Lesson 4

Build the database

YOU’VE COME TO A TURNING POINT in your project. In the early, exploratory phases, you looked at data—both in and out of maps—and evaluated it from various standpoints. You worked a lot with layer properties, but you didn’t operate directly on the data. You’ll do that now.

You have two main tasks in this lesson. Your first task is to populate the LARiverParkSite project geodatabase with the datasets that you chose in lesson 3. Working with the data will be your introduction to the geographic data processing, or “geoprocessing,” tools that make ArcGIS so powerful. That raises the question of whether the project really should have its own database. Couldn’t you continue to use the collection of folders and files you’ve been working with so far? Yes, you could, but there are good reasons to consolidate the data and use the LARiverParkSite project geodatabase that was created automatically when you created the project:

•You can keep the project data in a single location, rather than having it distributed among various workspaces.

•You can keep the project data separate from datasets that you don’t need.

•You can streamline the project data by eliminating unnecessary features and attributes while maintaining the original source data as a backup.

•You can impose uniform standards such as a common data format and consistent names for datasets.

•It will be easier to share the project data with others and to reuse it yourself.

Your second task in this lesson will be to complete the preparation tasks in the data requirements table. In addition to using geoprocessing tools, you’ll do spatial queries, table calculations, and other operations.

For more information, see the sidebar “Project database considerations.”

Project database considerations

For our simple database, we considered the following issues:

Data format: We put all the data into file geodatabase format. The geodatabase is the standard Esri spatial data format, and it has many advantages, large and small, over the shapefile format. We decided not to use feature datasets . Feature datasets are only required to support advanced data structures (topologies and networks) that aren’t discussed in this book. They can also be used as thematic organizers (they’re used this way in the Esri geodatabase in the source data for this project), but you won’t have enough feature classes in your project database to make that worthwhile.

Inputs and outputs: An analysis project has input and output data. You’ll store your input, or starting, data in one geodatabase and your output data in a separate geodatabase. This isn’t the only way to do it. You could store both the input and output data in the same geodatabase. The reason you’re doing it this way is because eventually you might want to run variations on the analysis. This would lead to multiple sets of results, where each set could consist of several feature classes. Keeping track of all that data in one geodatabase would be confusing.

Naming conventions: Conventions aren’t right or wrong in and of themselves. Ideally, they should be easy to remember and easy to apply, but the only real sign that a convention is “wrong” is that you don’t stick to it. Our conventions are as follows:

•To separate word forms with capital letters, rather than spaces or underscores. For example, VacantParcels rather than Vacant_Parcels or Vacant Parcels. (This typographic convention is called “Pascal case” or “CamelCase.”)

•To use natural singulars and plurals. For example, LARiver (one river) and MajorRoads (many roads).

•To use complete names, not abbreviations. For example, MajorRoads, not MjrRds.

•To prefer descriptive names to names that reflect software procedures. For example, ExcludedParkAreas is better than Parks_Buffer_Dissolve_Erase.

Coordinate system: Feature classes in a geodatabase don’t have to be in the same coordinate system. (Feature classes in the same feature dataset do have to be in the same system.) Because ArcGIS Pro projects data on the fly, you don’t have to worry about mixing and matching datasets. One reason, however, to keep all the data in the same coordinate system is that you don’t have to think about making sure the data frame is set to the appropriate system. Also, it’s considered better practice to make spatial edits to data in its native coordinate system rather than when it’s projected on the fly. You’ll project all the data in your database to the State Plane California Zone 5 coordinate system.

Maintenance and documentation: You don’t have to worry about updates, security, quality control, or other issues that apply to keeping a large database up and running. In this case, maintaining the database means keeping it uncluttered. In the course of an analysis project, it’s common to create datasets that are an important link in a chain of processes but that have no particular value once you reach the end of the chain. If you don’t remove this “intermediate” data from the geodatabase, it accumulates quickly, often making it hard to distinguish critical outputs and results from byproducts. (This is especially true for others who may want to look at or use your data, but it’s true for you as well.) In addition to keeping the database trim, you also want to keep it reasonably well documented. Output datasets that you intend to keep should have updated item descriptions to reflect the contents and purpose of the data.

Types of geodatabases

A geodatabase can be one of three types:

A file geodatabase, with extension.gdb, is stored as a collection of system files in a folder. It has no total size limit. Each dataset within the geodatabase has a default size limit of one terabyte, which can be increased to 256 terabytes. Multiple users can concurrently edit different datasets within the geodatabase.

A personal geodatabase,* with extension .mdb, is a Microsoft^® Access^® database. It has a total size limit of two gigabytes. Only one user at a time can edit the database. File and personal geodatabases serve the same purposes; the personal geodatabase is just an older version of the technology.

An ArcSDE^® enterprise geodatabase is stored in a relational database system such as Oracle^®, Microsoft SQL Server^™, PostgreSQL, or IBM^® DB2^®. (SDE stands for Spatial Database Engine.) Its size limits are determined by the database system in which it resides. Enterprise geodatabases support concurrent editing on individual datasets and provide database administration tools.

*Personal geodatabases are accessible with ArcMap and ArcCatalog but not ArcGIS Pro.

Exercise 4a: Project a shapefile

Your first task is to populate the geodatabase with starting data for the analysis. As needed, you’ll convert the data format from shapefile to geodatabase and project it to the state plane coordinate system.

Open the data requirements table

Having this table open may help you keep the various preparation tasks in mind. As you work through the lesson, you can refer to it or not as you like.

1)Using Windows Explorer, open the data requirements table from the MapsAndMore folder. If your table isn’t up to date, download the results for lesson 3 from the book’s resource web page, at esri.com/UnderstandingGIS4.

Most of the datasets need some preparation. Actually, if you count format conversion and projection as preparation tasks, they all do. For now, start with a dataset that doesn’t have anything listed in the Preparation column. The block centroids dataset in row 11 is one.

2)Minimize the data requirements table.

Get started

1)Start ArcGIS Pro and open your LARiverParkSite project.

2)Insert a new map and name it Lesson4a. As an alternative to using the Insert tab, try right-clicking the Maps folder in the Catalog pane and clicking New Map.

Open the Project tool

First, check the coordinate system of the Block Centroids layer to make sure it must be projected.

1)Open the Lesson2 map. (You can keep the Lesson4a map open as well.)

2)In the Contents pane, right-click block_centroids, and click Properties.

3)In the Layer Properties dialog box, click the Source tab (on the left).

4)Scroll to the bottom of the dialog box and expand Spatial Reference.

The geographic coordinate system is GCS WGS 1984. You’ll project it to the state plane coordinate system. This isn’t an on-the-fly projection of a layer in a map, but a geoprocessing operation on the feature class itself that converts all the WGS 1984 angular coordinates to state plane linear coordinates. You need a geoprocessing tool to do it.

5)Close the Layer Properties dialog box.

6)Close the Lesson2 map.

7)If necessary, return to the Lesson4a map by clicking the tab above the map.

8)On the Analysis tab, in the Geoprocessing group, click the Tools button to display the Geoprocessing pane.

The Analysis tab and Geoprocessing pane allow you to access literally hundreds of tools for any number of tasks. The most common tools are displayed in a gallery across the top of the ribbon. This gallery can be customized to include the tools that make the most sense for your workflow. Also, notice that the Geoprocessing pane initially displays Favorites (the tab at the top of the pane). This tab is also customizable.

9)In the Geoprocessing pane, click Toolboxes.

This pane displays all the tools included with ArcGIS Pro, organized logically into toolboxes. There are a lot of them, but most are specialized. The ones most useful to your project (and much of the typical GIS work) are the Analysis, Conversion, and Data Management toolboxes.

10)Expand Data Management Tools. Then expand the Projections and Transformations toolset, and click the Project tool. Clicking it opens the Project tool in the Geoprocessing pane.

Most tools look basically the same as this one: a dialog box with several settings, called parameters. Required parameters, such as the input and output datasets or feature classes and the output coordinate system, are marked with a red asterisk.

The ArcGIS Help panel summarizes the tool’s function. This tool takes an input dataset and creates a new output dataset in whatever coordinate system you choose.

11)In the upper-right corner of the pane, click the Help button . This button opens a detailed help page specific to this tool and its usage. Close the web browser when you are finished looking at the help page.

Project the block_centroids shapefile

Now you’ll fill out the parameters and run the tool. The first thing to specify is the input dataset, the block_centroids shapefile.

1)In the Project tool, hover over the red asterisk, which turns into an information button , next to the Input Dataset or Feature Class parameter. It reads: “The feature class, feature layer, or feature dataset to be projected.”

These parameter information windows help decipher the parameter names, which can often be rather technical or cryptic.

2)Click the browse button to the right of the parameter. Clicking opens a browse dialog box. Click the Folders item on the left of the dialog box, and then browse to ParkSite > SourceData > census. Double-click block_centroids to add it as a parameter to the tool.

Once you drop the input dataset in place, ArcGIS Pro can fill out some of the other parameters for you. It reads the input coordinate system (GCS_WGS_1984) from the metadata and directs the output to the default geodatabase. This geodatabase is where you want the data to be saved, but it’s not the feature class name you want.

3)In the Output Dataset or Feature Class box, highlight the entire path and press the Delete key. In its place, type BlockCentroids. The output path to the LARiverParkSite project geodatabase is restored.

4)Next to the Output Coordinate System parameter, click the Select coordinate system button .

5)Expand the Projected Coordinate Systems folder, then the State Plane folder, and then the NAD 1983 (US Feet) folder.

Be careful to use the NAD 1983 folder with that exact name. Several other versions of the name look similar, such as NAD 1983 (2011) (US Feet).

6)Scroll down and click NAD 1983 StatePlane California V FIPS 0405 (US Feet) and then click OK.

Because the input and output datasets have different geographic coordinate systems—WGS 1984 and NAD 1983, respectively—a geographic transformation has been listed automatically. When you project layers on the fly, you can bypass geographic transformations, but the Project tool makes you use them.

The default transformation chosen by ArcGIS Pro is usually the best choice—in this case, WGS_1984_(ITRF00)_To_NAD_1983. There may be times when you want to use a different one—for example, to conform to standard practice in your organization. In this case, you’ll keep the default instead of changing the transformation, but be aware that you can change it if necessary. For more information about geographic transformations, see the sidebar “Datums” in lesson 3.

7)Check your Project tool settings against the figure and click Run at the bottom of the Geoprocessing pane.

When the process is completed, the new BlockCentroids layer is added to the map. The BlockCentroids feature class with the coordinate system you specified has also been saved to the LARiverParkSite project geodatabase.

8)Close the Geoprocessing pane by pressing X in the upper-right corner of the pane.

9)If necessary, zoom to the BlockCentroids layer.

10)In the Catalog pane, expand the Databases folder, if necessary, and expand the project geodatabase. Confirm that the new BlockCentroids is present.

If you don’t see the feature class listed, right-click the database in the Catalog pane and click Refresh (or press F5 on the keyboard).

11)Confirm that the coordinate system of BlockCentroids is State Plane California Zone V and that its geographic coordinate system is GCS_North_American_1983.

How? Open the BlockCentroids layer properties under Source > Spatial Reference.

12)Open the Map Properties of the Lesson4a map and set State Plane California Zone V as a Favorite coordinate system by clicking Add to Favorites to the right of the projection.

How? In the Contents pane, right-click the name of the map and click Properties.

Setting a favorite projection saves the projection to the favorites group so it is easier to find.

13)Click OK on the Map Properties dialog box.

14)On the Analysis tab, click History .

The Catalog pane opens on the right showing the geoprocessing history. All geoprocessing operations are logged here in a list displaying which tools were run at what date and time along with any success or error messages. Hover over Project to see more details about tool parameters. Results are especially useful when a process fails because the error is reported in the Messages section.

You can reopen and rerun a tool with all the parameters already set from this list. Simply double-click or right-click the tool and click Open to open the tool. This is a convenient way to rerun the tool if you want to simply change a parameter or need to rerun the tool for any reason.

15)Return to the Project tab in the Catalog pane.

In the next exercise, you’ll add a feature class to the LARiverParkSite project geodatabase using the Copy tool.

Exercise 4b: Copy a feature class

In this exercise, you’ll copy the Parkland feature class to the project geodatabase.

Get started

1)If necessary, start ArcGIS Pro and open your LARiverParkSite project.

You’ll learn a useful skill of setting the geoprocessing environment. Environment settings are default values or conditions applied automatically to all geoprocessing operations.

2)Make a copy of the Lesson4a map and rename it Lesson4b.

Set the geoprocessing settings

There are many environment settings, but you’ll concentrate on the output coordinate system.

1)On the Analysis tab, click Environments , which opens the Environments pane.

2)In the Output Coordinate System drop-down menu, click BlockCentroids. This will apply the coordinate system from BlockCentroids that you defined in exercise 4a (NAD_1983_StatePlane_California_V_FIPS_0405_Feet).

3)Click OK.

Copy Parkland

The Parkland feature class is in the WGS 1984 geographic coordinate system and must be projected.

1)On the Analysis tab, click the Tools button to display the Geoprocessing pane.

2)In the Geoprocessing pane Search box above the tools list, type copy. As you type, ArcGIS Pro presents a list of possible matches.

3)Click the Copy Features tool.

4)Click the browse button to the right of the Input Features parameter. This opens a browse dialog box. Click the Folders item on the left of the dialog box, and then browse to the ParkSite > SourceData folder. Double-click ESRI.gdb to open, and then double-click Landmark to expand.

5)Double-Click the Parkland layer.

6)For Output Feature Class, type ParksRegional. Confirm that the feature class is saved to the LA River geodatabase.

7)Check your Project tool settings against the figure. Click Run at the bottom of the Geoprocessing pane.

8)Close the Copy Features tool when finished.

When the process is completed, the new ParksRegional layer is added to the map. The ParksRegional feature class with the coordinate system you specified has also been saved to the LARiverParkSite project geodatabase. Thanks to the environment setting, the ParksRegional feature class was also projected to the state plane coordinate system. As long as that setting remains in place—which it will, within the current project, until you change it—any geoprocessing tool you run will also cause the input dataset to be projected. As usual with geoprocessing operations, the outputs are new feature classes, and the original inputs are unchanged.

Inspect the results

Now you can see what you’ve accomplished.

1)If necessary, add the ParksRegional layer to the Lesson4b map, and confirm that the coordinate system is in state plane by opening the Layer Properties > Source > Spatial Reference of the layer.

2)In the Catalog pane, expand the LARiverParkSite geodatabase, if necessary.

It should contain two feature classes, BlockCentroids and ParksRegional, along with the three map notes layers (Line, Point, and Polygon). It should also include one table: LARiverPerennial.

3)Save your project by clicking the Save button.

If you’re continuing to the next exercise, leave ArcGIS Pro open; otherwise, close ArcGIS Pro, and close the data requirements table.

Exercise 4c: Prepare the city and county data

Now you’ll move on to data that needs more preparation. In the data requirements table, you listed City_ply and County as data needed for the final map. You made notes to reduce their extent because both feature classes cover the entire United States.

Processing data to get rid of extra features or attributes is a matter of choice. You could just as well leave the datasets intact and instead apply appropriate definition queries to the City_ply and County layers in the final map. One point in favor of small datasets is that they generally display and process faster. Likewise, an attribute table is easier to read if it’s not cluttered with unnecessary attributes. If you later decide to share the project data with others, it will also be convenient to have a smaller package.

You must be careful in deciding which features and attributes are “unnecessary,” because once you get rid of them, they’re gone—gone, at least, from that dataset. You’ll still have the original source data as a backup, so you can recover from mistakes. You probably wouldn’t delete features or attributes that weren’t preserved in another feature class.

Add a new map and change the coordinate system

1)If necessary, start ArcGIS Pro and open the LARiverParkSite project.

2)Insert a new map and name it Lesson4c.

3)Change the coordinate system of the new map to the state plane system that you’ve been using for this project.

How? In the Contents pane, right-click the Lesson4c map and open the Properties dialog box. Expand the Favorites group and select the state plane system. Alternatively, you can use the Projected Coordinate Systems, and then navigate to the state plane system.

Add data to the map

You’ll add the City_ply and County feature classes as layers to the map. Then you’ll select the features you want to keep and copy the selections to new feature classes.

1)In the Catalog pane, in the SourceData folder, under ESRI.gdb, expand the Boundary feature dataset.

2)Press and hold the Ctrl key and click the City_ply and County feature classes to highlight both.

3)Drag the datasets to the map window. The two layers are added to the map.

4)If necessary, drag City_ply above County.

5)Change the symbols to colors that suit you.

6)Zoom to Southern California.

Select counties

In this section, you’ll select the county features that you want to keep.

1)Turn off the City_ply layer.

2)In the Contents pane, right-click County and click Label.

The counties are labeled by name. Label positions change dynamically with the map scale and extent, so yours may be placed differently.

3)If necessary, pan the map to put Los Angeles County roughly in the middle of the display.

4)On the Map tab, click the Select tool . Click anywhere inside Los Angeles County to select it.

The selected feature is outlined in bright blue. This feature is probably the only county feature you’ll need for the final map, but to be safe, you’ll select its neighbors as well. You’ll do this using a spatial query.

5)On the Map tab, click Select By Location.

Spatial queries evaluate spatial relationships among features. These relationships include proximity, containment, adjacency, and intersection. Typically, features in one layer (the target layer) are selected according to their relationship to features in another layer (the source layer). Sometimes, as you’ll work with here, the target and source layers are the same so that features are selected on the basis of their spatial relationship to the selected feature(s).

6)Confirm that County is selected as Input Feature Layer. (It may already be selected.)

7)For Relationship, confirm that Intersect is selected.

8)For Selecting Features, click County.

9)In the Selection type drop-down menu, confirm that Selection type is set to New selection.

Touching features are considered “intersecting,” so in plain English, this query means that counties bordering Los Angeles County will be selected, including Los Angeles County.

10)Compare your dialog box to the figure and click Run.

On the map, Los Angeles, Ventura, Kern, San Bernardino, and Orange Counties are selected.

Hide unnecessary fields

The County layer will serve a purely cartographic purpose. That means the only attributes you’ll need are those you might want for labeling or symbology.

1)Under Contents, right-click the County layer and click Attribute Table.

2)Scroll quickly across the attribute columns to see what attribute information is provided.

There are about 50 demographic and economic attributes—none of which you need. Removing them will tailor your data to its cartographic purpose.

3)Click the Menu button in the upper-right corner of the attribute table and click Fields View. (Alternatively, you can access this view by clicking the Fields button on the Data ribbon.)

The fields view appears below the map, where you can customize how attribute fields are displayed on the map. Each field’s check box can be unchecked to hide the field. Field visibility is a layer property that you can turn on and off as you like—a hidden field isn’t deleted. Nevertheless, the setting affects the way data is copied. When you copy the feature class, hidden fields will be left out.

4)Above the list of fields, click to clear the Visible check box to turn all fields “off” (meaning they are hidden in the layer).

5)Click the boxes in the Visible column next to NAME and STATE_NAME to turn just these two fields back on.

6)On the Fields ribbon, click the Save button.

7)Close the Fields View pane (open pane below the map).

8)If necessary, open the County attribute table to see that only the two fields “marked” visible are displayed.

9)Close the attribute table, and save your project.

Copy the selected features to a new feature class

Using the Copy Features tool again, you’ll copy the five selected features and their visible attributes to a new feature class.

1)In the Catalog pane, click History.

2)The geoprocessing history will display in the Catalog pane.

3)Double-click the Copy Features tool to open it again.

4)In the Copy Features tool dialog box, click the Input Features drop-down arrow and click County.

You can choose input features from a drop-down menu when there are layers in the map.

5)In the Output Feature Class box, highlight and delete the entire path. Type Counties.

6)Click Run. When the tool is finished running, a Counties feature class is added to the LARiverParkSite geodatabase, and a corresponding layer is added to the map. As before, because of the environment setting, the Counties feature class was also projected to the state plane coordinate system.

7)Open the attribute table of Counties to confirm that the only fields copied from the County layer are NAME and STATE_NAME. The other four (OBJECTID, Shape, Shape_Length, and Shape_Area) are created and updated automatically by ArcGIS Pro.

The Counties layer consists of the five counties you selected. The islands are part of the Los Angeles and Ventura Counties features. Features with discontinuous geometry (islands are a common example) are called “multipart” features. If you click on an island with the Explore tool on the Map tab, you’ll see the entire county flash bright blue.

8)Open the Layer properties of Counties, and confirm that the Spatial Reference under Source is NAD 1983 StatePlane California V FIPS 0405 Feet.

9)Close the Counties Layer Properties dialog box and attribute table.

10)Under Contents, remove the (old) County layer to avoid any confusion.

How? In the Contents pane, right-click County, and click Remove.

11)Right-click the (new) Counties layer, and click Zoom To Layer.

Select cities

As with the counties, you don’t know exactly which cities you need for the final map. You’ll make an interactive selection that takes in an indefinite, but ample, number of features.

1)In the Contents pane, turn on the City_ply layer.

2)If necessary, drag City_ply above Counties.

3)At the top of the Contents pane, click the List by Selection tab , and then click to clear the Counties layer. This step makes City_ply the only selectable layer (so when you select by dragging to draw a box, the only features selected will be from that layer).

4)On the Map tab, in the Selection group, click the Select tool .

5)Use the mouse to draw a selection box similar to the one in the figure. (Your box can be bigger or smaller.)

When you release the mouse button, cities that are entirely or partially within the box are selected.

Note that the List By Selection tab on the Contents pane shows the number of selected features next to the layer name. In the example, 331 cities have been selected. It doesn’t matter if you selected more or fewer features.

6)At the top of the Contents pane, switch back to the List By Drawing Order tab.

Turn off fields to prepare for export

As you did with the counties, you’ll get rid of attributes you don’t need for your analysis.

1)Open the attribute table of the City_ply layer, and use the Menu button to open the fields view.

2)Click to clear the Visible check box at the top of the table to turn all fields “off.”

3)Under the Visible column, select the check boxes next to NAME and ST (an abbreviation for State) to turn these two fields back on. These are the only attribute fields you need for your project.

4)Compare to the figure in step 3, and then click Save on the Fields ribbon.

5)Close the fields view for City_ply.

6)If necessary, open the City_ply attribute table to see that only the two fields marked “visible” are displayed.

7)Close the attribute table.

Copy the selected features to a new feature class

Using the Copy Features tool, you’ll copy the selected features and their visible attributes to a new feature class. Instead of using the geoprocessing history, you’ll use another method to open the Copy Features tool.

1)In the Contents pane, right-click the City_ply layer, and click Data > Export Features. This option displays the same Copy Features tool in the Geoprocessing pane that you worked with earlier.

2)In the Output Feature Class parameter of the Copy Features tool, highlight and delete the entire path. Then type Cities.

3)Compare your tool to the figure, and click Run.

When the tool is finished running, a Cities feature class that contains just those features you have selected, plus the visible fields you selected, is added to the LARiverParkSite geodatabase. A corresponding layer is added to the map in the coordinate system you have chosen for the project.

4)In the Contents pane, remove the (old) City_ply layer.

5)Open the attribute table of the (new) Cities layer to verify that the export worked as expected.

The table contains the two attributes you kept, plus the software-managed attributes.

6)Close the table and any other open tables or panes under or on top of the map view.

7)If necessary, in the Catalog pane, expand the LARiverParkSite geodatabase. It should now contain four feature classes—BlockCentroids, Cities, Counties, and ParksRegional—along with the three map note layers and the LARiverPerennial table.

8)Save your project.

9)If you’re continuing to the next exercise, leave ArcGIS Pro open; otherwise, close ArcGIS Pro.

Exercise 4d: Prepare the river data

In row 5 of the data requirements table, you made a note to dissolve the LARiver dataset. This action will combine the river’s 265 individual line segments into a one-line feature, simplifying the task of creating a buffer around the river in lesson 6. The Dissolve tool creates a new feature class. When you run the tool, you’ll convert the LARiver shapefile into a geodatabase feature class as part of the operation.

Dissolve the river

A few common geoprocessing tools, including Dissolve, can be accessed from the gallery on the Analysis tab.

1)If necessary, start ArcGIS Pro, and open the LARiverParkSite project from your recent projects.

2)Make a copy of the Lesson4c map, and rename it Lesson4d.

3)Open map Lesson4d.

4)On the Analysis tab, expand the Tools gallery by clicking the drop-down arrow on the lower right. The Tools gallery provides quick access to some of the most commonly used tools among the hundreds included with ArcGIS.

5)Scroll down near the bottom to find the Dissolve tool in the Manage Data group. Click the tool to open it.

6)For the Input Features parameter, click the browse button and browse to the LARiver shapefile at UGIS\ParkSite\SourceData\City of LA\LARiver.shp.

7)Change the Output Feature Class name from LARiver_Dissolve to LARiver. Outputs of tools default to your project’s “home” geodatabase.

You’ll notice that the entire path to the geodatabase will be displayed when you hover your pointer over the text box. However, you only need to change the name of the new feature class (the last part of the path).

8)In the Dissolve_Field(s) area, select the NAME check box.

Selecting this check box preserves the NAME field, which you want to keep, in the output attribute table. It also affects the way the tool works. Instead of creating a single output feature, ArcGIS Pro will create a single feature for each unique value in the checked field. In this case, it results in the same thing, because the NAME field has only one value (“Los Angeles River”). If you selected a different field, however, the output feature class would have more than one feature.

9)Compare your tool to the figure, and click Run.

When the tool is finished running, a feature class is added to your project geodatabase, and a layer is added to the map.

10)Open the attribute table of the LARiver layer. Note that the Dissolve tool took the shapefile with its 265 features down to one record.

Except for the NAME field you selected, the attributes from the original table have been dropped for the one remaining record. Confirm that the length values match.

11)Close the attribute table.

12)Symbolize the river in a shade of blue, and increase its width.

For more information, see the sidebar “Dissolving features.”

Dissolving features

You can dissolve a feature class either by geometry or by an attribute. If you dissolve by geometry, common boundaries between features disintegrate. The number of output features depends on whether the “Create multipart features” box is checked. If it’s checked (the default), you’ll get one output feature with discontinuous geometry. If you clear the check box, you’ll get a unique, single-part feature for each spatially distinct area. In either case, the output table has no attributes except for those maintained by ArcGIS Pro.

If you dissolve by an attribute, common boundaries between features disintegrate only if the features have the same attribute value. Again, the number of output features depends on whether multipart features are created. If so, all input features with the same attribute value will become one output feature (with discontinuous geometry). If not, you’ll get a unique feature for each spatially distinct area. The attribute used for the dissolve is preserved in the output table.

In addition to the attribute used for the dissolve, you can set a “statistics field” to summarize the values of dissolved features for another attribute. In this example, the features are dissolved by TYPE, and SUM_ACRES is a statistics field (based on an ACRES field in the original table) that calculates the total acreage of the dissolved features.

Exercise 4e: Prepare the park data

The ParksRegional feature class is already in your project geodatabase, but you still have the preparation task of loading data into it. That’s because this dataset is missing the two park features that you saw in the NewParks shapefile.

Add data to the map

Now you can remind yourself which two parks are being discussed.

1)Make a copy of the Lesson4d map, and rename it Lesson4e.

2)Open map Lesson4e.

3)From the project geodatabase (LARiverParkSite.gdb), add ParksRegional to the map. Optionally, symbolize the layer in a shade of green.

4)Under SourceData, expand the ParkData folder and add NewParks.shp. Optionally, symbolize this layer in a different shade of green.

5)Zoom to the NewParks layer.

Compare attributes

You want to get these two NewParks features, along with their attributes, into the Parks feature class. You face a complication in that the datasets have different attributes.

1)Open the ParksRegional attribute table.

It has 1,209 records. Its user-managed attributes are NAME, TYPE, and ACRES.

The TYPE attribute describes whether the park is a local, state, or national park.

2)Open the NewParks attribute table.

It has two records. Its user-managed attributes are NAME, CATEGORY, ADDRESS, TELEPHONE, and HOURS.

Both tables have a NAME field. CATEGORY is similar to the TYPE field in the ParksRegional table in that it identifies the parks as state parks. The other fields don’t have equivalents in the ParksRegional table.

3)Close the open attribute tables.

Use Append to load data

The Append tool loads data from one or more datasets and appends the features into an existing dataset. It also provides tools for dealing with attribute mismatches.

1)On the Analysis tab, find the Append tool in the Tools gallery. It’s right next to the Dissolve tool you used in exercise 4d.

2)For Input Datasets, click NewParks. This dataset is the one to be loaded. Note that you can append multiple datasets, but you will be using only one for this exercise.

3)For Target Dataset, click ParksRegional. The data will be loaded into this dataset.

4)Change Schema Type to Use the Field Map to reconcile schema differences.

This schema type displays the Field Map parameter with additional options to describe how attribute values will be loaded from the input to the target dataset. (This is also referred to as “mapping fields.”) The Output Fields column on the left side lists the available attribute columns in the target dataset. The Source column on the right side lets you pick which field(s) you want from the input dataset(s). If the field names match, ArcGIS Pro assumes that the fields should be matched.

5)In the Field Map table, click NAME in the Output Fields column. Notice that NAME has a match, because there is a field named NAME in the NewParks shapefile.

Next, you will “map” the CATEGORY field from NewParks to the TYPE field in Parks.

6)In the list of Output Fields, click TYPE.

7)Click Add New Source, and then in the list of fields, click CATEGORY.

8)At the bottom of the list, click Add Selected.

You have set up the field map so the values from the NAME field in NewParks will be loaded into the NAME field in ParksRegional. The values from the CATEGORY field in NewParks will be loaded into the TYPE field of ParksRegional.

There is no ACRES field (by this or any other name) in the NewParks table, so there is no need to map this field.

The address, telephone, and hours information in NewParks won’t be loaded, because ParksRegional has no appropriate fields to accept the values. If these fields were necessary, you would have to add them to the target dataset before appending it.

9)Compare your tool to the figure, and click Run.

Review the results

1)Turn off the NewParks layer in the map, and notice that the two features have been added to ParksRegional.

2)Open the ParksRegional attribute table, and confirm that the two new park records were added at the bottom of the table. You should now have a total of 1,211 records in the table.

3)Close the attribute table.

For more information, see the sidebar “Field data types.”

Field data types

One of the essential properties of a field in an attribute table is its data type, which defines the type of information the field can hold. When a new field is added to a table, its data type is specified and can’t be changed thereafter. There are several field data types, but those used most often are text (sometimes called “string”) and the four numeric types: short integer, long integer, float, and double.

Text fields are for descriptions, codes, noncomputational numbers (such as postal codes or telephone numbers), and the like. The default length of a text field is 255 characters. If you know that your entries will be shorter—for example, if you’re storing two-letter state abbreviations—you should set the length property accordingly. In the interest of saving space, you can also use codes in place of long descriptions. In a geodatabase, codes and their associated values can be managed through a so-called “attribute domain” (not discussed in this book).

For numeric data, use short or long integers when the values are whole numbers, such as population or number of items sold. Whether to use the short or long integer type depends on how large the numbers are (see the associated table). Use floats or doubles when the values are fractional. Floats store six digits with precision (for example, 12345.6 or 1.23456). Numbers with more digits are stored with some rounding, which may slightly affect calculations. Doubles are stored with 15 digits of precision. Floats are suitable for most statistical calculations, such as population density and average income. Doubles are recommended for fields storing geographic measurements and calculations. ArcGIS Pro uses the “double” type in its Shape_Length and Shape_Area fields.

Table 4-1 summarizes the field data types available for geodatabase feature classes. Not all data types are available for shapefiles.

Table 4-1. Field data types for geodatabase feature classes
Text	Letters, numbers, special characters
Short integer	Whole numbers from −32,768 to 32,767 (uses 2 bytes)
Long integer	Whole numbers from −2,147,483,648 to 2,147,483,647 (uses 4 bytes)
Float	Fractional numbers: precise to 6 digits, then rounded (uses 4 bytes)
Double	Fractional numbers: precise to 15 digits, then rounded (uses 8 bytes)
Date	Dates and/or times
BLOB	Binary large objects, including special feature types such as geodatabase annotation
Raster	Small images
GUID	Unique feature/record identifier for features in distributed geodatabases
ObjectID	Unique feature/record identifer
Shape	Feature geometry type (for example, point, line, or polygon)

Make a spatial selection in the ParksRegional layer

It’s not one of your preparation tasks to reduce the Parks data, but the spatial extent of this feature class is bigger than it needs to be. Getting rid of extra features may help speed up some analysis operations in lessons 6 and 7. In the next steps, you’ll use Select By Location to get a copy of just those parks that are within three miles of the LA River.

1)Zoom to the ParksRegional layer.

2)Turn off the Cities layer.

Those big national forests to the north are definitely outside your area of interest.

3)In the Contents pane, select the ParksRegional layer, and on the Map tab, in the Selection group, open the Select By Location tool.

4)If necessary, click ParksRegional in the Input Feature Layer drop-down menu. (This layer should already be selected for you if you selected the layer in the Contents pane.)

5)In the Relationship drop-down menu, click Within a distance geodesic. For the Selecting Features parameter, click LARiver.

6)Use the Search Distance parameter to define 3 Miles as the distance.

7)Leave the Selection type parameter as New selection.

The spatial query will select parks within three miles of the river. By using the geodesic option, ArcGIS Pro will use the shortest path on the surface of a globe rather than the planar distance of the map projection, which is the shortest path in a two-dimensional Cartesian plane. If any bit of a park is within the geodesic distance, the feature will be selected. All the deselected features will be well out of your area of interest.

8)Compare your tool to the figure, and click Run.

9)Zoom to the City of Los Angeles bookmark.

On the map, park features within three miles of the river are selected.

10)At the top of the Contents pane, click the List by Selection button.

11)Look at the layer list, and note how many parks were selected. Again, these are the parks that are within three miles of the LA River. Confirm that you have 169 selected records.

12)Switch back to the List By Drawing Order tab.

Copy features

Now you’ll copy the selected parks in the ParksRegional layer to a new feature class named Parks.

1)Open the toolbox by clicking the Tools button on the Analysis tab.

2)Note that Copy Features is listed as one of the Recent Tools. Click Copy Features to open the tool. If necessary, search for it in the Search box.

3)For Input Features, click ParksRegional.

4)Name the output Parks.

5)Compare your tool to the figure, and click Run.

When the tool is finished running, Parks is created in your project geodatabase, and the layer is added to the map.

6)Under Contents, turn off the ParksRegional layer.

7)Resymbolize Parks in any shade of green.

8)Zoom to the Parks layer, and open its attribute table. There should be 169 records to match the parks you selected previously.

9)Close the table.

You don’t need the ParksRegional feature class anymore, so you’ll delete it from the geodatabase.

10)In the Catalog pane window, under your project geodatabase, right-click ParksRegional and click Delete. Make sure ParksRegional—not Parks—is highlighted in the Catalog pane.

The feature class is deleted from your project geodatabase, and the corresponding layer is removed from the map. (You still have the original Parkland data in your SourceData folder, so you can recover from mistakes if you have to.)

If the ParksRegional layer is not removed from the map automatically, right-click it and click Remove.

11)Save your project.

Exercise 4f: Prepare the block group data

In rows 8 and 9 of the data requirements table, you identified some block group attributes—population density and age under 18—that you must calculate from your existing data. You’ll add new fields to the table, and then calculate values into them.

Add data to the map

First, you’ll add the block_groups shapefile to the map and have another look at it before you copy it to the project geodatabase.

1)If necessary, open the LARiverParkSite project in ArcGIS Pro.

2)Make a copy of the Lesson4e map, and rename it Lesson4f.

3)Open the Lesson4f map.

4)In the Catalog pane, under SourceData, expand the census folder. Drag block_groups.shp to the map.

5)Zoom to the block_groups layer.

6)Open the block_groups attribute table, and scroll across the attributes.

You need only a handful of the two dozen or so attributes in the table. As with the parks, you didn’t make a note to reduce this dataset, but it will be easier to work with the important attributes if you don’t have to keep scrolling past the unimportant ones.

Turn off unnecessary fields

You’ll turn off fields you don’t need, so they won’t be included unnecessarily when you copy the dataset.

1)Click the Menu button in the upper-right corner of the attribute table, and click Fields View. (Alternatively, you can access this view by clicking the Fields button on the Data ribbon.)

2)Above the list of fields, click to clear the Visible check box to turn all fields off.

3)Select the Visibility check boxes for the following fields to turn them back on:

•FID (a unique user-managed identifier) (Make sure not to check the ID field.)

•TOTPOP_CY (total population)

•POP18UP_CY (population over 18)

•MEDHINC_CY (median household income)

4)Change the TOTPOP_CY alias to Total Pop.

5)Change the POP18UP_CY alias to Pop Over 18.

6)Change the MEDHINC_CY alias to Median HH Income. (HH is short for Household.)

7)Compare your fields view to the figure.

8)On the Fields ribbon, in the Changes group, click Save.

9)Close the Fields View pane.

10)Review the block_groups attribute table to confirm that the correct fields are on and that the alias is displaying properly.

11)Close the block_groups table and any open attribute tables.

Export block groups to the project geodatabase

Now you’ll use the Copy Features tool to copy and project the block group feature class into your project geodatabase.

1)Right-click block_groups, and click Data > Export Features.

2)In the Output Feature Class box, type BlockGroups to match your naming convention.

3)Compare your tool to the figure, and run the tool.

4)Close the Geoprocessing pane.

When the tool is finished running, a new feature class is created in the project geodatabase, and a layer is added to the map.

5)Under Contents, remove the (old) block_groups layer.

6)Open the attribute table of the (new) BlockGroups layer, and verify that the changes were applied as expected.

Calculate population density

Population density is the ratio of population to area. The Shape_Area field stores the area of each block group on the basis of the units of the coordinate system. (This field was added automatically by ArcGIS Pro when you converted the block groups to a geodatabase format.) You know the units are square feet, because those are the measurement units specified by your coordinate system. Since you must express density in terms of people per square mile, you’re going to add two fields to the BlockGroups attribute table: one to store area in square miles and another to store population density expressed in square miles. Then you’ll make the calculations for both fields.

1)At the top of the BlockGroups attribute table, click the Add Field button . This button opens the Fields pane with a new row started at the bottom.

2)For Field Name, type SQMILES.

3)For Alias, type Sq Miles.

4)For Data Type, click in the cell, and then click Double in the drop-down menu.

5)In the Fields ribbon at the top of the application, click New Field .

6)Add another field, and give it the following properties:

•Name: POPDENSITY

•Alias: Pop Density

•Type: Float

7)Compare your Fields pane to the figure in step 6, and click Save on the Fields ribbon.

8)Close the Fields pane, and return to the BlockGroups attribute table. Note that the two new fields now appear in the attribute table.

9)In the BlockGroups attribute table, right-click the Sq Miles field heading, and click Calculate Field. Alternatively, click the Sq Miles column header, and then click the Calculate Field button at the top of the attribute table.

The Geoprocessing pane opens with the Calculate Field tool displayed. This tool allows you to populate attribute values using a value, mathematical expression, or simple code written in the Python scripting language. You will be using a simple Python expression to calculate the Sq Miles field, with each block group’s area in square miles.

10)Confirm that BlockGroups is set as the Input Table parameter, and Sq Miles is set as the Field Name parameter.

11)In the text box under SQMILES =, enter the following text:

!shape.area@squaremiles!

12)Compare to the figure in step 11, and click Run.

ArcGIS Pro calculates the area in square miles for each record and adds the values to the table.

Calculate another field

1)In the table, right-click the Pop Density field heading, and click Calculate Field.

2)Confirm that BlockGroups is set as the Input Table parameter and Pop Density as the Field Name parameter.

3)In the list of Fields, double-click Total Pop to add it to the expression text box under POPDENSITY = . Field names appear surrounded with exclamation points (!).

Note that the field aliases you defined earlier are displayed in the list, but the field names are displayed in the expression box.

4)Under the list of Helpers, click the Division symbol (/) button.

5)In the list of fields, double-click Sq Miles. The complete expression should appear as follows:

!TOTPOP_CY! / !SQMILES!

6)Compare your tool to the figure, and click Run.

ArcGIS Pro calculates the population density for each record and adds the values to the table.

Add fields to calculate the percentage under 18

To get the percentage of the population under 18, you’ll subtract the 18-and-over population from the total population and divide the result (the under-18 population) by the total population. Again, you’ll need two new fields to hold your calculations.

1)Click the Add Field button at the top of the attribute table to open the fields view.

2)Add a field with the following properties:

•Name: POPUNDER18

•Alias: Pop Under 18

•Data Type: Short

3)In the Fields ribbon at the top of the application, click New Field.

4)Add a field with the following properties:

•Name: PCTUNDER18

•Alias: % Under 18

•Data Type: Float

5)Compare your Fields pane to the figure, and click Save on the Fields ribbon.

6)Close the Fields pane, and return to the BlockGroups attribute table. Note that the two new fields now appear in the attribute table.

Calculate the fields

Now that you have new empty fields, you’ll calculate values to fill them with data.

1)In the attribute table, right-click the Pop Under 18 field heading, and click Calculate Field to open the tool.

2)Confirm that BlockGroups is selected for Input Table, and Pop Under 18 is selected for Field Name.

3)In the list of fields, double-click Total Pop to add it to the expression text box.

4)Under the list of Helpers, click the minus sign.

5)In the list of fields, double-click Pop Over 18. The finished expression should read as follows:

!TOTPOP_CY! - !POP18UP_CY!

6)Compare your tool to the figure, and click Run.

ArcGIS Pro calculates the population under age 18 for each record.

The last block group calculation you must make is to divide the under-18 population by the total population to get the percentage of children. You have a potential problem with records that have a total population of zero.

7)Scroll back across the table to see the Total Pop field.

If you scrolled down the records, eventually you would find at least one with a population of zero. Block groups can occasionally be uninhabited. Since division by zero is undefined, your calculations will give you an error message. Instead, you’ll use an attribute query to select the records with nonzero values in the Total Pop field. Then you’ll run the calculation on just those records.

8)On the Map tab, in the Selection group, click the Select By Attributes button.

9)In the Select Layer By Attribute tool, confirm that BlockGroups is selected as the Layer Name parameter.

10)Add a clause, and fill it out to select features where the total population is greater than 0.

11)Compare your tool to the figure in step 10, and click Run.

12)Look at the BlockGroups attribute table to see that 6,404 of 6,417 rows are selected (displayed at the bottom of the table).

13)Close the Geoprocessing pane.

Calculate another field

1)Scroll to the end of the table, right-click the % Under 18 field heading, and click Calculate Field.

2)Confirm that BlockGroups is selected for Input Table, and % Under 18 is selected for Field Name.

3)In the expression text box, create the following expression:

(!POPUNDER18! / !TOTPOP_CY!) * 100.

Make sure you include the parentheses as shown.

4)Compare your expression to the figure, and click Run.

Values are calculated for the selected records. The deselected records still have null values. You’ll calculate these values to zero, because if no one lives in the block group, it’s reasonable to say that the percentage of children is zero.

5)At the top of the attribute table window, click the Switch Selection button . You should have 13 of 6,417 records selected.

6)Right-click the % Under 18 field heading again, and click Calculate Field.

7)In the expression text box (under PCTUNDER18 =), clear any text and type 0.

8)Click Run.

9)At the top of the table, click the Clear button.

You now have the attributes you need for population density and percentage of the population under age 18.

Calculate Summary Statistics

Because these calculated values will be used in the analysis later in the project, you must ensure the correct values have been calculated in the BlockGroups table.

1)Use the Summary Statistics tool, accessed through the Tools button on the Analysis tab, to calculate the following statistics for BlockGroups:

•Sq Miles: Sum

•Pop Density: Max and Mean

•Pop Under 18: Max and Sum

•% Under 18: Max and Mean

2)Name the Output Table BlockGroupsStatisticsCheck.

3)Compare your table to the figure, and confirm that all your values match. Then click Run.

4)Open the table (under Standalone Tables in the Contents pane) for BlockGroupsStatisticsCheck, and view the new fields.

5)Confirm your calculated values. Your values may be slightly different out to the last decimal places.

•Sq Miles	4,081.715443
•Max Pop Density	196,474.59375
•Mean Pop Density	13,631.553648
•Max Pop Under 18	3,114
•Sum Pop Under 18	2,316,079
•Max % Under 18	58.333332
•Min % Under 18	22.657363

6)Close the tables.

7)Save your project.

Exercise 4g: Prepare the parcel data

Your search for suitable park sites is limited to vacant land parcels. As you saw in lesson 2, vacancy is an attribute of the stand-alone, nonspatial Vacant Parcels table. You must associate this attribute with the Parcels feature class so that you can see and select vacant parcels on the map. You’ll do this with an operation called a table join. A table join attaches the attributes of one table (usually, a nonspatial stand-alone table) to those of another (usually, a feature class attribute table). The join is based on a field of values, typically an identification code, which is common to both tables. Values in the common field are used to match records in the stand-alone table with records in the feature attribute table. For more information, see the sidebar “Table joins and relates.”

Add data

First, you’ll add Parcels and Vacant Parcels to the map.

1)If necessary, start ArcGIS Pro and open the LARiverParkSite project.

2)Make a copy of the Lesson4f map, and rename it Lesson4g.

3)Open the Lesson4g map.

4)Under Contents, turn off all the layers except LARiver, Counties, and the Topographic basemap to simplify the map display.

5)Expand Folders in the Catalog pane, and browse to SourceData > City of LA. Then add Parcels.shp and VacantParcels.dbf to the map.

Because VacantParcels.dbf is simply a table and not a layer with vector features stored with it, the table is added to the Standalone Tables group in the Contents pane.

6)Zoom to the Parcels layer.

Identify the common attribute

You’ll look at both tables to find the common attribute, or key field, to form the join.

1)Open the Parcels attribute table and then the Vacant Parcels table.

2)At the top of the table window, drag the Vacant Parcels tab to the docking target on the right.

3)In the Parcels table and the Vacant Parcels table (on the right), note that both display an AIN (assessor identification number) attribute.

The AIN is a unique identifier. In theory, when you join the tables, each of the 29,461 records in the Vacant Parcels table should find a single matching record in the Parcels table.

For more information, see the sidebar “Table joins and relates.”

Table joins and relates

Tables can be associated in ArcGIS Pro through either a join or a relate. A join attaches one table’s attributes to the other table. (The join is “virtual,” meaning that it exists only in the map document; the two tables remain separate on disk.) A relate is a look-up relationship, in which you select records in one table to see matching records in the other table. A join is stronger than a relate because attributes in a joined table can be used to symbolize and query features on the map, whereas attributes from a related table cannot be. Both joins and relates require a common attribute to match records.

A join is appropriate when, for any given record in the feature class table (the table to which attributes are being attached), there is at most one possible match in the stand-alone table (the table from which attributes are being attached). A relate is appropriate when more than one match is possible. Consider some examples:

1) A feature class of parcels and a stand-alone table of vacant parcels, in which the common attribute is Parcel ID, a unique identifier in both tables. Each record in the Parcels table has, at most, one matching record in the Vacant Parcels table so a join may be used. The records have a one-to-one relationship: any given record in either table can have no more than one match in the other table. (Not all records in the Parcels table will have matches because not all parcels are vacant.).

2) A feature class of rivers and a stand-alone table of watersheds, in which the common attribute is Watershed ID. This is a nonunique identifier for rivers, because all rivers that drain into the same watershed, or drainage area, have the same Watershed ID. However, it is a unique identifier for watersheds. Because a river drains into just one watershed, each record in the Rivers table has, at most, one matching record in the Watersheds table, which means that a join may be used. The records have a many-to-one relationship: many records in the feature class table can match the same record in the stand-alone table.

3) A feature class of the Los Angeles River and a stand-alone table of improvement projects, in which the common attribute is River ID. This is a unique identifier for river features. It is a nonunique identifier for the stand-alone table, because more than one improvement project may be located along the same river. In this situation, a relate should be used because a given record in the feature class table may have more than one match in the stand-alone table. In a join, only one matching record could be attached to the feature class table; the others would be left out. The records have a one-to-many relationship: one record in the feature class table may have many matches in the stand-alone table.

Join tables

You don’t need to have the tables open to join them.

1)Close the two table windows.

2)Under Contents, right-click the Parcels layer, and click Joins and Relates > Add Join.

The Geoprocessing pane opens with the Add Join tool displayed.

3)Confirm that Parcels is set as the Layer Name parameter and VacantParcels as the Join Table parameter.

4)In the Input Join Field drop-down menu, click AIN. This specifies the key field in the Parcels table.

When you select the Input Join field, ArcGIS Pro will automatically look for the field with a matching name in the join table. Because you have an AIN field in both the input and join layers, AIN is matched for you as the Output Join field.

5)Confirm that AIN is selected for Output Join Field.

6)Click to clear the Keep All Target Features check box.

The only parcels that interest you are the vacant ones—those with matches in the VacantParcels table. If this box is checked, the layer will have all the parcels, with null values for those records that can’t be matched.

7)Compare your tool to the figure, and click Run.

When the tool is finished running, the Parcels layer redraws on the map. Because you chose to keep only the matching records, vacant parcels are the only ones that draw.

8)Open the attribute table of the Parcels layer. Click on Load All at the bottom of the table to display all the joined records.

9)Examine the attribute fields.

The joined table has the attributes of both tables. It has 29,461 joined records, which means that all the records from the Vacant Parcels table were matched to the Parcels layer.

10)Close the table.

Copy features

It’s important to understand that a join does not actually save the new fields to the input feature class. The join is maintained “virtually” for only this layer in this particular map. You’ll now create a new feature class in the project geodatabase, copying just the vacant parcel features from the joined table.

1)Open the Copy Features tool.

2)In the Copy Features dialog box, set Input Features to the Parcels layer.

3)In the Output Feature Class box, type VacantParcelsJoin.

4)Compare your tool to the figure, and click Run.

When the tool is finished running, the new feature class appears in your project geodatabase, and a layer is added to the map.

5)Under Contents, remove the Parcels layer and the VacantParcels stand-alone table.

6)Open the attribute table of the VacantParcelsJoin layer, and examine the attribute fields.

The virtual attributes of the joined table are now permanent attributes of the new feature class.

Field names from the two original tables in the join have been converted to aliases in this table.

7)Using the Menu button, you can turn off the aliases to see the complete field name that indicates with an underscore which source table the attribute came from.

Dissolve vacant parcels

You must still calculate acreage for the vacant parcels (row 3 of the data requirements table). At this point, you might be thinking, “What if there are some adjacent vacant parcels that are smaller than a quarter acre individually but would be more than a quarter acre if combined?” You might be missing out on some potential park sites simply because of property lines.

This figure shows two adjacent vacant 0.24 acres parcels. Separately, each is less than a quarter acre, but together they’re more than a quarter acre. You’ll want to combine them into a potential park site.

To address this possibility, you’ll dissolve the VacantParcelsJoin feature class, which will create single features out of parcels sharing a common boundary. In the process, you’re going to lose attributes. You don’t really need the attributes though—at least, you don’t need them as much as you need good park locations.

1)On the Analysis tab, open the Dissolve tool.

2)In the Dissolve dialog box, set Input Features to the VacantParcelsJoin layer.

3)Change the Output Feature Class name to VacantParcels.

4)Leave the Dissolve_Field(s) area blank.

You’re dissolving purely on the parcel geometry. See the sidebar “Dissolving features” for a discussion on dissolving on geometry versus dissolving by attributes.

5)At the bottom of the dialog box, click to clear the Create multipart features check box.

If you allowed multipart features, the output feature class would consist of a single multipart polygon. You’d have one big discontinuous vacant parcel.

6)Compare your tool to the figure, and click Run.

When the dissolve is completed, VacantParcels is added to the project geodatabase, and a layer is added to the map.

7)Under Contents, turn VacantParcels off and on a few times.

Even with the map zoomed out to the city limits, you can see some areas where parcel boundaries have disappeared.

8)Under Contents, remove the VacantParcelsJoin layer.

9)Open the attribute table of the VacantParcels layer.

It has 14,269 records, about half as many as the undissolved layer. The only attributes present are the four managed by ArcGIS Pro.

Calculate acreage

Now you can get back to acreage. ArcGIS Pro has recalculated the Shape_Area field for the dissolved parcels, but the units are in the units of the map projection. You need to convert them to acres.

1)Add a new field to the VacantParcels table.

2)Give the new field these properties:

•Name: ACRES

•Alias: Acres

•Data Type: Double

3)On the Fields tab, click Save.

4)Close the fields view.

5)Back in the table, right-click the Acres field heading, and click Calculate Field.

6)Type the following text in the text box under ACRES =:

!shape.area@acres!

7)Compare your tool to the figure, and click Run.

ArcGIS Pro calculates the acreage for each record and adds the values to the table.

8)Use the Summary Statistics tool to calculate the total sum of vacant parcels in acres and the average size. Name the Output Table parameter VacantParcelsAcresSumMean.

You should have close to 17,244.6 total acres and an average parcel area of 1.2 acres.

9)Close all the tables.

Clean up the project geodatabase

You’ll get rid of the undissolved VacantParcelsJoin, and then you’ll edit the item description for this VacantParcels feature class.

1)In the Catalog pane, in the project geodatabase, right-click VacantParcelsJoin, and click Delete.

Make sure VacantParcelsJoin—not VacantParcels—is highlighted in the Catalog pane.

2)On the prompt, click Yes to confirm your deletion. The feature class is deleted from the geodatabase.

3)In the Catalog pane, right-click the VacantParcels feature class, and click View Metadata.

Except for the title (which reflects the feature class name) and the file format (type) at the top, the item description is empty.

4)Confirm that VacantParcels is selected on the left on the Catalog tab. On the Home ribbon, in the Metadata group, click Edit.

5)In the Title box, change the title to Vacant Parcels (with a space).

6)Scroll down, and click in the Tags box. Type the following tags: parcels, vacant parcels, Los Angeles.

Include the commas: they separate tags.

7)Scroll down, if necessary. Click in the Summary box, and type: This dataset of land parcels in the city of Los Angeles supports queries on the size of contiguous vacant parcels.

8)Click in the Description box, and type: This dataset represents 29,461 original vacant parcels in the city of Los Angeles. Adjacent parcels have been dissolved, leaving 14,269 features.

9)Click in the Credits box, and type: City of Los Angeles.

10)On the Metadata ribbon, in the Manage Metadata group, click the Save button.

11)Close the Catalog and VacantParcels tabs, all the Lesson4 tabs, and any open tables.

12)In the Catalog pane, confirm that your project geodatabase has the feature classes and tables shown in the figure.

13)Save your project.

14)Close the data requirements table, if you have it open.

15)Continue to the next lesson, or close ArcGIS Pro. Save your changes if prompted.