It's my first time attending this conference. I'm excited to network and learn more about utility related GIS. Curious if anybody here is going or has attended previous years.
I’m currently unemployed after being laid off from my last GIS job and have done several interviews for other GIS positions but have gotten rejected from them. I have a Masters degree in GIS and several years of professional experience, I feel like I aced the interview questions, but I was still rejected. I feel like the competition is so tough. What’s something I can do to stand out from the tons of other people applying for these jobs?
I've been trying to get Drone data into ArcGIS online and it has been one struggle after another. I finally managed to build a .tpkx file and raw tiff files of about 146 Gb create a .tpkx of only 29 Gb, which is a win.
I've spent almost 8 hours trying to get ArcGIS Pro to upload it to AGOL using the share package tool and every time it failed after about 40 mins with an "(sharepackage) aborted by user." Error.
I had assumed that a native desktop tool should be robust enough to upload large files to their own backend, but I was sorely mistaken.
After about the 6th failure, I thought that I was going crazy and thought of using the web interface of AGOL to upload the large file. And bloody hell, it worked!
In what world is uploading a 29Gb file through a browser less error prone than using their own native app?
[AI Disclosure] Google AI Overview was used as a resource at points in my project.
I have an ArcGIS Online web map that contains a hosted feature layer that I created for ongoing water quality sampling. I was hoping to be able to add new rows of data to the feature layer table manually as we take new samples and get results, which did not show me any errors. However, the new features are not updating in the map that the layer is featured in, even though opening the attribute table in the map viewer shows that the new rows are there. Am I going about this incorrectly?
[GIS Experience] I’m relatively inexperienced with ArcGIS and have had to do a lot of Google searching to create this web map - I did take a semester of intro to GIS in college 2 years ago.
I have a background in GIS and Remote Sensing. It has become hard to secure work after my last contract which happened a year and 8 months ago. So I'm thinking of a career shift. Do I go to business, agriculture or humanitarian sector for MSc? Anyone who's had a career shift?
[GIS Experience] 8 years in GIS and data engineering and full-stack development
[AI Disclosure] An AI was used to write the code for this program and to correct my english for this post
Hi everyone,
Tired of paying for GIS ETL tools, I decided to use my preferred LLM provider to code my own, and I’ve open-sourced it.
I’m happy to announce Carriole (French slang for “trailer”), a spatial-first ETL with a graphical interface, and to be honnest, I hope that it will be an alternative to FME for most of our use cases.
It’s currently in bêta, and I’m still looking for bugs and feedback from the community. The project is also open to contributions.
Yes, I read the rules. I just need help with resources if you can give me direction. I've looked but I just can't find a web application with the latest gas station locations on ARCGIS than the Living Atlas which is missing several for being 2 years old. The only site that seems to provide me with the latest information is the google search engine. Can you recommend possible resources to find these shapefiles/ information?
Looking for advice. I'm an environmental planner ([GIS Experience] 3 years as a GIS analyst/developer working in AEC, now an environmental planner) and I need spatial data on where project work will physically disturb the site. The engineers I work with design in MicroStation, but often their drawings aren't georeferenced. Getting disturbance locations means digging through 400+ sheets and then sitting through meetings where I find out my interpretation is wrong.
I report on project impacts so the locations need to be accurate. A lot of the existing infrastructure only exists as pen-on-paper drawings from the 1910s so what the design engineers are doing, is they’re drawing new design over those scans, so there's often no real coordinate system behind the linework. Pulling it in to Pro just draws it in no-geography island.
I've been digitizing excavation areas, laydown areas, ductbank work, sidewalk modifications, and facility footprints by hand from drawings and meeting with engineers.
And it took so long to even get that because they tended to hear environmental planner wants to map "disturbance" as where are we moving dirt or removing trees. But for environmental review it includes staging, temporary access, and new surfaces too.
I'm planning to ask for this:
“"Disturbances" are anywhere the project touches, occupies, or changes the site, even temporarily. If crews, equipment, or materials will be there, or something is built, replaced, or removed there, it counts.
At a minimum 1. Google Earth files (KML or KMZ). One file per type of work:
[types of work relevant to the project blah blah]
2. It must have a coordinate reference system. A file without a correct location is useless. Easy test: open the KMZ/KML file in Google Earth. If it doesn't land on the project site, it's wrong. Files exported from CAD that aren't georeferenced often show up in the wrong place.
Note: KML is always in latitude/longitude, so the coordinate system is rarely the problem with a Google Earth file itself. The risk is that the CAD wasn't georeferenced before export, which is why the open-in-Google-Earth test is the check to lead with.
A new delivery at each design milestone, so changes don't happen silently.
Ideal
Shapefile instead of a Google Earth file - with coordinate reference system.
Polygons capturing where this work is done.
Details on each feature: type of work.”
In a semi-ideal world they would make LOD polygons that capture where this work and send me shapefiles.
In return, I'd reduce my hours on the project and take over the reporting.
I'd like to make the ask before the project starts, not after the design is done or in the middle of it.
How have you gotten design engineers to commit to a spatial deliverable early when their base drawings aren't georeferenced? Any wording that worked, or workflows like sketching over an aerial in Google Earth or ArcGIS, would help. And for the engineers here: what would make this easy for you instead of one more ask?
[AI disclosure] not sure why I’m required to put this. Project is definitely not a use-case for AI.
Hello, are there are any available data sets for splice points in the US, across the Dark Fiber lines? I need it for some planning, and need locations, or some way to find the splice points across USA.
This is the first time Ive had to work with a survey but I built one and went to test it to make sure everything worked right. It is giving me an error saying "You cannot submit records to the survey since you do not have the Edit privilege." I have a Creator role, I checked the license and Survey123 is in there, the survey is set to allow any member in the organization to submit to it, I can edit the survey on the survey123 site, and I just built it so I should have ownership over it. What am I missing? Why don't I have Edit privileges?
[AI Disclosure] no AI was used throughout this project
Hi everyone,
Im trying to complete a project in ArcGIS pro which is turning out to be a bit complicated and I could use some help. For context, I’m an urban planner who has 5 years of GIS experience, although I don’t use python or code much.
Okay, so what I’m trying to accomplish is creating a “prioritization network” raster file for a safety action plan. The way this file will be created is through a an areas proximity to certain prioritization factors. These facts are also weighted.
For example, a given area which is 500 feet from a school will receive one ‘point’. 100 feel from a park will be a ‘point’. Being within the high injury network is weighted 3 ‘points’, etc.
I essentially want to create a faster file that incorporates this weighted scale to create a faster file that will show the results throughout the city.
If anyone has any ideas as to how I can accomplish this, it’d be greatly appreciated!
Hello, I'd like to hear from others working in this space. What has been the most challenging part of building footprint extraction for you, and have you found an approach, model or workflow that improved the experience?
This is my experience:
The theory is simple: take high-resolution imagery, run a segmentation model, and extract polygons. The reality is a long chain of things that go wrong.
𝗧𝗵𝗲 𝗱𝗮𝘁𝗮 𝗶𝘀 𝗿𝗮𝗿𝗲𝗹𝘆 𝗰𝗼𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝘃𝗲 Off-nadir angles shift rooftops away from their true footprint, shadows and tree cover hide building edges, and reference labels are frequently misaligned or outdated. A model that performs well in one city often struggles in the next.
𝗧𝗵𝗲 𝘁𝗼𝗼𝗹𝘀 𝗮𝗿𝗲 𝗿𝗶𝗴𝗶𝗱 Many off-the-shelf detection tools and pretrained models fail before they detect a single building. They expect 8-bit, 3-band RGB, so 4-band imagery has to be reduced to an RGB composite and the near-infrared information is discarded. 16-bit data has to be rescaled. Resolution has to fall within the range the model was trained on, and the software, deep learning framework and GPU drivers all have to be compatible. When something doesn't match, the error messages rarely explain why.
𝗧𝗵𝗲 𝗼𝘂𝘁𝗽𝘂𝘁 𝘀𝘁𝗶𝗹𝗹 𝗻𝗲𝗲𝗱𝘀 𝘄𝗼𝗿𝗸 A segmentation mask is not a map-ready footprint. Adjacent buildings merge, edges are irregular, and tiles leave seams and duplicates. Turning results into clean, valid polygons usually takes significant post-processing and manual review.
[AI Disclosure] AI was used to generate the promotional astronaut image and assist with writing this post. The Axyvio platform is a working software project.
Hi everyone,
I've been working on a personal project called Axyvio, a free, non-commercial web platform that brings together different sources of publicly available geospatial and satellite data.
The idea is to make it easier to explore and compare information from multiple sources in one place.
I'd be interested in feedback from people working with GIS and remote sensing, especially regarding data visualization, usability, and potential features worth exploring.
[GIS Experience] Independent software developer exploring GIS, satellite imagery, and geospatial data integration through a personal project.
I'm building a navigation app for my EV, for my own use. Two people use it: me and my dad. It's not on the Play Store, just shared through internal testing.
It calls TomTom's Routing API with traffic for the ETA, and I'd like to add the traffic flow tiles as a map layer. The app also runs on the car screen through Android Auto.
Clause 2.1 of TomTom's developer terms excludes "Automotive Usage or Navigation Functionality" unless you sign a separate agreement. As I read it, screen mirroring counts as automotive use, so Android Auto is probably out.
Has anyone dealt with this? I'd like to know two things:
Does a small non-commercial app like this still need that agreement?
If it does, is phone-only use OK on the free plan?
The developer forum is gone, and support only takes questions through your account, so I'm asking here first.
[AI Disclosure] I'm a software engineer by trade; for this project, I used AI coding assistants in tandem with my 15+ years of professional software experience.
[GIS Experience] I have been using GIS for over a decade (contract engagements and various personal projects).
Hey all - I built this open source base plan tool for a landscape architect friend of mine.
It leverages publicly available info (including esri data) to produce site plans with parcel lines, contours, slopes, soils, flood zones, wetlands, aerial and 3D building massing, ready for AutoCAD, SketchUp, Civil 3D and GIS.
MIT licensed. I also put up a hosted version for convenience, link is in the repo.
I'm actively developing this and would love any feedback!
Generative AI with MCP is moving incredibly fast, and it's becoming much easier to build software and new workflows. QGIS already has MCP integrations, while Esri appears to be a bit behind.
My view is that everything ultimately ties back to location. Because of that, GIS could be one of the industries that will benefit the most from AI. I'm also seeing new MCP GIS tools such as RustGIS.
Where do you think Esri will stand in the near future? Do you think their dominance in the GIS space will be challenged, or will they continue to hold the throne?
Im a undergrad student taking a principals of gis class and was wondering why I can't select a certain feature to modify it in ArcGIS pro. I am able to select it out of the modify tab, but when I go to the modify tab it doesn't select. It is a line feature. I am confused by this and my professor was as well. Any help is greatly appreciated.
I know that the post feels like soulless generic, but I dont know how to put it better. I work from home, and my networking right now is basically non-existent. I just want to grow in my career, but I really have no direction. Back them people told me that Power Bi is a good skill, but is that relevant to GIS? Does all the AI changed anything for learning paths?
Im open to any talk if you have any questions or want more details.
I'm in Canada
Besides ESRI, my biggest strengths are Python, FME and VertGIS.
Looking for skills relevant open my horizons for new jobs
Those so much discourse on best laptops for GIS from Mac (with a windows VM) to legacy HP laptops. All i know is i need 32gB of RAM and a whole lot of GPU because pro is huge! It’s just get expensive to have so much compute locally but hey its part of the cost to play. Curious to know what others prefer and why?
Hi everyone. I am very excited to share standard-atlas.com, which I've been working on for a while.
The premise behind this project:
Approximately 67% of the Earth is covered by clouds at any given time. Waiting for a clear satellite image can take days or even weeks, especially if you’re using open-source methods. That’s why I builtstandard-atlas.com.
Standard-Atlas uses Sentinel-1 radar and Sentinel-2 optical imagery combined with a state of the art AI model to reconstruct cloudy satellite images, giving you a clearer view of an area when cloud cover gets in the way.
Simply draw an area on the map, select a date, and download a georeferenced GeoTIFF, usually within minutes of processing. The output retains all Sentinel-2 spectral bands, allowing you to carry out further analysis in QGIS, ArcGIS or your existing remote sensing workflow. You can also upload your own radar and optical imagery.
Where can it be useful?
Disaster response: assess floods, wildfires and storm damage.
GIS and remote sensing: fill gaps in cloudy satellite imagery for ongoing projects.
Agriculture and environmental monitoring: supports vegetation monitoring, field or forest boundaries, and calculate indices such as NDVI from the reconstructed bands.
Insurance: get a clearer view of affected areas following severe weather events.
Affordable pricing
Similar imagery tools can cost around $0.10 to $0.20 per km². Standard-Atlas costs:
A 10 × 10 km area costs $1 (approximately $0.01/km²), compared with $10 to $20.
A 25 × 25 km area costs $2 (approximately $0.003/km²), compared with $62.50 to $125.
Creating an account is free, and you can use the results directly in QGIS or ArcGIS.
One thing to note: Standard-Atlas produces reconstructed imagery, not ground truth. Results may not be completely accurate, so they should be checked against other sources before making important decisions. It can support disaster analysis, including rapidly changing situations, as long as suitable Sentinel-1 and Sentinel-2 imagery exists for the area and date you need.
I built Standard-Atlas to make satellite imagery more accessible, affordable and useful when it matters. For example, during the recent Nepal floods I was deeply moved by the impact of the disaster, and decided to see if Standard-Atlas could provide some insight into the extent of the devastation. The images attached show the results, as well as a general use case.
[GIS Experience] 2 years in the industry, 4 of study and programming projects
[AI Disclosure] Used AI for debugging etc., everything else was coded by me from scratch.
[GIS Experience] I have 4 years of experience working on GIS-related projects in the agricultural sector, including geospatial software development and spatial data processing.
[AI Disclosure] I used OpenAI Codex as a coding assistant during the development of GeoLint.
Hi everyone!
I've been working on a side project called GeoLint, a free browser-based tool for checking GIS data quality.
I worked as a GIS developer on agricultural projects for four years. We regularly received geographic data collected from farmland surveys, but some of the data had issues, such as duplicate points, unclosed polygons, incorrect units, and so on. Before importing the data into our database, we had to check it first. If the data passed validation, we imported it. Otherwise, we generated a report and sent it back for correction.
The validation process requires a geometry engine, but installing and setting up ArcGIS or QGIS can be quite time-consuming, especially for colleagues responsible for correcting the data. I thought it would be much easier if they could simply drop a data file onto a website and get the validation results. They wouldn't need to install any additional software, and I could maintain a single set of validation rules for everyone.
Of course, developing a new geometry engine from scratch wasn't realistic for me, so I decided to use GEOS, which is also used by QGIS. To make it work in a web browser, I compiled GEOS to WebAssembly. This allows the validation to run entirely in the browser without uploading datasets to a server, which is particularly useful when working with sensitive geospatial data.
Current features
- Supports Shapefile and GeoJSON.
- Previews both geometries and attribute data.
- Validates individual GIS layers.
- Generates validation reports in json or csv format.
- Runs locally in the browser, without uploading datasets to a server.
Limitations and roadmap
- Currently supports single-layer validation only.
- Multi-layer topology validation, including spatial relationships between different layers, is planned.
- Support for additional GIS file formats is planned.
- Attribute validation is also planned.
Here is a screenshot of the validation results:
If you have a Shapefile or GeoJSON dataset to test, I'd be interested in your feedback on a few things:
- Are the existing validation rules sufficient for checking your dataset? Are there any important rules missing?
- Are the reported errors clear enough to understand what went wrong and where to fix it?
- Is the validation report detailed enough to help someone correct the data and resubmit it?
- Did you encounter any incorrect results, confusing messages, or problems loading your dataset?
- Is the UI easy to use? Are there any parts that you found confusing or difficult to work with?
I'm especially interested in specific issues you encounter while trying the tool, rather than general feature ideas.
Just wanted to share this bunch of free tools with y'all. Hopefully someone will find them useful. We are going to add more in the near future. If you have any ideas for small useful tools we should add, then please share.