VersaTiles is a set of open-source applications that form a complete stack to create, host, and visualise OpenStreetMap data on the Web using vector tiles.
From the VersaTiles website:
VersaTiles lets you use OpenStreetMap based vector tiles, without any restrictions, locked-in paid services or attribution requirements beyond OpenStreetMap. You can use the freely downloadable tilesets from VersaTiles on your own infrastrure, in any way you like. Our open spec, royalty free and permissively licensed conatainer format works with virtually any webserver or CDN — with no requirement to pay unreasonable prices for “Tiles-as-a-Service”.
It includes a tile generator, based on TileMaker that produces tiles in the Shortbread schema. A converter produces tiles in the custom *.versatiles format from MBTiles. The VersaTiles format results on a smaller footprint—compared to MBTiles—and it doesn’t use SQLite under the hood. That means you can host it pretty much anywhere, either using the VersaTiles server or on a CDN; and clients can utilise HTTP range requests to access a subset of the data. The front-end is based on MapLibre, and includes map styles and a range of open-source fonts.
OGC Web Map Service (WMS) layers (Yes, they still exist),
A terrain extension allows developers to render 2D data on a 3D surface, and
Collision filters, hiding overlapping features and resulting in cleaner visualisation of dense data.
Deck.gl doesn’t get much recognition, but it looks like a serious web-mapping toolkit.
The market for open-source web-map libraries is getting crowded again. Some classic libraries are still around: OpenLayers, Leaflet, and MapboxGL (technically not open-source). With MapLibre, Gleo, and Deck.gl, some promising new implementations are on the rise. Technology-wise, map front-ends have stalled in the last couple of years. I hope this newfound competition results in advancements in the field.
Planet has published a library of React components to build map user interfaces using OpenLayers:
The @planet/maps library provides components for rendering maps in your React applications. The library acts as a wrapper around OpenLayers, transforming the imperative API into declarative components.
The purpose of this project is to provide a mapping between React’s declarative components and OpenLayers’ imperative API. In other words, this project provides a React renderer for OpenLayers.
Components exported by this package map 1:1 with classes exported by OpenLayers.
Component props map directly to properties that are settable on instances of OpenLayers classes. Exceptions to this are props like options (passed to the constructor only), listener props (e.g. onChange), and ref.
Components accept a ref that provide access to the underlying OpenLayers instance.
The examples only show a small fraction of the whole feature set of the library. I looked through the source code on GitHub, and it seems like many—if not all—OpenLayers classes have a corresponding React component in the library.
Leaflet, MapboxGL and Google Maps are supported; of the major contemporary libraries, only OpenLayers and MapLibre are currently missing. Terra Draw supports creating and editing points, lines, polygons, and circles and even includes a freehand tool.
Most products are set on one mapping library, and Terra Draw will be less valuable. But there are a couple of scenarios where Terra Draw is useful. Terra Draw could be an option if you’re building a new product and haven’t decided (or don’t want to commit) to one mapping library or base map provider. It allows you to focus on the problem, not the technology. In consulting, when different projects often require a different provider, Terra Draw allows transferring solutions across various projects, potentially freeing up time to work on other things. And TerraDraw enables you to adhere to engineering best practices: The drawing implementation is abstracted away so you can switch libraries later; for example, when a vendor decides to change to a more restrictive proprietary license.
Iván Sánchez Ortega introduces Gleo, a WebGL mapping library he’s been working on for a couple of months now:
Why you ask, if we already have OpenLayers and MapLibre doing pretty much the same thing:
The point is being able to understand the architecture of a WebGL map library. Because, as I said several times during the conference [FOSS4G], I still don’t understand what a “bucket” is in Maplibre parlance.
Building something for the sake of understanding the fundamentals of some technology is a perfectly fine reason to reinvent the wheel.
You can view the code on GitLab or follow Iván on Mastodon or Twitter, where he posts regular updates about his work on Gleo.
A design proposal for the modularization of the map rendering architecture can be found at #547. This modularization will allow new rendering architectures to be implemented quickly and more easily, and we anticipate that the modularization will give us a concrete framework to better interrogate various migration strategies.
I love this approach, gathering feedback from the community before starting the work to make actual changes to the code and architecture.
Polylines are an efficient way to represent line geometries. You provide a geometry, and out comes a scrambled string of letters and numbers that encodes the geometry in just a few characters. Polylines are helpful when you want to efficiently transfer geometry information between services. The Mapbox Static Images API, for example, can overlay complex geometries from Polylines, which wouldn’t be possible otherwise because the request-URL length is limited.
Leaflet was one of these libraries that I thought were done. While there have been constant updates and new releases throughout the years, there were rarely any massive, ground-breaking additions. Leaflet is built perfectly against its small, well-defined scope. Huge changes just weren’t necessary.
Dropping support for Internet Explorer.
This has been a long time coming, but now that Internet Explorer is officially end-of-life, it’s time to say goodbye. Going forward, Leaflet will move to an evergreen strategy that targets browsers like Firefox, Chrome, Edge and Safari.
Removing the Leaflet global.
As a developer using Leaflet, the capital letter L is probably intimately familiar to you. This is the Leaflet global where all of Leaflet’s functionality lives. To allow compiler tooling to better eliminate dead-code through a process called tree-shaking, we are removing this global variable. To preserve backwards compatibility with older plugins, we will provide a shim that can be imported manually that will restore this functionality.
There’s no release date, not even an estimate, and maintenance of the 1.x branch will continue in the meantime.
Felt have hired Erica Fischer and are reviving development of Tippecanoe, which hasn’t seen many updates in the last couple of years. The last release was on over two years ago.
Tippecanoe is an essential tool for geospatial-data providers. It creates vector tile sets from various geospatial formats and optimises the data for visualisation purposes, so the resulting maps allow viewers to understand the density of a data set without clustering or excluding data.
Speaking in the Felt blog, Erica hints at what might be next in store for Tippecanoe:
The special challenge of Tippecanoe at Felt is that it is being applied to user uploads with no opportunity for manual configuration, so it has to be able to make efficient, faithful, good-looking tiles without being given any hints about what kind of data it is tiling. I already know that it doesn’t currently do very well at low zoom levels with topographic contours, or with gridded data represented as individual polygons, or with continuous urban parcel polygons, or with branching systems of rivers, and I’m sure the uploads will also soon reveal other usage patterns that need to be detected and given some special treatment.
MapServer, together with PostGIS, was one of the first open-source GIS libraries I used as a Geography student some 20 years ago. If my memory isn’t too clouded, MapServer was among the first open-source products to implement OGC standards. Fantastic news that it’s still under active development and keeping up with the latest developments in the industry.
Just in time for FOSS4G next week and the annual OpenLayers Feature Frenzy, the OpenLayers team has released 7.0.0, a new major version. Over 90 pull requests went into this release, but two changes stand out: Internet Explorer is no longer supported. And WebGL rendering has been extended to support lines and polygons alongside points.
A renderer converts geo-data into data structures that browsers can render. In the past, OpenLayers has primarily relied on the Canvas API to render vector data. Compared to Canvas, WebGL is considered more performant, especially when visualising complex geometries or large datasets.
Adding more WebGL-rendering capabilities to OpenLayers has been an ongoing effort in the last few years, and there’s more to come:
The rendering API is still low level and experimental. Future releases will include a higher level styling API.
Technically this is a breaking change, but upgrading should be straightforward, according to the release notes:
[W]e changed the signature for a number of methods on a helper class that had been marked as part of the API in 6.x releases. While this is technically a breaking change, it is unlikely that applications were using this helper class, so upgrades should be straightforward.
I somehow missed this: Bertin.js has reached a significant milestone with its 1.0 release.
Bertin.js provides a comprehensive API to make thematic maps using classification, cartograms and tooling to add map components, such as titles, footers, legends, or graticules. It is a wrapper around D3’s powerful mapping capabilities, providing reasonable defaults so you can focus on designing your map and don’t have sweat intricate details such as creating a legend and specifying individual pixel coordinates to perfectly align symbols and labels.
Following last week’s post explaining the tile-addressing schema in PMTiles version 3, Brandon Liu now discusses its compression approach reducing the disk space required to store a global tile dataset to only 91.6 MB.
Update: Brandon clarified on Twitter, the 91.6 MB mentioned above only holds the data required to map Z,X,Y coordinates to the corresponding Tile ID. The actual global map data set is 80GB. (15 August 2022)