My name is Aileen Buckley and this is my colleague Mamata Akella, and we’re Research Cartographers on the Mapping Center Team at ESRI.

We’ll start out this session with an axiom well-known to cartographers: “A map is always done when you run out of time.”

So we’re here to talk to you today about how you can make the most of your time when creating maps with ArcGIS when creating maps with ArcGIS.

We’ll do that by showing you tips and tricks that are about 1 minute fixes for various mapping challenges.

In the next 70 minutes, we’ll show you how to go from…

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…this map…

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…to this one. We only have about an hour, so let’s get started!

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Before we get started, I want to point out that you don’t need to take lots of notes because we’ll be posting this presentation with the bottom notes on Mapping Center. They will include all the instructions for the demos we’ll show you.

So, you can just sit back and relax - focus on the content, demos and techniques we show you, and think of any questions you might want to ask us at the end.

We’ll show these URLs again at the end of this presentation.

For now – let’s get started.

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We’ve organized this presentation into a set of cartographic effects that relate to 10 different things, ranging from map projections to page layout.

Along the way, we’ll discuss symbolizing and labeling data for a variety of features, such as terrain, hydrography, cities, and boundaries. We also talk a bit about map elements and page layout.

And we’ll discuss some important cartographic concepts such as the substantive and affective objectives, figure-ground, visual hierarchy and visual association.

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Let’s start with the substantive objective – a term that cartographers use to refer to the content or “substance of the map”. This is what you want to show on the map –knowing this from the outset is the first thing that will help you save time!

Before you even sit down to make the map, see if you can figure out the story you want to tell, the audience you want to tell it to, and the media you will tell it through, such as paper, a PowerPoint image, the Web, etc.

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For this presentation, we’re designing a map of Washington Elevation as a referencemap that shows the topographic nature of the state including hillshading and elevation. We’ll also show related features such as hydrography. And to provide geographic context, we’ll show some administrative and cultural features.

We’re designing for a general informed public which we assume has at least a high school education and some minimum level of map use experience.

• We’re creating a map designed to be printed in color on 11x17 tabloid-sized paper

• in a landscape format.

• That means our map will be at a scale of about 1:1,700,000.

• Our printer is not really high resolution so we can only expect about 300 dpi.

• We also know that this map will not need to be photocopied.

These design and technical considerations will continuously guide us as we make this map.

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Now let’s move on to the set of cartographic effects – these relate to your map projection, which is one of the first things that an experienced map maker will notice about your map. Did you use the right one and did you make any necessary modifications to refine it?

You want to be sure to use a projection that reduces distortion and retains whatever spatial properties you need for your map’s story.

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Let’s switch the screen display so we can take a look at our map in ArcMap. Right now our original data are in a geographic coordinate system (WGS84).

We can move the cursor over the map, and by looking at the coordinates in the lower right hand corner of the screen, we can see that the center of the state is at about 120 degrees west longitude.

We’ll use this information to modify our projection.

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We’ll use a conic projection because it will reduce distortion in the mid-latitudes which is where our mapped area is located, and we’ll use a conformal projectionbecause it will retain shapes and angles.

So we’ll right click the data frame and click Properties, then click the Coordinate System tab. We’ll use a Predefined, Projected Coordinate System. The one we want is in the Continental folder for North America. Near the bottom of the list is the Lambert Conformal Conic projection for the contiguous United States.

Once we select this, we’ll click the Transformations button.

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We’ll keep the method that ArcGIS has already identified as the one to convert between WGS84 and NAD83 for the contiguous United States., So we’ll click OK.

Now we’ll move the dialog box to the side and click Apply.

We can now see that the result is tilted. So we need to make a modification so that Washington is “straight up”.

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We’ll click the Modify button and change the central meridian to negative 120 degrees which we learned earlier is about the center of the state. Now when we click OK twice to accept all the changes, we can see that the state is “north up”.

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OK – let’s move onto the next set of cartographic effects which relate to hillshades. The first tip is to project your elevation data before you create the hillshade.

So that you can see a little better why you should do this, we’ll turn off the Counties layer in the Table of Contents, and we’ll turn on the layer called “Hillshade of Unprojected Data”.

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The hillshade you see here is the result you get if you create your hillshade from an un-projected digital elevation model, or DEM, that is in geographic coordinates.

If we right click that layer and select Properties, and click the Source tab and scroll down to the Spatial Reference information, you will see that when your data are in geographic coordinates, like WGS84, there are no linear units. geographic coordinates, like WGS84, there are no linear units.

Using instead a projected coordinate system will alleviate this problem. We’ll cancel this dialog and turn off the ugly hillshade and show you how you can easily do this.

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Recall that we have set the projection for our data frame. We can use that to project our elevation data, which is SRTM data. We can simply right click the DEM, select Data, then Export Data and be sure to use the projection of the data frame for the spatial reference.

We’ll make it a GRID and change the name to Elevation and place it in a directory that we’re using for this demo. We’ll click Save and then click Yes to add the exported data to our data frame. Then we can remove the srtm_wgs84 grid from the Table of Contents. We’ll also remove the Hillshade of the Unprojected Data.

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Now we can make the hillshade – we’ll use ArcToolBox for this. In the Spatial Analyst toolbox, under Surface, we’ll double click Hillshade. We’ll make sure the Input Raster is the projected DEM (Elevation). And we’ll call the output “Hillshade”. Then we’ll click OK.

Now we can close ArcToolbox.

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We’ll turn off the Elevation layer and take a closer look at the results using our Hillshade bookmark. Let’s make some quick little edits to improve the display.

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We’ll right click the Hillshade layer, select Properties, and then move the dialog box out of the way. We’ll click the Display tab, and change the option for “Resample during display using:” to Bilinear Interpolation, which, as it notes, is good for continuous data like a DEM.

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When we click Apply, you’ll see that the hillshade looks less pixelly. What this does is to change the way the raster is displayed – it does not change the data!

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Now let’s click the Symbology tab and make some edits here. First, we’ll modify the color ramp. We’ll right click the color ramp to toggle off the Graphic View. You can see that the default color ramp for the hillshade is the Black to White color ramp.

We’ll right click the color ramp again and click Properties. Then we’ll click the radio button next to Color 2 to display it, and go back and click the color patch next to Color 1. Then we’ll click More colors, and in the Color Selector, change the HSV, which stands for Hue, Saturation and Value, values to 15, 15 and 45 to lighten it up and soften the color ramp.

We’ll click OK twice to get back to the Symbology tab. Here, we’ll right click the color ramp and click Save to Style so that we can use it again later. We’ll call it “Hillshade PNW” and click OK, and we will be able to find it later in our personal pstyle. Then we’ll click Apply to see the changes.

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Next, we’ll exaggerate the elevation a bit using a contrast stretch. So that you understand how this works, let’s click the Histograms button to look at the distribution of values in our data. First, you can see that the values in our hillshade range from a minimum of about 0 to a maximum of about 255. These are represented by the pink area on the histogram. You can see that they are tightly clustered around the mean and that the mean is shifted toward the right. This distribution is common for hillshaded surfaces.

This means that this majority of values are going to be in the middle range of our color ramp – that is, the medium grays. We need to stretch the values towards the tails so that more pixels are colored black and white.

We can do this with a contrast stretch. Let’s click Cancel to get back to the gSymbology tab.

For our map, we’ll use the stretch type of Standard Deviations, and we’ll first change the number of standard deviations to 4 and click Apply so you can see what it looks like when we de-emphasize the hillshade – notice how the landforms appear to be lower and flatter. This is because n=4 also means that we are not applying ANY 4 pp y gcontrast stretch.

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Since we’re making a map of elevation, we want to slightly exaggerate the hillshade, so instead we’ll use 1 standard deviation. Now when we click Apply, you can see that there is more contrast and the elevation is slightly more exaggerated.

With one standard deviation the lowest 16% of the pixels become black (or 0), and the highest 16% becomes white (or 255); the rest are scaled linearly from 1 to 254.

Thi i l th ff t i Z f t h ti hill h d b t thi i This is nearly the same effect as using a Z factor when creating a hillshade but this is quicker and easier to modify if you want to repurpose your hillshade or different maps.

Now let’s make one last change to the display.

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We’ll apply a Gamma stretch. Gamma refers to the degree of contrast between the mid-level gray values of a raster dataset.

Gamma does not affect the black or white values in a raster dataset – remember –we just used a contrast stretch to change to affect those. We’ll use the Gamma Stretch to modify the middle values.

By applying a gamma stretch, you can control the overall brightness of a raster dataset. We’ll change the value to 1.5 and click OK so you can see the effect on our final hillshade.

This will work really well when we overlay the elevation tint…

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…which is what our next set of cartographic effect relates to. An elevation tint is acolor ramp that you use to show the elevation on top of the hillshade.

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First, we’ll zoom out using our Full Extent bookmark. Then we’ll turn on and move the Elevation layer above the Hillshade layer in the Table of Contents and make sure both of these are below all the other layers.

Now we’ll right click the Elevation Layer and click Properties and click the Display tab.

We’ll move this dialog to the side so you can see the changes we’ll make.

We’ll change the Display Resampling to Bilinear Interpolation and the transparency to 40%, and click Apply. Then we’ll click the Symbology tab.

We’ll right click the color ramp to toggle off Graphic View and scroll down to select the Elevation #1 color ramp and click Apply.

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This is one of the default color ramps in the Esri Style that you often see people using to show elevation. The map looks like the wall maps we used to have hanging in our classroom as children – perhaps not the best choice for our mapped area.

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Now we’ll change the color ramp to Elevation #2 and see if that is any better. When we click OK, you can see that this color ramp makes Washington appear to have many snow capped peaks and a lot of tundra which is what the purple stands for. Again, maybe this is not the best choice for our mapped area.

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So we need a different color ramp. From Mapping Center, we downloaded a style called Color Ramps 2.0. In that style, we found a color ramp that we thought would work well for Washington. So we copied the color ramp into a style we made for this map.

We’ll reference our map’s style by clicking on Customize on the top bar menu, then Style Manager. At the right, we’ll click the Styles button and then we’ll “Add Style to List…” We’ll navigate to the location of the style, select it and click Open.

We’ll expand the style and click on the Color Ramps folder and in the right side of the dialog you can see the Elevation PNW color ramp that we will use on our map. Now we can click Close.

We’ll right click the Elevation layer and click Properties.

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On the Symbology tab, we’ll right click the color ramp to toggle off Graphic View. Then we’ll select the Elevation PNW color ramp in the list and click OK to see how this looks on our map.

You can see that the colors range from greens to browns to white – much more appropriate for the lush valleys, rocky slopes and snow-capped peaks in the state.

Remember the Gamma Stretch and the Contrast Stretch that we applied earlier. You can see how modifying those settings paid off when we display the transparent elevation tint over the hillshade -- the colors of the elevation tint are still saturated and vibrant, but we can also see the slightly exaggerated relief below.

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Let’s make one more edit to our elevation tint to clean up the areas along the shorelines. So that you can see the problem, we’ll use our Hillshade bookmark again, and then we’ll turn on our srtm_water layer – this is a water layer that was specifically compiled to work with SRTM data.

We’ll expand this layer in the Table of Contents and click the symbol and set the fill to No Color and the Outline Color to black and change the Outline Width to 1 point.

When we click OK, you can now see that there are some white pixels in the area that should be land.

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We can easily take care of these by changing their color to the green that is along the coast. To find that color, let’s use the Eye Dropper tool.

You can add this tool to your interface by clicking Customize on the top bar menu, then click Customize Mode. Click the Commands tab and then simply type in “Eye”. You can see that the tool is found. You can then click and drag the tool to any toolbar in your ArcMap session. We’ll click the Close button to close the Customize dialog.

We’ll now use this tool to click on a pixel with the color we want. The color definition is shown in the RGB, or red, green blue, color model. What is that color, Mamata? I’ll make a note of that here.

Now we’ll cancel the Eye Dropper tool.

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Now, in the Table of Contents, let’s right click the Elevation layer and click Properties. On the Symbology tab, you’ll see that there is an option to Display NoData as…. We’ll click the down arrow next to that and click More Colors.

On the Properties tab of the Color Selector, under Other Options, we’ll uncheck Color is Null.

Then we’ll click the Color tab and enter the RGB values for the color Mamata found – they were X X X.

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Now when we click OK twice to keep all our changes, the pixels that used to be white are displayed with the green color we specified. But now all the water is green.

To take care of that, we’ll use our srtm_water layer, which is a great lead in to our next set of cartographic effects which relate to…

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…symbolizing and labeling hydrographic features.

These types of features include rivers and streams, lakes and ponds, and, on our map, the ocean.

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We have some of those features in our srtm_water layer , so we’ll right click that layer in the Table of Contents, click Properties, and click the Symbology tab. We’ll choose to symbolize the layer using Categories – Unique Values and as the Value Field, we’ll select the FACC_DESC attribute. Then we’ll click Add All Values to see what the categories are.

We can use this layer to symbolize the inland waters and the ocean, which has the value called Water (Except Inland).

Notice that Land is also listed and we don’t want to symbolize that since we just spent some time setting up our hillshade and elevation tint layers. So we’ll select that value and click Remove. We’ll also turn off the option to symbolize <all other vales>.

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Now we can select a symbol for the rest of the features. We’ll right click one of the symbols and select “Properties for all Symbols”, then we’ll select the “Lake” symbol from the default Esri style – you can see that it has a light blue fill color and the outline is a darker blue .4 point line.

We’ll click OK, and now all the features will be drawn using the same symbol. We’ll click ok to see the changes on our map.

We can see that we probably want to eliminate some of the smaller lakes because at the scale of our map – 1,700,000 – we’ll only be able to see their outline and no fill color.

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So we’ll find a lake that is about the size we want to stop showing on our map and figure out how big it is. We’ll zoom in a little bit and the use the Identify tool to click on a lake. Mamata will make sure we’re looking at the lake attributes and not the attributes for some other feature.

We can see that there is an attribute called Shape_Area. We know the units are square meters because meters are the linear units for a Lambert Conformal Conic projection, so this will be a pretty big number. Instead of writing it down, we’ll right click it and select Copy because we need this number to allow ArcMap to only draw lakes that are larger than this. Now we can close the Identify dialog.

We’ll right click the srtm_water layer in the Table of Contents, click Properties, and on the Definition Query tab, we’ll create a query to show only the lakes with y q y yShape_Area >, and then we’ll right click and select Paste to complete the query. This is the area of the lake we selected.

Then we’ll click OK twice to see the results.

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Let’s use our Full Extent bookmark to discuss the next cartographic effect which relates to a concept that cartographers call “figure-ground”. This is the spontaneous separation of the map into a figure that draws the eye and the amorphous background. This helps your map readers know what part of the map or page to focus on.

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There are quite a number of ways you can promote this. We’ll talk about one that is really easy called a “whitewash effect”.

To achieve this effect, all you need is a map extent polygon for an area slightly larger than what you want to show on your map, and a polygon for the area you want to emphasize – for our map, that’s the counties of Washington, which we will now turn on in the Table of Contents.

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Creating a map extent polygon is really easy now that you can Convert Graphics to Features. You just have to remember that you have to be in Data View to do this.

On the Drawing toolbar, we’ll use the Rectangle tool to draw a box just outside the extent of our data.

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We’ll right click the data frame and select Convert Graphics to Features.

We’ll call the new polygon feature class MapExtent. Then we’ll click OK.

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We’ll click Yes to the option to Add the exported data to the map as a layer. Then we’ll select the graphic rectangle that we drew and delete it. You can see that the polygon feature remains in the view and in our Table of Contents.

Now that we have the map extent polygon, we can overlay it with the area for Washington.

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We’ll open ArcToolbox, and we’ll expand the Analysis toolbox. In the Overlay toolset, we’ll double click the Union tool. One of the input features is MapExtentand the other is the Counties of Washington. We’ll call the output feature class OutsideWA and click OK. We can now close ArcToolbox.

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The result is a polygon feature class that includes the counties as well as the map extent polygon. We’ll right click this new layer in the Table of Contents and open the attribute table.

Let’s look at the record for the first feature so you can see that it’s feature ID for Counties is negative and all the others are positive – this indicates to us that this is the polygon for the area outside Washington. Now we’ll close the attribute table.

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We’re ready for the last step in creating the whitewash effect. We’ll right click the OutsideWA layer in the Table of Contents and click Properties.

On the Definition Query tab, we’ll use Query Builder to select the feature whose counties ID is -1. We’ll click OK.

On the Symbology tab we’ll click the symbol and set the polygon fill to white and On the Symbology tab, we ll click the symbol, and set the polygon fill to white and the outline to No Color and then click OK.

On the Display tab, we’ll set the transparency to 40% and then click OK.

Now we’ll turn off the Counties layer so you can see the result.Now we ll turn off the Counties layer so you can see the result.

The whitewash directs the map reader’s focus to the area that’s important by washing out the area that’s not. An advantage of this method is that it shows your readers that the world really doesn’t stop at the edges of the mapped area – in our case, Washington.

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Now let’s move onto a VERY important concept that relates to almost any data you add to your map, especially point, line and polygon data. The concept is visual hierarchy, or the separation of the map layers into planes of information. This separation is the basis for being able to distinguish features and to tell which ones are more important than others.

We’ll look at how you can promote visual hierarchy for cities, streams, and b d i i th b l ll th l b l f th f t boundaries using the symbols as well as the labels for the features.

We’ll start with cities, so we’ll use our Cities bookmark so you can see things a little better. Now in the Table of Contents we’ll turn on and expand the Cities data that we got from the Esri Maps and Data DVD.

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We’ll right click the cities data and open its attributes.

Notice that we have a STATUS attribute – we’ll right click on this to Sort Descending. We’ll scroll down a bit so you can see that this attribute indicates if a city is a State Capital, a County Seat or both. Now we’ll scroll back to the top so you can see Olympia, WA which is both a State Capital and a County Seat.

We’ll use this STATUS attribute to symbolize and label our cities. Let’s close the attribute table.

First, we want to show you the symbols we created to show the cities – we did this inStyle Manager.

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To open Style Manager, we’ll click Customize on the top bar menu, then Style Manager and expand the style at the bottom, which is the style we created for this map.

We’ll click the Marker Symbols folder so you can see that we created a set of point symbols with the same exact name as in the STATUS attribute value we just looked at.

If you use symbols with the same names as the values in the attribute field – spaces and capitals included – you can automatically assign them to the correct features.

To show you how to do this, we’ll close Style Manager, and in the Table of Contents’ll i ht li k iti l t it l ti O th S b l t b we’ll right click our cities layer to open its layer properties. On the Symbology tab,

we’ll select Categories - Match to Symbols in a Style. We’ll set the Value Field to STATUS. Then we’ll make sure the style that is referenced is our WashingtonElevation style, and we’ll click the Match Symbols button.

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We saw earlier that the capital of Washington is also a county seat, so we can select the State Capital symbol and Remove it. We’ll also uncheck the option to show <all other values> because we are not showing the rest of the cities.

When we click OK, you can see that the cities are now symbolized. These symbols look pretty good at this scale, which right now is about 1:1,400,000. But remember, our map is going to be printed at 1:1,700,000.

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Now let’s use our Full Extent bookmark to see the whole map. When we do, you will see that the city symbols are being displayed at the same size as they were at 1:1,700,000. What we really want is for all symbols to always look like they will on our final map. To do this, we need to set a reference scale.

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So, we’ll right click the data frame, click Properties and on the General tab, we’ll set the reference scale to 1,700,000 and click OK. Now the city symbols go back to how they will look at this map scale.

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While looking at the map at Full Extent, you can also see that there are a number of cities outside the state of Washington that are also being symbolized. We do NOT want to show these cities.

So we’ll right click the cities layer in the Table of Contents, click Properties and click the Definition Query tab to create a query of [ST_ABBREV] = ‘WA’ and click OK twice. Now you can see that only the features within Washington are shown.

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Now let’s label the cities. So you can see this better, let’s use our Cities bookmark.

For labeling, we like to use the Labeling toolbar because it allows us to manage all the labels on our map in one dialog. To add this to our ArcMap interface, we’ll click Customize on the top bar menu, select Toolbars, then click Labeling.

First we’ll click the down arrow next to Labeling to check the option to Use the First we ll click the down arrow next to Labeling to check the option to Use the Maplex Labeling Engine. Then we’ll click the second button on the toolbar to open the Label Manager.

We’ll turn on and expand the view for the Cities label class. Then we’ll select it.

Notice at the right that you can add label classes from symbology categories. These are the same classes as on the Symbology tab of the Layer Properties for the cities layer.

We’ll click Add and then click Yes to overwrite the existing Default label class, and the two symbology categories will be used to create two new label classes.

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the two symbology categories will be used to create two new label classes.

First, we’ll click on the County Seat label class. We’ll change the font color to Burnt Umber – this is the same color we used when we created the County Seat markersymbol. Then we’ll set the size to 8 pts. We’ll also uncheck the option to stack labels.

Now that we have set these properties, we can use them to set the properties for our second label class.

We’ll right click the County Seat label class and select Copy Parameters. Then right click the State Capital County Seat label class and select Paste Parameters - this copies all of the labeling rules from one class to the other.

The only thing we need to do now is to add an underline to this label class.

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Once we’ve done that, we’ll click OK to keep all these changes.

The way we symbolized and labeled the cities creates a bit of visual hierarchy – the state capital is different from the other cities, but you should also be able to see that it is more of something - in this case, more important on our map. We created this visual hierarchy using the star in circle symbol and by underlining the label.

Now that our cities are symbolized and labeled, let’s look at how you can create visual hierarchy for streams and their labels.

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We’ll use our Full Extent bookmark and in the Table of Contents turn on the USHydroFlowlines layer.

To symbolize streams, cartographers often use a technique called “stream tapering” in which the features are shown with lines that gradually get wider downstream. This gives the map reader the correct impression that there is increasingly more water toward the river’s mouth.

The way to achieve this effect is to use an attribute for stream flow to symbolize the lines. There is a data set for the U.S. available on Mapping Center that you can use; it’s called USHydroFlowlines.

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We’ll right click this layer in the Table of Contents and open the attribute table.

We’ll highlight the attribute called FlowClass. We’ll Sort Descending on this attribute so you can see that the largest river – the Mississippi – has a value of 25, and if we scroll down to the bottom we can see that the values range from 25 to 1.

We’ll use this attribute to symbolize our streamsWe ll use this attribute to symbolize our streams.

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Let’s scroll back to the top of the attribute table.

Now we’ll highlight the LabelClass attribute and Sort Descending. This has values of 2 for the largest streams, and values of 1 for smaller streams. If we scroll toward the bottom, you will see that the smallest streams have a value of 0.

We’ll use this attribute to label our streamsWe ll use this attribute to label our streams.

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We’ll close the attribute table and right click the USHydroFlowlines layer and click Properties.

On the Symbology tab, we’ll use the Quantities – Graduated Symbols method and we’ll set the Value Field to FlowClass. We’ll click the down arrow next to Classes and change the number to 24, then we’ll set the symbol sizes to range from .1 points to 3 points.

Finally, we’ll click the Template button to change the color to Cretean Blue and click OK.

Now when we scroll down to see all the symbols, we can see that they range thl f thi t thi k li smoothly from thinner to thicker lines.

We’ll click OK, and in the Table of Contents we’ll make sure that this layer is under the srtm_water layer and then minimize the layer.

Placing the lines under the polygons helps create the correct impression of

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Placing the lines under the polygons helps create the correct impression of connectivity of the hydro features.

Now let’s label the streams. So you can see this better, we’ll use our Streams bookmark.

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We’ll open Label Manager and turn on the “USHydroFlowLines” label class, expand it and click the Default label class. Then we’ll right click it and select Rename class. We’ll call this Major Streams and click OK.

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We’ll change the color to Cretean Blue, set the size to 10, make it italic, and change the font to Times New Roman which is a serif font. A serif font has small decorations at the ends of the lines – a serif font is commonly used to label hydrographic features like streams. We’ll click the down arrow next to Regular Placement and use the River Placement option instead. We’ll also uncheck the option to stack the labels, then we’ll set the offset to 2 pts.

Finally, we’ll click the SQL Query button and type LabClass = 2 which is the attribute value we saw earlier for the largest streams. And then click OK.

You can use a SQL Query in Label Manager to define what to label and what NOT to label. This is the similar to using a definition query in the Layer Properties dialog to define which features to draw and which NOT to draw. Note that if you do not draw ythem to begin with, they will not be available for you to label.

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Now that we have set all these properties for the major streams, let’s use most of them to label our minor streams. First, we’ll add a new label class by clicking USHydroFlowlines and in the Add Label Class area we’ll type Minor Streams as the new class name and click Add. Now, just like before with our cities, we can right click the Major Streams label class and select Copy Parameters, then right click the Minor Streams label class and select Paste Parameters.

We’ll set the size to be 8 points and click the SQL Query button and change the LabClass to 1 which is the value we saw earlier for the smaller streams. And we’ll click OK. We’ll keep all the rest of the parameters as they are.

We don’t want to clutter up our map too much with stream labels, so we won’t create a label class for the smallest streams which had a value of 0 in the attribute table.

We’ll click OK to see how these labels look on our map.

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We’ll switch to Layout View and use the Print Extent bookmark to see how things look.

We’ll make sure that the USHydroFlowLines layer is under the OutsideWA layer so we continue to emphasize the area of Washington. Also, this layering will allow the streams to be drawn under the polygons so that the stream centerlines are not drawn on top of the stream polygons.

Notice that there are a few streams that are labeling outside the state – this is because all labels draw on top of all features, so they did not move under the whitewash when we reordered the layers.

L t’ li i t th t l b lLet’s eliminate these stray labels.

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We’ll open Label Manager and make sure that we are still working with the label class for the Minor Streams. Then we’ll click the SQL Query button.

Here we’ll load our Minor_Streams expression which is a query we created earlier to NOT label the streams outside Washington. It also includes the expression we typed in earlier to label only the streams with LabClass 1.

We’ll click OK twice to see the changes.

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Now let’s add the labels for our other hydrographic features – lakes. Let’s go into Data View and use our Streams bookmark again so you can see this.

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We’ve symbolized lakes using the srtm_water layer. We like these because they are at the same level of detail as our coastline so all the hydro polygons look similar.

Let’s see if it has an attribute we can use to label them. We’ll right click the layer in the Table of Contents and open the attribute table. Here we can see that there is no name attribute.

We’ll close the attribute table and turn on and expand the WA_HydroPolys layer. Then we’ll right click it, and open its attribute table.

You can see that there is a Name attribute. Note that there is also a FEATURE attribute that identifies what type of hydro each polygon is. And there is also a

tt ib t ith th i ilattribute with the area in square miles.

We’ll use these three attributes to label the lakes. In essence, what we’ll do is showthe lakes in the srtm_water layer on the map, but we’ll use the Washington hydro polygons for the labels.

Now we’ll close the attribute table.

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We’ll right click the WA_HydroPolys layer, select Properties, and on the Symbology tab, we’ll click the symbol and set the colors of the fill and the outline to No Color,and click OK.

Now we’ll click the Definition Query tab and click Query Builder so we can load our WA_Hydro expression. This expression does three things – it only labels lakes and reservoirs, they have to be 25 square kilometers, or larger, and they have to be in the state of Washington. Then we’ll click OK.

We’ll click the Labels tab and click the option to Label Features in this Layer. We’ll set the color to Cretean Blue, the font to Times New Roman, the size to 8 points, and we’ll make sure it’s italic. We’ll click Placement Properties, on the Label Position tab, we’ll click Position, and we’ll choose the Offset Horizontal option. We’ll click OK pthree times to see the results.

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Now that we have visual hierarchy for the cities and the streams, let’s move on to administrative features. For these, we’ll employ a concept called “visual association” in which features and labels intuitively appear to be associated to the map reader. We’ll use this for the county boundaries, their labels, and the county seats that we already have on the map. Let’s use our Full Extent bookmark so you can see this.

The feature class we have for county boundary lines is called AdminLines. We’ll turn this on in the Table of Contents and expand the view. Then we’ll right click it and select Properties, then click the Symbology tab so you can see that we are again matching to symbols in a style.

If we click the Add Values button you can see that we removed one attribute value –Counties. We want to symbolize these separately since we will also be labeling them. y p y gNow we’ll click Cancel.

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Let’s double click the International line symbol and click Edit Symbol. Here you can see that we are using a multi-layer symbol. The layer on the bottom is white and it is 5 points wide. The layer on the top is a cartographic line symbol with a dash dot pattern – common for international boundaries – and it is only 1.2 points wide. Since it is thinner, the white line underneath shows along the two edges.

We’ll click Cancel twice to get back to the Symbology tab. Then we’ll click the State line symbol and you can see that it is simply a gray line that is .6 points wide.

We’ll click cancel three times to see our map.

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Now we can add the county boundaries to our map.

We’ll turn on the Counties layer in the Table of Contents, expand its view, right click it, select Properties, and click the Symbology tab.

We’ll click the symbol patch to change the fill color to No Color, the outline width to 2 points which is thinner than any of the lines in our AdminLines layer If you .2 points which is thinner than any of the lines in our AdminLines layer. If you

recall, the Lakes symbol that we are using for the ocean has an outline width of .4 points. So the county boundary lines that are also coastline, state, and international boundaries will be hidden under the thicker lines.

Now we’ll change the outline color to Burnt Umber so it matches the color of the t t b l d l b l Thi i h t ill t th i l i ticounty seat symbols and labels. This is what will create the visual association.

We’ll click Apply and move the dialog box out of the way so you can see the changes.

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Then we’ll click the Labels tab, check the option to Label the features in this layer, click the Symbol button, and select the Country 2 label. We’ll change the color to --you guessed -- Burnt Umber and change the size to 8 points, then click Edit Symbol.

On the Formatted Text tab, we’ll change the Text Case to All Caps. We’ll click OK three times to keep our changes.

Then we’ll move the AdminLines layer under the USHydroFlowlines layer in the Table of Contents so that the boundaries that are streams will be apparent. And we’ll move the Counties under the AdminLines.

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Recall that we are making a map that shows the topographic nature of the state. We’ve already shown elevation by displaying a transparent elevation tint over the hillshade, but it would help our readers if they could find some actual elevation values on our map.

So we’ll add some elevation values using our WA_Summits layer. We’ll turn on and expand this layer in the Table of Contents. This is a subset of the summits feature class on the Esri Maps and Data DVD. We created it by selecting the points where we wanted to show elevation so that readers are able to tell which colors in the elevation tint relate to roughly which elevations.

Let’s right click the layer and open the attribute table. We’ll use the Name attributeto label the points we’ll use the attribute for elevation in meters to show the pelevation at the point. Now we’ll close the attribute table.

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So that you can see these better, we’ll use our Summits bookmark. We’ll right click the summits layer again and select Properties, and then on the Symbology tab, we’ll click the symbol and click Edit Symbol…

We’ll change the symbol type to Character Marker Symbol, and from the ESRI Default Marker font, we’ll use the triangle symbol. We’ll set the size to 4 points and the color to 70% Gray. We’ll click OK twice to get back to the Symbology tab. Then we’ll move the dialog box out of the way and click Apply so you can see the symbols.

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Now let’s label the summits. We’ll click the Labels tab and check the option to “Label features in this layer”. We’ll label these using the Name field, and we’ll use the default Arial font, change the color to 70% gray so it matches the point symbols, and set the size to 7 points. We’ll click Apply to see the labels.

Now we need to add the elevation values – we want to show these in both meters and feet. We can do this by using a calculation right in the label expression. We also want the elevation values to be a slightly smaller size and we want them to be italics. We can also do this right in the label expression.

We’ll click the Expression button and load the WA_Summits label expression. Inthis expression, you can see that the labels will show the name. And if we scroll to the right, you will see that we are using Text Formatting tags to change the font size g y g g g gand make it italic. Further to the right, you will see the calculation that is used to convert meters to feet.

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If we click the Help button, there is information at hand about how you can do this. At the top, are some examples of how you can do things like the calculation of meters to feet. If we scroll down a bit more, there are some examples of the kinds of text formatting tags that we used to change the font size and style. You can copy the examples in this Help document and paste them into the expression you are building to save time. We’ll close the help, and click OK twice to close the layer properties dialog.

Now you can see the labels with the name, the elevation in both meters and feet in smaller italic text.

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You can also see that some of the labels are overlapping. On the Labeling toolbar, we’ll click the Label Weight Ranking Button and change the Feature Weight for WA_Summits to 1, and click OK. Label weight ranking can be used to help prevent the labels from overlapping on your map, as we did here.

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Now let’s go to Layout View, use our Print Extent bookmark, and make sure that everything looks OK.

While Mamata is checking our final map, I’ll ask you if you think we need to add anything else to this map.

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Before you answer, consider that a guiding cartographic principle is that you should only ever add to the map those map elements, such as titles and legends, that are absolutely necessary.

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TITLE

OK – so what else does this map need. A title? Yes – almost every map does.

We’ll click Insert on the top bar menu to insert a title. Then we’ll double click it and change the title to “Washington Elevation”. We’ll click Change Symbol and use the same Country 2 symbol that we used for the county labels with some modifications.

We’ll change the color to black and the size to 20 points.

Then we’ll click the Edit Symbol button and on the Formatted Text tab change the Text Case to All Caps and increase the character spacing to 70.

Then we’ll click OK three times to accept all the changes, and we’ll move the title to a central location at the top of the map.

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MAP NOTES – data source, authors, projection, date of compilation

What else does this map need? A note identifying compilation details about the map, including the authors, the date of compilation, the map projection used and the source of the data.

For this, we’ll click Insert on the top bar menu to insert some text. We’ll double li k h b h h ’ll d d hclick the text box to change the contents. We’ll open a Word document that we

created earlier and copy the text from there, then open the text box again in ArcMap and paste it there.

We’ll click the Change Symbol button and again use the Country 2 symbol – we’ll change the color to black and the size to 8 points.

Then we’ll click the Edit Symbol button and on the Formatted Text tab change the character spacing to 20.

Then we’ll click OK to accept all the changes, and we’ll move the text to the lower right corner of the map.

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NORTH ARROW

Does this map need a north arrow? Should you even use one on this map?

No – it’s a conic projection so north varies across the map.

You can tell that this is the case because of the curvature and orientation of the boundaries that align with the latitude and longitude.

For example, the northern border of the state is aligned with a parallel of latitude –you can see that it curves. This is your clue that if you look at the north-south county boundaries that align with meridians of longitude, they will point in toward county boundaries that align with meridians of longitude, they will point in toward the center of the map at the top. This is because the meridians converge at the poles.

So, on this map, the only location where north is straight up is at 120degrees west longitude, which is what we set as the central meridian when we modified the projection of the data frame.

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projection of the data frame.

SCALE INDICATOR

Does this map need a scale bar? Should you even use one on this map?

No – it’s a small scale map so the scale distortion is so great that distance varies across the map.

However, we can include scale text, like a representative fraction. Let’s first make sure our map is still at 1:1,700,000. Then let’s double click the map note we inserted previously and add as the first line of text “Scale 1:1,700,000” and click OK.

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LEGEND

Do we need a legend? Not really!

Our state capital and water features use conventional map symbology.

Our counties and their labels are already visually associated so the map reader realizes that the only city labeled within a county is the county seat.

So that pretty much leaves elevation. Since we added summits at various elevations, the map reader can tell what elevations the elevation tint colors relate to.

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OTHER TEXT

So, is there anything else we need to add? Yes -- we really ought to add a label for the Pacific Ocean. We could use this same method to add text for the surrounding states and for British Columbia to the north.

To do this we’ll double click the data frame and you’ll notice that the border is now To do this, we ll double click the data frame and you ll notice that the border is now shown with a hatched symbol. This means that it is focused. Now let’s add some text for the Pacific Ocean.

On the Drawing toolbar, we’ll click the down arrow next to the text button to select Splined text. We’ll insert the spline in the ocean and then double click to finish the

li Th ’ll t P ifi O d li k t id th t t b W t thi spline. Then we’ll type Pacific Ocean and click outside the text box. We want this text to match our other hydro labels so, we’ll double click the text and click Change Symbol. We’ll change color to Cretean Blue, the font to Times New Roman, the size to 16, and we’ll make it italic.

We want it to span the area of the ocean on our map, so we’ll click Edit Symbol and th F tt d T t t b h th Ch t S i t W ’ll li k OK

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on the Formatted Text tab, change the Character Spacing to 400. We’ll click OK three times to keep our changes. And then we’ll make any final position adjustment needed.

Now, we’ll click outside the data frame to un-focus it.

To demonstrate what happens when you add text and graphics to a focused data frame, Mamata will use the Pan tool on the Tools toolbar and move the data in our data frame. You can see that the text stays in the same geographic position it was originally placed in. This is a great way to add text and graphics to your map when they relate to your data and not to the page.

We’ll click the Go Back to Previous Extent button to re-position the data in the data frame.

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So, that brings us to our last cartographic effect – the affective objective.

At the beginning of this session, we introduced the concept of the substantive objective – that is, the substance or content of the map. The affective objective is the “affect” or “look and feel” of the map.

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Every decision we made about color, symbol selection, type properties, hillshade manipulation, page layout and map elements was driven by an understanding of how we ultimately wanted this map to look. We wanted it to have an eye-catching, clean, yet authoritative look to it.

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In contrast, let’s go back to the PowerPoint so you can see a map that our colleague David Barnes made with the same data for the same area.

On this map, the colors, the fonts, the point symbols, the ocean vignette, the sepia tone and the detailed hillshade all combine to make it appear more antique and “old world.” He, like we, made every design decision relative to an affective objective that he identified for the map ahead of time.

In fact, Mamata is going to demonstrate some of the cartographic effects used here in our “Making Beautiful Maps” session.

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As we said at the beginning – the map is always done when you run out of time! And now we’ve run out of time!

We hope we have helped you learn some ways you can make the most of your time.

To help you more, the instructions on how to make the map we’ve shown you will be on Mapping Center in the bottom notes for this presentation We’ll also posted all on Mapping Center in the bottom notes for this presentation. We ll also posted all the things you need to make the map, including the data, map document, style, expressions and more.

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We encourage you to fill out your surveys to let us know if you found this presentation helpful, and what we might be able to do better in the future to help you.

We thank you very much for your time and attention, and now, we’re happy to take any questions you may have.

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