{"id":2289672,"date":"2024-03-26T09:57:01","date_gmt":"2024-03-26T16:57:01","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2289672"},"modified":"2024-03-28T16:13:36","modified_gmt":"2024-03-28T23:13:36","slug":"exploring-the-eclipse-with-map-viewer-analysis","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/exploring-the-eclipse-with-map-viewer-analysis","title":{"rendered":"Exploring the eclipse with Map Viewer analysis"},"author":7231,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[22941],"tags":[398132,33371,770492,27881],"industry":[],"product":[767992,36551,380802],"class_list":["post-2289672","blog","type-blog","status-publish","format-standard","hentry","category-mapping","tag-arcgis-storymaps","tag-map-viewer","tag-map-viewer-analysis","tag-storytelling","product-arcgis-image-for-arcgis-online","product-arcgis-online","product-arcgis-storymaps"],"acf":{"authors":[{"ID":7231,"user_firstname":"Cooper","user_lastname":"Thomas","nickname":"Cooper Thomas","user_nicename":"cooper_thomas","display_name":"Cooper Thomas","user_email":"Cooper_Thomas@esri.com","user_url":"https:\/\/cooper-thomas.com\/","user_registered":"2018-03-02 00:19:29","user_description":"Cooper is a cartographer on Esri\u2019s StoryMaps team. His maps have found their way onto the @Esrigram Instagram feed, the front page of Reddit, and his parents\u2019 fridge. In his spare time, Cooper enjoys playing Mozart to his houseplants so that they someday grow tall and strong.","user_avatar":""}],"short_description":"See how the StoryMaps team used Map Viewer's analysis tools to uncover insights about the path of the eclipse","flexible_content":[{"acf_fc_layout":"content","content":"

Spatial analysis was historically the domain of desktop GIS software. But that\u2019s no longer the case \u2014 and hasn\u2019t been, for some time. In fact, Map Viewer in ArcGIS Online<\/span> provides a broad suite of vector and raster analysis tools capable of fulfilling a variety of tasks. Because these tools run right in a browser window, they enable efficient, on-the-go workflows for GIS experts and part-time mapmakers alike.<\/span><\/p>\n

On the StoryMaps team, we are big proponents of Map Viewer\u2019s analysis tools. In some cases, these web-based tools have altogether supplanted workflows previously reserved for ArcGIS Pro. I won\u2019t pretend to know how the Map Viewer analysis tools actually work, but I do know that they are intuitive to use, fast, and don\u2019t interfere with other tasks while they run. And because these tools run in a web browser on any operating system, they are accessible to a wide audience without needing to install desktop software.<\/span><\/p>\n

We recently published<\/span> Mapping the eclipse: A journey through darkness<\/span><\/i><\/a>, a story that explores the path of the total solar eclipse on April 8, 2024. This article covers three different Map Viewer-based workflows that we used to highlight certain geographic features and phenomena relevant to this exceptional event.<\/span><\/p>\n

If you\u2019d like to follow along, you can download the eclipse path data referenced in this story directly from<\/span> NASA\u2019s Scientific Visualization Studio<\/span><\/a>. For more information about the Map Viewer\u2019s analysis tools, check out the<\/span> product documentation<\/span><\/a>. You can also browse step-by-step spatial analysis tutorials in<\/span> this gallery<\/span><\/a>, and review some of the terms used here in<\/span> Esri\u2019s GIS Dictionary<\/span><\/a>. To read the story, click on the animation below.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2289992,"id":2289992,"title":"EclipseLoopOptimized","filename":"EclipseLoopOptimized.gif","filesize":5393895,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/exploring-the-eclipse-with-map-viewer-analysis\/eclipseloopoptimized","alt":"","author":"7231","description":"","caption":"A selection of maps that appear in the eclipse story. Click the animation above to read the full piece.","name":"eclipseloopoptimized","status":"inherit","uploaded_to":2289672,"date":"2024-03-26 07:07:14","modified":"2024-03-27 19:24:26","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1280,"height":720,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized.gif","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized.gif","medium_large-width":768,"medium_large-height":432,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized.gif","large-width":1280,"large-height":720,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized.gif","1536x1536-width":1280,"1536x1536-height":720,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized.gif","2048x2048-width":1280,"2048x2048-height":720,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized-826x465.gif","card_image-width":826,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EclipseLoopOptimized.gif","wide_image-width":1280,"wide_image-height":720}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/storymaps.arcgis.com\/stories\/e7d0e4cef5044ecfaa54f44ac61de81e"},{"acf_fc_layout":"content","content":"

Selective highlighting<\/h2>\n

Selective highlighting is a cartographic technique commonly used in map-based stories to focus readers\u2019 attention on specific locations or features of interest. In essence, selective highlighting involves styling a subset of features in a dataset in a particular way, in order to visually separate them from other, similar features.<\/span><\/p>\n

In some cases, you may want to select and highlight features based on some common attribute value (e.g., belonging to the same category). This is often as easy as applying a data-driven filter. But in other cases, you might want to select features based on their locations, rather than (or <\/span>in addition to<\/span><\/i>) their attribute values.<\/span><\/p>\n

This is where the<\/span> Find by Attribute and Location<\/b><\/a> analysis tool comes into play. This tool extracts features from one layer based on their geographic proximity to another layer. Unlike other data management tools, this one doesn\u2019t actually modify the geometry of the features \u2014 it just consolidates those features in a new layer that\u2019s then automatically added to the map.<\/span><\/p>\n

For our story, we wanted to highlight historical tornado tracks that intersected the path of the April eclipse. To accomplish this goal, we ran the <\/span>Find by Attribute and Location<\/b> tool on a national dataset of tornado tracks (available in<\/span> ArcGIS Living Atlas of the World<\/span><\/a>) to extract all the features crossing the eclipse\u2019s path. We then used a combination of styles, layer effects, and blend modes to elevate these \u201cfocus\u201d features in the map\u2019s visual hierarchy. Here\u2019s an accelerated preview of the workflow, and the result, as it appears in the story.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2290012,"id":2290012,"title":"SelectiveHighlighting","filename":"SelectiveHighlighting.gif","filesize":1034021,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/exploring-the-eclipse-with-map-viewer-analysis\/selectivehighlighting","alt":"","author":"7231","description":"","caption":"Using the Find by Attribute and Location tool to isolate features of interest.","name":"selectivehighlighting","status":"inherit","uploaded_to":2289672,"date":"2024-03-26 07:15:20","modified":"2024-03-27 19:25:18","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":800,"height":410,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting.gif","medium-width":464,"medium-height":238,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting.gif","medium_large-width":768,"medium_large-height":394,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting.gif","large-width":800,"large-height":410,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting.gif","1536x1536-width":800,"1536x1536-height":410,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting.gif","2048x2048-width":800,"2048x2048-height":410,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting.gif","card_image-width":800,"card_image-height":410,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/SelectiveHighlighting.gif","wide_image-width":800,"wide_image-height":410}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

That\u2019s it! The <\/span>Find by Attribute and Location <\/b>tool makes it super easy to extract features from one layer based on their proximity to another layer. It\u2019s a great way to isolate features located within or near a particular area of interest. Learn more about the tool<\/span> here<\/span><\/a>.\u00a0<\/span><\/p>\n

Enriching a layer with demographic data<\/h2>\n

In the example above, our goal was to isolate a specific subset of features in one layer, based on their spatial relationship with features in another layer. We weren\u2019t, however, really concerned about the attribute values of those features themselves. But suppose we wanted to know something about those features? In our story, that <\/span>something<\/span><\/i> was the total population living within the eclipse\u2019s path. We didn\u2019t necessarily plan to map this data, but we wanted to have a good estimate of the affected population.<\/span><\/p>\n

As with many GIS operations, there are several different ways to approach this problem. For example, we could\u2019ve used the select-by-location workflow above to isolate populated places within the eclipse\u2019s path, and then added up their populations; or we could\u2019ve used spatial statistics to extract population counts from a separate demographics dataset.<\/span><\/p>\n

But both approaches would require us to furnish our own population layers \u2014 a task complicated by the fact that the eclipse will pass over Mexico, the U.S., and Canada. So instead, we used the<\/span> Enrich Layer<\/b><\/a> tool. As its name implies, this tool enriches author-defined features with attribute data sourced from Esri\u2019s repository of authoritative datasets. In our case, we wanted to add the latest population totals for Mexico, the United States, and Canada to our eclipse path layer. The tool generated a new layer that <\/span>looked <\/span><\/i>very similar to our original eclipse path layer, but contained the combined population in a new field.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2291012,"id":2291012,"title":"EnrichingLayer","filename":"EnrichingLayer.gif","filesize":801501,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/exploring-the-eclipse-with-map-viewer-analysis\/enrichinglayer","alt":"","author":"7231","description":"","caption":"A preview of the layer enrichment workflow used to generate a summary statistic. This figure is presented in the story alongside a population spike map.","name":"enrichinglayer","status":"inherit","uploaded_to":2289672,"date":"2024-03-27 00:57:02","modified":"2024-03-27 19:28:21","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":800,"height":410,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer.gif","medium-width":464,"medium-height":238,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer.gif","medium_large-width":768,"medium_large-height":394,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer.gif","large-width":800,"large-height":410,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer.gif","1536x1536-width":800,"1536x1536-height":410,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer.gif","2048x2048-width":800,"2048x2048-height":410,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer.gif","card_image-width":800,"card_image-height":410,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/EnrichingLayer.gif","wide_image-width":800,"wide_image-height":410}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

The <\/span>Enrich Layer <\/b>tool can be a huge timesaver, since it removes the need to manually seek out, validate, and process the equivalent data on your own. To be fair, this tool does<\/span> consume credits<\/span><\/a> \u2014 but your own time is probably a whole lot more valuable. The <\/span>Enrich Layer <\/b>tool is also well-suited for data exploration, as it supports a wide range of authoritative, thematic datasets from around the world. Learn more about the <\/span>Enrich Layer <\/b>tool<\/span> here<\/span><\/a>.<\/span><\/p>\n

Binning cloud cover data<\/h2>\n

High-resolution raster data can be remarkably illuminating, but the extreme level of detail can also distract readers and lead them to overlook a map\u2019s key themes or messages. As spatial storytellers, we\u2019re always looking for ways to reduce the cognitive load the maps place on readers \u2014 and aggregation is one method for helping readers interpret dense raster data at a glance.<\/span><\/p>\n

For the eclipse story, we wanted to show historic weather patterns along the path of totality, in order to locate areas that are reliably clear \u2014 or overcast \u2014 in April. (Spoiler alert: the prognosis isn\u2019t great.) Rather than visualizing the raw raster data, we decided to generalize it using a technique called binning.<\/span><\/p>\n

This process essentially involves creating a grid of regularly sized shapes covering the map\u2019s extent \u2014 we chose hexagons, as they pack together quite nicely \u2014 and then visualizing those shapes using values representative of the individual data points within them.<\/span><\/p>\n

This was our most complex analysis yet, and required us to string together a few different operations. First, we downloaded<\/span> cloud cover data from NASA<\/span><\/a>, and used<\/span> ArcGIS Image for ArcGIS Online<\/span><\/a> to upload it to our AGO organization. (Note that an ArcGIS Image for ArcGIS Online license is required in order to publish raster data to ArcGIS Online in an editable format.)<\/span><\/p>\n

Next, we used Map Viewer\u2019s <\/span>Generate Tessellations <\/b>tool to create a grid of identically sized hexagons covering the North American continent. (We settled on a hexagon size of 500 square miles, which hit the sweet spot between accuracy and ease of interpretation.)<\/span><\/p>\n

Then, we used the <\/span>Zonal Statistics as Table <\/b>raster analysis<\/span> tool to calculate the median percentage of April cloud cover within each hexagon over the past five years. The result of that operation was a table, so as our final step, we used the <\/span>Join Features <\/b>tool to join those values to their corresponding hexagonal features. Then, it was just a matter of styling the hexagons until we were satisfied with their appearance. See, that wasn\u2019t so hard!<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2291022,"id":2291022,"title":"BinningRasterData","filename":"BinningRasterData.gif","filesize":1286769,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/exploring-the-eclipse-with-map-viewer-analysis\/binningrasterdata","alt":"","author":"7231","description":"","caption":"Binning raster data can help clarify spatial patterns that might be easy to miss.","name":"binningrasterdata","status":"inherit","uploaded_to":2289672,"date":"2024-03-27 00:57:27","modified":"2024-03-27 19:30:59","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":800,"height":410,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData.gif","medium-width":464,"medium-height":238,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData.gif","medium_large-width":768,"medium_large-height":394,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData.gif","large-width":800,"large-height":410,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData.gif","1536x1536-width":800,"1536x1536-height":410,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData.gif","2048x2048-width":800,"2048x2048-height":410,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData.gif","card_image-width":800,"card_image-height":410,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/BinningRasterData.gif","wide_image-width":800,"wide_image-height":410}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Wrap up<\/h2>\n

Within the grand scheme of spatial analysis, the three workflows above are fairly unexceptional. And to be fair, the abbreviated walkthroughs conceal some amount of trial and error.<\/span><\/p>\n

What makes these workflows noteworthy, however, is that they were all completed entirely in ArcGIS Online \u2014 something that would\u2019ve been hard to imagine even a decade ago. It\u2019s no secret that Map Viewer\u2019s cartographic capabilities have evolved leaps and bounds in recent years. But the maps in our eclipse story also testify to Map Viewer\u2019s expanding analysis options and their accessibility to non-expert audiences. And that\u2019s worth celebrating.<\/span><\/p>\n

Have you used the Map Viewer\u2019s analysis tools to help you tell a place-based story? If so, sound off in the<\/span> ArcGIS StoryMaps Community<\/span><\/a>, or<\/span> let us know on social media<\/span><\/a> \u2014 we\u2019re always eager to see how you\u2019re applying these tools to your own storytelling projects.<\/span><\/p>\n"}],"related_articles":[{"ID":1833922,"post_author":"5241","post_date":"2023-02-22 09:43:07","post_date_gmt":"2023-02-22 17:43:07","post_content":"","post_title":"Introducing Analysis in ArcGIS Online Map Viewer","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"introducing-analysis-in-arcgis-online-map-viewer","to_ping":"","pinged":"","post_modified":"2023-07-21 14:28:43","post_modified_gmt":"2023-07-21 21:28:43","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1833922","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"4","filter":"raw"},{"ID":2236302,"post_author":"4951","post_date":"2024-01-31 16:02:12","post_date_gmt":"2024-02-01 00:02:12","post_content":"","post_title":"Totally Eclipsed","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"totally-eclipsed","to_ping":"","pinged":"","post_modified":"2024-01-31 18:32:51","post_modified_gmt":"2024-02-01 02:32:51","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2236302","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1351982,"post_author":"7231","post_date":"2021-09-22 16:10:25","post_date_gmt":"2021-09-22 23:10:25","post_content":"","post_title":"Maximize your basemaps in ArcGIS StoryMaps","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"basemaps-and-storymaps","to_ping":"","pinged":"","post_modified":"2026-03-10 12:35:32","post_modified_gmt":"2026-03-10 19:35:32","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1351982","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"}],"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/ThumbnailSM.png","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/03\/Thumbnail-1.png"},"yoast_head":"\nExploring the eclipse with Map Viewer analysis<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/exploring-the-eclipse-with-map-viewer-analysis\" 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