At the GITA Pipeline Forum in Houston, an enthralling presentation by Rich Henry of Pivvot, a recent startup that builds solutions for pipeline routing and other applications, highlighted how open source geospatial technology is transforming applications in a variety of sectors. Pivvot builds SaaS solutions using open-source components on Google Maps and Amazon Web Services to provide a web-based cloud computing platform with a curated database from over 900 public and private sources. The advantages of this approach for siting pipeline routes are dramatic; applying infinite computing resources, completely avoiding the arcane art of managing ESRI ArcGIS licences, and integrating hundreds of data layers making it possible to run alternative pipeline right of way scenarios in hours rather than weeks or months.
Recent technical advances have made it possible to implement cost-effective solutions for utility, telecom and pipeline asset management, integrating BIM and geospatial, and geospatially-enabled machine learning. Standards are a key underpinning in the development of geospatial applications for a number of vertical industries. There are now many widely adopted geospatial standards; WMS, WFS, GML, KML, InfraGML, PipelineML, WaterML to name just a few from the Open Geospatial Consortium (OGC) that were not available two decades ago. Furthermore, open source geospatial developers like open standards. Many open source libraries and applications implement standards from the Open Geospatial Consortium (OGC), W3C and GeoJSON. Since 1999 there has been rapid development of open source geospatial projects including MapServer, GDAL, PostGIS, GeoServer, OpenLayers, Leaflet, QGIS and others. The Open Source Geospatial Foundation (OSGEO) was founded in in 2006 and the open source code-base has enabled entrepreneurs to rapidly develop low cost geospatial applications because the cost of maintaining most of the code is shared across a broad developer community. I'll describe a few of the solutions built on open source components that I have encountered in the last few years.
Records management for utilities
One of the challenges faced by large utilities with multiple GIS, outage management, customer information and other systems, which are often the result of mergers, is how to make spatial and associated data, in different, often incompatible systems, accessible to all users not just GIS professionals. At Distributech 2018 I discovered how Duke Energy is running an off-the-shelf web-based product based on open source components that is being used by 8000 users, 2000 of them using it 24/7 every day, to access GIS and associated data in several GIS systems, both online and offline, using laptops, tablets and phones. A single, common easy-to-use web tool permits viewing geospatial asset data stored in GE Smallworld, ESRI ArcGIS, Intergraph GTechnology, spatialNET and Google Maps as well as non-GIS data in Maximo, SAP, three different outage management systems, four or five customer information systems, CAD drawings and photos and images.
At Distributech 2019 a new entrant IQGeo emerged into the utility and communications space and announced an alternative to traditional GIS. myWorld Capture is a mobile solution that prioritizes direct data maintenance from the field. Building on an open source geospatial platform that supports data versioning and interfaces to legacy utility/communications GISs such as ArcGIS and Smallworld, myWorld provides tools that make it possible to develop and maintain a high quality near real-time GIS with the information that is required for a complete network asset data model including equipment location, descriptions, connectivity, condition, and status.
Open access to municipal geospatial data
At GITA 2018 in Phoenix, Bob Basques, GIS Systems Developer at the City of St Paul, described a system called COMPASS he and his team have developed an easy to use tool that allows city employees and the public access to all of the City's spatial and associated data including, for example, scans of surveyors' notebooks, 2.2 million street level photos, and permitting and licensing information from 200 different applications. Based completely on open source components the system is compact and efficient enough to run on a Raspberry Pi.
Integrating BIM and 3D geospatial
At the GEO|Design+BIM conference I discovered mago3D a 3D web-based geo-platform developed by Gaia3D. It is open source and integrates many well-known open source geospatial products and APis. It has an engine for handling massive, complex BIM objects that supports LOD (level of detail) control and efficient spatial queries and culling (the removal of objects that are not visible to the observer which is key to efficient visualization or large, complex structures.) It integrates with two of the best known open source 3D virtual globe tools, Cesium and NASA WorldWind, for visualization in a geospatial context. Viewing BIM structures in mago3D has some similarities with a Google Earth experience. The source code is available under open source licenses.
Machine learning
Deep learning algorithms have been developed by academia and as a result the code for the most part is open source. For example, a deep neural network model developed originally for medical image segmentation called U-Net is open source and has been applied to identifying building footprints. Successful training of deep networks requires thousands of labeled training samples. Labeled data involves people on the ground manually ground-truthing land use types and other features so that the deep learning algorithms can learn what to recognize. Machine learning is computationally intensive and requires a distributed engine. Spark is a open source (Apache) project which enables distributed processing for global scale computation. Machine learning has been used successfully to identify building footprints and transportation networks and deforestation in satellite imagery.
RasterFrames is a free and open source toolkit allowing scientists, data scientists, and software developers to process and analyze geospatial-temporal raster data with the same flexibility and ease as any other data type. Open source training data is beginning to become available, for example, the System for Terrrestrial Ecosystem Parameterization (STEP) has 2000 manually labeled sites covering 17 different land cover types including five forest types scattered across all continents.
Pipeline siting
To identify an optimal route for a pipeline on your own local hardware involves stitching together many DEMs, calculating slopes, finding, downloading and integrating hundreds of data layers, and avoiding certain areas (protected or uncooperative owners). You have to worry about having enough disk space and the calculations can take a long time with no certainty of completion. Running these calculations on several machines in parallel requires an ArcGIS licence for each of the machines. Together this could result in months of data collection and processing. In contrast even for long pipelines an open source solution from Pivvot running in the cloud means you don't have to worry about file management and disk capacity or getting enough machines and licenses to run it in parallel. Using Pivvot's curated datasets data collection and processing can be done in a few hours and it is scalable to many data layers.
Migrating to an open source platform is easier than you think
Samuel Song is responsible for the National Cemetery GIS implementation within Veterans Affairs and like many in government increased use of GIS means a greater sensitivity to cost. Samuel outlined his experience in migrating to open source at a GIS in the Rockies conference in Denver.
He had been using ArcGIS Desktop as his desktop GIS, SQL Server as a database, ArcGIS Enterprise as a web server, and ArcGIS API for Javascript for his web GIS. To look at ways to lower his costs Samuel experimented with open source geospatial software; QGIS for his desktop GIS, PostgreSQL/PostGIS for his database, GeoServer for his web server, and Leaflet or OpenLayers for his web GIS (all part of the OSGEO open source geospatial stack). His most important findings are that QGIS is a very stable, powerful alternative to ArcMap, PostgreSQL/PostGIS is a stable alternative to SQL Server and perhaps most importantly migrating data to an open source spatial database from an ESRI Geodatabase was much easier than he expected. His overall conclusion was that with the currently available open source software stack it is possible to move to a fully open source platform from an existing ArcGIS implementation and that the migration is much simpler than expected.
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