Interpolate values

Open, save, and explore a map of Oaxaca, Mexico

In this section, you'll open a map, save a copy, and explore the layers you will use to predict elevation in Oaxaca, Mexico.

  1. Open the Interpolate elevation values map in ArcGIS Online.

    A map with two layers and a basemap appears.

    Map of Oaxaca, Mexico

  2. At the top of the page, click Sign In and sign in to your ArcGIS account.
    Note:

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

    You'll save a copy of the map in your account.

  3. On the ribbon, click Save and choose Save As.

    Save As

  4. In the Save Map pane, for Title, type Interpolate elevation values followed by your initials.

    You'll use the tags and summary from the original map. Tags are terms that allow people to search for your map. The summary provides information so people will understand your map's purpose.

    Save Map pane filled in

  5. Click Save Map.

    Your map is saved to your ArcGIS Online account.

    You'll investigate the data you'll use. The Elevation points layer shows where elevation values were measured on the ground, and the Oaxaca State Boundary layer shows the outline of the state in the country of Mexico.

  6. In the Details tab, click Content.

    Content tab

  7. Point to the Elevation points layer and click Table.

    Table button

    The table of attributes opens. Attributes are information about a map feature.

  8. Review the data in the table by scrolling up and down. Look for how many data points there are, the range of elevation values, and the unit of measure.

    Elevation points table

    Scrolling is one way to learn about your data. You'll try another way.

  9. In the table, click the Elev_meter field to open a menu and click Statistics.

    Statistics in menu

    A table with summary information for the selected Elev_meter field appears. The summary table is a quick way to learn about a field.

    Statistics pane

  10. Close the Statistics pane.

    Statistics pane Close button

  11. For the Elevation points layer, click Close Table.

    Elevation points Close Table button

Interpolate elevation patterns

In this section, you'll create a continuous elevation layer for the state of Oaxaca from the elevation points.

The map shows the elevation at 199 locations across the state of Oaxaca. When you interpolate points, you mathematically predict data values for the locations without values. The result is a continuous layer with ranges of values symbolized in different colors to help identify patterns.

Interpolation works with continuous data. Continuous data has a value at every location, and that value is only a little different from the value of a neighboring location. Temperature is a good example of continuous data. There is a measurable value everywhere on Earth, and in general, the temperature a kilometer or mile from where you are now is likely to be close to the temperature where you are. It might be a little higher or a little lower, but it's unlikely to be 20 or more degrees higher or lower. Elevation, the height of land above or below a reference level, is continuous data, too.

  1. Point to the Elevation points layer and click Perform Analysis.

    Perform Analysis

  2. Click Analyze Patterns.

    Analyze Patterns

  3. Click Interpolate Points.

    Interpolate Points

    You'll fill in the fields in the pane for the analysis.

  4. In the Interpolate Points pane, enter the following:

    • For Choose point layer containing locations with known values, confirm that Elevation points is selected.
    • For Choose field to interpolate, choose Elev_meter.
    • For Optimize for, confirm that the default, halfway between Speed and Accuracy, is set.

    Interpolate Points pane

  5. In the Interpolates Points pane, expand Options.

    You want the new layer to cover only the state, not the entire country.

  6. Under Options, set the following parameters:
    • For Clip output to, select Oaxaca State Boundary.
    • For Classify by, select Equal Interval.
    • For Number of classes, confirm that 10 is selected.

    Interpolate Points pane

    The results will be areas on the map. The Equal Interval method indicates that the areas should be created so that the range of predicted values is about the same for each area.

  7. For Result layer name, type Continuous elevation followed by your initials.

    Note:

    You cannot create two layers in an ArcGIS organization with the same name. Adding your initials to a layer name ensures that other people in your organization can also complete this lesson. Once a layer has been created, you can rename it in the map to remove your initials, which will not affect the name of the underlying data layer.

    Add Result layer name.

  8. Uncheck the Use current map extent box.
  9. Click Run Analysis.

    After a few moments, the new layer is added to the top of the Content pane and drawn on the map. The Continuous elevation layer includes the 10 classes, each symbolized in a different color. The darker classes have higher elevation, and the lighter ones have lower elevation.

    Map of Oaxaca with elevation symbolized

  10. For the Continuous elevation layer, click Show Legend to view the legend.

    Show Legend button

    The legend appears.

    Elevation legend

    The legend shows the range for each color. Since you chose the Equal Interval option, each of the 10 classes spans 296.3 meters.

  11. Uncheck the Oaxaca State Boundary layer to turn it off.
  12. On the map, click one of the lighter-colored areas.

    A pop-up indicates that the prediction is a range of elevations from a minimum to a maximum.

    Pop-up with elevation range attributes

  13. Close the pop-up, and on the ribbon, click Save and choose Save to save your map.

    Save

Open, save, and explore a map of India

In this section, you'll open a map, save a copy, and explore the layers you will use to predict air quality in India.

  1. Open the Interpolate air quality values map.

    A map with three layers and a basemap, centered on India, appears.

    Map of current air quality in India

    Note:

    The Recent Conditions in Air Quality (World) and Recent Conditions in Air Quality (India) layers are updated regularly. This means the maps you see that include these layers will look different from the images in this lesson. The layers you see will reflect the most recent data.

    You'll save a copy of the map.

  2. On the ribbon, click Save and choose Save As.
  3. In the Save Map pane, for Title, type Interpolate air quality values.

    Save Map pane filled in

  4. Click Save Map.

    Your map is saved to your ArcGIS Online account.

    You'll investigate the data you'll use. The Item Details page contains information about the source of data in a layer.

  5. In the Details tab, click Content.
  6. Point to the Recent Conditions in Air Quality (World) layer and click More Options.

    More options button

  7. Click Show Item Details.

    Show Item Details

    A new browser tab opens with details about the Recent Conditions in Air Quality (World) layer.

  8. Review the information and note where data is collected, how often the layer is updated, and how recent data must be to be included.
  9. Close the Item Details tab for the Recent Conditions in Air Quality (World) layer in your browser.

    You'll look at the data for air quality beyond India by using a bookmark. Bookmarks allow you to move to specific saved extents of a map.

  10. On the browser tab with the Interpolate air quality values map, on the ribbon, click Bookmarks.

    Bookmarks

  11. From the Bookmarks menu, choose World.

    World bookmark

    The map extent changes to show the world.

    Look at the map and note in which countries air quality data points appear. Do most countries have data points, or only some countries? For the countries that have data points, are they distributed evenly? Why would that matter if you plan to use interpolation?

  12. From the navigation tools, choose Default extent.

    Default extent

    The map changes extent to center on India again.

  13. For the Recent Conditions in Air Quality (World) layer, click Show legend.

    Review the legend to understand the symbols on the map. The upper half of the legend shows how the size and color of the symbol illustrate the air quality. Darker colors and larger symbols mean more pollutants and worse air quality. Lighter colors and smaller symbols mean fewer pollutants and better air quality.

  14. For the Recent Conditions in Air Quality (World) layer, click Hide legend.

    Hide legend button

    While you could use all of the data points in the Recent Conditions in Air Quality (World) layer to predict the air quality in India, you will use only those in India.

  15. For the Recent Conditions in Air Quality (World) layer, uncheck the box to turn it off.
  16. For the Recent Conditions Air Quality (India) layer, click the More Options button and rename the layer to Air Quality (India).

    Rename the layer

    This layer includes air quality data from Recent Conditions in Air Quality (World) but only for locations in India.

  17. Check the box next to the Air Quality (India) to turn the layer on.
  18. For the Air Quality (India) layer, click Table to review the air quality data for India.

    Which field includes the air quality value? What is the date of the most recent measurement? What is the range of values within India?

  19. For the Air Quality (India) layer, click Close Table.

Interpolate air pollution patterns

In this section, you'll create a continuous air quality layer for India.

  1. Point to the Air Quality (India) layer and click Perform Analysis.
  2. Click Analyze Patterns, then choose Interpolate Points.
  3. For Choose point layer containing locations with known values, confirm that Air Quality (India) is selected.
  4. For Choose field to interpolate, choose value.
  5. For Optimize for, confirm that the default, halfway between Speed and Accuracy, is set.

    Interpolate Points pane

  6. Expand Options and set the following.

    You want to the prediction layer to cover only India.

    • For Clip output to, select India Country Boundary.
    • For Classify by, select Geometric Interval.
    • For Number of classes, choose 5

    Interpolate Points pane

    The results will be put into classes. The Geometric Interval method classifies data based on a geometric progression. It is useful for visualizing data that is not distributed normally, or when the distribution is highly skewed.

  7. For Result layer name, type Continuous air quality followed by today's date and your initials.

    Continuous air quality layer name.

  8. Uncheck the Use current map extent box.
  9. Click Run Analysis.

    After a few moments, the new layer is added to the top of the Content pane and drawn on the map.

    Map of air quality in India

    Note:

    The Recent Conditions in Air Quality (India) layer is updated regularly. This means the results of your analysis that use this layer will look different from the images in this lesson.

  10. Turn off the Air Quality (India) layer.

    Map of air quality in India with recent conditions off

    The Continuous air quality layer includes the classes with each symbolized in a different color. The darker classes have higher air quality values, meaning poorer air quality, while the lighter classes have lower air quality values, meaning better air quality.

  11. Click one of the colors to see the range of air quality predicted for that area.

    Map of air quality pop-up

    How confident would you be about these predictions? Remember that the Interpolate Points tool can be used to find patterns, but it does not have the detail you would get if you measured the air quality at a specific location.

    Remember too, from reading the description of the data, that measurements up to 30 days old can be included in the air quality dataset. So, if there was a wildfire or other event that impacts air quality 27 days ago, and that was the most recent measurement from that sensor in India, it would be included in the current data.

  12. Save your map.

In this lesson, you used sample point data to predict patterns of continuous phenomena. You used elevation measurements taken at 199 points in Oaxaca, Mexico, to create a continuous layer to show the high and low areas in the state. Then you used today's air quality data to create a continuous layer to show the pattern of air quality across India.

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