FaceApp and similar reality-warping applications are especially fun to use in ways their designers never intended. Along similar lines, Google’s DeepDream (designed for photo manipulation) creates fascinating results using photographs but is even more stunning when applied to representations of cityscapes.

While training DeepDream (a neural network that adapts like a brain to new inputs) to identify, differentiate and understand images, Google researchers discovered it could “over-interpret” results as well. In short: it could start to “read into” images from previous experience, resulting in an array of beautiful (if disturbing) hybrids.

Once it went public, mapmakers were among those intrigued by the possibilities of geo-visualization, turning flat maps into seemingly living landscapes. Tim Waters, a geospatial developer, began taking OpenStreetMap data and running it through the system, generating these strangely psychedelic urban environments.

He discovered that a short run could create fractal and quilting effects, while longer and reiterated processing started to introduce faces and creatures to the mix.

Above: monkeys and frogs seem to emerge from the grid, while a coastal region forms the head of a bear, making the landscape look like a giant bearskin rug. Overall, the effects are quite beautiful, creating a sense of depth and adding character to what would otherwise be fairly generic representations.

A powerful tool for artists, designers and researchers, Terrapattern lets users seek out similar-looking locations from an aerial perspective, finding connections and patterns between disparate landscapes and built environments.

The premise is simple: start with a single place, be it a park or street, stadium or shipyard, then let the tool work its magic. The results are uncanny: colors, textures and shapes tied together by computer vision and clever algorithms. The broader use cases are infinite, but specific ones are possible too, like: a user could look for abandoned ships floating around the island of Manhattan.

The system works by looking at its subjects in layers, looking for identifying features like curves, edges and shadows that indicate height. In a way, its task is similar than some pattern recognition software since it is not called upon to identify the subject, just match it.

“For our purposes,” explain the creators, “‘interesting’ features are anthropogenic or natural phenomena that are not only socially or scientifically meaningful, but also visually distinctive—thus lending themselves ideally to machine recognition. Examples could include things like animal herds, methane blowholes, factories, destroyed homes, or logging roads. Many other patterns await discovery.”

The system draws on data from OpenStreetMap, combing through hundreds of thousands of images looking for something like whatever you submitted. Researchers can use tools like this to monitor natural habitats or make archaeological finds, but ordinary people can employ this tool to create art or make inquiries about the cities they live in. Even a quick tour around the engine reveals emergent macro-patterns from individual tiles, some worthy of wall art treatment.

Terrapattern’s creators are indeed excited for more non-standard and unexpected uses: “Terrapattern is ideal for discovering, locating and labeling typologies that aren’t customarily indicated on maps. These might include ephemeral or temporally-contingent features (such as vehicles or construction sites), or the sorts of banal infrastructure (like fracking wells or smokestacks) that only appear on specialist blueprints, if they appear at all.”

Using augmented reality highlights, hints and cues to guide bikers through complex city paths and streets, this conceptual system addresses issues of wayfinding and safety, speculatively asking: “Could a cycle path be created, or at least augmented, using connected technologies?”

Five initial functions are proposed by the Connected Cyclists project for this wearable prototype, all around themes of navigation in London, a place notorious for the variety of its path types and unexpected route shifts. With so many transitions between street paths, parks and alleyways, it can be hard for bikers new to the city to know where to go – subtle highlights of next steps could solve that problem.

“We see that cyclists often take bearings when paused at traffic lights—this interface could essentially simply provide the next direction, reinforcing the journey. We also feel that the visual nudge implied here, using the fabric of the city itself, is more akin to how cyclists move and navigate—a more fluid movement through and sometimes across the streetscape, as opposed to the very directed navigation delivered for drivers.”

Blind spot visualization assists travelers as they pass in the shadows of cars, buses and trucks, while an overall approach promoting backstreet network paths helps avoid traffic and poor air quality in the first place. Monuments, icons and landmarks displayed subtly in the background can also give clues to riders about where they are in the city.

Already there are many programs like CityMapper built on OpenStreetMaps that contain the necessary information about routes and paths but using those on the go via a typical mobile device means either unsafe cycling practices or frequent stops, hence the augmented heads-up display. “If these displays talked to the city around them—if they knew where the cyclist was and what they were looking at—they could give much more subtle spatial and contextual information that builds on the surroundings of the cyclist.”

The key is making such technology accessible and seamless, a distraction-free overlay to other visual information being taken in by those on bikes moving through the urban environment.

“Many cities are spending serious money, time and attention on improving the ‘hard infrastructure’ of cities to make cycling safer, more convenient, more attractive,” but “there is potential of a ‘soft infrastructure’ which can be overlaid on existing urban fabric to further support cycling, which takes advantage of contemporary technologies such as wearables, the internet of things, real-time sensor data, and so on.”

While none of this is a reality quite yet, “‘Design stories’ allow you to try on a future for size, and to imagine how a prototype might fit into its urban context. With prototypes to point at, critique and discuss we can begin to imagine other externalities or knock-on effects and build up both understanding and language to discuss what can otherwise be fairly abstract and technical ideas.”

Taking customized couture to the streets, Monochome allows you to turn any urban grid at a scale of your choice into a unique tank top, t-shirt, flare or pencil skirt.

Using OpenStreetMap, the company lets you select between a black-on-white figure/ground representation or more traditionally-gridded white-on-black map. Ordered now and these should arrive by Christmas – a perfect holiday gift to compliment some urban grid dog tags.

The user-friendly selection tool allows you to get incredibly precise with your pick, creating a composition that is both personalized and aesthetically pleasing through a combination of panning and zooming. The above set of four examples, for instance, are simply variations on the same location at different scales.

A number of standard cities are presented but you can also search for your own location or address or your choice. Due to the nature of OpenStreetMap, you are encouraged to add data for any place not already in the system.

Like giant-sized fingerprints, urban grid patterns are unique to each city – this project turns that individuating property into an wearable asset, allowing you to hang you hometown or favorite metropolis around your neck as a point of pride.

Currently in crowdfunding on Kickstarter, the Urban Gridded Dogtag set is a “collection of unisex accessory so that architects, cartographers, urban planners, urban explorers, nomads, travelers, jet setters” and others can enjoy. New York City, San Francisco, Paris and Tokyo – can you tell which is where? Many more are also shown below.

The tags come in laser-cut black, gold-plated or stainless steel, with circular variants also available for those who want something without the implicit military reference. Many major cities have already been ‘unlocked’ and further ones will become available depending on how well-funded the campaign becomes before it closes (just one week left!).

From the creators: “Each piece is carefully designed to capture the cities underlining iconic street network as a lace-like pendant. The information is sourced from gps data by openstreetmap to ensure accurate portraits of the city. With chemical etching technology, the pendants are produced on thick .020″ Stainless Steel with a high level of detail, consistency, and quality. We strive for the component of the dogtags to be locally sourced, made in the USA. Including packaging and mailing supply.”