 Welcome to remote sensing and GIS for rural development. This is week six, lecture five. We are wrapping up week six, which is half of the NPTEL course. I hope you are enjoying learning GIS techniques that can be applied for rural development, as much as I enjoy teaching. In this week, very specifically, we had looked at certain aspects in the data acquisition or data mining we call. How do you convert paper data into GIS data or a scanned image into GIS data? This helps tremendously because a lot of data are from the past, and they have a lot of value and information still in it, especially to create a time lapse image or a time series of data. So it is important to hold these data in GIS formats or digital formats so that we can compare readily. So let's dig into the last week, six lecture five, which is the closing lecture for week six, the midweek. And we have been looking at extracting data from maps. I hope the hands-on tutorial that I showcased arrived in the last two classes were helpful to redo that in your own system. We will also be sharing this data with you through the forum so that you can also try these examples. But I prefer you to find the data from the links that I gave because then even if the data is not new or outdated, then you can eventually find the link and download by yourself. We want you to create capacity by teaching and learning by doing rather than providing it readily available. Extracting data from maps, we have looked at point-shaped files and line-shaped files. Now we're going to look at polygon-shaped files. It is a similar process, but then the last part where we take all of this back into the GIS Earth Engine or Google Earth platform is where you will see wonderful images on how this image that we took from a paper map can be converted into a Google Earth, a real-life image that has been taken from satellites. So let's move on. We will complete the last part, which is polygon-shaped files. And then we'll jump into visualizing and Google Earth pro. So let me share the new map that we downloaded and used. So this is the same map that we have already done the point and the roads, which is lines, from the D43R12 sheet. And we also made sure that it is following on the Indian boundaries. It's not coming out of the Indian boundaries. So you see the poly points and then lines. And then now we're going to do the polygon. So for the polygon, we'll do two polygons, one in the Shibakot area. So we'll see what the water body means. If you go to the left side, you could see that a water body is given as a blue color, this one. It is a well-lined spring tank's perineal and dry. So you have a tank which could be perineal or dry. Dry is dotted. So here you have some part of a tank as dotted, whereas some part is perineal. So we'll map this and then the bigger Yerahanka Lake in this tutorial today. So let's get started. As we have done previously, we have to create a new shape file to incorporate the polygons from the paper map. So let's do this. It's a little bit of drawing exercise, but I hope you're enjoying it with me. Let's say we have labeled as roads and wells. So now we'll say water bodies. D43R12 is the sheet number. The geometry type will be polygon. And there's no additional values. The dimensions are the same. And you have the coordinate system which has already WGS84. Let's now create the fields. The ID is already created. The first field is exactly the name. Name of the water body. And that could be text data and just going to add field. If you forget to add, I showed you how we could add later once the shape file is created. One more thing we could add is the date. Date of checking of the lake or the water body. And that could be a date format. It is AD. And the date formats can be different numbers, dash, how you would like to be. We will see how the default works. Let's say date. There is no precision for it. We do add to the list. Now we have created three, ID, name, and date. Let's say OK. And let's start drawing. So now the water body shape file has been created. We can look at the properties to see the source. And you can see that the layer name is there. But we still need to incorporate it into the GIS folder that we want. As I said, you could always create a shape file on the fly. So you can create a shape file. But it is better to store it. So I purposely did not store it because we were trying these GIS files. But let's store it now. So the wells and tanks, I have to right click, export, save feature as a three shape file. File name is the same. We're going to just say rows dash B43R12. And then where do you want to store it? You can click here. And I am going to go to my URL folder GIS and then put it here. So this is where I would like to store it. So I can type it again B43R12. So I'm just going to copy it so that we can do it for the rest also. And we say OK. Same thing, let's do it for the other two. We're going to do export, save feature as, we're going to go here. Roads, instead of roads, I'll put wells. Wells underscore tanks. And I'm going to store it. And then it has already added it also. That's fine. Instead of wells and tanks, we can remove this for now. Move the legend. Let's save feature as, go back here. I'm going to go to roads. Yep, roads. We're going to replace it. Overwrite file. OK, we have overwritten the file. And we have wells, roads, roads. We remove one of the roads because we don't need it. It's still a temporary file and the water bodies, the last one. OK, export, save feature as, go here. Again, I don't want roads and stuff. It has water bodies. We'll now remove the duplicate. So just to show you, I'm going to take everything out. And then we're going to add them from here because we have exported them into the file. So let me add it. OK, now you can see it. Choose from my directory, all of the three. I'm opening, making add. We have it now. Good. So what has happened is we have all the files that we needed. And now we are going to add data for the water body. So for now we have, you can open the attribute table. There is different files that we have made. But we'll just remove it for now because we're going to show it in the Google Earth. So this water body has to be in blue color. So just as a symbology, let's change it to blue because water body is blue. Apply. OK. So if you open the attribute table, you'll find there's no attributes. Why is this? Because we haven't added it. We just created a water body. So now we're going to add it. So let's add the water body that we have created. So I'm going to just make it so that you can see this table. I hope you can see my screen. If not, let me open it again. Yes, now you can see it. So I'll keep it here. As I said, we'll do two water bodies. So the first water body is we're going to first toggle it. Once you toggle it, this new polygon comes. It's a green and a plus sign. So you are going to add a new polygon. So I'm going to click it. And now let's make only this water body. I don't want the perineal or the dry part. I just want the water body part. Good. And then right click. ID is one. And this is the fourth date is you can say once you click the date, it automatically picks a date. Let's say 16, 5, 20, say 11. Just a date. Just a date for our analysis. And we, as I said, promise, let's go to the lake. While we were doing the work, we said we wanted this lake, which is a big lake. And let's see how it has changed over time, for which we need the boundary. And that is what we're going to extract now. So I am going to do another one. And so I'm going to zoom in and click as clean as possible. And there are multiple tools in GIS to calculate this area. So once you have the location and the shape, it is easy for one to get the area using formulas and other aspects. And there is always a way to change and edit the vertex if you have issues. This is number two. And as I said, this is the area of the lake. And then let's say 21, 12, 21. OK, we have it. We can always edit it, but let's not edit it for now. And then this is a Jappur lake. It's a Jappur lake. Because now you're going to see the whole body. And let's see how it has changed. I have personally visited this lake. So I think I'll be able to see the changes in this lake. And all these are part of rural area in the past. And now they have become very urban and urban. So three water bodies are good. And then because this is a Bengaluru and people know that it is a land of lakes. However, because of organization and a lot of drainage was created to drain these lakes and then plots were built. For example, Khasargata plot is there, which is basically on a lake which was just drained away and the land was reclaimed for water bodies. OK, let's take one more. I take something in this area so that we can easily look at it in the map. This water body doesn't have a name, so we won't take it. OK, let's take a forest, a reserve forest, just for the sake of it. Because just not water bodies. Or we're naming water bodies the file. So we won't be taking that. So we can take this. Kepanahalli, all these small, small water bodies are also OK. So let me put the hand, bring it here. And this one is what we're going to look at. And again, this one, as many as you want, you can click in terms of the points. So don't feel shy to click more if you need more. And then as the names and your status is Marutinagar and let's say it has been taken in 2023. OK, so now we have four water bodies, correct? Open. Yes, four. And then we will close the toggle, save the edits, close it. Now we have four water bodies, four points, and four rows. So this is how you could extract data from your scan image. Now we have shapefiles that can actually go ahead and look at the region that we are looking at. So you have these roads. It's very tiny. You cannot see it. So let me go to the properties and change the line and color. So as I said, let's do two. And then you can see the road now coming up. So these are the rows 1, 2, 3, 4. And then you have open attribute table. The first one is selected. Let's clear all the selections so that you can see all the green lines are there. And then water bodies are there. Wells and tanks are there. So you have instead of wells and tanks, I think it has to be roads, OK? Again, properties. Let's make the line bigger. So roads, OK. To fly, OK. We have the wells. Yes. So we have the water bodies. And then we have the roads. The wells layer is also there. But let's look at these two in the Google Earth profile. So before that, what we can do is we can look at one more thing that I always wanted to do is look at this map in Google Earth Engine to see if or Google Earth Pro to see if the map has loaded properly. So for that, let us first take all these points of interest out. And we are going to look at the roads and water bodies. The point I am removing because if you zoom in too much in the point, you cannot see the well because the satellite image is not going to be there. But at least right now we do have three shapefiles created, point, polygon, and line. So now I am going to open the Google Earth Pro. Let me share my Google Earth Pro. Let me have it here. So this is my Google Earth Pro. I have zoomed in just to that area of Karnataka. Just to make sure that our map works. OK. So now what I'm going to do is we are going to add the first scanned image that we created. So this is a scanned image that we created. I'm going to add it. I hope you remember this is week 6, lecture 3, 4. We have scanned the map and I'm going to add it. So once you add our Google Earth Pro, let's see what happens. It is saying that I'm flying to the overlay area location. However, there is a pop-up which comes, which says the image is too big. I cannot import such a big image because of the hardware that my system has. It says the important image is larger than the maximum size supported by the hardware. If you want to create a super overlay from the source image, press Create Super Overlay, for which you need a lot of libraries. Let's not do that. If you want to view the whole image, rescale to maximum supported size, you can say scale. What the scale will do is it will downscale the image and then show at that particular location. However, as I said, we don't want that too because we want a zoomed high resolution from the paper image. The last one is if you want to view only a full resolution subset of the image, press crop. Crop means a part of the image comes in, not the full image. So let's do the crop. And then it asks me, where do you want to crop it? So if you pick a center of the image, then it crops as per the hardware. So as I said, we want to look at this lake. So I'm just going to click that lake. And the image is coming loading up. So once the image loads up, you can see the image has loaded up, but the entire image is not there because it has been cropped. You can actually drag and pull this, but this is the maximum you can go. So in terms of the cropping, if you do this type of cropping, then the map is moved. So don't, let's cancel and then redo this again because we should not be pulling and pushing the data because then it will get distorted. So now again, as I say, it is overlying to the location. And I'm going to pick only the image that is cropped, which is center of the location. Let's place it on the center of the lake. You can see that this image is very recent, 2023 Airbus Maxxer technologies using Airbus payload. And you can see that this has been done. The same file name can be there, it's fine. The opaque city is, if you decrease the opacity, then the map is transparent, okay? So if you see that now the map is blocking the satellite image, but if you go down, the map is gone because it's very, very slightly seen. So somewhere in the middle is fine, like this is fine because you can see both the map and the satellite image. Now I'm going to click okay. So once I've clicked okay, a beautiful thing that can happen is you can zoom in. See, now if you zoom in, you could clearly see that the lake, which is on this lake, which is a satellite image, coincides with the lake from the map. So the map is 2011, right? And this is 2023. So you could see that some parts of over the last 10, 10, 11, 12 years, the map says that the boundaries have been preserved, right? You could see that the map boundary, let me, maybe we could just more increase the opacity so that we can see the boundary, yeah. You see the blue color from the map boundary is almost the same. So maybe they've bundled it no more. So these are all buildings, right? So no more, you can toggle on and off. So no more construction can happen. All of this is taken care of. What has happened is the sides have been highly polluted and you can see that there's a lot of covered water bodies are there, which were not there in the previous lake. Okay, then it is a full clean lake boundary, but again, as I said, it is gone. So now what we'll do is we'll see one lake of the other. We also said this Javkur lake, as I said. Let's look at Javkur lake. So the paper map shows that the water boundary is here and this part is dry and this is perennial, right? Let's see if that coincides with the map. If you take off that, you can see that part of this area, this area has already been taken over. You can see here, right? So this dotted was initially a lake, dry part of the lake, but now it has been used for water treatment plants and other things that you can see. Some buildings are there, some houses are there. So you know what is happening, right? So this entire thing was the lake, but now it has been taken away. So this is a Javkur, very famous Javkur lake. You can see this part also, it's mapped pretty well. So this map and this map coincides. See how we have imported a paper map into a satellite map and because we accurately made sure the latlongs are all captured, the six points that we used are all correctly captured. Both the boundaries are correctly merging. This boundary, what you see now is a satellite boundary, okay? There is a lot of information here, but and no distortion because this is a satellite image. The boundary is what we see as the line, the line is the boundary. And if you overlay this part, you could see that, okay? So some part of the water body has been taken away and some part has been expanded, right? So right here, you could see that the boundary is almost on target except for this part. So this part, the boundary comes up here whereas here itself, they have closed. So they have closed it here and this part has been taken away. So let's look at this image in a time lapse. So I'm gonna click the time button, okay? And we can go back to let's say 2011. And now you could see that this part is not as populated as initially, right? So initially in 2023, you could see that a lot of construction has happened here whereas in 27, you won't have high resolution. So you won't see anything, but let's wait. Maybe the computer, the internet takes time to load. Yeah, it doesn't load because there is no image or the images. So like this also you will see which means only part of the image is there. Click on the best available resolution. So this is the best available resolution. Now I'm gonna click on our paper map. If I click on the paper map, again, I'm saying that the entire body should have been there. However, only part of the body is there because it has been used. So on paper, what happens is exactly the government officials know that this is part of the lake. However, it has been taken up by some construction activities. So these construction activities are there and it could be a water treatment plan. As I said, it is a water treatment plan which is for the public water supply schemes. So they can use it, right? So that is what we could see. Again, we'll go back to the El Ankar Lake. Yep, and you could see that the lake boundary goes up to here on the paper whereas on the image, it stops here, right? There is some very slight level of boundaries taken for construction and other purposes. Same way here, the boundary closes all along the black line and you can see perfectly it is closing. You can see how perfectly this road and the black line from the map are coinciding, right? Basically telling that this part, the water body part has been mapped perfectly. Again, the paper drawing also may have some distortion. So some part of the map may be not correctly done. So all the boundaries have been mapped well and good. Now we can also open the shapefiles that we had. Let me just open as S3 shapefiles. Yep. And as I said, let's do the water bodies. And when you add it last, do you want to apply a style template to the features you ingested? You'll say no, we don't want a style in the template but we just want the entire map, right? So once you click it, now you see that the four water bodies that we linked, one, two, three, four are there but the other two may be cropped because we went outside the boundary, that is fine. But now I can remove this, the map that we made because the map we made is covering the entire area but off the map, I'm only interested in the water body. So the water body is being taken now. Sometimes you have a tilt. So go and reset the tilt, it will turn back up again and you could see that the water body is there, correct? You could make the water body, again, properties. You can type in the name, style and color is there. If you want different colors, you can do different colors. You can just say outline is fine and then the outline color could be red just for our sake and then the width could be a little bit thicker. So seven and that is it, okay? So in this part, you could see that the lake boundary of Yelahanka was captured. It was captured to a particular extent and you could see that some part of the lake, maybe the clicking could have been off or the paper had more land, whereas in the reality it is not as big because some land has been taken away for construction purposes. One way of checking it, as I said, is running a time lapse of this data and you could see here, if I go to 2002, 2004, you could see that part of the lake is dry, most of the lake is dry and this construction has already been happening on the lake boundaries. Whereas on this side, they were respecting the boundaries. You could see the line was clear and only behind the line the houses are there, but as time progresses, as time progresses slowly the houses are coming near the boundary of the lake and then slowly encroachments can happen or the government would have said, okay, you can build some protection against it. So right now there's no breach. You could see there's no breach happening on this side, but more and more houses come up which demand water supply from the lake. Yes. So you could see here 102 just coming up which was not there in the previous images, right? So then you have all this water bodies and the road which was there, but I just went above it to show that water flows until here so that should also be taken as the lake area. So this is how you could import an image into GIS and then from the image which is old data outdated, maybe it's a sense of data that was shared by a government agency. You could run it in the GIS software, let me show you. And then we will pick out the data from it. So there'll be a lot of more data. See, a lot of legends has given. So you could easily see zoom in to as much as possible and then see how these maps were created. The size is not as big an issue here because houses won't have a size. The lake may have a size. You can use the scale here to say, okay, what is the perimeter? What is the width, et cetera? But you cannot, you cannot. Okay, let me just do a line measure and then I want it in kilometers, it's in kilometers and then it's a new and it's going to go from one point to the other. So it's 0.64 kilometers wide and it's not the same width because there are multiple widths on the thing, right? I'm just going to close and then we will use this to zoom out and zoom in. So there's a lot of data in this. Trees have been marked, wells, lakes, et cetera, have been marked. Ben nuru, as I said. So now if you import an image from 1800s from the British time, 1870, there's one data set I used. Then you could clearly see that how the land, how the water bodies have changed from 1870s, 1890s till 2022. With expansion, with increase in population and people migration from rural villages, there is a need for land and water resources but it should be sustainable. That is what is needed. And here what you can see is sometimes if the data is not there, you can use these kind of data. This is the same method you'll be using for satellite imagery and imageries that you can capture using phones, drones and unmanned vehicles or airplanes. All these data will contribute to rural development in mapping structures, mapping road connectivities and also mapping access to water. So for example, you know that there is a housing settlement in this map area and you have a water body where maybe if it's a village, people would go there and access water for a domestic supply. So they would walk and if it is too far, then they would eventually lose livelihood options or education options. So all of this can be mapped. And again, this is a static map. It is a 2011 map. It doesn't change. Whereas your GIS map can be updated as and when the data comes in. So here you can see that this is a time-lapse image. Let us quickly see a time-lapse image of this area to see how the population was before and now. So these are all agricultural lands. If you see now, you will see agricultural land is gone. Correct? Yeah, let's focus here. And then I am going back as much as possible wherever the data takes me. 1985 is the latest satellite data you have, but again, you'll have issues like this. The resolution is not good. However, this part is good. So this is 2004. These parcels of land is nothing but agricultural land. So now if I increase, so it does take time a little bit. The source of the data comes here. We will have a session on Google Earth Pro and you can see here that it is still circling. So in 2005, all this land was agriculture, but now in 2023, you can see how ground has been built, lot of land has been cleared and you could see that these things are populating. These are not sustainable in a longer run because the food security could be breached. All these land which were initially agricultural land has now become urban land, thereby demanding more power supply, water supply and other accessories there needs. With this, I will conclude today's lecture and also week six. We will reshare the final slide to close. So we will conclude here with week six lecture. In the week six, it has been very important because we have looked into how to look at new data and other data sources. The other data sources include satellite and other imagery that were not initially available for the public because these satellite data or the map data were in papers and people were storing it in papers because that is how the map was created and it was large maps which cannot be scaled down to a computer. But now since the globe can be scaled down into your computer using your GIS software, it is definitely possible to put the map which is much smaller than the globe. So all this we have discussed in detail. I really hope that you can go to your nearby Panjait office, government office and ask for paper maps. And if they say you cannot take it out, you can still take a snapshot using your phone and the same method you can use. Make sure you don't zoom in, zoom out and have angles when you take. Just keep the map under the table on the table and then keep it very focused to your phone and take an image. That is what a scanner does. A scan doesn't disturb the image and it scans the map. So same way scan the map, take the image, convert the image into GIS image in by using GIS georeferencing tool. Make sure you take points that are allowing you to anchor it. So suppose you have a map which doesn't have an anchor points. What do you do is you take the anchor points from a Google Earth engine. So that part we will cover in the next lecture. I will close today's lecture with this slide. Thank you. Thank you.