What is this artifact on this satellite image? AI and a colleague tell it should be a plane, but i do not understand how that should be possible. The speed over ground of the satellite, around 7 km/s is much faster than the speed of an aircraft at 250 m/s. In no geometry the plane would be on the scanning line of the satellite for so long. PLS explain
Good evening,
I’m 28M, with a background in Physics. After 5 years as an ML Engineer, I’d like to shift the direction of my career a bit. (I'm in a European country)
I’m considering looking for a master’s degree that would allow me to work in something related to sustainability, climate, oceans, space, or remote sensing.
I had thought about using my Physics background to pursue a master’s in meteorology/climate. However, I’m concerned that this path might tie me too closely to academia.
As an alternative, I thought about Geospatial Engineering, as it seems to be a more competitive field in the job market and one that might allow me to work on climate-related topics while still using machine learning/data science.
With this post, I’m looking for some insight into whether this seems like a good decision, or whether it would make more sense to simply apply for jobs in Geospatial Engineering / Geospatial Data Science instead of stopping work to do a full-time master’s.
I’d also be interested in hearing from people working in Geospatial/Climate/Oceans.
Wanted to share a study that just came out in The Forestry Chronicle where UgCS (drone flight planning software) was part of the methodology.
Researchers from BC Ministry of Forests used a Mavic 2 Pro with UgCS terrain following to fly 30 one-hectare plots across the Lakes Timber Supply Area. The aim was to estimate current timber volumes in managed lodgepole pine stands, 24 years after initial establishment, and compare them to growth model predictions.
The terrain following was the critical piece. These are rolling interior BC sites, and they needed consistent 1.0-1.5 cm GSD across every plot for the canopy height models to work. UgCS adjusted flight altitude continuously using DEM data so the camera stayed at a constant height above ground. About 200 images per hectare, processed in Agisoft Metashape.
Results: 0.92 correlation between the UAV-derived volume estimates and hand-measured ground verification plots. That's from a $1,500 consumer drone with proper flight planning, not a $50k LiDAR rig.
The forestry findings were sobering too. Only 56% of lodgepole pine were still healthy (down from 74% in 1997), and BC's standard growth models only matched reality when they plugged in updated site productivity and disease mortality numbers. The original model inputs were way off.
Full case study with specs and methodology: https://www.sphengineering.com/news/ugcs-terrain-following-uav-forest-inventory-british-columbia
Citation: Woods, A., McCulloch, L., Watts, M. and Di Lucca, M. (2026). Bridging the gap between forecast growth and realized loss in managed forests. The Forestry Chronicle, 102(1): 44-58.
Okay so context: I've been using QGIS for years. Love it, respect it, it's free, I get it. But every time I open it I feel like I'm defusing a bomb. Half my onboarding time with new interns is just "no, not that panel, the other panel, yes the one hiding behind that one."
Last week someone in a Discord I'm in linked a Windows app called TerraGIS and I clicked it half-expecting another bloated enterprise GIS tool with a 45-day trial and a sales call to unlock the export button.
It's... not that.
It's a clean, modern desktop GIS built specifically for Windows and the UI actually looks like it was designed after 2012. I ran it through some of my usual stuff:
The thing that got me was the TerraAI feature it does smart boundary extraction and segmentation from raster data. I've been doing that manually for longer than I want to admit. It's not magic but it's genuinely useful.
It also supports Shapefile, GeoJSON, GeoPackage, GeoTIFF the usual suspects. Nothing exotic, just solid.
The kicker? It's a one-time purchase. Not a subscription. Not "free tier with 3 exports a month." One time. And it's on the Microsoft Store so install/update is painless.
I'm not saying ditch QGIS. I'm just saying if you've ever handed a QGIS project to someone non-technical and watched their soul leave their body, this might be worth a look.
Website's TerraGIS if you want to poke around before committing.
Has anyone else used this? Curious if others have pushed it harder than I have specifically wondering how it handles larger vector datasets.
Hello all!
My organization has tasked me with finding and suggesting up to 5 geospatial conferences for 2027 (will probably actually send people to 2 maybe 3).
I'm looking for quality professional conferences on the topics of GIS, Geospatial, Remote senseing, GeoAI and drone mapping. The conference can be anywhere world wide. (We already know about ESRI).
Anyone have any suggestions? Again this is for next year 2027.
thanks
Hey,
I’m working on a remote sensing project using a fine-tuned YOLO model for object detection.
Right now I’m using Mapbox for satellite imagery, but I’m running into issues:
I’m looking for better alternatives (free or reasonably priced) with:
I’ve looked at things like Sentinel Hub / Google Earth Engine / OpenAerialMap, but I’d love to hear what people here actually use in practice.
Any recommendations or setups that worked well for YOLO or remote sensing pipelines?
Thanks!
Been working on an open-source geospatial ETL prototype called Dymium focused on standardizing fragmented geological datasets into ML-ready GeoParquet outputs.
Current pipeline handles:
My main motivation was seeing how much mineral/geological data is still trapped across inconsistent schemas, PDFs, shapefiles, and legacy formats.
Still very early-stage and intentionally scoped around the data-standardization layer rather than full modeling. README includes current limitations, uncertainty handling examples, and demo outputs.
I need feedback from GIS/geospatial/data engineering people — especially around:
Hi everyone,
I’m looking for a PhD position in geoinformatics or remote sensing, based in Europe (EU citizen). My recent research interests include SAR/InSAR for critical infrastructure monitoring (railways, pipelines, energy grids), super-resolution techniques, and real-time drone imagery processing — strong focus on dual use.
What matters most to me in a supervisor is someone who is present, accessible, and genuinely supportive of a student who wants to learn — a decent person and an expert. A friend who works in academia recently told me something that stuck: with a good supervisor, the PhD flows naturally; with someone who is absent or difficult to work with, you’ll struggle and drag it out for years.
About me: I’m 27, a data engineering team lead at a company working with ESA on the Copernicus programme. I hold an MSc in Geodesy & Cartography (GIS specialisation) from Warsaw University of Technology and a postgrad in Big Data / ML. Day to day I work with Sentinel data and have some experience with VHRs. I build processing pipelines around GDAL, maintain STAC catalogues, and create user-facing APIs and QGIS plugins — all in a cloud-native environment I use daily. I code in Python, use k8s and nix, and I’m eager to pick up Rust or Go. I’ve presented at FOSS4G, ESA Living Planet Symposium, EGU and IAC, and I teach EO courses at AGH Kraków.
If you know of any open positions or could recommend a supervisor, I’d really appreciate it. Thanks!
Hello,
I have a BA in Environmental Studies and a certificate in Spacial Data Science, and I am currently employed in a remote sensing lab at my Alma Mater as a researcher. I am specialized in machine-learning, deep learning, and end-to-end model development in remote sensing—I also had a remote sensing fellowship during my education. I have a publication for review as a primary author as well as a secondary author for a publication in progress. Although I only have a BA I consider myself to have the qualifications of a Masters student given that I took the entire masters curriculum during my time as an undergrad.
I am looking to branch out of academic research and get a position in this field. For those of you who have found employment in the field, do you think that given my credentials, (especially the fact that I only have a BA), is finding a career realistic for me, or is getting a MA the way to go; and if so, what industries tend to hire remote sensing positions? I haven’t seen too many positions and haven’t heard back from any that I applied to. Any help or guidance is appreciated.
