YouthMappers: a global youth movement on open mapping for humanitarian and development action
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00:00
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Transcript: English(auto-generated)
00:00
Thank you so much, Luca. My name is Patricia Solis, and I am a research associate professor of geography at Arizona State University. I'm also president of the Instituto Paramericano de Ereorofia Estoria de Oia, the first woman president.
00:20
And also, and I wanted to say though that the privilege, one of the most privileged roles that I do play is that of serving as the director and a co-founder of Youth Mappers. So it's an honor today. Thank you for the invitation, Luca and Bianca, to speak on behalf of the voices of
00:45
thousands of students around the world. So I want to tell you a little bit about Youth Mappers and give you a couple of examples on how we are beneficiaries of the work that you do free and open source software and open data, and how we are contributing to that as well.
01:05
One of the main platforms that we use, not the only one, is OpenStreetMap. I'm assuming many of you are familiar with this. Students around the world are creating and using Open Data through this open platform. And in fact, OpenStreetMap was started by a
01:24
student, a graduate student, Steve Coast, when he was a graduate student. Some people think of OpenStreetMap as a map. Some of them think about it maybe as a platform, open source platform. But I like to think of OpenStreetMap as a community,
01:40
indeed as a community of communities. There are many different people who come to the map, who come to open source, for many different reasons. And Youth Mappers is one of those sets of communities. We ideated the concept in 2014, about the need for a place, a visible place for young people and university students within this really important community.
02:01
We were able to launch it in 2015 with the support of the USAID. And from there, we started inviting universities and student groups around the world to join us. They are chapters of Youth Mappers. Those are student-led, faculty-mentored, and campus-based.
02:21
They are independent in the sense that they get to choose what they do and we provide support for them. In all, we estimate about 5,000 students on 324 university campuses in 67 countries. As you can see, it's really become a movement across that time, opening up this space for students to participate in visible ways.
02:42
79% of those chapters are in so-called majoritarian nations, which is in lesser economic income countries. And 45% of our students are women, which is really outstanding in a field where you see maybe 5 to 10% in many of the tech industries.
03:01
The way that we work is also using students. And as our ambassadors and facilitators, they support each other. We have a managing director, a communications director, and that's all of our full-time staff. The rest of us are also professors, volunteers, a group of organizers, and we're responsible for different domains of support for our students.
03:27
This constellation here is also to show you that maybe some of your organizations are supporters of Youth Mappers in big and small ways. Of course, we have our co-founders USAID, Texas Tech, George Washington University, West Virginia University, and Arizona State University.
03:44
My institution serves as the fiscal lead, but there is a constellation of supporters here. So let me take a moment. If you are a member of a Youth Mappers chapter, a co-organizer, or a partner, would you please stand up really quick? I'd like to thank you.
04:12
So what do we do? Where do we work? What do we create? Basically, we track how all the activity that we create on OpenStreetMap.
04:21
Over time, we have created at least 16 million buildings. These are the usernames that we do have registered. We don't have all of them. This is a volunteer effort that does not cost money to join. but to receive any of the benefits they need to register with us. So this is basically where our students are mapping.
04:43
You can see there's production of open data in places of the world that had been under mapped in OpenStreetMap. We want to make sure that the work that is created by and with our students is high quality.
05:02
So we provide an academy which not only teaches technical skills on how to do this, best practices, how to engage with the community, communication, leadership, ethics, and we also validate the work that our students do with the dedicated team that's based at George Washington. You can see we're also using different types of open source software
05:22
with this kind of work, JASM in this case. In addition to that, we offer internships. So if you would like to engage with us on that, you can contact us. We have a program that is dedicated to supporting our female mappers and also in mapping for women's development.
05:41
We have a research program because many of our students do create and use their own data in the theses and dissertations and a fellowship program where we activate their leadership. Truly, the students are not just the leaders of tomorrow. We really believe they're leaders today. So they map both locally and remotely,
06:03
meaning that they might map their own campus in the field, in the field sites where maybe they are doing some research and they also help each other and mapping what we call remotely. So there's mapping with and for our communities on the ground and
06:22
also mapping with each other. It's truly, I think, what Luca had mentioned is a family and part of the community of communities. So I'd like to leave you with that description, the big thought that we don't just build maps, we build mappers.
06:41
Let me give you a couple of examples on how we do this. The first example comes from a part of the world where many residents do not experience the full benefits of global development. We do align our work to the sustainable development goals and in this case
07:02
SDG 7 affordable and clean energy and SDG 5 gender equality. We have a lot of partnerships and this is done under the banner of everywhere she maps and led by the chapters in Sierra Leone. This is Tommy and Tijidanka who are local leads.
07:21
There are many places of the world that do not have access to electricity and some of our students actually do have to go to campus to get access to electricity. They maybe do their homework by candlelight and we had the opportunity to work in Sierra Leone with the Minister of Energy to help understand
07:42
where are the places in this country where they do not have adequate access to electricity. This is quite a big job because not even the buildings and roads are mapped entirely in Sierra Leone. So this is our process, at least part of the methodology that uses some of the
08:03
free and open source tools that I want to just focus in a little bit on how we do this. The first step is we need to identify those buildings and roads and we use RAPID that helps us identify through AI
08:20
to see where exactly they should be and then we use human validation to tag and name those roads if that's possible to name them. Some of this work is done remotely and a lot of it is also done locally, especially the attribute tagging. So the team of validators also goes through and checks to make sure that everything is complete and up-to-date.
08:43
We're using the right satellite imagery and it's ready for on-the-ground capture of Street View data. We need to know where are the utility poles, but this is not something that you can see from a satellite image very easily. So we're using Mapillary to capture the field data. In just the first few months, you can see the progress of
09:06
imagery data that was available from a Street View just in the first few months in Sierra Leone by our students. In all, they collected over 200,000 images on the ground, riding around on their motorcycles, on their bicycles,
09:24
on 15 different sites to help identify where are those locations that do have electricity and do not. So with that information, we were able to work with Map with AI and a Mapillary tool that I believe was developed, at least in part, inspired by the challenges that we were having.
09:46
So we're really grateful to be able to influence some of that innovation and benefit from it directly. That looks like this where you can see the imagery and validate it. It extracts the utility poles, or what it thinks would be the pole, and then you can adjust where it actually is on the ground.
10:05
This is a big help because our students can work together, many chapters around the world, on trying to help validate and correctly place where the utility poles are. With that, we're able to use Xendi, which is a system topology on
10:23
how those poles are connected. This predicts how the grid network is laid out, and that can also be validated again through the satellite imagery. Finally, our team at ASU
10:42
uses QGIS to do the power engineering design. This is led by our colleagues at the LEAPS Lab, Laboratory for Energy and Power Solutions at ASU, to be able to calculate the cost, calculate the loads, calculate exactly what it is that we are going to need based on these kinds of quick estimates. In all, we're able to cut the
11:04
amount of time down using crowdsourcing volunteers to about 15% of the time and effort that it takes to do this in other ways, in the traditional ways of identifying grid systems. We also estimate that in these sites, it's not everywhere in Sierra Leone yet,
11:23
but so far, our work has been able to reach the communities that serve 1.9 people who are currently without electricity, and so when the Ministry of Energy is able to use this data, we believe that this will come back to help some of our students, some of the very students that were involved in the data collection in the first place,
11:46
using free and open source tools. And if you were a part of the state of the map, you were able to see our documentary. We showcased this example in the documentary. We're going to be releasing that online soon, so follow us on Twitter, on social media, to get word of that release.
12:07
Blessing here gives us some great words, so think about making light enter this place using data, open data, and open tools. The second example that I want to talk about is one that we're leading at Arizona State University.
12:22
Oftentimes, people think of missing data as being a problem of only in the so-called majoritarian nations, but also in places like the United States. We are trying to confront some of the largest existential crises on our planet, climate change, and we don't have the data that we need. There are hidden vulnerabilities,
12:45
and we need to find them and address them as well. So with this particular project, we're addressing SDG 13, climate action, and SDG 11, sustainable cities and communities. As I mentioned, it's getting hotter. There's been a heat wave here in Europe as well, but in the state of Arizona,
13:06
we're also seeing it. This is a depiction of the month-by-month nightly temperature from 1900 to 2018, so you can see that every single month those numbers are going up dramatically.
13:25
In our county, the city of Phoenix and surrounding areas, in the county of Maricopa County, in the county every year, we see hundreds of heat associated deaths, people who die because it is too hot.
13:42
Last year, we hit a record. Unfortunately, 339 people in just that metropolitan area alone died of heat. If you had a hurricane come hit your city every single year, year after year after year, and hundreds of people perish, you might want to pay attention to that.
14:01
That's what we're trying to do. So we needed to figure out what was happening where some of this information was not available geospatially, and so I pulled together 80 different organizations. I liberated their data. This is data not normally used for
14:21
scientific purposes, and we united it to just get a bird's-eye view of what are the places in our city where we need to concentrate most. Depicted here in white, this is the population distribution across Maricopa County, sort of an uneven distribution. And then we were able to
14:42
identify, over the last several years, how many people and where received or asked for and received utility assistance. That means that it's hard to pay your utility bills for air conditioning in the summer, and a lot of people need help. Feeling like this would be a group that is very vulnerable to the heat. And
15:05
then we compared that to the indoor heat associated deaths. Indoor, because yes, people are perishing indoors, from heat. This is data from the County Public Health Department. So you can see here, there's a lot of red dots over the yellow dots
15:23
indicating a pattern that people are asking for help where there are the most morbidity. However, there is this part over here, I'm going to highlight in blue, this square, where you see a different pattern. There are a lot of heat associated deaths, and
15:42
no assistance, basically no assistance there. So we need to know what is going on. The map is helping us make this vulnerability visible to us. When you zoom into the satellite imagery there, you see this picture. First of all, you might notice that there's less green area in this in this swath of
16:03
residencies, but going even closer, these are where people live in what are called mobile homes. These are manufactured homes, trailers, basically housing that is not built on site, and usually it is very poorly insulated. Many of them, especially those built before
16:24
1990, are not energy-efficient at all, and it's sort of a precarious type of housing. We've also, because it is more affordable kinds of housing, people who aren't residents of this type of housing are
16:43
twice as likely not to be able to pay their electrical bill in the summer. Again, they have to pay for air conditioning, and it's not very effective and very efficient. We learned that mobile home residents who perished were twice as likely not to even have air conditioning present, and those who did were three times more likely not to have
17:07
electricity even just turned on because being afraid of the costs. Most women died indoors, and seven in ten of them were at least 50 years old, so it is a problem of our aging population. So despite that only
17:21
5% of the homes in our county are in this type of structures, the morbidity rates are 40%, up to 40% depending on what year you're talking about. So a grave vulnerability that was hidden in plain sight.
17:41
We're trying to work through some solutions and get much better data, not just for our county, but for the whole state, and so we've initiated and activated our Youth Mavs chapter and our unit with the help of others and your software to try to identify exactly where those solutions, where are
18:03
the most vulnerable and what those solutions could be. So I'll go through this with you. First of all, we had to figure out the attribute tagging situation for OpenStreetMap. It wasn't really clear what to call this type of home. People may move it on or move it off. Many times they're actually static. They do not move, but they are not a
18:22
normal type of housing single-family homes. So with our Youth Mappers teams, we took one part of this area, one of the most concentrated areas, and did a pilot project and worked through how to exactly identify this. We manually did
18:40
2,000 building features using the hot tasking manager and clarified a tag that would seem to work specifically for this type of housing. You can see the tag info really started to increase exponentially when we started to map these homes in early 2018.
19:03
So the next step was, this is impossible to do for the millions of homes in the United States by hand, so we took the Microsoft AI building footprint data to try to extract the building features and then locate, co-locate those with other data that we had where we thought that it was likely that we would see
19:22
manufactured homes, mobile homes. That means we had to overlay, query millions of records from our tax rolls, and also, we took, I didn't depict it here, but from the zoning, city-by-city zoning regulation so that we could guess which
19:42
blocks had mobile homes in them. I know you're not going to believe me, but this data didn't exist before we started this. And finally, we knew that we were missing some, so we just launched a campaign using MapSwipe to help identify where are the missing
20:01
homes. If they're not a part of an organized park, they might be on different kinds of properties, and so we encourage you to download it on your phone and join us. In the first week, we had almost 250 mappers already and got a third of the first, the pilot task completed. You'll see a tutorial on how to identify those from remote imagery so that you can help us find where we're missing from those
20:26
blended data sets. So from there, we're going to validate a statewide database, do a little bit of analytics, and try to get a really good set that would include demographics
20:42
or an estimate of demographics and also the costs. This is really important because in the United States, there are 20 million and growing residents who live in this type of housing. You can see somewhat of the distribution. They're in places where it's already warmer in the south and
21:01
along the coasts. But if you're following what's happening with climate change, you'll also see that this coincides with where some of the most dangerous heat waves are expected to be happening in the coming years. By 2053, these are the places in the U.S. that where two-thirds of the U.S. population would be at risk to experience
21:21
more than 70 consecutive days over 100 degrees. That's about 40 Celsius. So I mentioned costs and solutions. And of course, we've been trying to activate our whole university to identify everything from policy regulation to building fixes to energy efficiencies,
21:44
activating the city to include people in these parks in their public health campaigns, workshops for residents, and many different kinds of activities because there's a lot of stakeholders in this space, and
22:02
we were all missing it. There are about 88,000 mobile home residents that have already benefited from some of these solutions, especially in the city of Mesa. We have 82 different partner organizations, and we're activating about 40 different research students throughout the university.
22:22
This is really important because there are $3.6 billion in available assistance at the national level, but that is for low-income housing energy efficiency and weatherization. But people who live in mobile homes and trailers are not eligible for that on the basis of the type of housing that they have.
22:46
So we also made a documentary about this one, if you'd like to learn more about how that process unfolded, and we do have a heat solutions guide. So if you're living in the part of the world that is going to be experiencing some of these dramatic temperature changes,
23:01
hopefully we're not just the canary in the coal mine, but we can help find some of the solutions together. Also some features in national news to learn more. Happy to talk with you about this. Our youth mappers, as you see, have been inspiring all sorts of really important work using open data, open tools, and
23:27
these two examples were just two of many, many hundreds of things that our students are doing around the world. And a lot of them are important for the Sustainable Development Goals. And so inspired by this
23:44
network, we put together a collection of these in a book that is also going to be opened as open access. So look for that. Again, follow us on social media and for the release of that link. We do have an editor's copy at our booth if you'd like to see that.
24:01
There were 68 co-authors in this book, many of them from those majoritarian countries that I mentioned, including Tommy and the students in Arizona. I'd really like to think about their voices. Many of them are here today at this week, and we would really like for you to speak with them and learn from them.
24:27
We've learned a lot from them. It's been an incredible experience and a humbling experience to see the world through the eyes of young people and the innovations that they can create. They're not just human sensors.
24:43
They are innovators, and they have intellectual as well as technical abilities to contribute. Of course, we do this as a team. You are a part of that team. Your software, your data, your tools are a big part of what we are able to do.
25:03
And we'd really like to team up with you. Think about how we can activate our students. In the end, the future that we leave for the future of Phosphorgy, the future of OpenStreetMap, they're actually here present with us today.
25:22
So help me think of ways that we can engage them, make sure that they are part of the leadership, and be a good ancestor. Thank you.