Speaking the “Language” of Spatial Analysis and Science via Story Maps

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10-07-2018 10:21 AM
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DawnWright
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Last update: December 16, 2021

Spatial analysis has always been a hallmark of GIS, the “numerical recipes” which set GIS apart from other forms of computerized visualization and information management. With GIS we can pose questions and derive results using a wide array of analytical tools to help us understand and compare places, determine how places are related, find the best locations and paths, detect and quantify patterns, and even to make spatial predictions.

"The greatest potential for change and success occurs when we all understand and speak the same language—-the language of spatial analysis." -- Chris Cappelli

What better way to speak that language than via a story map, in either "modern" ArcGIS StoryMap or "classic" mode? As people continue to explore and share their world using this medium, some are venturing beyond the simple map tour mode of points linked to photographs, toward “stories” that examine, explore, and showcase the results of a spatial analysis. We’ll likely see more of these analytical stories as the story map medium is introduced into more GIS courses, particularly at the university level.

As you explore the story of spatial analysis, please KEEP SCROLLING DOWN for a small catalog of analytical story maps. Be sure to visit again as I will try to add to this page throughout the year!

Hot!  This story map is about ArcGIS Hub, a new technology currently in worldwide adoption, for creating and publishing open data in an easy and accessible way. See this gallery of Science Hubs, many of which include story maps. 

Scientists as Storytellers, from Esri's Charmel Menzel of our National Government Sciences Team, as presented at the 2018 American Geophysical Union (AGU) Fall Meeting. 

Esri's Applied Analysis and National Government Sciences Teams' Scientists Communicating with Story Maps Gallery.

A story map with both ANALYTICS and suggested societal SOLUTIONS: Take Action: Tools to Understand and Prepare for Extreme Heat.

Esri's Lauren Scott Griffin's "Analyzing Traffic Accidents in Space and Time" uses the classic Story Map Cascade to analyze automobile crash data in Brevard County, Florida using ArcGIS Pro. The study addresses important questions such as where are traffic accidents increasing (including as specific hot spots within a road network), and when are the most dangerous times to be driving. You can also download the data, follow the complete ArcGIS Pro workflows, and access additional resources on ArcGIS

Esri's Lauren Bennett’s “Drought Impact Assessment” uses the classic Story Map Series - Side Accordion Layout to guide the viewer through four stages of an analysis, culminating in a map of statistically significant decreases in soil moisture over a 35-year period, as part of longer term monitoring effort. See the demo of the story map at the 2014 Federal GIS conference (minute 2:14). In addition, this video at minute 6:28 is an example of using Python to schedule a task that can grab data from the United States Drought Monitor and recreate it as a live service that might be inserted into a story map.  

The USDA Forest Service’s Restoration Story Map Atlas uses the same format to show the results of analyses for the Pacific Northwest ranging from identifying the percentage of a watershed that could be effectively treated through active forest thinning, prescribed fire, or use of wildfire, to the results of a bivariate rendering of burn probability by conditional flame length.

 The Center for Research in Water Resources at the University of Texas at Austin uses the classic Map Journal app to tell the story of flood risk in and around Huarez City, Peru as based upon hydrodynamic modeling results. See the related blog post about this research. 


Other great analytical examples include:

Winners of the  2016 Global Content Challenge were required to use spatial analysis and submit entries as a classic Story Map Journal:

LAND

OCEAN

POPULATION

 

Analysis in the field, or stories of data collected in the field as inputs for spatial analysis, are also very important:

About the Author
Dawn was appointed Chief Scientist of Esri in October 2011 after 17 years as a professor of geography and oceanography at Oregon State University. As Esri Chief Scientist, she reports directly to Esri CEO Jack Dangermond with a mission to strengthen the scientific foundation for Esri software and services, while representing Esri to the national and international scientific community. Dawn maintains an affiliated faculty appointment as Professor of Geography and Oceanography at Oregon State. Follow her on Twitter @deepseadawn. More info. also at http://esriurl.com/scicomm and http://dusk.geo.orst.edu.
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