Learn essential demographic data skills
Part 4: Pair demographic and spatial data
In the previous section of this tutorial series , you learned about working with spatial data, including layers, vector data, and raster data. In this section, you will explore mapping using the tools you’ve learned for working with demographic and spatial data.
Data enrichment
Maps are powerful tools for understanding local and global populations.
When you consider people and communities, you are often interested in the intersection of where (spatial data) and who (demographic data).
Where is the population growing more rapidly?
When people move from one place to another, where do they come from? Where do they go?
To visualize demographic data as features on a map, it must be connected to place-based data in some way.
With the ArcGIS GeoEnrichment Service , you can link non-spatial data with spatial data.
Drag the slider button in the center of the map to see U.S. county boundaries (left) after being enriched with population density data (right).
The ArcGIS GeoEnrichment service is integrated into a variety of Esri products as the Enrich Layer analysis tool .
This allows you to take geographic features and add demographic data variables so that you can visualize this data on a map.
Use the data browser to explore the demographic data variables that can be used for enrichment in over 170 countries and regions around the world.
Geography levels
When you enrich geographic boundaries with data, you can organize, sort, and compare across populations in different places.
There are two broad categories of geographic boundaries: standard and non-standard.
Standard, or traditional, geographies—sometimes referred to as administrative boundaries or political boundary units—are typically set by government entities and are often used to define areas for demographic data collection and analysis.
Non-standard geographies establish boundaries that do not fall within traditional, or standard, frameworks.
Standard geographies
Every country and region has a unique set of standard geographic boundaries.
Many follow a similar structure when moving from most general (country) to most specific (often provinces, municipalities, districts, or subdistricts), with the levels in between varying in scope and terminology.
Standard geographies often vary from one country or region to another. Let's explore the four geography levels used in Japan .
At the top level are country borders.
Japan is an archipelago consisting of nearly 7,000 islands. The five largest are Hokkaidō, Honshu, Shikoku, Kyushu, and Okinawa.
Each island is bounded by the ocean, so Japan does not directly share any physical borders with other nations.
At the second level are todōfuken (prefecture) boundaries.
Japan is divided into 47 prefectures . 43 of these are known as ken (prefectures proper).
Osaka and Kyoto are fu (urban prefectures), Hokkaidō is a dō (circuit or territory), and Tokyo is a to (metropolis).
At the third level are municipality boundaries.
Japan’s prefectures are composed of approximately 1,700 municipalities.
Each municipality is given the status of a village, town, or city depending on its population.
The fourth and most specific geography level, known as cho-cho-moku, cannot be displayed at the country scale.
You must zoom in to a particular region to see these boundaries.
For comparison, these are the municipality boundaries shown earlier at the country scale.
These are cho-cho-moku, representing the most specific boundaries used for governance.
Some of these boundaries mark areas that are so small and close together that you must zoom in to see them.
These micro-districts are based on the seven-digit postal code system used in Japan.
In densely settled urban areas, some cho-cho-moku mark areas as small as a few city blocks, outlining neighborhoods, shopping centers, and city parks.
Put Japan's geography levels into context by learning how to estimate access to road infrastructure .
Non-standard geographies
Resources are not always neatly constrained by standard geographies. Waterways, mountains, deserts, and other landscape features play a role in how resources flow and where humans move and settle. These features often span multiple political boundaries.
Non-standard geographies provide an alternative way to summarize data using custom or non-traditional boundaries.
Just like standard geographies, non-standard geographies can be enriched with demographic data.
These boundaries present an context for counting people, assessing resources, and measuring access to different places.
You can draw a one-mile radius around a school that may encompass households from a variety of neighborhoods, towns, and other standard geographies.
A five-minute driving radius from the same school will take on an irregular shape due to traffic patterns and how streets are organized.
Non-standard geographies also exist on global scales.
The Mekong River Delta is a massive internationally managed watershed that spans six countries, including Lao PDR, Thailand, Cambodia, China, Vietnam, and Myanmar.
The boundaries that mark the Mekong River Delta exist beyond country borders and are as ever-changing as the rivers and floodplains that make up the watershed.
This directly impacts governance, resource management, and policy in this region.
Data apportionment
Standard and non-standard geographies mark areas for which demographic data can be retrieved using the ArcGIS GeoEnrichment service .
You can learn more about a municipality (a standard geography) or the community within a five-mile radius of a place (a non-standard geography) by enriching these types of boundaries with data.
For standard geographies, this process is straightforward.
You can retrieve data about the people in a place using the unit that it was reported in and aggregate, or add up, these units to get a summary-level view of that place.
On the left, population data is grouped at the municipality level within the country of Mexico.
Let's zoom in to the state of Campeche.
You can aggregate the individual municipality counts to determine the total population of the state of Campeche.
This process is relatively straightforward, as you are aggregating data based on standard geographic boundaries.
In other cases, you may want to know more about the population captured by a non-standard geography, such as the 10-minute walking areas around public libraries in Washington, D.C.
Let's say that you want to compare the median home value of houses that fall within each of these walking zones.
Using the Generate Travel Areas analysis tool , you can create a new map layer that calculates the 10-minute walking radius around each library across the city.
You can then enrich these 10-minute walking zones with demographic data variables found in the data browser, such as median home value.
Median home value is reported at the household level.
With the Enrich Layer analysis tool , the ArcGIS GeoEnrichment service apportions this data based on the ten-minute walking zones in order to retrieve and summarize the median home value within each of these boundaries.
In the context of congressional apportionment , the U.S. decennial census is used to keep track of how many individuals reside in each state.
Representatives are allocated to states based on population. This shapes how state voting district lines are drawn through the process of redistricting.
This ultimately affects the makeup of the Electoral College, which determines the outcome of presidential elections.
While there are different methods for approaching apportionment, the common goal is to be able to accurately retrieve demographic data for any area.
This process involves using weighted estimates for population density, also called settlement points, to collect precise counts of the data contained by any given non-standard geography.
For a deeper dive into data enrichment, apportionment, and settlement points, visit Apportionment for GeoEnrichment and Analysis for Smaller Economic Development Agencies .
What's next?
In this tutorial series, you've gained foundational knowledge for working with demographic data. Over the course of these four stories, you explored:
- Types of data, methods of data organization, and vocabulary for talking about data
- Differentiating between data, variables, and layers
- How to use the data browser and ArcGIS Living Atlas to find layers
- Benefits and best practices for working with vector versus raster data
- Key differences between standard and non-standard geographies
- Geography levels and the concept of a geographic hierarchy
- How geographic boundaries enable grouping, analysis, and visualization of demographic data through data apportionment
Take some time to reflect on what you've learned. Did anything surprise you? What was exciting or challenging? What do you want to explore in more depth?
Revisit each story. When you're ready, dive into the final piece of this five-part series with the Explore spatial data tutorial. This hands-on workflow will walk you through using census data to map populations by generation to inform business expansion.
For additional practice, make a demographic map in five minutes , assess access to public transit , investigate and share election results , or combine mapping with historical narrative in the Tell the story of Irish public history tutorial.
To continue learning about demographic and spatial data, explore the Tutorials gallery , a collection of tutorials and tutorial series presenting dozens of pathways for working with spatial data across Esri products.
