 So, the last topic today we are going to discuss will be the sources and nature of geospatial data. Learning objective, here we are going to deal with the spatial and non-spatial data. In the last class, we discussed about the spatial data. Now, here we are going to again discuss about the spatial and non-spatial data structure. To get an idea about digital elevation model, SRTM, leader and other dataset, these are the elevation dataset, global elevation database. Now, to understand the data input and output process and devices, data verification correction stories and conversion data conversion in GIS environment. Now, first data types, the spatial data and the non-spatial data. Very simple. The spatial data will be the features in GIS environment for say point, line, polygons with a x y information. This is the spatial data. Now, any information regarding that feature, any information that means the attribute information which is attached to that particular feature will be your non-spatial data. For instance, we know that this is a point, spatial data because it has a x y coordinate. It will be defined on the basis of x y coordinate. Now, if a name is attached to this particular point, suppose the name Guwahati city, then this is going to be your attribute data, non-spatial data. So, basically two types, spatial data and non-spatial data. Spatial data will give you the information about x y. So, it will be a feature in GIS environment, point, line, polygon and any name, any attribute attached to that particular feature will be your non-spatial data. Now, digital elevation model. Digital elevation model is a digital representation of the arts topography. Basically, here we are going to depict the elevation information for geographic locations. So, here location will be there, x y coordinates will be there and the elevation information will be there, z value will be there. And from these information, we can generate a digital elevation model. So, for any digital elevation model, you must understand that you need to know the location information and the elevation information. If you have these two sets of information, then you will be able to get this digital elevation model. Now, there are two concepts actually, which is attached to the elevation model. One is your digital elevation model under depth, one is your terrain model and one is your surface model. One is DTM and DSM. Now, this terrain model basically represents the bare earth surface, terrain. It will see, that means the ground earth surface. This will be your terrain. Now, the surface model, which actually will represent the surface. That means if there is a, that means if there is a building, building height will be considered. There is a tree, tree height will be considered. So, in a city, there will be a drastic difference between your terrain model and the surface model. So, the contours are basically terrain informations. Isolines connecting the points with equal elevation, same elevation. Contours are, gives us the idea about the terrain, not about the surface. But if you are flying an aeroplane and collecting the altitudinal information, that means from a satellite, if you are collecting the information, you are not going to get the terrain model. Because the height of this building will also be considered, surface model. Please see the difference. Now, methods to obtain the DEM. Obviously, using remote sensing, LiDAR data, light detection and ranging, aerial photogrammetry, flying an aircraft also, we can get the elevation. But in that case, it will be terrain model or surface model, surface model. Now, drone imagery can also be used. Topographical maps, Saudi-India topographical maps, where we can have this, you know, control information, benchmark, triangulation height, spot height, all using all them. All of them, we can create this elevation model. GPS, real-time kinematic GPS means, suppose you are carrying a GPS with external antenna and you are moving. Kinematic. Then for every point, it will collect the altitudes and you will be able to capture it. But the point is, you are using a GPS. Your elevation will be ellipsoidal or geoidal? Ellipsoidal. Ellipsoidal in that case. Theodolite or total station survey, geodetic survey. At the specific location, you are going to collect the altitude information. Ellipsoidal or geoidal? Geoidal. Geoidal. Lokal. Yes. No. DEM data sources, N number of data sources. Like one of the most widely used data sources is your SRTM, Sakal Raza topographic mission. Global DEM data you can get. Zetopo, Globe, Aster, Jassat's Global also 3D world. These are the platforms. These are the particular data from where you can get DEM data with a different resolution. Few of them are 30 meter resolutions and more than that. These are the DEM data sources. Please go through it. Now, input and output devices in GIS. This is very important. You see, the GIS depends on the data. We know the GIS is a decision support system. Now, how efficiently it is going to support your decision is based on how perfect or precise data you have provided. What precise data you have provided. If your data is garbage, you will get garbage. Now, how to input data in GIS environment? There are input devices like satellite images are a good source of data to the GIS. Any maps which is digitized in a GIS environment can provide the data to GIS analysis. Keyboards, manual data entering, pointing devices, mouse, taxpayer, joystick. Joystick is required for 3D modeling. Scanner. You are scanning a specific base map and you are going to convert it into a scanning. The base map will give you a raster data. Then you can convert the raster into vector. Please remember, all analysis in case of GIS regarding the geographic features point line polygon can be performed on vector data only. For continuous analysis, you need a raster data. For discrete analysis, you need a vector data. If you want to know the land use land cover changes, then your analysis will be based on raster. If you want to know the distance, the proximity, connectivity, vector. Because this is going to be a discrete analysis. Outputs. This is as per your wish. You can generate graphs, tables, output maps, thematic maps, any types of maps you can generate. And this you can get a copy of it using the printer, plotter. So, this is going to be output devices in case of the GIS. All these map printing devices. Now GIS data conversion. Two concepts only we have to understand. One is your rasterization. One is your vectorization. Now this rasterization is all about converting the vector data into raster data. That means you have a map in GIS environment. And in that map, the entities are actually map using a vector data. Suppose you have a district. Suppose Assam. Road map of Assam. There will be roads, districts and the administrative boundaries and important places. We know these are the discrete informations. They must be stored in a vector data format. Now using an output device, you are getting a map, road map of Assam, a print out. This is a rasterization. You have converted the vector data into raster data. You get a print of your digital map. Now vectorization will require some effort. Because here you are going to convert the raster data into the vector data. So, first you have to use an input device to scan that particular base map. You have to keep take it into the GIS environment. Then you have to create these features, point, line and polygon. And you have to go for digitization. Using a mouse or joystick, you have to go for entering the data. You have to create both spatial data and the non-spatial data. For instance, you have to create the point first. Then you have to name the point. That this is a place known as a Guwahati Jorhat or something like that. Or then you have to create the boundary. Suppose this is a national boundary, international boundary in case of Assam. And you have to digitize it. You have to convert the raster image into a boundary. That means a line image. And ultimately the districts, they will be created as a polygon. So, it will require some time and effort to convert the raster data into the vector data. So, this is known as a vectorization. So, rasterization as we have understood, that is a very simple exercise. You have to simply take the help of the output device. Take the print out and your vector will be converted into raster. But a raster conversion to vector, vectorization, involves some basic elements. The line thinning, line extraction, topological reconstruction. And there are different methods to convert this particular, any raster data into vector. That means vectorization. You have to see the line thinning. How? You see, your road may be appeared as a very broad line in your raster image. Or it can be broken line also. Pixelated lines can also be possible. That pixelated line, when you are converting into a polyline in GIS environment, it will thin. This is going to be line thinning. Line extraction, there are some gaps. You have to extract it. So, all these exercises you have to perform in case of your vectorization. Now, I am going to stop here. Thank you. Thanks for joining.