New Trajectools 2.1 and MovingPandas 0.18 releases
Today marks the 2.1 release of #Trajectools for #QGIS. This release adds multiple new algorithms and improvements. Since some improvements involve upstream #MovingPandas functionality, I recommend to also update MovingPandas while you're at it.
I’m continuously testing the algorithms integrated so far to see if they work as GIS users would expect and can to ensure that they can be integrated in Processing model seamlessly.
Also added some more #trajectory statistics to the default output: start and end time, duration, length, and average speed, ready for further analysis directly from the #QGISProcessing toolbox or in the #QGIS model designer
More work on #QGIS#Trajectools today: #MovingPandas TemporalSplitter and ObservationGapSplitter are integrated now. SpeedSplitter and StopSplitter are still on the todo list
I wonder if it's better to have all splitters in one processing algorithm or if I should implement four independent algorithms instead 🤔
And so the #QGIS#Trajectools quest continues: Merging tools that logically belong together and applying default styles to better show the computed speed and direction values
Also switched to the @movingpandas logo as a plugin icon
In the recent post "Setting up a graph db using GTFS data & Neo4J", we noted that -- unfortunately -- Neomap is not an option to visualize spatial nodes anymore.
Exploring a hierarchical #graph-based model for #mobilitydata representation and analysis
Today's post is a first quick dive into #Neo4J (really just getting my toes wet). It's based on a publicly available Neo4J dump containing #mobility data, ship trajectories to be specific.