Roadside Point Clouds

If, like me, you see roadside pointclouds in your sleep and want nothing more to do with them ever again, just ignore this post (PhD's can do that to you!) - but if you are interested in feature extraction then have a look at this project. Seems to be a collaboration to develop a method and language for feature extraction with standardised datasets for testing. The examples of all the different assets alone could be useful.

https://beta.openlsef.org/topography-assets/

Kepler

Kepler on GitHub caught my eye a few weeks ago - it is an open source, client side geospatial analysis tool for large datasets. Plenty of sample data to try if you don't have any ready to go - the New York taxi dataset and animations are worth a go if nothing else.

RUS and Sentinel 1

RUS was one of the big eye-openers for me from the IEOS a few months back - this is the customised virtual machine (VM) allowing fast data download and processing in a powerful computing environment provided free of charge by Copernicus. They've a webinar coming up showing how Sentinel 1 data can be used for mapping land subsidence - I'd recommend it for anyone interested in what can be done with the RUS platform.