This fantastic animated visualisation by Joshua Stevens shows black carbon being dispersed into the atmosphere as a result of fires across Australia. The data is from the GEOS forward processing (GEOS-FP) model, which regularly takes observed data and uses that to work out what is going on in the atmosphere.

If you wander around any particularly large city, especially in winter, you’ll notice how little sunlight actually reaches the streets. In this visualisation (and accompanying story), The New York Times explore how the shadows of New York City change over the year. What’s really cool is that you can interact with the visualisation to find out how long a particular part of the city is in shadow over the day in each season.

And just like that, the #30DayMapChallenge is over! It’s been a pleasure witnessing all the amazing spatial visualisations that have been produced over the past month. So many people were involved and it’s been fascinating to see the wide range of approaches to each theme. It’s also been a fantastic demonstration of the power of free and open tooling, with many visualisations created using QGIS or Web-based mapping frameworks.

I’m planning to highlight a selection of my favourite visualisations for a future issue, though for now I wanted to link to a great resource by Aurelien Chaumet who has collated a large number of entries from the past few weeks. Mapspiration galore!

Offset Earth is a subscription service that plants trees and supports carbon offset projects on your behalf. For a relatively small amount each month you’re able to move closer towards reducing the impact of your carbon emissions. Not only that, the supported projects help benefit the local communities by creating sustainable jobs and restoring wildlife habitats.

What I like about Offset Earth is that they make the entire process simple, guilt free, and in a way also gamifying it. There’s something addictive about seeing your virtual forest growing on your profile, which in reality isn’t virtual at all. Other people can also donate trees to your forest, which is a lovely alternative to gifts that you don’t really need.

I’m by no means a perfect global citizen, and can no doubt do much better in many areas of my life, however initiatives like this are a great start. The way I look at it is that doing something like this is far better than doing nothing at all.

If you like the idea then sign up using my link as we’ll both get some extra trees. More importantly, the planet will get some extra trees!

If you use R for spatial visualisation then you’re probably already aware of Rayshader. For those of you who haven’t heard of it before? Well, you’re in for a treat.

In short, Rayshader is a framework for 2D and 3D data visualisation in R. One of the cooler aspects of it is the ability to create realistic spatial visualisations that utilise lighting and other fun stuff. The latest update brings with it a range of improvements, like a high-quality renderer, OBJ export, and more.

I’ve been working with NetCDF data a lot over the past few weeks. Something that quickly becomes obvious with NetCDF is that, while powerful, it’s not the simplest data format to work with for creating visualisations.

With this in mind, I was happy to stumble across Panoply — a visualisation tool created by Nasa for interrogating and visualising NetCDF data. I’ve found it really handy for quickly investigating a dataset and throwing together some basic maps. From there I can then do some heavy lifting using other tools like GDAL.

For the QGIS users out there, you’ll want to check out the latest 3.10 release. The update brings with it a huge amount of improvements; including changes to the labelling system, a logarithmic scale for graduated styles, tonnes of layout and print composer improvements, to name just a few.

I highly recommend checking out the changelog linked above to get a full sense of the updates that relate to your workflow.

In this post, Sajjad Anwar from Development Seed takes a look at the future of OSM and how we’re going to get there. Key takeaways are more focus on verification, better utilisation of AI, and notification when the physical world changes and the map needs to be updated. There are some interesting insights here and I’m excited to see how OSM is going to evolve over the coming years.

An old one but a good one! This relatively short post on the NASA Earth Observatory blog tackles the topic of scaling data in spatial visualisation. Specifically, it looks at the differences between linear and logarithmic methods for stretching the intermediate values and how to choose the right start and end values for better contrast.

If you use GeoTIFF then you’ll be interested in this post from Koko Alberti. In it he takes a detailed look at the various approaches for compressing GeoTIFF and optimising it for lower file size and decent performance, including benchmarks on read/write speeds and a variety of other metrics. An incredibly useful resource.

Public transport datasets are amazing, especially when they include the real-time position of each vehicle. Fortunately, a lot of cities and transport authorities are realising the value of this data and making it available through APIs. The linked dataset here is for real-time positioning of public transport in Helsinki — it’s one of the best.

If you’re like me and weren’t able to attend NACIS this year then you’ll be glad to hear that the videos of the talks have been released and are available on YouTube. So many amazing talks on so many different topics — this’ll keep you busy!

One event that slipped under my radar this year is OpenGeoHub. It looks like it was a really interesting one and the talks have been uploaded to YouTube.

It’s been a pleasure seeing the maps submitted by Cristina for the #30DayMapChallenge — they have a fantastic attention to detail and design. Each has been submitted through her agency z creative labs, which is also worth checking out. Cristina’s Twitter feed is a recommended follow both for mapspiration as well as data visualisation and design content.