 Good afternoon everyone. Thank you for joining our webinar. As you know these, we have been in touch with your focal points, Ms. Nurjan team, for basically to understand your needs and requests for further, let's say, online capacity buildings within the context of our integrated land use planning project is a project for IH spacing. Of course, we were hoping that we could do this type of trainings in person as it's much more useful and also more interactive but unfortunately considering the situation it was not possible so far but not to waste any more time and especially because our project is relatively a small project and we'll end in couple of months. We didn't want to wait any further and lose any more time. That's why with the help of our great experts, Ingrid Tarsian says at Garcia we managed somehow to continue this series of webinars online. So as you probably seen the first webinar was already done about the IHUP concept and what we really mean by integrated land use planning, the methodologies and how we would like to develop the scenarios, what are different parts of the integrated land use planning and what we have done so far within the context of this project. As you probably know we did socio-economic analysis, we did some soil sampling with your help and we are now waiting also for the results so we can come up with some sort of scenario development. As you probably know this is a TCP project and under this TCP project which is technical cooperation facility done by FAO it is not possible to do the whole integrated land use planning methodology. So we have chosen basically two different parts of the whole plan like socio-economic analysis and the soil sampling as I mentioned to develop later on the scenarios. But anyway these series of webinars are somehow part of also our project and we hope that you would benefit from this online. Please feel free to ask questions. We hope that it will be an interactive discussion as well. Our experts will give their presentations but then there will be also some time given for questions and answers. I'm sure Ingrid will explain how today's webinar is organized. I don't want to take more of your time. I just wanted to welcome you. Of course this webinar will be later on uploaded as well online so for those colleagues who couldn't make it today we encourage that you send them later on the link so they can listen to the recordings. Again thank you very much for your time and I wish you a very fruitful webinar. So I give the floor to Ingrid and I'm sorry I didn't introduce myself but I believe most of you already know me so just for the records again I'm Sara Marjani the London Water Officer for our FAO office in Central Asia and based in Ankara for Central Asia. Thank you and back to Ingrid. Thank you Sara and thank you everyone. My name is Ingrid, I'm a FAO International Consultant and I will share my screen. Okay thank you for being here and it's a pleasure to give this webinar as Sara said this is the second webinar of five that we have organized. It's called Fundamentals of GIS for Land Use Planning. Now why this isn't and there it is. The first one as Sara said was already recorded and the video was uploaded in FAO's web page. It was about the methodological framework and today we are in the second webinar which is about using GIS for Land Use Planning. The third webinar will be held on August 31st. It will be about Google Earth Engine as a Geoprocessing Tool. You will have to, I don't know if you can hear my cat but he wants to enter and if I don't let him in, sorry. He will be all the webinar talking. Okay so the third webinar will be on August 31st. It will be about Google Earth Engine which is a geoprocessing cloud-based platform really useful to obtain a lot of information and processing information in Google's cloud. Sorry. The fourth webinar will be about landing degradation and gravity indicators using these indicators in Land Use Planning with a special emphasis on land utility trends which is one of these indicators. And the last webinar will be about using our software for analyzing special data and digital soil mapping. The idea of these webinars is that one builds on the other and that after this last webinar we will have a training on digital soil mapping in which we will use all of these tools. So the idea is to start building on for this last training on digital soil mapping. As I said the first webinar is already uploaded. Here is the web page in which you can find it. There are three videos and the last video, the third video which is the one that I prepared is also an introduction for this webinar in which I talk about all these tools. So if you already see it, great. Okay so today we will have four parts. I will start with an introduction on GIS and then Cesar Garcia will give a practical demonstration on how to use QGIS for land use planning and working with vector data. Then I will again take the floor to give an introduction on using satellite derived data. And finally we will have a practical another practical session with digital elevation models and other and different variables that can be derived from these models. So let's start. Well maps are one of the most important human inventions and they are basic tools to explore the world, to communicate ideas and manage our land are really essential in land use planning. We can use maps in different stages of land use planning and to communicate ideas to stakeholders and make decisions based on maps. I found this when I was preparing this webinar and I think it's very nice because it's in Anatolia. The world's oldest map is supposed to be there. It's there is from almost 9000 years ago and well you have a long history and tradition of maps as you can see and you probably know. And this bird eyes view that we take for granted like now we use Google Earth it's very different from that old map and it's a big step for human evolution and it requires a demands a map making formal map making requires that humans to be organized to actually have this bird view and formal map making. Nowadays maps are of course very different. They have different, for example, you can have you we have graphical scales, numerical scales, a coordinate projection system, a legend, etc. And there is a new era in cartography, which is digital mapping and digital maps have the same functionalities of paper maps, but they have extended extended functionalities and this we can look at different areas, we can update them often, they can be interactive, etc. And this is possible because of the global positioning systems satellite network because of computers and other technologies of the late years that have made this possible. And GIS in this context give us a it's a great tool for working with different layers of information as we can see here and that a stratification is key for you look and for these types of projects because we work with multi-dimensional data and we need to analyze compare and visualize and manage these different layers of data and this is something that GIS is great for. So GIS is actually more than the software. We usually refer to GIS as the software, but there is also hardware methods that are human resources that use them. And regarding the software, there is a question that we usually ask ourselves and is which GIS software should we use. If you if you would like, maybe I will not read it now, but if you have experience in GIS and you work with a software and you can write it in the chat, I will then look at it. I probably think that if you do you work with ArcGIS and well it is a great software, there are many possibilities and you need to choose the one that that is best for your objective. Some of them are more related to are better to manage vector data, others for satellite derived data and we will work today with QGIS. Why? Well, because QGIS first of all is a free and open source GIS. It has many capabilities. It works well with vector and raster data and there are many plugins that you can connect to QGIS and one of them, for example, is terms.earth, which is one that we will take a look in our on the next one, the other webinar. And with these plugins, you can do many, many things. We will look today at some plugins for multi-criteria assessment analysis and also for analyzing digital elevation models. So this is if you work with GIS, it might be very basic, but maybe not all are familiar with these terms. So I would like to talk about this for a second. There are two data models in GIS. One is the raster and the other is vector. Special data has two components. One is the spatial position, the spatial data itself. Another and the other components are the attributes. So what is the difference between raster and vector data? Basically, how do you, which is the data model you use for the positional information? So for raster, we use a grid. As you can see here, this is a digital elevation model of IS, basing, and if you take a zoom in, here we can see a grid. And for each cell in the grid, we have another each value, for example, of elevation. Elevation will be the attribute. And the grid itself is the positional information. The most common format for raster is the geotiff. You get one file, which is the extension is tiff. With vector data in the raster data, we have a wall-to-wall approach. We have values for all the area. We have a grid that covers the whole area. But with vector, we have three basic forms for positional information. Points, lines, and polygons. And the most common format for points, for example, in this example, in this map, sorry, here this is the map of IS. And if you can see the points with different colors, they represent the location of the site where soil profiles were taken for this project. For example, lines are a collection of points. We could be rivers or roads. We will work with this data today, with QGIS. And polygons represent areas. For example, a lake could be a polygon or an area where you know something is happening in particular. And the most common format that is used for this type of data is the shape file. This is a type of file that comes from SV, which is the model of QGIS. But there are other formats, for example, the Geo package, which are more efficient than the shapefiles. But still, the shapefiles are the ones that are mostly used. And as you can see here, one shapefile is actually not one file. When you have to send a shapefile to someone, you need to send many files, and you will receive many files, not only the one with the extension point SHA, SHP. You also get different files that, for example, the PDF is the database, because for each feature here, for example, for each point, and a database is associated with different attributes. For example, for each point, we could have electrical conductivity, soil organic carbon, pH, etc. And that information is in this file. You also get the projection file and many other files. So talking about projection and spatial data, I will not go very deep into this, because this is a whole, a lot of mathematical and physical information to actually understand all of this. But there are two concepts that we will see now that are very important when we work with GIS and with spatial data. Why is that we need a geographic coordinate system to position our data? When we talk about latitude and longitude, we are using a geographic coordinate system. And for that, we need to refer these coordinates to an origin. For that, we need to represent the Earth somehow. And we know that the Earth is actually not like this. It's not a perfect sphere. For example, the radios in the equator is larger than that in the poles, and it's not perfect. So there are different ways and different systems to represent the Earth. One of the most common or mostly used ones is the word geodetic system, WGS. And it allows us to reference our geographic coordinate system. But to represent this in a map, because this is a sphere, we need to put it in a planar surface, we need to project this into a planar surface. And as you know, a sphere is not a developable surface. And it means that this is an example of an orange. If we have to put the peel of an orange in a plane, you will distort it. So maps necessarily distort the data itself. And there are different ways to project different types of projection of cartographic projections. And when we talk about projections, it's exactly that sense. If you see in this image, you have a lamp in the middle of the Earth, of the representation of the Earth, and you project it on different types of developable surfaces. What do I mean by developable surfaces? For example, if you use a cylinder, you can cut the cylinder here in the red line and you get a plane. So depending on the projection that you use, you will get different maps. For example, here we have the cylindrical projection, the conical projection, and the planar projection. And depending on where you place the surface is the projection you also will obtain. Why am I talking about this? Because then we will have to use it. When we obtain maps from different sources or when we download information from satellite information, we sometimes need to make transformations and make sure that we are doing things right. These are three types of projections. I think it's very nice because, for example, this is the Mercator projection, which is a cylindrical projection. And you can see here Antarctica is huge. So it's Greenland. It's bigger than South America. And this is not true. Actually, South America is bigger. It's larger than Greenland. So the sizes are distorted with this projection. In this other projection, the Carl Peter projection, the sizes are relative to each other are better. As you can see Greenland and Antarctica are so much smaller now than South America, but maybe the shapes are not so well. And I always like to show this projection. This is a planar projection because it's the one that we have in the United Nations logo, the axiomotor projection. And this is a data set, a public data set, the EPSG Geolithic data set, which is used by most GIS. And here each country and each area can have a special, for example, you have a code, for example, for Turkey is the EPSG 32637, which is this is the datum and this is the projection. And it is really good to make transformations. Okay. So for what are we doing for our project and for land use planning? Well, we can use GIS to have all these different layers of biophysical parameters and variables that can help us in the process of land use planning to work together with stakeholders participation. We can have land cover, land productivity trends at the digital elevation model. And we can, for example, we using GIS calculate the area of each of the categories as you probably know, better than me. GIS is mostly covered by arable land, 40% of the area, followed by trans lands with bare area, 30%. And we are also adding other layers of information from global products, such as the FAO's Global Soil Organic Carbon. We will also obtain maps of soil characteristics from digital soil mapping from the results of the lab. There are also many other products that are available and that are free. And we will talk about this also next webinar that you can download, for example, using Google Earth Engine or you can work with them in the cloud. For example, fire intensity or urban or lights that give you an idea of how cities and well, there are many, many products that could be useful. Of course, you always, these are very general products and depending on the scale you are working, whether they will be useful or not. And that is why it is also important to work with products at national level and regional level and local level. And we know that Turkey has a lot of information that it could be really useful, for example, the potential forestry activities map, the certification risk map, the water erosion map of Turkey. And these products would be great to also use them for IS and for the project and for land use planning. Okay, so how do we use this information? First, we have the information, how do we use it? How do we combine it? And GIS offers as the opportunity to, for example, use multi-criteria analysis. In the previous webinar, I know if you've seen it or not, I showed this example of this study that was published this year and for Turkey, for Konya region, where they use different multi-criteria decision analysis techniques to make a beekeeping suitability maps. What is land suitability? FAO defines land suitability as the fitness of a given land, of a given type of land for a defined use. So in this case, the defined use was beekeeping. So what they did, what you do with multi-criteria analysis, after you think of which is this final use of the land that I'm aiming at, you define which are the limiting factors for this. For example, for beekeeping, bees need, of course, plants. They need water, some sources of water. And once you define all these limiting factors, and you have maps for each of them, in this case, they use them derived variables, topographic variables, climate variables, and many, many maps. You define the for each criteria, which is the optimal range for beekeeping. And combining them, there are many different ways to analyze the data. Basically, what you do is you give a weight to each of them. You can obtain, for example, these type of maps, which are suitability maps. And here in red, we can see areas that are not suitable for beekeeping. And in green, we see areas that are very suitable for beekeeping. And this is, for example, a product that would be very useful to have for land use planning. And we can create suitability maps, for example, for forestry activities, or for a special type of productive activity. Also, multi-criteria analysis is good to make analysis of decision alternatives. Together with stakeholders, we can analyze how different decision alternatives will turn up. And, well, this is something we prepare together with Soledad Bastidas. And it's very schematic. This is not true. And this is, for example, one is to keep our mind towards what we are aiming at in land use planning. We need to define which areas are more appropriate for different uses and for each of these, you can use different criteria. For example, areas of permanent forests, areas where we have forests, where we do not have, well, for example, we have positive trends of land productivity, et cetera. Together, of course, with a participatory approach and discussions with stakeholders. Okay. So now, Cesar, give the floor to Cesar. He will show you some activities, some practical exercise using vector data of IS basin. And he will give an introduction on how to download, use, and QGIS. So that is all for me now. Thank you very much. And I will stop sharing. Okay. Thank you, Ingrid. Okay. Let me share my screen. Bear here the chat and everything. And you see my screen? Yes. Yes, yes. Okay. I will show you some things. I will let me, I think I will turn off my videos so that you can get a better transmission of my screen. And also some web pages I want to show you. Okay. I will just give a brief introduction to QGIS and also show you some examples of how to open data and we can do a bit of a simple exercise. We don't have much time, but we will do some exercises. So first of all, QGIS, you can search in Google or anywhere for the name and you will be, you will be taken to this page. This is the QGIS web page where you can download the last version of QGIS. There are different versions. I will open the change log. So if you come to download now, you probably will find some standalone versions. So depending on your computer, most of the computer now are 64 bit. You can check that in your computer and decide which version will you download. They normally have a new version. They update it every three months or something like that. And then they have one version that they update once a year. So this is a more stable version of QGIS. So it's a very tested version and they put it here and it remains the same for a whole year. And this one usually has the more different or more updated tools. This is a QGIS that is open source. So normally there are different tools that you can use, but we like this very much because it's easily to teaching courses. We use it with a lot of plugins. And it's a very large community from different parts of the world. So this is, for example, this is a new version that was recently launched. You can see there are a lot of members from different institutions, educations and research and government. And this is just some of the new features that are in this new version. So they are growing very quickly. Every time you see a new version coming, it's updates very quick. They have a lot of information and tutorial or how everything works. It's really advancing faster that you can keep track. And so it's a very good and complete software for QGIS. And the good thing is free. You can download it. You can share with anyone and you can start working right away. You can publish your data and you don't need to pay anything. So once you download it and you open it, this is the window you will get. Perhaps some news or if you have recent project, it will give you some of the recent projects. But for the first time, this is what you will see is very standard of many GIS. You have here in the middle the map canvas where your map and information will appear. And then you have some toolbars here with most of the commonly used tools. Just to zoom, to save the projects, open layers. We will see some of these soon. And then you have panels, a lot of different, this is a toolbox. So a lot of different toolbox here. One of the good things about QGIS is that they have their own tools, but they mostly connect to other software like for example, Grass, which is also one of the first free GIS that was around. Saga GIS, and then you can download a lot of different plugins and tools that they all appear here. And when you go inside, you have different sort of tools. So it's a very complete, and how you can see, there are a lot of tools to do a lot of stuff. You also have the possibility of connecting to Python and R. So you can also program whatever you need and it's missing. You can also make a model builder. So there are a lot of different possibilities. And this is also, you have these different panels here that you can configure it. I always think I always recommend you can turn on and off. For example, if you don't like this one, you can make a space and then you can turn it on again if you want the tools at hand. But it's always good to have these two. For me, these are the main panel. This is the browser. So here is just like a file browser. I can go to my different hard drives and different folders and look for information. And here is where the layers. The layers I'm going to be opening will appear and I can manage my layers that I'm seeing. So let's just do that to see how it works. So Ingrid told us that you can have vector layers. These are the shapefile. I'm using shapefile because it's the most common thing and also with other software, most of the software use shapefile. But in Ingrid mentioned, there are other more efficient ways of storing vector data. Can you put that because we cannot see the maybe bigger, a bigger resolution, we cannot read anything with these two small. Okay. No, I don't think I can. No, okay. Put it with a, I don't know how I can do it. Don't worry. Perhaps changing the resolution of the screen. We can give it a shot. Let me see. Now it didn't change. Not much. No, it got bigger here, but it didn't change there. Let me see if I choose something like this. Yeah, there. I can see it better. Thank you. Okay. Now this is too big for me. But so here we have some shapefiles and some raster files. You can see this is a logo of a vector and a raster. Okay. And then as I mentioned before, this is the browser so I can go to any folder. For example, I have this one for the webinar as data. And I can just get, for example, this is a soil map. I can just double click. And it appears. I can also, for example, if I have here my folder, I can bring it here. And for example, if I want to close this layer, I can just remove it from here. I can also come to here and add the same layer just by dragging and dropping the shapefile inside. You see it opened the same file, but it changed the color. So most of the shares over have this functionality. When you open a file, what you open in is a different elements and the different geometries. In this case, these are polygons and they normally open with a random color unless you already specify somewhere in the file, some particular style. It will open like that. And there are multiple ways to open files. You can also come here. This is the main file opening window. You can open vector, rafter, mesh, text files, delimited by coma or any other differentiation. You can open up your packages, different sort of layers, virtual layers, layers that are in the internet, in different type of servers. Everything can be open from this data source manager. But the easier is, of course, coming to the folder where you have the data, you just double click or you can also, for example, this is the LAN cover, drag and drop, and it will also be open. So what do we do now that we started open layers? So the first thing I see now is that LAN cover is the last layer I see. And it's open on top of the other. I can change the order, the order of what I see just by moving this one on top of the other. So this is a nice here. So it's like you are looking from the top. So first you are looking at LAN cover and then to soil, but because one is covered in the other, you can see only one. So let, for example, come to the soil one, which is has lesser units. And you can do some of the first things you do normally when you open a layer is to explore the layer, what this layer contain, what information. So here, if you do a right click, or also if you double click on this name, you will be taken to the same place, which is the layer properties. Layer properties have information about this layer. So the name is Aya soil. It's a S3 shape file. It's a multi polygon layer. And it give you some other data sources also tells you, which is a coordinate reference system. So this is projected in UTM. And here in symbology label, you can change and you can see and you can do a lot of actions. So for example, layer properties, this symbology is the representation here on my map. There are different things I can do here. I can just change the color if I like something like this. I can also decide which is the color of the lines, the field, and I also have different possibilities. For example, I can do categorize. Categorize, it will mean I will give to every polygon a color, depending on a category. So which is the category here is value. Let me see what we have. Okay, we have BGT and area. These are two things that I have to choose. I will choose BGT, classify. And these are different soil types, for example. So every soil type gets a different color. I can change this color if I don't like the orange. I can double click. It will open yet another window and I can say, okay, this one instead of orange, I want a bit more red. And there you go. And with that, I changed the color of the different elements with the property in the database. So like Ingrid mentioned, every of these polygons here is associated to a database. Where is the database? Well, if you right click on the name again, you can go to this open attribute table. And this open attribute table will take us to the... Let me make it smaller. Will take us to the attribute table. So I have 442 polygons. And as I can see, for most of these polygons, I have these two fields. One is the name of the soil and the other is the area of that polygon. Here is the information that I can use. I can use for these layers. We will see more examples later. And I have some tools here where I can zoom in, zoom out. But I can also move with my mouse. If I move the wheel of the mouse forward, I can just make a little bit of a zoom in. And I can use these tools. If you see every time I stop in a tool, it will tell me a little bit of what this tool does. So a bit of context information. This one is called identify fitters. So if I click on this one and then I click here, it will automatically open another window, which will contain information on this polygon. So for this case is a soil type B and this is the area. If I click this one, it will be a soil type A and this is the area. So as you can see, every figure is associated to some database where you have a lot of information. So that's the basic concept of vector layers in a GIS system. So let me turn off this one. As you can see, I still have selected. I can still select because I'm on this layer. I am on the selecting tool. So if I want this to stop, I can come and grab the hand and now I can move. And nothing gets selected. This can be close. Let me see then the other layer that I have. Just click here. This is the land cover. We can see what information we have here. We can go to the open attribute. And we will see this is a bigger attribute table. It has 21,463 small polygons for this area. And they have different things. They have ID. They have different codes. This is a land cover code. And then here are the land cover categories. These are in Turkish. And here are some land cover categories, some names in English. So all of the information that I have here, I can use for something. I can filter and select depending on the area on the type of land cover. And we will do in a little bit an exercise about this. So I can also do the same and give some color to this layer. If I double click, I can come to symbology. And I can also color by giving a different color to every land cover. I can do like this. And here is the name of the land cover. And every land cover will be given a different color. So here you have, it's a bit ugly. Another thing you can do here is for example, you can turn on and off any category. So if you are interested in seeing one category or not seeing one category, you can one by one put them on and off. So that was a possibility we didn't have before, but now that we categorize it with the land cover, I can choose what I want to see. If I, instead of land cover, I choose another of the layers. I can also do another of the fields in the database. I can also do the same. You can also have prepared styles. So here I already, once you change the color, you adjust the name, everything, you can save these styles to use later. That is what I did. And now I can load and style that I already prepared for this layer. So if I come here, I can come to AS data and load this style that I already prepared. Load the style and you'll see it will change to the color in it makes. So now the map looks a bit better, at least for me, maybe two pink still. But as you can see, I put arable lands in different tones of yellow. Then you have all the different type of grasslands in different tones of pink, artificial in red, some blue for water, some permanent crops are in this type of green and in very dark green is the forest. So we can zoom in a little bit and explore the data. And also if you use this tool, you can come and check for every polygon, what is the information that we have. We have this different sort of information and for every of this volume. Let me zoom out again and let me open yet another layer. Another of the layers I have here is the study area. So this is our study area. I can put this probably on top. And I can use, for example, do a simple fill, just put a transparent fill and a surrounding line. So everything you can do here is very personalized. You can change mostly everything about this data. And I will open out the road information. So this is another layer. Ingrid mentioned that there were different type of layer. There were polygons, mostly what we've been using. And this, as you can see, is different. This is a line. So this layer is made of lines. And these are the roads. I probably can put this into a darker color, black. Okay. And here we have the roads. Where this road been taken from. Okay. This is also something interesting. You can get a lot of different information from different sources. I took these roads. So we've been seeing this. I do this road from open street map. Open street map is a similar to Google Earth. It has a lot of, sorry, from Google map. It has a lot of information about the different things, the roads, different features that you can find in a map. And you can download from different sites. For example, here you can, if it is something very small, you can export it directly from here. But there are another interesting places like this is the geofabric. It's a repository. You can upload information from all Europe. Or here by country, you can also download a lot of information about the, in different format in shape file or in different databases for the whole Turkey. Or you can use also this overpass turbo is another option that is there. Here you can build queries to the database they have. So for example, here I put Turkey and I asked for the administrative level boundaries, level four. So this is what I get. And I can just download only, only this. So there is a lot of information here. You can just go to open street map. And you will be able from there, you will be referred to these different possibilities, depending on what you want to do. There are some tutorials around. We'll teach you how to download information. And basically you can get road maps, boundary, a lot of information. So okay, now we have a lot of data here. We have a land cover. We have our study area. We have roads. So I will make a very short exercise to show you some of the very quick and simple functionalities. This is a bit the idea. The idea is to look for, you know, like the example that English show about the beekeeping. The idea will be to make something similar. I mean, I want to do something in this, in this area, some specific land use. And I need to find areas that have woodland. These woodlands need to be far away from the road, more than 500 meters. And I also need to be close to the water. So I need to be less than 7 and 50 hundred meters from a river or a lake. For example, if I want to do a suitability map or to find a place that is in the water, I can use this type of line. And these are my restrictions. This is what we are going to do now. Very quick, because I think I ran out of time. So the first thing we say is we need to have woodland. So we have a land cover map and we have woodland here. In green. So remember, we say we have a database. So usually in GIS, there are many ways of doing the same thing. For woodlands, I will just come to the database. And here I can filter. I can, I'm seeing the whole, all the 21,000 features. And I have zero selected. But I can come here and put a filter on a field. So if I open a filter and I choose the land use name here, I can start running woodland. So here is woodland. Oops. Here is a woodland. And if, if I press okay, I will get, as you can see here in this look name, all of the features I'm seeing, they are from woodland. So I have filtered from the 21,000 units. I have only 213 in this table. The one that are land use woodland. So I can do something very simple. I can just come here to the edge. And select every feature on this table. So here I have selected 213 features. So every feature is with woodland. Now, if I come to the map, I am sorry. Here you see all turn, all the woodlands are now yellow because I have selected all my woodlands. So now that all my woodlands are selected, I can come here. Where say I asked my land cover and export. And I can create a new shape file. So here I am in my layer. I asked land cover. I will just call this. I asked woodland. So I can create a new shape file and I can use this option here. Save only selected features because I only selected the woodland. When I create my new shape file, you see it's already been open. I'm sure it will appear soon here also in my, in my folder. I have a new feature called IS woodland that only contains, if I go to the attribute table, it only contains two 213 features, which are my woodlands. So I make a new shape file only with my woodlands because these are my areas of interest for this exercise. So let me just turn this off aside. Now I have another requirement. That was 750 meters away from the water. Sorry, close to the water, less than 550 meters. This information is also in land cover. The land cover has information about the water, some of the river, some of the lake. So I can also take the information from there. But I can do a different way this time. Instead of building a new shape file, what I can do is to filter this shape file here. The first thing I will do is to unselect everything. So this is the bottom is to deselect everything. Now you see my woodlands are already green. And this is another approach at filtering. I can go to the layer and I can open here this option filter. And this will give me the query builder query builder. I can just select using the database. And I can do anything I want. So I'm focused on land use name. And here I can say, okay, show me which are all the possibilities from land use name. So here I have water bodies. I want water. So I will put land use names equal to water bodies. I have another one here, which is natural water bodies flowing. These are the rivers. So if this is a water body standing or if it's a water equals to natural water bodies, I'm interested in those places. Then I say, okay, always taking us along. So here, as you can see now my land cover only shows me these features I have selected. Doesn't show any other land cover. And if I go to the attribute table, the attribute table only will contain these features. So it's almost the same as if I created a new one. Because every operation I do now with this land cover will only be done on these features that you can see the other features. The ones that are from other land covers that are because I have this filter will not be processed. So here I can run one of the tools that I need to define a the 750 meters range. This is the geoprocessing tool. I have this tool here called buffer. So what I can do here now is take my IS land cover. And here in this dance, I will put 500, sorry, 750 meters. I have also here an option that means dissolve. I will click this one. And I will show you what it does. And I can save this to a file. This will be my water buffer 750. Okay. This is what I get now. If I overlay this, this will be showing me which are these areas that are closer to 750. I can put here my land cover. So this buffer is 750 meters from any water source. And this in brown are my forest. So here I can see where I have a coincidence between these two criteria. Why did I click dissolve? Because as you can see, there were a lot of different elements in this land cover. So this was one element. This one was element. If I don't use dissolve, it will make just a polygon. 750 meters around of each of the features will be a single different feature. But because I put dissolve, every boundary in between these two, it's eliminated. And now, for example, if I come here to my water buffer and I select this one, you see, this is a single. This is a huge polygon where everything is connected. And in this case, it was better like that. So I have the first two elements. I have the water, the 750, and my forest. What I can do next, I can come here to the vector. Here you see there are most of the, not most, but the common QG tools for vectors. As I mentioned before, here is a huge processing toolbox with a lot of vector tools to complement this one. But this is easier for this example because it has different small drawings that will tell you what this tool does. What I want to do here is clearly this one intersection. So where these two layers meet. So I have the water buffer and the woodland. I want to see where these two are together. I will save this to a file and I will put this in wood water. Okay, run. Let me put it on top. Okay. Now we see in this red color are all the areas. If I turn off the other ones. I already created a shape file where I have this thing. Areas that have woodlands and are closer to the water by 750 meters. I have yet another criteria that they need to be far away from the road because what I'm going to do doesn't require to be close to the road. Maybe the roads are too stressful for the animals. I'm going to take care. So I have my road here. I think we can skip this because we are running out of time. Okay. And finish with only two criteria and maybe show the plugins. Okay. So here, just to mention is it will be the same to the rose you can make a buffer and then you can remove these areas that are 500 meters. Here in the vector, you have all these different possibilities. You can use the union. So where two layers meet, you can use the difference. For example, where the roads are just take this piece out. This is the one you will have to use. So you can make it manually like this, for example, to make a suitability map, or you can use to do different plugins. And here, for example, there is something in plugins, you have the plugin manager. It will open this window here. Here I already made a search. I just put criteria for criteria. And you get different plugins that being developed from different people that you can install and you can try. This is just pressing. For example, this is not installed. You can install and just run it. And here to show you to also, there are some tutorials in Cushy's webpage about multi criteria overlay. Of course you can do this. This is using all free data from the same places I got it from OpenStreetMap. And they convert it to raster and they do the multi criteria analysis in raster. So you can go using the raster different plugins. This is a raster plugin that was already there. Or you can use, for example, for Vector, if you can also to their page of QCIS, you will have here a lot of information about every plugin. They have the code so it's free and you can also look at what the different methodology is. Some plugins like these are also well documented. You have here a tutorial on how to run this plugin. These plugins work for Vector and it has different models that you can use to do multi criteria assessment. What I just was doing here is just not a word-to-word approach. It's just to choose which are the areas. I only want to see these polygons, but you can use different methods like the one that will be keeping the English show. You can get the whole map of the study area and you can see which are the best places, which are the average places and the worst places. You can just keep a little bit or you can do a word-to-word approach in Vector or in raster, depending on which data you have. But there are different tools that you can use and different approaches. So I will continue later with the raster and elevation. Ingrid, then I give the word back to you. I don't know if there are some questions from participants. Or we do it at the end. If there are any questions regarding this, maybe we can answer them now. Or should we continue to work with the digital elevation models? I think there's no question. Okay. So if you let me share the screen, Cesar. Okay. So Cesar just showed you a little bit of how easy it is to work with QGIS. I strongly encourage you, if you are GIS users and you are working with other software, to take a look at QGIS. And well, he showed a very simple way to obtaining a suitability maps for a specific use. And now I will give a very brief presentation on an introduction on using satellite-derived data. And then Cesar will continue working with digital elevation models for ISBasing. So remote sensing is a very broad term. The satellites are just one of the platforms by which we can obtain remote sense data. Remote sensing is defined as the acquisition of information without making physical contact with the objects. So I always bring an example from history, which is good to enlighten us. And in World War I, for example, they use pigeons with cameras to obtain pictures and information. And this is also a type of remote sensing. A remote sensing platform could be also a light one. In 1957, the first satellite was sent to space, which was the Sputnik. And nowadays we have so many satellites that are surrounding us and obtaining lots of information. I think it's good to keep up with all the information that is available because it could be very useful and it's free. And there are different types of orbits of satellites, the geostationary, which go from west to east over the equator. And they keep the same direction and rate of the earth. So they show always the same area. And also the polar orbits. This is an example of how they allow to map the whole world by polar orbiting our planet. And like this we can obtain, for example, most sites, which are composite, come from the composition of several satellite images. Also it's good to, especially if we are going to work with digital elevation models, I think it's good to remember that there are two different ways of obtaining information to two different types of sensors on board of satellites. Some are active and some are passive. Passive means that they, this is the example of passive, which the light from the sun is reflected and that is what the sensor in the satellite captures. Active is the same satellite sends information, sends energy, and that is what it gets back, for example, at the radar wavelengths. So each sensor can obtain and measure the energy at different ranges of the spectrum. And this is what we call bands. You know, we have, depending on the wavelengths, for example, the visible light, it's very, very narrow as you can see. But some satellites also see infrared, some sensors and other portions of the electromagnetic spectrum. I will go quickly on this because it's just to give an idea. Different satellites have sensors that can perceive information at different ranges of the, at different wavelengths of the electromagnetic spectrum. And here we can see what we call bands, depending on which area, which energy they are perceiving. So, and then we can mix these different bands and emphasize the information that we want to see. For example, if we can mix the red, the blue and painted in these colors and the green. And here, for example, we can see easily see the land cover in this, in this image, for example, we can see urban areas, we can see areas where vegetation is green or not. And this is a broad world to explore and to get information and it's really good to, for example, for land cover, we can also measure changes in this, in time, changes in land cover. Here we can mix different bands to enhance vegetation and this is what the vegetation index is doing. We will go deeper on this on one of our webinars. NDVI, EVI, SAVI, there are many vegetation indexes with mixed, mixed, for example, the red and the near infrared bands of the information. And we can see, for example, with many dates in a temporal resolution, we can see how vegetation is in the productivity is increasing or is decreasing. And this is really good for land degradation for monitoring and mapping land degradation. Also, we can use this information, satellite data, the information to map soil salinity. We will not use this for IS because we have the information from the soil sampling, but it is also a use. And also with the active satellites, we can model elevation and have digital elevation models. Well, this I already said that remote sensing is a great tool for mapping land degradation. And, well, digital elevation models can be produced not only by remote sensing information, but also by topographic services. They produce relief maps and they can be represented as raster or vector based using the triangular irregular networks, but they are commonly used using remote sensing data and as raster layers. Oh, this picture shouldn't be there. I don't know why, but the shuttle rather topography mission, which was flown in 2000, we kind of gives information for a 90 meter resolution digital elevation model. And it was later in product at 30 meter resolution was launched and it is free and it is for the almost the whole earth. It can be downloaded from internet here we can see for example, the 90 meter resolution. DEM for IS now Cesar will show you this with more detail also the 30 meter resolution and a five meter resolution digital elevation model. And the great thing about this is that we do not only get elevation, we can derive many other variables such as slope, which is, for example, a very important variable to measure and estimate the risk of erosion. For example, or for for this suitability maps could be a very good variable to consider. We can derive aspect where it is facing north, southeast or west, west of east, actually, and there are also other topographic indexes that you don't even need to calculate them they you can download them directly from the internet. So I was very quick because we are running out of time and I give back the floor to Cesar so that he can work on the digital elevation models of IS basing and show you how to obtain all these derived data and how to. And one of the good things for example I told you that we have three different digital elevation models for IS. So which one do we use what are the how do we explore these digital elevation models how do we see which is best or which is if there are any problems in one of them. How do we obtain these variables derived from them using QGIS. Thank you. Okay. Okay, so if there is a question about the last section or what English has said, just let me know. We have 15 minutes or so Cesar. Okay, so I will try to make it quick. But anyway, questions are very welcome so please just let me know, interrupt me if there is any. So here are you already my screen again. Okay, this is where we stop. Here I have already some DMs like English show this is the 90 meter this is the 30 and this is a five meters I can open this. All together here and we can perhaps explore a little bit I will put the five on top 30 and 90. Okay, now if we zoom a little bit if we look from here from the distance, the whole basin, if I turn on and off. You cannot see much of a difference between the five the 30 and the thing but if we get closer. Probably when we start coloring, we will be able to see the pixels, the pixel size. But just to give you an idea, we can just go to any of these and look with our inquiry tool. And what we will get is English show so for every pixel, I will just get an elevation. So basically this is a matrix and every cell has only one value. So what are these different sources of elevation come okay there are different places that you can download data. There is a lot of data available as English say, you need to find what is there and then decide which one to use and make a bit of a quality check and controls. And here is this earth Explorer, all of these SRTM this DM 90 meters and the 30 meters are coming from here. And then you have this alos, let me turn off the video. And then you have here also, I'm not adding this to the example, but this is alos pulsar is another option is a 12.5 meter meter, 12.5 meter resolution. Here from CJR. There is also the source of the 90 meter DM digital elevation database. This is also very easy, all of these are freely available so you just need to find the bottom of sales and load data like here. And then you can just click in the in the place you are and you can get a S Riazky or geodeaf with the them from your area. This is one of the best. I mean, is a 90 meters, but it's very, it's been around for many years and it's really, it's really good. Then there are these combination. This is a new version of the Aster G them. This combines the after with the SRTM and this is 30 meter resolution also is the newest product from NASA. And also we don't load a lot from Google Earth ancient. This is to connect with the next webinar. So here you have most of the same sources. So this is the 90 meter elevation product from CJR. You can also use it directly and process it in Google Earth ancient, and you can also download it from here. Just to show you that there are different possibilities. The thing is that then you need to see, okay, depending on what your project is your, your, the size of your study area. If you're working a national level, perhaps 90 meter is more than enough. If you're working in a smaller area, you may need some more resolution. I have to show you some basic tools. This also works in the same way that before you can come to symbology and there are perhaps different options, but you can also color the DM using different, different colors. In Google Earth you have a huge options on palettes. You, you can go here like very deep in, let me see. My screen is a bit big. I cannot see where the things are opening. Okay, here I have also some specific palette for topography. There are a lot of options that you can put here just to make, to make it look nice and change the color and perhaps be a bit more descriptive. So here is color from 400 meters to 1600 meters in this color range from greens to browns and whites. And perhaps here you can more easily see the pixels of these different products. I will compare them now. I already have a project so I don't lose time putting color to, to all of these. Also you can copy the style and for example I can quickly paste the style on these two. So now they all have the same style and if I maybe zoom here, I can see the difference. I don't know if you can see between the 90 meter pixel and the 30 meter pixels and here maybe is a different between the five meter pixel you see is much more smoother. And there are a lot of tools that you can use to manage and explore the DM. Most of the tools are here in raster. If you come to analysis, you will find here tools like a slope, which is to measure the slope aspect which shows you which where the orientation of the slopes are if they are facing north, they are facing east, west. This is very important because sometimes the northern slope have a different humidity, a different evapotranspiration and a different vegetation than the southern slopes. So it's a very important variable to compute and also the hill shade. Hill shade is a rendering of the, I can quickly show you. So you can, you can choose a light source and it will simply create a layer containing lights and shadows, giving you this texture of like a 3D texture and help you explore much better your DM. Now, just let me close this project and I will open a new project I already have calculated the slope aspect and all this variable for the different DMs. So here is a 90 meter DM. What did I do here? I just calculated, just give the same colors that I showed you before and added this hill shade. Here the only trick is if this is normal coloring, you will see this coloring, just the layer, the DM because it's on top. But if I can put here in blending mode, if I put multiply, this is a special option where I can see the colors of these first layers, but also the texture or the color of the layer that is behind. And here behind is my hill shade that I just showed you before. So I can see a color version of my hill shade, which helps me better to understand where are the high places, where are the valleys. And here we can also compare for example this with the 30 meter resolution. You see per half is much is much better. Can you see if I put the 90 meters and the 30 meters, you can see a bit more of detail. And I can also add the five meter resolution. So here we are at the edge. And you can see here in one side, the five meter DM and here in the other side of the line, you can see the 30 meter resolution. So obviously, five meter is much better than 30 meters. This gives you the bigger the pixel size. This is the 90 meter is give you a smoother version. But at the end, these are all models. So this is a raster model. You can build it as English say from different satellites, passive satellites, like different images from different angles, stereoscopy. You can use a rather information like the SRTM mission. You can use LiDAR, drones, different things in order to get these different DMs. Of course, every one has the particularities. As you can see the five meters allows you to see a lot of things that if you put the 90 meters, you will not. So this is very, very clear that more resolution is better. Not always is the case. You can you can check different things. For example, here I also calculated the slope. This is the slope of the 90 meter DM. So here, darker places are flatter and whiter places have the slope, more slope. So if we put this back and I put my slope on top, perhaps we can see here at the edge of these mountains where the slope is going up, you see the lighter places where the slope is higher. And when you put the slope on the different maps, let me turn on the slope on all of these. So this is a lot of the 30 meters. And this is a slope of the five meters. One of the interesting things to see, I always check the slope because in the slope you see a lot of different things about how this DM was modeled. So as you can see here, there are a bit of a, I don't know if you can notice. Some strange lines here in the 90 meter resolution. Not many, but there are some. If you go to the 30 meter resolution and you zoom in, you will see some of these lines too. A bit more often. And if you go to the five meter resolution. The slope and if you also zoom in, you will see also some straight lines like here, different black lines and also some white lines that appear to be kind of like contour lines. So because of this is always a different models, all of the models have issues, I mean, some, some kind of problems and when you project these models. For example, this 90 meters DM was produced or is distributed in a geographic information system, in a geographic coordinate. And if you want to project it into a flat area, you kind of this, you make some distortions in the map and when you make this distortion, this kind of things happen. What is the implication of this? Well, it depends on what are you going to use your DM for? What is the information that you are going to take? If you are going to do solid ocean and you have a, and the slope is very important and you have these things, it perhaps affects your maps and give you some strange results that then you need to correct. So it's very good to explore the data first and see what happens. And for that, there is a very nice plugin here. It's called here manage plugin. There are a lot of plugins that are profiles, profile tools. So if you put these profile tools, there are different plugins with different profile tools. This is also a good plugin and you can basically use any of these tools to make a profile. Let me see if I can find my profile plugin. We have five minutes to wrap up Cesar so that we can have questions. Okay. Good. Then I will see if I find it. It was the icon here, but it's not anymore. Okay. So you can use any of this profile to make a 3D, to make a line and to make a 3D of your study area and see how the profile of the different DMs and a slope are distributed. But a good thing that you can do also to see how the DMs are behaving, the best thing that you can try, it's always to delineate watersheds. So there are some different tools to delineate watersheds than you can use. Here in your toolbox, you can search for a watershed and there is this watershed tool from a grass GIS. You just simply put your elevation map and, for example, I already have it here. You can have a lot of information, but very interestingly, you can also have the river networks distribution. And you can basically put on this on top of different maps, you can use, for example, I can use here a pink map, the pink satellite. I can put here an image from being and I can see here with my basin where my river network is. And that's give you a pretty good idea if the DM is working well or if having a lot of errors. So you can see this is a 90 meter resolution DM. There are some rivers that you can see in the image and for the resolution is very good. So the water is flowing, the way it's supposed to flow is following the river. So depending on the modeling you are doing, this can be a good option. And also here I was preparing this also for the same five meter DM. These are the streams of the five meter DM. And you can see, for example, here how these streams are following what you can see on the high resolution image below. So does this give you an indication on how good there are some areas where some errors or some stretching things are happening. But mostly you can see how this DM is behaving and it's following what you can see in the image. I mean, where you see a river or where you see drainage lines in the fields, you can see that the model is also finding these as streams or places for the water to run just across the road. So this gives you a pretty good idea of how these different models are working. So it's really good to use this watershed tool and always try to delineate the river network, because it helps you understand if the product that you have is where is working good, where is accurate, where there are problems, perhaps these areas are too flat or have been a lot of issues here that make the model get some confusion. But it gives you a good idea of how things are working. And also other things that Ingrid mentioned, different indexes. Basically, you can derive a slope, which is this one we saw. Also, a very useful is the aspect. So here we have the aspect derived into categories. So places that are looking to north are in green to south are in yellow. So this also correlates sometimes very well with what you see in mountain regions that when you have some slopes, the vegetation behaves different depending on the angle they are looking to the sun. So it's a very important variable, but then you can also derive another things like this one. This is a map of landforms. You can classify it if you are in a peak, if you are in a valley, if you are in a slope, if the slope is very intensive, or if the slope is just the upper part of the slope, the lower part of the slope. So there are a lot of different indexes. And from here you can see this is an extract from Google Earth Ancient where you can directly download these indexes. The landform, the chili, which give you some idea of evapotranspiration because it also looks at where the depending on the angle that the slope is facing. If you will get more sun or less sun and you can use to account for evapotranspirations and topographic diversity index that could be related to solar ocean. And there are a lot of different possibilities, index like this that you can get from Google Earth Ancient, but you can also use some tools in GIS. You have this very nice tool from GRAS, which call slope and aspect that can give you also profile curva tool and transgencial curva tools and different derivatives of the slopes. And also SAGA has another model that is called slope aspect and curva tool and you can choose from many different. These are the papers that describe different type of indexes that you can use when you have a DM to make maps for different variables and different use if you are looking at erosion or different things. And here you can just put if you put the slope just to show you one more thing. So here are the different. These ones that I showed you before the slope aspect and curva tool. So these are from different software GRAS and SAGA, but they are already integrated all into GIS. So if you have a DM, you can just come here put your DM. And then you can choose which of these different methodologies you want to use and which index you want to calculate. So just to show you a quick overview, there are a lot of different tools. Ready and very easy to use with a DM to delineate basing, to delineate streams and to delineate or to calculate different indicators for digital elevation mapping. Okay. I will stop here. So there is time for questions. If there is any question. It was quite fast. Very little time to show a lot of things. Okay. Thank you Ingrid and Cesar. Thank you very much. And most of the questions. I think most of us has a question. I have a question. I'd like to thank Cesar and Ingrid indeed for their very nice presentations, especially about about the presentation on raster data. It was quick. So I wish we have more detailed presentation on raster data. That was, that was the piece of information that I want to share. The resolution of five meters, 30 meters and 90 meters in relation to EM. And we'll look at their overlapping with the image, especially image data from 90 and 30 or not overlapping with the actual object, actual imagery, but five meters, five meters is better. But there are still significant mistakes in the five meters, but the mistakes might be occurring because of the development of the DM. There might be a maze. Corn, for example, in the land. So the image only shows the top of the maze. That is why the mistake occurs. Or if there are lots of rocks in a mountain. So the image cannot go through under the rock. That is why some mistakes might occur. Especially for the use of five meters. Do you have any suggestions in mind that that you can that you can give us so that we can make five meter resolution better than the DM better. And you also showed the stream in five meter resolution. So some stream, some segments of the stream in the, in the crop lands, for example, this just cannot be the truth. So there has to be a mistake. So do you have any analysis suggestion in your mind for us to, to compensate for these mistakes to correct those mistakes in five meters. Thank you. Okay. Good. Yeah, I, one of the things I also here I wanted to show you here I found my profile tool. And so here you can basically let me just show you something. So this is the slope. Okay. So here you can just put a DM and you will get this profile. So it's like a slice of an area. This is nice because you can explore the different between the different DM. Let me put the five meters here. And we can, we can chat about it. Layer, because I have increased the resolution. Then I cannot see anything in my screen. Let me see here. I can put this back here. Okay. I think I made a mistake. Okay. I wanted to show you a better comparison with the two different DMs. I've been exploring this a little bit. What, what do you have here is that perhaps now I can. No, I can. It's true. If you, if you check this DM, you can see there are a lot of issues. Sometimes there are some errors in the data like here. And this when you see this in the, in the image below, this corresponds to some trees. And also you can see here some scales here. So when, when you, when you check the five meter DM. And when you make a zoom, you see that there are like shams. So you have a flat area and then go down a flat area and then go down. And the model should be something like the black line. So something is moved. And this is, yeah, because of the, of the origin of the data. Normally when you do a stereoscopy or when you use images from different with different view that come from satellite or drones. You need to do some processing in order to remove the trees and to remove the things. The thing you can do here with, with the, I mean, there are works you can do if you have the original data, perhaps process it in a different way. So you don't have this, this sort of, of things here that they look like a terracing. There are some ways to remove in trees, but always that you remove these trees, you have to, you produce some a bit of artifacts. One of the methodology that I found one that worked good for. There was this one, there was this region with the pools. Well that one actually, this is a mistake that one. How we can really remove this mistake? How can we correct it? That is the question. I think that these are the electrical masts, electrical poles. How can we, how can we correct this mistake? This is a mistake. Yeah, this you can probably mask, make a mask and make an interpolation. I think you should try, you can try something like that. It is not creating a big problem, but then creating slope or being might come across important mistakes. But there's a local, some localized mistake, but sometimes they might encounter many mistakes at once. As you can see here, these are trees which are a mistake. If you cannot remove them, then there'll be mistakes in the slopes that we generate. In order to correct those mistakes, do you have any method in mind? They're not creating a big problem for the time being, but they may create a problem in the future. Any suggestions in your mind that you can make to us? There's not a well or something, there's not a pet or something in here. This is a mistake, that one also is a mistake. Yes. Yeah, as you can see, this top of mistake is type of these are holes. I haven't tested, but there is a tool here that you can use. It's called a pit removal or filling gaps. It's a way of making sure that the DEM doesn't have any of these holes. This one is a kind of a filter that produces a depression less elevation layer. So if you model hydrology here, once the water gets into this hole, it will not be able to get out. So what this tool does is supply a filter and try to fill these holes with data. So it will probably solve some of the mistakes in the DEM. So some of the mistakes maybe are solvable with this type of filter. Well, I think it solves the small problems, but it may not solve the big problems, but still says I thank you very much for this nice explanation. Okay, there is also another way that you can do is you can put your DEM into a team format. So you can make a transform this DEM into a mesh. This is a vector model, the triangulator irregular network, you can put it into that and then you can convert it into raster again. So you will basically reduce the, we tried it, we tried it and it is not creating any solution, unfortunately not. And you have the original data that created this DEM. So this DEM comes from a stereoscopy images or is it like, what is the original data? We have this 5 meter DEM for Ayash, let's say, and this is the problem that we generally see in this. And in our land studies, in 30 meters DEM or 10 meters DEM that they create using a machinery come with mistakes. If you do not do manual correction, generally you see such mistakes they say, they say in the digital models as well. Well, you know, Turkish soil is quite rugged, full of slopes and rugged terrain. That is why the maps really come with lots of mistakes, generally large mistakes, unfortunately, and we don't know how to compensate for that. Yeah, it's complicated, but if you have the original data that originated this DEM, this DEM was created using, I don't know, by the look of it, it was created using stereoscopy images. For example, you have some trees, it can be overlooked for the time being, but if the trees are so much, so many, so intensive, then you cannot overlook it because if the trees are so many in the agricultural land, then what do we have to do? We have to really make lots of efforts in order to eliminate them. Yes. Yes. No, I think you have these sort of things, the trees, then there are these gaps here and then there are these contour lines here that when you draw a line, you can see here that this also pattern. I think the previous one where the power plant transmission lines, power plant transmission masks or something, so it is creating lots of problems. They are called high-water transmission lines and I think that's what we see. Okay. These are high-water transmission lines of the power plants, energy power plants. They are not holes actually, they are quite diverse, they are elevated things, they are the electricity and masks. Yeah, one thing you can always do is to do a pit, this fill gap in order to fill some gaps and then you can use another filter to try to remove the error, but that will change the DM resolution. You will be passing from five meters, for example, if you go to 10 meters or 15 meters, you can remodel the DM at a higher resolution. In this type of remodeling, perhaps you can get rid of a lot of mistakes, but you will also lose a lot of resolution because instead of five meters, you will have 15 meters. So it's kind of a trade-off, but if you see when you see the water lines, in many places the DM is quite good, it's really capturing the water and everything. Yeah, if you want, I can try a little bit, I will try in a little bit of place. You know, there is no longer some solution and I will... He would be more than glad if you can try it sometime, try to solve this mistake. But so you only have the DM, you don't have the data that originated the DM. Just a model, no, not the original data, no. Because with the original data, you probably can solve it more easily. Of course, of course. But if you don't have the original data and the model, you only can fix some things you can fix. But normally when you fix something, you break another thing. We have to be careful not to break anything. Okay, but I will try a little bit. Yeah, thank you. Thank you. Thank you, thank you. Thank you, Mustafa. Another question from the floor? No, I think not. Okay, in the absence of questions, I'd like to declare the session closed. Mrs. Sarah, would you like to say anything to wrap up the session, to close the session? Thank you very much, no, just thanks for everyone's participation. Okay then, thank you indeed, Ingrid and Cesar. Thank you for your nice presentations. And thank you all for the participation and contribution. And I'd like to thank our interpreters, Deniz and Kıyal, for their interpretation. And if you have any questions later for Cesar or Ingrid, you can always contact us. And we can get to your answers later. See you in the third webinar. Aylin, I'm sorry, are you going to have access to video recordings of today's webinar? Who are we going to approach for the video? My colleagues have already recorded the webinar, both in Turkish and English, and we will be sharing the link with you. Thank you very much for everything, for all the organization. Thank you, see you later, bye. Thank you, thank you very much, see you in the next webinar. Thank you for your time, bye-bye. Thank you Deniz and Kıyal. Thank you.