Analysis in ArcGIS Online: A Review of Analysis Capabilities

Analysis in ArcGIS Online: A review of analysis capabilities 

This blog post is a summary of the materials discussed in the Esri Training module “Analysis in ArcGIS Online”, and my findings while completing several tutorials. The presenters are Derek Nelson, John Thieling and Allison Rost. These presenters explain the different types of analysis and introduce ArcGIS Online and the new Map Viewer. The goals of this training module are to: 

• Select the most suitable analysis tools based on your dataset and the questions you aim to address 
• Enhance your analysis project by leveraging the resources available in the ArcGIS Living Atlas 
• Conduct analyses on feature layers to identify specific locations, uncover patterns, and carry out proximity-based assessments 

Here are some key notes I took during the presentation:  

Why perform analysis in ArcGIS Online? 

• Cloud-based 
• Access to public data- layers and services 
• Share results and maps, making it easy to integrate with apps 

Types of Analysis:

Feature analysis – 

• Uses Vector data (Points, lines, polygons) to represent geographic features 
• Summarizes features based on geographic location, measure distances around or between features, and quantifies spatial patterns 

Raster analysis – 

• Analyze and process imagery and raster datasets – You are basically analyzing pixels 
• Analyze imagery to derive surfaces via:  

• • Algorithms 
  • Spatial Patterns 
  • Terrain 

Learn more about the different types of spatial data

Credits –  

• A currency used in ArcGIS that are used when performing analysis 
• Can be capped by the administrator. As a Penn State user, if you need additional credits, please reach out to a Penn State ArcGIS Online Administrator. 

The Map Viewer 

When we open the Map Viewer:

Everything to the left is the mapcentric capabilities –  

• Layers 
• Tables 
• Basemap 
• Charts 
• Legend 
• Bookmarks
  • You can use this tab to save specific areas you are observing 

This section (37:50) explains the step-by-step process when performing spatial analysis on ArcGIS Online. This is the completed workflow for analysis in ArcGIS online: 

• Ask questions about the data you are using and what tool can be used to analyze your data 
• Prepare the data by loading it into ArcGIS Online as a web service, or enriching it with other data to make it more suitable for what you are studying 
• Analyze the data, but keep in mind you may have to use different analysis tools like join, summarize nearby, or even create buffers 
• Review the results to determine if you need to modify your analysis, or include a element that was left out 
• Publish the information, a great example of this is to make a Story Map with your narrative of the analysis 
• This allows stakeholders to make decisions, which repeats the process 

Analysis Capabilities 

This next chapter describes the tools and functions, authoritative content, Analysis history, and charting. The presenter then adds a layer of all the US Counties to demonstrate some of the functions found to the right of our map 

The filter tool is almost like a query, where you can write an expression that will select an area

The presenter then goes into analysis tools and uses the enrich layer tool to add sports fan data into his selected state, Texas. In my example, I filtered the county data to Pennsylvania, and added crime data from the enrich layer tool. In the ‘add fields’ section of the styles tab, I was able to choose different types of crime for my map, then set the style to ‘chart and size’ to display all types of crime across each county. On the ‘Configure charts’ tab, I chose the same variables which allowed me to display a statewide crime index. 

 

 

 

 

 

 

Testing an analysis tool: Join Feature 

In this part of the video, the presenter filters the United States Counties layer into only those that encompass Loma Linda, California, and enriches the layer with health data such as average alcohol consumption, etc.  Using a table that displays the quality of life in this area from an outside source, the presenter explains the Join Feature , an analysis tool that transfers the features or attributes from one source into another, based on spatial or temporal attributes. In this case, the table  joined to the enriched layer is spatially based in Loma Linda and was able to connect both together using both columns that displayed the County FIPS (Federal Information Processing Standard, an identifier for counties and tracts).  

 

When I repeated these steps, I decided to use the tracts of the counties within Loma Linda (San Bernardino and Riverside) and enrich them with the demographic data of the people who live in these areas. Since the presenter did not provide the exact table necessary to replicate his analysis, I found a dataset online from the Census of the walkability index of all the block groups in the United States. I decided it would be interesting to see the census data of these defined tracts.  

 

To do this, I had to find a unifying locator column from both inputs, the Census tract boundaries, and the walkability index. For this, I decided to use the Tract FIPS to join both layers together; However, I had run into the problem of having too large data for the computers to process on Excel, so I chose to only select some of the tracts for the join feature. The result is some of the tracts being shown with the join feature from both counties, and I realize I should have done a much smaller example.  

 

Nathan Vincent is a Sophomore from the Lehigh Valley majoring in Geography in the College of Earth and Mineral Sciences, with minors in Geographic Information Science, Information Sciences and Technology, and Sustainability Leadership. Nate’s interests include Land Use, Transportation, GIS, and Information Technology. Nate has been working at the Donald H. Hamer Center for Maps and Geospatial Information since April 2023.