few countries in the world that has what matters in order to be able to have predictive um understandings of the future which is

43:04gold highly pristinely maintained highly integral product because with AI you know how it works garbage in garbage out >> yeah yeah yeah 100% worse garbage art >> exactly but with but the fact that we have produced and we had the foresight to know that maybe AI wasn't a thing back then but it is now >> and building metrics >> allowing people to create predictive understanding of risks and I wish we had that 15 years ago, but we didn't. But we had it now. I think that's what makes this award so special because it's really timed at a at a

43:46moment where our agency has shown and produced a lot of public value for an Asia. >> Mhm. Certainly >> a lot of times scientists don't get involved in that element of like hey how much you know we we you know we do the justifications we conduct reviews we do all that due diligence but to be able to represent our division in demonstrating the many thousands of times NASA earth science generates public value it's it's quite the privilege because we're not the only guys there are people who are who can monitor air quality at fine resolution,

44:26who can protect firefighters from the lines of fire using NASA satellites. There's so much going on and they picked us. But let me tell you, for every black marble, there's 100 other NASA Earth scientists out there who are just doing crazy stuff, thinking differently, and generating results that are directly impacting people's lives.

Thank you, and why showing the method matters

44:50>> Yeah. Well, we're we are huge fans of NASA at the podcast and I think all of our viewers are huge fans. So, I think you're doing you're doing a great service for doing this kind of work and triple and the Golden Goose Awards are just such a great way to recognize something like this. I hope you know we continue funding this kind of stuff. We continue doing this kind of stuff. It's it's an incredible privilege to talk to you. Congratulations on the award to not just you but also uh your co-reients. Um, yeah, this was this was really fun. I I learned a lot. Um, I hope you don't mind the technical questions, but I don't think you did. I think you're an engineer at heart. >> You've enthused me. I that's for sure.

45:30>> All right. Well, um, yeah, I'll be seeing you later today. It's going to be a fun time. >> Thank you. Thank you again. Thank you for all the work you do. I mean, it means a lot to us to share how we do our work with integrity because it takes years. >> Yeah. And I think >> and and for you to deep dive on the algorithm, it it means a lot because it shows that you're doing the due diligence that's required to build that credibility with your audience. >> Yeah, um a lot of the time folks, most of the folks tell me no one's going to read that. It's like people read it. >> No, I mean you'll be surprised. You'll be surprised at how many people resonate

46:12to the methods of how you get the data, you know, because as scientists, I think, yeah, I'm just going to go on a little tired, but like as scientists, um, convincing the public that what we're saying is not made up is, I think, as important as communicating what it is that we found. >> I think that's that's a very important point because you're giving us the opportunity to show that we're not using a black box. >> Yeah, I know. Yeah, it's not we're it's it's not made up, right? This is this is not just word that somehow it works. Like this is actual >> physics. Yeah. This is Yeah. This is just physics being applied in a very reasonable way. There's assumptions that are like open. that you can see what the

46:52assumptions are >> and most of I mean we it it's almost destiny but a lot of the physical processes and principles that the team we learn as grad students we learn from the real pioneers of earth observations that build those legacy systems that are now being retired and so that legacy I mean we couldn't take no know we couldn't take full credit if it weren't for those who you know were standing standing on the shoulders wrong. People going back to the 80s, the 70s were build the first radiator transfer model. Like I mean the science is just if you really want to start, you need to go all the way to powers, you know, like freaking way.

47:33>> Well, maybe we'll have you on the podcast for a much more lengthy conversation and we can start with at least radiative transfer. Um, but it was a pleasure talking to you. Um, and congratulations again.