Fooling around with QGIS (v 2.18) global program-settings, I found some interesting setting. It allows the user to copy geo-features directly from the table to the clipboard as GeoJSON (geom + attributes). So, no „export to…“ etc. is needed.
Nachdem ArcGIS Pro von ESRI erwachsen wird und sukzessive vermehrt im GIS-Alltag zum Einsatz kommt, anbei ergänzend zur Serie zur Anwendung bestmöglicher Transformationsparameter zwischen dem österreichischen Bundesmeldenetz und WGS84/ETRS89 die Implementierung dieser in ArcGIS Pro (Stand Version 1.3.1).
As a QGIS-User on Fedora-Linux I was at first happy having QGIS 2.14.x (LTR) in the Fedora 24 repository. After installing it with DNF the problems started… QGIS had some missing dependencies:
- pyspatialite error
- PyQt4-webkit error
Many different organisations have to deal with the management of guideposts – especially in alpine regions. Sometimes all the data about the guideposts is managed in databases and GIS-Systems.
This week Facebook started to block the usage of Facebook messages/chats on mobile devices just with the browser – Facebook forces their „products“ (=customers) to use their messenger-App (with all the device-rights this app wants…).
A little detour allows to further use FB messages/chat with your mobile browser 🙂
Shapefile Top30 airports 2015 with passenger numbers 2013-2015 as an attribute – Downloads
After importing geodata from the GIS to MongoDB and creating a spatial index (part 1), the exciting (spatial) adventure starts. With „normal“ (relational) databases and their spatial extensions (Oracle spatial, PostgreSQL/PostGIS, SQLite/Spatialite,…) a lot of spatial queries and geoprocessing are possible. So let’s try to find out which adresses have to be evacuated 250m around some „event“…
MongoDB (3.2) is a kind of database-hipster at the moment – with improving support for spatial data. So it was time for me to discover some of it’s features concerning spatial data. As a GIS-user my first intention was to get some bigger simple (point) geodata into MongoDB. Part 1 covers this topic, part 2 will cover some spatial operations within MongoDB. I also want to do some performance checks between PostgreSQL/PostGIS and MongoDB related to geodata.