 Welcome to the NPTEL course on remote sensing and GIS for rural development. This is week 12, lecture one. I welcome you all to the last week for the NPTEL lecture. I've enjoyed the process of teaching this concept throughout these 11 weeks. And now we are at the applications and summary side of remote sensing and GIS for rural development. There has been a lot of engagements on the forum, which I highly appreciate. A lot of notes has been exchanged between the IITB team and the participants. And moreover, happy to see that a lot of students found applications to these in real life scenarios. Instead of just keeping these outputs as fancy images on papers and articles, it is welcoming to see that a lot of people relate this to the current scenarios in rural development and the issues. With this note, let's get into week 12 of the lecture. And what will happen in this week is we will be discussing about the applications of this software, where to use it, how to use it, etc. And we will also be looking at some real case studies. Why? Because we want to show that these case studies can happen if you use remote sensing in a way that you have always used data and other sources, like observation data. So let us again start, looks like the screen is off. I am going to share my screen again, so that we can quickly look into this week's lecture on how to use remote sensing data and GIS for rural development. Let's move on to the application side. So remote sensing for rural development and applications included in week 11, what we came across is we looked at a lot of open source data, we created a lot of data that can be mapped and available for the public. We found out beautiful resource available online for free, of course, open source, which can aid us in mapping schools, healthcare and roads. Please note that when this course was designed, there was a lot of emphasis also to be put on the rural infrastructures. This is because you may find links to do LULC, water crop identification in multiple lectures and videos, but very less talk about schools, healthcare and roads in rural regions. I have explained clearly why and how the need is and showed you the tools that can be used to estimate the length of the road, the width of the road and more importantly, to document the location of these structures which are absent in the real-life scenario. We also looked at OpenStreetMaps for adding layers, checking layers and applications. These are needed because we wanted to showcase if there is a lot of need for OpenStreetMaps and how to input more. If I had done the same study, the same example for London or New York or other big cities or even rural regions in the US, you'll find a lot of data coming out. It is because the capacity is better in the US to use these mobile applications and OSM software whereas here there is a need for capacity development. This course and you guys as students who are learning these will have a better niche of using this because now you have hands-on experience, you know how to show the data, you know how to search for the data in the quick query and you also know how to plot it for applications. So now in week 12, which is the final, final week of this lecture series, we'll be looking at government databases because we are going to focus on applications. It is very, very important to have rural development infrastructures. However, monitoring and evaluation is also needed. For example, there is a lot of monitoring and evaluation in big, big programs. However, the data is collected very less for it. If someone asks me quickly what is the benefits of the middle scheme meal, the meal, the midday meals for school kids, it was very hard to justify when the scheme introduced. But then slowly we have the data to show that many students have come to school in rural regions and they were healthier because the body mass is different. They had access to eggs which is high in protein and also they were able to devote time for studies because otherwise they would be earning or working in the field for growing crops for their food. So now the food is put on the plate. So the two, three hours they work for that specific food, they can put in school. Then they can go back and work in the field for their family. That is different. But for each person, they also work for the food and stuff and healthy food. It's not just rice and dal. You do have samjis, which is vegetables, curry, rice with your soul and sambar and stuff. So everything is given in most of the regions I've visited and we visit a lot of villages through this lecture series and in my current position we have to visit a lot of villages and it is happy to see that the scheme is running well in many, many regions. So it's more positive and the benefits are there. But the same can be applied to other schemes, rural schemes like check dam scheme, Mandrega scheme, IWMP scheme. Where are they working? How are they working? We need to see. And with less data on the application side, we are going to see how we could use already remote sensing data which has been collected by itself through satellites. How can we use it to address these issues and concerns? So with this, we will be looking at government databases in Mandrega, IWMP as a start to look at where the structures the government is putting up and for how long. And then I'll give you some snippets of how to go back to the GIS and remote sensing data sets and download these data sets for application. This is going to be just an intro because I've already taught you how to download the data and all where you will be connecting the data with a problem statement in this week and then making a solution. We'll also look at case studies for applications of remote sensing, water quality and quantity. Both we will see in one lecture and then LULC mapping, the different mapping schemes that are available and the new indicators and dashboards that are coming up due to remote sensing and the GIS applications. Please note that most of this will be from my own group because I know what data went in. I know the limitations and challenges which I'll be happy to disclose because all these studies are using proxy data which is remote sensing data. So there is a lot of concerns for a lot of people on limitations and challenges. So I will be explaining those in detail and then we will wrap up this week's lecture and the entire individual course with a summary, small summary. So let's get in. We discussed about the rural infrastructure issues. The water supply we had looked at connectivity has increased like gel germination, the tap connection has increased, but is the source enough to provide the water? How do you get a remote sensing data for that? Okay, so if you see for rural drinking water supply it's not possible. The only thing you can map is the source of the water. Let's say you're taking a lake area and then if your area is diminishing and there's no water in summer, technically there's no water for supply. So this is how you should be thinking of using remote sensing data for indicators that you cannot directly measure. Like for example, the school children walking to fetch water. This is a very powerful image where a boy is going to school, whereas a girl is going to fetch water. They should have equal rights for education. They should have equal right for a quality of life. But this is the scenario. So we need to support our girl children. We need to make sure that they stop being used because of these issues. We need to support them with better access to water so that if at all they are forced to take water, at least they can quickly come back to school. Changing the mindset is going to be very, very difficult, but at least we could change the time that requires for them to fetch water. As I said, when I was a kid, I had to fetch water when I was in Chennai, 4 o'clock, 3 o'clock in some summer times when the city was dry, the supply would come at 4 o'clock in the morning. We have to wake up, run to the street, take water, come back and sleep and go to school. Even that was difficult, but think about the half a day gone for fetching water. So it is going to be difficult for us to go into the villages and change the mindset of why are you doing this to women and girls children. The best way is first to get them quick access of water and that will improve their access to education. It's all indirectly connected, but very, very connected, but indirectly. If you say just go to school, we will give you water. They will not bring it up to notice because bringing water supply to everyone through tankers is not going to happen. So the challenge of admission has a very, very good impact on women education because even though it is not on an education ministry, if the water access is there, then the girls children will go to school. So then we have rural housing. The scheme exists, but it needs to extend to all regions. This is a concern that we found. And how do we map it? We can definitely map it through remote sensing images. You can take an image of an area which has been declared as a rural housing region and then go back and forth in time. So if you know the scheme started in 2010, you can take images from 2005 in a particular village, let's say my own village, and then see how the houses have come up. And if you know that those houses have been built using the rural housing scheme, then it adds benefits. It's a monitoring and evaluation tool. So initially, we were finding how urban, rural conversions happening between rural and urban, but now we can also use the satellite data for identifying these locations where the housings have come up. And the rural water storages, as I said, if you have a lake and a pond and the water is drying up, you can definitely capture it through the satellites. The volume may differ because maybe it has sanitation, maybe it has reduced storage due to encroachments, but at least you know the perimeter if the water levels are changing. The other rural infrastructure is in hospitals, schools and daycares. We did find these data in OSM, which is a very rich database and constantly increasing in spatial and temporal resolution. The connectivity during COVID was less, the networks, the cell towers, etc. I've already also showed that the cell networks have their own coverage maps. You can just download them, georeference them, and then put it on your housing maps to see if the houses are away from the internet or along the internet cycle. Then we also have the rural locations and accessibility to schools and then food ration shops, etc. We did research for ration shops, we didn't get it, so maybe some government agency can share that data for you to map or you can go to a particular district and start mapping college students as a project. You can map all the ration shops in NGIS platform or Google Maps that you use for travel can also find these ration shops. The rural roads was a big concern. As I said, there is software that can automatically detect roads, but it did not detect the roads that are connected to the field. There are a lot of issues. Just in the last week, we did mention that the distance from the produce to the highway can be highly reduced if we use these roads to a better extent. In this week, what we will do is we will revisit some of these things that we discussed in early weeks and now address it with what data we have collected over the 11 weeks that can address this. For the connectivity, as I said, we could use the recent Landsat 8, 9 and Sentinel 2 images ranging from 10 meters to 30 meter resolution to map the water bodies, both this one, the rural water supply and the rural water storages. If you map the supply and if you say this is a supply for the scheme, the Georgian mission or the rural water drinking schemes and you know that the water is diminishing in summer and totally gone, then you can say that the mission has to have other sources for water, otherwise it will crumble. So this is how you could do monitoring and evaluation in a very direct way by using indirect data. So the supply data can give a proxy of the volumes that can be extracted from the villages. Then the housing scheme, as I said, you can use both Sentinel Landsat 8, 9 to map an area and then show how the housings have developed. We will see some of these housings in the new course of time. There's a lot of program memory schemes that can have the maps made for these areas and we can see how many houses have been built because the budget has been given. Let's say they give you 10 lakhs for a village for 10 houses. They should have a data on before and after so that they know the houses have been built. If you look at many claims of this toilet schemes where they said toilets could not be built, however, the corruption on the ground could say that some people say they built the toilets but they didn't build the toilets. These kind of concerns were raised by people. It could be raised by multiple parties and people but it can be defended or supported using satellite data. That is all I'm going to say that if you know that a particular area was cleared for a community toilet and 10 latrines were purchased in the scheme, you could definitely do it. So the government can now hold the contractors who are doing these corruption to make sure that they are doing it well. Same with road quality. A lot of people are saying road quality is bad, road quality is the road doesn't exist after a monsoon rain. So now you have satellite images that can prove it. So if you know that cars are going on the road and heavy vehicles are going and the road is good but if you know that it is all broken and only cycles are going and around people are using another way, that is an indicator of the failure of the road. So the government can use, so you people, you students as capacity for the government can aid in evaluating the end monitoring. So the government is pressured to have schemes to work but down on the ground level a lot of people, a lot of externalities will make it not work. So the government can now use these remote sensing images through people, students who have built capacity on GIS to address these issues. With this, I will start with one very good website that NABARD has created with the support of ISRO and it is mapping of NABARD infrastructures. So NABARD is the rural man which is supporting all the infrastructure planning and management activities in rural regions. So if you click this link, we will be opening in a new page. I will share that page with you to show how the website can be used. But before that, let me just quickly go through the bullet points so that we'll use it. So NABARD website in the movement has NABARD watersheds and the field data links. The NABARD watersheds is the watershed management programs under NABARD schemes. You have multiple NABARD watershed programs and we can click on each to see how it is working and where is it located. Most importantly, the location, the budgets are going to come out. There is no evaluation of it even though it says monitoring. It is just to monitor the locations but not the benefits. So we are going to show you how to monitor the benefits in the next lecture. But first, let's see this data, how you could pull out and then use it in land use, land cover maps and other indicators in remote sensing and GIS database for your studies. So then a user manual is available for looking at these locations and studying it. How to use this website? Please go through the user manual and then you have mobile version on the phone. You can actually collect data, look at these locations when you're on the field. You can extract points and data from these fieldwork, which is very important that we will be showcasing now. So let me share the webpage. Okay, great. So when you open this, the link will come like this. But before that, I would also like to show you the way to search it because sometimes the link may be updated. As I always share, nabad, booban, just type nabad and booban, you will get it. The first link would be okay nabad as part of development booban, isro gateway to the earth. So just let's click the isros nrc gateway to the earth and then this picture comes out. So I'm going to use the link that we have chosen here. It's the same thing, but you'll have different colors depending on what I selected earlier. So we have this you can select a particular region. As I said, you have seen just in this colors, it could be it could be anything. The legend is here. You can see the legend. It says the projects which projects are there, IGWP, WDF, all these are both national and international pundit supported projects. We have spring shed RSC on the spring areas in Maharashtra. We have some springs in the Western Ghats and all the Himalayan regions, which are very, very important. If you recollect this with the groundwater maps that we discussed earlier, you know that this belt is highly groundwater depleted, but very less schemes now. So maybe you could propose using those data to the government saying that they should put more structures there. Okay, so we have this and then there's a discussion forum you can click on to see how things work. Okay, you can have updates, usability, what data you want to have. So you can just say here, just someone 15 days ago have asked, can you put some other data onto it and then use for students? Can you give it for free for students? And then how you use it, etc. So you can have these. It is currently today's date and any updates. Very, very recent forum you could see. And then also the number one will also take you the Google page for some people may take you to this one. So this link I will ask you sometimes to log in. So you can also log in as a citizen. If you come down, you can say you can log in as a citizen or you can use if you're working with the government, they'll give you these data. So there's a user manual, mobile app download, new version has been released, you can do it. So if you click on citizen, it will open the same page that we have here. Okay, great. So just for bandwidth, I'll reduce these pages. Okay. And then we will also close the other ones. So then okay. So now we are here. These are the different schemes that you can see on the top. And you can select the scheme you want and why it has been done. You have to read about these schemes. So for example, the IGWDP, if I just type IGWDP and then watershed development program. So let us see if there is the Indo-German watershed development program. As I said, these some of these are through government fellowships and partnerships. And it has 30,000 hectares of dry lands through 300 projects across India, four states. It's a very good initiative. So the order indicates that. And we can see. So let's start. So number of watersheds, you can click on a watershed on movement. And then the project, as I said, all these projects, you can individually click. So I have known about the IDF, IGWDP. So let's click that. And then you can see which states where the locations are. And then all the states, you want all the states, all the three states the data is there. Here it says four states. However, right now the update is only at three states. It's fine. Let's keep it all. Then there might be these investment states. So the last update is on March 22. Just very, very recently. And you have these states. You can download the data and export it to Excel. And also you can see how many districts are covered, number of watersheds that are covered, and then area, treatable area, households covered, how many households beneficiaries. So this is what is needed for evaluation of the program. And then the total PFA is ongoing projects, completed projects. So I'm going to zero. Everything is completed amount sanctioned and amount distributed. The sanction and distribution become same and utilize in lax is there. So this is around sanctioned is around, if you say it's 121 pros. Because it's lax. So 122 pros, you can say. So that is how much money has been put in the scheme. And now you can click this to zoom it out. You can click this out and then zoom in to see which locations are having these watershed problems. You can click on a particular dot. It will ask, it will tell you what the locations are. For example, says name of the watersheds, Interpol, Rajasthan, Chittargarh, IOTT, WTCM, and then all these things are given in these metadata. How much amount distributed and how much has been done. So it's one of the project in this area. And the data sanction is this. So now what you could do is use multiple data. Sources to go and see the effect here. The name of the watershed is Bundalpur and distributed Chittargarh. And now you know that let's do the Sentinel help quickly as an evaluation tool, because that is what is missing here. So what you see here is locations, but still it's very, very important, but you don't see any evaluations and monitoring, which what we will be doing. You have the statistics of the data and also the when it came into existence. So you'll have to juggle between these websites. You have juggled between the Indian data site and a good remote sensing data site like this. And then you can just quickly go through the data. So while that is happening, let us keep this up. And then you can click the field data here. You can also collect data for each program. Let's say IGWP, the same program we can choose. All states, all states can happen. You can click here, you can see the same three states, not four states, but let it keep there. Which district you want to see all district? Okay. So you can also say Gujarat, all districts, watershed clusters, all activity, what kind of activity you want to see. So Gujarat is now taken. And then all, let's click all. And then this is the field data. Okay. So, and then which watershed we were looking at, Goodalpur, district of Sitogar, or Rajasthan, we can do Rajasthan also. So I'm going to click Gujarat, all districts. We can take Sitogar. Okay. And then all we can take, and then statistics can come in. So these are the different statistics. It's very hard to clear. You don't see a clear button, right? So the only way is to refresh it while this comes up. So I'm just going to refresh these buttons. So it just takes some time to refresh. And then let's go to EO Hub. Meanwhile, okay. So in the, in the watershed, I am going to select IGWP, DPE. And then state, let's select just Gujarat for now. And then district. You cannot remove the all, which is interesting. Okay. And then all, I can say, Sitogar, but still all will be there. You cannot remove all for some reason. And then all or which watershed cluster you would like to see. But now let's say also all statistics will come. But now here we will go to the program again, IGWP. State will say Gujarat. And then districts is all watershed clusters are sub-activity. You cannot change these much. So if you can see here, all activities are coming. You want others. So let's keep it all. And then sub-activity is also all. You can start date and period to see the data, which is available. Again, this data is different than the monitoring and evaluation data that we are discussing about. Let's say period is fine. You can, you can select the year, let's say 2012, January, let's say 1, to date is 22nd March, let's say a week. So one thing which is interesting here is we can actually do the current scenario. So I'm teaching now in 2023. For one reason is that I don't want to show the updated data. And you can see that 379 points have been found. You can go to the mouse here and then zoom in to one of these locations to look at the data. So the data is interesting. If you look at it, you can click on it. It will have an image of the project. Bhuvanabad is the project at DC. And then the name Bhuvanabad DC training was given, the date of the training. What did they do? Start date, end date, amount, sanction, etc. So what did they do? You can see here there was good training and some pictures taken with the farmers. And that's it, the data you could see approved. And then there is a person who approves it. So I've spoken to an ABAR team and they say very clearly that not all can approve this. Only the manager and the senior most people will look into this database and then approve it. Once they approve, it comes on line for citizens to see. So engineers constantly update the data. And you can see that the project ended in 2018, approved on 2020. So two years approximately, they will use it for checking the data and then approving the data, uploading the data, etc., etc. So it does take a little bit of time and then we can close this. We can go to another project area. Let's say Dachod. I'm going to show Dachod in a very particular sense because I work in Dachod with a couple of NGOs. And I know they also are doing some very good work. So this is not to compare the work, but to take a region where you have NGOs working and also people working on the data sets. So this is the same organization I also work in. It's a good water and development foundation as a visiting scientist for some time. And you could see that they are NGO partners. What do they want to do? They want to do on weather based agro advisory. So based on the climate, they will give advisory to the farmers. Agro decisions can be taken. So the image has not been come up and now it has come up. So you can click on the image to make it big. And you could see that the farmers the NGO people are working and then you can zoom in and zoom out. So what was it used for? It was workshop on good construction practice. Multiple workshops are there. So we don't know which banner to trust. And some data is also there. But it looks like a stakeholder workshop. It's not a fully a data that you can export. So this is the concern as I said we have. We do not have a data that we can export. So it happens. Okay. So the screen is not visible. Let me share the screen. My initial screen. So if you click on this website, this photograph, it will come up. So I'm going to do it again. You could just click on this photo. You can see the photo come up and you can read, zoom in and read what they do. And it's really good to see some data, etc. Please it looks like a stakeholder workshop. Okay. The first image doesn't come up. Maybe some issues as I speak to zoom. And let's see if it comes up. It's not from. So this is some data set on a workshop. But what is it on the ground? What does it mean on the ground? We don't know. So just focus on this name. As I said, I've also worked there. We will take a paper that we published with them collaboratively on the issues and concerns and how we address them using satellite sensing data. So this is how we can find the points and then use it for our research. So it's a date. And based on the date, you can have different points. So the different legends are here. This is one thing. At least you can see NRN plantation and party culture. So you see some plantations and fruits that have been growing here as per their comment. It is Wujrat Dahut, who the farmer's name is there, some numbers and links to do the things are there. So you can see the start and consumption data is 2016. And this has been approved on the 23rd of 2016. So during the project, they collected the data, it seems because the project ended in 2016, but the data was collected almost on the ending time. So that is also good. And so this kind of data you can extract. So locations you can take and extract. See, the location might be hard to take, but I've already taught you how to georeference. So take this image like this, you can cut copy paste, or I'll just show you the trick. You can use a Word document. So let the Word document come up. And you can take a print screen. So in the print screen, you can make a small image that you can save as a paper. So I'm just going to click print screen. And then this is what I taught my students also because the boundaries is very hard to collect. And so you will have, so on a Word document, just control paste, your image will come. And all you have to do is format, and then crop image. Use the crop tool, take the image, or use any paint software or anything you want. So here we have an image. You can save this as a picture. You can click, right click, save as a picture. And then import the picture on GIS for ground proofing and georeferencing. So once you georeference, what happens is, now you have the locations. These locations can be extracted. And you see those boundaries? Those boundaries can also be extracted. So this is how I have taught my students when there's no data, don't complain, there's no data, but start collecting data. So with this, I will stop the discussion on this website. As you see, there's not much data you have for evaluation, monitoring of these locations, where the locations are is present. Not all is covered. So slowly maybe they are going to put it up. In fact, the IIT Bombay has also been approached by them to see how we can robustly make these databases because the computer science department here is very, very knowledgeable of these things and see how to collaborate with NABAR on creating these websites. So it's pretty good to see and then you can remove it. And you can see other programs. Similarly, quickly we can do a soil watershed development program. Let it update all states, how many states are there, more states are there. So let's say do Maharashtra. You cannot take it out. So let's say it's fine. All same period, just search for it. And these points are coming up. So these are the points where a different scheme are working, not the same scheme, but different scheme. So you can click on this and see nothing much is coming. So we can go zoom out to see any other data that it's working. So not all datasets have the pop-up. So maybe this one has it. All the green ones have the pop-up. So this is going about soil improvement. So I'll put the productivity another bar, pretty progressive district. And you have been approved very recently and 2020 was a project. So they're basically building vermicompost. It looks like to improve the soil, the fertility and stuff. So I'm happy to showcase this, which is a dashboard, which has GIS and one layer behind. But the idea is to extract this information and use it for your work. I will show you here also, as you've seen in the previous. You can also put the location there and then see, now we have 2009, the program started before and after 2009, what happened? So all these can be directly maneuvered through this sentinel hub. I've already shown this how to search for a location and then do a compare between images. So you do an NDVI or NDWIP4 and after. And then we'll do it. So I'll show this in the next class because of time. Let me stop here. But please go and refresh your notes on the materials that were shared in class. Again, monitoring is there. Evaluation is not there. So how do you evaluate a program? So that is what we'll be addressing in this week. I will see you in the next class. Thank you.