Partner Profiles: Geospatial Enabling Technologies (GET)

Boundless partners are an important part of spreading the depth and breadth of our software around the world. In this ongoing series, we will be featuring some of our partners and the ways they are expanding the reach of our Spatial IT solutions.

GETGeospatial Enabling Technologies (GET) was established in 2006 with the vision of becoming one of the leaders for Spatial IT solutions and services in Greece as well as more broadly in Europe and Africa. Specializing in the field of geoinformatics, GET provides robust solutions for both the public and private sector.

Since 2010, GET has deployed and supported OpenGeo Suite as part of their projects. From the very beginning, GET held a strong belief that Boundless was the premier provider for commercial open source spatial software. Through its partnership with Boundless and the use of OpenGeo Suite, GET has been able to implement projects for private companies as well as public authorities and government agencies in Greece including the Hellenic Regulatory Authority of Energy and the Greek Ministry of Agriculture. GET has also offered technical support, via the GET SDI Portal, to many public agencies like the Environmental Protection Agency of Athens and the Military Geographic Institute of Ecuador.

Hellenic Regulatory Authority for Energy (RAE)

“With the goal to provide advanced geospatial solutions based on open source, we consider Boundless an essential, valuable partner with whom we could design and implement projects effectively,” said Gabriel Mavrellis of GET.

This successful partnership derives from a relationship where each organization greatly benefits by sharing knowledge, expertise, opportunities, and vision. The developers and project managers at GET deploy projects based on OpenGeo Suite and share their knowledge and expertise with Boundless through the implementation and maintenance of solutions in Greece and abroad.

GET has successfully organized training seminars on OpenGeo Suite to provide Greek engineers and developers with a greater familiarity of the platform and its functions. GET is also a proud contributor to QGIS, providing training and translating a large part of the QGIS user interface into Greek.

If you’d like your company to be considered for our international network of partners, please contact us!

QGIS Compared: Visualization

Gretchen PetersonAny GIS professional who’s been paying attention to the professional chatter in recent years will be wondering about QGIS and whether or not it might meet some or all of their needs. QGIS is open source, similar to proprietary GIS software, runs on a variety of operating systems, and has been steadily improving since its debut in 2002. With easy-to-install packages, OpenGeo Suite integration, and reliable support offerings, we obviously see QGIS as a viable alternative to proprietary desktop GIS software such as Esri’s ArcGIS for Desktop.

But will it work for you? The short answer is: most likely yes for visualization of most formats of spatial data, probably for analysis of raster and vector data, probably for geographic data editing, and probably for cartography. Those are all very subjective assertions based on my personal experience using QGIS for the past seven months but I have been using proprietary GIS for over fourteen years as an analyst and cartographer and have written a couple of books on the subject.

By all means give QGIS a try: download and install it, drag-and-drop some data into it, and give it a spin. This is definitely a good time to evaluate it and consider adopting it across your organization.

Visualizing spatial data in QGIS

In this first post, I’m going to focus on visualizing spatial data in QGIS. These basic functions are straightforward and easy to do in QGIS:

  1. adding datasets

  2. moving datasets up and down in the layer hierarchy

  3. zooming around the map

  4. selecting features based on simple point-and-click

  5. selecting features based on complex selection criteria

  6. viewing attributes

  7. creating graduated color schemes


Strength: Versatile and efficient format support

In fact, QGIS is an effective means of viewing and exploring spatial data of almost any type. If you have complex data, you might be interested to hear that the newest release of QGIS boasts very fast, multi-threaded, rendering of spatial data that may even make it faster than leading competitors. When I began creating the map shown above, I accidentally added all of the Natural Earth 1:10m Cultural Vectors in triplicate to the project, causing some minor heart-palpitations as I realized it was going to try to render close to 100 vector layers all at once. However, my fears were unfounded as it took only a few seconds for them to render once they were all added. In the realm of visualization, it does most of the other tasks that a GIS professional would expect as well, including support for custom symbol sets (in SVG format). Adding GeoJSON data is simple, just drag a geojson file onto the Layers list. Here, we show a portion of James Fee’s GeoJSON repository of baseball stadiums:


Mixed results: Raster visualization

That said, raster visualization can yield unexpected results depending on what is desired. Some raster datasets have tables that associate bands with RGB values such that specific cell-types are rendered certain colors. Often, landcover datasets will have this kind of structure so that, for example, the raster is rendered with blue for water, green for grass, white for ice, and so on. Unfortunately, QGIS doesn’t yet support rendering based on associated table files for rasters. Another slight irritation is the continuing use of binary ARC/INFO GRID formats by some agencies who distribute raster data to the public. If you have one of these datasets, QGIS can open it but you must point to the w001001.adf file using the raster data import button.

Mixed results: On-the-fly reprojection

One of the most important ways to make GIS user-friendly is to support on-the-fly projection. I still remember when projecting on-the-fly became a part of the software that I used to use. It was the end of 1999, and life was so much easier when multiple datasets from multiple agencies in multiple projections could all be jammed together into a single project, producing a map where all the data layers were in the correct projected space. This was because reprojecting not only added extra steps requiring you to reproject everything into a common coordinate system even if all you wanted to do was visualize the data, it also meant maintaining multiple copies of the same dataset, which contributed to folder clutter and using up of valuable disk space. QGIS supports reprojection on-the-fly but it is an option that must be set in the project properties dialog. Some glitches with projections still seem to occur from time to time. Zooming in, for example, sometimes causes the map to zoom to a different place than expected. However, this unexpected behavior is inconsistent, not a showstopper, and may be fixed soon.


Hidden gem: Context

The other important aspect of visualizing data is having enough underlying context for the data. Country boundaries, city labels, roads, oceans, and other standard map data are crucial. Proprietary GIS software generally contains basemap layers that can easily be turned on and off to support visualization in this manner. QGIS also has this capability, in the form of the OpenLayers plugin, which serves up Google, OpenStreetMap, Bing, and Yahoo basemaps at the click of a button. The OpenLayers plugin is free and installs just like any other QGIS plugin—you search for it in the Plugins menu, press “install,” and make your basemap choice in the Web menu.



While QGIS may need a small amount of improvement when it comes to raster visualization and on-the-fly projection, these aren’t hindrances to a typical visualization workflow and are only mentioned here out of respect for a fair and balanced assessment. By and large, my testing has convinced me that the robust visualization capabilities that QGIS offers provide more than enough impetus for many organizations to make the switch to QGIS. In later posts, I’ll discuss how QGIS performs with respect to analysisediting, and cartography.

Partner Profiles: Agrisoft

Boundless partners are an important part of spreading the depth and breadth of our software around the world. In this ongoing series, we will be featuring some of our partners and the ways they are expanding the reach of our Spatial IT solutions.

AgrisoftEstablished in 2002, Agrisoft is an Indonesian consulting firm specializing in integrated spatial solutions using open source software. Agrisoft offers consultancy, integration and training services, product development, and knowledge of clients’ business processes.

With a population of 250 million people and a booming business community, Indonesia has proved itself to be a growing market for Agrisoft and Boundless. While the market for spatial solutions is still young, Agrisoft encourages the use of spatial software for business by promoting its value and establishing it as a viable solution. OpenGeo Suite provides a complete set of tools for Agrisoft’s clients to build spatially-enabled applications and GeoServer, OpenLayers, and PostGIS have become the preferred solutions among Agrisoft’s clients.

SIH3: Sistem Informasi Hidrologi Hidrometeorologi & Hidrogeologi

Tools and expertise from Boundless have enabled Agrisoft to expand and improve on some of their largest projects and they count among their customers the Indonesian Geospatial Information Agency and the Republic of Indonesia Ministry of Agriculture. In a current project for the Republic of Indonesia Agency for Meteorology, Climatology and Geophysics, Agrisoft is working on the SIH3 Portal, an information system for hydrology, hydrometeorology and hydrogeology. This project makes use of applications built on OpenGeo Suite to browse and explore maps showing different information and Agrisoft is redesigning the graphical user interface using OpenLayers 3.

Agrisoft continually encourages the use of open source spatial software and looks to Boundless for industry best practices and guidance for their current and prospective customers.

If you’d like your company to be considered for our international network of partners, please contact us!

Introducing Versio: Distributed Version Control for Spatial Data

Boundless is pleased to introduce Versio, our new data management and collaboration platform built specifically for spatial data. We’ve been working on Versio for over a year, extending the power of the GeoGig approach into an online platform that will transform the way organizations collaborate on, control, and share their spatial data.

Versio homepage

Versio is now available in private beta with select customers and community members. We expect to release the full platform in early 2015, but if you would like to get an early look and help us improve the product, please request an invitation at

The Problem

Spatial data is dynamic, and anyone who works with it knows that keeping it updated is a challenge. The larger the organization, the worse this problem gets. Increasing team sizes, field-based data collection, and integrated workflows that depend on the publishing of timely, updated datasets increases the complexity of managing spatial data. Too often this challenge is met by emailing shapefiles around, resulting in a file naming nightmare, and a labor-intensive process to merge data together. Alternatively, if you have the money, an expensive versioning database can be used, but even that suffers from potential centralized outages, file locks, and complex system administration.

The Solution

To solve this problem, we looked for a new model of collaboration – one that has revolutionized software development – distributed version control systems.  Boundless first introduced the distributed versioning concept to Spatial IT with GeoGig, an open source tool that draws inspiration from Git but adapts its core concepts specifically for spatial data. As GeoGig has matured, we built Versio to broaden the audience by including a high-performance server and easy-to-use web interface.

Versio’s distributed versioning model and repository data structure enables new approaches to collaboration and data management. On the collaboration side, data owners and GIS analysts determine specifically who they collaborate with, creating private data repositories and inviting others to join, or sharing a data repository for the
crowd to update. Changes to a dataset can be stored in a different “branch” of the repository, and data owners have explicit control over what changes are merged back into the core repository.

The repository data structure preserves the entire lineage of a dataset, allowing a user to track and visualize changes over time. Rather than relying on a central database, each individual’s working copy is a complete repository of the spatial data. Each “commit” to the repository is saved as a discrete version, yet also maintains its relationship to previous versions in the repository. This allows users to visualize the lineage of features across all versions, as well as the changes between different versions. Additionally, file sizes are minimized since only the changes between versions are stored (eliminating redundant data) and it is easy to rollback to a previous version of a dataset.

With Versio, we want to support as many editing workflows as possible, both online and offline. So we’ve made the platform client-agnostic to support traditional desktop GIS software as well as web, mobile, or custom applications built on the Versio API.

Request an invitation to the Versio private beta at!

GeoGig Grows Up, Contributed to LocationTech


We’re proud to announce that GeoGig is approaching its first major release and we’re contributing the project to the LocationTech working group at the Eclipse Foundation.

For those not familiar with the project, GeoGig is an open source tool that draws inspiration from Git (hence why it was previously called GeoGit) but adapts its core concepts to handle distributed versioning of spatial data. With GeoGig, users are able to import spatial data into a repository where every change to the data is tracked. These changes can be viewed in a history, reverted to older versions, branched in to sandboxed areas, merged back in, and pushed to remote repositories.

Learn more about GeoGig and how to use it with these posts and videos:

As one of the founding members of the LocationTech initiative,  we’ve given several talks at LocationTech events and look forward to continuing to participate in the LocationTech Tour. Join us at the events in New York on December 9th and Washington DC on December 11th.

PostGIS Training: Creating Overlays

PostGIS training At Boundless, we recognize that software is only as good as the problems it can be used to solve. That’s why we don’t just develop the best open source spatial software, we also teach you how to use it with supporttraining, and workshops directly from the experts.

One question that comes up often during our PostGIS training is “how do I do an overlay?” The terminology can vary: sometimes they call the operation a “union” sometimes an “intersect”. What they mean is, “can you turn a collection of overlapping polygons into a collection of non-overlapping polygons that retain information about the overlapping polygons that formed them?”


So an overlapping set of three circles becomes a non-overlapping set of 7 polygons. screenshot_69

Calculating the overlapping parts of a pair of shapes is easy, using the ST_Intersection() function in PostGIS, but that only works for pairs, and doesn’t capture the areas that have no overlaps at all. How can we handle multiple overlaps and get out a polygon set that covers 100% of the area of the input sets? By taking the polygon geometry apart into lines, and then building new polygons back up. Let’s construct a synthetic example: first, generate a collection of random points, using a Gaussian distribution, so there’s more overlap in the middle. The crazy math in the SQL below just converts the uniform random numbers from the random() function into normally distributed numbers.

WITH rands AS (
  SELECT generate_series as id, random() AS u1, random() AS u2 FROM generate_series(1,100)
    50 * sqrt(-2 * ln(u1)) * cos(2*pi()*u2),
    50 * sqrt(-2 * ln(u1)) * sin(2*pi()*u2)),4326) AS geom
FROM rands;

The result looks like this: screenshot_70 Now, we turn the points into circles, big enough to have overlaps.

SELECT id, ST_Buffer(geom, 10) AS geom FROM pts;

Which looks like this: screenshot_71 Now it’s time to take the polygons apart. In this case we’ll take the exterior ring of the circles, using ST_ExteriorRing(). If we were dealing with complex polygons with holes, we’d have to use ST_DumpRings(). Once we have the rings, we want to make sure that everywhere rings cross the lines are broken, so that no lines cross, they only touch at their end points. We do that with the ST_Union() function.

CREATE TABLE boundaries AS
SELECT ST_Union(ST_ExteriorRing(geom)) AS geom
FROM circles;

What comes out is just lines, but with end points at every crossing. screenshot_72 Now that we have noded lines, we can collect them into a multi-linestring and feed them to ST_Polygonize() to generate polygons. The polygons come out as one big multi-polygon, so we’ll use ST_Dump() to convert it into a table with one row per polygon.

SELECT nextval('polyseq') AS id, (ST_Dump(ST_Polygonize(geom))).geom AS geom
FROM boundaries;

Now we have a set of polygons with no overlaps, only one polygon per area. screenshot_73 So, how do we figure out how many overlaps contributed to each incoming polygon? We can join the centroids of the new small polygons with the set of original circles, and calculate how many circles contain each centroid point. screenshot_74 A spatial join will allow us to calculate the number of overlaps.

UPDATE POLYS set count = p.count
  SELECT count(*) AS count, AS id  
  FROM polys p 
  JOIN circles c 
  ON ST_Contains(c.geom, ST_PointOnSurface(p.geom)) 
) AS p

That’s it! Now we have a single coverage of the area, where each polygon knows how much overlap contributed to it. Ironically, when visualized using the coverage count as a variable in the color ramp, it looks a lot like the original image, which was created with a simple transparency effect. However, the point here is that we’ve created new data, in the count attribute of the new polygon layer. screenshot_75 The same decompose-and-rebuild-and-join-centroids trick can be used to overlay all kinds of features, and to carry over attributes from the original input data, achieving the classic “GIS overlay” workflow. Happy geometry mashing!

Want to learn more? Try our Introduction to PostGIS online training course!

Juan’s Thoughts from NSGIC

Last week, a few of us here at Boundless attended the National States Geographic Information Council (NSGIC) Annual Conference in beautiful Charleston, SC. NSGIC’s mission is to promote statewide spatial coordination activities in all states and to be an effective advocate for states on national policy and initiatives. It’s an important mission and we were proud to be Gold Sponsors this year.

NSGIC 2014 Annual Conference

What I Presented

I had the privilege to deliver a well-received keynote presentation on Monday evening entitled “Open Source Geospatial Software: Current adoptions and future technologies solving today’s and tomorrow’s challenges”. While that sounds long and complicated, I basically went over the opportunities unlocked by adopting open source spatial technology and how organizations at the local, state or federal level can take advantage of them. The spatial software industry is one of the few where the open source tsunami hasn’t yet fully revolutionized the way we work. However, it is happening and I’m glad to finally see increasing diversity in our ecosystem of available tools. As with most ecosystems, this will bring about a healthier long-term outcome.

What I Learned

Instead of talking about what I said, I would like to share a bit of what I heard. NSGIC puts on a great program and one of the best things about this conference is seeing first-hand the challenges that states face. They are usually strikingly similar across states, both in concept and timing, which is a testament to the level of coordination that happens among states, local governments and, in many instances, the Federal Government (which was represented by agencies such as NOAA and USDOT).

“No single source of truth.”

Throughout all the high-quality presentations, I was very interested to see how most states have what I call the “data roll-up problem,” where different jurisdictions (i.e. counties) often produce and maintain the data but states collect it as part of the “authoritative” source of information. The biggest challenges to producing statewide data that is complete and comprehensive are usually non-technical, and we heard great stories about how states are breaking down barriers when it comes to accessing data.  Guess what? Charging for data usually ends up being more expensive than implementing an open data policy! When it comes to the technical details, I believe Boundless will have a lot to say in the next year with the work we have been doing on distributed versioning of spatial data to help address some of these challenges.

“Don’t fight the web.”

I was also pleasantly surprised to see how most states have a very modern approach to their services. They realize the importance of the web, and have an IT approach for delivering content and services to their users (which thanks to some very advanced open data policies, in many cases includes just about everybody). We even got to hear novel approaches to geocoding, like using Natural Language Processing (NLP) to extract places from documents so they can be placed on a map (with open source libraries, of course). Imagine having a map of all your legislation!

See you in Annapolis!

At a time when budgets are tight, it’s refreshing to witness local, state and federal agencies resort to innovative and imaginative approaches to solving problems. At Boundless, we are big proponents of efficiency through the use of open source spatial software and we are happy to bring our point of view into the conversation while realizing that every organization is at a different stage in adopting open source models and software. We hope to further this discussion at the NSGIC mid-year conference in Annapolis in February of 2015.

Ann’s Perspective on FOSS4G 2014

FOSS4G 2014

As Paul Ramsey mentioned, last week almost 900 members of the open source geospatial software community came together in Portland at FOSS4G 2014. We were proud to sponsor, privileged to participate in over nine presentations and nine workshops, excited about our new QGIS offerings, and pleased to see even greater interest in our PostGIS,  GeoServer, and OpenLayers offerings during the conference.

The power of Spatial IT resonated throughout the conference as participants were able to highlight their projects and unique use cases of open source geospatial tools to solve a wide variety of technical and business problems.

Highlights from our sessions

Paul conducted a very useful session on how to convince managers to embrace PostGIS and replace proprietary database offerings. The blend of technical and business elements in Paul’s talk spoke about the need to not only use the best available software, but also the continuing need to educate organizations about the value derived from using open source software.

Jody Garnett helped review the new and noteworthy features in GeoServer introduced over the past year. Since GeoServer is part of the core of OpenGeo Suite, it’s always promising to see new support for new standards like WCS 2.0 and new formats like GeoPackage and NetCDF become part of the software.

Andreas Hocevar helped describe what’s new and how to get started with OpenLayers 3. His talk provided an overview from a user’s perspective and covered common use cases and new features to help developers get comfortable with integrating spatial information into web applications.

The LocationTech events highlighted the ability of the community to truly embrace cooperation in the interest of advancing common projects and common goals.

FOSS4G is about community

A true sense of community, however, was the best part of the conference. There was a great feeling of camaraderie throughout the weeklong event. All of the presenters and booth participants, regardless of affiliation, were joined together by the common cause of promoting the value of and expanding the use of open source tools to reduce the cost of legacy GIS implementations and escape the monolithic, proprietary software options that dominate the industry.

Nothing drove the open source message home further for me than the train ride I took from the magnificent World Forestry Center back to my hotel after the gala on Thursday evening. Seated on the train, my badge now tucked in my purse, I was relaxing on the quiet train and became captivated by a conversation amongst three gentlemen seated just a few rows away. The three were discussing their week at FOSS4G, which seemed a very positive experience for all. And then, one of the men observed, “Open source is really becoming a standard in GIS. Even Esri was in attendance at FOSS4G.”

Well, I suppose that is just the point for the community — if you can’t beat ‘em, join ‘em! Whether Esri is genuine in their open source support or not remains to be seen but what is evident is they can no longer afford to ignore open source. Open source is a part of the geospatial software ecosystem and will continue to grow and provide more affordable opportunities for people to expand the technology into critical business and IT applications throughout their organizations.

I’m already planning for FOSS4G 2015 in Seoul!

Paul’s Perspective on FOSS4G 2014

FOSS4G 2014

The world of open source geospatial gathered itself together again last week, as Boundless joined almost 900 developers, users and managers at FOSS4G 2014 in Portland, Oregon. This is the ninth such gathering I’ve attended, and they all have a special local flavour: in this case the flavour of locally-sourced ingredients and micro-brewed beer.

Exciting Technology

Each year also has it’s own favored technology, the topic that packs rooms and spills attendees into the halls: in the early days, MapServer and then PostGIS; Java technology like GeoServer and GeoTools; the first open source slippy maps like OpenLayers; new server technologies like Node.js. This year the topics that I observed drawing in the big crowds were vector tiles and drones.

Vector tiles are close to home, a technology I understand and have experimented with, and if PostGIS, GeoServer and OpenLayers are not producing and consuming vector tiles within a year I will be surprised. There’s lots of demand for the technology, a solid use case in mobile clients, and a clear implementation path forwards.

Drones, on the other hand, represent a whole new opportunity for open source since, like open source software, cheap drones and sensors democratize information about location. Cheap tools and open software are a great match. Aaron Racicot shared his experience building a quadrocopter for image acquisition for under $700, and Stephen Mather described how he processes drone photos from imagery into a 3D point cloud and textured terrain mesh using open source tools. From here it’s not hard to imagine a future where a digital model of a city could be automatically and continuously updated from the cameras of hundreds of personal drones swooping around.

New Ideas

In talks there were some great examples of Spatial IT: building tools that integrate spatial thinking with existing IT architectures and data flows. For example, the improved MapFish Printing module, which may find its way into OpenGeo Suite over the next year, is centered around producing reports (which might contain maps) rather than producing maps (that may have some reporting).

Similarly, practical and incremental transformation stories from proprietary to open source were common. Sara Safavi presented basic case studies and patterns for integrating open source into proprietary shops: web first, database first, or desktop first, but never all at once. Karl-Magnus Jonsson shared the story of his city’s move from 100% proprietary to 100% open source over several years of gradual transformation: first the web, then the database, and finally then the desktop.

Growing Community

On the show floor was the usual collection of companies like ourselves supporting particular open source projects for enterprises, but a few companies in different but important categories: Amazon and OpenShift, promoting the deployment of open source geospatial systems on their platforms; and PlanetLabs, talking about their new sources of earth imaging. As the open source economy grows, the number of companies that generate value indirectly from and for open source is growing along with it.

Next year FOSS4G will be in Seoul, South Korea, which will give international attendees a great opportunity to learn what is happening in Asia in general and the Korean technosphere in particular. I’m anticipating seeing some truly outstanding work that would otherwise be very hard to discover, it’s going to be a must-attend event.

Thanks to the organizers in Portland for a seamless and enjoyable event! And thanks for putting a bird on it!

The Spatial IT Job Board

CareersThose of you who’ve seen Paul Ramsey’s Spatial IT and the Spatial Web presentation or read Michael Terner’s blog piece know that we see a great future for software developers and IT professionals with an interest in spatial technology. Below are several job openings we’ve seen in the past month.

Job Listings

There are plenty of opportunities for Spatial IT professionals but if we missed any relevant positions please contact us and we’ll be sure to include them in future job board posts.