Introducing Crunchy Data Warehouse: A next-generation Postgres-native data warehouse. Crunchy Data Warehouse Learn more
Elizabeth Christensen
Elizabeth Christensen
Crunchy Data hosted the third annual PostGIS Day on November 18th.This was our second year with a virtual format and another year of record attendance! We had attendees from more than 99 countries.
Kat Batuigas
Kat Batuigas
In my last post, I did a simple intro to foreign data wrappers in PostgreSQL. postgres_fdw is an extension available in Postgres core that allows you to issue queries against another Postgres database. It's just one of many foreign data wrappers
Paul Ramsey
Paul Ramsey
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.
Previous versions could access rasters in public buckets, which is fine for writing blog posts
Paul Ramsey
Paul Ramsey
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.
Martin Davis
Martin Davis
My colleague Kat Batuigas recently wrote about using the powerful open-source QGIS desktop GIS to import data into PostGIS from an ArcGIS Feature Service. This is a great first step toward moving your geospatial stack onto the performant, open source platform provided by PostGIS. And there's no need to stop there! Crunchy Data
Paul Ramsey
Paul Ramsey
One of the less visible improvements coming in PostGIS 3.2 (via the GEOS 3.10 release) is a new algorithm for repairing invalid polygons and multipolygons.
Algorithms like polygon intersection, union and difference rely on guarantees that the structure of inputs follows certain rules. We call geometries that follow those rules "valid" and those that do not "invalid".
The rules are things like:
Paul Ramsey
Paul Ramsey
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?
For many use cases, the right way to model a continuous spatial variable is a raster: a regularly spaced grid where each square in the grid contains a value of the variable. This works for temperature and precipitation; it works for elevation and slope; it even works for travel times and wayfinding.
For this blog post, we will build up a temperature surface for Washington State, using the discrete temperature measurements of a set of Department of Transportation (WSDoT) weather stations.
Paul Ramsey
Paul Ramsey
Spatial indexes are used in PostGIS to quickly search for objects in space. Practically, this means very quickly answering questions of the form:
Because spatial objects are often quite large and complex (for example, coastlines commonly are defined with thousands of points), spatial indexes use "bounding boxes" as index and search keys:
Paul Ramsey
Paul Ramsey
We at Crunchy Data put as much development effort into improving GEOS as we do improving PostGIS proper, because the GEOS library is so central to much geospatial processing.
The GEOS library is a core piece of PostGIS. It is the library that provides all the "hard" computational geometry functionality:
Kat Batuigas
Kat Batuigas
As a GIS newbie, I've been trying to use local open data for my own learning projects. I 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