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> FOSS GIS software is pretty good but suffers from the usual lack of budget.

FOSS GIS is incredible these days. You can do everything in open source - it just sometimes requires a bit of work. Between qGIS (+SAGA/Grass/etc.), postGIS, python tooling like GeoPandas, leaflet/cesium, etc. there's plenty of tools for different things outside the ESRI ecosystem, you just have to learn to use them. This is a long way from the dark ages 10+ years ago when much of this capability was closed source or via some ridiculously complex text interface of GRASS.

ESRI's market dominance on GIS analysis is still a big thing though but only really a hangover from the days when ArcGIS had much more capability and lock in coroporate training was a thing. Now qGIS has essentially most of the same capability, but ESRI's corporate training structures etc. are still there to some extent. It is losing its stranglehold though, especially amongst GIS 'dabblers' who don't want to sign up and lock in to a massive corporate account for whom the ESRI older-style value proposition isn't really there. qGIS is even an accepted option for local government these days in many places.

Geospatial is both complex and diverse though. There's a lot of industries there and while there's big easy simple 2d GIS markets in mining, government zoning and military, there's also a lot of other stuff going on and its all moving fast. 3d, temporal data, drone photography, lidar and satellite etc. There's lots of innovation happening there right now and new ESRI monoliths being built.

I can't think of another library that has had as much of an impact on a niche field as GDAL.

What does FOSS GIS software have to do in order to compete against ESRI? Or which packages have the best chance to?

For example, few consider going with Oracle anymore now that you have PostgreSQL but that took a long time. So, looking perhaps as far as 10 years, which FOSS GIS software might even have a shot to start displacing ESRI in the future?

From my perspective at least theres a few main sides. From least to most ESRI-dominant:

- Web - ESRI never had a major horse in this race. Google Maps is still there but more common now is Leaflet and Cesium for 3D is basically the only option. Both Leaflet and Cesium are FOSS.

- Server - As you say postGIS is now the industry standard

- Programming - There's some people using ArcPy if you are in the ESRI ecosystem but the plethora of FOSS libraries out there are probably bigger in scope and fit together better than ESRI. PyQGIS is another option but in my experience not as heavily used as other open source libraries (all of which are based on GDAL, OGC standards and the Java Topology Suite)

- Desktop analysis - This is ESRI's core stranglehold and I think qGIS is now a competitive option for most users (certainly it has most of the core functionality) however there's a lot of inertia to move from big companies especially those that want ongoing external support/training.

Co-opting universities to teach using Esri tools is a big part of Esri's marketing. They provide those tools to schools below cost, encourage (bribe) profs to incorporate their toolset heavily into their curriculum with free seminars in nice places, and it's often a revolving door between academia and Esri research posts.

Reminds me of the opioid industry!

Don't forget the SAS institute! Same business model!

SAS, matlab, ersi they all have the same business model. Subsidize students so they don’t know a competing tech and also capitalize and nurture corporate lock in.

I could rant about sas for ages. Its like it was purpose built to encourage anti patterns and Its own docs show code style is a foreign concept to the company.

Oracle pushes Java in universities too.

>>start teaching way more programming. The biggest regret of my education was that I was mostly taught how to use Geospatial tools rather than how to make my own.<<

This, a thousand times over. During my first geography degree I had a lot of GIS modules. I loved it, the capabilities it offered and so on. But it soon became clear that if you wanted to become genuinely good at it, you needed to learn programming, or at the very least have a very basic understanding of it. In this respect, my course was woefully inadequate; professors would perhaps touch upon it rather tangentially, and my requests to include programming in the course modules were brushed off. "You'll do more of that during your Masters!" they said. The reality is that even the MSc had very little of it. If I could say something to all those fresh-faced GIS undergrads, is this: learn programming; it will give you a much better understanding of how it works, it will greatly increase your capabilities in terms of what you can do (as Waterluvian so eloquently said).

For those of you wondering, I did my undergrad in the UK, graduated in 2009.

Also, greetings from a fellow geographer!

I am currently working as a programmer, that works mostly with geospatial data. I would never ever describe myself as a GIS person, nor a geospatial programmer - just because what GIS usually amounts to is a glorified data entry position, or some relatively simple spatial analysis.

Challenges presented in spatial data are really really fun, and interesting, you can extract so much more information if you also include their spatial relationship.

Sadly the industry itself is severely underpaid. If not for my excellent colleges, challenging but fun problems i would swap to typical soul crushing webdev job for thrice my pay.

TL;DR: Lean programming, and also learn GIS - they work perfectly together.

> As for Google Maps. The biggest tell is that there’s almost no geospatial capability in the software. They don’t want you to analyze and understand. They just want you to consume “where is X”. It’s a standard Google vector for ads approach.

It was never meant for that. That is/was Google Earth Pro.

A similar product, Google Earth Enterprise is now open source, amazingly. (http://www.opengee.org/)

Not to be confused with Google Earth Engine, which is the most shocking piece of technology I’ve come across in my career and is absolutely free if you can get access: https://earthengine.google.com/

Hey, either this news didn't reach my community or it went without much fanfare. What is it compared to Google Earth Pro?

Earth = consumer globe viewer.

Earth Pro = prosumer Google Earth.

Earth Enterprise = private, offline globe.

Earth Engine = research-oriented massively parallelized ML-based imagery analysis platform.

Google Earth Enterprise is a very different thing, but is a great call out.

As someone outside of this space, why do you find it shocking?

Intrigued. Why ‘shocking piece of technology’?

The Twitter thread linked at the very top of the page talks about it. https://twitter.com/mouthofmorrison/status/12656350684684861...

Point 9? That Google could (will?) just kill it at some point?

Rio Tinto runs some inhouse software that utilises (amongst other things) Google Earth Pro for analysis of open-pit minesite walls, constantly scanning for movement or changes that could lead to instability of a wall or road.

Open source GIS is awesome if you're able to go your own way and don't need someone to hold your hand through every step of the process. The sheer amount of functioning - and fast - code & data is pretty much unparalleled. It doesn't hurt that most of it is free (as in beer) and accessible to anyone with time, interest, and a willingness to learn.

Echoing your point though, you have to be willing to code. However, I've been working with geospatial data for going on four years now in various academic settings, and it still blows my mind that I can process a very large amount of publicly available data, very quickly, on old equipment and make meaningful contributions to research & policy.

Source: Worked through ~1.3K hdf5 files in the last couple of hours

seriously though, if I had a nickel for everytime one of the gis staff asked me to process something for them using postgis because arcgis would crash on them I would be rich. it seems like gis staff have turned into pretty map makers and most of the real processing and such is done in open source tools (postgis, gdal and python)

Totally concur; I've been giving myself a crash course in GIS as I ship for a house. Seems like a lot of GIS tools, although very flexible, are not built to handle a city's worth of fine-grained data. PostGIS is the only one who loves me!

I'm curious what a (consumer-level) house seeker can do with PostGIS that existing services can't provide. Do you merge and use datasets, etc. I was thinking of doing this in my own house search, and I would be happy to hear some pointers...

When you say, "robotics + GIS packages", what exactly do you mean? I've had a little experience with ESRI products, and a lot of experience with robots, but I don't understand the connection here.

Mobile robots are highly instrumented spatial data collection platforms. Here’s a very brief high level view. Regrettably I only touch on the surface of what is considerably deeper.

https://roscon.ros.org/2018/presentations/ROSCon2018_Unleash...

https://github.com/locusrobotics/qgis_ros

Ah I see, thank you for the follow-up!

Anything that has to work on mobile is pretty much never going to have much in the way of "analyze and understand" when it comes to maps. There's just not enough space.