 So first of all a warm welcome thanks for all of you for joining us and let's start with a brief introduction So I move to I'm the founder and of geo awesomeness and Alex I'm Alexander Włóczkowski. I'm a director Working at Pricewaterhouse Coopers leading the team that is often Well described as the coolest team across the whole firm, which is a global center of excellence in drone and satellite technologies super happy to be here and discuss with you guys Hi, I am Laura. I'm co-founder of tilebox So we provide a software framework for companies to develop their own data pipelines in a reliable and scalable manner And yeah, really excited to be here Okay, hello everybody, my name is Anit vanja I work for Planet Labs here at the seed in Germany and there specifically. I'm working in the Earth observation lab, which is Planet's R&D group so to say on We talk about it what we are doing there. So happy to be here My name is Sabrina and I'm a product marketing manager at up 42 for those of you that don't know up 42 We are a platform and marketplace for geospatial data and analytics I will talk a little bit more about what that means in a second Really excited to be here and take part of this panel Hi, my name is Arnis. I work for European Agency for the space program quickly for those who are asking what exactly is this formerly we were known as GSA and we're operating the Leo A constellation of Genesis satellites and a diagnosis them and two years ago. We're renamed to EOSPA and some additional responsibilities were put on us with the within the Earth observation field and My responsibilities are in that I contribute on basically Promoting the uptake of Copernicus to to those user groups that it's not currently addressing. Thanks Okay, I think Arnis. I don't think you need the mic Maybe can you like keep the mic to the arena and then check if it if your mic is working? No, what okay Looks like the two of you would need it But okay, I'm sure we will figure out a way and just FYI and the way we've structured the panelists We basically will have 30 40 minutes of questions with the panelists from my side And I would love to open up the floor if you have any questions that you want to throw And we will make sure that we have a second mic to run around so keep your questions in mind And we will get to them And so let's kick things off and it With you because you are the innovation person and you're from planet one of the biggest data providers out there right now so let's start with how this Observation the imagery the high cadence has changed environmental monitoring and reporting especially when it comes to sustainability Okay, so for those who don't know what planet is doing So we are an aerospace company and over the past decade We have built a set a constellation of earth observation satellites So optical satellites with three to four meter resolution and others But I will mainly talk about the one the three to four meter resolution What does it mean our mission so we we started building this constellation with the mission to image the earth once per day And I mean image the entire land masses once per day and we can say we have achieved that objective We are able today As I said to image every point on earth and in average have acquired a whole archive which consists in 2000 images per location on earth and with that we are we are able today to provide a At the very high spatial resolution a very high temporal Cadence of observations that allows an almost real-time monitoring. So I think it's we're making that data available Through to our customers, but also through specific programs like the Nikfi program, which is the Norway Norwegian international climate and forest initiative To map for example the whole tropical forest So it's basically become we take the best image shots from these Daily image acquisitions to combine monthly mozaics and through this provide access to Enabled users to monitor the tropical forests, which are the earth's lungs on a relatively high cadence and that globally so I mean this is Just to say that it's the high spatial resolution But high temporal cadence and also making that data available through our platform and through specific access programs And how has this like for your customers were working and reporting people like pwc Made a difference Alex Do you think that the high cadence is a major selling point for environmental reporting? you know so Yes, and no right so environment does not change overnight Right, so so you don't really need to monitor it's on a daily basis But you need to have a high trust for the data that it provides So the more data that you have to verify the the results of your analysis the better, right? So Yeah, I think it also depends on the type of applications. It's true. You don't need it for each Application for example for crop monitoring you a higher cadence is definitely more useful considering the dynamics of a crop for other changes it might not be necessary, but By just having the possibility to access an image every day It also allows you an almost real time or it provides you the possibility to monitor something change happening Whenever you need it so not the need to wait for an image to be acquired Let's say in a week or so, but to rather also it gives you the tool to to react also in almost near real time so to say Interesting to bring them, you know given that that you at up 42 focus on a platform driven approach How do you think the user requirements the fact that now we have high cadence imagery is shaping the industry? Is it meeting the needs of the ESG reporting industry? Or do you think there has to be more done in terms of the data in terms of the approach in terms of the APIs that are available? So yeah working at a 42 and of course representing a platform and marketplace I think for me. Yeah, this is a lot has been done already But even more can be done when it comes to data access standardization of data So when it comes for example to data standardization, that's a very important topic for us At the 42 and very topic closer to my heart. So adopting geospatial standards to make it easier to work with Data, so for example stack standard it's cloud optimized shield if so for me That's that's a topic where we will continue to see more advances and more can be done But also yeah making it easier also to access more data sets so we talked a lot about we gave some examples But more data sets especially when it comes to sustainability for example thermal data Making more Making more out of star data as well But as well as hyperspectral data also topics that I'm personally very excited And I think it will see more in the future and more can be done to really Make sure that we benefit from earth observation data and unlock the social economic benefits for everyone So Arnes maybe switching more from like say the corporate perspective to more of the European governmental Scientific perspective at use but one of your main directives is to drive market access to drive more applications, right? So you have high cadence imagery from planet you have data platforms like up 42 How does you spa approach these problems? How do you make access to data easier? What what is your approach? in the general approach is of course to to look at that what's needed and Not to go from the from the technology push approach, but try to follow this Need led approach of course in the in the sphere of sustainability regulatory Push is is There we have since it's a you know the tragedy of the commons it's an economic problem that we're in with the climate change with the with the Emission and we have to we have to somehow think that together the Didn't the needs are there, but they are driven by by regulators outside beyond the US based policy and we are there on the somewhat solution side and we might help with some of the you space program elements like a layout like Copernicus But also take wider industry and support adoption of methods at one industry and I must say that I See that the current regulation Across to the elements of Green Deal. It doesn't follow really a prescriptive approach It follows where you prescribe technology how to either? Enforce a regulation it leaves the open how you can comply and prove that you are you're actually complying with the with the ethos of regulation and I think that's that creates confusion on the industry side on the user side But that should be looked as an opportunity to actually innovate and and not to be tied into some prescribed technologies Not to get into precise technologies and Arne spoke about the market pull and Laura You are a startup you've raised a seed around to make space data infrastructure easily accessible So with your goal to revolutionize the space data management, what challenges do you see in the market? Why did you enter the market and what are you trying to solve? Yes, so common challenges. We've seen is first fast and high performance access to data in a way that it also Improves the developer experience of working with that data and by data. I mean Ro payload data telemetry ADCS and so on so we come a little bit earlier on that Yeah, we've seen companies facing delays of months just to access a subset of their data And yeah, and this has consequences on the delays on product development and also revenue generation another common pitfall and Challenges that we see is how to effectively Distribute work across infrastructure So how to schedule near real-time products in a way that reduces friction between the teams that are currently working on those products That it reduces manual input and that it's also scalable whether you have one satellite or 15 And the last one that I've seen is basically how to also effectively reduce the Data volumes that need to be downlinked So basically on board processing right now means the scripts that call out co-processors and we really think there is a lot of Room of improvement in there and that's something that at least the tilebox. We are we're working right now Yeah, I mean we have on the panel two of the biggest data providers in planet in a new spa Is this a problem that you're also tackling should Laura be concerned about your efforts internally to make this infrastructure Easily available or is she working on a problem that's kind of outside your preview? Maybe I know do you want to start? Yeah, no, I think for us for sure as We are producing a lot of data on a daily basis. It has been part of our Evolution also to I mean the scope the focus was also the objective was to be able to serve that data also as it is acquired so we have Moved away from this being a data provider satellite building satellites data providing data only Towards what we call in our north star strategy earth data platform. So it's clearly Our idea also to to provide these data sets together even with first derived insights To enable a customer to build their application on top of it. So for sure this platform aspect Also accessing data building applications that are scalable without the need to download it, etc. So not Doing it the old way It's definitely one of the things we are trying to tackle and Because of that we we have recently also a joint forces with synergize who has built the Sentinel hub Which is one of the earth data platforms? Providing these processing capacity also so because we thought together we could reach The goal much faster than we can as as planet only so for sure it is something that's In our genes also how to how to deal with these aspects and I think Yeah, I think that that is an evolving Let's say domain for sure Continuously challenged by the amount of data volume that are produced by the different actors. So Ernest, do you want to react? Yeah, just I wouldn't Put us as opposing on opposing sides the industry in general and and for example Copernicus as a public publicly owned earth observation system because at the end of the day Copernicus actually built by the industry itself at the end of the day and But what is there the public remains it retains control over this this thin layer of of And and some ownership of the technology but so to ensure long-term viability of the system Which is very crucial for for multiple policies both in with the relation to the green deal to safety security. So At the end of the day, it's the industry that builds and if the industry can offer some something better better components that Copernicus will also improve but it will remain as as some But basically essentially a public Service but built on on industry Interesting Alex as a person who's working in the consultancy industry How is this data aspect of it the access of like what Laura is working on? How does it affect you? Is this a problem that you face or is it? Somehow mitigated because of the amounts of data that you use No, I mean working with data at scale is always difficult, right? You need to have the right tools the rights of processes the right processing capabilities so the more solutions there are that actually Enable you to automate the work and make your life easier and Make Other the work of people You know automated and let them focus on actually the the the hard stuff on know the the analyzing the data and thinking about all of the Applications and getting the right insights and knowledge out of it rather than no processing and tools and all the things that are really no Redundant and that we don't really need to we shouldn't we shouldn't really need to know focus on it This is this is something that no big organizations are looking for And we also don't want to have all of this data stored in-house, right? We want to use Planet servers or solutions such as platforms such as up 42 or different tools that will enable us to Process it at scale at the end what matters is not really know the data and the processing But the insights and the knowledge that you are deriving out of this data, right? And this is what is really creating the value, right? So The the consulting sector is always where the value or focuses on where the value is, right? So this is why We are often using now different solutions and tools that that you guys provide and offer Nora getting back to you. Was it your experience so far from investors? Do they ask you similar questions in terms of who your competitors are or is it more that the value understanding is already there in The market when it comes to space data and access to it both We organically started bootstrapped so we saw the need and we started building towards that need We got early customers and then of course once things start going you really need to it's a big issue, right? So you want to grow fast and you were on a you want to be able to capture clients and to deliver to them So that's why then when investors ask Yeah, the market is ready the market is there and it just keeps growing if you think about the projections of Amounts of data that are gonna come it just keeps increasing data never reduces We better have good tools in place to be able to handle it efficiently Interesting so we've spoken quite a bit about Data and now I want to shift gears a bit and go into a topic that not a lot of people are interested in but I'm personally really interested in Which is policy making an harness you have a lot of experience in remote sensing and you've been working for a new agency for a while now So how is earth observation data like influencing policy making at the you level especially now given the new EU deforestation Are they are going to be more such earth observation driven policymaking? What's your opinion? well, of course the earth observation data does influence policy by informing policy makers policy makers have to be informed in order to make reasonable policies So and and Copernicus as one of the earth observation systems a global one Does contribute a lot with they with a very long time series for example of of climatic parameters of environmental by job by a physical parameters and If you have a baseline you can actually assess if something is changing in an impact of the policies is Being achieved in some other aspects. You have to Look at the impact of policies but you also have to enforce for some of the policies and there sometimes the information has to be much more detailed much more local and I see that there is a lot of opportunities for other providers. Maybe we don't have the The global look as we have To Alex do you agree? Do you as a from a consultancy perspective? Do you also see policymaking as a tool that can drive the use of earth observation for sustainability for ESG reporting? Yeah, I mean for sure, right, however So how it's how it's defined today I mean the policies do not say that you should use earth observation data, right? The policies say what you need to report however, like when you gave the example of The deforestation policy So there is no other way to monitor it Effectively at scale then to do it using earth observation data, right? So on one hand the the policy is not defining it. I think you've complained about this a Little bit initially and on the other hand now it is pushing the industry to use this data Which indeed creates some confusion and no lack of standardization and and and so on But on the other hand, no, this is something that we see no gradually No kind of no growing and adopting and there are always first adopters that that want to know establish some sort of Standards or press precedents know on how do you how do you report and then others are following? So this is something that is right now organically happening and now we see some of the the big players on the market already Reporting on it using earth observation data. I mean for a while now So Yeah Okay, and Sabrina. Do you see an uptick in more clients looking for data? Especially because of the new regulation. Yeah, I would say yes. So for example with the new regulations now that Come with sustainability focus this year. There's definitely more and more interest But for me in addition to the policy is something that I wanted to mention now It's also we shouldn't forget that one of the main objectives that we should be all doing is really making it easier than ever Truly access data and work with it Insta extract insights from the data at scale So not only focuses on what the policies are there and there are plenty of course for deforestation Also a lot of policies when it comes to mining and other industries But really like we thought leadership showing the use cases showing what you can do with the data and enabling more and more downstream integration applications for for customers, I think that's also where we can influence a lot and Yeah, we can do a lot especially with platforms and marketplace is like a 42 And it does such policies somehow influence the algorithms that you try out at the your lab or is it? Doesn't really matter because the policies are always a few years late and your work is always a few years ahead. I Mean, I think for sure we are Watching also, we are aware of what the policy is recommending But I think we are also an ambassador in that sense that through the data and what we see Customers do with the data what we think we can do with the data. We are also Communicating clearly about the potential the data set has and I think it's it's maybe not the policy directly recommending to use also observation data, but there's Also, I see it in the disaster framework In the disaster domain there are the Sendai framework where it was clearly also recommended to use Earth observation data to monitor disasters You said it in the different station Contacts, so I think also in cup so agricultural monitoring of observation data is recognized as a data source because it's it's a neutral Data source which has a lot of power if interpreted correctly, so of course that's always the last mile, but For sure. This is We're happy to see that it is continuously picked up as a data source That because we sell also observation data, but also because we believe in the power this data set has now I guess everyone today when we were walking around in the geo we saw a lot of drones and When we talk about Earth observation we tend to sometimes only focus on satellites and not the drone aspect of it And Alex luckily for me and works a lot with drone data surprise surprise So how do you see this the aspect of drones? Is it more a complementary or is it already challenging? Satellite-based observations in different industries, especially when it comes to again ESG and sustainability reporting insurance for example, yeah, I mean so so the two data sources are Fully complementary right and basically serving different purposes and different use cases, right? So you would not use drones to monitor on a large-scale area types of challenges for example of deforestation, right? You'd use satellite data to do that, but when you want to report, I know on specific emissions generated by your Set of factories in a given areas then no drones would provide you with the right payload the right sensors to actually You know do that. So these are no two totally different data sources Serving totally different use cases Unfortunately, you know that the market know very offensive a little bit as a competing data sources Why I think it it should not be treated this way. These are basically Totally totally different and I mean we are working towards educating the markets Which data? Would be you know the optimal for for which specific use cases and which scale of use? Yeah, the entire time that you were speaking to bring I was agreeing to you So I was what do you think do you also are a big fan of drones? Do you want to see more drone data? Of course So I'm personally of course biased, right? But I fully agree with what you were saying Alex right the complementary approach So for me using for example satellite data to monitor at scale whether it's deforestation or infrastructure monitoring and then really using drone or other area of resources to Focus on boy are smaller a why I think and really improve efficiency safe resources safe costs So you have also full believer For that complementary approach and I really don't see those either or Yeah, so just that's why I was nothing on the whole time regardless of the use case I think there is a lot of opportunity for Using different types of remote sensing data Laura how is it a tile box? Of course as a startup you have to focus somewhere So you're focusing on space data, but do you also see yourself? Able to work with drone data, or do you see it as a completely different challenge? Definitely. Definitely. I think they have they have similarities in terms that For from both drone and satellite you get raw data and you get telemetry data from drones probably from several drones and then you need a Flexible and high-performance system to create other products. So that's similar one difference that I see currently is that the process on how to get the data close to Scalable compute so in the case of satellites, they benefit from established network of Space service providers and ground stations that have high bandwidth towards cloud services And I think in this case maybe for drones It's more relevant on-premise deployments. So that's one of the difference that that I currently see Let's stay with scalable computing. Do you think as an industry? Do we make maximum use of scalable computing or do you think like there is a lot of room for improvement? I think there is used there is there is used made of that, but I think there is room of improvement in terms of how to Schedule it properly how to not die out of cloud costs And yeah, how to how to more effectively process data? That's basically one of the course of tilebox how to more effectively Distributed in a distributed manner, which is one of the course of tilebox across clusters and across even clouds how to distribute that data processing Interesting, and that's one of the reasons why I wanted to have Laura on the panel because as an industry whether you call it your Spatial or Earth observation we tend to focus a lot on the data But not on the computing aspect of it And I think we can learn a lot from computer science. So we've been speaking a lot about data So maybe we should switch a bit more into the Computing the aspect of it and I'm going to start off with you to be now And what is like for you as a data-driven platform as a you know, just special marketplace How do you see AI algorithms? What are the new technologies that you see popping up in your marketplace? So For me like platforms and marketplace can play a very important role in really removing the technical and economic barriers That still exist unfortunately to accessing geospatial data So some of the new things that I'm personally excited about is more and more data sets that are coming up I did mention when when we were talking at the beginning of the panel Thermal data sets also hyperspectral. So for me those Data sets regardless of the use case whether it's monitoring efficiency of solar panels, whether it's obviously wildfire Huge topic right now with availability and more and more data sets like this I think they will play a huge role when it comes to sustainability Also for me we did touch a little bit briefly on that but combining different types of data sets or whether that's optical and SAR or Also, as we just talked about using potentially satellite data and then more targeted drone Data for more specific AOI is something that I'm really excited to see And I also did mention at the beginning geospatial data standards That's personally something that I think there is need for more standards whether it when it comes to AI and adopting AI for At scale, but also yeah when it comes to really like making it easy to work with Geospatial data. So I think companies are still struggling with different data types different data format So standards are just a cloud-optimized duties is something that I'm personally really excited about and I think something that we'll see more and more Arnes, how do you see it? How is use part tackling AI in Earth observation? Is this the topic for you at Muspa? Directly We are not engaged with producing any of the Copernicus services While we are working at Facilitating reuse of that and there of course we would we want to and can facilitate the use of any method Including in machine learning to to create value and we have actually some instruments in horizon Europe calls That some of them are actually open now, so check it out And maybe you your company institution can can contribute somehow Are you aware of any open calls right now? Exactly, yeah You know AI is like as a is a method that can be applied to almost anything and to be to do things better Anyway, and then and therefore I see it as a pervasive technology that should be everywhere with caveats, of course For example, I've seen in safety critical applications There are additional requirements towards application of AI for example But that's already like application specific and we don't go there Alex, how do you see the use of AI in the industry with We're either in the drone industry for autopilot applications or also the satellite industry No, so so I mean obviously this is a big promise of future automation, right? And today AI is good at solving some simple problems, right? So for example Detecting no forest, right? This is a fairly simple problem But it's still not there when it comes to you know solving more complex problems know with Objects that are more diverse and no different environments and so on right so I Would wish that we would be able to do much more with deep learning today But the reality shows that no there is still a lot of human interaction and analysis today required to work to solve this more more complex problems, but I think that we are also at the beginning of this Journey so when we look at what happened over the course of the last year with generative AI Right and no things that are discussed in the industry where you would be able to know ask any query to satellite data and no receive some Meaningful no answers. So so I think that this revolution is actually still ahead of us and The the real value that that will come with the using satellite data at scale Will still I mean it's still not not really no use. We are just scratching the the the surface for now. So I Expect a lot actually in the next three to five years in terms of the automation that is that is about to happen and No, the the whole value that will be extracted I'm both from from satellite data and and when it comes to automation related to drone data Okay, speaking of generative AI just a quick show of hands. Who of you has been using chat GPT the last couple of weeks months? Okay More or less everybody so on it so everybody is using chat GPT When can we expect something similar from planets so that we can just type over Earth observation query? We're thinking about it No, I think it's one of the topics which In my group especially because it's There's several machine learning engineers experts and deep learning Also thinking seeing what what is coming to the market How we can combine our Earth observation data with other sources To as you say just type find me My house or find me. I don't know. Tell me what's the yield of that of that field Type it and get it so that that's one of the thinking we're not working on it right now But it is definitely something which is on in our minds but With with the archive I take our example now that that we have built over the years An archive of sex of six years basically It's calling to use machine learning to be exploited to to use artificial intelligence And that's what what we are working on specifically also in the Earth observation lab We are looking at how we can leverage that archive train models with this historical Basically, yeah, this historical information and then see how we can play at that to a downstream application So basically not use any label but train a model and then ask it to Classify crops or find me the change in that area For example a change in the build-up area and then see how we can use these technologies also to get that information quickly And then as I said before know how customers build applications Also using leveraging that technology so also combining it with other sensors So not only other information, but also other earth observation centers, which is what we are also doing To to derive Insights which we call planetary variables Where we're not using only our data, but also leveraging the Copernicus So these more reference sensors from Copernicus or Landsat To derive to add value and to make the best out of these data sets and use machine learning also to build Do this sensor fusion and modeling Take a quick second, but I would like to get all of your opinions on this Just take a mental second. Also you just to have it in mind How long do you think it will take before we have something like chat GPT with a reservation data? I'm gonna start with you and it I Don't think it will take very long But okay, what are we talking five years? Oh, no, three to Oh To yeah two years to bring up if you had to bet your entire house and all your savings I Would also agree two to three years Honest, I think we are there like last week. I had I'm writing code three days per year So I can formulate the prompt or a question, but I I forget the syntax So last week I had to write a function to analyze some some data set and The chat GPT was good at it. I formulate the correct prompt and I get the function that works I can get my stuff done It's amazing Is there? Laura, I'm also optimistic and I think probably before the next intergeal We're gonna find some companies already Showcasing some cases like this. So yeah, I think it's gonna be fast as a professional person Who is always guesstimating? I Would I would wish to be that optimistic as you so I think that no It will help us with solving specific, you know questions count number of cars count number of people count number of trees But with no giving Kind of more meaningful answers when it comes to you know Extracting knowledge not extracting kind of information I think that there is a long way to go, right? I mean so I mean it's here Years to come I'm curious to hear later on how close where you were or if you had a different opinion I'm more or less at the end of my question. So I will open up the floor. So think about your questions And so Laura back to you and how does tile box infrastructure management potentially change the game for you Yeah, so well basically tile box is an abstraction layer that runs on top of Infrastructure like for example Google Cloud provides, right? So what it does is that is it allows companies to develop the in-house of the pipelines But already at the scale and in a very reliable manner. So one of the things that we do Like linking it now to the challenges that we talked before is that we offer unified access That is compatible to space service providers So any company that is launching right after commissioning they get access to their data and they can immediately develop products We also tile box also does all the infrastructure management. That means Deployment scaling load balancing so companies can just again focus on creating their products and not battling infrastructure In a very distributed manner. So running their pipelines across different clusters and different clouds And this comes very handy for example in in cases of data fusion when you have data from different sensors store in different locations, right? And moving that data around is very costly. So we offer this possibility to process close to where the data is stored Then another difference that we that we bring is that we deploy directly on the customers account So the customer keeps full control of the data and algorithms Yeah, and the next step that we are working on is to lift Tilebox from the ground to in orbit So customers can deploy software or will be able to deploy software in space the same way they would do it on the ground They can start a data pipelines directly on the payload Or directly on data centers in the space And then continue on the ground reducing volumes reducing light latency and at the end basically reaching the customers way faster So that's that's basically what we are working on right now And and how do you see this Sabrina because you also operate in a similar space where you make it easier so the API's and so on Do you think products like Laura's can make the up for the two operating even better reach a bigger audience? Yeah, I would be very excited to see how this could happen. I mean, I think we There is a potential for collaboration cooperation. So definitely For me as I mentioned the access the infrastructure That we need to really like process to special data extract inside the scale is really what's going to change the industry So, yeah, I think definitely Arnis you're a person who programs in addition to working at USPA. So how do you see this? Is it something also exciting for you? Does it make your life better to have such a distributed platform? I Yeah, actually could you repeat the question because actually I do not hear you quite well to be honest, okay? So I think now it's much better much better. So my question was to you How does distributed infrastructure like what Laura offers changes things for you? Does it make it easier for you as a programmer? well at USPA level we're quite several layers of abstraction from from that because the data from sentinels Data from Copernicus services by ECMWF JRC European environmental Environmental agency They are the ones building the products with the help of industry and there has been a shift from private cloud to using public clouds which are much more scalable and Of course that goes together with with processing on cloud of course And there were several initiatives the CDSE Copernicus data access ecosystem run by ESA to facilitate this processing on cloud for the for the sentinel data and So there is effort to address this obvious problem with the with our data Glad to hear that so Alex coming back to you You've got a lot of decades of experience engaging with the community. Thank you. You are just Confirming that I'm old So what's one pressing topic in your that deserves more attention in your opinion? No, so so what I'm particularly I mean, I'm excited about a lot of different No Things like no when I think about the the archives that no planet has you've mentioned about this And I mean how much knowledge is really, you know, there is still to be discovered No, about different processes that are happening on the on the planet and now it is really, you know, fascinating but What fascinates me is how the resolution is Improving so today we've got eight companies providing I think 12 satellites that offer 30 centimeters Resolution satellite data in 2027 we are expected to have 131 satellites providing no 30 centimeters data resolution So now it will and besides the fact that it's still very very expensive to access and know a lot of People on the market are complaining about this. There is enormous amount of new use cases that Know that will be unlocked. You can imagine things like no monitoring. I know ports right today when you've got Two or three satellite images a day you know, you are not able to to know like to the efficient Monitoring, but if you will have a satellite image taken every 10 minutes Like it will be enough to To to basically unlock a lot of different use cases that are not really viable Today, I mean there will be a lot of challenges related to managing Of course, there's terabytes or petabytes. I mean tsunami of data that that that will be that will be out there But it's fascinating. You know, what kind of new possibilities it will it will give us and Know, hopefully how easy easily it will be accessible because with competition on the market now comes also know more Focus on the on the customer and know perhaps competing on the on the price and on Availability of this data and I mean, I just hope that it will not go into government capacity But it will also come to the commercial market I want to get the opinion of the others as well But maybe we need to open up the floor for questions. So if you can keep it short on is one or two sentences What do you think is the one pressing challenge in geo or in earth observation today? I see it as the last mile because often technology is there. It's been proven it works It's the adoption is limited by by often lack of Other limitations in the regulation or accepted means of compliance that do not envisage The usage of methods beyond the traditional ones. I see that's an opportunity That can be worked on at the pan European or national levels Thanks And Sabrina, do you see a similar challenge or do you see another pressing point that need to tackle? I think there is there are a lot of pressing challenges Definitely agree with everything that was said for me. So so maybe number one continue with thought leadership educational content Really showcase what can be done with the data? It's really like demonstrate the use cases and show how really customers can benefit commercial, of course use cases and of course Making sure we continue to make the access to data to the infrastructure and to the processing algorithms needed to Make sense of that data. So I think for me, those would be the two main challenges and opportunities Laura, what do you see as the pressing points? Where do you see opportunities? Well, the bigger challenge that we see right now is how to as I mentioned Effectively process these amounts of data that just keep increasing and how to unlock new use cases Through either data fusion or even integrating complex algorithms and AI or machine learning modules So in this case also modularity is very important and reusability is very important So those are the biggest the biggest things that I see coming up and it Besides having the need for more data because I think you want to say more data But what would be another pressing challenge? I think from a very completely different Very technical aspect down to the actual analysis a big challenge Which I keep seeing in the work we do in the earth observation lab is Giving value to the information we derive for which we rely or depend a lot in the earth observation sector on ground truth And I think there's a lot of ground truth out there But we are not able to to access it So I think this is a bit of a challenge depending on on the domain and for example in agriculture is super difficult So I think they're I see we can still do a lot to also make use of that data to also Provide better earth observation based products Because they are more reliable we can train models much better with a higher accuracy So I think that's for me That's close to my heart because of what we do and because that is a daily challenge also for us I really like that answer. Yeah, so that's more or less all I had for questions I wanted to open up the floor for more questions from your side Juliana is there with a mic Does any of you have a question? Or were you completely satisfied with the questions that I had and you don't want to ask any more questions Was was it a question? No, okay Then may I have a yes sure? I Feel very much reminded when it comes to some of the feds that you delivered right now or the information on the discussion we had With open data and smart cities So is there something we can learn because this was a process that happened already a few years ago And perhaps we can learn with it About data that we can use for the whole earth. So I don't know but perhaps you have an idea for that So you mean that the challenge to we we have so many data When it comes to cities So many different data and we speak about different data about the earth So and the question is can't we learn from the process that happened there already during the last few years? And how to deal with it and who owns the the data and who can deal with it and so a lot of processes These are the same questions that were Were there so in a sense that I think the question goes more towards can we adopt some of the open data? Practices the standards that were adopted by the smart cities Towards earth observation. Yeah, I don't know but this is it's another level. So this is a smaller level We speak about cities and we speak about Denmark as a very digital country we today we heard that they have a nearly a digital twin So we are we're close to it and now we speak about earth data Perhaps one day we will have a digital twin of the earth how cool would be that but to deal with that We first have to know. Okay. What do we do with it at the end? How can we change it? Why is it achievable at the end? But how can we do it? How's the path to it and what can we learn from cities because it's much much smaller much more handleable It's a big question I know but it raised in my head Yeah, I make comment like it's a general question. So a general comment It's good that you are building Solutions and cities and then you think that it's a digital twin is coming It's gonna emerge basically as a set of small solutions each of them will be essentially a simple solution for a simple problem perhaps but once you Have a set large set of those working together through open a standard data standards fair fair data Findable accessible interoperable reusable data That will at some point emerges digital twin basically so it's a set of simple solutions That's my take on this Anybody have a comment or an addition to it I'm personally also interested to see the use cases that earth observation data enables So when we talk about smart cities, of course planning cities in a smarter way We're talking here about sustainability today. So to reduce emissions. That's just something that's yeah, I would like to see more and more of I think it's very sector-dependent As I gave the example of agriculture before We I think we're we're not managing to convince also the agricultural Industry farmers to share that data because maybe we we don't manage to communicate What's the benefit of doing that? No, so I don't know how we can overcome it personally, but Yeah, maybe the cities are a good example This is why it came to my head to speak about smart cities because when we when we look at Copenhagen that was as far as I know they they opened their data and they gave it to everyone and then it was Surprisingly high number of new apps and new solutions that came out of this process That nobody expected before and that might be happened when you as you said just leave the data to Let us access Have more access for more people to the data and let's see what will happen And that might be one solution. That's why I said can we learn from that what happened there in a small in a smaller way for this bigger way I Guess your words are Music to the years of the Open Geospatial Consortium that's working a lot on data standards and so on So yeah Right and as we came on to the stage Juliana mentioned to me and we are in Germany and we are already a few minutes late And I was so happy that we might finish on time and I can say yeah I finished right exactly on time, but we didn't we are a few minutes late, but I really enjoyed it So thanks a lot to you Alex Laura and it to be an honest I hope you enjoyed it as well And I hope you guys had a good time and you learned something new or at least you had a lot of fun Joining us this evening. So thanks a lot Bring a lot of applause for my panelists