Limit the study area

Rather than analyze rural areas across all of Japan, you'll limit your study area to Shikoku, the smallest of Japan's four main islands. First, you'll add Metropolitan Employment Area (MEA) data to a new project in ArcGIS Pro. Then, you'll extract rural areas from this dataset. Afterward, you'll add population data.

Add MEA data

In Japan, the designation between rural and urban is based largely on employment and commuter ties to city centers. MEAs are municipalities in which the core city population is at least 50,000 and the surrounding commuter population is at least 10,000. For your analysis, you'll define rural areas to be municipalities that are not MEAs (meaning their population is lower than the minimum value).

First, you'll add a layer that contains all the municipalities in Japan.

Note:

The definition of urban and rural areas varies by country. The distinction may be defined by population density, land use, distance between development, or other factors.

  1. Start ArcGIS Pro. If prompted, sign in using your licensed ArcGIS account or ArcGIS Enterprise portal using a named user account.
    Note:

    If you don't have ArcGIS Pro or an ArcGIS account, you can sign up for an ArcGIS free trial.

    This lesson was most recently tested for ArcGIS Pro 2.7. If you're using a different version of ArcGIS Pro, you may receive different results.

    If you're signing in to an Enterprise account, ensure that ArcGIS Pro is configured to use your organization's portal.

    ArcGIS Pro opens. It contains a list of project templates under the heading New.

  2. Under New, click Map.

    Map template in the list of templates

  3. In the Create a New Project window, change Name to SDG_Japan. Click OK.

    A blank map project opens in ArcGIS Pro. Depending on your organization's settings, the default extent may vary. First, you'll change the basemap to one that will emphasize your data.

  4. On the ribbon, click the Map tab. In the Layer group, click Basemap and choose Light Gray Canvas.

    Light Gray Canvas basemap option

    The Light Gray Canvas basemap has a simplified appearance, so the data you add to the map will appear more prominently. Next, you'll add the MEA data.

  5. On the ribbon, on the Map tab, in the Layer group, click the Add Data button.

    Add Data button

    The Add Data window appears. You can add data from your computer, an ArcGIS Online organization or Enterprise portal, or ArcGIS Living Atlas of the World. The MEA data is hosted in ArcGIS Online.

  6. Under Portal, click ArcGIS Online. In the search box, type Metropolitan Employment Areas owner:Learn_ArcGIS and press Enter.

    Search for Metropolitan Employment Areas

  7. Select the Metropolitan Employment Areas layer and click OK.

    The layer is added to the map and the map extent changes to show Japan.

    Japan with MEA data

    Municipalities that fulfill the conditions to be an MEA are styled with various colors depending on their suburb category. Municipalities that aren't MEAs have no color. (Depending on your zoom extent, you may be able to see the boundaries between the municipalities.)

Filter the data

Next, you'll filter the data. First, you'll create a definition query to show only municipalities in Shikoku. Then, you'll select the rural Shikoku municipalities based on MEA status and export them to a new feature class.

  1. In the Contents pane, double-click MetropolitanEmploymentAreas. In the Layer Properties window, click the Definition Query tab.

    A definition query allows you to display only features with specific attributes. In particular, your definition query will display municipalities in Shikoku's four provinces: Ehime, Kagawa, Kochi, and Tokushima.

  2. Click New definition query.
  3. For Definition Query 1, use the menus to create the expression Where PNAME includes the values Ehime,Kagawa,Kochi,Tokushima.

    Definition query to filter by Shikoku provinces

  4. Click Apply. Click OK.

    The filter is applied.

  5. In the Contents pane, right-click MetropolitanEmploymentAreas and choose Zoom To Layer.

    Because the layer only displays municipalities on the island of Shikoku, you navigate to the island.

    Municipalities on the island of Shikoku

    The municipalities that qualify as MEAs are those that are styled with a color. The other municipalities aren't MEAs, so you'll consider them rural. Geographically, most of the island is rural.

    Next, you'll select the rural municipalities and export them to a new feature class. You can make the selection by creating an expression, similar to the expression you made for the definition query.

  6. On the ribbon, on the Map tab, in the Selection group, click Select By Attributes.

    Select By Attributes button

    The Select By Attributes window opens to the Select Layer By Attribute tool. You'll run this tool after setting a few parameters.

  7. Set the following parameters in the Select Layer By Attribute window:

    • Confirm that Input Rows is set to MetropolitanEmploymentAreas.
    • Confirm that Selection type is New selection.
    • For Expression, click New expression. Create the expression Where AREATYPE is equal to RURAL.

    Select Layer By Attribute tool parameters

  8. Click the Verify the SQL expression is valid button (the green check mark).

    If you correctly created the expression, a message appears saying that your expression is valid. Validating an expression checks that the expression's syntax can be understood by the software. It does not guarantee that there are any features that fit the expression.

  9. Click OK.

    Shikoku's rural municipalities (those that are not MEAs) are selected.

    Rural municipalities selected on Shikoku

    Next, you'll export the selected features to a new layer. This layer will contain only the municipalities you're interested in analyzing.

  10. On the ribbon, on the Analysis tab, in the Geoprocessing group, click the Tools button. In the Geoprocessing pane, search for and open the Copy Features tool.

    Copy Features tool in the Geoprocessing pane

    By default, layers will be copied to the project's default geodatabase, a special folder that you created when you created the project.

  11. For Input Features, choose MetropolitanEmploymentAreas. For Output Feature Class, change the output name to Shikoku_Rural.

    Copy Features tool parameters

    The copied layer is added to the map. You no longer need the original feature layer showing all of the municipalities, so you'll remove it.

  12. Click Run.
  13. In the Contents pane, right-click MetropolitanEmploymentAreas and choose Remove.

    After you remove the layer, only the new Shikoku_Rural layer is visible.

    Note:

    The default symbology of the copy is random and may differ from the example images.

    Rural municipalities on Shikoku

  14. On the Quick Access Toolbar, click the Save button.

    Save button

    Your project is saved.

Add population data

Now that you've identified rural municipalities in the Shikoku region of Japan, you'll add population data, which you'll need to calculate the percentage of population within 2 kilometers of all-season roads.

In Japan, population estimate data is collected at the cho-cho-moku level. Cho-cho-moku are small administrative regions within municipalities. First, you'll add a layer of all cho-cho-moku in Shikoku. Then, you'll clip the layer to contain only cho-cho-moku in rural municipalities.

  1. On the ribbon, on the Map tab, in the Layer group, click Add Data.
  2. In the Add Data window, if necessary, click ArcGIS Online. Search for Shikoku Cho-cho-moku owner:Learn_ArcGIS.

    Search for Shikoku Cho-cho-moku

  3. Select the Shikoku Cho-cho-moku layer and click OK.

    The cho-cho-moku are added to the map. (The dataset has a large number of features and may take a few moments to load.)

    Next, you'll use another geoprocessing tool to clip the extent of the cho-cho-moku layer so that only cho-cho-moku in rural areas are shown. Cho-cho-moku are subdivisions of municipalities, so cho-cho-moku boundaries fit exactly within municipality boundaries.

  4. In the Geoprocessing pane, click the Back button.

    Back button

    Tip:

    If you closed the Geoprocessing pane, you can reopen it. On the ribbon, click the Analysis tab. In the Geoprocessing group, click Tools.

  5. Search for and open the Clip tool.

    Clip tool

  6. For the Clip tool, enter the following parameters:

    • For Input Features, choose Shikoku Cho-cho-moku.
    • For Clip Features, choose Shikoku_Rural.
    • For Output Feature Class, change the output name to Shikoku_Rural_Population.

    Clip tool parameters

  7. Click Run.

    The tool runs. After a few moments, the new layer is added to the map. Currently, you can't see the new layer because it is obscured by the original cho-cho-moku dataset.

  8. In the Contents pane, right-click the Shikoku Cho-cho-moku layer and choose Remove.

    The clipped layer is now visible.

    Rural cho-cho-moku in Shikoku

    You now have rural population data at the cho-cho-moku level for Shikoku.

  9. Save the project.

In this lesson, you added nationwide municipal data to a new map. You created a query to limit that data to Shikoku and created a new dataset with only rural municipalities. Then, you added population estimate data and clipped it to the rural municipalities. Your map now only contains data for your study area.

In the next lesson, you'll use this data to calculate the percentage of rural population within 2 kilometers of all-season roads.


Evaluate road access

In the previous lesson, you added and filtered municipality and population data to your map. In this lesson, you'll add all-season road data. Then, you'll create a 2-kilometer buffer around the roads and estimate the percentage of rural population within that buffer. Your result will give an idea of how well the Shikoku region follows the United Nations' SDG Indicator 9.1.1, a measure of sustainable development.

Buffer road data

First, you'll add all-season road data to the map. An all-season road, according to the metadata for Indicator 9.1.1, is "a road that is motorable all year round by the prevailing means of rural transport (often a pick-up or a truck which does not have four-wheel-drive)."

For the Shikoku region, the emergency transportation road system best meets the requirements for an all-season road. You'll add this data to the map and create a 2-kilometer buffer around it.

  1. If necessary, open your SDG_Japan project in ArcGIS Pro.

    You'll add the emergency transportation road data from ArcGIS Online. This dataset came from Japan's Ministry of Land, Infrastructure, Transport and Tourism, which maintains National Land numerical information on a variety of transportation and land-use topics.

  2. On the ribbon, click the Map tab. In the Layer group, click the Add Data button.
  3. In the Add Data window, click ArcGIS Online and search for All-Season Emergency Roads owner:Learn_ArcGIS.
  4. In the list of search results, select the All-Season Emergency Roads layer and click OK.

    The layer is added to the map.

    All-season emergency roads in Shikoku

    Next, you'll use a geoprocessing tool to create a 2-kilometer buffer around the roads.

  5. On the ribbon, click the Analysis tab. In the Geoprocessing group, click Tools.
  6. In the Geoprocessing pane, search for and open the Buffer tool.

    Buffer tool in the Geoprocessing pane

  7. Change the following parameters (do not run the tool yet):

    • For Input Features, choose All-Season Emergency Roads.
    • For Output Feature Class, change the output name to All_Season_2km_Buffer.
    • For Distance, type 2 and choose Kilometers.

    Buffer tool parameters

    These parameters will create a 2-kilometer buffer around each road feature on the map. Because the road features are connected to one another, this will lead to many overlapping buffers. You'll change the dissolve type so that instead of multiple buffer features, the output creates a single feature.

  8. For Dissolve Type, choose Dissolve all output features into a single feature.

    Dissolve Type parameter for the Buffer tool

  9. Click Run.

    The new layer is added to the map.

    Road buffers in Shikoku

    Next, you'll clip the rural cho-cho-moku to the buffer. The output layer will show the portions of rural cho-cho-moku within 2 kilometers of an all-season road.

  10. In the Geoprocessing pane, click the Back button. Search for and open the Clip tool.
  11. For Input Features, choose Shikoku_Rural_Population, and for Clip Features, choose All_Season_2km_Buffer. For Output Feature Class, change the output name to Rural_2km_Buffer.

    Clip tool parameters

  12. Click Run.

    The layer is added to the map.

  13. In the Contents pane, uncheck All-Season Emergency Roads, All_Season_2km_Buffer, Shikoku_Rural_Population, and Shikoku_Rural.

    Rural population data clipped to road buffers in Shikoku

Estimate population by area

Unlike when you clipped the cho-cho-moku layer to the municipalities layer, the boundaries of the cho-cho-moku do not line up with the boundaries of the buffer. Because of this, only portions of many cho-cho-moku are represented in the clipped layer.

It wouldn't be accurate to use the full population of the cho-cho-moku for your estimations if only part of the cho-cho-moku is close to roads. To account for this problem, you'll calculate each cho-cho-moku's population proportional to its area within the buffer.

  1. In the Contents pane, right-click the Shikoku_Rural_Population layer and choose Attribute Table.

    Attribute Table option

    The attribute table for Shikoku_Rural_Population opens. The columns are fields, and the rows are each cho-cho-moku.

    In the Shape_Area field, the first cho-cho-moku area (ObjectID 1) has an area of 36,915,164 square meters.

  2. Open the attribute table for Rural_2km_Buffer and look at the Shape_Area value for ObjectID 1.

    Area of clipped cho-cho-moku

    The area value is about 21,388,602 square meters, smaller than the value for the same area in the Shikoku_Rural_Population table because the Clip tool automatically calculates a new Shape_Area value after the tool runs.

    Next, you will calculate the rural population within the 2-kilometer buffer by joining data from the two layers and calculate the percentage of each cho-cho-moku's area.

  3. In the attribute table for Rural_2km_Buffer, click the Add Field button.

    Add Field button

    The fields view opens. In this view, you can add, edit, or remove fields. A new field has already been added to the bottom row. You'll change its settings.

  4. In the final row, for Field Name, type Area_Proportion. For Alias, type Percent Area in Buffer. For Data Type, choose Double.

    Percent Area in Buffer field

  5. Click under the new field to add another field. Give the field the following settings:

    • For Field Name, type Pop_Proportion.
    • For Alias, type Population in Buffer.
    • For Data Type, choose Long.

    In the attribute table, the new fields are added, but the data is currently null. You will calculate the values in later steps.

  6. For the Shape__Area field, double-click the Alias cell and type Clip Area.

    Updated Shape_Area alias

  7. On the ribbon, on the Fields tab, in the Changes group, click Save.

    Save button

  8. In the Contents pane, right-click Rural_2km_Buffer, point to Joins and Relates, and choose Add Join.

    Add Join option

    The Add Join window appears.

  9. Set the following parameters:

    • For Input Table, choose Rural_2km_Buffer.
    • For Input Join Field, choose ID.
    • For Join Table, choose Shikoku_Rural_Population.

    Click Validate Join and click OK.

  10. Open the attribute table for Rural_2km_Buffer and scroll to the right.

    Fields added to attribute table from join

    The fields from Shikoku_Rural_Population are now in the Rural_2km_Buffer layer's attribute table. The added Shape_Area field is the area of the entire cho-cho-moku.

  11. Right-click the Shape_Area field and select Fields to open the fields view.
  12. Double-click the Alias cell for Shikoku_Rural_Population.Shape_Area and rename it Cho-cho-moku area.

    Alias for the added area field

    Now you can calculate data for the null fields by creating an expression. First, you'll calculate the proportion of each cho-cho-moku's area in the 2-kilometer buffer.

  13. Close the fields view. If prompted to save changes, click Yes.
  14. In the attribute table, right-click the header for the Percent Area in Buffer field and choose Calculate Field.

    Calculate Field option

    The Geoprocessing pane opens to the Calculate Field tool. To find the proportion of area, you'll divide the clipped area by the cho-cho-moku area.

  15. In the tool parameters, for Expression, in the Fields list, double-click Rural_2km_Buffer.Shape_Area.

    Building an expression

    The field is added to the expression.

  16. Click the division symbol and double-click Cho-cho-moku Area.

    Your final expression reads as follows:

    !Rural_2km_Buffer.Shape_Area! / !Shikoku_Rural_Population.Shape_Area!

    Expression to calculate the Area_Proportion field

  17. Click OK.

    The Percent Area in Buffer field now shows the amount of each cho-cho-moku within the 2-kilometer buffer, expressed as a rate or percentage. Using these values, you'll estimate the population of each cho-cho-moku that is within the buffer by multiplying the area rate by the total population.

  18. For the Calculate Field tool, change the following parameters:

    • For Field Name, choose Population in Buffer.
    • For Expression, delete the current expression and build or type the following expression:

    !Rural_2km_Buffer.Area_Proportion! * !Shikoku_Rural_Population.D0001!

    Calculate Field tool parameters to estimate the population in the buffer

  19. Click OK.

    The Population in Buffer field is calculated. The result is an estimation of the population of each cho-cho-moku that is within the 2-kilometer buffer.

Summarize the total population

You've estimated the population within each cho-cho-moku that lives within the buffer. Next, you'll summarize these values to find the total population. Then, you'll compare that value to the total rural population in Shikoku to estimate the percentage of the population with access to all-season roads.

  1. In the attribute table, right-click the ObjectID heading and choose Summarize.

    Summarize option

    In the Geoprocessing pane, the Summary Statistics tool opens. This tool summarizes information in an attribute field based on parameters you specify. You'll run it to find the sum of all the population in the buffer.

  2. For the Summary Statistics tool, enter the following parameters:

    • For Output Table, change the output name to Shikoku_Rural_Access.
    • For Statistics Field(s), for Field, choose Rural_2km_Buffer.Pop_Proportion.
    • For Statistic Type, choose Sum.

    Summary Statistics tool parameters

  3. Click OK.

    The tool runs and the Shikoku_Rural_Access table is added to the Contents pane, under Standalone Tables.

  4. Close the Rural_2km_Buffer attribute table.

    Before you open the table you created, you'll run the Summary Statistics tool again. This time, you'll calculate the total rural population in Shikoku using the Shikoku_Rural_Population layer.

  5. Open the Geoprocessing pane, and search for and open the Summary Statistics tool.
  6. In the Summary Statistics tool, change the following parameters:

    • For Input Table, choose Shikoku_Rural_Population.
    • For Output Table, change the output name to Total_Rural_Population.
    • For Statistics Field(s), for Field, choose 2015 Total Population.
    • For Statistic Type, choose Sum.

  7. Click Run.

    The Total_Rural_Population table is added to the Contents pane. Next, you'll compare the summarized values in the two tables.

  8. In the Contents pane, right-click Shikoku_Rural_Access and choose Open.

    The table has three fields. The SUM_Pop_Proportion field has a value of 736,316. This value represents the estimated rural population living within 2 kilometers of an all-season road in the Shikoku region. You'll copy this value to compare it to the total rural population.

  9. Double-click the SUM_Pop_Proportion value to edit it and press Ctrl+C to copy.

    Copying the cell value

  10. In the Contents pane, right-click the Total_Rural_Population table and choose Open.

    In this table, the SUM_D0001 field shows the total rural population in Shikoku: 872,986. You'll create a new field and calculate the percentage of the population with all-season road access.

  11. Click the Add Field button. Add a field with the following parameters:

    • For Field Name, type Percent_Access.
    • For Alias, type Percent Rural Access.
    • For Data Type, choose Long.

  12. On the ribbon, on the Fields tab, in the Changes group, click Save. Close the fields view.
  13. In the Total_Rural_Population table, right-click the Percent Rural Access heading and choose Calculate Field. In the Calculate Field tool, press Ctrl+V to paste the value you copied in step 9, and create the expression (736316 / !SUM_D0001!) * 100 and click OK.

    Parameters for Calculate Field tool

    Based on your analysis, you can estimate that about 84 percent of Shikoku's rural population lives within 2 kilometers of an all-season road.

    Percent Rural Access field calculated

    Based on your analysis, you can estimate that about 80 percent of Shikoku's rural population lives within 2 kilometers of an all-season road.

  14. Close the tables and save the project.

In this lesson, you added all-season road data and performed proximity analysis by creating a 2-kilometer buffer around roads. You then estimated the population of each cho-cho-moku that intersected the buffer. Afterward, you determined the percentage of the total rural population that lives within 2 kilometers of an all-season road. Using the summary tables you created, you can now report on SDG Indicator 9.1.1 regarding the Shikoku region in Japan.

This workflow can be used for SDG Indicator 9.1.1 reporting in other regions or countries. The spatial analysis techniques you learned can also be employed to gain demographic insight on other key issues.

You can find more lessons in the Learn ArcGIS Lesson Gallery.