 This is Dr. Simha Chillam, working as an assistant professor at NIRDPR, National Institute of Rural Development and Panchayatiras, NIRC Center, located here on Linga Hoti, adjacent to this particular center. And here today we will be discussing there are four units under course three on special analysis and applications in geoinformatics. In these four units we have first unit as geo-processing functions and tools which can be seen as a unit and the four units are very important for the informatics as it's analytical tools. The one is the map making, data generation, formulation, then editing. After that finally the data, special data which through analysis only it will be utilized in various applications in the informatics. Like many applications maybe you plan for infrastructure, you may plan for natural resource management, you plan for various things but the application, the analysis of special tools are very important. Different analytical methods, analysis, procedures we have in special analysis. So let us see under this geo-processing functions which we have and tools which we have under this unit tree. It's under unit tree, geo-processing functions and tools. As I said there are many functions and tools we have under this geo-processing which is very very important one. Let us see the functions and tools which we have under this geoinformatics. The first and foremost function is vector overlay analysis. I think by this term you are all aware what is the vector, what is the raster. The vector where we have point line polygon, all your geographical data, spatial data will be demarcated. The entities geographical features entities will be demarcated using point line polygon using x y coordinates through this vector format. When you come to the vector overlay it's like a geometry which we have point line polygon and their associated attributes will be overlaid operations create a new geometry and a new output geospatial data set. Almost it's a common overlay or union or intersection. These three are looking different but it's almost same. Like one upon another, suppose you have the road layer then you have the building layer. We call layer in geospatial tools you know. One upon another if you overlay it put it as a map will form its overlay. But when you overlay it one upon another you can also create this combined all this different thematic data into a common or single data set or single map form. This vector overlay analysis which we have basically it's in a point on polygon. Overlaid when the overlay happened in the vector. Point on line, point on polygon, line on polygon, polygon on polygon. But never happen the analysis like polygon on point, line on on point. Point is a small entity which have single coordinate. One X and one Y. If you see this is the point, this is the line, this is the polygon. For example you can overlay point on polygon, point on line, point on line on polygon, line on line, point on point. But polygon cannot be on point, polygon cannot be on line. So that your things will not be visible if you overlay in diverse mode. That is what this slide is indicating. When you go for vector, vector overlay point on line, polygon on polygon, line on polygon. You can see here how the overlay technique used to happen. Point, line, polygon. So, I think in the Mrotrick frequency in the picture point in polygon overlay. So all points are overlaid on polygon map and hence point polygon in the new data layer is a new attribute of polygon for each point. Why? Because point is a small entity which have single X, Y. It will be on overlaid on polygon. The attributes will be joined together into the polygon feature which is the large one. You can see here how the overlay is to happen. Line on polygon, polygon on polygon again. You see this is the polygon, this is the polygon. When you overlay, use the overlay technique, polygon and polygon. If you see the attributes also, it comes as a polygon feature only. So this way you have the overlay techniques. Three entities like point, line, polygon, how overlay technique can be done as a analysis. Then second one is raster analysis. The raster analysis is little different than your vector analysis. Your vector analysis directly geographical features a point line polygon will be overlaid one upon another. But whereas raster analysis is overlay analysis different, it is a pixel based one. If you see here the raster with more than two layers is easier than overlay of vector data because it does not include any topological operations. And then it is also local operations like based on the value of the pixel, it will be overlaid. For example, we have the land use line cover map, different times it is raster data. So wherever the same pixel value is enabled, here cropla and here cropla that will be mixed together in the raster format. Let us see. Then we have another tool for the spatial analysis is spatial buffering. I think this buffer we have already discussed earlier one. Spatial buffer means the area of extent if the point is there and you can make it two kilometers from this point which I am going to establish. What are all other features we have will be known through this buffer tool. If I am going to start one ATM over here, is there any ATM centers within two kilometer radius from this point where I am planning that will be known through this buffer tool. So along with this point not only point this buffer can be done line also. If you have the line drainage canal, new drainage canal you are giving. So what is the extent of area will cover within 500 meters. So how much land cover, waste land covers where you can convert into agricultural land. How much fellow you have where you convert into agricultural land while providing this drainage system. For this you can see the buffer analysis. The many cases this buffer analysis is very important because when you plan for any infrastructure facility or other facilities right amenities in the villages this buffer function is very very essential to run this. Knowing what are all available knowing what are all not available knowing where it is how much distance and then will be knowing only accessibility through this buffer function. The accessibility of the facilities which you have geographically. For example, I am putting here one drinking water scheme. So how much for it is from the settlements, the hamlets. Is it accessible to the villages to get the water if as how far it is. If I am putting ungoverned center how far it is. Is it accessible which I am proposing the location is suitable through this buffer tool one can run the same. You can see in the picture which we have given point line polygon all these three things we can do the buffer as a special analysis right which is very important friends. In fact, buffer tool along with other union or you have intersection but buffer is very important. In many cases not only for planning and also to monitor what are all available with the new geographical area will be known with this buffer tool only right. And then we have another tool that is union and intersection which are important again. You can see as picture is indicating the union is an analytical process in which the features from two or more map layers that combine into a single composite layer right. You can see picture there are two different thematic layers right different thematic maybe fellow land and agricultural land different maps being done or only agricultural land and water resources. When you have two different layers to the adjacent area I want to make it single for example. Fellow agricultural land I want to show as a single map then we use union and the final output will be like this two polygon combined together right combined together all the adjacent with the adjacent place as a combined feature it is called union and you will also having all attributes together in that particular new map which you have and also we have intersection. Intersection means the one geographical data map will be there thematic data another thematic data is there both where it is matching that should be that will be separated you can see this is the intersection the red which you are seeing right for example we have the drainage canal right. So, my drainage canal is covering in my area only this much portion where I am getting irrigated agricultural land. So, I want to see how much irrigated land from that X drainage canal in this case we use intersection right the how much land in my geographical area that drainage system is entering the stream is entering where I am getting irrigated facility irrigation facility that you can extract using this intersection option right the one is union second one is intersection okay there are two different tools being given and these two also used for planning or even monitoring also where when what geographically if you want to see the union intersection both can be used. Then we have a special autocorrelation and it is used basically really and special autocorrelation also one of the major tool where GS helps understand the degree in which one object similar then other is nearby object in new geographical area we have a canal so what are all other similar features we have in new geographical area study area that will be known will be demarcated using this special autocorrelation the similar feature which are all adjacent area is available that can be taken from this then we have weighted regression this is also another statistical technique you say where you can use the special non-special when the input variable difference from location to location from this formation the weighted regression model you can give the different weightages to the different locations for example we have three different components and the land use land cover right agri-crop land having weight is more fallowland having less right irrigated area having medium such a way you can give the weightages for different analysis purpose in special tools these basically we use for rest analysis where where you go for any I mean planning tool when you go for run this like a drainage or to know the suitable locations we used to give this weighted or weighted regression