Google Earth Engine for Mineral Exploration: Free Tools Most Geologists Don't Use

Last month I was sitting with a senior geologist from a Lahore-based exploration firm. Smart guy. 23 years in the field, mapped half of Chagai. He asked me what software we use at GeoMine AI for our preliminary alteration mapping.

I said Google Earth Engine.

He blinked. "The Google Maps thing?"

No. Not the Google Maps thing.

And honestly, that conversation is why I'm writing this. Because if a geologist with two decades of field experience doesn't know what GEE is, then 90% of the working geologists in Pakistan are leaving free tools on the table — tools that would've cost $40,000 in licensed software fifteen years ago.

What Google Earth Engine Actually Is

Google Earth Engine (GEE) is a cloud platform that hosts petabytes of satellite imagery — Sentinel-2, Landsat 4 through 9, ASTER, MODIS, SRTM elevation, SAR data from Sentinel-1 — and lets you run analysis on Google's servers using JavaScript or Python. You don't download anything. You don't need a workstation with 64GB RAM. You write a script, hit run, and Google's data centers do the math.

For non-commercial research and government use, it's free. For commercial work there's now a paid tier, but most exploration-stage analysis fits inside the free quota if you're careful.

Here's what that means in practical terms. A geologist sitting in Quetta with a laptop and decent internet can pull every cloud-free Sentinel-2 scene over the Ras Koh range from 2015 to today, run a band ratio for iron oxide alteration, and have a target map by lunch. The same workflow on ENVI with locally downloaded data would take two weeks and a dedicated machine.

The Tools Most Geologists Skip

Look, the problem isn't that GEE exists. The problem is that most geology curriculums in Pakistan still teach remote sensing the way it was taught in 2003 — with ERDAS Imagine, single-scene downloads, and manual band stacking. Nobody's showing students the cloud-native workflow.

A few things in GEE that almost nobody in our industry uses:

Sentinel-2 cloud-masked composites. You can median-stack 60 scenes over a target area and basically erase clouds, haze, and seasonal vegetation noise. For a place like Azad Kashmir where cloud cover ruins single-scene analysis 8 months a year, this is the difference between useful imagery and garbage.

ASTER Global Emissivity Dataset. Free. Hosted. Five thermal infrared bands that are gold for mapping silica content, carbonates, and clay minerals. ASTER stopped collecting SWIR data in 2008 (the detector died), but the archive is still the best free hyperspectral-adjacent data we have for argillic and phyllic alteration zones. I used this last year for a quick scan over a property near Chilas — flagged a 2.3 km zone of probable sericite alteration that the owner had no idea was there.

SAR coherence change detection. Sentinel-1 radar penetrates clouds and works at night. By comparing two SAR images of the same area, you can detect ground disturbance — illegal mining, new road cuts, landslides over a fault. For monitoring lease boundaries in Gilgit Baltistan, where I own 15 mines and can't physically visit them in winter, this is the only tool that actually works.

SRTM and ALOS DEM derivatives. Slope, aspect, curvature, drainage extraction, lineament density. Run a focal statistics filter on a 30m DEM and you start seeing structural controls that aren't obvious on a topo map. Most porphyry systems in Pakistan sit on intersections of regional lineaments. You can map those for free.

A Real Workflow for Pakistani Exploration

Let me walk through how we actually use this at geomines. Say a client comes to us with a 15 sq km lease in Khuzdar and wants to know if there's copper potential before they spend on ground crews.

Step one. Pull all Sentinel-2 Level-2A scenes from 2019 onward, filter for less than 10% cloud cover, median composite. That's maybe 80 scenes reduced to one clean image.

Step two. Run the standard alteration ratios. Band 11/Band 12 for clay minerals. Band 4/Band 2 for iron oxides. Band 11/Band 8 for ferrous iron. Threshold the outputs and you've got three alteration maps in about 40 minutes of scripting.

Step three. Pull ASTER scenes from the 2000-2008 archive when SWIR was still alive. Run the Ninomiya indices for OH-bearing minerals and carbonates. Overlay on Sentinel-2 results. Where they agree, your confidence is much higher.

Step four. Pull SRTM, extract lineaments using a Sobel filter, density-map them. Cross-reference with alteration anomalies. Targets that sit on lineament intersections AND show multi-sensor alteration signal — those are your drill candidates. Or at least your ground-truth-this-first candidates.

The whole thing runs in maybe 6 hours of analyst time. The same workflow with downloaded data and desktop GIS would take a junior geologist two to three weeks.

This is the part that frustrates me. The data has been free since 2015. The platform's been free since 2010. And we're still hiring teams of three to do what one trained person with GEE can do in an afternoon.

Where GEE Falls Short (Being Honest)

I used to think GEE could replace everything. Then I tried to run a serious mineral prospectivity model on it and hit the wall.

It's not built for heavy machine learning. The classifiers (CART, Random Forest, SVM) are fine for basic supervised classification, but if you want to run a proper convolutional neural network on multi-temporal stacks, you'll fight the platform. That's why our actual production pipeline at GeoMine AI uses GEE for data ingestion and preprocessing, then exports tiles to our own GPU infrastructure for the AI layer.

Also, the JavaScript API has quirks that'll make you want to throw your laptop. Memory limits hit you at strange moments. The Python API (via geemap) is better but still has quota issues for large area work.

And the free commercial use ended in 2023. If you're a private mining company now, you need a paid Earth Engine license or an academic partnership. Most small exploration firms in Pakistan don't realize this and are technically out of compliance.

Still — for a junior exploration company, a university lab, or a provincial mineral department trying to do reconnaissance over thousands of square kilometers without a satellite imagery budget, there's nothing else that comes close. The Sindh and Balochistan mineral development authorities should have GEE-trained staff in every regional office. They don't. That's a missed opportunity worth hundreds of millions of rupees in better-targeted licensing rounds.

If you're a working geologist in Pakistan and you haven't opened code.earthengine.google.com yet, what are you waiting for?