 Yeah, I'm Ian Shuler with Development Seeds. We're a shop that does a lot of work with open data and open source. And I'm here to talk to you. I guess we've heard about water. We've heard about air. And now we're going to talk about land from space. So we'll have basically everything covered by the end of the presentation. Let's see. Imagery data, whether it's from satellites or drones, is some of the most valuable open data that exists. Location-based data in itself, GPS data, is estimated, depending on who you talk to, between a $40 to $100 billion dollar year industry. And the data that comes from satellite images is just as valuable for uses in everything, from agriculture to forestry to mining to public safety and others. And so there's tremendous economic value and social value to be derived from imagery. But it's been very difficult to work with. It's been a set of data that has been in the hands of a few. And some of the things that we're trying to do is to make it much more widely available. So every day, there are 175 Earth observation satellites that circle the Earth and take pictures. Take pictures of things like this and like this, all throughout the world, blind to borders, blind to economic ability, constantly collecting information. Some of that data is coming in as raw pictures like these, but also satellites have the ability to see a spectrum that the human eye can't. So you can look at ultraviolet light. And you can look at infrared light. You can look at soil moisture. You can look at elevation. You can look at other things that tell you really interesting things like the health of vegetation or where might be areas that are prone to landslides or where areas that there seem to be economic development. And that data together is of tremendous value for understanding the Earth and understanding the Earth's populations. This data is tremendously valuable to people who are trying to understand the effects of climate change, people who are looking at conservation of forests of sea, people who are managing wildfires and trying to work through disasters on the ground, again, whether that's wildfires or whether that's understanding the effects of flooding in areas that are most likely to be impacted by upcoming floods. Putting that over imagery gives you an idea of what the likely impact of that is going to be. Or you could look at use it from an accountability standpoint as well. So this is an example in Mexico where there were two hurricanes in a row that hit Mexico in 2013. This is an example of taking that historic imagery and comparing that to the locations of projects where the government funded reconstruction projects. So to see was that funding spent in places where it seems to be appropriate? And to be able for the public to be able to compare that public finance data with the actual storm events to drive additional data or drive additional information. Here's an example of using 20 years of open nighttime imagery to understand the development of India from 1992 to 2012. So there's a really great data set, the MSP, of nightly satellite imagery across the world. It's a data set that's messy in a lot of ways, but it provides a really, really rich set of insights into development across the globe and gives you the ability to look at specifically where is their light at night, light in the 8 p.m. to 10 p.m. time when people are turning on the lights. And that allows you to see a lot of different interesting things. One, you can see Diwali from space, which is pretty cool. The festival of lights is actually visible from space. But another thing that's quite interesting is you can look at it to see how resources are allocated. And so here's an example of in Uttar Pradesh in northern India. The yellow line is the average light output curve over 20 years for the Uttar Pradesh or a constituency, Hardoy and Uttar Pradesh as a whole. The red line is one constituency within Hardoy. And so you can see that this period that spans between around 1998 and 2001, it bumps above the average. And so you can start to ask questions about, well, why did that area have a higher level of light output than others? And it turns out that that area, the MP from that area, was put in as the minister of energy for exactly that period of time, where there's a bump in the light output from that area of the country. And as soon as he was no longer the minister of energy for Uttar Pradesh, it goes back to normal levels until it bounces again at the more recently in the last few years. So we're not sure what happened there. Maybe a cousin was able to get the ministry at some point later. So what to do with all this data? Again, there are 175 satellites circling the Earth every day, generating tremendous amounts of data. What does this look like and where is this coming from? And to what degree is that data actually open? Well, the majority of open data still comes from government sources of one sort or another. For imagery data, and the RBG, the pictures of the Earth, a lot of that comes from the Landsat program, which has been in place since 1972, collecting more than 40 years of imagery that's been run by the US government. Exciting, there are one of the exciting things that's happening in the space is that the Sentinel program, the European Space Agency, is an ambitious program to launch seven different satellite missions before 2021, which will collect even better imagery, higher quality, higher resolution imagery. The Sentinel-2, which was launched last year, which is one of their main imagery gathering satellites, is already producing data. And that data should come online in a more programmatically way within the next few weeks. Other satellites that both the European Space Agency and NASA are putting out are looking at soil moisture, are looking at atmospheric conditions, are gathering information about more climate and weather effects. And so that will also be incredibly valuable data for researchers, but also for the public at large. Commercial, there's been a growing commercial industry around satellite data. There's been a bit of a revolution in how satellites are built and launched. You've seen the rise of small satellites, which are cheaper. They're easier to build. And you can deploy them in droves or in fleets rather than having one big satellite that's collecting once a day. You can have essentially continuous coverage or daily coverage of the entire planet. You also, the greater availability of launch vehicles has made it possible to do this. So with entry of companies like SpaceX, it's easier to get things into space, and that's creating a lot of data. To date, there aren't many companies that are providing open data in the satellite space. There are a few examples of this being the case, primarily around natural disasters. And so around Nepal, for instance, a number of satellite companies, Skybox, Planet Labs, and Digital Globe, each release publicly available imagery over Nepal to anybody for whom it could be of use. And so around disasters in particular, you do have a bit of an example or a bit of a history of providing open data. It seems that there's an interest in expanding that further, and it's likely to expand over the next few years. The number of companies have made commitments about data that they would release in the public. Skybox has a Skybox for a good program, and they are already producing, releasing imagery of developmental value or of emergency response value. Planet Labs recently, the United Nations Global Goals Summit, made a commitment to release $60 million worth of imagery. Akila Space is a company that's not only interested in releasing imagery, but actually the hardware designs to produce satellites, although that's being held up by regulatory issues. So you have people on all sides who are seeing the benefit of open in aerospace and the benefit of this open data. And I think that increasingly we'll see commercial providers also involved in the open imagery game. And interestingly, hobbyists, and this is a bit where drones come in, it is easier for people who are interested in providing imagery of their or wherever the world that they're interested in collecting it to gather that information and to provide it openly. Drones have become extremely popular as a hobbyist activity as well. And we're hopeful that in the same way that individual mappers and geographers and individual community organizers help to create an asset as rich as open street map of address and map data from around the world, that we're on the precipice of being able to do something similar where we can actually have an evolving picture of the entire Earth that's being maintained by people who have a commitment to open data in public domain. And so the hobbyist side, I think, is extremely exciting. The trouble is that imagery data is still really hard to work with. There aren't a lot of very good tools. It is very heavy. It is expensive to maintain. It's expensive to move. And so part of what we need to do if we really want to power an open data revolution around imagery is to make it easier for more people to be engaged in the process. Some of that starts with government and making those rich stores of government data, sentinel data, Landsat, and other data sets more accessible. One great example of this was earlier this year, AWS committed to taking the last two years of Landsat imagery, Landsat 8 imagery, and putting it on AWS in a way that it can be very easily programmatically accessed. And that takes it from being where it was technically available if you were willing to navigate the USGS's system and to learn how that worked and to go in and download that data yourself. It made it more programmatically available and easier to navigate and easier to work with. And that allowed us to build other tools on top of it that would make it more widely available to other audiences. Sentinel data is not quite at that point yet. I think sentinel data, well, the license is right. They have the license right for public use, for commercial, all the things you would want to have. The actual technical infrastructure to make it readily available isn't there. And so this is going to be a great thing for Europe to take on is to take that fantastic data that's coming in through the sentinel program and use that as an engine for geo growth in the open geo industry across the continent and globally by making that data more accessible. Currently, the situation with sentinel data is with still a lot of NASA and USGS data is that if you are a researcher, you're a scientist, and you have the time to learn how to use some very specific tools. And if you have the patients for dealing with the registering and getting approved and dealing with the system, then you have the ability to do some very, very powerful things of that data, but it's not accessible to everybody. And so some of the things that we were able to do, again, off AWS is to make it available to two very key markets, or two very key sets of people. One is individuals who aren't experts, who aren't GIS experts or remote sensing experts, but who want to be able to access this information, a journalist, or a community organization, or a company. And so building very user-friendly interfaces, this is an example of Libra, which is an entirely open-source tool practicing Landsat imagery. This makes it much more easy for people to find and begin to use that data, or make the data programmatically accessible, so it doesn't actually require a human at all. Another set of tools we built called Landsat Util allows you to script out the use of the collection, the processing, and the publishing of satellite imagery to give those building blocks that allow it to be more easily plugged into other things. And so with those together, we were able to build two very specific tools that we think are useful to this audience. One is Open Aerial Map, which is an index of openly licensed satellite and drone imagery around the world. And so here's an example. In the Philippines, a drum imagery that was collected after Haiyan could be put online to allow other people to use that as a tracing layer for OSM, or allow researchers to be able to look at past data and projecting future information. And you have all of that archive of data through time, so you can see data from different points, pre-disaster, post-disaster, just the evolution of an area over time. That is, again, is a place where you can collect available open imagery. This is particularly useful for drone operators who are gathering a lot of imagery, but don't have an easy way to make it available and make it discoverable to a wider audience. And so Open Aerial Map is an attempt to have a home for all of the openly licensed imagery. And this is something that we are a technical partner in, but it's being done in partnership with a number of other organizations, the Humanitarian OpenStreetMap team, Planet Labs, and a number of other groups. Another example is a commercial example of an organization Astrodigital, a company that took the tools that we developed in order to make monitoring possible. And so this is an example of setting up a way to monitor a shale field for any new imagery and do automatic processing of that imagery so that decision makers in the field can have access to imagery and data derived from that imagery immediately. And so that, again, gets the question that I had posed earlier today of how do we take open data and actually make it actionable, actually make it answer questions for people. So that's where I think we see the field right now. We think it's a really exciting time. If you're interested in joining, there's an event next week in Washington, D.C. for anybody who happens to be there called SAT Summit. We'll be discussing some of those things and anybody here who's interested in going can get a free ticket using that coupon code. Thanks very much. Fantastic. Thank you.