The most comprehensive reference on cloud-optimised geospatial data formats so far is brought to you by NASA IMPACT, Development Seed and the Cloud-Native Geospatial Foundation.
The guide includes detailed descriptions of increasingly popular data formats like COG, Zarr, COPC, GeoParquet, FlatGeobuf and PMTiles. It’s an essential bookmark if you deal with geospatial data on the Web in any form.
Very Spatial has compiled a collection of free and open books on spatial analysis.
I am teaching a straight forward, stand-alone Spatial Analysis class for the first time in a couple of decades. That means that I have been looking at resources to share with the class, especially reference materials that they can access given that they will mostly forget what I tell them by February once the next semester is in swing.
The call for presentations for next year’s FOSSGIS conference is now open until 6 November. Every year, FOSSGIS gathers German-speaking makers and users of geospatial open-source software and the OpenStreetMap community. The conference organisers are looking for proposals for presentations, lightning talks and workshops covering project news, use cases and research.
FOSSGIS 2024 will be hosted in Hamburg at the TUHH campus from 20 to 23 March 2024.
FlatGeobuf, GeoParquet, PMTiles, whatnot—I find it hard to understand when and how to use new cloud-native data formats. Brandon Liu has answers.
For analytics use FlatGeobuf or GeoParquet:
FlatGeobuf and GeoParquet are analysis-focused formats. They’re useful for answering queries like What is the sum of attribute A over features that overlap this polygon? But their design does not enable cloud-native visualization like COG does.
You can convert FlatGeoBuf and GeoParquet data into cloud-friendly formats using tools like Tippecanoe:
The best-in-class tool for creating vector tiles from datasets like FlatGeobuf and GeoParquet is tippecanoe, originally developed by Mapbox, but since v2.0 maintained by Felt. Tippecanoe doesn’t just slice features into tiles, it generates smart overviews for every zoom level matching a typical web mapping application. It adaptively simplifies and discards features, using many configuration options, to assemble a coherent overview of entire datasets with minimal tile size.
The output from Tippecanoe can be PMTiles a format that can be read in the browser:
The last missing piece is a cloud-friendly organization of tiles enabling efficient spatial operations. This is the focus of my PMTiles project, an open specification for COG-like pyramids of tiled data, suited to planet-scale vector mapping.
The post doesn’t go into any technical details. I enjoyed as a short and sweet overview of these new(ish) formats and how they are related.
This post by Jed Sundwall is a comprehensive look at the current state and future of Source.Coop, a repository for open data by Radiant Earth.
MapStack has similar goals, and back in May I wrote:
Mapstack doesn’t tie in with existing tools. Currently, there is no tooling to create or manage data, collaborate or visualise the data. It’s a place where the result of data processing might be hosted. Open data providers have invested in the infrastructure to host data—it’ll be hard to convince them to migrate to Mapstack instead.
I have similar thoughts about Source. These data repositories can be useful for providers of small-scale datasets who don’t want to run their own infrastructure, but I question whether we’ll see large, global datasets on these repositories. But Source already hosts several substantial datasets from big names such as NASA, ESA, or CGIAR, presumably because of well-established networks by the people involved in building Source—I have been wrong about these things before.
Currently it’s hard to understand what data is available on Source without paginating through all datasets. The platform lacks advanced search functionality that lets me look for data by geographic region, data format, or time. And to preview the data, I have to download it first and use third-party tooling. A map or table preview on the website would be far more convenient for people to explore data. (Both of these features are on the Source’s roadmap.)
A comprehensive overview of libraries, command-line and web tools, frameworks, and data providers that have already adopted the recently released GeoParquet 1.0 standard.
Geofencing business Radar introduced a new suite of APIs, aiming to get a slice of Google Map’s and Mapbox’ business:
Radar Maps Platform has it all, including base maps, geocoding APIs (forward geocoding, reverse geocoding, IP geocoding), search APIs (address autocomplete, address validation, address autocomplete), routing APIs (distance, matrix, route optimization, route matching, directions), and UI kits (address autocomplete).
Our beautiful vector base maps support classic, dark, and light themes. You can easily add base maps and UI kits to your website with v4 of the Radar JavaScript SDK.
There is nothing ground-breaking in the announcement; the features offered in the platform are the pretty standard. But Radar’s pricing is competitive, so you might as well keep this one on our radar. (Yeah, I love a rubbish pun.)
A new map style has been added to the OpenStreetMap site:
It’s a mix of osm-carto and OpenTopoMap. It has many improvements: more tag support (busway, embankment, cuisine, solar plants, aquaculture, pitch, sea, tree etc.), CJK fonts, etc. There is also better internationalisation: country specific road shields, peaks using imperial system in the US, hierarchical place rendering in China, etc.
Zoomed in, it looks a lot like the standard OSM styled. In lower zoom levels, it reminds me of school atlases I grew up with. Very nice.
How hard can it be to make two simple maps, one showing the location of addresses and one showing sales by US state? James Killick tried products from all the big names—ESRI, Google, Microsoft, and Felt. Turns out, getting started is not straightforward.
Killick went into the experiment pretending he had no prior experience, which I think is unfair. Complex software is a reflection of a complex problem space, great flexibility, or both. Not everything can and should be dumbed down to the level a disinterested teenager can be bothered to understand. Instagram is easier to use than a traditional camera but the photos all look the same. Mapping software, like any design tool, requires domain knowledge: You need to know what you want to achieve. You need to know what kind of maps exists, and which can be used to most effectively represent your data. If you know these things you’re more likely to already know the right tools and where to find them.
And let’s not forget Felt is just over one year old now but they already raised the bar for map-tech user experience and managed to remove a lot of complexity from the process through clever design and impressive software engineering. Give them a little more time and they will further change the way we think about making maps. In a few years time we might ask ourselves why map-making was so difficult in 2023.
From the MapScaping blog:
However, map tiles are the only way to create a seamless, smooth and multi-scale user experience for large planet-scale geo-data. Even as devices become more powerful, the detail and volume of geo data grows commensurately. The boundless supply of rich data, combined with the demand for smooth, instant-loading maps, means tiling will always remain an essential part of the digital mapmaker’s toolkit.
Are Map Tiles an Obsolete Technology? The answer is “no.” Betteridge’s law of headlines holds up.