 Good afternoon everybody, um, yeah, I think I'm coming through. I don't see any Wild gestures that things are not being recorded. So please everybody who's joining our webinar this afternoon Want to wish you a warm welcome to yet another Crayodious cloud ferro webinar Today I am going a bit back to basics Yeah, I've been asked if I could just do a more general talk about Earth observation data So I will go a bit through the Yeah, some observators observation Yeah, have principles fundamentals and I will in the end highlight some some example use cases that Yeah from from our Crayodious platform how we use this at Earth observation data sets. So I'm warning you. I'm really not going too much into detail. I just want to keep it general For people who are just starting with Earth observation are just generally interested in the data to get to know a bit more about What is data? Is what you can do with it and and so on And so don't pin me down on too many technical details in the questions I can answer a lot hopefully but but yeah This is this talk is not intended to to really go into the nifty grifty technical details with satellite data Now, let me quickly switch to my presentation That I will have to do like Boom boom share screen And I will Share my PowerPoint which should be coming up now I think so and let me go to the beginning first. Yeah, so Let me start with a agenda for today so I would like to talk a bit about Yeah, the general print introduction into the Earth observation principles as I mentioned before Then I would like to spend some time on the Sentinel missions at the moment There's four operational Sentinel missions And I would like to go through each of them because they are forming the backbone of the data sets on the Korea's platform And yeah, they are very popular and used in many application fields like agriculture as you can see the image on the bottom right and Yeah, then I would like to highlight the older data sets that we have a bit less in a bit more general as well And then I would like to showcase three use case examples First relating to air pollution monitoring From the Sentinel 5p mission then send for cap software Send for cap stands for Sentinels 4 and a common agricultural policy. So it's a agriculture Agricultural monitoring which is a Software is using Sentinel 1 Sentinel 2 and Landsat 8 data for that I will talk a bit about that and then I would like to finish off with showing some VHR very high resolution imagery that we have Available through the platform as well so Let me go into the introduction into the Earth observation principles. Let me start at the beginning Earth observation sensors are The sensors bounded on platforms and they all work to a specific They all work in some part of the electromagnetic spectrum that can be Optical and the optical domain so optical and atmospheric sensors as well They usually are operating in the visual near-infrared and short-wave infrared domains So that's if you look at the spectrum image on the top Top right is pretty much in the middle Visible spectrum and a little bit to the left of it in the infrared domain So infrared is also that domain where the TV remotes work And then with the SARS SARS stands for synthetic aperture radar Radar is a longer wavelength and they yeah They they are just to the left of the infrared and domain So these the way the wavelengths in which radar satellites operate is between a few centimeters up to let's say one meter of Wavelength, so they are They are yeah, also part of the part of the electromagnetic spectrum are just a different wavelength and yeah The waves the radar waves of different Properties and different effects on the yeah on on on the Return signal to the satellites, which I will highlight later Then one very important aspect to keep in mind is that Earth observation sensors can be passive, which means that they're only receiving Electromagnetic radiation, so that's Optical sensors it's like a photo camera basically you don't send well You don't you don't send a signal To a camera on your phone or in a photo photo camera It's just Capturing the light that has been sent by the Sun and is reflected on a surface and Back to the sensor in the case of satellites and the sensors on board the satellites And or sensors can be active, which means that they're both emitting and receiving Information or the radiation And this is the case for a synthetic aperture radar. They send the radar pulse from the satellite all the way down to the surface of the earth this Signal is then in some way Reflected back to the the sensor part of it, of course, you can imagine that not all this and the signal is Is reflected back I have to say scattered back officially In microwave we talk about back scattering and not reflecting so much And that signal is then received by the Sensor on board the satellite and recorded and from that a radar image is is built But it's also very important to keep in mind is that Yeah, the Electromagnetic spectrum is not all transmitted Equally through the atmosphere you can see on the bottom right graph the blue areas are the Transmittal windows as you would call that which shows you that on the left The scale is the other way around and the top image. So the further to the right you go the longer the wavelengths are That's the visible in the visible domain, there's quite a quite a decent transmission of about 1.0.5 and This this is there's a very big gap in the middle In the far and extreme infrared where there's no signal attenuated by the atmosphere at all and in the far right It's where we and where we in the microwave domain. There's a very good transmittal transmission of electromagnetic waves, which is the the microwave domain Which is this is also very important to keep in mind that yeah, we're really operating in Areas where actually signal can be transmitted through the atmosphere. Otherwise, there's no point and to And to to have a sensor all the way up there Then I would like to highlight a bit what yeah, but kind of earth operation satellites Do we have I mean it's a huge range and they're launching loads and loads last Sunday. There was a A record launch of a hundred and forty three satellites from one rocket They were mostly nano and very small satellites from small smaller companies and Building cheaper satellites and launching them in in bigger amounts But you can yeah, but it tells you that there's a there's there's a lot of earth observation satellites up there at the moment Yeah, earth observation satellites can be targeted to specific application domains That can be meteorology is very obvious. There's meteorological satellites atmospheric Satellites satellites that measure the composition of the atmosphere for example, but they can also be focusing on urban Studies agriculture environmental geosciences. You name it Then we have the different sensor types on satellites that can be up as I mentioned already before you have optical the main the main And yeah, the main categories here are the optical and near infrared sensors Then you have the star which is the radar satellites and others. They're also experimenting now more with well with Satellites with lasers to perform altimetry And so there's this there's a lot of different sensor types Yeah, space resolution is a very important Category of all criteria and it can be low Which can be a few kilometers by few kilometers for each grid cell size that that the sensor can measure it's mostly for the meteorological satellites have a lower resolution and Then it can be higher and to very high and very high is usually a spatial resolution of less than one meter There's quite a few Satellites now up there that can measure less than one meter or let's say two meters Then high is in the domains of 10 to 20 to 50 meter square grid cell size, which is the Spatial resolution that the Sentinel Sentinel one and two missions operate in mostly Yeah, then very important categories. Well, it's a spectral resolution. How many bands does a satellite have? In the optical domain, this is very important How wide is the band for each band on what is what's the spectral domain in which each band can measure? How sense sensitive sensitive is the sensor? I mean the Spectral resolution is a very important aspect of a satellite. It's not all about spatial resolution A lot of people think that the higher the spatial resolution the better the data, but that's not necessarily true Then a revisited time is also very important category for Distinction between Earth observation satellites Some satellites they cover a very wide swath a very wide path in one go So they cover the entire globe in one day Whereas some others have a very narrow swath and they need a lot more time to revisit the same spot on the globe again and So they can be in the order of weeks Or yeah, I mean the old Landsat has a revisited time of about 16 days, which is nowadays quite low Yeah, and the size the size I mean the size of the satellite they can be big small or nano nano We think it's less than 10 by 10 centimeters Smallest, yeah, it's a bit bigger and bigger is yeah This is all a bit relative to these categories, but the size can definitely Yeah, it can be very variable Yeah, then Constellation that that that also is a distinction you can have a single satellite You can have like a double what that you often see with radar satellites now that they fly by basically in tandem There's a well-known tandem X-Mate mission, which is two radar satellites flying just off behind each other and they In this configuration they can do some very interesting Measurements on the topography for example, or you can have a swarm or constellation nowadays with these nanosatellites There's a few companies that build very small satellites and they launch them Yeah, by the dozens in one go So then yeah, they there's lots of them and then yeah the ownership That's that's that's one distinction. I would say with ownership or maybe I could also name this data availability or accessibility and there's a lot of commercial providers that Provide data that you have to pay for and there's also quite a few public providers now well known as the Landsat missions from NASA and the USDS in America and of course our central missions From the Copernicus program in Europe. This is all public data freely available Can be reproduced can be used without any limitations So yeah, I've talked a lot about satellites and what what's now the ideals EO satellites. I mean Yeah, if if somebody would want to design a satellite doesn't know anything about satellites, but what would he or she And and there wouldn't be any limitations in what what technical capabilities would be and what would they want They probably would want a very high spatial resolution Very wide swath width. So that's the area covered in one acquisition They basically the width of the angle in which it looks a very good radiometric Quality very much cloud-free data. So no clouds because clouds are usually disruptive very cheap data to replace or multiply Or they're not the data. I mean here that the satellite And the data should be very free. Well, does this satellite exist? No, it doesn't because Every satellite is a trade-off between technical capabilities different user requirements and available budget, etc. Etc. So that's a have this image on the right with a number of different satellites both commercial and public And publicly available the satellite or not the satellite but data from Satellites that either record publicly available or commercial data And they look very different, but they have all different capabilities and they usually focus on one or more of these categories for example, the Maxar worldview in some in the middle right that's a Satellite from a commercial provider, which offers very high resolution data on less than half a meter. I think I believe But it doesn't come for free and yeah, it can only cover a very small area in the world in one go Whereas for example, the ETA Sentinel 1a can cover a very wide swath in one day So every satellite is different and all really focusing on different needs And so yeah, but but usually the best way for what I always say When you want to do an earth observation study, don't stare Focus on one data source only try to combine it from different sensors and try to Do you to use the advantages of each data set? So you will get a better end result um Then oh, there's a lot of text here, but there's a few things I still would like to do to mention and because a lot of people often ask me about these things So you have a satellite. That's that has recorded data What there's what what are the only different types of data doing and what are these? abbreviations acronyms meaning so there's a few few things to really keep in mind. There's there's there's more and there's more data Criteria and then then I have on this slide, but these I think are the most important one so, um the satellite the earth observation data does Yeah, one of the one of the most important one is In terms of data set this is in what acquisition mode of the on the satellite was this data acquired for for example, here you have the sentinel one IW EW and SM SM acquisition modes they all stand for different ways to operate the satellite Sentinel one is quite a quite a yeah, it can it can be switched to different settings to satellite for example over oceans they usually record data in the EW which is the extra white swath mode And over land is more the IW which is the interferometric white swath mode. So which is narrower than the EW mode But then you also have the SM mode, which is the strip map mode, which is a very narrow resolution So these are the the acquisition mode is a very important parameter when it comes to the data types and Yeah, and also focus on what what you need. You can select which data type you want to focus on Um, then the product or processing level. Um, yeah, that's a very important one. Um Because it's really yeah, it really depends on your needs To what level you want to what level you want to start with if you're interested in, um, yeah in Getting the most Most advanced parameters from satellite data. You're really researching what what what kind of data what kind of Yeah Information you can get from satellite is probably more useful to start at the lower level If you're interested in just getting a nice image of how for example Yeah, a field is growing overseas and you can probably start with a higher level higher level data And that has already been pre-processed to that level where you can easily compare different images from different dates, for example So level zero is very raw data. Not many people use it. Uh, I mean is and and also nasa They pre-processed their satellite their landslide and sentinel data straight to level one Um, because yeah, it's it. Otherwise, it's it's very difficult to get started with. Um Yeah, level level one is is the level that you often get from the the providers. Um, so it has been time reference and geo referenced um And in sensor units level two is often Is a level that a lot of people want to use So often these steps from level one to level two is quite a quite a tricky one But you can see also on cryodias we we we provide now a number of processors that that process the Imagery that comes from the the data archives to level two from level one to level two straight away So users can easily start working with their level two data So for example in optical data, this level one to level two, that means it's an atmospheric correction, for example Or for sentinel one the radar data is often like a terrain correction and a calibration Uh of the of the of the data So you can uh, but the basic you see level two means that you can compare one image with another And you can assume that that they will be comparable that there's no errors due to our atmospheric Effects or due to terrain effects that that that that might make the comparison invalid Um, yeah level three and level four. They are higher levels that that are often They're derived from from from a workflow or from processing workflows after this And that and those those variables are often the results the really the the the final results of of models That that can be used in for example further analogies Yeah, um Then a question and I often get as well, which is a product type. What does a product type mean? Well, basically what it means that products from one sensor they can be processed into different product types Uh serving different user requirements. That's that's that's a bit vague, but uh, what it means that data in the same processing level can be processed to uh Yeah, uh to to different types of data for a very good example is the sentinel one s lc and g rd distinction s lc stands for a simple single look complex. So that's the the radar signal split into The component for phase and intensity or power I should say Um Which can be used this this type of data can be used for analysis into interferometric studies So basically comparing one radar image with another and looking at how the phase has changed Which can be used for example for mapping of elevation mapping of of subsidence of terrain um But yeah, often users don't need to do that or they're interested in other things and for that you have the the g rd data Which is it's the same processing level, but it's it's just processed to a different level It's a bit more user friendly already And and we're not looking into phase and and intensity parameters anymore, but just at uh, yeah back scatter units already so that's um It yeah, I mean I can talk a lot about this but there's a lot of information on the web Also, if you look at the link below, there's there's the user guides for all the different sentinel data sets Uh, I would really recommend to to read more. It's a very clear website and they explain it pretty well Um, then yeah, the data principles. We're going to the next category, which is the relative orbit Um Which is very important for sentinel one, especially for the interferometric studies, uh, that yeah satellite fly with a number number of relative in a system of relative orbits And these are basically fixed over pass rooms over the globe So there's about I think 200 relative orbits for sentinel one And they're just the path that that it flies over And each sentinel Satellite there's two of them sentinel one satellite Um, each of these they fly the same relative orbit 12 days after the previous time. So Um, yeah, the official revisit time of sentinel one Uh Is uh is now six days because there's two satellites that fly Fly behind each other But um, yeah per satellite it's 12 days. So yeah And then yeah, this is um, the last one is uh, what I call the the the basically the geographical the tiles or the path for row system And it which means that the for sentinel two we have a tile system for land salt We have a path and row system and these The uh, they're basically, uh fixed areas on the globe like square tiles all around the globe In which the data that's recorded, uh, is is is just cut uh are cropped into the yeah Um, so if you look at a specific area, you can find a tile code in the sentinel two tiling grid system and you can uh all the data is delivered in uh for uh in in uh per tile for this this specific uh for every every time this satellite flies over So it's uh, yeah, um, so it's very easy to to know if you say i'm looking at this tile you can you can just Search for the data that's there and then for every time every time there's data recorded within the tile The data will be made available for this uh for this tile um So then i would like to focus a bit more on the the specific sentinel satellites Uh sentinel one let's start with the beginning There's two satellites two sentinel one a and sentinel one b Launched in 2014 and 2016. Um And these this these satellites they operate uh in c band So that's that's a wavelength of about 20 30 centimeters if i'm If i'm correctly, uh, memorizing the the wavelengths exactly uh in two polarization modes so Yeah in v v and v h modally, which is the the the direction in which the signal is transmitted and received And it's an active sensor. So it sends out a signal which is uh scattered back and and and the scattered back the the back scattered signal is uh recorded As i mentioned already the six-day revisit time in a spatial resolution can start at 10 meters But it's usually lower. I mean with radar. It's not so clear Um, there's often some filtering needed to make the data a bit. Um, yeah A bit, uh, I would say good-looking but but to to correct for some some some some specific Very specific phenomena that you have with radar data So you can use 10 meter data, but often people resample it or filter it to about 20 meters So it's still quite quite a good Spatial resolution. So the application domains is um, yeah, as i mentioned Earlier ready terrain mapping agriculture forestry emergency mapping or polar studies Yeah, what are the advantages? Well a radar signal is uh hindered by clouds and that's a very big plus And also it can record at night because it's an active sensor. It sends its own signal So if it's dark it can send the signal and and you get information back So is there's there's there's much more Useful data being recorded them in an optical center Um, yeah, it's a good. It's got a very good radiometric quality and it's got a white swath. It covers quite a white area in one go On the image on the right you can see already what these different acquisition modes that I mentioned earlier mean Uh, it's just basically looking at the different width of the area that you look at and and Either you focus more or less depending on the acquisition mode Yeah, the disadvantages what I often hear is that spatial resolution is not as good as people would want it Um, yeah, they're they're a very big and heavy data sets, especially when you look at slc data So you need a lot of resources for processing And there's still quite a bit of preprocessing needed until you can really use it Yeah, and the data is it it's a different type of data than optical data optical data It just looks familiar because your eyes also work in optical domain. So as a human being you're very used to looking at optical data and microwave so radar radar Data looks a bit it's different. You look in a different domain. There's a different interaction with The surface of the earth. So that makes the data more difficult to interpret Um, but yeah, it's a very popular mission actually at the moment getting more and more popular because of this this Yeah, uh, guaranteed acquisition basically because there's no clouds Especially in areas where there's lots of clouds like the tropics or northern europe Yeah So, um, that's sent on the one. Let's go to number two Which is very similar in a sense that there's also two satellites flying sent into a sent on to b launched Just after sent to no one in 2015 2017 um Yeah, this is a multi spectral optical sense Mission with 13 bands invisible near infrared and shortwave infrared domains Also a six day revisit time and spatial resolutions are 10 20 or 16 meters depending on the band I think the the optical bands in the visible Domain are 10 meters spatial resolution um So it's a it's a very popular mission. I would say it's really it really provides very good data very reliable and Yeah, and and and it's it's it's been used in many different fields like yeah, but I mentioned as well there Again agriculture forestry has a lot of interest there coastal cities or inland water for water studies as well But also power studies. So it's uh, it's a very wide range and I can name a few more application domains there But I just yeah picked a few there advantages as I mentioned already is that yeah the data People find the data more easy to interpret And also it's got a very good radiometric quality. It's just a very well built satellite a very very good sensors These advantages. Yeah clouds As any optical sensor and there's a lot of clouds Every cloud is recorded. Um, there's plenty of very advanced algorithms to filter out the clouds to to make sure that yeah And these these algorithms are getting better and better, but you can't deny the fact that if there's a cloud you you can't see the ground Um, yeah, so that that that that that will always be a problem with any optical Any optical Mission, but depending on where you live in the world. I mean in in in warmer latitudes like the Mediterranean or Parts of the more desert arid like climates. It's it's a yeah, it's very useful. Um, you know And yeah, what I say is also all these there's a lot of atmospheric corrections needed to uh to make make sure that The acres are comparable And atmospheric corrections. They're very complex models and there's a lot of different algorithms out there and And and there's no consensus really which one is the best so, yeah And yeah, so it it's sometimes difficult to to to really calibrate the data So it you can really compare one image with another Um, then I go to Sentinel number three and yet again, there's two central sentinel three satellites Go flying at the moment sentinel 3a and sentinel 3b And this is a very very different sensor a very different mission in the sense that there's basically three missions in one satellite Uh, three centers on one satellite. So you have the SLS TR The instrument which is um a thermal instrument measuring uh land and water surface temperature um, or basically, uh into interfere infrared radiation or And that that's kind of that that then converted to land and water surface temperature Oh, yeah, is is a spectral an optical scanner It's a bit like a low resolution uh sentinel two, but it used a lot, uh for yeah for global Uh global mapping so not not part of the global but really the global mapping and then you have the s-roll s-r-a-l Which is an altimetry measure, which is also a radar which measures the the height um Yeah, and because it is a very low low resolution sensor It is about the spatial resolution about 300 meters For the olci and 500 meters for the s-o-s-d-r. It has a very low revisit time So basically every day is covering the entire globe every one or two days Yeah, um application domains, uh, yeah temperature measures or service temperature ocean color as well. So there's a lot of oceanic uh Use for ocean oceanographic applications a lot into topography or global land cover Yeah So it's a it's also a very wide range of applications also because it's all these different sensors And it has advantages that it's a very short revisit time very diverse range of applications that this advantage is It's a lower resolution and sentinel two basically, but it it it it serves again It serves a very different Need this this satellite Um, then there's one more sentinel Satellite up the sentinel 5p which is Yeah, it's just one satellite is launched in 2018. So three years ago And it's equipped with a tropomy instrument, which is a spectrometer Sensing in the ultraviolet to a shortwave infrared It's a very low resolution. So seven by seven kilometers and it's looking at atmospheric composition And there's a revisit time of every one day. So it comes over every day and it's it's uh, yeah, it's it's used for Atmospheric composition measuring so a number of uh different chemical Components of the atmosphere like NO2 CO, but also aerosols methane ozone Yeah, so it's um, it's really um, it's it's a different different different Uh Application domain all together than the previous ones in that sense But it's uh, yeah, it's very interesting and it's very being Popularized quite a bit last year during the first corona lockdowns when they could notice Or they could measure the changes in air quality Uh over specific areas in the world. So here you can see in the image in china, which was a very impressive Decrease in air quality when the major lockdown started their last year march Um, so yeah, it's it's it's an interesting mission Um, yeah the advantage again shorter visit time And it's got a wide range of uh atmosphere components And there's a lot of well calibrated products in level two already available So you can really start playing with the data very easily Yeah, and it's this advantage is the lower resolution, but that's the nature of atmospheric monitoring. I mean as Yeah atmosphere Atmospheric missions tend to have a lower resolution also because the the signal they try to catch from the Uh from the atmosphere. It's it's a very weak signal So they they you have to sample from a larger area to get a yeah more a better signal to noise ratio so, um Was this and sent for cap on creodias. That's the wrong title there. Anyway, this was what I meant Here is the other missions that we have on creodias not the sentinel mission. So I quickly go through this You have lonset five seven and eight, which is fairly similar to sentinel two It's an americans mission Then we have s mos which is an isa mission which is a passive microwave Uh scanner which measures ocean some moisture and ocean salinity. So it's uh um, yeah, it's it uh And it has a very low spatial resolution But it's a very popular mission as well for global studies Then you have data from the entry submission, which is a very old satellite, which is not active I think it stopped working in 2012. So it's already quite. Oh, yeah here in 2011 actually Uh, it was a huge satellite a bit like sentinel three, but then much bigger even with a lot of different Uh sensors on board But yeah, we have the merris data, which is the same as the sentinel three or the precursor to the sentinel three l l c i data and also asa data, which is uh, uh, uh, c bond c bend sar Synthetic aperture radar data precursor to the sentinel one mission Then we also have jason three data, which is uh, Ultimetry data similar to sentinel three as a roll data and then we have a few, um Satellite satellite data from very high resolution Satellites, which I will mention later in the use cases. Um, they're yeah, they're very high resolution So lower than one meter spatial resolution And they operate in a multispectral domain visible in the near infrared and it's commercial data But I'll highlight these a bit later as well Then I quickly want to go through this. There's also data that's not necessarily satellite data But it is often derived from satellites, which is uh, let's say high level two level three Uh, uh, products uh from different Copernicus service project. So we have the climate change service They have the atmosphere monitoring service the emergency monitoring service the land monitoring service and the marine environmental monitoring services There, um, yeah, there there's a very big archives of data We don't have them all completely stored on the cryodias, but we can always add more if a user is interested um But I would I would suggest uh to to uh, yeah to to Meet a bit further on these data set because quite often data that you uh, that you would like to use is already available through one of these services even one of these Copernicus services um Yeah, and then we have also uh, uh Ancillary some more data sets again have a different long header there Um, that is the Sentinel one orbit data. So we stored the orbit data, uh from Sentinel one as well But we also and much more A lot of people are interested in this terrain data and we stored a complete archive of SRTM, which is a terrain model recorded in 2002 from a space shuttle mission It's really available. We have the map zen data, which is fairly similar to SRTM, but it's uh Expanded a bit into areas where SRTM doesn't cover and um, yeah, and and improved Wherever the data was available, but yeah, we have that data as well. And what we start using now, which is, um I started offering more and more as the Copernicus DEM, which is a more recent Terrain model of the world Covering the complete world so from pole to pole From the Terra star X and the tandem X missions um Yeah, we we have that available in 30 meters and 90 meters spatial resolution um and Yeah, that that's that's that's something we are we are integrating better and better on our platform so we also would like to offer that as a Terrain model that you can use to process other data sets. For example, Sentinel one or Sentinel two data And I'm also one one data set that we have is a land cover map of europe based on Sentinel two data, which is the s2 s2 glc it's uh developed it's processed on creodias developed by the local remote sensing institute here in Warsaw cbk pan And um, yeah, that's that's also available for any user to to look and and and and download And then I would like to round off a bit to the oh, yeah to the the use cases um Some work that I've been doing over the last years or so just just some nice examples of what you can do so this um been looking into analyzing sentinel 5p data Um, but there's there's a list of different parameters there But I was looking I was interested in what's the impact of forest fires On the atmosphere. How can you monitor forest fire emissions smoke from forest fires? from sentinel 5p data And so I used aerosol data for from the sentinel 5p mission And I was looking a bit if I hope the animation comes a bit through and last When was it last summer and of last summer in the west of the united states? There was a very big amount of forest fires And on the animation on the right you can see Through different weeks in the end of august to to the end of september You can see how the aerosols so the basic the particles in the atmosphere were drifting from um From the west of the united states to the east and and that's yeah that I've used very simple um Script to download and process this data and and and and build this animation all with open source and free pros What is it? Scripting languages like python and r Um, so that's that's that's a nice example of how you can can visualize use satellite data to visualize Yeah events for example And then have another use case Yeah, I've mentioned already this sent for cap software It's um, yeah, it's a platform that's developed by the sent for cap consortium Which is mostly led by the university in louvre in belgium And yeah, it's a system in which a user for example a Somebody who's working at the pay agency in in in one of the european union member states or any Other person involved in agriculture and would like to monitor what's going on in an area can be a country can be a region um, they can Start a virtual machine, which is uh, yeah on on the criodias platform where the software is all pre-installed Um, and then they can start using the software straight away By defining an area of interest a period of interest The system will automatically download and pre-process Sentinel one two and lance of eight data From level one to level two and there's a number of different A different uh algorithms available for example a crop type mapper a In the detection of mowing events algorithm um That and that that can help the user to to uh investigate analyze It can you know our agriculture activity and yeah So here, uh, yeah, here's uh an overview of the different products that can be generated on send we sent for cap So the crop crop type map a grassland mowing product vegetation station the status indicator and a number of agricultural practices Um, as you can see there Um, I mean the platform the the software is still being developed. I think and um And we are in good good contact with the leader the developers and the leaders of the consortium And so any user can can easily start start using Yeah, this this software, um, yeah without having to install anything basically And then the last Use case or example, I would say And is this very high resolution data that we have available. Um, we have now VHR imagery from three providers Yealin from the yealin one satellite the casio set and the compsat satellites And it's a commercial offer so that imagery can be ordered through criodias We don't have the entire archive really available But we can we are building on an integration of their api the api from the casio set And that's the first one. We'll be having ready very soon uh, so any user can you can use our api to Or are they are data finder to search through the the archive and uh, and then can order it through uh, Through through our platform as well I have to mention that this imagery does not come from free Because it's uh, yeah, it's a commercial offer. So it's an add-on. It's not it's not open and free data On the right, you can see in a comparison of sentinel 2 on the top right image in the south of england this is and the yealin one Area image of the same area and there might not be very clear on your image at home, but there's a quite a distinctive quality difference So yeah, if you're interested, I would suggest to contact our sales department as well and they can provide more information and then I would like to stop with the last Example of very high resolution data in action This is an actual video which is recorded from a satellite from a yealin one satellite. So it's Satellite manages to capture an area for a Specific amount of time. So and and and puts all the images in in a bit of a movie Um, and the funny thing is you can see cars are driving from space. So I'll play this movie. I hope it works Yeah, it's coming and it's zooming in and I hope You will be able to see something on your screens at home Um, but if you look closely on the major road There there are some bits moving and that's moving cars Um, yeah driving through by route. This is by route so It's pretty impressive these days what what you can do from satellite. I have to say and this is uh, it's a very good example um So with that use case I would like to uh, oh, there we go again Well, let's do it once more hopefully you'll see a bit Manage to distinguish something um, but this is the last slide of my presentation. So I would like to uh, yeah If if you want to more further information, please contact our uh, either our sales department Psemec Psemec Joav Muita with email or for any technical support and Send to the email there And then I have a few more things. I am coming now Uh, yeah to uh, I have to highlighted uh, if you want to Keep in touch or want to get more training There will be more upcoming webinars. So please go to this, uh website there to finish off by Saying thank you all for joining this webinar. I hope you learned a little bit. Uh, yeah, I would like to say, uh There this is just a quick introduction that I I I wrote But there's loads more to learn. Um, if if you have any questions, feel free to reach out to uh, to cloud ferro as well creodios, uh, or on the yeah On the twitter, linked in our facebook pages that we have as well and That from my side that will be it then and everybody have a Very good day or afternoon Or morning, wherever you are in the globe