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Researchers in the social sciences are interested in the consequences of institutions, increasingly on a global scale. Institutions that may be negotiated between states can have consequences at a microlevel, as local populations adjust their expectations and ultimately even their behavior to take institutional rules into account. However, large-scale fine-grained analyses that test for the complex evidence of such institutions locally are rare. This article focuses on a key institution: International borders. Using computer vision techniques, we show that it is possible to produce a geographically specific, validated, and replicable way to characterizeborder legibility, by which we mean the ability to visually detect the presence of an international border in physical space. We develop and compare computer vision techniques to automatically estimate legibility scores for 627,656 imagery tiles from virtually every border in the world. We evaluate statistical and data-driven computer vision methods, finding that fine-tuning pretrained visual recognition models on a small set of human judgments allows us to produce local legibility scores globally that align well with human notions of legibility. Finally, we interpret these scores as useful approximations of states’ border orientations, a concept that prior literature has used to capture the visible investments states make in border areas to maintain jurisdictional authority territorially. We validate our measurement strategy using both human judgments and five nomological validation indicators. 

The Border Crossings of the World (BCW) dataset explores state authority spatially by collecting information about infrastructure built where highways cross internationally recognized borders. This geolocated information is recorded using high-altitude imagery from 1993 to 2020. We describe how the data were collected, demonstrate the dataset’s utility, and offer advice and best practices regarding use of the data. These data present clear evidence of visible and long-term state investments in authoritative displays of states’ intention to ‘filter’ entry into and exit out of their national jurisdiction. Researchers can use these data to test theories on the causes and consequences of border hardening for security outcomes, border management cooperation, political violence, terrorism, trade and migration flows, transnational crime patterns, and human rights conditions. Because the data are precisely geolocated, they are easy to combine with existing spatial datasets.