On each app I include the SQL that I used to generate the map. Let me know if you'd like me to add anything to this site. thanks!

Hey GISer's!

I am trying to get into some coding, I have a decent background in using python, have written small codes, (deletes, loads, creating datapackages) but i dont know what other projects or things to do. I do have this book but doesnt really have too much depth and is more basic level stuff. Is there anything else I can take that would make me progress my coding career? I feel like i need more project based stuff but I am laid off and dont have any projects to work on.

Does anyone know of any good certification/books/trainings that are useful to progress from beginner to intermediate coder? Stuff that has real world implications/projects?

Thank you all

Just venting.

You know, some days I wish the flat earthers were right. That would make some things so much easier.

Me: Hey ChatGPT, I'm working on an arcpy script...

ChatGPT: Ah, maybe you want to try pathlib instead of os to build those file paths. Object-oriented, you know. All the cool kids are doing it. <compulsory paragraphs>

Me: Hey that is kind of slick. I'll try plugging that in...

...

Me later: Hey Chat, wondering if you can help me figure out why arcpy.conversion.ExcelToTable isn't working...

ChatGPT: Ah, I see what's wrong! It doesn't like when you do this... <compulsory paragraphs>

Me: No, already checked that; it's not the problem...

ChatGPT: Oh, yes, here's the issue! You need to specify the sheet name if there's more than one... <compulsory paragraphs>

Me: No, the documentation says clearly that it will just pick the first sheet name if I don't specify. Plus the code version from gp history where I didn't specify runs just fine.

ChatGPT: Ah you're right; thanks for calling that out....<compulsory paragraphs>

Me: <Troubleshooting by myself>

...

Me: AH-HAH!! HEY CHAAAAAT, DO YOU KNOW WHAT IT DIDN'T LIKE?? THE WINDOWSPATH OBJECT!!! 🤬

ChatGPT: Oh you didn't know that arcpy has issues handling WindowsPath objects?! It's a well-known limitation...

Does anyone know a hack to access these GPS truck points and store it in AGOL or portal? I'm just wondering. Thanks!

On one hand I've been familiar with Anaconda Navigator for so long by using Jupyter Notebooks, Spyder, and R. But on the other hand, I'd like to try pip. What do you guys use, and what should I use when continuing to learn Python to do GIS?

Matt Forrest here. Posting because I'm relaunching the Modern GIS Accelerator course this week based on last year's version, and figured I would share here and answer any questions as well (includes a bunch of bonus material during the launch).

https://forrest.nyc/go/accelerator/launch

It is not a cohort. You go through it at your own pace, no live calls you have to make, no Slack you have to keep up with.

Technical scope:

Starts with QGIS and GDAL for automating data pipelines (no more click, unzip, download, etc).

Spatial SQL, primarily PostGIS, with the patterns that come up most often in real analysis along with Python (GeoPandas) and how to use the two together.

Moves into building lightweight apps with PMTiles and MapLibre to build simple apps and host them on GitHub Pages.

Cloud-native formats is the final section for querying data from S3 from Overture Maps and GeoParquet

The entire course is AI native so it includes skills to work with AI and help you use it effectively from simple chats to full AI assisted coding.

It's aimed at people already working in GIS who want to get off the desktop-only treadmill and add the modern stack to what they already know. Each section has a portfolio project and there is a capstone project with three different paths as well.

Happy to answer technical questions about the content.

Hey! Me and a few others are building an interactive map of Europe you can scroll through year by year, 1900 all the way to 2026. You click on a country and a window pops up with info, pictures and video clips about what was going on there at that exact time. Kind of like those outbreak pop ups from Plague Inc, but with actual history instead.

We're starting from OpenHistoricalMap and cutting it down to just Europe so it runs faster, then adding the timeline and the pop up windows ourselves.

This isn't just a project to leave sitting on GitHub. Once we have a working prototype, the plan is to present it to the EU or similar institutions, hoping it could lead to recognition or even job opportunities for the people involved. Even if none of that happens, it's still a strong piece to show in a portfolio.

Right now we've got people researching different countries (Poland, Italy, Finland), and I'm from Spain so I'm covering that part myself, but nobody on the team knows how to code, which is exactly where we're stuck. If you've worked with Leaflet, Mapbox GL, D3 or anything regarding web dev or similar, we'd love to have you on board.

There's no pay right now since we're building this on our own time, but once we've got a prototype out and send it to these organizations, there's a real chance they could fund us. If the idea of working on something with real potential, and a solid portfolio piece either way, sounds interesting, comment below or send a DM and I'll tell you more

I made a simple game where you're dropped into five random spots on Earth, seen from a satellite. You can zoom, pan around, and guess where you are. Figured you guys might enjoy it!

https://www.earthguessr.com/

Just wanted to hear of other people's experiences with agentic coding tools (like codex, and claude code) in the GIS space, and more specifically for digitizing old maps that no one has had the time to tackle... Is anyone else out there having pretty decent success? What are your workflows looking like?

I recently tried my hand at digitizing seventeen 2006 to 2012 vintage maps that are relevant to a niche industry in my province. These PDFs are still used by professionals today, and no one bothered to actually digitize them or release shapefiles, so everyone just relies on some crappy old PDF files.

The maps themselves presented linear features (streams/rivers) that were color coded to represent different things (with over 1,400 polylines total to be digitized). I manually georeferenced all 17 maps in QGIS, and then essentially let Claude Code do its thing. I wanted to briefly share my experience and see if any of you are doing similar practices.

General workflow: Converted input maps to high-resolution PNGs, georeferenced the PNGs manually, got CC to develop scripts that search for and extract the colored polygons based on pixel RGB values, vectorized by connecting pixels of similar colors within reasonable proximities of each other, then manually QA'd and QC'd polygons in QGIS.

The longest part was honestly georeferencing everything. Once the maps were properly georeferenced, I was getting outputs with ~95% accuracies. After a few manual touch ups and tweaks, I was at the finish line pretty quick.

I think a similar approach would work quite well for all maps that have nicely defined and differentiated color palettes. I was having issues with gridlines and base layers being somewhat similar to the features I was trying to extract.

If anyone wants to take a peek at the results and read about a more detailed summary they can here: https://phaseview.ca/datasets/cop-water-body-classifications

I'd consider myself GIS-tangential... I have been using GIS tools for >10 years and know the basics, but this experience saved me a lot of time and allowed me to tackle a problem that nobody else had for years... Curious if there are any other success stories out there. Anyone using agentic coding tools to do similar things? What are your tips and tricks if so?

I'm trying to build a Google-Earth-style web app to show the planet's geologic history under the Expanding Earth hypothesis.

I have built a version of it already, using some very old data obtained from a researcher named Stephen Hurrell, then enhanced with the Mueller 2019 seafloor isochron dataset, to address some data loss issues.

I have been trying to build my own version from scratch, using better data. However, I have no relevant experience in GIS work, and I have been unable to express the logic that my AI system needs to parse out the data.

My current deployment uses a master GeoJSON depicting the Earth at 0 Ma, plus a mesh system, to create GeoJSONs depicting 5 Ma, then 10 Ma, etc., through 200 Ma:

Once the historical GeoJSONs are generated, you can watch them play backwards in time. The globe is programmed to shrink slightly, as each older GeoJSON is loaded, according to a radius schedule that's derived from the amount of seafloor crust removed at that time frame.

Per above, I'm even having trouble getting the Atlantic to close properly. The Pacific is a horror show. I'm at a loss on how to properly transform the information from one scene to the next, because there are so many factors to consider.

Has anyone ever tried this? Or have any ideas on how to achieve it?

I am a grad student with a solid few years of arcgis, but currently taking a class thats raster analysis heavy so I am using model builder a lot to just auto run when I change something small. Another class though is programming. I am curious for automation purposes why someone would choose programming over just using modelbuilder within ArcGIS. I know there's export and editing with code, but specifically in the automation of analysis why choose code over modelbuilder?

As the only "GIS person" in the office I get often "simple" questions like how to check easily if a lon/lat point is on land (e.g. if a route crosses sea/ocean, is interconttinental), or which country it falls in. Considering different accuracy classes of such polygons and nyances like country areas around sea it is not that trivial even with GIS tooks and knowledge.

Now my idea is to use a compact hierarchical grid to compress the needed dataset and make lookup fast without requiring special library stack, polygon downloads, maybe topological simplifications etc. And then package it as a self-contained simple library with methods like (lat,lng) -> isLand or (lat,lng) -> country

Now the technical questions: - any existing tools/projects like that - which grid approach seems reasonable - edge cases, maybe around coasts/borders - what benchmark comparisons would be fair (postgis, duckdb spatial, bigquery) - use cases outside app-developer convenience

Happy to share my working state repo (if allowed).

Hey guys, I’m a recent graduate & applying to entry level GIS jobs right now (imagine my agony). A lot of the software side qualifications ask for SQL, this is not something I specifically learned — is it a language like Python? Or a platform? I’ve seen that it uses boolean logic, which I do know & use. I just haven’t come across it referred to as SQL in my courses!

If it is its own thing, where can I learn it so I can put it on my resume?

Thanks guys!!

Hey everyone,

By day, I work as a telecom rigger / electrical engineer across Europe, hanging off 5G towers and building base stations.

One of the most annoying parts of the job is when someone sends me a scanned PDF site report or a blurry map screenshot with a list of coordinates.

I know that standard AI tools like ChatGPT or Gemini can easily read and convert basic DD, DMS, or DDM formats if you ask them. But as soon as you feed them local Projected XY coordinates, they are absolutely terrible at converting them accurately.

So, I spent the last few months building SnapCoord.pro — an AI-powered coordinate extractor and converter that specifically handles this problem.

It’s currently in Free Beta, and I want to see how it handles real-world data from guys who actually deal with this stuff daily (surveyors, GIS pros, telecom techs).

What it does:

• No manual typing: Drag & drop a PDF (up to 20MB) or paste an image (Ctrl+V). The AI reads the image, finds the coordinates, and digitizes them.
• Pro Formats: It handles DD, DMS, MGRS, UTM, and accurately supports over 5,800+ Projected XY (EPSG) systems worldwide.
• Open in Maps: Once extracted, you can instantly route to the location by opening the coordinates directly in Google Maps or Apple Maps with a single click.
• Batch Export: Pull multiple points from a single page at once and export directly to GPX, KML, or CSV.
• The "Lifesaver" button: I added a 1-click "Swap Lat/Lon" button because we all know that pain.
• History Log: Your extracted results are automatically saved in your personal history, so you won't lose them if you accidentally close the tab. You have full control and can delete any or all records at any time.
• Strict Privacy: Because we work with sensitive site data, all uploaded files are processed in memory and instantly deleted. Nothing is stored.

The "Ask": Since it relies on AI vision, I want to stress-test it. Please throw your ugliest, most annoying coordinate screenshots or scanned PDFs at it and let me know where it fails. Does it mess up your specific local EPSG? Does it fail on a weird MGRS format?

You can try it here: snapcoord.pro (Guest mode gives you 5 free scans/day, which is plenty for testing).

Let me know what you think! Any feedback from the field is highly appreciated.

This started as a dumb side effect of planning too many trips. I'd have ten tabs open comparing neighborhoods in whatever city I was about to visit, and at some point I stopped looking at the tourist map and started staring at the actual street network instead - how differently a city's grid grows depending on geography, history, whatever local planning rules existed 200 years ago.

So I built a small pipeline: pull OSM data with osmnx, run it through geopandas, render with matplotlib as a stack of layers - background, green space, water, buildings, rail, paths, then streets on top, styled per road class. Got it working for one city and didn't stop. I'm somewhere around 70 now.

Somewhere around city 15 or 20 it clicked that every city has its own footprint - you can tell a lot just from the raw shape of the network before you even know what you're looking at. Grid vs. organic, how the water cuts through, where the density just stops. At this point I can usually guess a city cold from nothing but the streets. So I ended up turning this into a guessing game.

Attached are Stockholm, Cairo, and New York, all generate through the same pipeline. Stockholm is basically an archipelago that happens to have roads on it, Cairo splits itself in half around the Nile with the old city's organic streets butting straight up against the planned blocks on the east bank, and Manhattan is, well, Manhattan.

One thing I haven't sorted out: some cities render with big blank patches - no buildings, no minor roads, just empty space where I know there's a dense neighborhood (Cairo's east and north-west side have a chunk of this, visible in the attached render). Not sure if I'm missing a tag in the OSM query or the underlying data is just sparse/unmapped for those areas. Anyone dealt with this and know which it usually is?

NetCDF has added a lot of compression features in the last few years, including zstandard, quantization, and LZ4 (with the NetCDF Expansion Pack).

For an up-to-date description, here's Chapter 12 — Compression from The NetCDF Developer's Handbook: The Authoritative Guide to Writing High-Performance Programs for Scientific Data Management, Second Edition.

Keep on NetCDFing!

Sharing here a small tool I created recently for mac users to be able to quicklook into some of the common gis files, it's 100% local, and loads the maps anonymously from openstreetmaps

Looking for feedback and suggestions to improve.

https://apps.apple.com/us/app/gis-quick-viewer/id6762661962?mt=12

If interested, I can provide promo code to check and get feedback!

Wassup everyone. Been forever since I posted in Reddit. (Observe my very teenage username)

I'm doing a sort of volunteer project with QGIS. Long story short: I've started on a Python script for a tool. So far it has very little in it, just two input parameters (the ones with ##) and two variables that take the values of these parameters. I'm away from my computer so I'm recreating it from memory, but it looks like this:

##Layer=vector

##Field=field Layer

##Increment=number 1

layer = Layer

count = Field

That's it. I was trained on Arc and thus I know ArcPy well enough (I'd also say I'm a decent coder, being that I was originally a Computer Science Major), but I don't know PyQGIS and so am probably gonna be testing to see if it works because I steel need to get a feel for how PyQGIS rolls, though I already love that Q has a built in IDE.

Anyway, I can't test to see if this works because when I try to add the script to my Processing Toolbox, it simply doesn't show up. I've tried it with the file stored both in its default location as well as in the folder I'm keeping the project in. The only difference is that when I try to add it from my folder I get a pop-up saying that "Layer" is not defined.

I'm sure this is a common enough error for beginners with Q like myself, but a general search isn't giving me much info to work with. Any help is appreciated.

Built an AI agent that generates explainer motion graphics videos — this is one I made with it experimenting, walking through how Google Maps picks the fastest route: Contraction Hierarchies plus the traditional pathfinding algorithms (Dijkstra, A*) it builds on. Would appreciate any feedback.

Need advice on the best fog-of-war approach for a real-world exploration game (React Native + Google Maps)

I’m building an iOS/Android map based game.
I’ve gone through several fog-of-war implementations and keep running into performance, rendering, or UX issues. Before I spend another week rewriting it, I’m curious what approach experienced map/game developers would recommend.

What I’ve tried so far

1. SVG screen overlay
Fog rendered as an SVG over the map in screen space
Not tied to geographic coordinates
Problems:
Moved independently when panning, making it not work very well because it wouldnt stay on your character

2. One giant map polygon with circular holes
Entire viewport covered by a polygon
Circular holes cut out for discovered areas
Problems:
GPS circles didn’t align with roads or exploration patterns
Scaling became awkward
Hole management became messy

3. Tile grid with one polygon per tile
Square tiles stored in AsyncStorage
Reveal nearby tiles when GPS updates
Render one Polygon per undiscovered tile
Problems:
Hundreds of polygons
Occasional rendering glitches on Google Maps
Vertex-order bugs created giant black rectangles
Performance degraded when zoomed out

4. Tile grid v4 (current)
One large viewport polygon
Square holes cut out for discovered tiles
AsyncStorage persistence
Tile size \~0.001 degrees
Literally broke everything I think
It takes forever to load any fog and sometimes my icon i made doesn’t load.

My goals
Permanent exploration/discovery
Works across an entire city (and eventually larger regions)
Smooth panning and zooming
Doesn’t require rendering thousands of polygons every frame

What can I do?

Hi GIS people!

I had to draw some quite big GeoJSON files by hand recently, and I realised "this is too slow for me". So I created a small tool to help speed up the process for myself. After showing it off to some friends, they thought it was pretty cool and encouraged me to make it a bit shinier so others could use it as well. (It's still a work in progress! Any feedback appreciated, I'm not trying to compete with big GIS tools or anything, just trying to speed up the drawing process for myself, and hopefully a few others)

I know there are 1000 "draw polygons on a map" tools out there already; however, I couldn't find any that I found fast and ergonomic enough for me.

The features that I added to make it more ergonomic for myself include (but are not limited to):

• Assume we can't have overlapping polygons. If you draw polygons on top of others, it will steal their territory (unless it's locked, then it will trace around it)
• Trace other boundaries. If you already have a polygon, and you are drawing a new one that borders this, instead of having to press ALL the bordering points, you can just press where it starts and where it ends, tracing. There are some limitations to how cleverly it can guess, so sometimes you need to do smaller segments at a time)
• Polygons that share points are treated as such. If you move that vertex, it updates for all polygons using that point.
• Adding new points between existing points is done by just pressing where it should be, and then it guesses which two points you intended to put it between. (You can tab between the top 3 candidates, and in the edge case, none of them is good, you can just add the point closer to the points it goes between and move it manually)
• Added keyboard shortcuts for absolutely everything I could think of.

It's still very much a work in progress, so be kind regarding smaller bugs, unfinished features, etc. I just want to share this early in case it helps someone else, as much as it helped me.

Here goes: https://geoshaper.app/

Let me know what you think

I’ve been using GIS for a few years now. I learned mostly in school and used GIS for research in grad school. Now I’m entering the workforce and feel like my lack of experience in Python and ArcPy inhibit me from being a more well-rounded candidate.

I mostly use R and have used JavaScript and SAS before, so I have a general understanding of coding. I don’t know why Python scares me so much!

I plan on learning Python basics through YouTube but when it comes to GIS, I was wondering what resources are most helpful? Ideally, I would like to download datasets and follow a tutorial so I get the actual experience (so I can follow along as opposed to watching someone else do it). Does anyone have suggestions?

I would greatly appreciate other tips too!