Tag: spatial

Feed: R-bloggers. Author: Edzer Pebesma, Roger Bivand. [This article was first published on r-spatial, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. [view raw Rmd] Summary: Packages rgdal, rgeos and maptools will retire by the end of 2023 . We describe where their functionality will go, what package maintainers can or should do, and which steps we will take to minimize the impact on dependent packages and on reproducibility in general. The R ... Read More

Feed: Planet PostgreSQL. pg_featureserv provides access to the powerful spatial database capabilities of PostGIS and PostgreSQL via a lightweight web service. To do this, it implements the OGC API for Features (OAPIF) RESTful protocol. OAPIF is part of the Open Geospatial Consortium (OGC) OGC API suite of standards ... Read More

Feed: Planet PostgreSQL. Every once in a while, a post shows up online about someone using GPUs for common spatial analysis tasks, and I get a burst of techno-enthusiasm. Maybe this is truly the new way! ... Read More

Feed: AWS Partner Network (APN) Blog. Author: Javier de la Torre. By Javier de la Torre, Founder and Chief Strategy Officer – CARTO CARTO Everything happens somewhere, and therefore everything can be analyzed from a location perspective. GPS data, addresses, parcels, administrative boundaries, routes—all of these are spatial data and this data type is growing fast. Spatial data is a vital ingredient in today’s applications, enabling capabilities ranging from asset tracking and location-based marketing to monitoring deforestation and more. Analyzing spatial data has traditionally been done on transactional databases like PostgreSQL with PostGIS. Modern data warehouses are now enabling levels ... Read More

Feed: Planet PostgreSQL. One of the curious aspects of spatial indexes is that the nodes of the tree can overlap, because the objects being indexed themselves also overlap ... Read More

Feed: Recent Announcements. Amazon Redshift support for GEOGRAPHY data type is now available for spatial analytics. GEOGRAPHY data type is used in queries requiring higher precision results for spatial data with geographic features that can be represented with a spheroid model of the Earth and referenced using latitude and longitude as spatial coordinate system. With this announcement, Amazon Redshift can now support two major spatial data types - GEOMETRY and GEOGRAPHY to perform the vast majority of spatial analytics, opening-up support for many more third-party spatial and GIS applications. In addition to the GEOGRAPHY data type, Amazon Redshift also released ... Read More

Feed: Neo4j Graph Database Platform. Author: Clair Sullivan. Happy September! We have a lot in store this week for Twin4j. First, we would like to remind you of the upcoming, live re-runs of the NODES 2021 workshops, scheduled for the week of September 13, 2021. All workshops are at a time that should be friendly to attendees of multiple time zones, and recordings will also be available if you cannot attend live. We also have a variety of fun content this week, including knowledge graphs, using the Neo4j spatial capabilities to map out locations along ... Read More

Feed: Planet PostgreSQL. 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 that you can use in Postgres, so for today's post we'll look at another that works especially well with spatial data formats: ogr_fdw.I had also previously talked about some different ways to get spatial data into a Postgres/PostGIS database, but the cool thing about foreign data wrappers is that they're an alternative to needing to have ... Read More

Feed: Recent Announcements. Starting today, Amazon Redshift introduces spatial query performance enhancements, 3D/4D geometries, and new spatial functions in Amazon Redshift to improve processing of spatial data. With the today's performance enhancements you can significantly enhance geometry query throughput by up to 100x in some cases transparently and automatically. The performance enhancements also optimize and accelerate spatial queries with large table JOINs. Support for 3D/4D geometries in spatial queries greatly expands the range of spatial use cases where 3D/4D spatial coordinates is required to accurately represent the multi-dimensional data. In addition to the above new spatial features, there are more ... Read More

Feed: SAS Blogs. Author: Guohui Wu. In a previous post, I discussed spatial econometric modeling and how spatial regression models can be used to account for various types of spatial dependence in the data. In many data analyses, we often face the issue of not knowing the true model from which our data is generated. To resolve this model uncertainty issue, general practice is to perform model selection. This is done by fitting a set of candidate models and comparing their fit statistics using some criteria such as Akaike information criterion (AIC) and Schwarz information criterion (SBC). Among those candidate ... Read More