Park Tiles is one of my main responsibilities as a National Park Service cartographer. My predecessor, Mamata Akella, is responsible for creating Park Tiles. When I took her place at NPMap in 2015, I became responsible for overseeing the release of version 3 and designing a new style: Light. Since then, I've also worked to reorganize all the code (CartoCSS) to be size efficient and easily updatable.
Park Tiles is a suite of online basemaps designed to fit the National Park Service’s graphic identity. Built with simplicity and flexibility in mind, Park Tiles basemaps can be used as stand-alone reference maps, or customized web maps with additional data overlays. Park Tiles integrates with Places, giving parks complete control over what data appears within their boundaries. Outside of park boundaries, Park Tiles relies on OpenStreetMap data to provide additional context.
Behind the scenes
Park Tiles is built using Mapbox Studio Classic – a program designed for building CartoCSS styles to render source vector tiles into raster tiles for display in a web browser. Park Tiles version 3 uses custom NPS data inside of park boundaries and OpenStreetMap data outside of park boundaries. To blend the two data sources, we developed an approach that uses three separate tile layers to isolate base data, OSM data, and NPS data, combining them only on the browser end. The approach works well for many parks, but since we rely on parks and regions to create and provide the data, there remain empty parks, or parks for which NPS data runs outside of park boundaries. Park Tiles is a huge collaborative effort, and therefore will always be a work in progress. However, since the release of Park Tiles 3 in early 2016, nearly 100 parks have already adopted Park Tiles on their public websites as the default visitor map. View an example of Park Tiles in the wild at one of our nation's most popular parks: Great Smoky Mountains National Park.
Park Tiles Styles
Park Tiles 3 offers a suite of basemap styles to support a wider range of NPS maps. Bringing all these styles into alignment (and designing a new one) was a major goal for my first few months of work at NPMap. The default style for Park Tiles 3, Standard, was designed to serve as a general-use, reference basemap. However, maps built with a narrower purpose and audience can work better with alternate styles. If seeing everything on the ground is a priority, Imagery may be appropriate. If a data overlay needs to stand out, Slate or Light may provide more suitable contrast. More basemap styles means more flexibility. These styles are available for parks to use in NPMap tools like NPMap Builder or NPMap.js.
Standard is the default style for Park Tiles 3. Standard is designed to reflect the NPS graphic identity established by Harpers Ferry Center with muted colors but enough contrast and clarity to serve as a stand-alone reference map on a park website. A detailed style reference for the Standard style is a available here.
Imagery replaces the subtle tans and greens of Standard with vibrant satellite imagery provided by Mapbox. Imagery displays park labels, general place labels, and NPS road and trail labels inside park boundaries. NPS Places road and trail features are translucently styled inside parks to offer context where these features cannot be seen in the satellite imagery. Satellite imagery is visually busy, posing challenges for clearly overlaying other data. However, in appropriate contexts, it can be used to show real-world detail that does not appear on simpler basemaps.
Slate offers a dark grey basemap that helps brightly colored overlay data stand out. Dark basemaps have become popular for displaying thematic data with a modern aesthetic, and Slate allows parks to join in on this trend. Fashion aside, Slate was also designed with low-vision viewers in mind (see original blog post). Users who invert colors in their browser for easier viewing will find that Slate remains more legible than other styles.
Light was my first major contribution to the NPMap suite of basemaps, designed to be extremely low contrast and nearly colorless – ideal for overlaying any kind of additional data. Light offers just enough context to present data that can almost stand on its own.