Investors, traders, and risk teams need to verify commodity flows, industrial activity, and portfolio exposure faster than quarterly filings or customs records can confirm them, especially across assets and countries no analyst can visit in person.
Satellite data observes the same commodity terminals, factories, and physical assets on a repeating schedule, turning a market’s actual activity into an independent, verifiable record instead of a company’s self-reported numbers.
This guide breaks down how satellite data supports trading, investment, and risk workflows, which data types each task requires, and helps you find the right data and provider for your finance program.
Table of Contents
Key takeaways
- Satellite data turns commodity flows and industrial activity into independent, market-wide signals
- Verifying corporate disclosures against satellite evidence carries the most weight for investors
- The shortlist narrows fast once you know whether you need a trade-flow feed or portfolio-level climate risk
Before any provider enters the picture, a finance program has to settle what it needs from the data itself. The summary below sets out the sensors, resolution, and cadence that most trading and investment workflows depend on.
| Primary sensors | Optical, SAR, and satellite AIS |
|---|---|
| Working resolution | 3-30 m across optical and SAR |
| Typical revisit | Near-daily to weekly |
| Core indices | Tank fill, vessel position, CH4 gap |
| Entry cost | Free open data, or from $2,700 per year |
| Main constraint | Crowded signals lose their pricing edge |
Those figures cover the baseline that most finance programs run on. Programs that depart from it, through portfolio-level climate risk, corporate verification, or macro activity indices, change both the sensor mix and the cost.
How satellite data is used in finance
Satellite data enters finance workflows at five distinct points, each relying on a different sensor type and delivering different decision support to traders, portfolio managers, and risk teams.
Commodity inventories and extraction activity
Crude oil and refined product inventories move markets days before an official report catches up, which is why several analytics platforms track physical storage directly from orbit. Kayrros runs its Crude Oil Intelligence product over more than 12,000 crude oil storage tanks worldwide, and reports an 82 percent correlation between its tank readings and Brent prices, with a lead time of one to three weeks over official data.
Ursa Space approaches the same problem through radar rather than a visible-light camera, running a weekly Global Oil Storage product that measures floating-roof tank fill whether or not the sky is clear. The same aggregator applies the technique to solid commodities too, publishing a fresh weekly volume for iron ore stockpiles at ports through its Stockpile Measurement API. The method has a hard limit that is easy to miss: it reads the height of a floating roof, so tanks with fixed roofs, LNG among them, stay opaque from orbit.
Trade and freight flows as a leading indicator
Vessel movements are a leading indicator for trade volumes long before a customs filing or a shipping invoice appears, which is why several trading desks watch the water itself. Kpler fuses signals from more than 661,000 vessels tracked daily across a combined terrestrial and satellite AIS network of over 13,000 receivers, turning raw position reports into cargo and refinery-throughput signals.
Kpler checks its own commodity forecasts before a trading desk has to, backtesting them against official benchmarks including JODI and the EIA rather than asking a desk to take a proprietary model on faith.
Industrial and retail activity indicators
National statistics on industrial output can lag by weeks and are not always independently verifiable, a gap SpaceKnow built its business on. Its China Satellite Manufacturing Index publishes three times a week, positioned by the company as a faster, independent alternative to the official manufacturing PMI, and its GEMSTONE program extends the same approach to coal, iron, lithium, and other commodity-linked indices.
Planet lists commodity monitoring and supply-chain intelligence among its own finance use cases, built on the same near-daily, 3 m PlanetScope archive it sells into agriculture and defense. Its Analytic Feeds apply machine-learning object and change detection across that archive, letting a research team turn repeated imagery of a single facility or region into a quantifiable activity signal instead of a one-off snapshot.
Physical climate risk in investment portfolios
A wildfire, a flood, or a drought does not check an asset’s ownership structure before it hits, which is why insurers and asset managers increasingly want site-level hazard data rather than a regional average. Kayrros runs a Wildfire Risk Monitor built for investors, insurers, and firefighting agencies, drawing on the same source-agnostic satellite archive it applies to crude oil and methane.
That same logic extends beyond fire risk. Kayrros launched a Nature Impact Platform in March 2026, giving financial institutions biodiversity intelligence tied to specific holdings rather than a sector-wide estimate, with BNP Paribas named as an early user.
Verifying corporate disclosures
Self-reported figures are only as good as the incentive to report them accurately, and methane is the clearest example on record. Kayrros finds that satellite-measured methane typically runs two to ten times larger than what companies report themselves, a gap its Methane Emissions Disclosure product packages for financial institutions assessing financed emissions. A version of the same Methane Watch data is also available at no cost through the company’s own open data portal.
Physical claims are easier to check than financial ones once a satellite is watching the site continuously. Vantor’s Sentry product runs continuous change detection across hundreds of locations at once, the kind of standing evidence an analyst can use to confirm whether a stated plant expansion or construction timeline actually matches what is happening on the ground. The disclosure side of the same measurement is covered in our guide to satellite data for sustainability.
What satellite data you need for finance
Different finance tasks call for different sensor modalities, resolutions, and revisit cadence, and mixing them up wastes budget on the wrong spec. The table below maps each common task to the data requirements it actually demands.
| Task | Sensor modality | Resolution | Revisit | Key index / band |
|---|---|---|---|---|
| Floating-roof tank fill monitoring | SAR | 1-10 m | Weekly | Roof height from radar geometry |
| Dry bulk stockpile measurement | SAR or optical (volume from shape) | 1-10 m | Weekly | Volumetric stockpile change |
| Vessel position and trade-flow tracking | Satellite and terrestrial AIS | Exact position report | Continuous | Vessel position, port calls |
| Industrial and manufacturing activity index | Multispectral optical | 3-30 m | 3x weekly to near-daily | Site-level activity index |
| Physical climate hazard mapping | Optical and thermal | 10-30 m | Daily to weekly | Burn scar, hazard index |
| Corporate methane emissions verification | SWIR / hyperspectral | 25-30 m | Daily to weekly | CH4 concentration |
| Facility and site-level change detection | Very high-resolution optical | 0.3-0.5 m | Per tasking | Change detection |
With the data requirements mapped, the next step is finding which providers can supply them. The section below covers the analytics platforms and satellite operators most relevant to finance programs, from crude oil inventories to portfolio-level risk.
Satellite data providers for finance
The providers below have documented finance use cases and data products that map to the tasks in the table above. The mix leans toward analytics platforms and data aggregators rather than imagery operators, since a fused signal usually matters more to a trading desk than a single picture.
| Provider | Type | Best for | Key finance spec | Entry point |
|---|---|---|---|---|
| Kpler | Data aggregator | Commodity trading signals | 661,000+ vessels tracked daily | Demo request |
| Kayrros | Analytics platform | Crude oil inventory forecasting | 82% correlation with Brent price | Demo request |
| Ursa Space | SAR analytics aggregator | Cloud-penetrating storage data | Weekly SAR tank fill measurement | Contact for pricing |
| SpaceKnow | Analytics platform | China manufacturing activity index | China SMI published 3x weekly | Contact sales |
| Planet | Satellite operator | Near-daily commodity monitoring | PlanetScope 3 m, near-daily | Imagery from $2,700 per year |
| Vantor | Optical satellite operator | Persistent site-level tracking | Sentry: hundreds of sites at once | Quote or UP42 marketplace |
For a ranked shortlist of the underlying imagery market these platforms draw from, our guide to the best satellite imagery providers covers the operators and resolution tiers behind the analytics layer above.
How to choose satellite data for finance
The first question is not which provider to pick but whether the data changes a decision at all. A single satellite image is not an edge by itself, and whatever advantage a fresh commodity read offers erodes fast once several desks buy the same feed. If a company already reports the same number every quarter, the satellite version is a cross-check, not new information.
Coverage gaps are the second limit, and they tend to open exactly when a position depends on them. Optical sensors cannot see through cloud or darkness, a tanker queue can shift between one clear pass and the next, and a revisit cadence measured in days is too slow for an event that resolves in hours. SAR and AIS-based products close part of that gap, but neither substitutes for the other.
What the position actually needs decides the product. A macro read on industrial activity or trade flow can run on an index or a fused AIS feed, while verifying one company’s specific claim needs imagery or radar pointed at that company’s own sites. Confusing the two wastes budget on a broad subscription when a single tasked image would have answered the question.
Legal use is the fourth constraint, and it depends on jurisdiction rather than on which vendor sold the data. Using satellite-derived signals to inform a trading decision is treated differently across regulatory regimes, and what counts as permissible alternative data in one market can trigger disclosure or insider-trading questions in another. Confirm the rules for your own jurisdiction and asset class before building a strategy around any single feed.
Budget shapes the access model more than it shapes the sensor choice in this market. Every analytics platform in this guide sells through a demo or enterprise contract rather than a published rate card, so the real cost comparison happens after a conversation with sales, not on a pricing page. Planet is the exception, with a published subscription starting at $2,700 a year for teams that need the underlying imagery rather than a packaged signal.
Verdict
Finance is the vertical where a signal usually beats a picture, and where satellite evidence is often used to check a number the market has already priced in. Physical commodity inventories are the most mature use in this pool, covered by both Kayrros and Ursa Space at a weekly cadence with published accuracy or correlation figures.
Trade-flow and industrial-activity signals sit a step further from a single asset, which is why Kpler’s vessel network and SpaceKnow’s manufacturing index exist as standalone products rather than imagery add-ons.
Teams building portfolio-level climate exposure or checking a specific corporate claim turn to Kayrros for risk products or to Vantor’s persistent site monitoring, and Planet’s near-daily archive underwrites all of it with the broadest, cheapest entry point in the group. For a full ranked view of the imagery and analytics market covered here, see our satellite imagery providers guide.
Frequently asked questions
Below are answers to the questions finance buyers most commonly ask. Each answer points to the section where the full detail lives.
How is satellite data used in finance?
Satellite data supports five core workflows: tracking commodity inventories and extraction activity, reading trade and freight flows as a leading indicator, building industrial and retail activity indices, mapping physical climate risk in a portfolio, and verifying a company’s own disclosures. The detail is in “How satellite data is used in finance“.
What satellite data does verifying corporate disclosures require?
Checking a specific company’s claim usually needs imagery or radar pointed at that company’s own sites, not a market-wide index. Methane verification runs on SWIR or hyperspectral sensors at 25 to 30 meters, while confirming a stated construction or expansion timeline needs very high-resolution optical change detection instead. The mapping is in “What satellite data you need for finance“.
Can satellite data predict commodity prices?
Not on its own. Kayrros reports an 82 percent correlation between its crude oil inventory readings and Brent prices with a one-to-three-week lead, which is a strong signal, not a forecast guarantee, and that edge narrows once a reading becomes widely available. The honest limits are discussed in “How to choose satellite data for finance“.
How much does satellite data for finance cost?
Most of the analytics platforms in this space sell through a demo request or an enterprise contract rather than a published price. Planet is the exception, with a subscription starting at $2,700 a year for the underlying imagery archive. Pricing by provider is covered in “Satellite data providers for finance“.
Which satellite data providers are best for finance?
Kayrros covers the widest range, from crude oil inventories to wildfire risk and methane verification, Kpler and SpaceKnow lead on trade-flow and industrial-activity signals, and Ursa Space and Vantor cover storage measurement and site-level verification. Provider details and access models are in “Satellite data providers for finance“.
Does satellite data work as a stand-alone trading signal?
Rarely by itself. It works best as a cross-check against a filing, a shipping record, or another data source, and the edge it offers shrinks once several desks buy the same feed. Legal use also depends on jurisdiction, a factor discussed in “How to choose satellite data for finance“.
My passions are Earth Observation and Satellites, and my profession is Data Analysis. I combine both within ObservationData.com to show you the use cases of Earth Observation, to help you find the right provider, and to share your experiences.
