Iron Ore Series Part 3: How to Measure Stockpiles


Geoffrey Craig, Senior Product Strategist

The size, importance and geographic scale of dry bulk commodities, such as iron ore, copper and cobalt, make satellite-based tracking an ideal solution for monitoring global trends.

Traders and analysts lack access to high-quality data on market fundamentals, particularly for inventories (i.e. stockpiles) from public sources.

This is a pain point because stockpiles are a key market indicator. Stockpiles grow when supply is greater than demand, and vice versa, making information related to their size valuable to physical and financial traders. 

The same situation exists in the crude oil market, a topic with which we are already well-acquainted. Every week we measure inventories at more than 1,100 oil storage locations around the world. 

Ursa Space has now broadened its inventory measuring capabilities to include dry bulk commodities, starting with iron ore, the main input for making steel. 

We developed an algorithm that employs radar satellite imagery to volumetrically measure dry bulk commodity stockpiles. 

Radar imagery boasts numerous advantages over optical imaging – such as seeing through cloud cover, or dark of night, and tracking minute topographical changes over a broad area.

Our technique utilizes radar images captured from diverse viewing angles to create a 3D reconstruction of a given scene.

The graphic below shows an example of a 3D reconstruction taken of an iron ore stockpile in Serra Norte, Brazil.

Serra Norte, Brazil

Accuracy Validation

To test the accuracy of the algorithm, we looked for a location with trusted height data to compare our measurements against. 

The site selected was Chimney Bluffs on the southern shore of Lake Ontario.

Chimney Bluffs features unique geological features — large clay formations that rise up to 150 feet and resemble the shape of iron ore stockpiles. 

Moreover, data on Chimney Bluffs was available from the US Geological Survey (USGC). 

USGC published a Digital Elevation Model (DEM) derived from LiDAR technology collected over Chimney Bluffs in November 2022. 

Chimney Bluffs, New York

3D simulation of Chimney Bluffs based on USGS LiDAR data

We compared our height estimates with the corresponding USGS values for six specific locations at Chimney Bluffs that account for the full range of elevation changes within the formation. 

After the successful validation of our algorithm’s accuracy, we turned our sights to selecting stockpile locations of strategic significance to the iron ore market. 

In earlier articles, we discussed the names of  the top exporters and importers, along with the key ports in each of those countries where iron ore is stockpiled.

From this list, we selected certain locations to regularly collect radar imagery over and measure stockpile volumes.

The resulting dataset is the topic of the next installment in this series, highlighted by an exciting product launch announcement.

If you’re interested in stockpile measurements now and want to chat right away, you don’t have to wait until the formal announcement. Fill out the form below and we’ll be in touch. 

Other articles in this series:




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