Getting Started with Living Atlas

Introduction

In this lab, we were introduced to the learn.arc.gis.com and the living atlas.  The website, learn.arc.gis.com, has a wealth of information with lessons ranging from the simplest of tutorials to much more difficult ones.  These lessons will be explored and used in this assignment. One of these lessons will be the “Getting Started with ArcGIS Living Atlas.” This introduces the living atlas within ArcGIS Pro which is extremely useful, as it is an ever-growing collection of curated and authoritative geographic information from around the world.  This includes maps, apps, and data layers that can be used in any project.

Methods/Lab Assignment

The first part of this assignment was to explore the website on our own and talk about five that are of interest to us.  To start, we opened the website in which the link can be found below:

Figure 1: Learn ArcGIS

In order to gain full access to all the lessons, an account and subscription is needed.  Fortunately, Purdue has access to this through the enterprise login. The next process then involved logging in.  After signing in, you are directed back to the homepage where you can see the new lessons that have been posted. In order to find some of interest and explore the website, I clicked the explore all lessons link. This led me to all of the lessons available.

The filter tool is extremely helpful for searching for more specific material which includes filters of the capabilities, products used, industries, format types, and regions.  The search bar at the top allows for certain lessons to be found. Since I am interested in safety, I filtered to show the “Public Safety” industry. One of the lessons I found was “Perform Visibility Analysis to Increase Security.”  This is an example of how certain lessons of interest can be found using the filters. Below are five examples of some of the lessons that can be found:

Example #1: Perform Visibility Analysis to Increase Security

Figure 2: Example 1

In this lesson, the city of Philadelphia is deciding on a security deployment for an event to take place in a local park.  The user will conduct an interactive 3D visibility analysis in ArcGIS Earth to determine whether security personnel will have a line of sight on the event.  The fixed locations and dynamic patrol routes will be analyzed including the aerial route of a helicopter. The amount of the surrounding area security forces will be determined as well.

Example #2: Expand a Small Business

Figure 3: Example 2

For this tutorial, you are a small business owner of a laundry and dry-cleaning facilities.  You are interested in expanding into new markets. As with all businesses, it can be risky to expand.  This risky factor will be analyzed by looking at your most successful stores and determining what factors contribute to a successful laundry and dry-cleaning store.  These factors will then be used in a suitability analysis to determine a new market area for expansion.

Example #3: Policy Mapping - Safe Streets to Schools

Figure 4: Example 3

In this lesson, you’ll suggest policy actions to your city’s local government that will reduce the likelihood of accidents.  This is in response to an accident that happened near an elementary school in your city that has drawn the attention to the topic of pedestrian and bicycle safety.  With this, you’ll map accident data regarding pedestrians and cyclists struck by vehicles. Then, the number of accidents will be determined within each school one to identify the five most dangerous zones.  These findings will then be presented with a story map that provides narrative context that helps users understand your position.

Example #4: Streamline Deliveries with Drive-Time Analysis

Figure 5: Example 4

For this tutorial, a new Chinese food delivery business, Wok & Roll, opened near Fort Lauderdale, Florida.  The issue with the business is that it tends to have more orders than drivers, and the owner is unsure what to blame, inefficient routes or too few drivers.  As delivery manager, you must solve why freshly cooked orders grow cold inside the store. This will use ArcGIS to identify the most efficient delivery routes during rush-hour traffic.  To further help with the Tapestry Segmentation, that same data will be used to build customer profiles and steer advertising dollars.

Example #5: Balance Territories for College Recruiters

Figure 6: Example 5

In this lesson, you are an analyst at a marketing firm that specializes in college recruiting.  One of the large universities is a client of your firm, and you are tasked with promoting the undergraduate degree programs at the high schools in Marion County, Indiana.  In order to accomplish this, you are tasked with allocating resources at your firm toward direct promotion, outreach, and enrollment efforts.

The required lesson for this lab was one with the Living Atlas as mentioned earlier.  The lesson we will be working with is “Get started with ArcGIS Living Atlas of the World.”

Figure 7: Get Started with ArcGIS Living Atlas of World

In the first half of this lesson, we are a researcher preparing to study the potential impact of the Grand Ethiopian Renaissance Dam which is being built on the Nile River in eastern Africa.  In order to do this, we must learn about the current water levels in the region. This is done by going on to the Living Atlas website which can be seen below in Figure 8: Living Atlas Website.

 Figure 8: Living Atlas Website

After signing in, the full catalog of the Living Atlas content can be viewed by clicking browse.  Since we will be exploring the impact of the Grand Ethiopian Renaissance Dam which is being built on the Nile River, we are going to search “water.”  This resulted in more than a thousand results returned. To help narrow the search, there are categories below the search bar for trending, basemaps, imagery, boundaries, people, infrastructure, and environment.  Since this is pertaining to the environment, we will click on that. This can be seen in Figure 9: Environment Selection.

Figure 9: Environment Selection

This limited the searches down, but it is still rather difficult to find what we are looking for.  For Filters, this is where I choose Layers, and for the Region filter, I chose World. After scrolling through the list of layers, I found the necessary layer with GLDAS Soil Moisture 2000 – Present.  This can be seen in Figure 10: GLDAS Soil Moisture 2000 – Present.

Figure 10: GLDAS Soil Moisture 2000 – Present

After opening this in Map Viewing (which can be seen in Figure 11: Soil Moisture in Map Viewer), the soil moisture can now be explored.  The legend is helpful in determining the different colors rather than guessing.  This can be seen in Figure 12: Legend of Soil Moisture.

Figure 11: Soil Moisture in Map Viewer

Figure 12: Legend of Soil Moisture

The areas can be explored by simply clicking on the area of interest.  Since this is pertaining to the area of the Nile Delta, north of Cario, Egypt, this was the area that was clicked on.  This can be seen in Figure 13: Exploring the Soil Moisture.

Figure 13: Exploring the Soil Moisture

In order to gain more context into the water levels in both Ethiopia and Egypt, an app will be used.  Applications in the Living Atlas have been built from the data that can turn layers into useful tools.  This can be found right next to the browse tab clicked on earlier. The app that will be used is the Water Balance App.  This can be seen in Figure 14: Water Balance App.

Figure 14: Water Balance App

After opening the app, the coordinates for the Grand Ethiopia Renaissance Dam were searched (11°12′55″N 35°05′35″E).  This can be seen below in Figure 15: Location of Grand Ethiopia Renaissance Dam.

Figure 15: Location of Grand Ethiopia Renaissance Dam

The chart of the water balance of the area can be seen below in Figure 16: Water Balance Chart of Ethiopia.  This area of the highlands of Ethiopia from the headwaters for the Nile River receives a fair amount of rain, so there is always moisture in the soil.  This is in contrast to the Nile Delta which can be seen in Figure 17: Water Balance Chart of Nile Delta.

Figure 16: Water Balance Chart of Ethiopia

Figure 17: Water Balance Chart of Nile Delta

 Further exploration can be done with another chart within the application.  This can be seen in Figure 18: Further Exploration with another Chart.  The soil moisture can be seen in this chart.

Figure 18: Further Exploration with another Chart

The precipitation can be seen in the region by selecting it from the menu.  This is reflected in Figure 19: Precipitation of Africa.

Figure 19: Precipitation of Africa

The second part of this lesson is exploring the urbanization patterns in the United States over time and space.  This will be done using ArcGIS Online.  ArcGIS Online is a more simplified version of ArcGIS Pro, but it can be done anywhere without having the application downloaded.  Like mentioned earlier though, an account has to be signed into and a subscription is needed for full access.

Figure 20: ArcGIS Online

After signing in, a map can be created by clicking the Map tab.  Similar to ArcGIS Pro, a map is created showing the lower 48 states of the United States.  This can be seen in Figure 9: Creation of a Map.

Figure 21: Creation of a Map

The basemap here tends to be a little too much for analysis, so this was changed to a Light Gray Canvas.  Next, the data to be added to the map was searched for. This is done by clicking Add and then Browse Living Atlas Layers.  A list of layers will then appear in the pane. Like mentioned previously, this can be filtered and searched to find exactly what is needed.  This can be seen below in Figure 22: Living Atlas Pane.

Figure 22: Living Atlas Pane

Since this project involves the environment, that is the category that was selected.  The content within the map area was filtered to only show this. In the search bar, “land cover” was searched.  In the result search, there is the item named USA NLCD Land Cover. This is the one that will be used. Each data file will have badges that can be used to quickly find the highest quality and most trustworthy data.  This one for instance, has the Authoritative badge (meaning it has been verified by an authoritative source), the Living Atlas badge (indicates this item is included in the Living Atlas), and the Subscriber badge (indicates that the user must be signed in to an ArcGIS account to access the layer).  This can be seen below in Figure 23: USA NLCD Land

Figure 23: USA NLCD Land

This was added to the map.  In order to really analyze the data, a city was chosen to see the urbanization of.  Las Vegas, Nevada was searched and the location can be seen in Figure 24: Overview of Las Vegas, Nevada.

Figure 24: Overview of Las Vegas, Nevada

With this layer, there are several years of data associated with it.  A time slider appears at the bottom which can be adjusted to see the urbanization of the dates.  This can be seen in Figure 25: Time Slider.

Figure 25: Time Slider

Certain years can be compared with one another.  This can be seen in Figure 26: Las Vegas - 2005 vs. 2006, comparing the Las Vegas of 2005 to that of 2006.

Figure 26: Las Vegas - 2005 vs. 2006

These steps were also used to see the cities of the East Coast such as Washington D.C., Baltimore, and Philadelphia.  This can be seen in Figure 27: Comparison of East Coast Cities.  For these, the layers were adjusted to show four distinct classes of development.  These classes can be seen in Figure 28: Legend of Classes.

Figure 27: Comparison of East Coast Cities

Figure 28: Legend of Classes

In order to better distinguish these classes, the Cyan to Purple color ramp was selected.  This can be seen below in Figure 29: East Coast Cities with Cyan to Purple Color Ramp.

Figure 29: East Coast Cities with Cyan to Purple Color Ramp

The final step of this is saving this map which can be seen in Figure 30: Saving the Map.

Figure 30: Saving the Map

Since the Living Atlas contains maps made by the community, this map will now be one that can be accessed by anyone.  There was an additional part in this tutorial using ArcGIS Pro, but I will demonstrate this by coming up with a map on my own using at least five layers as required. 

After trying to find layers that would relate to each other and show important data, I came up with 5 data layers that I deem the possibilities for correlations to be found.  These layers are as follows:

1.               Population: Shows the population of the cities in the United States

2.               Heat Map: Shows the population in a more specific way, showing the whereabouts of the majority of the population in the United States.

3.               Per Capita Income for 2019: Shows the area of the average income per person in a given area of the United States

4.               Republican Affiliation: Shows political affiliation, more specifically the Republican party affiliation, of the United States

5.               Democratic Affiliation: Shows political affiliation, more specifically the Democratic party affiliation, of the United States

For this lab, I wanted to see how the population and income affect political party affiliation in respects to the location of a big city.  Typically, there tends to be a higher concentration of people with the downtown area of a city with a slightly lower income that tends to favor the Democratic Party versus a slightly lower concentration of people in the suburbs with higher income that favors the Republican Party.  This could be due to a number of reasons, but for this assignment, we will look to see if this general stereotype is true.  The city, or area, I have chosen is one of the fastest growing metroplexes in the country the past few years that is home to the 4th largest airport and 31st largest airport in the United States.  This area is the Dallas-Fort Worth Metroplex.

To start, I worked on the layer of the population and added it in.  I layered the heat map on top in order to show where the higher concentration of the population is.  This can be seen in Figure 31: Population of DFW with Heat Map.

Figure 31: Population of DFW with Heat Map

The next layer I worked with was the Per Capita Income of 2019.  This can be seen in Figure 32: Per Capita Income of DFW in 2019,  and the scale can be seen in Figure 33: Scale of the Per Capita Income of 2019.

Figure 32: Per Capita Income of DFW in 2019

Figure 33: Scale of the Per Capita Income of 2019

Lastly, the two layers I worked with were the Democratic Party Affiliation and the Republican Party Affiliation.  I attempted at first to stack these layers, however, that did not work quite well, as the colors changed. Due to this, I used them separately which can be seen in Figure 34: Democratic Party Affiliation of DFW and Figure 35: Republican Party Affiliation.  I did layer the heat map over these to try that out which can be seen in Figure 36: Democratic Party Affiliation of DFW with HM and Figure 37: Republican Party Affiliation with HM

Figure 34: Democratic Party Affiliation of DFW

Figure 35: Republican Party Affiliation

Figure 36: Democratic Party Affiliation of DFW with HM

Figure 37: Republican Party Affiliation with HM

The final maps that have combined all of these layers can be seen in Figure 38: Final Map and Figure 39: Final Map with Heat Maps.

Figure 38: Final Map

Figure 39: Final Map with Heat Map

Conclusion

The Learn ArcGIS website is an extremely helpful outlet to turn to if you need assistance with anything ArcGIS related.  There are so many lessons on there that range from the simplest of tasks to highly advanced ones. To add to this, the living atlas can save a tremendous amount of time and resources by using layers created by others that are accurate and precise.  The products that can be created are extremely effective. I highly recommend exploring both tools, as you will not be disappointed.