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Global Port POI and Geometry Data for Improved Supply Chain Analysis

February 11, 2022
Fletcher Berryman

Since fall of 2021 SafeGraph has been steadily growing the number of geographies in which we provide Places (points of interest) data and currently are past 200 nations (which, for those geo-nerds among you, means we’ve surpassed the 193 UN members count by also adding support for a number of sub-national administrative units and autonomous regions).

Places will always be the foundation for our other datasets, such as Spend, which append additional columns of information to each row (location) for further context. But we also recognize that organizations need to contextualize these points by adding in their associated geometries reflecting the surface area of particular places. That’s why we have prioritized expanding our Geometry datasets worldwide, including unique categories of places that are relevant for our customers. Above all, one category of locations has been requested more than others: ports.

By understanding where ports are globally and their surface area extent, analysts can get right to asking critical questions about the locations themselves, well before joining other datasets for added detail.

As of writing this blog post, we’ve cast a wide net (maritime pun intended) by releasing approximately 5,400 ports across 172 countries.

By intersecting existing mobility data with these POIs and polygons, customers will be able to ask macroeconomic questions around the overall state of trade in a given region(s) or drill down to specific ports and make comparisons of relative performance. With the addition of a wkt_area_sq_meters column analysts can also explore relationships between the size of ports and their import/export volumes.

Beyond direct analysis of the ports themselves, this large addition to SafeGraph’s offering only strengthens the existing opportunities for site selection analyses by allowing for customers to examine which POIs are (or are not) concentrated around ports and consider the business ramifications of their presence. Understanding the types of POIs that thrive or flounder (maritime pun #2) in the vicinity of ports will inform the uncovering of potential gaps and opportunities in their respective markets.

While the problems for which analysts are trying to solve with ports are quite varied, we at SafeGraph have observed that one of the most common goals is to develop a clearer measure of trade activity in lieu of transactional information or some other formal data source from respective port authorities. This is particularly prevalent in emerging markets where there may be little to no data publicly or commercially available detailing import/export figures per port. Compounding this problem is the introduction of COVID-19 into the equation: averages from previous years and historical data trends are proving less valuable as we see supply chain constraints so drastic that container ships can be seen stuck in queue for miles outside many of the world’s largest ports.

Like most spatial analysis, the best solutions in this regard involve the layering of multiple types of data. We’ve seen a trend over the last several years of organizations using satellite imagery to identify the number of ships coming in over time to a particular series of locations. This can be more reliable than one might expect if averaged over a long enough period, even with the shortcomings of satellite imagery such as cloud cover or a limited image inventory that week in mind. Still, even the best satellite imagery comes at 30cm resolution and to purchase such high resolution imagery is extremely expensive, especially when buying many exposures to then measure change over time. Analysts often rely on less clear resolutions such as 50cm or revert to medium resolution in the 1m - 5m range. This resolution will still capture objects such as container ships, land vehicles and containers themselves but will likely fail to delineate port boundaries, which are hard to make out from above. 

With accurate geometry information, analysts can intersect their imagery with reliable polygons to ensure their counts are realistic and not accidentally looping in vehicles or other measured objects outside of the port boundary (for example, workers’ vehicles or nearby industrial facilities not tied to port operations). An added benefit is the fact that buying satellite imagery is usually done by submitting a polygon to the provider who then prices their quote based off of the surface area of the polygon submitted. Thus, less accurate polygons might potentially lead to buying coverage that’s not needed. Over many months, this could bleed tens of thousands in unnecessary costs.

With SafeGraph’s ports coverage, clients can know ahead of time that the boundaries will be accurate regardless of how remote a market may be. They’ll also save the countless hours required if they were to digitize port polygons in-house, and finally avoid the likely errors that would come along with such a manual effort.

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