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Mapping Class: Efficient Map-making using Templates and Stylesheets, with Steve Spindler

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Welcome back to another edition of Mapping Class! The Mapping Class tutorial series curates demonstrations and workflows created by professional cartographers and expert Avenza software users. Today we have Steve Spindler, a longtime MAPublisher user, and expert cartographer. Steve has put together a 15-minute masterclass on creating maps from start to finish using templates and stylesheets. This video is jam-packed with useful tips and tricks that show how Steve uses templates, stylesheets, and a host of MAPublisher tools to design a beautiful map in minutes.

Steve has produced a video to show the complete, un-cut, map-making process. The Avenza team has produced video notes (below) to help you follow along.

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Efficient Map-making using Templates and Stylesheets
by Steve Spindler (video notes by the Avenza team)

Readers of the Avenza resources blog will recognize Steve Spindler as a recent feature of our Cartographer Chronicles spotlight article. Steve has also been a frequent contributor to the Mapping Class blog series, where he has shared his tips for using MAPublisher to make eye-catching maps. Some of his recent contributions cover his techniques for using attribute expressions to edit street labels and working with OSM data in MAPublisher. 

Today, Steve is doing something a little different. Instead of focusing on a specific tool or technique, he has put together a complete 15-minute masterclass showing how he creates a map from start to finish. In this uncut demonstration, Steve discusses his tips for importing data, using MAP views, applying stylesheets, and even labelling. Steve shows how using templates and preconfigured MAP themes can make map creation a breeze.

Using a Template

In this demonstration, Steve will be creating a congressional district map showing the municipalities of Pennsylvania District 17. Steve discusses how using a template to create your map can significantly improve the speed of map creation. Templates can be used to configure standardized design elements that can be recycled across several different map projects. Templates are especially useful in situations where different maps form part of a series with shared design components and colour schemes.

For this tutorial, Steve uses a template that includes some basic stylistic elements he typically includes in all his congressional district maps. The template comes preloaded with custom borders, Titles, subtitles, an inset map, and a scale bar. His template is already configured with custom fonts and colours that will give some uniformity across his different map projects.

Steve has also set up swatch groups for his template. This ensures each map created with the template uses the same colour groups. Setting up swatches in the template also makes it easy to swap out or change the colour of different map elements. As an example, Steve uses the drag and drop functionality of the swatch panel to automatically adjust the “core colours” of his map template (text, border, and scale bar colours) from brown to green. 

Steve’s template comes preloaded with an inset map containing all the congressional district boundaries for Pennsylvania. Using the drag-and-drop functionality of MAP Views, he can place a “District 17” data layer into a new MAP View that will contain the main body of his map project. Using the MAP View editor, Steve can assign a custom scale and choose an appropriate projection. This will ensure any new data layers he brings into the MAP view will be correctly aligned and accurately projected. 

Import and Prepare the Map Data

With his template configured, Steve now brings in some new data. He wants to access municipal boundary polygon data found on a PostGIS database stored locally. You can specify the specific data table within the database he wishes to add using the Import tool. More importantly, shows how he uses spatial filtering options to specify the region of interest. The spatial filter means that only the data relevant to the map extent is loaded in (very useful when using large datasets).

Using the Crop to Shape tool, Steve cleans up the imported data layer by removing any polygons that fall outside his district boundaries. Next, he uses the Simplify tool to remove extraneous vertices, with that his data is ready for stylization!

Apply Styles with MAP Themes

MAP themes are one of the most powerful tools in the MAPublisher toolset. MAP Themes allow you to configure rules-based stylesheets that work with attribute information stored in map data layers. Using pre-coded attribute values in his municipal boundary layer, Steve can assign colour fills to each municipality. Using colour in this way is a bit more eye-catching than using generic boundary lines, and makes it easy to see the shapes of each municipality.

MAP Themes can not only set the stroke and fill for each polygon, but also apply graphic style effects such as “inner glow” to give each shape a more defined appearance. Since MAP Themes are entirely rules-based, it’s easy to modify and apply styles across the entire map without needing to adjust appearance settings for each vector layer individually. 

Labels and Details

With his MAP Themes applied, Steve needs to finalize the scale bar that appears in the bottom right corner of the map. Since the template he uses comes pre-configured with a MAPublisher cale bar, it’s only a matter of dragging and dropping the scale bar layer into the appropriate MAP View. If you recall from earlier, Steve set up this new map-view with its own map scale and projection, meaning the scale bar will automatically be adjusted to fit the map data once it is placed in the new MAP view, creating an accurate and informative scale for viewers.

Lastly, Steve uses the MAPublisher LabelPro add-on to apply labels to each of the municipalities in his map. Similar to MAP Themes, the LabelPro tool allows Steve to configure rules-based label layers that manage label placement and style. The labelling engine ensures that labels are placed to avoid collisions, eliminate label overlap, and reduce label clutter. Finishing the map with a few minor touch-ups and voila!, Steve has finished his Pennsylvania District 17 Map in less than 15 minutes!

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About the Author

Steve Spindler has been designing compelling cartographic pieces for over 20 years. His company, Steve Spindler Cartography, has developed map products for governments, city planning organizations, and non-profits from across the country. He also manages wikimapping.com, a public engagement tool that allows city planners to connect and receive input from their community using maps. To learn more about Steve Spindler’s spectacular cartography work, visit his personal website. To view Steve’s other mapping demonstrations, visit cartographyclass.com

People, Parks, and the Pandemic: Designing Infographics with Avenza MAPublisher

Resources

Here at Avenza, we love finding interesting data and using it to create engaging maps. In this blog, we show you how we used the powerful spatial data manipulation and cartographic styling tools found in MAPublisher for Adobe Illustrator to create an infographic exploring how park visitor patterns changed in the United States in 2020 using a truly interesting openly available dataset.

Recently, Google made its COVID-19 Community Mobility Reports public. These reports use aggregated anonymous mobile GPS data to explore how global human activity patterns in specific location categories (parks, retail, transit, residential, workplaces, and grocery) changed as a result of the ongoing pandemic. The U.S. dataset is massive, containing estimates of daily visitor activity for each location category in every county. Each data point provides an estimate of that day’s percentage increase or decrease in visitors relative to a pre-pandemic baseline period, meaning the data reflects how pandemic restrictions on that day may have impacted park space usage in that specific location.  Below shows a sample of the raw dataset, listing five data points covering Feb 15-19th activity patterns in a single Colorado county.

We downloaded the complete dataset (February to November 2020) from Google’s mobility reports data portal. The dataset contains nearly 900,000 records of all 3,143 counties in the U.S.  We wanted our infographic to focus on the parks category, which includes every national, state, and local park, as well as public forests, campgrounds, beaches, marinas, dog parks, and gardens. Using the open-source statistical programming language R, we were able to aggregate the dataset into a more manageable size. Below, you can see how some basic filtering of these “cleaned” datasets already shows evidence of some interesting patterns, but we felt that mapping the dataset would be much more engaging.

Maps are powerful story-telling tools, and we felt this data would be more interesting if you could see how park visitor patterns changed not only with time but also with geography. To make working with map data in Adobe Illustrator easier, we used the MAPublisher Import tool to load in a shapefile of U.S. state boundaries. The tool allows us to treat our dataset as a fully functional graphic element in Illustrator while still retaining all geographic properties integral to spatial data (attributes, topology, and coordinate systems). 

To visualize the data as a map, we needed a way to associate each record in our tabular dataset to a specific location (in this case, a State). To do this, we used the Join tool, which takes our “cleaned” tabular parks dataset (stored as a CSV file), and links it to our mapped states shapefile using the shared State names column. 

We started to think about how to design the layout of the infographic (this is where having a mapping environment in Illustrator really shines). We wanted it to consist of three main parts: a large labelled map showing the average change in park visits over the entire year; a vertical series of maps showing how park visits varied month to month; and a handful of pop-out maps with insets highlighting specific points in the year and specific regions of the country.

We chose to stylize the data into thematic maps, which use colour to represent specific values in the data at different locations. Instead of tediously configuring individual colour fills, we used MAP Themes to establish a rules-based stylesheet that applies a colour automatically to each State based on the monthly park visitor columns stored in the map layer’s attribute table. We chose a “thematic map” colour group from the included ColorBrewer 2 swatch library to best show positive and negative changes in park usage. 

Next, we populated our main map with labels showing the percentage change in park use for each state. As many cartographers know, placing and configuring labels can be a significant time sink. Fortunately, we could use the MAPublisher LabelPro add-on to provide collision-free, rules-based label placement. We could configure the label rules to automatically handle collisions, alignment, and placement of labels for each state. Using the leader lines option in the LabelPro Rules panel, we were even able to create offset labels that prevent crowding the map.

Finally, we decided that to create some insets to highlight specific parts of the country.  From a “master” map,  we used the Crop to Shape tool to crop the map data to our desired inset extents. Using Crop to Shape is quick, and also retains the styling elements (colours, labels, strokes), topology, and attribute integrity of the cropped map layers. 

With most of the maps completed, all that was left was to populate the infographic with text and graphics. Using the MAPublisher layout tools, we added a functional North Arrow and customized the automatically generated legend layer to suit our infographic’s design. Lastly, we used an Illustrator graph tool to create a vertical line graph of park activity along the left side of the infographic.

Presenting the dataset in this way makes it much easier to extract insights and craft a story from the data. Some patterns are immediately noticeable, such as the overall increase in park space usage that is observed for most of the US during the pandemic period. This isn’t exactly unexpected, as parks were one of the most accessible forms of leisure activity and recreation amid widespread social distancing and retail/entertainment closures. We also see how state-specific factors may have affected park usage in different regions of the country at different times. Some states, such as South Dakota, had eased restrictions on out-of-state visitors to their park systems, resulting in a spring season surge in park usage earlier than their neighbours. Conversely, states which typically draw a high proportion of international tourists, such as California, Hawaii, and Florida, saw more of a decrease in average park usage as a result of global air travel decline. These patterns and stories are one of many that can be identified, providing compelling examples of why maps are such powerful tools for visualizing data.

The beauty of working with MAPublisher to create this map-heavy infographic is that we were able to implement the powerful mapping and data manipulation tools of a dedicated GIS while seamlessly integrating the advanced art and design tools offered by the Adobe Illustrator graphical environment. Together, these tools turned what would have been a complex workflow of importing and exporting data between different software, and allowed us to create the entire infographic in a single mapping and design-focused fully integrated workspace.

See the Full infographic below:

 

References:

Data – https://www.google.com/covid19/mobility/
Pandemic Timeline – https://www.ajmc.com/view/a-timeline-of-covid19-developments-in-2020
Raw Park Visitor Stats – https://irma.nps.gov/STATS/
Camping Stats – https://koa.com/north-american-camping-report/

News Reports and Park/State-Specific Articles

“Camping in Tennessee’s State Parks Increase during Pandemic.” Wreg, AP, 9 Dec. 2020, wreg.com/news/camping-in-tennessees-state-parks-increase-during-pandemic.

Marcus Schneck. “Camping at Pennsylvania State Parks ‘Going through the Roof’ as Coronavirus Restrictions Ease.” Pennlive, 1 July 2020, www.pennlive.com/coronavirus/2020/07/camping-at-pennsylvania-state-parks-going-through-the-roof-as-coronavirus-restrictions-ease.html.

Anderson, Patrick. “National Parks in South Dakota Remain Open as Others Close across the Country.” Argus Leader, 17 Apr. 2020, eu.argusleader.com/story/news/business-journal/2020/04/17/coronavirus-south-dakota-national-parks-remain-open-others-close/2981675001.

Henderson, Catherine. “Having a Hard Time Finding a Campsite in Colorado This Summer? You’re Not Alone.” The Know Outdoors, 15 July 2020, theknow.denverpost.com/2020/07/15/colorado-camping-covid-national-parks-state-parks/241704.

Wiley, Melissa. “What the 10 Most Visited National Parks in the US Have Said about Their Plans to Reopen, from Opening in Phases to Implementing Social Distancing Guidelines.” Business Insider, 21 May 2020, www.businessinsider.nl/are-national-parks-open-covid-19-coronavirus-united-states-nps-2020-5?international=true&r=US.

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