Global Port POI and Geometry Data for Improved Supply Chain Analysis

Global trade doesn’t move in a straight line anymore. Shipping routes have shifted, port congestion has become routine, and official trade data often lags months behind what’s actually happening on the ground, especially in emerging markets. Supply chain analysts are left trying to answer basic questions, like which ports are busiest, which are underused, and what’s happening around them, without a reliable source of truth.

This article looks at how port point-of-interest (POI) and geometry data closes that gap. We’ll cover how analysts use accurate port boundaries to measure trade activity, cut the cost of satellite imagery analysis, and evaluate site selection opportunities near global ports.

Why Official Port Data Isn’t Enough Right Now

Global shipping has had a volatile few years, and 2025 didn’t settle things down. According to the UN Trade and Development’s Review of Maritime Transport 2025, global seaborne trade volumes are projected to grow just 0.5 percent for the year, a near stall compared to prior growth rates, even as ships are sailing much farther to avoid risk. Rerouting around the Red Sea pushed 2024 ton-mile growth to nearly 6 percent, one of the highest on record, simply because cargo is traveling longer distances for the same trade volume.

That rerouting has a real cost. Egypt’s Suez Canal revenue dropped roughly 40 percent from its 2023 high of close to 10 billion dollars, as container lines diverted around the Cape of Good Hope. Transshipment hubs like Salalah saw double digit volume declines, while ports that became new first calls for Europe bound cargo, like Barcelona, picked up meaningful volume instead. Multiple 2026 shipping reports note that rerouting is still the default for most carriers, with only cautious, partial returns to the Red Sea route.

Meanwhile, global container port throughput actually grew through this disruption, crossing 1 billion TEU for the first time in 2025, up 8 percent year over year. Smaller ports outside the traditional million-TEU hubs grew even faster, up 21 percent collectively, as trade activity spread beyond the usual chokepoints.

For analysts, this creates a specific problem: the ports that matter most to a given supply chain question are shifting quickly, and official government or port authority data often can’t keep pace, especially outside major trade hubs. That’s the gap port POI and geometry data is built to fill.

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What Is Port POI and Geometry Data?

Port POI data identifies the precise location of maritime ports as individual points on a map. Geometry data goes a step further by defining the actual boundary, or polygon, of each port’s operational footprint rather than just a single coordinate.

SafeGraph’s Geometry dataset currently covers more than 80 million POIs with polygon boundaries across 195+ countries and territories, including ports across nearly every major trade market. Each port record includes a wkt_area_sq_meters field, giving analysts a standardized way to measure and compare port size directly.

Here’s what a single port record looks like in practice:

A single port POI record, complete with location name, city, and ISO country code, before it’s joined to a geometry polygon or other datasets.

Zoomed out, that same structure repeats at global scale:

 SafeGraph maps ports across nearly every country with maritime trade infrastructure, each defined by its actual surface area rather than a single coordinate.

This matters because a port isn’t a dot on a map, it’s a physical space with berths, container yards, storage areas, and access roads. Treating it as a single point loses the spatial context that trade, logistics, and site selection analysis depends on.

Measuring Trade Activity Without Official Port Data

One of the most common reasons analysts turn to port POI data is to build a trade activity proxy where formal reporting doesn’t exist or lags too far behind. This is especially common in emerging markets, where port authorities may publish data quarterly, annually, or not at all.

By intersecting mobility data with port POIs and polygons, analysts can estimate regional trade activity, compare relative port performance, and track change over time, all without waiting on an official release. Pairing that mobility signal with the wkt_area_sq_meters field also lets analysts explore whether port size correlates with import and export volume in a given region, a useful sanity check when validating a new market.

This approach won’t replace customs or port authority data where it’s available and current. But in the markets where that data is sparse, delayed, or simply doesn’t exist, it’s often the only scalable way to build a directional read on trade activity.

Reducing Satellite Imagery Costs with Accurate Port Polygons

Satellite imagery is one of the most common ways analysts track vessel activity at ports over time, counting ships entering and leaving to build an activity index. It works well when averaged across a long period, but it comes with real limitations: cloud cover interferes with capture, and high resolution imagery is expensive to license repeatedly.

Here’s a simple illustration of why the polygon matters. Say a 30cm resolution image covering a port’s full estimated area costs several thousand dollars per capture, and an analyst needs monthly captures over a year to track change. If the port’s boundary is overestimated by even 20 to 30 percent, because it was hand digitized quickly or sourced from an outdated map, that overage gets priced into every single capture. Across twelve months, that inaccurate polygon can add up to tens of thousands of dollars in imagery spent for coverage the analysis never actually needed.

Accurate geometry solves this two ways. First, it keeps vessel counts realistic by intersecting imagery with the true port boundary, so ships or vehicles just outside the port aren’t miscounted. Second, since most imagery providers price by polygon area, a correctly sized boundary means analysts pay for the space they actually need to analyze, not a rough estimate. SafeGraph’s port polygons are built to eliminate both the in-house digitization work and the pricing risk that comes with hand drawn boundaries.

Using Port Data for Site Selection and Market Analysis

Port data isn’t only useful for analyzing the port itself. Because ports concentrate specific kinds of commercial activity nearby, like warehousing, logistics, freight forwarding, and light manufacturing, they’re a useful anchor point for site selection analysis.

Layering POI data around a port’s boundary lets analysts see which industries already cluster there and where there’s a gap. A market with strong port throughput but a thin logistics or warehousing footprint nearby, for example, can point to real estate or operational opportunity. The same analysis works in reverse for risk assessment, showing companies which of their existing facilities sit closest to ports facing volume declines or rerouting pressure.

Closing Thoughts

Trade routes are shifting faster than official reporting can keep up with, and the ports that mattered most a few years ago aren’t necessarily the ones that matter today. Port POI and geometry data gives analysts a way to ground trade activity, imagery spend, and site selection decisions in accurate, current boundaries instead of outdated estimates or stale government figures. As global shipping continues to reroute and rebalance through 2026, that kind of spatial accuracy is becoming less of a nice to have and more of a baseline requirement.