Login

r/remotesensing

▲ 16 r/remotesensing

I am going to start a new job with Planets satellite, how can I prepare myself to not be overwhelmed?

 Hello all

I will start a new post doc in September during which I will have to work with Planets images.

The lab I will working with used to study coastline resilience from orthophotography and they would like now to see if its applicable to Planets imagery. The idea will be to use coastline extraction algorithms.

I never worked with Planets but I used to work a bit with Sentinel-3 for vegetation (algae) detection and simple observation of coastline from orthophotos using QGis. Do you have any recommendation to help me to be prepared to start my new job? Do you know if I could practice somehow with another type of freely-accessible images so I do not get overwhelmed on day-1 ?

Thank you 😊

reddit.com
u/Skua60 — 1 day ago
▲ 34 r/remotesensing

We’re building AI for humanitarian demining in Ukraine. Here’s what you’ll find here.

A single drone survey can generate thousands of high-resolution images. Add thermal cameras, magnetometers, ground-penetrating radar (GPR), satellite imagery, and GIS layers, and suddenly you’re dealing with gigabytes of data describing one territory.

For us, the hardest part is no longer collecting data. It’s processing, combining, and interpreting it in a way that is actually useful for people working in the field.

We’re the team behind UADAMAGE, a Ukrainian company developing AI and geospatial tools for humanitarian demining and territorial analysis.

Our goal is not to replace demining specialists or make safety decisions automatically. We use AI to reduce manual work, improve situational awareness, build risk maps, and help experts focus on areas that may require closer investigation.

Here we’ll share the technical and practical side of what we’re building, including:

  • UAV mapping and remote sensing
  • thermal, multispectral, magnetic, and GPR data
  • sensor fusion and GIS workflows
  • AI-assisted image analysis and anomaly detection
  • field-testing approaches and geospatial processing pipelines
  • lessons learned while developing technology for humanitarian demining in Ukraine

Our first posts will focus on how different sensors observe the same territory differently, and why combining those perspectives is often more valuable than relying on a single dataset.

If you’re interested in AI, GIS, drones, remote sensing, robotics, or humanitarian technology, we’re glad you’re here.

— UADAMAGE Team

u/UADAMAGE — 2 days ago
▲ 61 r/remotesensing+4 crossposts

New tutorial on the plugin AI segmentation in QGIS just dropped (:

You will learn how to detect and vectorize any feature from satellite or drone imagery directly inside QGIS

  • It covers : Automatic Mode: Scan an entire area with text prompts to batch-extract features in seconds
  • Semi-Auto Mode: Extract single, complex objects with one click for maximum control
  • Shape Regularization: Automatically square building corners and clean up polygon boundaries
  • And basically just the full Workflow: Edit vertices, adjust confidence filters, and export clean layers with attribute data

We pushed a lots of updates recently so a tuto was definitely needed haha, hope it will help

youtu.be
u/Glass-Caterpillar-70 — 4 days ago
▲ 14 r/remotesensing+1 crossposts

TERRA release v3 Ember

00:00 TERRA for Explorers
00:46 TERRA Studio

I've been building an open source desktop app for classifying land cover over a specific area from Sentinel-2 time series.

You draw an area on a map, set a date range, and classify. Imagery is read on demand from the Planetary Computer STAC catalog as COGs. There's a Random Forest path, a temporal transformer, and Prithvi-EO 2.0 embeddings.

It reports where the classification is wrong, not only how much of it is right. Agreement with the reference map is broken down per class and across spatial blocks, so you can tell whether the disagreement sits in one corner of the area or throughout it. Throughout usually means the model is being asked about ground it never learned, and there's a diagnosis between two runs that measures that distance.

There's also a canopy simulation that grows the classified crop in 3D and lights it with the hourly sun for that location.

Why Sentinel-2 and not something else: it's what the method here was built and validated on, it's open at 10 m with a roughly five day revisit, and it carries the red edge and SWIR bands the indices depend on. The obvious weakness is cloud, and in Brazil the cloudiest months sit right on top of the crop cycle. That's why SAR is where I want to go next, with other sources after it.

What it isn't: a QGIS or Earth Engine replacement. It targets farm to landscape scale areas under a fixed protocol. The classifiers emit five land cover classes and were fitted for study areas in western Paraná, so an area in another biome can come back confident and semantically wrong. I'm aware of that and working on it; for now the domain-shift diagnosis exists so the problem is visible instead of silent. Agreement with the reference is concordance with an annual map, not field truth.

On AI: my background is machine learning and remote sensing, not full stack development, so I used AI coding assistants for much of this. The frontend is where that shows most, and where bugs are most likely. The Python sidecar, where the research methods actually land, and the Go backend are written and reviewed by me continuously.

https://github.com/rexionmars/TERRA

u/Beginning-Claim5655 — 3 days ago
▲ 0 r/remotesensing+2 crossposts

(Urgent) Downscaling help needed

I'm in a crunch. I am working on a research project involving climate change related projections. I have downloaded GCM data (single variable: precipitation) from CDS, now the data (how GCM data is) has very coarse resolution, I need to downscale the data into higher resolution of 1×1 Km to run a model I have developed. I have data from 5 different models from 4 different SSPs. I am trying to downscaling it using different methods I could but cannot get it right and it's been 3 weeks. I don't have enough time, I need help.

reddit.com
u/matterhorn276 — 5 days ago
▲ 4 r/remotesensing

Geoint tools

Hi guys, I'm new to GEOINT and would like advice on which websites/platforms you use to analyse satellite imagery with a decent resolution \~5m. I've tried several but the resolution wasn't great.

If you have as well any recommendations for which tools I should/could use for better results I'd love to hear your advice!

Thanks for your help! 🙏

reddit.com
u/Affectionate-Ad144 — 5 days ago
▲ 21 r/remotesensing

looking to get into Remote Sensing — what areas are still underexplored?

I’m a sophomore majoring in AI & Data Science, and I’m interested in getting into the remote sensing field.

I’ve started working on some basic deep learning projects, mainly image classification and before/after change detection. However, I’m struggling to figure out what problems are actually worth working on.

Are there any areas in remote sensing that are still relatively underexplored, have significant limitations, or haven’t seen much advancement yet?

Also, from the perspective of a deep learning engineer, what areas of remote sensing would be worth learning and exploring? I’m particularly interested in problems where I can apply DL rather than just using existing models.

I’d appreciate any suggestions for interesting problems, research directions, datasets, or projects that could help me explore the field seriously.

reddit.com
u/MentalFig6149 — 10 days ago
▲ 10 r/remotesensing

Defense industry

I have seen lots of job openings within the defense industry involving remote sensing. I feel like a lot of the work sounds really cool so I’m wondering if any people who have worked in defense have advice/ cautions/ suggestions about their work experiences?
- I would also be interested in your background/ what you studied / how you ended up working where you did

reddit.com
u/Intrepid_Extreme9773 — 9 days ago
▲ 6 r/remotesensing

New to Remote sensing how to use Spectral library to identify crops

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!

reddit.com
u/Izzyball11 — 10 days ago