The cool thing about foreign data wrappers is that they're an alternative to needing to have everything in the same data store. With spatial data being stored and shared in so many different formats, imagine being able to abstract that conversion away and just focus on analysis. Read on for a couple of quick demos.
Raster data access from the spatial database is an important feature, and the coming release of PostGIS will make remote access more practical, by allowing access to private cloud storage.
One theme of the 3.2 release is new analytical functionality in the raster module, and access to cloud-based rasters via the "out-db" option for rasters. Let's explore two new functions and exercise cloud raster support at the same time.
A common situation in the spatial data world is having discrete measurements of a continuous variable. Every place in the world has a temperature, but there are only a finite number of thermometers - how should we reason about places without thermometers and how should we model temperature?
As a GIS newbie, I've been trying to use local open data for my own learning projects. I've recently relocated to Tampa, Florida, and was browsing through the City of Tampa open data portal and saw that they have a Public Art map. That sounded like a cool dataset to work with but I couldn't find the data source anywhere in the portal. I reached out to the nice folks on the city's GIS team and they gave me an ArcGIS-hosted URL.
There are a lot of ways to load data into a PostgreSQL/PostGIS database and it's no different with spatial data. If you're new to PostGIS, you've come to the right place. In this blog post, I'll outline a few free, open source tools you can use for your spatial data import needs.
The PostGIS raster has a steep learning curve, but it opens up some unique possibilities for data analysis and accessing non-standard data from within PostgreSQL. Here's an example that shows how to access raster data from PostGIS running on Crunchy Bridge.