Add boundary and malaria data

First, you'll process large general datasets to remove unnecessary information and focus only within your geographic area of interest. To do this, you'll access global boundary files from the United Nations Second Administrative Level Boundaries (UN SALB). The boundary files will serve as reference data needed to analyze and visualize population and malaria incidence later in the tutorial.

Access boundary data

The SALB program provides a global repository of authoritative geospatial data for countries down to the second subnational level. It provides reliable, disaggregated geospatial information to measure and track SDG goal progress.

  1. Go to the data page for the Democratic Republic of the Congo on the United Nations SALB website.

    Several dataset file types are available for download. The CSV and Excel data options will only provide a table and not the polygon shapes of the boundaries. The GeoJSON and Rest API options allow you to create a layer from a URL. The Shapefile and Map Viewer options are additional file types you can use to create a copy of the feature class in your ArcGIS account. For this tutorial, you want to create your own copy of a feature class of the secondary administrative level boundaries, so you will use the GeoJSON link to create the feature class layer.

  2. Under Geospatial Datasets, for the most recent Administrative units (Polygon), right-click GeoJSON and click Copy link address.

    Copy link address for the GeoJSON button for Administrative units (Polygon) under the Geospatial Datasets section

    You now have the URL to the GeoJSON in your computer clipboard. Next, you will open a blank map in ArcGIS Online.

    Tip:

    The URL is https://geoportal.un.org/arcgis/sharing/rest/content/items/53ccd2a327e8402a892be58c6ffa595a/data.

  3. Sign in to your ArcGIS organizational account.
    Note:

    If you don't have an organizational account, see options for software access.

  4. On the ribbon, click Map.

    Map on the ribbon

    A blank map appears in Map Viewer.

  5. On the Contents (dark) toolbar, click Add and choose Add layer from URL.

    Add layer from URL in the Add menu

  6. In the Add Layer window that appears, for URL, paste the GeoJSON URL you had copied. For Type, choose GeoJSON and click Next.

    URL and Type set in the Add Layer window.

  7. For How would you like to add this file? Choose Create a hosted feature layer and add it to the map and click Next.
  8. On the next page, enter the following:
    • For Title, type DRC_SALB and add your name or initials.
    • For Tags, type DRC, UN, and SALB, pressing Tab or Enter after each tag.
    • For Summary, type Secondary administrative level boundaries for the Democratic Republic of Congo from the UN SALB program.
    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 tutorial. 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.

  9. Click Create and add to map.

    The DRC_SALB layer is created and added to your map.

    The secondary administrative level boundaries layer added to the map.

    Before you continue, it is good to save your web map progress.

  10. On the Contents toolbar, click Save and open and choose Save as.

    Save as on the Save and open menu

  11. In the Save map window that appears, enter the following:
    • For Title, type DRC malaria rates and add your name or initials.
    • For Tags, type DRC, UN, SDG 3, and malaria, pressing Tab or Enter after each tag.
    • For Summary, type Web map showing progress towards the UN SDG goal 3 for malaria in the Democratic Republic of Congo by second level administrative boundaries.

    Save map window

  12. Click Save.

You have added boundary data from the UN SALB. Next, you'll add malaria incidence rate data to your map.

Download and prepare malaria data

The Malaria Atlas Project (MAP) is a World Health Organization (WHO) partner for collecting malaria incidence data across the world. The smallest disaggregated data available is at the first level administrative boundary. Since you have boundary data at the second administrative level, you will use imagery layer data for malaria incidence rates and use the Zonal Statistics as Table tool to join it to your boundary data. Being able to monitor and analyze disease rates at smaller administrative boundaries can aid in more targeted and strategic interventions.

Note:

The Malaria Atlas Project publishes count and incidence data in an aggregated format as well.

Since the UN SDG goal is to reduce the rate of malaria by 90 percent from 2016 to 2030, you will obtain the imagery layers for 2016 and 2020 to analyze the progress toward this goal so far.

  1. Go to the Malaria Atlas Project's Data page.

    The Data page provides a lot of useful information about the rate and count of two major types of malaria parasites. You will use this data page to download the pixel data, or imagery layer, showing the incidence rate of the Pf parasite, which is the most prevalent strain, for the DRC for the years 2016 and 2020.

  2. On the upper left of the page, click the Maps tab.

    Maps tab on the Malaria Atlas Project's Data page

  3. Under Layer Catalogue, click Malaria.

    Malaria in the Layer Catalogue list

  4. For Global Pf Incidence Rate, click the Download button.

    The Download button for the Global Pf Incidence Rate dataset

  5. In the Download Layer(s) from selection window, for Extent Options, choose Clip to Country. Click Select a Country to clip to, and in the drop-down menu that appears, in the search bar, type Congo and choose Democratic Republic of the Congo.

    Clip to Country and Democratic Republic of the Congo selected.

  6. Click Download.

    A zip file downloads with a separate imagery layer for each year of data, from 2000 to 2020 for the DRC.

    Note:

    If you encountered an issue with downloading the data, download a copy of the imagery data for 2016 and 2020.

  7. Extract the zip file you downloaded.

    The unzipped file contains imagery data for each year of data. You are interested in the imagery file for 2016 and 2020.

  8. In a new browser window or tab, go to your ArcGIS Content page.
  9. Click New item.

    New item on the Content page

  10. In the New item window, choose Imagery layer.

    Imagery layer in the New item window

    The Create imagery layer window appears, open to the Step 1 Get started page.

  11. For Choose the layer types that best suit your needs, ensure that Tiled Imagery Layer is selected and click Next.
  12. For Choose a layer configuration based on your imagery, choose Multiple Imagery Layers and click Next.
  13. On the next page, for Select input imagery, click Browse.
  14. In the Open window, browse to your extracted folder and hold the Ctrl key and click the 2016 and 2020 imagery files to select both.
    Note:

    If you are using the provided zip file, there will only be two imagery files available.

    2016 and 2020 clipped imagery layers in the unzipped folder

  15. Click Open.

    The files are added under Select input imagery. The Upload status column shows the uploading progress. When it is complete, the status bar turns green.

    Upload status shows the two imagery layers have completed uploading.

  16. Click Next.
  17. On the Set item details page, for Title, click Define title.
  18. In the Define the title template for imagery layers window, click Prefix and type DRCMalaria. Click Suffix and type your name or initials.

    The Prefix and Suffix entered in the Define the title template for imagery layers window.

  19. Click Apply.
  20. For Tags, type malaria, drc, and incidence rate, pressing Tab or Enter after each tag. Optionally, you can enter text for the Summary and save the imagery layers to a folder of your choosing.

    Tags entered in the Tiled Imagery Layer window.

  21. Click Create.

You have created two imagery layers showing the malaria incidence rate clipped to the DRC. Next, you will add this data to your web map.

Add malaria data to the map

You will add the imagery layers of malaria incidence rates for 2016 and 2020 to your web map. You will also rename the layers so they are shorter and more readily understandable.

  1. Open the browser tab with your DRC malaria rates web map.
  2. If necessary, on the Contents toolbar, click Layers. In the Layers pane, click the Add button.

    Add button in the Layers pane

    The Add layer pane appears, open to layers in My Content.

  3. In the Add layer pane, for the imagery layers you just created, click the Add buttons.

    Add buttons for the created imagery layers

    The layers are added to your map.

  4. In the Add layer pane, click the back button.

    You now have three layers on your map. Before you continue, you will rename the layers so they are shorter and easier to work with.

  5. For the DRC_SALB layer, click the Options button and click Rename.

    Rename in the options for the added DRC SALB layer created from the UN SALB GeoJSON

  6. Rename the layer DRC_SALB.
  7. Use what you have learned to rename the imagery layers Incidence raster 2016 and Incidence raster 2020 accordingly.

    The layer names are updated.

    Layers renamed in the Layers pane.

The layers are added and ready for further analysis.

In the next section, you will use analysis tools to connect or join the data from the imagery data to the administrative boundary data.

Join malaria data to boundary data

The imagery data you created provides incidence data as pixel data. This is useful information to get very fine-grained information. But you are interested in making policy and funding decisions at the administrative boundary levels. You will use analysis tools to summarize the incidence rates within each of the secondary administrative boundary levels.

Calculate incidence rates by administrative boundaries

First, you will use the Zonal Statistics as Table analysis tool to calculate the average rate of malaria incidence by the secondary level administrative boundaries for 2016 and 2020. The results of this analysis will produce two tables with a summary of malaria incidence by administrative boundary.

Note:

If you do not have a license for ArcGIS Image for ArcGIS Online, you can add the MalariaRate2016_SALB and MalariaRate2020_SALB (Learn) (Learn) tables to your map instead and skip to the next section to continue the tutorial.

To add the tables, on the Contents pane, click Tables. Click the Add button. Search ArcGIS Online for MalariaRate owner:Learn_ArcGIS and click the Add button for the two tables.

  1. On the Settings toolbar, click Analysis. In the Analysis pane, click Tools.

    Tools in the Analysis pane

  2. In the search bar, type zonal statistics and choose Zonal Statistics as Table.

    Zonal Statistics as Table tool in the Tools pane

  3. In the Zonal Statistics as Table tool, enter the following:
    • For Input zone raster or features, choose DRC_SALB.
    • For Zone field, choose adm2nm and click Select.
    • For Input value raster, choose Incidence raster 2016.

    Parameters entered in the Input layers section in the Zonal Statistics as Table tool pane.

  4. In the Statistical analysis settings section, enter the following:
    • For Statistic type, choose Mean.
    • For Output table name, type MalariaRate2016_SALB.

    The Statistic type and Output table name entered in the Zonal Statistics as Table tool pane.

  5. Above the Run button, click Estimate credits.

    Estimate credits link

    To run this tool will require 1 credit.

    Note:

    To learn more about credits, see Understand credits.

  6. Click Run.

    It may take a few minutes to complete.

  7. Click the History tab in the Analysis pane.

    History tab in the Analysis pane

    As the tool runs, you can view the tool progress.

    When the tool has completed running, the table is added to your map in the Tables pane.

  8. On the Contents toolbar, click Tables.

    Tables on the Contents toolbar

    The blue dot next to Tables indicates that a new table has been added.

  9. In the Tables pane, click MalariaRate2016 SALB - ZonalStatisticsTable.

    The table appears.

  10. If necessary, scroll until you see the Mean heading.

    MEAN field heading in the table for MalariaRate2016 SALB

    The Zonal Statistics as Table tool calculated the mean malaria incidence rate within each secondary administrative level. To make this number more understandable, you will need to multiply it by 1,000 to get the rate per 1,000 population. You will use Arcade later in the tutorial to accomplish this, but first, you need to use the Zonal Statistics as Table tool to calculate the mean incidence rates for 2020 data.

    You can rerun a tool in Map Viewer using all the same parameters. You will open the tool with all the same settings that you ran for the 2016 incidence data, but will adjust it for the 2020 incidence data and run it to create the table for 2020 incidence data.

  11. Close the table.
  12. In the Analysis pane, if necessary, click the History tab.
  13. For the most recent Zonal Statistics as Table tool, click the options button and click Open tool.

    Open tool in the options menu for the Zonal Statistics as Table tool on the History tab in the Analysis pane

  14. In the Zonal Statistics as Table tool, adjust the following:
    • For Input value raster, choose Incidence raster 2020.
    • For Output table name, type MalariaRate2020_SALB.

    Parameters for Incidence raster 2020 in the Zonal Statistics as Table tool

  15. Click Run.
    Note:

    To run this analysis tool will require 1 credit.

  16. On the Contents toolbar, click Save and Open and click Save to save the map.

You now have two tables with malaria incidence rates in 2016 and 2020 summarized to the secondary administrative level in the DRC. The data is only a table, so next, you will join the data to the feature class layer so you can visualize the data on the map.

Join tables to the boundary layer

In this section, you will join the data from the zonal statistics tables to the DRC_SALB layer. This will enable you to visualize the summarized incidence rates in 2016 and 2020 by the administrative boundaries.

  1. In the Zonal Statistics as Table tool pane, click the back arrow to return to the Tools pane.
  2. In the Tools pane, click the back arrow. On the Tools tab, search for and click the Join Features tool.

    Join Features tool in list of results on the Tools tab in the Analysis pane

    The Join Features tool opens.

    To join features, you will choose the target layer, the layer you want to add data to. In this scenario, you want to add data to the DRC_SALB layer. You will also choose the Join layer, the layer or table containing the data you want to join. The MalariaRate2016 SALB - ZonalStatisticsTable table contains the data you will join to the DRC_SALB layer.

  3. In the Join Features tool, for Target layer, choose DRC_SALB. For Join layer, choose MalariaRate2016 SALB - ZonalStatisticsTable.

    Parameters entered in the Input features section of the Join Features tool pane.

  4. Under Join settings, in the Attribute relationships section, for Target field, choose adm2nm. For Join field, choose adm2nm.

    Target field and Join field parameters entered in the Join settings section in the Join Features tool pane.

  5. Under Result layer, for Output name, type DRCSALB_2016.
  6. Click Run.
    Note:

    To run this tool will require 0.418 credits.

    A new layer, DRCSALB_2016, is added to the Layers pane.

  7. In the Layers pane, click the options button for the DRCSALB_2016 layer and choose Show table.
  8. In the DRCSALB_2016 table, scroll to the MEAN field.

    The 2016 incidence rate values from the MalariaIncidence2016 SALB table are joined by the second level administrative boundary feature layer.

    Next, you will use the Join Feature tool again to make another layer that will include both the 2016 and 2020 rates for the secondary administrative boundaries.

  9. In the Join Features tool, update the following:
    • For Target layer, choose DRCAdmin_2016.
    • For Join layer, replace the existing layer with the MalariaRate2020 SALB layer.
    • For Output name, type DRCSALB_2016_2020.
  10. Click Run.
    Note:

    To run this tool will require 0.418 credits.

  11. Open the table for DRCSALB_2016_2020 and review the MEAN and MEAN 1 fields.

    The MEAN field contains the mean incidence rates for 2016 data and the MEAN 1 field contains the mean incidence rates for 2020 data.

    Joined fields in the DRCSALB 2016 2020 table

Style by incidence rates

Since the UN SDG goal describes incidence rates per 1,000 persons, you will use Arcade to multiply the incidence rate values by 1,000 so you can visualize the data in the same unit as the goal.

  1. In the Layers pane, click the Hide layer button for all the layers except the DRCSALB_2016_2020 layer.
  2. In the Layers pane, ensure the DRCSALB_2016_2020 layer is selected. On the Settings toolbar, click Styles.
  3. In the Styles pane, for Choose attributes, click Expression.

    Expression button under Choose attributes in the Styles pane

  4. In the New Expression window, click the Profile variables tab. Click the arrow for $feature.

    Arrow for $feature on the Profile variables tab in the New Expression window

  5. In the list of variables, choose MEAN.

    MEAN variable on the Profile variables tab

    The Arcade code for the variable MEAN adds to the expression.

    Code for the MEAN variable is added as Arcade code in the New Expression window.

  6. At the end of the expression, type *1000.

    Arcade code to calculate incidence rate per 1,000 people in 2016

  7. Click Run to test the expression and ensure there are no errors.
  8. Click New expression to edit the expression title. Type 2016 Incidence Rate per 1,000 and press Tab.

    The expression title updates.

    Expression title updated.

  9. Click Done.
  10. In the Styles pane, choose the Counts and Amounts (color) style.

    Counts and Amounts (color) style under Pick a style in the Styles pane

    The layer is styled by the 2016 incidence rate per 1,000 persons.

    Map showing the 2016 incidence rate of malaria per 1,000 people in the DRC.

    Next, you will style another layer to show the incidence rates in 2020.

  11. In the Layers pane, for the DRCSALB_2016_2020 layer, click Options and choose Duplicate.

    A copy of the layer is added to the Layers pane. You will rename each of these layers so you can remember the data they represent.

  12. Rename the DRCSALB_2016_2020 layer to Incidence SALB 2016. Rename the copied layer Incidence SALB 2020.
  13. Ensure the Incidence SALB 2020 layer is selected and in the Styles pane, click 2016 Incidence Rate per 1,000.
  14. In the Expression window, update the Expression title to 2020 Incidence rate per 1,000 and press Tab.
  15. In the expression, delete the existing code. Use what you have learned to add the MEAN_1 field and multiply it by 1,000.
    Note:

    Click the Profile variables tab, and click the arrow for $feature. Choose MEAN_1. Add *1000 to the end of the expression.

    Arcade code to calculate the rate of the 2020 incidence rate and the expression title updated.

  16. Click Done.
  17. In the Layers pane, turn off the visibility for the Incidence SALB 2016 layer.

    The map is now styled by the 2020 incidence rates.

    Map showing the 2020 malaria incidence rate per 1,000 people in the DRC.

You have joined the malaria incidence data to the secondary level administrative boundaries of the DRC and styled the 2016 and 2020 data by incidence per 1,000 people. At this point, you only have a visual comparison between the incidence rates in 2016 and 2020. It would be more informative if you can calculate the difference between the two incidence rates on the same scale so you can compare the change in incidence rates between the two years.

In the next section, you will style the map to show the progress toward the SDG goal so you can share it with relevant stakeholders working to achieve the goal.

Style the map to monitor progress

SDG goal number three includes reducing the rate of malaria per 1,000 people by 90 percent from 2016 to 2030. To monitor progress, you will style the map to show the percent change between 2016 and 2020, the latest data available, and configure the pop-up so the web map is accessible to stakeholders who are working toward achieving the goal.

Calculate percent change

You will use Arcade to style the map data to show the percent change of incidence rates between 2016 and 2020.

  1. In the Layers pane, duplicate the Incidence SALB 2020 layer.
  2. Rename the copied layer SDG 3 Goal Progress.
  3. In the Styles pane, click the existing expression.

    First, you will use Arcade to define two variables to represent the incidence rate values for each year.

  4. In the Expression window, clear the existing text and type var y2016 =.

    Arcade code to define the variable y2016 in the Expression window

  5. On the Profile variables tab, under $features, choose the MEAN field.
  6. In the Expression window, add the text *1000.

    The y2016 variable defined by the MEAN field multiplied by 1000.

  7. Build the variable y2020 or copy and paste the following code:

    var y2020 = $feature.MEAN_1*1000

    Next, you will calculate the percent change between 2016 and 2020.

  8. On a new line, type or copy and paste return ((y2020 - y2016)/y2016)*100.
  9. Click Run to test the code.

    Run in the Expression window

    The output returns as expected, but there are too many digits after the decimal point. You will use the Round function in Arcade to limit the number of digits that appear after the decimal point.

  10. After the code return, type Round(. At the end of the line of code, type , 2).

    The entire line should now read:

    return Round ((( y2020 - y2016 )/ y2016 )* 100 , 2 )

  11. Click Run.

    Output result

  12. Rename the expression title to Change in incidence rate.
  13. Click Done.

You have used Arcade to calculate the percent change in incidence rate between 2016 and 2020 at each of the secondary level administrative boundaries in the DRC.

Style to show goal progress

Now that your data is prepared and calculated, you will style the map so that it is clear and ready to share with stakeholders to make plans to meet the SDG goal.

  1. In the Layers pane, ensure the SDG 3 Goal Progress layer is selected. In the Styles pane, choose Color and Size.
  2. For Theme, choose Above and below. Click Style options.

    Theme set to Above and below for the Color and Size style and the Style options button.

  3. For Symbol pair, choose Circles with arrows.

    Symbol pair set to Circles with arrows in the Style options pane.

  4. Click the symbol below Symbol style.

    Symbol under Symbol style in the Style options pane

  5. In the Symbol style window, click Fill color and choose the Blue and Red 6 color ramp.
    Tip:

    To see the name of a color ramp, point to the ramp.

    The Blue and Red 6 color ramp in the Ramp window

    In the Style options pane, the histogram shows that the malaria incidence rate of most territories and cities in the DRC has increased between 2016 and 2020. You will adjust the upper boundary so that it is more clear which ones have increased over 100 percent.

  6. In the Style options pane, on the histogram, drag the top slider to 100.

    Top slider on the histogram set to 100.

    The smallest symbols are very small. To make them more visible, you will adjust the Size range.

  7. For Size range, set the left slider to 10.

    Size range set to 10 in the Styles pane.

  8. Click Done twice.

    The layers are styled.

    Map styled to show the percent change values.

    The default basemap is very colorful and has a lot of details. To make the most important data on your map stand out, you will update the basemap to a more neutral and minimal design.

  9. On the Contents toolbar, click Basemap. In the Basemap pane, choose Dark Gray Canvas.

    Dark Gray Canvas basemap in the Basemap pane

    The basemap updates to a more neutral design.

    Basemap updated on the map.

  10. In the Layers pane, remove the following layers:
    • DRC_SALB
    • Incidence raster 2016
    • Incidence raster 2020
    • DRCSALB_2016

    There are only three remaining layers.

    Remaining layers on the map

  11. Save the map.

Configure pop-ups

Next, you will format the pop-ups for the layers. You will only show the pop-ups for the SDG 3 Goal Progress layer, so you will disable pop-ups for the other two layers.

  1. In the Layers pane, click the Incidence SALB 2016 layer to select it. On the Settings toolbar, click Pop-ups.

    Pop-ups on the Settings toolbar

  2. In the Pop-ups pane, turn off Enable pop-ups.

    Enable pop-ups turned off in the Pop-ups pane.

  3. Turn off pop-ups for the Incidence SALB 2020 layer.

    Now you will format the SDG 3 Goal Progress layer pop-ups. Although you already built expressions to style the layers, the attribute expressions in pop-ups are a different profile with different functions. You will build attribute expressions that will be used in the pop-up. First, you will build attributes expressions to use in your pop-up text.

    Note:

    To learn more about Arcade profiles, see the page about Profiles.

  4. In the Layers pane, click the SDG 3 Goal Progress layer. In the Pop-ups pane, under Options, click Attribute expressions.

    Attribute expressions under Options in the Pop-ups pane

  5. In the Attribute expressions pane, click the Add expression button.
  6. Name the expression 2016 Incidence Rate. In the expression, delete the existing text and type Round($feature.MEAN*1000,2).

    Attribute expression for 2016 Incidence Rate

  7. Click Done.
  8. Add another expression for the 2020 Incidence Rate with the code Round($feature.MEAN_1*1000,2).
    Tip:

    In the Attribute expressions pane, click Add expression. Name the expression title 2020 Incidence Rate. In the expression, type Round($feature.MEAN_1*1000,2). Click Done.

  9. Add a third expression titled Percent Change using the following code:
    var y2016 = $feature.MEAN*1000
var y2020 = $feature.MEAN_1*1000
return Round(((y2020-y2016)/y2016)*100,2)
  10. In the Attribute expressions pane, click the back arrow.
  11. Click Title. Delete the existing text and click the Add field button.

    The Add field button for the Title in the Pop-up pane

  12. In the Add field window, choose adm2nm, type a comma, and click the Add field button and choose adm1nm.

    The pop-up title is updated.

    Title for pop-up configured.

  13. For Fields list, click the options button and click Delete.
  14. Click Add content and click Text.

    A text editor appears.

  15. Copy and paste the following text:
    2016 malaria incidence rate: {expression/expr0} per 1,000
2020 malaria incidence rate: {expression/expr1} per 1,000
Percent change: {expression/expr2}%
    Tip:

    To paste without text formatting, press Ctrl+Shift+V to paste.

  16. Highlight the text 2016 malaria incidence rate and click the bold button. Do the same for the 2020 malaria incidence rate and Percent change text
  17. Click OK.

    The pop-up preview updates with the pop-up configured.

    The pop-up text is configured.

  18. Save the map.

Share the map

Finally, you set the web map to share with everyone so you can share this link with stakeholders.

  1. On the Contents toolbar, click Share map.
  2. In the Share window, choose Everyone (public) and click Save.
  3. In the Review layer sharing window, click Update.

You used Arcade to calculate the percent change in incidence rates from 2016 to 2020 for each secondary level administrative boundary. You configured pop-ups to show the incidence rate for each administrative boundary in 2016 and 2020, and the percent change. The map has been styled and configured for sharing with stakeholders.

In this tutorial, you were tasked with monitoring the progress on reaching the UN SDG goal number 3, to reduce the incidence rate of malaria per 1,000 people by 90 percent by 2030. You obtained secondary administrative level boundary data from the UN and malaria incidence data from the Malaria Atlas Project. You converted the malaria data from an image into a raster layer and used analysis tools to calculate zonal statistics and join the malaria data to the administrative boundary layers. To make your map clear and relevant to stakeholders working on reaching this SDG goal, you used Arcade and styled your map to show the percent change and configured pop-ups with the most important data. Finally, you set the map to share with everyone.

You can find more tutorials in the tutorial gallery.