Hyperspectral vs Multispectral: What Actually Works for Pakistani Mining Geology

Someone asked me last week why we don't just buy a hyperspectral dataset for every client project and call it a day. Fair question. The answer is longer than most people want to hear, so I'll give you the short version first: hyperspectral is incredible when you can afford it and the conditions cooperate. Multispectral is what you'll actually use 80% of the time. And the honest mining geologist admits both.

Let me back up.

The difference in plain language

Multispectral sensors capture light in a handful of wide bands. Sentinel-2 gives you 13 bands. Landsat 8 gives you 11. ASTER gives you 14 (and those SWIR bands are genuinely useful for clay and carbonate alteration, which is why we still use a satellite that stopped collecting SWIR data in 2008 — old ASTER scenes are gold for historical baselining).

Hyperspectral is different. Instead of 13 bands, you're looking at 200+ contiguous narrow bands. EO-1 Hyperion had 242. PRISMA, the Italian one, has 239. EnMAP, Germany's, has 224. Each band is razor-thin — maybe 10 nanometers wide — so you're essentially getting a full spectral fingerprint for every pixel on the ground.

Why does that matter? Because minerals have absorption features. Specific dips in specific wavelengths. Kaolinite absorbs at 2.20 micrometers. Alunite absorbs at 2.17. Muscovite sits around 2.20 but with a different shape. On a multispectral sensor those three look basically the same. On a hyperspectral sensor, they're three distinct species — and each one tells you something different about the hydrothermal system underneath.

So yes. Hyperspectral mining workflows can, in theory, map individual alteration minerals. Multispectral remote sensing tells you there's alteration. Hyperspectral tells you what kind.

Why we still run most projects on multispectral

Here's the thing that nobody selling hyperspectral services will tell you upfront.

Coverage. Sentinel-2 revisits every 5 days, free, globally. PRISMA revisits when it revisits — and you have to task it, wait, hope the cloud cover cooperates over Chagai or Kharan, and then pay for processing. For a 2,000 sq km license block in Balochistan, getting complete hyperspectral coverage can take months. Multispectral? I can pull a cloud-free composite this afternoon.

Signal-to-noise. Narrow bands mean less photons per band. Hyperspectral scenes are noisier, and you spend real time on atmospheric correction, denoising, and minimum noise fraction transforms before you even start geology. One of our junior analysts spent 3 days cleaning a single PRISMA scene over Waziristan before it was usable. Sentinel-2 is ready in an hour.

Cost. Commercial hyperspectral tasking from airborne providers runs $15-40 per sq km in Pakistan depending on resolution. A 500 sq km survey lands somewhere around $12,000 just for acquisition. For a mine owner in Gilgit-Baltistan sitting on a 50-hectare claim, that math doesn't work. For a major copper exploration play in Reko Diq territory? Different conversation.

Vegetation and cover. Honestly, this one catches people. Hyperspectral's advantage collapses when the ground is covered in even moderate vegetation or weathering crust. And a lot of Pakistan's mineralized belts aren't the clean bare-rock outcrops you see in Nevada hyperspectral case studies. The Chitral belt has snow half the year. The Hazara region has soil cover. You need SAR and DEM work to even see the structural grain before spectral analysis means anything.

So when do we actually reach for hyperspectral?

Three scenarios, in my experience running GeoMine projects across the country.

First — when a client already has a drilling target and wants to refine it. You've identified a gossan through Sentinel-2 band ratios. Good. Now before you spend $80,000 on a drilling program, throw hyperspectral at that 10 sq km. The alunite-vs-kaolinite distinction can tell you whether you're looking at high-sulfidation epithermal gold (shallow, hot, acidic system) or advanced argillic alteration that's barren. That single discrimination is worth the price.

Second — lithium pegmatites. Spodumene has specific absorption features around 2.2-2.3 micrometers that multispectral bands smear across. We've had much better luck flagging candidate pegmatite fields in the Kohistan region using hyperspectral than ASTER ratios alone.

Third — when you're arguing with an investor or a regulator and need defensible mineralogical evidence. A multispectral anomaly is suggestive. A hyperspectral SAM (spectral angle mapper) classification pointing at specific indicator minerals is something you can put in a report and defend in a meeting.

What we actually do at GeoMine

We treat this as a layered problem, not a binary choice. SRTM DEM for structural geology. SAR for weather-independent surface roughness and structure. Sentinel-2 and ASTER for regional alteration mapping and vegetation-adjusted band ratios. Then, for priority zones — and only priority zones — we fold in PRISMA or EnMAP hyperspectral scenes where the archive has them. Our AI models train on all of it together.

The output isn't a pretty satellite picture. It's a ranked prospectivity map with confidence scores. The client doesn't care whether it came from 13 bands or 239. They care whether the anomaly holds up when they put a drill in the ground.

And I'll admit — I used to be much more evangelical about hyperspectral. Three years in, having watched enough field crews come back from ground-truthing exercises, I've gotten humbler about it. The best tool is the one that answers your specific question at the scale you can afford. For regional reconnaissance across Pakistan's 600,000 sq km of prospective terrain? Multispectral, every day. For that final 5% decision before drilling? That's where the expensive toys earn their keep.

Which one you need depends entirely on what stage you're at. Where are you in your exploration cycle?