 Good morning everyone, my name is Claudia Bielinska and I represent Cloud Ferro Company. Here at Cloud Ferro Company I'm an Earth Observation Product Manager and today I would like to give you a brief introduction to CREODES platform, Copernicus platform for Earth Observation Data Access and Processing. Thank you very much for joining our webinar. I hope this one hour together will be beneficial for you, so you will have a chance to learn more about our platform. I hope that some of you are already our customers, CREODES users, so maybe you will hear again something about CREODES and maybe some of you plenty of things will be new things. So our today's agenda is from the beginning, CREODES platform architecture, how it's built, how it looks like, what can you find on CREODES platform, then available data collections, so both Copernicus data and paid very high resolution data. Then I would like to show you some practical things like how to use our tools, your browser and your finder and then we will move to Cloud Dashboard and I would like to show you how to set up a virtual machine on CREODES and this time I would like to show you how to set up virtual machine with Windows operating system. Before on our previous webinars we showed you how to set up virtual machine with Linux operating system and today we will use Windows and at the end we will have some time for a Q&A session, so you can ask your questions during my talk and we will try to answer your questions but at the end also we will try to have some time to discuss your questions if you will have any and then if anything will come to your mind you can always write an email to me and at the end you will see my email address so I hope that this session will go smooth and we will learn some things. So let's start from CREODES platform architecture. I would like to start from something else because as all of you probably know that CREODES platform is a cloud computing environment but let's think how data access and data sharing looks today. I think that some of you know how to use cloud platforms and you are doing it in your everyday work but I know also that some people are still stuck to another way, another path of data accessing and data sharing. So actually this slide, this process shows how it can look like but this process is really time consuming and it takes stages, it takes a lot of steps. So starting from satellites which acquire data then the data are received by some ground stations and then they are stored on ground stations and then they are published on some servers, some data hubs and then the user is coming to the data hub taking the data to his computer and then processing the data on his computer and then sharing the data with his colleagues with some people. So it's really time consuming process and it's not in one integrated environment but it's completely spread into different stages, different levels. So what we would like to change, we would like to change the way of data accessing and data sharing and that's what cryodias do. So cryodias is a change because when you want to acquire, when you want to access lots of data and really heavy data, when different users are accessing this data and the users are spending 80% on downloading and preparing the data for processing and then also when you process the data on your laptops, on your computers, it takes really a lot of time. So cryodias is something which is really I would say powerful and really useful. It's actually one common environment. It's a data repository, it's a cloud platform, so you can access the data, you can process the data, everything together in one environment. So today I will show you this one environment and I hope that you will start using cryodias. So basically cryodias, it's a cryodias portal and on that portal you can find very useful tools, EO Finder and EO Browser. So these tools are dedicated for users who would like to visualize the data online, who would like to download the data locally to computers, to computers. And then we also have cloud dashboard. So cloud dashboard is dedicated for users who would like to use cloud environment benefits. So cloud dashboard gives you access to Earth observation data, to a huge repository of the data and also it gives you environment for data processing. Also data storage, so everything in one place. So of course depending on the user needs you can only use portal and I would say quite intermediate tools or you can move to cloud and then do everything online in cloud environment. In general cryodias platform was built for European Space Agency, for European Commission and it's really dedicated to Copernicus. It was actually built for Copernicus scientific program because the Earth observation data which you can find on cryodias and mainly the data from Copernicus program. So from Sentinel mission plus the other data I will tell you more later on and also very high resolution data. So cryodias portal is a public cloud. So everyone can make a use of the cryodias portal and also can use cryodias repository. So make a use of the data set which are available and what is hidden under this cryodias portal, cloud services. So compute Earth data processing, block storage, object storage, virtual networking and backup. So when you store your data on the cryodias platform your data are safe. When you want to access the data, add more data, transfer the data, you can have different storages, different virtual machines and then everything is combined in one complete environment. So you don't need to switch to different computers and to different platforms because it's one common platform. So when we talk about this cloud environment we have to highlight that for our users we offer different virtual machines. So we have a lot of virtual machines and differences between those virtual machines are mainly in course, RAM and SSD network storage. So depending on your work, depending on the data, depending what you do, how much data do you process, you can choose a virtual machine which will be dedicated for you for your work. So we have our virtual machines have already, have already, have already, let's say, are communicated with the Earth observation repository. So when you enter virtual machine you can, you have access to Earth observation data repository immediately. So you can make a use of the data immediately. Then we have virtual machines which are dedicated for, which are dedicated for users who are using specific software like remote sensing software, GIS software. So for example we have virtual machines with ArcGIS installed but also with QGIS, with Snap and with different software. Of course you can install your software, you can install everything you want on a virtual machine and then use everything online in cloud. We have also dedicated servers and you can see that those dedicated servers have different number of cores, RAM and SSD local storage. We have also virtual machines with GPU and the GPU is especially needed for data processing, for AI or machine learning. So I think that everyone can find something for themselves to, to make, let's say, work and projects process easier, easier. Then coming to the data, what data collections do we offer? What data collection can you access for free and for what you have to pay? So starting from, from Copernicus. We have available data, imagery data from Sentinel mission. So starting from Sentinel-1, which is the synthetic aperture radar satellite, you can access the data Sentinel-1 on a different level of processing. Then we have optical satellites Sentinel-2A and Sentinel-2B. And also here you can access different level of processing. So one level 1C and level 2A. So before the atmospheric correction and after the atmospheric correction. Then going farther, Sentinel-3, also A and B, then Sentinel-5P, which is especially dedicated for atmospheric analysis. And apart from Sentinel's, we have also data from Lancet Satellite, and we set SMOS, and actually newly added data from MODIS, Terra and Aqua satellites. Besides, we have also, we give our users access to Copernicus services. So here you have access to Copernicus atmosphere service, emergency, land and marine. So those services are not available, I mean access to those services is not available from our tools, Finder and Browser, but from virtual machines. And access to those services and to those data is completely open. You don't pay anything for the access to those data, and even for downloading. So you can download the data to your computer, or you can use it online, online depends on you. So imagery data, which are very useful for different analysis, but also we have different digital elevation models. And here you can see the whole list of our products available. And what is important here, for example, Copernicus digital elevation model. We have Copernicus DEM in different resolutions, in 30 meters and 90 meters for the world coverage of digital elevation model. We have also data from Altimeter, from JSON3. And also you can have access, also free access to product S2GLC, which is Sentinel to Global LandCover classification. So this classification was done for 2017, and the whole Europe was classified. So you can access the data and see different classes of LandCover classification. And I know that this classification will be will be done also, will be updated. So hopefully soon we will also publish the data from this classification as soon as the project will be, of course, finished. Then moving to VHR commercial data. So very high resolution commercial data are dedicated for a bit different purposes. I would say more detailed classification, more detailed analysis. So we give you access to data from Chinese Satellite, Zhilin-1, from Kazakhstan Satellite, Kaseosat, and also Korean CompSat. So you can see that, for example, resolution of that kind of VHR data is completely different, because here we can even access the data in centimeter resolution. So for example, 40 centimeters of CompSat. And then four meters, 1.6 meter resolution, which is also good. We can compare it to Sentinel-2, for example, which is 10, 20, and 60 meter. But maybe at this point, as I'm talking about resolution, I would like to also tell you that from now on, we have available online new processor, which is called Enhancer. And thanks to this Enhancer, you can receive much better resolution of Sentinel-2 data, so not 10 meter resolution, but 2.5 meter resolution. You can order processed data with this Enhancer online and via your finder, you can see how it works. Okay, so if you would like to learn more about the data, please visit our website. And if you would like to learn more about Sentinels, also please visit a dedicated to Sentinel website. To sum up, what you need to know about CREODES platform. So first of all, access to the platform is completely for free, and it's open to everyone. You can access the tools, your finder and your browser. You can access your browser without registering yourself, but if you would like to search for the data and download the data to your computer using your finder, you have to be registered users. But of course, registration is completely for free, and then using the tool and using the data is completely for free. So you receive free and immediate access to all the Copernicus data sets, which are available. And of course, downloading is for free. But also to users who would like to use data and who would like to use our cloud environment, cloud computing and stored services are paid. So if you would like to use virtual machines, we can have different models, different I would say pricing models per usage, so hourly and fixed term monthly, annually. This is something you have to pay for it. And also if you would like to use our processors, which are available for Sentinel-1 and Sentinel-2 data, those services are also you have to pay for it. And then if you would like to have access to very high resolution imagery, this is also something which you have to pay for it. And from this point, I would like to encourage you all to test our platform. For the beginning, if you would like to apply, we can grant you 150 euro free credits, so you can launch your virtual machine and you can try if Creo-DS is a platform for you. Then as I was talking about Creo-DS tools, I would like to show you what kind of tools we have in our offer. So first of all, when entering Creo-DS portal, you can have access to your browser and your finder and also cloud dashboard. But for all of you who are Python, Python fans, we have Jupyter Notebook and the access to Jupyter Notebook is also for free. So using Jupyter Notebook, you can prototype anything and you can also use Earth observation data repository online from Jupyter Notebook environment. Then we have also third-party application. So you can access, for example, S2Sins, which is the kind of application to visualize Sentinel data in 2D and also 3D. But this third-party applications are also kind of applications built and developed by our users, for example, in the frames of ISA projects. So as the S2GLC product was developed, and then it's open and it's available for all of the users. Okay, from this point, I would like to show you your browser and your finder. I would like to show you how those tools work and how you can use it on your own. So I will switch to the browser. Okay, so coming to the Creo-DS portal. Here in the tab Tools, we have your browser and your finder, also cloud dashboard and the Jupyter app. So let's start from EOBroser, which is the tool for data browsing and data visualization. So to use EOBroser, you don't have to be registered users, but to use EOFinder, you have to be registered user. So if not yet, you are not registered, please just click the button register and register yourself to use the full benefits of the platform. So I will log in myself and then I will go to EOBroser. So here in EOBroser, you can see the map. So it takes actually my location. So we are located in Warsaw. Here on the left side, you have the whole list of data available here online. Data you can visualize here and you can search for the place of your interest. So here I would like to see Sentinel-2 on level 2A, so after the atmospheric correction. And I would like to see the data without clouds. It would be the best to see without clouds, but sometimes it's just simply impossible. So I will place here 10% of the full cloud coverage. Then we should select time range. So at the time range when the data was captured, so the time of our interest. So I will go to, let's say, March and then ending today. So let's click search and see if there are any nice data without clouds from the place which we are here now. Okay, so I see that here we have because first of all we can see the results here and also we can see the results on the map. So we can visualize it from map or from this search field. So I will visualize the data. So quickly the data were visualized. This is RGB composition. So based on the three channels, but here in the visualization tab, you can see that we have here different modes of visualization. So here now we have true color. Let's maybe find some river. We can have scene classification map. So here we can see the green areas and build up areas and then water bodies. We can have a false color, so using infrared. So in the bright red, you see all the green spaces in Warsaw. Then we can have a false color visualization and DVI visualization. So to detect green areas, detect agriculture fields, detect the forests and so on. We have here moisture index and we have also shortwave infrared. And the WA, so to detect water bodies and NDSE SI sorry index. So we can hear, for example, click one of the tabs of the visualization and we can compare, for example, false color to the RGB visualization. Here before I have added some pins. So those are green fields in one of the regions in Poland. And I can visualize the data. So I have here visualization of NDVI and also sorry, visualization of RGB. So if I would like to compare those images, I have to click here to compare. And then comparing by opacity or comparing by splitting those two. Let's say windows. So we can see how it looks in RGB and how it looks visualized by NDVI index. So this is what's created as browser is for. And then also when we are in the visualization tab from this window, we can download the image, but the image will be downloaded as a screenshot, not as the whole Sentinel file with all of the bands. It will be just a screenshot so you can, for example, present to your colleagues, paste it in your presentation and so on. So let's move back to create a portal and then go to tools. And then let's see EO Finder. So EO Finder, I would say is more advanced tool. So from this tool, you can search for the data by indicating here different criteria and you can download the data. I mean download the whole Sentinel file. So maybe let's move to Italy and then we can indicate here observed time or published time. So when the satellite observed that area or when the data were published to our repository, you can also search a place on the map. You can also write the name of the place here. Or you can, if you know what's the identifier of the Sentinel data you want to search, you can also put the product identifier here. So I will go to publish and then I will start to search for the data from May and then ending here today. Cloud coverage, of course, as less as possible. Then we will choose collection. So Sentinel 2. And here maybe I would just add that you can see more data available. So you can browse the causal satellite data, modis aquaterra and also Copernicus dem. But then I will just choose Sentinel 2. And then level processing 2A. And I will draw a polygon on the map to search for the data of the particular area around Venice. And then I will click search. Okay, so I have a couple of sentinels. We can see that cloud even zero percent. I can visualize it on the map. Coming one, looking at images one by one. So if I will find the one which I like, it can be here. I can simply visualize it. It looks good for me. And then I can download it. So by clicking this button download, the whole imagery, the whole Sentinel file with all of the bands will be downloaded locally to my computer. You can also, for example, add the data to your cart. So you can just, you know, as an in-store, collect the data. Some of the data are available online. So you can download them directly. But some of the data are kind of orderable. So we have to order them first. We have to download them first to our cache and cache. And when it will be available, you will be informed and you will be able to download them to your computer. So this is one way of using the whole data repository, downloading the data directly to your computer. But what I wanted to show you today is how to use a cloud environment and how to use virtual machines. So I will go back to the Creo-DIS portal and then I will go to tools and then cloud dashboard. Here, at the first window of cloud dashboard, we have to be, we have to log in. So using open ID connect means that we are using our login credentials as they are used for Creo-DIS platform. So yes, we are using it, connect. So we are connected to our environment, to our dashboard. And if we would like to open, launch new instance, new virtual machine, we go to instances. So from this window, you can see that for example, I have here one virtual machine which was created yesterday. You can see the whole information about the virtual machine. So from this point, you can disconnect, you can shut down your virtual machine and do anything which is possible here. So this is the kind of first window which informs you about your environment, what virtual machines you have and how do you use them and if they are running or if they are not running. But to launch virtual machine, we should click the button launch instance and then we will be moved to the pane for launching instance. So let's start from the instance name. I will call it pio, then we go to source. So source means, for example, what operating system our virtual machine should have or if it has to be the image, instance snapshot, volume, volume snapshot. If you will choose the image, so the virtual machine will be simply the image of the image of operating system. So here you can see that the list of available images is quite long. And we have her, for example, here, sent us with sent for cab. We have windows with ArcGIS and Ubuntu with QGIS. So different operating systems with, for example, already installed software, TensorFlow for machine learning. So depending what you would like to do. But I would like to simply use the windows image. So we can see that Windows 2019 is available. So I would like to add this one to my virtual machine simply by clicking this arrow up. So it was added. We can see it here and we can move to flavor. So what flavor should be of our virtual machine? At the beginning of my presentation, I showed you that we have plenty of different flavors depending on RAM, depending on total disk and so on. So here you can see that we have very small flavors, let's say. And then the numbers are also growing. So like very big extra large. So for today's purpose, I would like to use, for example, this one. So E01 large. So it will be enough for me. And this virtual machine has already connection to Earth observation data repository. So while entering the virtual machine, I will be already connected to the repository with the data so I can use the data in virtual machine. Okay, so I was connected. I mean, I added the flavor and then I will go to networks. So actually here adding the networks mean that we will communicate, means adding channels for communication. So first of all, we should add the private network to communicate with our virtual machine and also with different instances. And also we should add this connection EO data, so means the connection to Earth observation data repository. Okay, the next step and the last step actually is security groups. So if we want to have our virtual machine visible from outside, so if we want to ping it from outside, so our remote desktop will be visible for us, we should add this security group. So allow ping SSH from remote desktop. So by adding, by clicking this arrow, we will just use this security group as it's already here. And then this is the last step, which is just enough for us to create the virtual machine. And then we should just click launch instance and it will be immediately launched. We should just wait a bit for building it, preparing it, and it will be running. So here what is important, IP addresses. So when we are creating virtual machines, the IP addresses, private IP addresses are already created. But very important step is also to allocate floating IP, which we will do soon. Then I would like to move to the console or my virtual machine to establish the password. Because I'm not going to use the virtual machine from, let's say this window from the browser from Dashboard. But I would like to move to the remote desktop and to use it there. So from this point, I would like to open the console and then establish the password for administrator so I can access the virtual machine from outside. Okay, it takes time to open to start the console. Getting ready. Okay, as always with live demos, sometimes it doesn't go so quick. But that's technology, so let's give it time. Okay, we have here the running console. Okay, as it's not running so quickly, maybe I would just simply show you how to access the virtual machine from the remote desktop. But okay, yes. So it says that the user password must be changed before signing in. Okay, that's right. So that's what we want to do. So here the administrator window, we have to find ourself with the running mouse. We have the mouse is doubled here. So sometimes it's hard to catch it. Yes, so here we have to create a new password. Okay, as we created it, let's enter. Let's change the password for the administrator. Okay, the password was changed. Okay, and then it's applying the changes and you can enter the console from here. But as you can see, using console from this place, it's quite painful. So let's move to remote desktop. So I would simply go back to instances. And then the only last step which I have to do is to allocate floating IP. So from this place, associate floating IP. Sorry, not allocate, but I will choose associate floating IP. So we have to choose the IP address for our virtual machine and the port which will be allocated to our virtual machine. So let's not allocate it to EOData IP, but rather to our private network. So this will be, it will be this one. Okay, sorry, I was somehow, okay, again. And this one and let's associate the IP. It's working and soon the floating IP will be added. Okay, so our floating IP is here. So here in the dashboard in this window, you have all the necessary information you need to know to work with the remote desktop. Okay, so from here, I would like to open the remote desktop. So then we choose the floating IP. Okay, somehow I can see, let's see. Okay, I didn't see my floating IP newly created. So I will choose the one which I've created yesterday. So this is the completely different, I mean the completely same step. Okay, and entering the virtual machine. Okay, so we are here. So this is our virtual machine. So if we, with Windows operating system. So if we would like to see the Earth observation data repository from the desktop, we have here the script written to mount the L data. So if we click the script here immediately, we will have the access to Earth observation storage, the whole repository. So you can see it's here and the total size is 44 petabytes. So really a normal repository. And we will try to see what's inside of this repository. So of course we will see what's inside, but then if you would like to work with the data, you need a dedicated software. Yes, so here you see that we have here Copernicus services, NVSAT, JSON, Landsat, and the whole package of Sentinel data sets and also SMOS. So here we have current data sets, which are available online. We online, we have also archive data sets. So if only you would like to, for example, compare to some analyzes of the data, comparing different stages, different months, you can search for the data here and you can use the data from this place, of course, using dedicated software. So that's the way of creating a virtual machine and then entering the virtual machine from the remote desktop. I hope this will be useful for you. So this is the windows and if only you would like to see how to create it with Linux, please visit our YouTube channel to see the tutorials. Okay, so then I will come back, I'll just disconnect my virtual machine and then I will come back to the presentation. Okay, so yes, I was here already created the virtual machines. Maybe at the end I would like to give you very short information on how our users are using Creo-DIS platform, what products they developed, what projects they've made, they finished on Creo-DIS platform. So one of the good example is actually software Cent4CAP. So Cent4CAP works on Creo-DIS platform and this is the freeware software dedicated for agriculture monitoring. So basically Cent4CAP software uses sentinel data and also Landsat data. So this is all actually dedicated for CAP purposes. So while using Cent4CAP software, you can, for example, generate such products as cultivated crop type map, grassland mowing products, vegetation status indicator, and then agriculture practices monitoring products. So you can actually get really nice and useful products so for the agriculture monitoring. And the Cent4CAP software is all the time, let's say, modernized and new versions has been developed. So you can check the software and see if it will be useful for your purposes. Then another example is S2GLC, which I have already told you about. S2GLC was a product, was a project, actually, developed by Space Research Centre Polish Academy of Sciences and it was one of the European Space Agency projects. So in 2017, they have prepared classification of sentinel to data. So you can see the whole map of Europe, land cover map of Europe with different class types. And then also an interesting project developed by Space Research Centre and also Institute of Geodesy and Cartography, which is called EOSAT. So those are services for Earth observation based statistical information for agriculture and the project was dedicated for the main statistical office and also agency for restructuring and manufacturing modernization of agriculture. So also based on sentinel data set, they have prepared classifications from different years to compare the agricultural state of Poland and to see how it has been changed over the years, over the months, over the different seasons. So as you can see, Creodes platform is the platform, the cloud computing platform, which can help you in developing such nice projects and also which is really helpful if you have big data to be processed and if your products, if your sorry projects need powerful environment and if you need really to process the data in a short time, but really, but in really efficient way. I hope you enjoyed the webinar and of course I encourage you to visit Creodes platform and to test the platform and to see how it works for you. Thank you very much. Bye-bye.