Our proprietary analysis of SQM's operations in the Salar de Atacama demonstrated a >95% correlation between our satellite-derived estimates and the company's reported shipment volumes, providing a powerful predictive edge for financial and strategic decision-making.
Lithium is the bedrock of the green energy transition, yet its supply chain is notoriously opaque. On-the-ground production data is often delayed by months, creating significant information asymmetry in the market. For investors, traders, and competitors, this lag represents missed opportunities and unmanaged risk.
Our platform fuses hyperspectral imagery with Synthetic Aperture Radar (SAR) to pierce through the opacity. We transform raw satellite data into actionable commercial intelligence, providing an unparalleled, near-real-time view of mineral production anywhere on the globe.
Sociedad Química y Minera (SQM), a leading global lithium producer, operates a vast network of solar evaporation ponds in Chile's Salar de Atacama. These ponds, spanning over 44 km², are the nexus of their production and a perfect candidate for remote analysis.
By monitoring these ponds, we can quantify the precise stage of lithium concentration and predict output volumes long before they appear in quarterly reports.
We move beyond simple observation to quantitative analysis through a proprietary three-step process.
Standard RGB and NDWI analysis identifies all active brine ponds in the target area.
Our machine learning models analyze hyperspectral data to detect the unique signature of high-concentration lithium brine.
By tracking pond volume and concentration over time, we build a predictive model of future production and shipment volumes.
The chart below shows a direct comparison of our estimates against SQM's reported figures. Our data acts as a powerful leading indicator for the company's performance.
The close alignment demonstrates the accuracy of our methodology. The slight deviation in Q1 2023 was correctly anticipated by our models, which detected reduced pond harvesting activity corresponding to a significant drop in global lithium prices.
This methodology is extensible to other evaporated minerals, including potash and magnesium.
See how iLika Geospatial can provide a custom intelligence solution for your organization.
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