[MUSIC] Hello again and welcome back. In this lecture I'm going to show you how to use the Point Density tool. We won't use any particularly fancy metrics for it but it's a way to transform a discrete set of locations into a continuous field. We've done this before with things like the Euclidean distance where we have the distance to features. But the Point Density tool gives us a different metric. It can tail off further so there might not be really much of a value out here because there's no real point density here or in here. But we can get a sense for just how much information is in these areas where information can be a couple different things. So to start, let's just take a quick look at it. So once again we're in spatial analyst and in the density tool set, and the tool we're going to use at point density. And I specify my Input features. And, I can optionally give a population field. And we're going to run it with an without that. And for now, let's do NONE. And the population field is a way to give the points a different value than they have on their own. So if we went without it, it's going to do density of the actual points in each location where each point counts as one. But if we went with the population field that field can contain values and it's going to then treat that point as, instead of one, it's going to treat it as whatever number it is. For the density and since density is a value over an area in this case it can significantly increase the value and we can leave the area the same to compare it. So I'm going to call this layer point density, regular and I live output cell size at the default. It calculates it by using the extent and divided by 250. And let’s have it do a circle with default radius as well. So it's a Map Units Cell, it's gives up 80 meter radius around each point is or around each cell is what it searching for the density and let's run it. Okay, and it's pretty quick and if I turn off the points for a sec, we can see sort of pattern here. So if we look at each cell, it's clearly searching the given area for more points. And we can see that there is with higher numbers of points or kind of in between a cluster of points have higher values even, I think make sense. I don't know if there’s a lot to explain here, we got this little bubbles where we have a few points and lighter colors. We’re having less density and the bottom class that it gave us means that this area doesn't really show up in any darker color than the lightest. Well we can tweak the perimeters a bit here, so what if I run it again, all right let's start with the other one. So I'm going to go results in current session and I'll double click on the tool there, and now let's run it with population. And in a population field I have some just kind of made up data for customer traffic to each of these locations. So maybe they're all businesses. And I want to see where the highest density of customers is. So the customer traffic field is my value field here for the density. And I’m going to leave everything else the same and click OK. And not massively different, but we get different results still. And let's turn off the points again and we can kind of look back and forth. And we see some changes, it seems to consolidate a little bit. And that might just be because the data, but we still get a different result here. And another thing that we can see is that here the highest value is 857 or the highest value here is 270,000. So what it's doing is for each cell it's summing the values of the neighboring population field before it does the density calculation. So if our customer data is in the hundreds in a lot of these cases for each cell that's looking in an 80 meter radius. It's then summing the populations fields here, it's going to get a large value for per square kilometer because it searches within 80 meters. And then in the math it then divides that as if it's representing a square kilometer and we get this for value here of 270,000 costumer traffic units per square kilometer. Now let's run this one more time in tweak the settings just once more. And we can still use the population field, but now to 150 and just kind a see how that goes. And just like when we were working with local statistics, we have a few different shapes we can search with. I'm going to leave it as a circle, but we can use some of the other units there, or some of the other kind of search area types. And I'll click OK again. And now this looks a little different and in fact a little smoother to me. It looks maybe more like, it somehow seems more appropriate to the data to have this kind of larger cluster in here. Because that seems to be what's going on this is the most dense area. And then as we get further out it kind of tails off in a more even way instead of having these striations in it. So if we change the search area it's then getting the data from much further around it before it then does the division by area. Now this isn't truly a hotspot analysis or anything like that. We could do that in the spatial statistics toolbox down here with the mapping clusters. But it gives us a sense for where things are going on in a raster format and once again giving us a way to transform vector data to raster. In a way that's kind of meaningful that we can use in some other work flow. So we can then take this into raster calculator or any other number after tools for processing this density measure here. Okay, and I'll keep this short. That's really all I have to show you about this tool right now. I just want to make sure you know about it, and know about this density tool set as well. This is it for a special analyst at this point, and I encourage you to take a look through the tool box again. Now that you're more experienced with GIS and see all the different tools that are here. May be when you've looked at but, before you didn't have as big of an understanding of all the geo spacial concepts. And you might have actually have some different ideas looking through it again. I tend to kind of look through whole tool box every handful of months because I think that each set of tools here can kind of help once you get each different concept in GIS. A lot of the looks at spatial analyst in this course have been focused much more on just kind of getting you to know a concept as opposed to using it in depth. And that's because there's so much there but I want to make sure you have a sense for the wide variety of capabilities, since you're all coming from different backgrounds. No one tool or workflow is going to completely encapsulate everything. I've tried to show workflows, but I've also tried to show you different tools that might give you ideas for workflows of your own. Okay, so that's it for this lecture. In this lecture we looked at points and city with a few different sets of parameters using the population field and just using the regular format of having each point count as one. And then we got rasters back that summed the values over the total area that it was searching in. It’s a great way to turn your vector data into a raster and preserve some of the input data for future processing and transform it to a new format that has new meaning as well. Okay, see you next time.