Introduction to ArcGIS Spatial AnalystEsri staff discuss and demonstrate the analytic functionality and main components of the ArcGISSpatial Analyst extension.

http://video.esri.com/watch/1953/introduction-to-arcgis-spatial-analyst

Video Transcription00:01 My name's Steve Kopp, this is Liz Graham, and we work on the Spatial Analyst team andtoday we're going to...

00:06 ...talk about an introduction to Spatial Analyst.

00:10 Just curious, how many of you guys never used Spatial Analyst but want to?

00:17 Great, so like almost half.

00:20 How many of you use Spatial Analyst a lot but just specific pieces of it?

00:24 Like, yeah.

00:26 And ninjas? Ninjas? People who know as much as we do. Alright. Or more.

00:37 Not to imply that we are ninjas; we're definitely not.

00:40 So, we'll leave you guys to the ninja status.

00:45 Okay. So, for those of you don't use Spatial Analyst yet, we'll give you a little bit of anoverview here...

00:51 ...at the beginning and we're going to talk a little bit about sort of an overview of SpatialAnalyst, and then...

01:04 So, we're not going to have a lot of time to go into depth on very many of those topics, andthere's going to be...

01:08 ...a few times I'm going to refer to other workshops that are available on some of those topics.

01:13 So, for some of the areas, it will talk about in these slides, there's entire workshops dedicatedto those...

01:20 ...and we can point you to those, as well.

01:23 There's also some demo theaters downstairs dedicated to some of these topics, as well.

01:29 So first off, what is Spatial Analyst?

01:31 Spatial Analyst is integrated raster and vector spatial analysis tools.

01:37 And, it seems kind of obvious to include that slide and that bullet point, but I really want to

reinforce this point.

01:44 It's raster and vector.

01:45 Spatial Analyst is not really just about raster analysis.

01:49 So, we've actually gone to a fair bit of effort to allow what would have been traditional rasterGIS capabilities...

01:55 ...spend most of our time going through the variety of analytic capabilities available in SpatialAnalyst.

01:56 ...to accept feature data as input and to create feature data as output and to do thatintelligently.

02:05 So, it is an integrated system.

02:07 And it's an extension product, as you know, that adds functionality to Desktop, where most ofyou use it...

02:13 ...as well as Engine and Server.

02:17 Now, the graphic in the bottom right is actually Spatial Analyst running in a web page.

02:23 This is actually a solar radiation calculation from a website from the City of Seattle.

02:29 There were a few demos that you saw on Monday that were using Spatial Analyst and othergeoprocessing...

02:34 ...functionality through web services.

02:37 Yes, you can serve analysis capabilities. Okay.

02:41 Not only can you serve them, but if you have geoprocessing functionality that's served, youcan...

02:46 ...consume that directly as a tool in Desktop.

02:49 That's not really what today's about; if you want to know more about that, I can point you...

02:52 ...to a workshop specific to that topic.

02:55 Eight-thirty tomorrow morning.

02:59 So, some key features of Spatial Analyst.

03:02 There's about 170 geoprocessing tools for the Spatial Analyst extension that work on all the...

03:08 ...raster formats that you can use in ArcGIS.

03:10 So, if you can read a raster dataset with ArcGIS, you can use it as input to a Spatial Analystfunction.

03:18 Similarly, it works on all vector formats, as well.

03:22 Now, we include these points because this wasn't always true, and this isn't true in all GISsoftware.

03:28 And also because the way that we do that changed a few years ago.

03:32 We used to make scratch files in the background, and we don't anymore.

03:36 So the reason that that's important for those of you who have been using it for a while is therewere some...

03:40 ...limitations for those scratch file formats, and when we got rid of that, we changed thearchitecture...

03:46 ...how we read and write data through these analytic functions, it actually made it faster andit reduced...

03:52 ...some of the problems that you were running into that you maybe didn't quite understand.

04:00 Spatial Analyst also includes a calculator with map algebra syntax, and I point that outbecause we think...

04:05 ...that's a pretty important key feature of doing spatial analysis.

04:10 How many map algebra people do we have in the room today?

04:14 Not very many here? Okay.

04:15 We'll talk a little bit about map algebra; I won't dwell on it too much, though.

04:18 And finally, Spatial Analyst has a really great developer experience, and there is a workshopdedicated to raster analysis...

04:25 ...with Python that specifically covers that, and a lot of that is about working with SpatialAnalyst through Python.

04:34 So what does Spatial Analyst look like in the desktop?

04:36 So, Spatial Analyst is a toolbox in the ArcToolbox window with a set of functional categories.

04:45 We can also access this functionality from the geoprocessing pull-down menu in version 10...

04:51 ...where I can also lock the toolbox.

04:53 I can use these tools in ModelBuilder, which Liz will show us in a few minutes, and also usethem in the Python window.

05:02 What about Spatial Analyst toolbar? Anybody curious about that?

05:06 9.x people who haven't moved to 10 yet, there's a little surprise there for you if you used touse the toolbar.

05:11 We got rid of the Spatial Analyst toolbar in many of the ways that you think of it.

05:15 It's still there, but it only has a few tools on it now.

05:19 That pull-down menu that was on the Spatial Analyst toolbar has gone away.

05:24 The reason that that went away is it was causing a lot of confusion and it was basicallyduplicate functionality...

05:29 ...the things you could do in the toolbox and things you can do from the pull-down menu.

05:33 They didn't share the same environment, they behaved a little bit differently, and whathappened was...

05:39 ...when we made it possible to add geoprocessing tools to a dialog, to a pull-down menuusing...

05:47 ...standard Windows customize, now you can make your own Spatial Analyst toolbar.

05:52 So, I've got a little sample toolbar that I made here; I do a lot of hydrology work, and I work...

05:57 ...with the hydro tools in Spatial Analyst a lot.

05:59 So here I created a little toolbar, it has a hydrology pull-down, and I put some of thecommonly used tools on there.

06:05 Sink, fill, flow direction, watershed, et cetera, as well as some custom tools...

06:10 ...a Python tool for calculating soil wetness, ModelBuilder models for doing condition numbers,things like this.

06:18 So, I did all of this with no code; it's just standard Windows customize, drag-and-drop littlethings. It's really easy.

06:26 The other thing that we added in version 10 was the ability to search; we improved the searchcapabilities...

06:32 ...to be able to search for tools.

06:35 We did a lot of work on the names and words that we index to go with those to make it easierfor you to find tools...

06:43 ...because the toolbox I showed you, you know, 170-plus tools just for Spatial Analyst...

06:48 ...the toolbox list has become too big to navigate that tree control.

06:52 There's like 700-and-something tools in that list.

06:55 So, using the search window is a much quicker way to do that now.

06:59 We tried to put a lot of words in there that you might think of, you know, like, if you wanted tosearch for "clip" but...

07:04 ...you couldn't think of "clip," you can put in, like, "cookie cutter," and it'll actually find theClip tool for you, okay?

07:11 And, actually, if you search for tools and you're not finding the thing you're looking for...

07:15 ...and you have recommendations on new keywords we could add for things, just let us know,you know...

07:21 ...through tech support or through the forums or whatever, please add these keywords to thisthing...

07:25 ...'cause this is what people in my industry always call this tool.

07:31 Spatial Analyst includes a few additional pieces for the geoprocessing environment...

07:38 ...and these are things we want to set up at the beginning of a project before we start.

07:42 Things like cell-size extent, map projection, and possibly a mask.

07:48 Cell size is probably the most important one for Spatial Analyst users because it actuallycontrols the results...

07:55 ...of your analysis and we default the cell size to the largest of the inputs because we don'twant to fabricate data.

08:03 What I mean by that is, in the example here, if I have two datasets, a 25-meter resolution and10-meter resolution...

08:09 ...dataset and I want to create an output from that, the default behavior is it's going to createa 25-meter resolution output.

08:17 The reason for that is I don't actually have enough information in my 25-meter resolutioninput...

08:24 ...to create a 10-meter resolution output.

08:27 I can do it; I can change that environment setting to be the minimum of the inputs, and theremight be reasons why...

08:33 ...you want to do that.

08:34 I just caution you that when you change the default for the output cell size, do it for a reasonand understand what that is.

08:44 It's usually going to be best to set it to an explicit number or same as some other dataset...

08:49 ...that you want all the pieces of your project to conform to.

08:53 The same with the extent.

08:55 You want to set a processing extent to constrain the extent to a particular area.

09:00 The extent for Spatial Analyst also includes another parameter called the snap raster, andwhat the snap raster...

09:06 ...does, it allows you to co-register the origin of the grid cells to be the same.

09:13 The reason that that's important and you want to check the extent, the cell size, and the snapraster...

09:18 ...is because you want all the datasets that you create to be perfectly co-registered.

09:23 Because if they're not, if they're offset by a quarter of a cell size or if they're different cellsizes...

09:29 ...every time you do an analysis, one of those inputs is going to get resampled to match one ofthe other ones.

09:36 So if you set this at the beginning of your project, you're going to minimize the resamplingthat occurs...

09:41 ...and resampling of raster data is not something that you want to do repeatedly; it willdegrade your data, right?

09:48 So, it's better to leave the data like it is as much as you can.

09:53 There's also a mask option, sort of to constrain your analysis to nonrectangular area, like awatershed or a...

10:01 ...census block or something like that, or a ZIP code.

10:05 And then it's also important to think about and set a map projection.

10:10 I know that most of the data that you find shows up in lat-long and you don't know whatdatum it is...

10:16 ...and you just do it in lat-long, it's fine, right?

10:20 It's really not fine to do your analysis in lat-long very often, okay?

10:24 Most of the time it's not.

10:26 Because a lot of times you're going to do things like measuring distance and measuringareas...

10:30 ...and doing that in lat-long is just not going to work, okay?

10:34 So think about the map projection that you need to use for the type of work that you're doing.

10:39 There have been some changes in things like the buffer tool to use geodesic distances...

10:45 ...so you can actually input points, lines, and polygons in lat-long and get buffers out that areactually...

10:52 ...true-distance buffers, but that's only in the buffer command; that's not throughout thesystem.

10:57 We're not using geodesic distance in area everywhere, so.

11:01 Okay. Moving on.

11:04 So one of the first things you want to do in your analysis is look at your data.

11:08 You want to explore your data; you want to understand your data.

11:11 So, the way that we do that, it starts with things like Identify, you know.

11:15 Using the Identify tool and poking around and looking at my data.

11:19 Changing the display of the data; using different stretches on my data.

11:23 I can also do selections on the data, and the way that we do selections on raster data isthrough the attribute table.

11:29 So, an integer raster dataset - a dataset that's integer values, not floating point values...

11:38 Now, you don't have to have additional fields in that, connected to that to be able to do...

11:43 ...selections on it; you can search on the values.

11:46 So if I have a dataset that was, say, land cover, and there was a land cover type coded...

11:54 ...with the value of 2, and that was Forest.

11:57 If I wanted to, you know, highlight all of the, or select all of the forested areas, I could click...

12:02 ...on that in the attribute table, and it would select all the cells of value 2, or the forest cells.

12:08 And then if I wanted to run an analysis, I could actually use only those selected cells if Iwanted to.

12:13 So that selection that I do on the attribute table is actually honored during the analysis...

12:18 ...just like if you did a selection on features and used that as input to your analysis.

12:24 We have an interactive tool for doing histograms of the data distribution values.

12:28 That's histograms of the entire dataset or of selected areas you can select through graphic.

12:35 And also a zonal histogram tool, which I'll talk about a little more, which is in a little while...

12:40 ...which allows us to look at the distribution of values within zones.

12:46 So with that, I'll switch over to Liz, and she'll show us a little bit of this.

12:52 Thanks, Steve.

12:54 Throughout my demonstrations today I'm going to be walking us through a suitabilityanalysis...

12:58 ...to find the best location for a new ski hill.

13:01 But before I get started with that, I'd like to show you around the application that Steve wasjust talking about.

13:06 So my data is in the Lake Tahoe area.

13:08 I have some elevation data, some power lines, and some roads.

13:12 The triangles represent peaks in the area.

13:15 But first, let's enable the Spatial Analyst extension.

13:19 To do that, you go to Customize > Extensions and check on Spatial Analyst.

13:23 After doing this, you can access the Spatial Analyst functionality.

13:27 The first thing I'll show you is the toolbar.

13:30 Go to Customize > Toolbar and down to Spatial Analyst.

13:35 As Steve mentioned, there's a drop-down list that has layers.

13:38 I've selected Elevation.

13:40 There's a Create Contours tool and a Create Histogram tool.

13:44 You can see that this is the distribution of values in the elevation layer because that's thelayer that I have selected...

13:49 ...in the drop-down list.

13:51 If on the Drawing tool, I would use this Graphic Circle tool and draw a circle around MiddleMountain...

13:56 ...and then do the histogram, you can see I get just the distribution of values underneath thegraphic.

14:03 So that's a good way to explore your data initially.

14:06 To access the Spatial Analyst tools, you can click this Toolbox button, which opens up thetoolbox...

14:13 ...Spatial Analyst toolbox - made up of several toolsets that contain different functionality.

14:18 But if you're unsure of the tool you're looking for, you can always use the Search tab.

14:22 If you click Tools, you'll limit your search just to tools.

14:25 And here, you can type in the tool name you're looking for...

14:28 ...something that reminds you of the functionality that the tool does that you're looking for.

14:32 Another way to access the Spatial Analyst functionality is through the Python window.

14:37 You can click this button to open up the Python window and type and execute Pythonexpressions that use...

14:43 ...Spatial Analyst functionality, as well.

14:46 Most often, Spatial Analyst tools are written in algebraic format, so the left-hand side isequals the tool...

14:53 ...or the function name or operators and that's the expression.

14:57 We're not going to go into that a lot here today, but there's other workshops on that.

15:02 So now we know how to enable and where to find the functionality, but as Steve pointed out...

15:06 ...before we do any actual analysis, it's important to set environment settings.

15:11 If you go to Geoprocessing > Environments, this is where you can enable your differentenvironment settings.

15:17 Your workspace, your output coordinate, your processing extent - including your snap rasterto limit...

15:23 ...the amount of resampling, and under the Raster Analysis tab is where you can set your cellsize and your mask.

15:29 I've set my cell size to 30; that's the coarsest resolution of any of my inputs for today'sanalysis.

15:36 Now let's go back and search for a tool called Hillshade.

15:41 It comes up there on a drop-down.

15:43 If I cursor down to it and hold Ctrl Enter, the tool's just going to open.

15:47 If I didn't do that, if I just hit Enter, it would just do a search and populate here and then...

15:51 ...I'd have to click and open the tool, so that's just a little shortcut.

15:55 I'm going to select the input raster elevation.

15:58 I'll supply a useful output name, such as Hillshade Oak.

16:05 I'm going to leave the azimuth and the altitude of the sun as a default values.

16:11 The z factor can remain 1 because all of my units, my x,y units and my z units, are all in thesame measurement.

16:18 They're all meters; I don't need to convert anything.

16:21 This just tells me the dataset exists on my computer and I'm going to overwrite it and I'mokay with that.

16:29 You can see what's added to the display here is a really nice illumination of the study area...

16:33 ...but what would make that even a better picture of what's going on is if I drag this hillshaderesult underneath...

16:38 ...the elevation dataset, and then if I add some transparency to the elevation dataset.

16:43 To do that, I'm going to use the Effects toolbar.

16:47 I also access that through the Customize toolbar's expression.

16:51 Again, elevation is chosen in the drop-down list, and this is the transparency.

16:56 I'm going to adjust the transparency on the elevation dataset to about 30.

17:00 Now you get a clear picture of what's going on in the study area, where the ridges are...

17:04 ...and where the other slot areas are within the study area.

17:08 And we'll pick up here after Steve gives us more insight on some functionality.

17:12 Okay. Thanks, Liz.

17:18 So there's a lot of tools in the Spatial Analyst toolbox, like I said, about 170 or so tools.

17:23 These are some of the functional groupings of those tools, and you don't need to read all thesebecause basically...

17:28 ...we're going to go through these, each of these a little bit, one at a time.

17:33 We're going to start with the simplest stuff that there is, the mathematical operators.

17:37 So, we can take two raster datasets and combine them together using sort of traditionalmathematical operators.

17:44 And what we do is combine spatial data with mathematical operators to create new spatialdata.

17:50 So, these are sort of the nouns, sorry, the verbs where the spatial data are the nouns of thelanguage.

17:57 So if we have two datasets we need to add together - we want to do a units conversion...

18:01 ...or something like that, this is the way that we do that.

18:04 And if you look at this, you can understand now, when we talk about the cell size and theextent...

18:09 ...and the snap raster being the same, if you look at this graphic, where I'm trying to add twodatasets together...

18:15 ...you can begin to understand why if they were different cell sizes, or if they offset a littlebit...

18:20 ...I would need to resample one of them to match the other one to create a new output.

18:27 We use these mathematical operators as well to do things like map queries.

18:31 So we have a set of Boolean and logical operators that we can use on our spatial data.

18:37 So in this case, I'm looking for places where the soil is sandy and dry.

18:42 And I just use a Boolean "and" to do that.

18:44 So, dataset and dataset, and it creates an output for me of true and false, or a Boolean output.

18:54 We also have a set of mathematical functions that we can use to create new analyticscapabilities.

19:00 So, traditional arithmetic functions; the example at the bottom is about turning floating pointdata into integer data...

19:07 ...which might be something you need to do - trig functions and exponential functions.

19:12 I might want to make a soil wetness map, where I know that the formula for that is thenatural log of the area...

19:20 ...divided by the tangent of the slope.

19:22 So, I can actually combine these things together in a single expression to make that result.

19:29 The way that I do that is using this language we were referring to called map algebra.

19:35 Now map algebra is a tool in the toolbox, but it allows you to access a lot of otherfunctionality that is...

19:42 ...also available as geoprocessing tools.

19:45 Now, the nice thing about the map algebra is it's very readable; it's a nice sort ofnatural-language way...

19:51 ...to look at spatial analysis functions.

19:55 The example in here, smooth hill equals hillshade, focal statistics, elevation times .3048; doesthat sound like...

20:04 ...it might be anything you might understand what that is?

20:07 What would it mean if I had elevation data and I'm trying to multiple it by a number like 3048?

20:13 Does that ring a bell to anybody?

20:14 That might be a units conversion, yeah?

20:17 Okay. So that's really all I do.

20:19 Elevation dataset, this is my raster dataset, the times sign, and the number I want to multiplyit by.

20:26 Now, just like in any other mathematical expression, I want to do that thing first and...

20:32 ...use the output of that as something else.

20:34 So I put parentheses around that and then run the focal statistics function.

20:39 The focal statistics function's default behavior is to calculate the mean value within a 3-by-3neighborhood.

20:46 So what I'm trying to do is smooth the data a little bit.

20:49 I'm trying to create a dataset I want to use for cartographic effect.

20:53 And then I'm going to create a hillshade of that, which was the tool that Liz just showed.

20:58 So I create an expression with an output named "smooth hill" equals the hillshade of theresult...

21:04 ...of the focal statistics function, which is taking the result of elevation times .3048.

21:10 Okay? Seems pretty simple once you break it down, doesn't it?

21:14 So there are some changes that we made to the map algebra, for those of you who usually useit.

21:18 We changed the map algebra a little bit in version 10 to make it work better with Python...

21:23 ...which is the native scripting language of ArcGIS.

21:26 So now we have a really tight integration between map algebra and Python, which allows uswithin...

21:31 ...the Python language to mix map algebra and all the other geoprocessing tools, as well asto...

21:37 ...import and use other Python libraries with our ArcGIS functionality.

21:47 So moving on sort of in complexity a little bit, we have a set of distance and proximity tools inSpatial Analyst.

21:55 So we can calculate straight-line distance - you know, Euclidian distance from point to point.

22:00 We can calculate the distance; we can calculate the direction of movement; we can allocatespace to a collection...

22:07 ...of points; and we can also do what's called cost weighted distance, or cost allocation wherewe use...

22:14 ...another raster dataset that provides what we should think of as an impedance surface...

22:18 ...or a cost of travel through an area.

22:21 And in both of these cases, we can also do things like shortest path.

22:25 What is the shortest distance between two points, if I'm using this cost distance method?

22:32 So this is an example of some of the outputs that we might create.

22:35 In the center, I've got a little dataset, point A and point B, and I want to find the distancebetween them.

22:42 So I can do a map of straight-line distance, and this looks like buffers, doesn't it?

22:46 Well, it's a little different than doing things like the buffer tool would do.

22:51 What the buffer tools does is allows you to create circles of specific distance away fromfeatures.

22:59 What we do with Spatial Analyst is we actually create a raster dataset where each cell is

coded with the value...

23:07 ...representing the distance to the nearest point.

23:09 So it's actually a continuous distance map.

23:12 And then we can threshold that through the renderer and through reclassify to do otherthings with it.

23:18 But just remember; it's a continuous map where every cell has a different distance...

23:23 ...and it's the distance to the nearest point.

23:27 Another output of these distance functions, as I mentioned, is the direction grid, which isthe...

23:31 ...direction of travel to the nearest point.

23:33 So in this case, this would be a Euclidean direction output.

23:37 We can do an allocation of space, so if I do an allocation - this is sort of like Thiessen polygonsor Voronoi polygons.

23:45 And we can also do a cost-weighted distance, and this is where I'm bringing in an impedancesurface or a cost surface...

23:51 ...another raster dataset whose values are multiplied by the map distance to make a map thatrepresents...

23:58 ...a difficulty of traveling between two places.

24:03 So, if we look back again up at the top, obviously if I was doing Euclidian distance betweentwo points, A and B...

24:09 ...it would be a straight line between them.

24:12 But, maybe for some reason I can't travel through here.

24:15 I want to consider some other things because what I can see in the map is, that's actually...

24:19 ...traveling over the top of a mountain.

24:22 That might not be a place that I can go; maybe the vehicle that I'm traveling in won't gothere...

24:27 ...or maybe I just don't want to walk up that hill.

24:30 So what we can do is use the Spatial Analyst to combine multiple datasets to make a map...

24:35 ...that represents the cost of travel.

24:38 That might be the cost of traveling uphill versus downhill.

24:41 It might be, how difficult is it to travel through this land cover type?

24:45 Is it easier to travel over barren ground or forest or rock or through agricultural fields orthrough urban areas?

24:54 Or, is it a soil type that I can't travel over? Or is it too wet? Or is there a barrier in the way?

25:00 Okay. So I can combine those things together and use those in the cost distance function toweight the result.

25:06 And what I end up with is a path that goes down along the shoreline of the lake, right?

25:13 Now, what if I don't want to know just the path?

25:16 Maybe there's some reason I need to know other options.

25:19 So what we can do is create a corridor of travel between those two points, okay?

25:25 So what we're actually doing here is, from point A, calculating the cost distance to every pointin the dataset...

25:32 ...and then the same thing from point B, the cost distance to every point in the dataset.

25:38 So this is what the cost distance map actually looks like.

25:41 And see, it's not concentric rings or buffers; it looks much different than that.

25:46 Then we combine together those two cost maps, and what we see is, if we don't want to traveldown along the lake...

25:52 ...there's actually an alternate corridor here over the top of the mountain.

25:56 It's higher cost, but for some reason, I might be interested in that.

25:59 Did somebody have a question?

26:01 [Inaudible audience question]

26:20 So the question was, what if I have a vector grid - so you mean like a regularly-spaced set ofpoints...

26:28 ...that I wanted to use in my model.

26:30 So in order to do that in these particular functions, you would actually convert those to araster dataset.

26:38 But if they're already gridded, you wouldn't actually probably do an interpolation; you just uselike the Points...

26:43 ...To Raster tool and just convert it directly.

26:51 Okay. Moving on. Density functions.

26:54 So, we have variety of ways in Spatial Analyst to create surfaces, and one of those is to createdensity maps.

27:01 And a density map might be what you guys think of when you think of the term heat map.

27:06 How many people are familiar with the term heat map?

27:11 Okay. And if I ask each of you around the room, What is a heat map, I bet we'd get at least...

27:17 ...three different answers; maybe more.

27:21 And I would assume, also, that some people have made things with the density functions thatthey call heat maps...

27:27 ...and some people have used other tools in ArcGIS and called them heat maps.

27:31 Heat map is kind of a generic term, but most commonly what people are thinking of...

27:35 ...when they think of a heat map is an amount of occurrence of something...

27:39 ...a frequency map of how common is something in a particular place.

27:44 So normally, we would do that with the density functions.

27:47 We have two ways to do that, the simple density and kernel density.

27:50 And the difference is just that the kernel density function creates a smoother output.

27:54 It fits a distance-weighted kernel over the data so you don't get these concentric rings...

28:00 ...where you have sparsely sampled data.

28:02 But what we use density for is to make maps that represent frequency or magnitude oversome area.

28:10 So, the number of people per square mile, number of trees per hectare, you know...

28:15 ...number of roads per, you know, whatever.

28:19 So we can use feature data, point data, or line data as input to these density functions.

28:26 So just keep in mind - density functions are about magnitude per unit area.

28:30 They're something you use on count data.

28:33 I have a number of something.

28:36 And I just make that point to contrast it from later on when we talk about interpolation.

28:43 We have a collection of tools in Spatial Analyst for doing neighborhood and block statistics.

28:48 You know, like, what does that mean?

28:50 Well, neighborhood and block statistics are about looking at individual raster cells and theirneighborhoods...

28:57 ...and calculating some new value.

28:59 So we might use these for, a classic application would be like image processing functions...

29:06 ...where you do want to do high-pass and low-pass filters and things like that.

29:09 Those are neighborhood operations.

29:11 We use them for filtering; we use them for data smoothing and the block functions as well fordata aggregation.

29:18 But really all we're saying is, for a single processing cell, like the one in the middle here thathas the value of 1...

29:25 ...we want to look at a 3 x 3 neighborhood and calculate some new value; and, in this case,we're going to...

29:31 ...calculate the mean value of that 3 x 3 neighborhood.

29:34 That value is output at 3.22; I write that to that cell; and this is a scanning function that just...

29:40 ...goes across the entire dataset and does the same calculation for each cell.

29:45 So every cell in the output on the left, on your right, is going to have a different valuepotentially.

29:53 Contrast that with the block-statistics functions where, with that same 3 x 3 neighborhood,I'm actually...

30:02 And then I don't move over one cell.

30:04 I actually move over an entire block and make a new calculation.

30:09 So we use this primarily for data aggregation purposes.

30:14 And one of the more common utility functions that people use in Spatial Analyst is the zonaloverlay tools.

30:21 So first we need to understand what a zone is.

30:23 That's all the cells that have the same value.

30:26 So I talked previously about, I had a dataset that was land cover, and the value of 2represented forest.

30:32 So that 2, that forest, would all be one zone, okay?

30:37 And what I can do is calculate, say, for each land cover type.

30:41 What is the average elevation per land cover type? Okay.

30:47 Or I can calculate, what is the average slope per watershed?

30:52 So the zones that I'm using as input, these areas, they can be rasters or they can be polygons.

30:59 ...calculating the mean value and applying to the same block.

31:02 So I can use a set of polygons as my watershed boundaries and input a continuous datasetlike slope...

31:08 ...and then calculate statistics on those to drive, like, my hydrologic model.

31:15 This is an example of slope at the top, a very continuous dataset.

31:21 At the bottom, I have watersheds as polygons, and the output is computed as average slopewithin each watershed.

31:32 Now similar to that, we have a data exploration tool called Zonal Histogram, and what ZonalHistogram...

31:38 ...allows us to do is to create graphs.

31:42 Maybe we don't want to know what the average slope is in each watershed.

31:46 We want to know, say, a breakdown of the distribution of slope within each watershed.

31:52 So the graph at the bottom, I've got five watersheds that I was looking at and I have five slopeclasses in each of those.

31:58 This is getting to that issue of raster/vector integration.

32:05 ...whereas in watershed 2, 3, and 4, there's a lot of higher slopes.

32:10 And I can tell from just that bar graph that watersheds 4 and 5 - sorry, 5 and 6 - are actuallymuch smaller in area...

32:19 ...because I can look at the cell counts, how large of an area they are.

32:23 So, it's an interesting data exploration tool and really can help you in understanding...

32:27 ...your data and the phenomenon that you're modeling.

32:31 So when I was talking about density a moment ago, I said that it's about working with countdata.

32:37 Contrast that with interpolation tools, which are about working with measurement data.

32:42 So this is another thing that people might think of as a heat map.

32:46 What we're doing here is taking measurements in space and trying to estimate values atunmeasured locations.

32:55 I went out into the landscape and I sampled soil chemistry at a bunch of places and I want tocreate a map...

33:01 ...that represents, you know, soil pH.

33:04 Now, I didn't go out into that field and sample every 30 meters across the entire landscape,you know.

33:11 Off of, you know, a very large area, I might only collect a hundred samples, but I might create

5,000 cells.

33:19 So we use interpolation tools to estimate values at unmeasured locations.

33:24 Now there's a lot of ways that we can do that in Spatial Analyst, in 3D Analyst, inGeostatistical Analyst.

33:30 We're not going to go into depth on that; we did a workshop on that earlier today, and those...

33:35 ...slides will be available online if you want them.

33:39 But there's a variety of ways that we do that - I think I'll just flip over to this one and help youout...

33:45 ...because we get a lot of questions about interpolators.

33:48 Because there's many ways to interpolate data, people have a lot of questions about it...

33:52 ...because how you chose an interpolator has a lot to do with what the output surface mightbe.

33:59 And the thought that goes into choosing that interpolator has a lot to do with how that datawas sampled...

34:04 ...and what the phenomena is that you're trying to model.

34:07 So, a few quick pointers.

34:10 You don't know anything at all about your data but you need to make a surface and see whatyour data looks like.

34:15 Use the Natural Neighbors interpolator.

34:18 So, why Natural Neighbors?

34:20 Because interpolators have some characteristics that allow them to exaggerate data.

34:26 They estimate values that haven't been sampled.

34:29 So they might actually create values that are higher and lower than what was actually in thesample dataset.

34:36 Sometimes these are good things, but if there's too much of it, they create what we think of asartifacts in the surface.

34:42 They're exaggerations of things that might not really be there.

34:46 So the good thing about Natural Neighbors is it's fast, it's simple, and it doesn't create anyartifacts.

34:52 It's very clean in that regard, very conservative.

34:56 So if your input data is contours, there's really only one answer, and that's to use theTopoToRaster tool.

35:02 The TopoToRaster tool is designed to work well with contour data input.

35:07 I'm not going to go into why contours are difficult for interpolators today, but I'd be happyto...

35:12 ...explain it to you and it's in the other presentation.

35:15 If you're not trying to create an elevation dataset from your contours - let's say your contoursrepresent...

35:21 ...soil chemistry - then there's a parameter in the TopoToRaster tool called DrainageEnforcement...

35:26 ...just click that little checkbox off, okay?

35:30 If you're making elevation data, particularly for hydrologic purposes, leave the drainageenforcement on.

35:37 If you're not creating an elevation surface, turn the drainage enforcement off.

35:42 TopoToRaster also allows you to input not only contour lines but also things like spotheights...

35:48 ...points, streams, lakes, cliffs, things like this, so.

35:53 It's a very specialized tool and it's very useful if that's the type of surface that you need tocreate.

35:59 So what if you know that the high and low values in your phenomena have not beensampled...

36:05 ...but are actually really important to you?

36:08 Then, if you're just using Spatial Analyst, the recommendation is to use spline.

36:12 But you need to be careful when you use spline because if you have points that are very closetogether...

36:18 ...but very different in measured value, that's when you're going to start seeing artifacts inthe surface...

36:23 ...because spline is going to try to fit a smooth curve to those points, and you're going to endup...

36:28 ...with these big exaggerations in your surface.

36:30 So you just need to be a little careful when you use spline.

36:34 Now if you happen to have the Geostatistical Analyst extension, our recommendation...

36:39 ...instead would be to use local polynomial interpolation.

36:43 A lot of people actually have the Geostatistical Analyst extension but don't actually know it,so...

36:48 ...if you're not sure if you're on a ELA or a university site license or some, you know,government contract...

36:54 ... or whatever, there's a really good chance you actually have Geostatistical Analyst and justdon't know it.

36:59 So it's worth looking into; there are some really nice interpolation methods in GeostatisticalAnalyst.

37:06 So what if your surface is not continuous?

37:09 And that may seem a bit like an oxymoron, that I have a discontinuous surface, but it's a realthing.

37:14 So I'm trying to create, for example, a surface that represents a geologic formation, a buriedsand lens.

37:24 And, I want to model the top of that sand formation, but it's old geology, right?

37:29 There's faults and things that happen, and those faults have offsets.

37:33 So when I use an interpolation algorithm, if I know that there's a surface with a distinctoffset...

37:40 ...I can include that as a feature, as a line feature, in my interpolation so that I don't lookacross...

37:46 ...that barrier for sample points on the other side, okay.

37:51 So if that's the case, there's a tool called Spline With Barriers for you to use.

37:55 So, if for some reason you need to use a geostatistical technique or want to explore that...

38:03 ...then I would recommend you look at the Geostatistical Analyst and use the empiricalBayesian kriging technique.

38:08 This is a new one in 10.1; it's also known sometimes as easy-button kriging or black boxkriging.

38:16 It actually does a lot of the hard work of geostatistics for you because it does parameterestimations.

38:22 So you don't actually have to do all the variogram modelings that sort of intimidates...

38:27 ...people about using kriging techniques.

38:30 The other nice thing about empirical Bayesian kriging is it doesn't assume stationarity.

38:35 So there's an assumption about stationarity in structure in data that's a requirement fortraditional kriging.

38:42 If you don't understand that, that's okay.

38:44 You don't need to understand that in order to use EBK.

38:47 You only need to know that that's no longer a requirement, because what it does is it fits themodel...

38:53 ...it changes the fit of the model as you move across the dataset.

38:57 If you're interested in geostatistical techniques, I would encourage you to look into theempirical Bayesian kriging...

39:02 ...and I believe Steve is doing - not me, Steve, but the other Steve - is doing a demo theater...

39:08 ...on surface interpolators this afternoon.

39:14 So once we have - oh, sorry, this one is about interpolation with barriers - this is the resultfrom the...

39:21 ...Spline With Barriers tool, and what you can see here in the top right is this is a geologicsurface...

39:27 ...with a series of offsets and gaps in it.

39:30 So, at the bottom left, this surface is actually a salt dome formation where there's actuallygaps...

39:37 ...okay, or holes, in this geologic formation.

39:40 It's not continuous.

39:43 If you look at the shape of the contours you can see, obviously, you know, we've got 4,000here...

39:48 ...and 5,000 over here - there's a big offset between the two sides of this surface.

39:56 So once we've created those surfaces, we have a bunch of analytic tools we can use to analyzethose surfaces.

40:03 Liz showed us the Hillshade tool, which we commonly use for display purposes and we mergethat...

40:08 ...with the elevation data, but also things like slope.

40:11 We need to make maps that represent the steepness of the surface.

40:15 You know, if I'm doing house siting suitability, building suitability, there's certain slopes that Ican build on...

40:22 ...and certain slopes that I cannot build on.

40:24 I need to be able to make a map of that.

40:28 You need to calculate the aspect on the surface.

40:30 I want to know which way the sun shines, okay?

40:33 I want to know if, at high latitudes, am I on a south-facing slope or am I on a north-facing

slope?

40:39 This has a lot to do with what kinds of plants will grow there, how much solar energy theyreceive.

40:48 And we also have a variety of viewshed tools, viewshed observer points and a few others.

40:52 And these allow us to specify locations in the landscape and understand what can be seenfrom this place, okay?

40:59 I'm putting in a fire tower and I want to see what I can see.

41:03 I'm putting in wind turbines and I want to know where they can be seen from.

41:08 We use the viewshed tools for this.

41:13 We also have some solar radiation tools, and what these allow us to do is calculate...

41:18 ...the amount of solar radiation hitting the earth's surface.

41:22 Now, this is not a generic tool that just looks at, you know, your latitude and some simpleequation.

41:28 It actually uses the morphology of the terrain and looks at shadowing effects at differenttimes of day and times of year.

41:36 So it actually has a calendar in it that allows you to specify, you know, give me the solarradiation budget sample...

41:43 ...you know, every three hours from June through July for this particular area, okay?

41:52 The output of this tool is measured in watt hours per meters squared.

41:57 Originally when we put this in, we did it for sort of natural resource application regions...

42:03 ...because this is information that's used, for example, in fire modeling to estimate plantmoisture.

42:10 It's used in a variety of things like snow hydrology and other things.

42:14 But the place that it's actually gotten used the most is solar panels.

42:19 People want to figure out, If I put solar panels on the roof of my house...

42:23 ...if I put solar panels on the roof of this building, how much energy can I actually create?

42:29 Now, in an urban landscape, it's actually important that you understand the shadowingeffect...

42:34 ...from adjacent buildings, and that's what this tool will do for you, okay?

42:38 So if you look here in the middle, you would think in downtown LA, the roof of everybuilding...

42:42 ...would have the same solar potential as every other building, wouldn't you?

42:45 But it's not actually true, because if you look here in the middle, there's a couple of blue ones.

42:50 They have really low solar potential because that's a shorter building.

42:54 And on the south side of the building are some taller buildings that, at certain times of theday, shade it, okay?

43:01 If you're shaded early in the morning or late in the day, it's really not a big deal; you're notmissing much solar radiation.

43:07 But if you're shaded in the middle of the day, it really makes a much bigger difference.

43:11 So the way that this was done, there's a few, actually, websites, Solar Boston and Salt LakeCity...

43:18 ...are two of the ones that are pretty nice.

43:22 The Python code that we used to do this, the JavaScript code for the app that these sites arebuilt out of...

43:29 ...is actually all available on the Resource Center.

43:31 If you wanted to build one of these for your own city, it's a pretty clearly understood model ofhow to do that now.

43:37 I think Ryan's actually doing a demo theater on this, this week, as well.

43:41 So with that, I'm going to turn it back to Liz, and she's going to start telling us about some ofthe...

43:46 ...pieces of this ski suitability model we're going to build.

43:49 Thanks, Steve.

43:50 So previously I showed you how to enable the Spatial Analyst functionality and how to accessthe tools.

43:57 Let's go ahead and see some of the tools, or toolsets, Steve was just speaking about.

44:01 He mentioned the density tools, such as kernel, line, and point density.

44:05 The distance tools, such as corridor, cost distance, cost path, and path distance; as well as theinterpolation tools...

44:13 ...IDW, kriging, natural neighbors, TopoToRaster.

44:18 This is where you find your raster calculator to execute your map algebra syntax.

44:24 The Math toolset contains these math functions, as well bitwise, logical, and trig functions.

44:31 The Neighborhood toolset is where you find the block statistics and the focal statistics.

44:36 Solar radiation, which was what Steve just finished speaking about.

44:39 There's Area Solar Radiation, Point Solar Radiation, and this diagnostics tool - the SolarRadiation Graphics tool.

44:46 In the Surface toolset, you've already seen the Execute Hillshade, but you also find aspect,slope, and viewshed.

44:54 And down here in the Zonal toolset is where you'll find Tabulate Area, Zonal Histogram, andZonal Statistics.

45:00 So now that we know some of the functionality, what Spatial Analyst can do, and where tofind the tools to do it...

45:07 ...let's think of some criteria that are going to be important when determining the bestlocation for a new ski hill.

45:11 Some of the criteria I came up with would be snow depth.

45:14 We want a place that has a lot of snow so that we don't have to make as much snow...

45:18 ...so it's a little cheaper to keep our ski hill open during the season.

45:22 So snow depth is going to be important.

45:25 I thought maybe the distance to the center of town.

45:27 There's a town down here, and I think if we built the ski hill closer to the center of town...

45:31 ...maybe we could get more people to show up in the evenings and maybe have some nightskiing...

45:35 ...and maybe generate some more money for our ski hill that way, so that might be animportant criteria.

45:40 And gradient's an important criteria; we don't want to put it anywhere too flat.

45:43 Even if it's a high elevation, the gradient's important for the slope, right?

45:47 We need a good slope for a ski hill.

45:49 So let's look at the tools and the data that I have and see if I can generate that information...

45:53 ...and use it in my suitability model.

45:56 So I have elevation data, and Steve taught us about the Slope tool, so if I go here to theSurface toolset...

46:02 ...and open Slope tool, I can input the elevation data, give it a useful output name, such asSlope Out.

46:12 I'm going to leave it in degrees, although I could also output in percent rise and again the zfactor can remain 1.

46:19 I go ahead and execute that tool and add it to the display with this dataset, and you can seethat green...

46:25 ...represents relatively flat areas, small degrees of slope, and the red represents...

46:30 ...much cheaper areas relative to my study area.

46:33 So here is relatively flat and over here it's relatively steep.

46:37 So that's going to be important when we go to combine our criteria for our ski hill.

46:42 Another thing I mentioned was snow depth.

46:43 I think that would be important.

46:45 Now I don't have a raster that represents snow depth, yet; all I have are these points.

46:49 And at each of these locations, there's a weather station, and I know the average annualamount of snow.

46:55 Using those points, I can use one of the interpolators and generate a continuous surface.

47:01 The interpolation tool I'm going to use is Natural Neighbors, which is the most conservativeof the interpolators.

47:08 I'm going to input my snow-depth points, select the snow-depth field - that holds the value ofthe snow depth.

47:15 The cell size is inherited from my environment settings.

47:19 I may as well as give it a name such as, I'll put Snow Depth.

47:27 And go ahead and execute that tool.

47:31 The result is added to display - it's not very intuitive because of the color, so let's fix that.

47:35 We'll go to Properties > Symbology and find a different renderer.

47:39 How about light blue to dark blue.

47:42 Areas where it's light blue are relatively, I'd say relatively shallow, and areas that are darkblue are relatively steep.

47:51 So now we have a continuous surface representing snow depth.

47:54 That will be an important criteria.

47:56 The last one I mentioned is the distance in the center of town.

47:59 I have a little line segment down here - you can't really see it - it's the center of town, and I'mgoing to generate...

48:05 ...using one of the distance tools - the distance from every pixel in my input study area to thatlocation.

48:12 And to do that, I'm going to use the Euclidian distance tool.

48:17 My input feature, in this case, is the center of town.

48:23 Again, I'll provide an output name, EucDistTown.

48:29 The maximum distance I'm going to leave empty, and this is going to allow the tool toexecute...

48:33 ...to the full extent of my study area.

48:34 If I wanted just to cut it off after 5 kilometers or 10 kilometers, I could enter that here, but it'snot necessary in our case.

48:41 And again, the cell size is inherited from the environment.

48:44 I'll run the tool.

48:48 So now you can see that the yellow areas, or orange - I don't know what color that is - isrelatively close...

48:52 ...to the center of town and blue is relatively far.

48:55 Every pixel in this output has its own value.

48:58 If I click here using the Identify tool, it's about 9 kilometers to the center of town.

49:04 This location is about 15 kilometers to the center of town.

49:09 And this one's about 21 kilometers to the center of town.

49:14 So in the next demo, I'll combine these in a meaningful way to find the best location for a newski hill.

49:18 But right now, Steve will teach us a few more things.

49:21 Thanks, Liz.

49:23 So, so we've got things like slope measured in degrees, distance in kilometers, snow depth inmeters.

49:34 And we want to combine those together to create a map that represents how good of a placeis this to build a ski resort.

49:43 So how do we combine things like that together?

49:47 Well, the first thing that we want to do is that we want to change some of those variables...

49:53 ...to what we think of as a common scale.

49:56 We want to remap these values where each dataset will represent its suitability for a skiresort.

50:04 What does that really mean?

50:05 It means, I want to take the slope map and turn it into something that represents how good...

50:11 ...are certain slopes for building a ski resort?

50:15 How good is a certain snow depth for a ski resort?

50:18 How good is a certain distance to town for a ski resort?

50:23 The way that we do that is with the reclassification tools, and what this allows us to do isreclassify...

50:29 ...individual values or ranges of values into some new value that has a different meaning forus.

50:35 So we can take slope ranges - I want to build a ski resort, so I want to take things, you know...

50:41 ...0 to 20 degrees and make them one class, and 20 to 30, and make them another class.

50:47 I use the reclassify tools to do that.

50:52 And then when I want to combine those things together, what I can do is assign weight valuesto them and say...

50:59 ...you know, slope is really important, 'cause it's about downhill skiing.

51:04 And distance to town is kind of important.

51:07 Or, having good snow is really important.

51:10 So I can add what we call a percent influence - you can't quite read it in the dialogue...

51:14 ...but you'll be able to read it in the demo - a percent influence of how important each of thosevariables is.

51:22 And each of those datasets, those variables I have reclassified into classes that make sensefor my suitability model.

51:30 And I can use the Weighted Overlay tool to assign individual values to those.

51:36 Maybe a little better example of that.

51:38 So we use the Weighted Overlay tool to do sort of the classic GIS problem of finding "where isthe best place."

51:45 And "where is the place" is a very, sort of generic concept.

51:49 But the way that we're doing this for finding the best place for a ski resort is the same waythat you would...

51:56 ...find the best place for a coffee shop, or a likely place to find an endangered species, or thebest place to...

52:00 Change the slope values, okay?

52:04 ...you know, grow a certain kind of plant, okay?

52:08 It's really all the same pattern.

52:10 So, think about what kind of problems you're trying to solve in terms of "where is the bestplace"...

52:17 ...and what kinds of criteria you might use from the GIS to do that.

52:21 What criteria would you use, what kinds of classes would you use to describe those?

52:27 And then you can use the Weighted Overlay tool to combine those things together...

52:31 ...to assign those weight values, the importance of pieces of this, and you run the WeightedOverlay tool...

52:38 ...and you get a result, and you're like, wow, nice map!

52:41 And then what do you do?

52:43 You're not done.

52:45 The real power of the Weighted Overlay tool is that you can just go back to the same dialog,it's already populated with...

52:51 ...everything you set, and you say, "Well, you know, the snow depth is much more importantthan I thought it was."

52:57 So change the snow depth percent influence.

53:03 Play with it.

53:04 It's all a subjective model.

53:06 People use the Weighted Overlay tool, for example, the people from Trust for Public Land...

53:11 ...who won the award on Monday - the TPL people, Breece and those guys - they used theWeighted Overlay tool...

53:18 ...and technique in stakeholder meetings with citizens.

53:22 They're trying to figure out the best place to build parks.

53:25 They invite the community in and then actually have a documented workflow, these exercisesthat...

53:30 ...they take the community through to have them determine which criteria they think areimportant...

53:36 ...and to assign those weight values.

53:38 And then they compare each other's maps, right?

53:41 So, it's not something for one person to do as an expert and make a decision by themselves.

53:46 This is actually a collaborative tool where you can actually engage other people and getexpert opinions...

53:51 ...on different pieces of it.

53:53 And what the Weighted Overlay tool itself allows you to do is just have an easy place tomodify...

53:58 ...those weights and rerun the tool without having to go redo all your work again.

54:03 You just change a few values, hit OK, and do it.

54:08 So we'll let Liz show us how we actually do that.

54:13 As promised, it's time for the modeling part.

54:17 So to create a model, you right-click, say New Toolbox; that's the first step.

54:24 As you create a new toolbox, you right-click New Model.

54:29 I already have a model started here; I'm going to open it up in an edit session.

54:33 I didn't only think of those three criteria that we looked at last time.

54:36 I thought of a few more criteria that we should include, and then I categorized them intothree submodels...

54:42 ...issues that had to do with the development the ski hill, the terrain of the ski hill, and theaccessibility of the ski hill.

54:49 So let's go ahead and zoom in and see part of this model.

54:52 In terms of development, I thought things that might be important were the soil type.

54:56 What soil's best to build on, what's difficult to build on, especially with slopes involved.

55:01 Land use. Who owns the land?

55:02 Will I ever be allowed to put a ski hill on there?

55:04 Is it protected land or private land or public land?

55:07 Oh, that's landowner; sorry - land use.

55:10 Is it swamps? Is it forest? Are there already buildings there?

55:14 I mean, that's important stuff to consider when building, when looking for a new location.

55:20 Terrain. We already looked at snow depths and we generate our continuous surface thatrepresents snow cover.

55:25 Elevation. You saw me, I already used slope to calculate gradient across my study area, butelevation...

55:31 ...is also the input to the Solar Radiation tool, where I can get an output of how much sun this

slope is receiving.

55:39 Maybe too much sun would affect the snow depth, but maybe not enough sun would be reallycold...

55:44 ...in winter months to ski there, so that might be important to consider.

55:48 In terms of accessibility, it's expensive to build roads and power lines, so we want to considerhow far our new...

55:54 ...ski hill is from existing infrastructures, or how close it is to the center of town, 'cause weneed lots of people there.

56:00 So there's all kinds of criteria to consider.

56:03 But the first thing you need to do after you identify the criteria is derive some data from them- some...

56:09 ...continuous data - like we did in our last presentation, using Natural Neighbors or slope orwhat have you.

56:15 And now you have a whole bunch of rasters that are in different units of measurement...

56:19 ...whether it's degrees or - what were some of the - the distance to the center of town.

56:26 So now as Steve pointed out, we need to reclassify these datasets.

56:30 So down here, I have a section of my model that's not complete.

56:32 I have the output and the Slope tool, but now let's use the Reclassify tool to reclassify thedata...

56:38 ...so that I can use it with the rest of my model.

56:40 So if I go to the ArcToolbox, reclass toolset, and drag Reclassify onto my model...

56:47 ...and use this connecting one, the output of slope can become the input of Reclassify.

56:52 If I double click Reclassify, you can see that the input is slope elevation.

56:58 I'm reclassing the value field and these are the degree values.

57:02 This class represents zero to two degrees, and it's being assigned a value of 1.

57:07 Let's go ahead and set up our own classification.

57:09 If I click this Classify button, you can see here that there are several different classificationmethods...

57:14 ...I can select, such as equal interval or natural breaks.

57:18 And I can also choose the number of classes that I wanted.

57:22 Now since we're trying to do something specific with this in analysis, let's consider how these

values interact...

57:28 ...with the notion of building a new ski hill.

57:30 I spent some time thinking about this and I think we need five classes.

57:33 We need a class that represents relatively flat areas for parking lots and lodges; somethingthat represents...

57:39 ...a relatively little bit of steepness, or a small degree of steepness, for bunny hills andgreens...

57:46 ...something a little bit more for the intermediate skiers, more for black diamond...

57:50 ...advanced skiers; and then probably one category that's just too steep to ski, like it's notuseful for a ski hill.

57:57 I can create these classes by dragging these bars and maybe setting it to where I want...

58:02 ...but I think it's a little easier just to come over here and type.

58:06 I'm going to have my first class, from 0 degrees to 10 degrees.

58:10 My second class is from 10 degrees to 20 degrees.

58:14 So 0 to 10 can be good for parking lots; 10 to 20 is good for beginner slopes; 20 to 30...

58:20 ...we'll call those intermediate slopes; 30 to 45 can be our advanced, our black diamondslopes; and then...

58:27 ...everything else, 45 to 60, too steep to ski.

58:30 I'm going to say, Okay, and I'm going to go ahead and run the Reclassify tool.

58:39 I want to add this to display, but first, I'm going to set layer symbology so it's somethingmeaningful to us.

58:46 So Slope Reclass is the layer of symbology I set up.

58:49 Now, if I add this to display, you can see that the gray areas represents good for parkinglots...

58:55 ...green, the 2, is relatively not steep, good for beginners; blue is for the intermediate; blackwould be...

59:04 ...black diamond slopes; and the red is too steep to ski.

59:08 So we've done that, but how important are they in our model?

59:10 That's the next question we need to ask ourselves.

59:12 And how important is that information in relation to the other criteria in our model?

59:18 So the output from Reclassify is using the Weighted Overlay tool.

59:23 Going into this Weighted Overlay tool, I have three datasets.

59:26 I have the reclassified snow depth values, the reclassified radiation values from the solar...

59:32 ...and now the reclassified gradient values.

59:39 So I have my five classes here on the left; now let's, how important are they?

59:44 Well, all reclassifies in this model are all weighted values on a scale of 1 to 9...

59:52 ...where 1 represents not important at all or undesirable or unsuitable for a ski hill, and 9 isthe value...

59:58 ...I selected to be highly valuable for a new ski hill.

1:00:01 So we need to maintain that same scale across all of our datasets.

1:00:07 We know that 5 is highly unsuitable; it's not good for a ski hill, so I'm going to give that a 1.

1:00:13 Parking lots are important, but I feel as though we could probably flatten some land if weneed, so let's give that a 3.

1:00:19 Now what kind of a ski hill do we want to focus on?

1:00:21 Do we want it to be for beginners, intermediate, or advanced skiers?

1:00:25 What's important to us?

1:00:27 Well, I'm going to design it for advanced skiers, the adventurous people.

1:00:30 So I'm going to go ahead and give this a 5; the intermediate's even more desirable, and theblack diamonds...

1:00:35 ...are the most desirable slopes in our suitability analysis.

1:00:40 Next over here, you can see I have a red X, and that's telling me that my percent influencesdo not yet equal 100.

1:00:46 They only equal 70.

1:00:48 So we need to set the percent influences across these three rasters to equal 100.

1:00:53 So what's the most suitable, or what's the, has the most percent influence within our model?

1:00:59 What's the most important criteria out of these three, and how do they relate to one another?

1:01:03 Snow suitability, I think, is extremely important because snow is expensive to make and it'snecessary for a ski hill.

1:01:10 The slope, I think, is probably second to that.

1:01:12 And sun, well, people are going to have to dress warmer if there's not enough sun.

1:01:15 I mean, it's not quite as important, alright?

1:01:17 So now I've sent my present influences, and the results of this weighted overlay...

1:01:24 ...and the results of my other two submodels all go into this weighted overlay and I do thesame process.

1:01:31 I'm going to run both of these weighted overlay tools and the final result will be added todisplay.

1:01:37 It's running the two tools now.

1:01:41 And let's take a look at our final suitability.

1:01:43 So we know we set it up on a scale of 1 to 9.

1:01:46 Not all the values are there; that's okay.

1:01:50 Two is the least desirable area in our study area.

1:01:54 Let's not build a ski hill over here.

1:01:56 Eight, the darker green, is the most highly desirable location for a new ski hill, and thatlooks to be...

1:02:01 ...around Sourdough Hill in Lost Corner Mountain.

1:02:03 So that would be the best place to build a new ski hill for advanced skiers.

1:02:07 But if we opened up the model and started changing our weights around...

1:02:10 ...if we change the idea or if we got new development information, then we go back to themodel...

1:02:15 ...modify some of the numbers in the Weighted Overlay tool, and run it again.

1:02:18 Like Steve was saying, it's an iterative process.

1:02:21 Thanks, Steve.

1:02:23 Thanks, Liz.

1:02:25 So everybody kind of get that?

1:02:26 You understand how you would apply this to your own types of problems in trying to do...

1:02:31 ...suitability modeling and site selection?

1:02:34 So there's a couple of other ways to do this.

1:02:36 One of the ways we added a few years ago is known as fuzzy overlay.

1:02:40 So in the same way that she was talking about using the Reclassify tool and the WeightedOverlay tool...

1:02:45 ...there's another sort of parallel way to do that, which uses fuzzy reclassify and fuzzyoverlay.

1:02:51 And the fuzzy part of this is not about fuzzy boundaries, it's about fuzzy sets.

1:02:55 So, fuzzy in this case is about set theory and how much something belongs to one group oranother.

1:03:02 The difference between fuzzy overlay and weighted overlay, in this case, is I don't have to...

1:03:04 ...calculating the accumulated flow across the elevation surface.

1:03:06 ...specify discrete class boundaries.

1:03:09 I don't have to say that, you know, 10 to 20 is this value and 20 to 30 is another value.

1:03:15 I can use continuous functions, okay, so I don't have to specify discrete boundaries for theclasses.

1:03:21 The other thing that's different about it is, I don't have to have everything be additive.

1:03:26 In the case of weighted overlay, it's an additive overlay.

1:03:29 It's this and this and this, all added together and then normalized.

1:03:33 In fuzzy overlay, it can be this and this, or some criteria or another criteria.

1:03:39 So you can mix "and"s and "or"s in the same model.

1:03:44 We have a few sort of specialized domain-specific functions in Spatial Analyst, as well...

1:03:49 ...some hydrologic tools, which we presented yesterday, and these slides will be available.

1:03:55 Tools for creating watersheds and stream networks...

1:03:59 ...that basically work by calculating the direction of flow across an elevation surface and...

1:04:08 And then we use this for creating things like watersheds and stream networks and doingstream ordering...

1:04:13 ...and calculating flow length and things like this.

1:04:18 We also have a few groundwater modeling tools for doing simple, two-dimensionaladvection...

1:04:22 ...dispersion modeling, so if you happen to have a head grid and a hydraulic convectivity...

1:04:30 ...and porosity [inaudible], then you can use these tools to calculate...

1:04:34 ...two-dimensional vector flow fields of flow magnitude and direction and drop particles onthem...

1:04:39 ...and see where they go, and do Gaussian dispersion from those.

1:04:43 Sorry if I'm going a little quick through that; we're running a little short on time.

1:04:46 I've got something else I want Liz to show you.

1:04:48 And we have some multivariate statistics tools.

1:04:50 These are things that you might think of more classically as image processing tools...

1:04:55 ...so if you come from an image processing background, you may see things like principalcomponent...

1:05:00 ...analysis and national lightweighted classifiers.

1:05:03 The better way to show this is for Liz to show us the Image Classification toolbar, whichallows us...

1:05:08 ...to do interactive training sample selection and interactive classification of multibandimagery.

1:05:16 And we'll just show that one instead of talking about it.

1:05:21 So, I have a satellite image here of the Lake Tahoe area and I want to do a supervised...

1:05:25 ...classification of that using training samples.

1:05:28 To access the Image Classification toolbar, I go to Customize > Image Classification, andhere's the toolbar.

1:05:35 Here, you can see I have the imagery selected in the drop-down layer, and this is how Idraw my training samples.

1:05:41 So the first class I'm going to make represents water in this image.

1:05:45 So you can go ahead and make some areas that represent water.

1:05:49 If I open up the Training Sample Manager, I can then select those training samples andmerge them into one class.

1:05:56 I'm going to call this Water and, conveniently, it's already blue.

1:06:01 The next class I'm going to make is for the clouds in the study area.

1:06:04 I need to make sure that they remain clouds in my output classified raster.

1:06:09 Again, I'm going to go ahead and select them and merge them and call them Cloud.

1:06:15 Oh, and that's white; we're close enough.

1:06:16 Okay, our next one is the rock, so the bedrock over here.

1:06:20 Now if I was doing this for real, not just demonstration purposes, I'd want to zoom right inand...

1:06:25 ...make sure I'm getting really homogenous samples of the rock, but obviously this is howit's done in a demo.

1:06:32 So I'm selecting some bedrock here.

1:06:35 One thing you might want to do, though, is if you select these, then there's some diagnostictools up here.

1:06:39 The Histogram tool shows you the distribution of the cell that I've selected.

1:06:45 And as you can see, because they're all bedrock, these histograms all overlap pretty well.

1:06:50 There's also the scatterplot.

1:06:52 This might look dispersed until you look at the axes, and actually these clouds all overlapquite well.

1:06:59 And if I look at the matrix of the statistics, then that can also help determine whether ornot...

1:07:04 ...I've done a good job of selecting my training samples.

1:07:08 So I'm going to go ahead and merge these, call them Rock, and color them gray.

1:07:14 The last class I'm going to create in the study area has to do with the vegetation, which isthe red.

1:07:19 Again, I encourage you to zoom in and be much more meticulous than I'm being.

1:07:23 But there we go, now we have some vegetation.

1:07:26 I can merge these again.

1:07:27 If I mistakenly had merged the rocks in with that class, you can always use the Splitbutton...

1:07:33 ...to break it back apart and go back to what you had previously.

1:07:36 Or if one of those training samples doesn't fit after you look at the statistics, you can splitthem...

1:07:41 ...delete them, create new ones, all that.

1:07:44 So I'll merge them; I'm going to call it Veg for vegetation, and it's green.

1:07:49 From the classification - oh, before I do that, let's make sure that we have really distinctclasses.

1:07:54 We don't want a lot of overlap; we want to be very clear with how we do our classification.

1:08:00 Here I've selected all the classes; now when I do the histogram, it's across all thoseclasses...

1:08:05 ...and you can see that they're pretty distinct.

1:08:07 Likewise with my scatterplots; they're pretty separate.

1:08:10 All my blues fall together - all the greens, the grays.

1:08:14 Oh, the whites are up here. They're hard to see, right?

1:08:16 They're also pretty distinct classes, so that's a good sign in terms of classification.

1:08:21 So I go ahead and use the Interactive Supervised Classification tool, and it produces thisclassification.

1:08:28 If in this Effects toolbar I select that Output Layer I just generated and use this Swipe tool...

1:08:34 ...I can swipe back and forth and see how well I did.

1:08:37 Look, I'm not too happy right here, if you guys can see where those black arrows are.

1:08:41 It seems like I have more clouds in my image than result in my classification.

1:08:45 So what I can do is I can go back and I can keep adding; just draw a few more trainingsamples until, you know what?

1:08:53 These are also clouds, and I can merge those in, and now when I do the classification - let'smake sure...

1:09:00 ...I select the right one - did I get any more of those clouds? I'm not sure.

1:09:06 So you can go back and you can keep reiterating the process and continuing on andupdating...

1:09:11 ...deleting, or moving, et cetera, until you get a classification in which you're happy with.

1:09:17 Thanks, Steve.

1:09:18 Thanks, Liz.

1:09:19 Was that the fastest image classification you've ever seen? That's pretty awesome. Yeah.

1:09:26 For all of us who used to do it the hard way in the past, before there was like actually away...

1:09:31 ...to look at your image on a computer display, that's pretty shocking.

1:09:36 So after we do a classification like that, we end up with these kind of speckly-looking things,right?

1:09:44 And that really doesn't look much like good GIS data.

1:09:46 So there's a collection of tools in Spatial Analyst that allow us to do data generalizationand...

1:09:52 ...cleanup of raster data, and these are tools like Majority Filter, Expand, Shrink, Nibble,things like this.

1:10:01 So without going into too much detail on those, if you just watch the little graphic in thecorner...

1:10:04 ...we run, for example, Nibble on that and remove all of the individual or two- or three-cell

areas and then...

1:10:11 ...run Majority Filter on that, you can see that looks much more like what you would thinkof as GIS data, right?

1:10:17 Now the way that those tools work, they actually try to preserve the morphology of the data.

1:10:23 It's actually replacing cell values with, for example, the majority of the neighbors sharingthose boundaries, so.

1:10:31 Okay.

1:10:34 With that, one of the things, if you haven't seen this slide yet in one of the geoprocessing...

1:10:40 ...or Spatial Analyst presentations, there is a geoprocessing resource center now.

1:10:44 When we talked about resource centers in ArcGIS Online on Monday.

1:10:49 There is a community for analysis, and if you go there, there are a lot of good things there.

1:10:57 Things like these presentations, some of the demos that you see, a lot of sample tools andsample scripts.

1:11:03 So there's an education gallery where we have a lot of articles and videos and things likethat...

1:11:09 ...as well as a tool gallery.

1:11:10 Now the important thing about the tool gallery, it's not just the things that you see the littlebitmap pictures of.

1:11:17 There's a button here called More Gallery Posts.

1:11:20 Click on More Gallery Posts; there's a lot more stuff there, okay?

1:11:24 Things that we built, things that you guys built; there's lots of good things there.

1:11:28 So, we just moved over to this new gallery approach at 10.1; we're still migrating over someof the...

1:11:34 ...old materials and indexing those, but expect to see that growing a lot more in the comingyear.

1:11:42 Please fill out a session evaluation.

1:11:44 If you haven't been doing that, the session ID for this particular workshop is 811.

1:11:50 We do actually read all of your session evaluations and all those comments that you write,and we do change our...

1:11:57 ...presentations and create new presentations and drop old ones based on the type offeedback that you guys give us.

1:12:03 So, if you need to run to another session, it's two forty-five now, and we'll hang out and

answer any questions you guys have.

1:12:10 Thanks.

© Esri 2014 http://www.esri.com