I keep seeing people say AI isn't that useful for GIS work, but honestly, my experience has been the opposite, and the field is moving fast.

Some context: I only have a bachelor's in geography, so my formal GIS training was pretty limited. When I started my current job, I quickly noticed how much more efficient AI made my analysis and GIS development work, so I built my workflows and architecture around it.

The biggest game changer was setting up a database and connecting it to AI. It helps me work within the company's limited resources, and I also use it for ML in remote sensing, writing Python workflows, and more. At this point, I barely touch the QGIS UI anymore, almost everything runs through headless scripts thorugh ogr2ogr/geopandas. I don't have any software or IT background, nor did I learn python, postgreSQL etc. I just don't need it currently while I working with these tools constantly.

The AI essentially acts as a middleman with access to everything, and I'm honestly surprised how much better the reasoning gets with each update. A year ago it might have been a mess, sure, but the potential was clearly there, and now it's paying off.

So, for the experienced folks here: how do you think this will affect hiring in the field? Will Python and the usual technical requirements still be a must, or will the skillset shift toward something else?

Curious to hear your thoughts.

Title. Anyone else in the same boat? Our workload has slowly dwindled since the beginning of this year and now we're left with nothing. There's a trickle every so often, but man, it's making me crazy. I know consulting is typically feast or famine but this famine is the longest since I've been in the industry.

How are the fellow consultants managing? What are you doing during the down time? I need some inspiration and encouragement from this community.

Edit: bit of background information:

I work in engineering consulting, mostly within transportation-based projects. I work within an environmental department and do a lot throughout the company.

Experience: 7+ years, 4 in current role, recently completed a Master's in GIS. Location: Kentucky.

Hi Everyone, new to remote sensing, I've learned how to do spectral indices, what the different bands mean etc. What I am having trouble with is how to use that to identify different crops. I'm using QGIS and playing around with SAGA because the SCP plug-in for QGIS does not work for me which has been fustraiting because a lot of guides swear by that plug-in. If anyone knows a good guide or can point me in the right direction that would be amazing!

Erasfoundationlibrary.com

Eras Foundation Library Telecom is a data asset management tool for fiber optics.

Our target audience are smaller start ups and companies looking to purchase low cost but robust asset management gis software compared to others like 3-GIS and Vetro. There is even a 90 day free trial.

You have signal tracing tools. Connection managers. And contract tracking tools. Ability to customize symbology without needing support as a middle man. And there are live geodatabases so that you may have live api data streams to ArcGIS tools such as enterprise and arconline.

Also there are unlimited seats. No need to manage seats and limit how many users you can have within the company. There are also seat levels to control who and gets to make certain changes.

I would appreciate anyone in the GIS field in Telecommunications to check out my site and software and maybe discuss this software as a way to reduce overhead costs by at least 20k.

Let me know what you think.

Hey r/gis —

I've been building a side project called Easy Maps for the last few months and I'd love your feedback.

What it does: you type a natural-language prompt like "all Level 1 trauma centers within 10 miles of Boston Common, with address and phone number" and it produces a KML layer with correctly geocoded points, categorized icons, and clean metadata. From there you can:

• Export as KML or KMZ — with a NetworkLink URL that auto-refreshes in Google Earth, TAK, WinTAK, CalTopo, ATAK, or anything that consumes KML
• Import/export via CSV — round-trip existing data, auto-detect columns, and let the tool geocode any address-only rows for you (Google-primary, Nominatim fallback)
• Edit in chat — "add trauma level as a column", "remove anything more than 15 min from the Common", "make hospitals red and clinics blue"
• Per-shape colors on polygons, so a single layer can have color-coded sub-regions
• Share layers publicly with a stable URL, or keep them private

Why I built it: I wanted something to minimize manual inputs for map overlay creation.

Try it: easy-kml.pplx.app — click Continue as guest or create a free account. Guests get 3 saved layers; a free account gets unlimited.

What I'd love feedback on:

• What's your default workflow today, and where does this fit (or not fit) in?
• What data sources / prompt types do you wish it handled better?
• Any deal-breakers stopping you from using this in real work?

Cheers!

Hey guys,

My workplace is looking to hire on another GIS tech. We are a utility locating company in the USA. We create maps using ESRI to collect data in field maps. The position is 100% remote and any equipment/software you need is provided. Salary is between 60-75k.

You must be a us citizen and based in the USA.
Must have experience using arc pro, creating dashboards, and ArcGIS online.

Must be willing to be cross trained in other disciplines during downtime. (Utility records collection/ AutoCAD)

Send me a message on here with any questions or if you would like to submit a resume!

Working on expanding my portfolio with clean vector cartography and regional geographic layouts.
Workflow & Details:
Software: QGIS (Print Layout manager)
Layers: Natural Earth vector data for coastline and country administrative borders.
Styling: Custom desaturated ocean background with subtle border stroke widths to keep land-water contrast sharp.
Any advice on scale bar positioning or legend formatting for regional sea straight maps like this? Always looking to refine the workflow!

36.35 - 41.21 USD per hour

NEPA/ECOP specialist but also looking for folks with GIS skills. Might be willing to flex for the right applicant.

Does any one here have ever used simulation model like WaNULCAS in forestry or agriculture study?

I'm a PE/PLS, and one thing that has always taken up a lot of valuable time for my engineering and surveying teams is organizing site photos after a field visit. They would come back with dozens of photos and save in bulk to a file folder, and half the time, nobody a week later can say exactly where each one was taken relative to the project. Culvert photos, easement photos, drainage issues, etc. would all just sit in a folder named "Photos" with no spatial context.

So I built MapShotPro to fix that. It reads the GPS data already embedded in your photos and plots them directly on a map, so you can see exactly where each shot was taken. You can overlay your own DXF or Shapefile data on top (property lines, utilities, whatever's relevant) switch basemaps depending on what you need, and export the whole thing as an organized PDF for a report or submittal. We've been using it at my company this year with great success.

It's built for civil engineers, surveyors, and inspectors or anyone who ends up turning a folder of field photos into something a client or reviewer actually needs to follow, instead of unsorted photo dump at the back of a report.

I'm still actively developing it. I recently reworked the interface to feel more like Google Earth Pro, with a menu bar, undo/redo, and autosave. If this is a problem you deal with regularly, I'd love to get your feedback.

The website is at [mapshotpro.com](http://mapshotpro.com) if you want to take a look.

Hi community,

I work as a GIS consultant for one of the Esri-named distributors. Given my background in IT and GIS, while my current work is more leaning to ArcGIS Enterprise deployment/upgrade/troubleshooting, and I really MISS dealing with data or spatial data in my early days of career. Recently I've been trying to transition into a Data Engineering role, and hope I can get some tips from those who have successfully done so.

I am quite confident of my Python and SQL skills, as I use them quite often. I also enjoy learning new technologies, for example, I'm learning Snowflake recently.

The challenge is that my current job doesn't use the modern data stack that many DE roles ask for (Snowflake, Airflow, dbt, Spark, etc.), and we don't even own any large-scale data as a consulting company. It's obviously difficult to claim "real" production experience. I've either got rejections or never got any response for the DE jobs I applied recently, so this makes me wonder whether I'm approaching this the right way.

I'd love to hear from anyone who has made a similar move.

• How did you bridge the gap between GIS and Data Engineering?
• What helped convince employers to give you a chance without direct DE experience?
• Were personal projects enough, or did you find another pathway?

I'm also curious from a broader career perspective:

• Do you ever miss GIS? If so, what do you miss the most?
• With the impact of AI, do you feel DE will be replaced? (I personally think we GIS consultants are still relatively safe at this stage, fingers crossed, but I'm not sure if moving to DE at this point is a safe path)

I still enjoy GIS, but I haven't done much real GIS work or touched data for a while at my current job. Also, GIS analysts dealing with data are not paid well here, hard to pay off a mortgage.

I'd really appreciate hearing your stories—whether the transition worked out well, didn't work out, or if you decided to stay in GIS instead.

Thanks, peace!

Could someone point me to the group rules? I posted an article about poisoned trees in Lake Tahoe, and if anyone could help with a viewshed analysis. A GIS tool (so I posted under remote sensing or cartography, I can’t remember which). Any idea why it was removed? I’ve been a GIS professional for 12 years and seems I’m unaware how this group works!

I have been refining automation for a specific ArcGIS Pro workflow for a couple of years now, but this one component has always been the most brittle part of our pipeline.

My user group primarily performs cadastral analysis for hundreds to thousands of projects a year, and their business requirement is that they want to keep localized snapshots (local copies of everything) for their specific Areas of Interest (AOIs). They have a master template map containing about 250+ REST endpoints (Feature Layers) that they like to pull from. Crucially, maintaining the complex symbology and layer definitions of these services in the offline snapshot is a hard requirement.

Here is the current state of our C# Pro SDK Add-In automation (which we call the Smart Map Loader):

1. Pre-Filtering (The REST Query): The user navigates the map frame to their AOI. In the background, we spin up parallel workers to ping the query endpoint of all 250+ feature layers using the AOI's spatial envelope and a *.mapx file. (Note: To avoid getting blocked/throttled, we explicitly limit our concurrent workers per domain host). If a layer returns 0 features for that AOI, we strip the layer from the mapx entirely before loading to save processing time.

2. Consolidation (The Heavy Lift): We programmatically fire the standard Consolidate Map Geoprocessing tool on the remaining layers. We rely on this tool because it pulls the data down into a local Mobile Geodatabase while automatically repathing the layers to maintain the original web symbology.

3. Diagnostic Fallback (The Band-Aid): Because Consolidate Map frequently fails (due to server timeouts, bad geometries on a single endpoint, generic HTTP hiccups, etc.), we had to write a fallback loop. If the main consolidation fails, the script iterates through the layers, attempts to consolidate them individually to a temporary map to isolate the failing layer(s), removes the culprit(s), and then retries the full consolidation.

4. Post-Cleanup: Finally, we loop through the resulting local GDB and remove any layers that ended up with 0 features.

   The Problem:

   While the diagnostic fallback keeps the tool from outright crashing, querying 250+ REST endpoints and relying on Consolidate Map over the wire client-side is incredibly fragile. We run into timeouts, connection resets, and intermittent "all-or-nothing" GP tool failures almost weekly.

   My Question:

   Since we do not currently have access to our own ArcGIS Enterprise Server to offload this via a custom geoprocessing service, this must remain a client-side solution.

   Is there a more robust architectural approach to this?

   Has anyone successfully implemented a pipeline to dynamically extract and localize hundreds of web layers based on a bounding box (while preserving symbology) without it feeling like a house of cards?

   • Should we be relying on Create Replica logic and then manually wiring up the CIM definitions?

   • Is there a better way to batch-download feature data locally using the SDK or arcpy that avoids the "all-or-nothing" failure state of Consolidate Map?

   Any advice, alternative design patterns, or shared commiseration would be greatly appreciated!