 next will be your GIS data types where we are going to discuss about the topology and all learning objective explain the basic concept of raster and vector data describe the overview of team triangulated irregular network illustrate about the topological relationship as I have already mentioned in the previous section now get an idea of the raster and vector data format now raster data raster data as we all know any digital picture is a raster data that means it's a pixelated data so all the pixels it contains a digital information a number 8 bit image, 60, all these right and the particular number which actually contains that information that means if you zoom a particular picture then you will be able to identify these pixels like square pixel cells raster data represents any element on the real world into an array of rectangular cells these array of these rectangular cells are known as pixels this particular data is very useful because it's a simple data structure easy and efficient overlaying you can overlay different raster files one over another in GIS environment and it's a high special variability is efficiently represented suppose you have a picture of this is also we do in our real life suppose the picture of Guwahati in 1901 if someone has taken or suppose the picture of Guwahati in 1947 15 august 1947 a picture of Guwahati pan bazar today you can compare the special variability so it is very efficient way visually we can understand ok there is a difference some development has occurred ok so this is very easy it enables the raster data set now next one is a vector data now this vector data is concept consist of discrete geometric locations discrete geometric locations now these vectors are the graphical objects that have you know geometric primitive such as point lines and polygons will be our vector data ok as because this vector data consist of the discrete geometric locations so these are going to have a well defined geometry which doesn't exist in case of your raster data set because it is an array of picture cells ok now this vector data is very useful why because they have a small file size individual identity like points will be kept as a point vector data lines will be kept as a line vector data area will be kept as an area vector data ok so this vector data are the you know feature class as we have already discussed feature class under a geodata base or there are different formats of this vector data which I am going to discuss now this here you can make the distinction between the raster data and vector data now same points here are represented as picture cells ok lines in vector data picture cells now this is a comparison between the raster data and the vector data ok so structure, grip in case of raster data vector data points line and polygons specific geometry representation each cell stores a single value or attribute number ok and geometric shapes with associated attributes geometric shapes with associated attributes then your topology encodes special relationship I am going to you know discuss it in detail analysis raster data suited for the continuous analysis vector data suitable for the discrete analysis and there are like for our satellite images any satellite images Google Earth these are raster data ok or the GIS environment the data we are going to create the geometric roads lines points areas will be your vector data set there is another difference between vector and raster ok we will continue later we will deal with it this is a triangulated irregular network this is also belong to a category of vector data basically this thin data represents the elevation ok and it enables us to visualize the elevation so can you see we can visualize the elevation here ok so this thin is a three dimensional data represent representation model in the GIS environment it is a three dimensional data where we will have x, y and z information ok so each node in the thin data each node in the thin data will have the ultra-dimensional information ok and if we visualize this thin surface in GIS environment the particular points the nodes will be elevated with respect to its elevation elevation information it will be elevated then you will be able to get the 3D field in the GIS environment so thin data actually enables us to do the three dimensional analysis triangulated irregular network ok now here comes the topographical relationship the spatial relationship now this topology in GIS refers to the spatial relationship connectivity, contiguity, proximity and all so to understand the topology basically focus on understanding and representing how different spatial elements are related to each other in terms of its adjacency, connectivity, containment or other geometry relationship for instance for instance before drawing a line connecting two points ok so your topology will be that this particular line has to touch the point A and B so this is the relationship because this particular line we know the indicates the distance between point A and B you must have to join these two points to get the distance or for instance suppose you are creating a polygon data set for the districts of Assam now in the polygon data set for the districts of Assam each of these adjacent polygons they must you know overlay with each other there cannot be any empty spaces right two polygons suppose you have drawn ok if there is any gap between the two polygons then it will create the third polygon suppose the two districts suppose Nogao and Morigao districts the boundaries are you know has to be common of these two polygons ok the boundaries shared by between Nogao and Morigao or Nogao and Gulaghav now suppose while creating the polygon if you have you could not achieve the boundary overlay between Nogao and Gulaghav district then there will be gaps now these gaps in the polygon environment will be treated as another polygon now what about it it is going to be new NPD which does not exist in the real world ok so here you can define the relationship that there cannot be any gap in between two adjacent polygons this is the topological relationship ok or suppose you know that two parallel roads you are drawing ok now these two parallel roads you can define because you know that in real world they do not overlap ok so in the GIS environment you can define the topology prior to creation of these two polylines you can define that they must not overlap ok then whenever you try to overlap these two you know lines then their error will be solved error will be indicated ok so or suppose you are drawing some iso lines if you are aware of the iso lines iso lines connect the points with the equal information equal data suppose for instance suppose controls controls are the iso lines connecting points with same elevation now we know the iso lines cannot intersect each other so this is a topological relationship in GIS environment we can define this topological relationship while creating the different features ok this is the you know very powerful actually relationship tool which is present in the GIS environment now topological relationships there are mainly three types of topological relationship connectivity area definition and contiguity ok now I am going to deal them one by one like topological rules in case of polygon can you see I have just listed few of these topological rules like polygon must not overlap ok must not have any gas can you see as I have already cited these examples ok for line line must not overlap I have already cited one example ok must not intersect for iso lines I have already cited that example so these are a topological relationship you can define while creating the feature data set feature classes ok point point must be covered by boundary of suppose Guwahati must be within boundary of come room metro district ok if it is false outside then the error will be shown so these are the topological relationship the connectivity contiguity proximity ok these relations can be defined using the topology in GIS environment ok now these are the common raster and vector data formats for raster data like JPG ok widely known raster data format in our mobile phones or cameras we are capturing the images in JPG format PNG ok point network graphics or graphic intersense format tag image file format or IMG format in case of your satellite images IMG format ok vector data SHP commonly used in the RGS platform ok for safe files ok KML keyhole markup language particularly this is used in a google earth analysis and all zpx particularly used for capturing the GPS data gnss data ok gpx ok tiger or geosation these are the popular vector data format ok which we are going to use so these safe files in a within a geodata base is a feature class ok this safe file within a geodata base is a feature class and combination of feature class will be your feature data set now here I would like to show you a basic difference between the raster data and the vector data the origin is different actually in case of your raster and vector data you see as we have already defined the vector raster data what is this array array right so in case of your array array of pixels if I have to refer to this particular pixel ok then suppose it is a b c d 1 2 3 4 now this particular pixel will be referred as a1 ok and the subsequent pixels will be identified so here the origin is actually left top see for raster data for vector data x y coordinate suppose this is a point we know the line will be the combination of 3 points 3 suppose this is a line feature so this is a line feature point feature x y coordinate ok now here the origin will be left bottom see basic difference so suppose this particular point will be given as x 1 y 1 ok this will be given as x 2 y 2 so here we are going to start at the bottom left top right basic difference between raster data and the vector data