 Hello everyone. Good morning, good afternoon, good evening. Thanks for joining us today. Happy GIS week and happy GIS day in advance. I know we're celebrating a day early, but that's okay. We can't have enough of GIS celebrations during this week. I hope that any event or workshop that you have been attending this week has been fruitful and productive. Thanks to everyone who has joined us. Please feel free to introduce yourselves in the chat. Let us know where you're joining us from and why you're so excited about GIS day. My name is Mary M. Rabi. I'm with the UN Sustainable Development Solutions Network. I'm the head of SDGs today. And we have the pleasure and honor of being a member of the EO toolkit for SDG 11, which is one of the work streams led by the EO for SDG initiative. Today, we are going to hear from my colleagues from the GeoSecretariat, from UN Habitat, from ESRI, and from the European Commission Joint Research Center. We have a very exciting training scheduled on Earth observation for SDG 11, calculating the degree of urbanization. So before we jump into the training session, we're going to hear from our colleagues at the UN Habitat headquarters in Nairobi. I know that they have had a series of workshops and meetings related to this topic and methodology. So we're going to hear from them. Then we're going to hand it over to my colleague, Martin, from the GeoSecretariat to tell us a little bit about EO for SDG and the toolkit. Then we'll hand it over to my colleagues, Kira from ESRI, and Pietro from the European Commission Joint Research Center for the training. And please do stay with us until the end of the training, because at the end of the session, I'm going to let you know how you can get your hands on a free ArcGIS license to use so that you can then go through the training and learn paths over the next year. So five of our participants in honor of GIS Day will receive a free ArcGIS license. So stay tuned, and I'll let you know how you can win one of those licenses. Without further ado, I'm going to hand it over to my colleague, Dennis and Michele, who are in Nairobi. Over to you. Thanks. Thanks a lot. Hello, everyone. Dennis from Nairobi. Michele, come say hi. Hello, everyone. Michele. We are here with a big team of about 30 people, that is something people from different countries who are working with us this week to share experiences from implementation of the de-globanization that we've been supporting the last three years across 13 countries. And of course, this relates to the global need for harmonized city definition. A journey that we started in 2016 at the Habitat Conference in Ecuador. And we've been working with multiple partners, of course, including the European Commission to support the adoption of a globally harmonized method that can help us to measure urban trends in a more consistent and harmonized manner. So we're really excited that activities have implemented through the years which started with global consultations in 2018-2019 with about 85 countries on the feasibility of having a globally harmonized method to define cities and urban areas, which then led to the adoption of degree organization by the UN statistical commission for global adoption and application for measurement of the STGs. It's really a journey that has been quite interesting and we've engaged with different countries and seeing how this de-globanization manifests and shapes the local context. So the adoption of the method in 2020 came also with a request to us, Habitat, the European Commission, World Bank, ILO, OECD and FAO who are the sub promoters of this concept of harmonization to support countries to actually be able to implement the method using their data. So from this is where we started another process of supporting countries directly to implement the de-globanization using their own data and national processes that build on enhancing collaboration and partnerships between national statistical systems but also other relevant agencies at the national level. So the first phase we've supported 13 countries which I will pass here today, I'll pass them screen over around so that you see who is here. 13 countries here, we have Kenya, we have okay, let me see how this goes. We have Kenya, we have Egypt, we have Philippines, we have Tunisia, we have Ecuador, we have Chile, we have Kazakhstan, we have Indonesia, we have Peru, we have Nepal, we have Mexico and Azerbaijan. Did I see Kenya? Okay, so we have two representatives coming from each country, majorly from the statistical system but also the ministries that are responsible for human development. And we've been really having very interesting last two years to work with them and also many other multiple partners at the national level to apply this method. So this week we are really having these countries share their experiences on what has been the outcome of applying de-globanization as the recommended global standard for measuring urban and rural trends but also the intersections between these different urban rural continuum manifestations. So we are happy that we've had a very successful three years with countries and we're looking forward to continuing this because we are just rolling out another phase of support to another 40 countries in partnership with UNICEF and UNEPF and we really look forward to hopefully looking or rather seeing the application of the de-globanization based on the training we're going to have today. And thanks a lot to S3 for of course supporting this lesson on application of de-globanization for ACATGIS Pro and some of the countries I know have been asking us say this is available and I'm happy also European Commission has really made it possible to have these tools available for ACATGIS Pro for all the countries. So Mario if you allow me I will quickly show you who is in the room and we will stop our intervention and get back to our session for the day. Sure sounds good. Thank you. Okay. I hope you're visible uh I'm what are you saying? Yeah I'm not my hand is now I'm visible. Hi this is Amir from Egypt. You are Amir, how are you? How are you? I'm from Egypt. Amir from Kenya. Salam, also from Egypt. Salam, Samira from Tunisia. Oh, okay. Hello, from Philippines. Hi, I'm from Philippines. Amir from Egypt. Gracias. Hey George, you're an habitant. Hey Jasper, you're not that good. Hi, Marlon, Ecuador. Hello, I see. Hello, muchaus, from Malawi. Hello, thanks for Malawi. Amir? Hi, Nepal from India. They're having their coffee. Hi, from Masafacha. Yeah, hola. Saludos. Hello from Mexico. Okay, last two. Hello again from Egypt, Hasan. Hola, saludos, Francisco Moreno, from Mexico. Okay, Mariam, that's it from us. Thanks for allowing us to say hi and truly wish all the best in the session today. I look forward to also seeing the results from the global application by the different people who will be part of the training. Great, thank you so much Dennis. It was so lovely to see everyone in the room. Thanks for joining and we look forward to learning about all the great work that you're doing and leading in your countries. Great, so without further ado, I am going to hand it over to my colleague Martin Clark from the GeoSecretariat to tell us a little bit about the EO4STG initiative and the EO toolkit for STG11. Over to you, Martin. Thanks, Mariam. And afternoon or good morning, everybody. I'm just going to share my screen, if I can. Here we go. Yeah, thanks for the opportunity to speak. I won't waste any precious time because I'm sure you're all eager to get on with training itself. But just to give you a bit of context, a bit of background to kind of where the EO4STG initiative came from or is framed by and specifically what the EO4STG human settlements toolkit is all about. So I am the Urban Resilience Coordinator at the Group on Earth Observations. I'm based here in Geneva with the rest of the GeoSecretariat team. Geo, for those that weren't familiar, is an intergovernmental partnership. We've around 115, 120 national governments and then 160 plus other organisations, private sector organisations, civil society, NGOs, etc. All working together to try and promote the use, uptake, application of Earth observations as a public good. So that really means ensuring that Earth observations data, information and insight is open equitably, you're publicly accessible and is being put to use to address some of society's greatest challenges. I think that is best framed by the sustainable development goals, which you find referenced or reflected throughout a lot of the work that Geo does, but also some of these other major global policy initiatives like the Paris Agreement, New Urban Agenda and the Sendai Framework for Disaster Risk Reduction. Geo is largely funded through in-kind contributions from its members, from the participating organisations I mentioned. And we have a work programme which is around 40 activities in that work programme, which covers all sorts of engagement priorities, we mentioned climate change, urbanisation, SDGs. EF SDG is just one of those activities. And it's a very central one and we find that it's not only, it's focused on the SDGs, but it works across all the other activities on our work programmes, as well as engaging with organisations external to Geo. So at the moment, I mean, it was established in 2016, it's currently co-chaired by both NASA and JAXA, the Japanese Space Agency. And the general purpose of this initiative really is to organise and realise the potential of Earth observations and geospatial information to advance the 2030 agenda. So we're at the midpoint now and it's still of major relevance. There are three goals really, or aims that the initiative seeks to achieve. And that's really in the demonstration of how EO Earth observations can actually contribute to monitoring and implementation of the SDGs, increased skills and capabilities of those wanting to or using Earth observations to further SDG activities and achievements and then to raise awareness of, I guess, the importance and the use of Earth observations in support of the SDGs themselves. We've got a board that's been established with 100 plus affiliates and a variety of organisations that support the implementation of this project. There are sort of four SDGs that we currently cover. Six on clean water, 11 on sustainable cities, 14 on life below water and 15 on life on land and there's around 24 individual indicators that we can use Earth observations to measure. And monitor, that's not to say that there are other targets and indicators throughout the SDGs that we can contribute to, but these are the ones with the greatest opportunities, at least in the first instance. The one that we're going to hear about today and the focus of one of our sort of offshoots, if you like, the EO toolkit for sustainable cities and human settlements. There's about seven indicators in that SDG that Earth observations can be very useful for. And I suppose I'll just talk a little bit about what we actually do. So it's all about sort of developing and promoting standards like the degree of urbanisation that Dennis referred to before, getting the use of those standards written up and detailed in policy briefings and other publications, running events like we've got today, capacity building trainings and awareness raising activities, as well as showcasing some of the interesting applications uses of the projects themselves through an annual awards programme, which in fact, we just concluded last week in Cape Town, where I know some of you are present. As you can see, there's a wide range of organisations that contribute in some way to that activity. And I would urge you to, for those of you with the kind of urban leaning focus, I would urge you to have a look at our toolkit on sustainable cities and human settlements. There's lots of resources in there, links to data, descriptions of tools and methodologies, as well as a number of use cases detailed that demonstrate how these tools and methods have been put to use in real life and some of the impact that we've realised from that. Anyway, I'll cut it short there. Do feel free to reach out if you've got any questions on the toolkit on geo more generally, and I think we'll share some email addresses afterwards, but I'll hand back to you now, Marie. That's very much. Thank you so much, Martin. We're having some technical issues with one of our speakers, if you give us a moment, we're going to have my colleague Kira Morish from Esri join us for the next segment of the webinar. So please just give us one moment. Yes, in the meantime, maybe I can comment and thank the connection from Nairobi event. I think it's really nice to see how this is becoming a global endeavour and how countries are committed to the implementation of the degree of urbanisation worldwide. I think it's really amazing the way we've gone through and how people are now able to disaggregate statistics by degree of urbanisation, especially with regards to sustainable development goals. I think this is a very powerful tool and also a success story for people who work in GIS. And also you show the, we've seen the power of capacity building exercises stated by the partners in the degree of urbanisation and implementation, you an habit at the European Commission. I think there's really space for everyone to get to learn how to produce statistics by urban and rural areas. So it's again, I think this one, an occasion to show that really everyone can, with some free data and tools, calculate a bit of the progress towards sustainable development goals. Thank you so much Pietro. Maybe Richard, if you could make Kira a speaker, that would be great. I think she has joined as an attendee. That way she can enable her mic and camera. Unfortunately, I cannot see her in the attendees list. Okay, so maybe what we'll do is Pietro, we can start with a training session and then once we're able to get Kira online, we can have her present a little bit more about the learn lesson. So once again, thank you, Martin, for the introduction and Pietro, over to you for the training. Yes, thank you. Okay, then I will start to share my screen here and thank you through this journey in the degree of urbanization application on Esri tools. So we thank again our colleagues at Esri for producing this nice learn lesson. If you are not on this page, then I advise you to find it on Google. You can also Google it easily and find it by searching Esri training degree of urbanization. Or if you click on this link, you will land on this page where there is this nice step-by-step procedure on how to apply the degree of urbanization to your own data anywhere in the world. To run this training that I'm going to demonstrate today, you need ArcGIS Pro and then you see I have it here on my screen. Then you also need the global human settlement, the GURBA toolkit, which is a bunch of software tools we have produced at the European Commission explicitly for the production of the degree of urbanization. You can have it by clicking here on the proposed link. Then if you scroll down a little bit, you find this section here with the degree of urbanization. Then you can download the ArcGIS version online. It does the online and offline version, but the online one is fine. It just needs to connect briefly to the internet to check that your system requirements are satisfied and download a bit of the backbone code. Otherwise, you can also download an offline version, put it on a USB stick and use it later. The standalone version is a standalone interface that does not work with ArcGIS. It is then an independent interface that you can run without having the need for ArcGIS installed, but today I'm going to demonstrate the ArcGIS version. I'm going to download this one. I have downloaded it already, of course, to save you some time. The other thing we need to run this training is to download the package, of course, the dataset package that is here at step number one. I'm going to click here and save it somewhere, let's say here. I have saved it already, but I'm going to overwrite it. It's a lite file, so it's only 1.9 megabytes. Then I will navigate to the folder in which I have saved my file and double click it. This will open ArcGIS. I am under a proxy server, so I need to enter a password to access the internet. This is my company policy. Sorry for this. It's going to happen only once. Okay, here is the main interface of ArcGIS that many of you should know already. Here you see the content of the dataset. Today we're working on a case study in New California, which is a faraway country for me because it's on the other side of the planet in Oceania. The dataset contains what could be called a census map. This is how it looks like. It contains the polygons of the administrative areas or the enumeration areas counting the population. I can also rename this map as a census. This will help maybe because later we are going to produce more maps. Okay, let's call this census. We can see the attribute table, of course, to check what's inside. You see there is a bunch of polygons and each has a name and a population attribute and then a province of appartenance. Here we are going to use the population attribute to first produce a population grid and then classify each of this polygon by degree of urbanization. This is the ultimate goal of this training. Then we can use this classification to produce and break down statistics in each of these polygons by its class in the degree of urbanization. Let's say we can first label our features maybe so we see their name appearing and maybe we can also change the symbology here to something a bit nicer in order to see the population growth, the population distribution across the different districts here. With this color scale we see immediately how where is the capital city which is Nomea here and the surrounding areas that are also quite populated here. We could also of course normalize this by the area but we are not doing it now for brevity. This is the first thing that the dataset contains. Then you see there's another dataset which is called GHS build. This one is actually the built-up surface identified on satellite imagery for this area. It's a raster dataset so it contains the beta squares of built-up surface in each pixel encoded as meter squares so it goes from 0 to 10,000 because it is actually at a 100 meter resolution. We can check this in the raster information properties and you see that it's 100 meters. We can also symbolize it better maybe we can mask zero values and zoom in a bit to see how it looks like. Maybe I can also use another color scale that is maybe clear. We see again how the area of the capital city contains the highest land surface occupied by built-up. We're going to use this built-up surface to specially desegregate the population that we've seen in the census. We're going to distribute the population that is lying in each of these polygons based on where the buildings are. We use this proxy variable of built-up as a desegregation variable. Okay we can keep the census here shown. The good thing that I also wanted to mention is that in this training the GHS built layer is preloaded but if you go to our website the GHS global human settlement layer website which is at this link we've seen it before to download the tools. We can also download the data so if you are interested in another area of the world you can click here on data and tools download the data and you will be sent to this page. You see there is a tiled globe so you can download from here the built-up area you're interested in. Here we are in New Caledonia it's this area here. We are going to use the built-up surface so again the meter square of buildings encoded at pixel level but we may also download the volume information because recently my team the global human settlement layer team has produced a global volume information layer which contains the cubic meters of built-up volume. It is made by extruding the surface times the height so from here you can as well download the volume information and bear in mind this is a multi-temporal information layer so you can download the data set for any of the time slots proposed. Okay let's go back here at our New Caledonian case study and now we need to import the library with the tools that I downloaded previously so I need to go here in the catalog and on toolboxes and click on add toolbox then I have I am sent here automatically to the directory where I have downloaded the tools but you may need to navigate to the folder where you downloaded it. There is details about this operation in the website of the training on azure web page. So when I import this toolbox I have a list of tools and as I said before what I want to do here first is the desegregation of population on a population grid. Let's create the first and output folder I'm going to create it here in this let's say home directory that I have dedicated to this scope I will call this output okay and then I will open my ghs population to grid tool is the tool dedicated to the special desegregation of population from sensors to build up and I am sent to this interface first thing I need to do is to select an output workspace I'm going to add a new connected folder here maybe I'm just navigating to the actual place so where I've saved the where I've created my output folder just give me a moment I need to find it here this pc x gis week and output folder I'm going also to add it here in the connected folder because it's going to be useful also later so here it is gis week okay let's go back to the population to grid interface here I am asked to enter an output projection by default it would be this world more wide which is an equal area global projection because we are doing we're dealing with population distributions and possibly computing population densities so it is needed that the projection is an equal area one then here I need to load my population polygons layer it's they're those ones so I'm just going to drag them here and from the attribute table of this population census I need to select the population attributes that we saw before being this population 2019 the other fields are to optimize the computation this one is a stepwise field that is used to optimize the computation or we have the option to load a point layer in case your senses is not structured in polygons but in point features I don't have this case here so I just need now to load the built-up raster which is this one remember again and I'm dragging it here so this one is going to be used for the disaggregation of population then I'm going to run the tool it's going to take a moment in the meantime I can create a new map that I'm preparing to visualize the results I'm going to name this one as population grid and then I'm going to dock it then this one is pointing to Italy which is the place I'm connecting from but of course I want to link it with the the new caledonian case study so I'm going to click on link views with center and scale and it's going to show me new caledonia however the projection is different because by default the projection used is not this equal area I was mentioning before but the standard global marketer projection so I'm going to go here click on the properties and then in the coordinate system select the mole wide one if you don't have it in the far in the favorites you can simply search 54 009 which is the psg code for world mole wide and it will appear here I'm going to click okay and you see that the present the projection now matches good and I see also that there is the population to grid completed so I'm going to open the output folder it is here output folder and you see that there is a file in here it's a raster file as expected because we have a population grid I'm going to create the pyramids to ease the visualization and I'm going to act a bit on symbology for example I'm going to set this color scale for example I'm going to visualize it as a minimum maximum and edit the min max values ranging from zero to let's say 1500 which is usually a good value at one kilometer resolution and then I'm going to mask the zero values good so this is how my population grid looks like and we can zoom in to the area of the capital and we see how the population has now been allocated to the capital which with much higher precision compared to the census here we barely see any difference in terms of population distribution between these three departments here like pita dubia and montore or numea and then we actually see that on the population grid most of the population is actually lying in in the capital is actually living here in the capital so we can even click on pixel and visualize the number of inhabitants that has been distributed here based on the built up surface so we've used the simple meter square of buildings of built up area in in this region to distribute the population that appears as an attribute in the population census good now we can we can pass now with the second tool and to do so I'm going to open the degree of urbanization grid to double click here and this one is intended to create another grid which holds a categorical value standing for the degree of urbanization classes this requires an output workspace as well I can select the output folder just as before and a population raster which is the one I produced at the preview step so I'm going to go here and select my population grid at the thousand meter resolution I'm going to use the reduce urban center fragmentation which uses again the built up raster to actually avoid having urban centers scattered in many fragments and pieces around my map so with this option I'm going to have a more rather more compact urban centers I'm going to load the built up raster here and leave the rest of the options as default I'm running the tool now and in the meantime just as before I'm creating a new map appearing here I'm going to dock it at the bottom of my screen actually in this corner here I'm going to name this one I'm going to change the the projection of this map as well to worldwide and I'm going to rename it also as degree of urbanization great okay and then the output files have been produced so I will navigate to the output folder and I see there are plenty of things all these are let's say the features the feature files in shape file format corresponding to the different classes but there is also a raster file with the classes in categorical values I'm going to open this one the level two classification of the degree of urbanization ArcGIS asks me to calculate statistics and pyramids I'm going to say yes and this is my map so the colors that you see here correspond to different urbanization categories I'm going to list them all by changing the label here in the symbology so then is the value that corresponds to water then 11 stands for very low density rural grid cells 12 stands for low density rural grid cells then 13 is for rural clusters so a bit denser like villages and then 21 is for suburban and very urban grid cells and then we have 22 which is for semi dense urban clusters 23 which is for dense urban clusters and 30 which is for urban centers good but this legend we can zoom again at around the area of the capital city and see how the capital city is an actual urban center so it's a city as expected it is surrounded by a bit of suburban and very urban areas there are also some villages or rural clusters there is also a semi dense urban cluster here a dense one here it seems pretty nice and then the rest is more or less rural with some villages or rural clusters here and there you can check on our methodology the thresholds of population size and density used to produce this classification but I'm not touching it right now because I want this session to be very practical okay now the last step I want to perform is the creation of the classified territorial units so I want this starting map here with the census units to be colored according to the degree of urbanization categories so I want to assign to each of these units a degree of urbanization class in order to do that I open the degree of urbanization territorial units classifier again I will have to click on an output folder and I select the usual one I will need to load the territorial units from the starting census in shape file and then I can set up this stepwise field to optimize the computation and group units together by province or by district and then the tool will iterate over each group of features but I don't need this because it's a small file and with a relatively small area so I'm going to leave that one blank I just need to select the population attribute here which is this one then there's the option to input a cross tabulation field in case I already have my national urban and rural classification for each administrative area then the tool will produce a comparison between urban and rural classification according to the national definition and the degree of urbanization definition I don't have this field in my census attribute table so I will leave this one blank as well I just need to load the population roster from output produced the before so I'm going to go to the output and select the pop2g output so the population grid at 1000 meters and the degree of urbanization roster so this one I'm also to select this one level one or level two is is the same if you select level one you will only produce level one now if you select level two you will produce level two and level one level two contains more classes they're the one I listed here level one contains fewer classes let's select level two and run the tool in the meantime I'm also creating a new map here as usual I'm putting it here and then here I'm going to the properties rename it as classified territorial units units and change the coordinate system to worldwide okay here it is and now in a moment we will see the results so I think it's also nice and convenient this feature of ArcGIS pro which I love personally to have multiple maps synchronized and in this way it's easy to visualize data sets that needs to be compared that need to be compared to complete it it's going to be called just like this input shape file which is NC 2019 population I'm going to find it here and see 2019 population plus there and then and then there is a suffix which stands for the tool so GHS DUTUC territorial units classifier here's the shape file I can drag it here to my map I have this monocolor map so I need to import a symbology for this one and to do so I go to the symbology tab then click on import symbology and the symbology layer is going to be here in the output folder so you have multiple options you can either visualize level one or level two I suggest you visualize level two because it's the one we've been visualizing in the grid so let's select level two and then run and here it is so what you have here enlarging the legend here what you have here is a classified census with the territorial units assigned with a class from the degree of urbanization level two let's zoom into the area of the capital city so you see here that this area of the capital city is classified as city and then this area here it's slightly dense because the suburban area is dense down and also a semi dense down so in the end it inherits a class which is dense down and this class is attributed by majority of population so based on where the majority of population lives across these cells in the rural in the degree of urbanization grid and here this one is classified as a village because the majority of population in this polygon lives here in the cells of rural clusters so here it's how it looks like there's the rest of the island is classified pretty much as rural there is only this district here which has you see quite some population concentration it is classified as rural clusters in the degree of urbanization grid and then it inherits the village categorization under the territorial the classified territorial level good so I think this is it for this training remember you can look at it again step by step on this website if you want you can also access a thought of a version of the training at this link that I'm going to show now it's the U academy degree of urbanization this one is a free and open course which contains all the information you need to run the tools this one is for standalone version of the tools so it it's not the one in ArcGIS but it contains also a lot of theory and background information so if you go to this link and then unroll you can access all the different modules if you're interested in knowing more about the methodology of the degree of urbanization you can also google your stat degree of urbanization manual and you are going to be directed here to this methodological manual to define cities towns and rural areas for international comparisons there is a version in English one in French and one in Spanish you can download so once you have produced this output it's very easy to disaggregate statistics of your sustainable development goals indicators by urban and rural categories and then it's much nicer to produce insights or your key partners like UN habitat or even to disseminate the results to the public and remember this definition is intended for international comparisons so it might differ a bit from what you expect at national level but it's common to everyone in the world so that's why it's great because everyone can produce the same statistics with a common definition thank you so much I have I've come to an end so I thank you and let you intervene if does cure our someone again yeah so thanks again so much for that training session and thank you Thomas from the GRC for also responding to the questions and sharing the links in the chat um we'll share our email at the end for anyone who would like to um ask more questions we'll direct it to each of the other different speakers but for now we'll hand it over to Kira Morish from Esri to tell us a little bit about the learn path before we conclude the session Kira over to you thank you um Pietro thank you so much for presenting that lesson as well so the lesson that Pietro walked through is really from the European commission they've done all the hard work and we have translated it into um the the Esri software so if you're using ArcGIS Pro this is a great platform for you to be able to step through the processes that Pietro just showed no problem thank you very well done and um Carmel is here as well if you wanted to say anything thank you so much um Kira and I think Carmel is sharing the link to the learn path in the chat for anyone who would like to learn more and follow and as I had promised uh the beginning of the session um I will now share my screen just to give you uh our contact information so as I mentioned in honor of GIS Day Esri has given us five ArcGIS licenses to share uh with um our participants so if you're interested to go through the learn path or to explore ArcGIS for any other projects um feel free to email us at scgstoday at unsdsn.org share a short paragraph on as to how you're going to use the ArcGIS license for a specific project and we will randomly select five of our participants and follow up with instructions on how you can access the license so again feel free to email us with any questions or requests to win the opportunity to access one of the licenses at sdgs today at unsdsn.org and feel free to follow us on any of our social media accounts we'll be sharing recording of the session in the next couple of days thank you all for joining us it's lovely to see people joining us from all over the world thanks for sharing uh and introducing yourselves in the chat unfortunately we don't have time for a Q&A session but as I mentioned feel free to reach out with any follow-up questions and we'll connect you with uh with the different speakers uh happy GIS week happy GIS day um thanks for joining us and have a lovely day bye everyone