 Welcome to the NPTEL course on remote sensing and GIS for rural development. This is week 11 lecture 3. I am happy to welcome you for the sections where we will be looking at something very novel and unique that we are learning in this course. As I explained in the urban centres and urban regions there is multiple data that we can readily use. On top of that the government, agencies and private companies collect data. Whereas when it comes to rural regions there is much less of data that comes in therefore in this week we had introduced the concept of synergized mapping which is very new and unique because either people use only remote sensing or only observation data and some people do merge them both but then with crowdsourcing data we are developing new skills. This is going to be the future because a lot of people depend on crowdsourcing for updating the data at a very high speed both spatially and temporally. Now think about adding another layer on this when it comes free open source then the potential benefits are a lot and very enticing for everyone to use. On that note we had looked about the concept of synergized mapping in the previous lectures and we found that OSM open street map has been widely used across regions across the countries globally for crowdsourcing of data. So you don't have to maintain a database, you don't have to maintain servers for the data to come in and use by users because all of this has been funded and operational till date from 2009. Slowly it has grown to a very robust system and while it seems that we are promoting this particular app it is not for their benefit but it is for everyone's benefit. Think about an open source system where we have data and updated regularly. The last slide we looked at someone just entering data 11 hours ago so spatially and temporally also it will be one of the best data and if there is some kind of schematic system that encourages people to participate then more and more data will come. In this world of data as everywhere it is very important to have a system and a platform where data can be easily, seamlessly coming in and used for benefits after we merge it with couple of data. What is missing in the OSM part is the remote sensing applications which we will be doing in our current class. We will be using the benefits of multiple systems, remote sensing, GIS, OSM and then merging them all into GIS platform and then checking on how the research can be done further. On this note in week 11 lecture 3 what we will be doing is seeing how we could combine OSM, RS and GIS, OpenStreetMap remote sensing and GIS interfaces for rural infra mapping and development. Please remember that a lot of people do ask more on water aspects for this course. This is not a rural development for water it is also for other resources and while agriculture is the key dominant livelihood I had put more time on agricultural resources land, soil, water, vegetation but we cannot neglect the other infrastructures because the reviewers of this course while they said it is very good they also wanted these to be reflected. So as a whole I am going to give the next three sections for it and some case studies and references on how these case studies have been done will be conducted in week 12. We are coming to the end and you would have seen that I do not have much summary for each topic because you can always go back to the lectures and view it but if I use summary then I am losing a couple of lectures. So I encourage you to go back I can give a hint of summary at the week 12 but at week 11 what I am proposing is please go back to the lessons I have seen couple of students sending uploading their materials on the forum which is very very useful which is very much making us happy because they are putting so much time on this work so we are very happy for that and we would like to say that even though some of your comments I could not readily address because of the need of the course we have made it more robust. There will be some updates in the columns of data that we are going to see now. So let us see how we are going to map OSM plus RS plus GIS for total infra map plus development. So how we will do is I will just go through the steps and then we will follow the same steps in the OSM platform. So we will first extract by name, name of the attribute and then the boundary. So OSM is mostly for extracting shapefiles, vector shapefiles not for raster because you won't expect people to share raster for a particular area let us say a school boundary. We will be discussing more about the rural infrastructures that I have given you introduction in the previous initial slides because when we talked about rural development we talked about water, soil, nutrients, forest cover, agroforestry which all we have covered but we also mentioned about education, access to schools, access to healthcare these kind of attributes. And these are not rasters these are vectors so these are vectors that are stored as attributes in the system and we will be accessing them through these OSM. The point of introducing this software is also for you to put in the data so it's not only one way it's not only that I should be using this data I can also contribute to this data by having a login and then putting in the attributes. We'll show you how this can come in play especially for the regions that we have already looked at. So we can choose what type of attributes we would like we can choose points, nodes both are kind of similar because those are point shapefiles we can choose a point shapefiles for location of schools, hospitals, educational institutions, kindergartens, ungun bodies etc. Rational shops all these are points because it's a location. We can also have other shapefiles which are under the vector columns which is one as points we have already seen then we have lines and polylines we have multiple lines that can be connected. One good example is your waterways in rural areas, streams, springs etc. and more importantly your road networks because we want to connect the livelihoods to the market. We also have the last one which is polygons and the polygons are very important because parcels of land can be mapped you can map the size of schools. We'll show you how the school size will be different both as a point and as a small area polygon and we'll go through these exercises together. So there are three types of shapefiles that can be generated through this OSM very focused on rural development which is points, multi points and then we have lines, polylines and we have polygons that can be shared. An example would be you can also have queries for crop selection. It can be banana or sugarcane or you can do banana and sugarcane. So how will this be helpful? Let's say I'm going to map cash crops in Pune region. When I went recently to Pune I was shocked to see a lot of people converting from sugarcane to banana because they're having a good market in the Middle East. So this banana can be taken as a crop or it can be combined with sugarcane as a cash crop and then searched. So in OSM we will be doing a lot of queries. We will search for data and then plot the data using internet access. Healthcare also we'll be doing in the sections, schools we'll be doing as a polygon and a node and we can also search by village name. Only problem here is make sure that the village name is same as what the OSM software might have. So OSM is you can imagine as a database sitting in a cloud and what you will be doing is while running the QGIS program to connect with OSM you will be building a query to download the data. When you download the data it will talk to the cloud, bring the data, correct? So in the cloud there are a lot of databases and the spelling might be very different. So for example, India spelling is INDIA. Only when the spelling is correct you will bring India's data. Like if you write like West Indies, if instead of West Indies you will put West India then it won't go to West Indies, it will go to West part of India. So now you have a hint how these names came into existence. So naming is very, very important and you will be very cautious in putting the correct spelling otherwise it will be difficult. And to beat this we always use shapefiles. I'll show you how to do both so that you can quickly do queries in the next three lectures on schools, we'll start with schools today then colleges and then we'll also look at healthcare institutions and then finally go to the location of the crops. It is also important to understand that there are limitations because it is free, because open source, there's a lot of quality checks that we need to do because not all would be doing it for accurate quality, it both happens in proprietary and open source. We cannot say that since people get a salary they're going to do it correctly nor we can say that since it's free it's correct. So there could be some issues and errors, we should be able to check it and what we will be doing is we'll be using Google Earth Pro as a means to check on the data and then save a shapefile. All the data searches that we do and populate in QGIS we can save as a shapefile. For all this you need internet, this OSM package runs on internet because the database is so big and it gets updated often, you cannot keep it outside in a server and then connect to it or on your laptop and connect to it. You need a cloud or a server which is connected to high speed internet. So your internet will talk to the server, collect the data and market. It's not like you download all the data. So when you download the plugin, which we did in the last course, you only download the interface to the plugin, not the data sets. So what we'll be doing is we'll start the interface and show how we will be using a quick query tool to assess these different data sets that we want. So quick query looks like this. You have the preset which is already set conditions to search for data and then you have the data that you want to extract. The key variable, the key column is what is the variable about on the OSM database? And what is the value? So here you could look at it as key is the overall theme and the value is the attribute name. So the overall theme is amenity and then you have hospital. The overall theme is hospital health care and then you have value as hospital. So sometimes why this is needed is sometimes there will be different names given. Instead of in India, let's say we will put all hospital data and health care, not in amenity. But maybe in Nepal, you will be putting it in amenities and not in health care. So what happens is when you're doing a mapping of the Ganges health care facilities, the ones in Nepal will be omitted. So that is why you can have one query built and add other queries to it. You can strictly make it as a condition as and or you can make it a condition as are, which means, so for example, if I put and here, so after the query, the results for wherever amenity is equal to hospital and health care is equal to hospital will only come. And if amenity hospital is not there, health care hospital is not there, it won't come. It won't be populated. Whereas if you say are, then both will come. Amenities that are labeled under hospital and health care, which are labeled as hospitals will also be populated in the page. So let's look at one query and then we'll come back to the next slide, which talks about, it will be talking about the quality checks. I'll just introduce this slide, but we'll come back again. We'll be looking at checking the data, how to check the data. Some key notes is the data of the data is not possible to have for every single data because it is updated frequently, which means the temporal resolution is very, very high. It cannot be updated equally. For example, you can see here for the tricky reason that we'll be doing today, someone has input data just hours ago, 16 hours, one day ago, et cetera. So in that note, we cannot keep on updating the temporal cycle. And also we are not sure like every day the data will come correct. So you cannot guarantee it, but you can see that it is the most updated data because people do put in data. Accuracy may not be the same as different users. So as I said, all volunteers may not be trained in the current level, but all volunteers have equal access to this website and they can contribute equally. There is some clearances of data. You cannot put wrong information in it. There is some checks and all, but it won't check for more, more accuracy. For example, if you're picking a building from the top alien view and then say it's a school, it may be a school, it may be a hospital, it may be a shop, no one knows except the user has put it in. So there's no one on the ground who goes and checks it. Maybe a concept that can come is voting. Like people can vote if they're on there and say, yes, that is a school, yes, that is a hospital or a mall. Then that voting system can create confidence. Like for example, you have a hotel. How do you choose a hotel on your app? You will say, okay, how many people have had food? How many orders? And how many good reviews have been there? Five stars, four stars, et cetera. The same like that, we can map it here and then say that how many people have actually verified it and based on that the star ratings will go up. Most of the time in rural regions, this will not be working because you don't have that much people contributing anyways. So we'll have a very less, less amount of data. The terminology is many have different terms for names. So for example, someone will call a school as school, someone will call it as an Anganwadi, someone will call it as a kindergarten. So you will have to be careful enough to negotiate these names and then pick the data and then make your own database through the Google checking, which we'll be doing. So with this, as promised, let's get into the schools checking for which you would need to have your QGIS up, which we already have. And I'll be sharing the window space here so that we will be looking at the QGIS plus the plugin page. So I'll share the entire screen that you can see. And what we'll be doing now is we will be looking at the plugin. So how do you open the plugin? You'll go to vector, go to QSM and then you'll see it here. Sometimes what happens is you will have the data being mapped at regular intervals, okay? And the software gets updated frequently. So you will need to make sure that the data comes in regular intervals and you keep on updating. Also the software gets updated. So I had run into this issue, so I'm putting it up here while recording if this happened, right? So the software stopped to communicate. Why? Because it was being updated. So always if the software, the plugin crashes, go to the plugins and then see if you need to update them, okay? I'll show you quickly. So the quick QSM, you could see that in the last lecture it was 2021, which is 2.1.1 version we used, but just now, so today's date is 21st March 23, just last night or in the morning today because of the European time, they updated it. So once they update, this will stop working until you update it and it will not tell you that you need to update like your other apps because this is not a paid version, right? They will not force you to update it. So I had that issue and I had run again and again and finally found out that you have to update it. So whenever there's an issue, just quickly update it, it will work. So as I said, I have opened the QSM app and when it comes to the plugin, you will have this quick query already loaded. Go to quick query and then you have the preset values. I'll show you an example of preset. We'll compare that soon, but let's say education. And then you have education kindergarten or facilities, education college, okay? Or school, we can have since school is a theme, we'll have education school. Once you say school, what it does automatically, it says amenity schools will come. This is a preset search. So for this thing, the key theme is amenity and under the value it is school. You can add another one because it's just amenity, right? So you can add another one, say R and then it could be, you can go here and say kindergarten, it won't populate because you have to populate the theme. So let us populate education will not be there, amenity. And kindergarten, okay? So kindergarten has come up. So now we have two questions. It is amenity is to be equal to school plus, and or amenity will be kindergarten. Or if you say and then both have to be yes, yes. Both have to be true for the output to come. Like for example, the school in IIT Bombay does not have a kindergarten. It has only one to 12. So only that school will come up, but the IIT Bombay school will not come up in this map because it has no kindergarten. If you take my school that I went to in Chennai, yes, it will come up because it has schooling from LKG UKG to plus two. So you see how one search, you have to be careful about it. The query button is if you know how to do Python coding, you can type the query, but that is what BigQuery does. It freezes interface so that you can populate the query automatically. And these are other OSM file where you want to save it. What type of OSM files do you want? The dietary can be temporary. Keep it temporary for now because you'll be saving it only if you like the data. And then you have parameters, abort, et cetera. Parameters you need to have this overpass access to API, which will be loaded. So now we have the search things selected. And what we'll do now is in, where do you want? Is it within a village? You can give a village name or a district. So I'm going to say through Sira Palli here. Now what happens is if the spelling is different, it will not pick up. So make sure that if you know the area, I have already shared all the data with you in terms of the links, where to get data, where to get district boundaries, block boundaries, use the boundary, use the spatial boundary rather than this. So I'll show you that. What I have done is I've already loaded Trichy, which is a short form of Trichy Palli. And a lot of people still use that in official names when they write. So it's still usable. Let's say layer extent. And the layer extent are these, one of these three spiles, I'm going to say Trichy. And then I've showed you how to extract that from the overall shapefile. Also you can do this. So for example, if you have this selected Tamil Nadu, which we'll do later as an exercise. So then only Tamil Nadu will come up. So because of this, let me just make this sound. So because of this open box, we cannot do the select tool now because it's already selected, but let's show you the other way. This is your history. It gives you the history of what you have searched and collected data and the advanced part is where you will have to tell, do you want the boundaries? Do you want the lines or nodes? This will take too much time if you have everything, right? So let's keep nodes and points. We want the location of the spools. And then we'll say ways and lines. We can keep that, okay? Nodes and points we'll keep. Ways and lines is paths. Way is a path. Do you want the way pathway to the school? We don't need it. Do you want a road line to the school? We don't need it. Do you want a relationship to the school? Multi-strings, we don't want it. Do you want a polygon? It gives the area of the school? Yes, let's keep it. So some data could have come as polygon. Suppose I'm a user, I gave a data for the school. I would have given it as a polygon or a point, right? So this aspect is where you will be careful to negotiate how to bring the data in. So I'll just say both. It will take some more extra time, maybe a couple of seconds for my system because my area is small. If you use a big state, then a lot of data has to be given. A lot of time has to be given, right? So all this is enough. All these keep it default and then go back here and say run query, okay? If you say show query, like if you go here now, nothing is populated. But if you say show the query, now it gets populated. So the code that you gave in quick query is automatically converted to a Python. The selections you've given, the selections you've given, all these selections have converted to a query and it says school or kindergarten for the particular thing. And it says you need to time out for a particular time and then it says for the particular extent. So everything is coded. Now all we have to do is run the query. I'm running the query. Here on the bottom, it says running the query. One layer has been uploaded, okay? Let's see what layer has been uploaded and it has been the locations. Amenities is school, kindergarten, okay? Let me zoom into that layer, right click, zoom, okay? So once you zoom in, you could see that this is the quality issue I was talking about. Some have been labeled as tricky schools but they're outside the boundary. You cannot blame them, okay? Maybe their location, the phone or the GPS unit they were using has that big of an error, which is possible or and or they would have done a wrong spelling and stuff. So as I said, it is our duty to check the data before you use it. Any student, anyone who's using this for research purposes needs to look at the data. So I'm gonna zoom into the tricky boundary and you will see that both these are outside, there are clusters outside but there are good clusters inside also. So let's open this, amenities schools, right? And then we'll say open attribute table and you have this beautiful table coming up with random IDs, no ID name, no school name, but it's just a school and it's stuff. At least you know like it's a school and under that there is no cities, syllabus, only some have it. For example, this has K-P-A-V-M-G-A-C dot in. It is a school name with the opening hours. So only some people like it could be a good business for them to put it on the map. So people understand where the school is and then you have the maybe the principal's name, the email, street, office address and then what are the brands they have? Suburb, state, postal code, Tanjavur. So here's that, it's a Tanjavur district but why is it in Trichy? We don't know. So these are the outliers, okay? So when they typed it, they put Tanjavur but the location, geo-location is somewhere else or when they did the geo-location it's in Trichy but the name is Tanjavur. So all this should be Trichy or Trichyrapalli but it's not there. The school names are pretty good. At least the names they have put and some random is nothing, no data there but the point is there. So some data errors are there. Okay, so it is our duty to filter it and use it. So now beautifully we have done this part and as I always say, we are going to, we need to, this is in temporary file. So we need to save it, export the save feature as amenity schools will go here to see where we want. So let us create a folder for this. This is all our materials that we have for this course. So I say OSM test and we are going to say Trichy. Amenities, we'll just say schools. Schools under amenity, right? So I'm going to save it as a shape file and save. And then add the file to a thing. Yes, we can add. And now this has been added. So you can remove this file, which is temporary. We can remove the layer. So what I've also done is, I've also done behind this another file with a different set of search. So I'll add that too or we could do another quick search. So here we are, the quick query is there. I've said Trichy boundary is fine. Let's do one with the name. So in and around Tiruchira Palli. Tiruchira Palli, right? I'm going to remove the preset. So I'm going to reset the preset. And then I'm going to go to education. Not there, government. Yes, government is there. Let's make government supports. Okay, there it is. So if you click here, you will find all the different keys that are available. So we have click government and under the government, what are there? So I've clicked education. You can also search for it. I'm going to add another layer saying that amenity, R. And then in the amenity, there's all these things, right? So let's say school plus R. Let's say amenity, kindergarten, plus private schools. We don't want colleges, right? So we'll just keep like that. We can say government, kindergarten. We don't have kindergarten. Anganwadi doesn't come, right? So this is where we don't have the names and all. I purposely wanted to show you. I've already tried these. It doesn't work, correct? So we can have tutorial college under amenities, but not under the government. So the government is only schools are there. So let's try another amenity here, which could be only animal boarding and building. So we can also remove the layer if we don't want. So three days is enough. And as I said, I'm going to do Thiru, Thira, Palli, right? You want to save that in the new, okay, you can save it in the new question. Do you want a preset like this? If you want a preset, you can save. Otherwise it's fine. Again, I'll remove the ways, lines, relation, multi-strings, I'll keep the polygons. I'll show you why and then we'll do it. Okay, oops. So this can be default. And then I'm going to go on the query. So it is to keep it into the column. Okay, the layer has been added. Apparently there has been only points. There is no polygons, which is okay. But for Tamil Nadu, you can get polygons. I'll show you in the next clip for schools. So now we have Prichi schools, just by preset condition, by this condition. And then we have the government entities. Let's save this also, export, save feature as, and then I'll go here in the same Prichi. And this is not a preset. This was just a government plus schools, government schools. Yeah, you cannot add symbols, so don't add symbols. Yeah, this is fine. So I'm just gonna say, okay, add the map. And then I'm going to remove this amenity location. Remove it. Okay, yes, sir. And we have all this, right? Always save your work. Okay, so now we have two shapefiles. I'm going to add another shapefile for Tamil Nadu. We'll see why. I'm going to zoom out a bit. So now, Tamil Nadu, I want to take the schools. So what I'm gonna do, I'm gonna do the select button. Sometimes you can make a shapefile. Suppose you don't know, you don't want to make a shapefile, you just want this. So what you do this is, you can click. You can clear the selection. Okay, so for now, let us take these points out. And then even the G out, and then just keep the states. Okay, we can copy the coordinate, but let me go to open table. Oh yeah, it's not allowing me because the name is not there. There's no create an identifier, so it's fine. So let's go to the table, right? If you double click on this, it can also show you if you want to, you can close this because it is disturbing your screen. And then you can select a particular state and then make a copy of it. Let's say like this, you can zoom in. I think the other one can be corrupted. I'll show you why. So now I've selected this and then you can select this tool and then just click on this. So when you click on a particular file, what happens is you can select a particular district. I'm gonna show you by Tamil Nadu region. So for example, here, as I said, we can do state, district. This is the second name, this is the state name. So you can click on top and then all the Tamil Nadu I can select. So here, here, Tamil Nadu. And then if you click from here to here, all Tamil Nadu I am selecting. So you can have the Tamil Nadu map coming up. So both you can do if you want or you can just select one. So now my select tool is opening up. For some reason, the select tool now it's opened up. So the select tool was kind of hiding behind. Now it's good. So what are these two? These are monetary territories. So some part of it is wrongly named by the dataset that is fine because we are going to go look at this part. So now Tamil Nadu is selected and what name I've given is, I'll show you again, just delete this and then I'm selecting Tamil Nadu. So just click this button, click on the state you want. It'll get selected. Then you go to vector QSM, open the QSM box. Okay, multiple QSMs are opening. We don't want that. Okay, so we've already selected this. So let's close this. Now we are here and then we'll say education, right? How many T's? And here I'm going to say that I wanted in my layer extent, India states, right? India full states, but only the selected. So I don't want the entire country. I want only the selected and I am going to do the advanced. I'm taking the ways out, relations out only the polygons and points. So it's going to be big, but quickly to run at least in my system. So I'm going to run this. Now we have three shapefiles, one as a preset condition for Trichy, two as a search for Trichy box using government and immunity data and number three for Tamil Nadu with the polygons also included, right? So now what we have done is we will be able to reload it. Let me reload it here by selecting this, which I've already shown. And then I've saved it here as a shapefile, okay? So TN scores poly open add, okay? So now we have the TN scores poly which has been selected. And you could see that when I say Tamil Nadu it not only selects Tamil Nadu but all the other regions also. I'm just going to clear this and keep this. As you said, there is a lot of data issues. So these are not definitely Tamil Nadu. These are in Kerala and these are outside. So there are a lot of data issues and errors but nevermind you will be able to look at it differently. So what happens here is this immunity this immunity has been created but it also has something inside, okay? I'll show you. So it is also a polygon not only a point. So within the point there are multiple polygons also stored. That is what is happening. So I have extracted the polygons on the map and then kept it here. So now we have Tamil Nadu polygons, Tamil Nadu locations out of through to searches. We're going to open Google Earth throw and then put the data in. So for example, let me just hide this for now and then remove these because I just tested before we show these in the class. For you also it is necessary to know how to remove these because it will just cause a lot of errors if you have both of them opening at the same time, right? So let us remove your history a bit, okay? And then let's say delete contents. Yes, it will just keep on deleting the contents. So that now we are free to use and we can also delete or remove these. Okay, so now what do you do is you go to file, you say open, you want only the shape file in the OSM thing we have these two schools and stuff. So let us open them. Once you open them, it says, do you want to apply the same style? Okay, say no, why? Because when you apply the same style you are limited for putting the same style location. So I'll say no. And then you want to apply same for the second one to say no again. And it is going to go to the Trichy location, okay? So now these are the schools in Trichy. Again, you have to go to view, reset, tilt. So now it has come up. So if you remember in one of the previous classes we made up a point for my village school at dry school has been marked. However, it is not in the OSM database. You can see here from the previous thing we have drawn the boundary. We have said at dry is the village but there is no school there even though I said that yes, there is a school. So this is the school I told my parents went and I visited the school area a lot but it is not marked because the data has not been input by any user, okay? So maybe after this course we will be inputting that. But if you go to other places in Trichy the city places you will see the schools. So you can see the school here. So one of the school is there. You can click on that. It will give the properties and then say that okay, the school is there, okay? The school name may not be there. That's why it's not populating. It depends on where the school is and if they have given the names. We have seen that in the list. Not all schools are having the proper data entries. So these are schools. So now if you go in and see. So these are three points for the same school. It's not three schools. Can you see it like a school? Okay, beautifully, the data has captured the location of the school without any government record. And this is open source. People have put in. You can see that you can enter here. Maybe there's a parking. You have this ground. How do you know it's a school? Because the construction, the construction is normally long classrooms and the central ground where students play. So you have a big ground. You have this assembly area, assembly main building, admin building, and then the classrooms. So this is how you could see that there is a lot of names. How do you know? You can check. You can also click one of these places and then see if as you zoom in, if some schools are like famous schools are there, they will populate. So for example, this looks like a small school. This is on the road. So maybe it's not a school, but this could be a school. Correct? Opposite, oh yeah. This is a big school. Oh, there it is. So Tirucharapalli multi-purpose school. The point is outside the road, but this is a small area. You can push it inside. So in your analysis, so now you save the shape file, you can just edit the shape file here. You can, for example, go to properties in this part and then move it. I don't know which one the data is. So we can quickly check here. It's this one. So you can go to properties and then physically move them if needed, but it's going to take a lot of time. But at least you know which ones are there and you can put a point now. For example, you can put a point saying, okay, there's a school that is the name, it has been checked, et cetera. So now think about instead of starting blindly, you have all the data to start and put these locations. So this is about schools. I'll also add the other shape file, which is the polygon. We will be stopping soon because of the time, but when you add the Tamil Nadu polygon, it will say it's too much. Do you want all of it? No, I'm just going to say restrict the view because we cannot plot thousands. Zero features important because there's no features there. So I have to zoom out for this region. Okay, let's zoom like this and then reload it again. There will be thousand features. So thousand attributes, we don't want that. So let's say restrict the view only for this. 12 bar imported, same thing. I don't want the same template. I want this. So now you're going to see area. This is a polygon. I'm just going to zoom out and then let's see where these... So now I'm going to remove the places and borders so that we can see the buildings, right? Okay, there's one. We've got one. Okay, so this has been labeled as a school. You can click open and you can see the school there. So someone has detailed it very nicely, the school location with a polygon. And you can actually add places and borders here to find what is at school end. Bollford, Planned Girls, High School, School. So you could see even now, if I go back to my Eterite, it's not marked because that is a problem in rural India. We do not have much of the data marked. Whereas in an urban center, yes, it has been marked widely. So here I've shown you how to come to a particular area and then mark schools based on points and polygons from an open source system. And then you put it in Google Earth and check. We'll revisit this in the next class while we do other attributes. So here in this today, we will stop here with an attribute on schools. We have checked the data. We have also done some minor edits if needed. And then we'll be able to create a database. I'll see you in the next class. Thank you.