Community features 3 facts, 5 geo people Earlier this week I stumbled across the “3 facts, 5 geo people” conversation doing the rounds on Twitter. In it various people within the spatial community have been opening up and sharing some facts about themselves and advice for others. More stuff like this
Community features Map with Me Map with Me is a fun tool created by Javier Arce — it’s a way to create maps with your friends and other people online. The code is also open and able to be taken and remixed to create your own version if you’
Community features Joshua Stevens You may not already know about Joshua but you’ve probably seen one of his visualisations online or in the news. He works at NASA Earth and is the Data Visualisation and Cartography Lead there. He’s constantly working on and sharing interesting visualisations,
Community features NOAA climate and atmospheric data If you’re interested in weather and atmospheric data then you’ll love the datasets available from NOAA. From weather models, to satellite imagery, to radar data captured during severe weather events. Data Access | National Centers for Environmental Information (NCEI) formerly known as National
Community features Annotated LIDAR point cloud of Dublin The Urban Modelling Group at University College Dublin have captured and released an annotated LIDAR dataset for an area of Dublin. The annotated data is incredibly detailed, down to individual doors and windows in some cases. DublinCity: Annotated LiDAR Point Cloud and its Applications
Community features Stop using zip codes for spatial analysis In this article, Matt Forrest makes his case for why zip codes are bad for accurate spatial analysis and insight. He delves into the history of the zip code and its quirks — for example that the codes aren’t attached to a geographic area,
Community features How geological maps made the Apollo Moon landings worthwhile We’re still not quite done with map-related content about the Moon landings. This time I’m featuring an interesting article on how geological maps were integral in the planning and ultimate success of the Apollo landings and the science that followed. How geological
Community features Mapping all the tunnels under Washington, D.C. I find subterranean data and maps incredibly interesting for some reason — probably because they’re maps of things that are otherwise invisible. This article on the various tunnels underneath Washington, D.C. delves into just what sort of tunnels exist (and why), as well
Community features LandViewer now features change detection that runs in-browser It’s now possible to perform change detection analysis of satellite data without leaving your browser through the LandViewer. The new change-detection tool allows you to perform pixel-based comparison between satellite images and do things like outputting the difference between the images (eg. detecting
Community features H3: Uber’s hexagonal hierarchical spatial index While not new, Uber’s H3 spatial index framework is well worth a highlight. Originally created to optimise their ride pricing and dispatch, the hexagonal approach has proven popular and is being used by a variety of other people. The link details how it
Community features AgentMaps If you’ve ever played Sim City then you’ll be familiar with agent-based simulation in a spatial context, from the individual people all the way down to the energy and water as it flows through the network. AgentMaps is a JavaScript library for
Community features Netherlands building ages Using an open dataset of building and address data, this interactive 3D map visualises the age of buildings across the Netherlands. The age needs to be taken with a pinch of salt — as it’s been proven to be inconsistent in places — however it
Community features The White House using LIDAR data This visualisation from Scott Reinhard is another great example of LIDAR data being passed through Blender to create a 3D effect using realistic lighting and shadows. There are no 3D building models being used here — the result is created by artificially extruding GeoTIFF elevation
Community features Landfall — hand-made, physical 3D nautical maps I stumbled across Landfall a few months ago and have been fascinated by their work ever since. Their speciality is physical 3D topographical reliefs that are painstakingly crafted by hand from nautical charts and Ordnance Survey maps. You can commission them to create a
Community features Elastic maps Do you know what would make maps better? If they jiggled and wobbled as you move them around! This is exactly what these elastic maps do, giving elevated areas more elasticity than the lower areas as you move the map around. The result is
Newsletter Spatial Awareness #8 Read issue 8 of the Spatial Awareness newsletter, rounding up the latest in the spatial community.
Community features RUS Training The Research and User Support for Sentinel Core Products (RUS Training) is a place to learn all about how to use Sentinel satellite data. It’s free and there are a selection of upcoming courses to choose from. Previous courses and webinars have been
Community features 50 Must-follow Twitter accounts for spatial data science Lists like this are usually hit or miss, but this one by CARTO is spot on with the people you should be following within the spatial community. They’ve provided a little description about each person which is a nice touch. 50 Must-Follow Twitter
Community features Echoes in space If you’d like to learn about remote sensing using radar then you should check out the Echoes in Space course. It’s online and you can join the course even after its started, so you can learn at your own pace. Echoes in
Community features Open Datasets — Scale And last but not least, Scale have collated a whole range of datasets around autonomous vehicles, from sensor data to maps and annotated videos. The data comes from various places and is well worth checking out if you’re interested in this space. Open
Community features Lyft autonomous driving dataset Following in the theme of autonomous vehicle data, Lyft recently released their own dataset captured from their fleet of vehicles. Containing raw camera and LIDAR sensor data, they also hope that the data can be used by others to improve the algorithms and other
Community features Argoverse The various datasets and maps released by Argoverse contain a wealth of information captured by their fleet of autonomous vehicles. Their aim is for the data to be used to help others to test, experiment and teach self-driving vehicles. HomeTwo public datasets supported by
Community features How to render a map of San Diego's smart city streetlights with HERE XYZ, Python and Tangram HERE have released a tutorial on processing and mapping the street light sensors from the City of San Diego. They use Python for processing the data, HERE XYZ for hosting and filtering the data, and Tangram for outputting it in a Web browser using
Community features Visualising animated radar data with vector tiles Normally when you hear of vector tiles you think of static data — buildings, roads, etc. One area which isn’t well documented with vector tiles is how to use them with temporal data, especially if it needs to be animated. This approach by Mapbox
Community features Mapping the land between the tides “Thanks to the Moon, the Sun, and gravity, the place where the land meets the sea is not a fixed line.” — a simple concept to understand, yet one which is often overlooked when reading a map. This article on the NASA Earth Observatory blog
