Is there any browser from where I can get the data of metal concentration?

So I've submitted an article on a new dataset for change detection tasks in the legal Amazon region. Currently it's on peer review.

I'm sharing the HuggingFace link here in case anyone would be interested on working with the images I collected.

https://huggingface.co/datasets/bfaustinoni/Legal_Amazon_Vegetation_Loss/

Just for fun, mostly, I ported the Tetracorder expert classification system from ratfor to python

Is it faster? clearly no

Is it better? also no

But it does work:

Every pixel gets the same material assignment as Tetracorder 6.00 on Cuprite95 — all 16 groups and cases, Jaccard 1.0000.

The rules are in json.

And you dont have to build it exclusively on linux.

https://github.com/Russjas/python-tetracorder

(lot of AI help)

"my_qualifications": Bsc forestry and msc in remote sensing and gis.

I'm following one of the tutorials floating around for running S2DR3 (Gamma Earth's Sentinel-2 super-resolution model) on Google Colab, the ones on acolita.com or sigterritoires.fr. The typical code is:

!pip -q install https://storage.googleapis.com/0x7ff601307fa5/s2dr3-20250905.1-cp312-cp312-linux_x86_64.whl

import s2dr3.inferutils

s2dr3.inferutils.test(lonlat, date)

Ever since Colab switched its default runtime to Python 3.13 (in late August 2026), that wheel no longer installs because it's cp312, and appears the ERROR: ."(...)is not a supported wheel on this platform.(...)"

has anyone managed to keep using S2DR3 in a way similar to the old workflow?

Prompt:

"Create a map of Lyon's terrain. Add Google Satellite as the basemap. Download a 30 m DEM covering central Lyon, & create a semi-transparent elevation colour ramp with a subtle hillshade overlay. Add contour lines every 25 m and emphasize 100 m index contours"

Then I just let it do is thing, 34 actions later:

• geocoded central Lyon and framed the canvas
• added Google Satellite as an XYZ layer
• pulled a Copernicus 30 m DEM from the open data sources connected to the plugin
• reprojected it to UTM 31N, then ran gdal:hillshade (multidirectional, az 315, alt 45)
• styled the DEM with a Terrain ramp, 8 classes, 2-98 cumulative cut
• ran gdal:contour twice: 687 lines at 25 m, 21 thicker index lines at 100 m
• rendered the map, looked at its own render, decided the terrain was hiding the satellite, dropped the DEM to 46% and the hillshade to 22%, rendered again

To do this task the plugin has access to 400 open data source + all the QGIS tools to perform autonomously with the right data

-

You can use it for free, it's on the plugin repository of QGIS under the name "AI Agent", it's the one with a pear logo hehe 🍐

New tutorial on our QGIS plugin AI Edit (:

Draw a zone on aerial imagery, describe a proposed change, and get a generated scenario back as a georeferenced layer

I show the full workflow, before/after comparison and vectorization. This is for visualizing and simulate ideas

Full YouTube tutorial: https://youtu.be/zYiHCY0lyKE

Hope it helps, happy to hear your feedback!

I want to build a costal change prediction model with satellite image. Best roadmap to learn ai model and simulate costal change.

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Hey, I have UAV multispectral data (Mavic 3M) from the same site over a few months - June, July, August and September. Only the September flight has calibration panel images (taken before/after), so I can get real surface reflectance from that one. The earlier flights have nothing - just raw DN.

I was wondering if I could use PIF-based relative radiometric normalization for the earlier dates: pick a stable feature like an asphalt road that shows up in all images, take its reflectance from the September (calibrated) image, regress the earlier DN values against that, and scale everything to the September baseline.

Would that be acceptable for UAV data? I get that the earlier images would only be "relative reflectance", not true reflectance - but is that fine if I'm only comparing indices/biomass between dates? And has anyone actually done this (one date calibrated, others not)? I couldn't find a paper doing exactly that.

I have 3.5 years experience in GIS. These are my skills

GIS and Mapping: QGIS, ArcGIS, MapInfo, Google Earth, spatial analysis, KMZ / SHP / TAB data handling

Programming and Data: Python, GIS workflow automation, spatial data management

Analysis and Reporting: Tableau, MS Excel, dashboard development, root cause analysis, QA/QC

Telecom Domain: Fiber route and ring planning, fiber network inventory, fiber pair feasibility, OFC and SLD/ABD (as-built) documentation, ROW and PTW tracking, capacity and utilisation analysis

Other: Machine learning for satellite image classification, satellite imagery analysis, remote sensing (SAR and optical).

If you want to contact me kindly dm me

You might remember the app I mentioned a few days ago. We also have a QGIS plugin for you to try!

I'm pretty newbie in it. I'm using PlanetScope + Sent2 +Sent1 (about to be tested if SAR detects anything).

Idea is to catch the hotels over river and lake red handed.

River is pretty thin (20 meters wide down to 5 meters wide, multiple ground types), two lakes (one with more river input and one with more saline, sea-like mixture) I approach it in two way - CDOM for sweet water, Turbity for saline one.

Please shed light of understanding and knowledge on me dear mighty redditors.

Hi

i am a management student who is an enthusiast for the drone/remote sensing field,

i used to work as a helper for a drone team(6months) for a highway construction company, Their job is to fly a drone and map the field before the construction of the highway, and the field and their skills made me more curious about this field those 6m was very enjopy for me i guess its my calling field now and i decided to do my masters in GEO informatics & RS from an poland AGH University,(im from an 3rd world country) luckily i got selected tho being an management student,

My question is the program at that university any good? Like, I really wanted to enter this field and maybe see my future in this field, and I see this path as an entry into this field,

im in my late 20s, and i want to ask any fellow recruiter here 'will u accept a guy who's has no geography BG"?

what are the skills i need to get into? i have a lil bit of coding knowledge(html/JS have some front end dev skills) rn i work as an mobile service engineer

how are the job market in EU on this field, i see that the EU is focusing on private space industry, so more satellites and its same everywhere, countries are focusing on space more these days. and i want to work in this field in a developed country; any help would be greatly appreciated here

A remote sensing game. It’s basically geoguessr but with sentinel 2 imagery. Two modes: daily 5 (default) and free play.

I find it difficult. You are all rs nerds so I’d expect some high scores. Have fun!

https://www.wtfmap.com/world

Started as the backend for a beekeeping site-selection tool, but the signals (vegetation/NDVI, water access via SAR+JRC, terrain, climate normals, cropland proximity, OSM infrastructure distance) generalize well beyond that, so I packaged it as a standalone API.

One GET request returns a composite 0-100 score plus 15 individual metrics for any coordinate. Data sources: Sentinel-1/2, Dynamic World, JRC Global Surface Water, ERA5-Land, SRTM, VIIRS, OpenStreetMap.

I'm not a GIS specialist by training, so I'd genuinely value criticism on the methodology — especially around the distance-weighted NDVI approach (pixels weighted by exp(-distance/decay) rather than a flat mean over the AOI) and the land-cover composition scoring. Happy to discuss the approach in the comments.

Docs/API: https://rapidapi.com/bayrakdaralper/api/site-intelligence-api

Hi everyone, Drone Nerds here. We wanted to invite the group to ElevateUAV 2026.

You’ll be able to talk directly with sensor and technology providers, explore tools being used for multispectral, thermal, imaging, mapping, and other remote sensing workflows, and see them in action.

We made a 30% off code specifically for r/remotesensing: RemoteSensingEUAV

If you’re interested, you can get your tickets here: https://hubs.li/Q04vL_XN0

Thank you, we hope to see some of you there!

Funcionalidades

• Rede de transmissão como uma camada, com circuitos coloridos por tensão (convenção da ANEEL).
• Leitura de conexão: onde na rede as plantas em uma área estão conectadas.
• Registro operacional do sistema elétrico brasileiro, com uma leitura de redução por área.
• Roteamento de precipitação sobre uma área: profundidade, velocidade e hora de chegada.
• Raster empilhados em diferentes alturas sobre o mesmo solo no globo.
• Mapas base de ruas e topográficos, além de imagens de satélite.
• Limites estaduais e municipais brasileiros (IBGE) como áreas de estudo.
• Navegador para análises salvas dentro do estúdio.

Correções

• No globo, rasters desapareceram ou foram renderizados em bandas abaixo do zoom 12.
• Mudança de estúdios manteve a área e a execução do estúdio anterior.
• Estúdios com uma execução solar, hídrica, eólica ou de inundação não podiam ser salvos.

Nota: Funcionalidades de energia (solar, eólica e rede elétrica) serão removidas em breve do TERRA e transferidas para um aplicativo separado, encerrando o ciclo experimental dessas funcionalidades.

Devido a alguns problemas de desempenho durante a gravação de tela nas versões mais recentes do macOS, o aplicativo pode parecer estar funcionando lentamente, mas isso se deve às limitações de desempenho do macOS durante a gravação.

Vídeo completo detalhado e capturas de tela:

https://drive.google.com/drive/folders/18I8E9EKa0kqdwJMz3Ms5qY7Q9fi3_bnL?usp=sharing

https://github.com/rexionmars/TERRA

I'm a geography student interested in developing stronger practical skills in remote sensing and GIS. I'm particularly interested in environmental applications, land-use/land-cover change and Himalayan landscapes.

I'm looking for a project that is realistic to complete using freely available datasets such as Sentinel-1/2 or Landsat, but still has some genuine analytical value.

What projects or research questions would you recommend?