Infoterra has been in the geospatial business for over 25 years, since its founding in 1980 as the UK National Remote Sensing Centre. In that time, NRSC grew, formed international partnerships with space agencies, expanded into aerial data collection, and was eventually privatized and re-named “Infoterra” in the late 1990s.
As a major re-seller of remote sensing and aerial photography in the UK and Europe, Infoterra has had to manage larger and larger collections of data for customers. With the rise of the internet, Infoterra has moved more of its data catalogues online, and customers have gotten used to having direct access to information about data holdings.
In 2001, Infoterra implemented a new aerial imagery catalogue for the UK Ordnance Survey using PostgreSQL, in support of a large data acquisition program. By the end of the contract, the database was managing 1 million metadata records without any operational issues, and Infoterra felt confident to move to larger architectures based on PostgreSQL.
As individual data collection programs were run at Infoterra, each tended to have its own data management and order fulfillment process. After the success of the Ordnance Survey project, Infoterra decided to consolidate data management and order fulfilling into a single corporate system, the “GeoStore”.
The GeoStore uses PostgreSQL/PostGIS as the database backend, UMN Mapserver for map rendering duties, and a variety of bespoke applications for data loading, order fulfillment, and access. The data managed in GeoStore now include:
Ross Elliott is a Senior Software Engineer for Infoterra, and has helped design the GeoStore system and its predecessors over the last five years. “To justify any software we use, the main requirement is that it be cost effective”, says Elliott, “and for the most part that means we choose open source.”
“Without PostGIS, we would have to go back to Oracle”, says Elliott, “and this would incur huge costs for us. Most of our database servers have at least two CPUs, if not more, and most are attached to the web in some way. This could easily add another £1,000,000 to our costs in licensing, plus annual maintenance.”
The UK Ordnance Survey database is one of the largest unified spatial data sets in the world, and Infoterra has built special tools for handling the huge volume of features. For data loading, Infoterra developed an application to bulk-load the Ordnance Survey GML data into PostGIS in just 12 hours — an average load rate of almost 14,000 features per second.
In addition to the GeoStore, Infoterra builds and runs a number of small custom systems for other companies, most of which run on PostGIS. Oracle is used when the customer demands it, but Infoterra builds with PostGIS when given the option. “PostGIS has made our systems possible to design in a way that suits the way we want to work without worrying about license costs” says Elliott, “It is an easy choice to go with PostGIS.”
As a software engineer at the Howard Hughes Medical Institute, I work on a collaborative neuron reconstruction and analysis software called CATMAID 1 (screenshot: 3), which is used for neuroscience research. We use PostGIS to represent neurons in a 3D space.
They consist of 3D points that reference their parent nodes or are the root [=soma of neuron] if they have no parent). Together with synapses, point clouds and TIN meshes for modeling compartments in a dataset, they model the spatial aspects of our neuroscience world. Users create those neuron reconstructions manually in a collaborative fashion plus segmentation programs can be used as additional data source. Using its spatial indices, PostGIS helps us to quickly query neurons in a particular field of view. The space of a single project contains sometimes 100s of millions of interconnected individual points. We also do bounding box intersection queries between neurons and compartment meshes, which then refine in the front-end by doing more precise intersection tests.
This software is used by quite a few research labs and as far as I know they all do their own hosting with a dedicated server and this is what we do as well. The reason being mainly that wth larger datasets, we benefit from machines with a lot of RAM (>256G), fast SSD/NVMe drives and many CPUs as well as fast local data access for e.g. image data.
Thanks so much for making PostGIS work well in non-GIS contexts too—-it makes my life much easier!
Vanguard Appraisals is new to the GIS world. In fact, we aren’t really in the GIS world; we just kind of brush up against it. We do mass property appraisal for entire county and city jurisdictions, and we develop software to collect, price and maintain values. We also host assessment data online so that homeowners can search and find property information much simpler from the comfort of their own home. Our software and websites are used in 7 states (IA, IL, MN, MO, NE, ND, SD).
Nautilytics is a small data visualization and GIS startup based out of Boston, MA. We use PostGIS and PostgreSQL, among other open-source tools to build powerful web applications for US government organizations, public, and private sector companies.