Cartographers and Photogrammetrists

Cartographers’ jobs involve preparing maps from photos, survey notes, and other data ^{[1] [1]}. Today many routine parts of this work use AI tools. For example, software can automatically stitch thousands of drone or satellite images into 3-D maps and even label features like roads, buildings, or forests.

Britain’s Ordnance Survey (the national mapping agency) has built an AI system that compares new aerial photos to existing maps and flags changes (new houses, roads, etc.) for human review ^[2]. This automated change-detection cut map-update time by about half ^[2] while still having people “rapidly assess” each flagged change manually ^[2]. In short, computers now handle much of the data processing, but cartographers still do the final checking and interpretation ^{[2] [3]}.

Many mapping agencies are starting to use these AI tools because they save time and effort. For instance, Ordnance Survey’s CTO notes that automating feature extraction from imagery “ensures faster map updates” ^[3]. In one project, the AI caught about 92% of real changes in maps and halved the work compared to doing it all by hand ^[2].

These gains make investing in AI attractive. However, new software and training cost money, so smaller mapping teams may adopt it more slowly. And because maps affect real-world decisions (land use, infrastructure, property lines, etc.), experts insist on “responsible AI” – keeping humans in charge of key decisions ^[3].

Tasks like interpreting legal boundary records still need people ^[1], and Ordnance Survey emphasizes upskilling staff and preserving human creativity alongside efficiency gains ^[3]. In practice, AI tends to augment rather than replace cartographers: it does the repetitive analysis, while humans focus on problem-solving and quality checks ^{[2] [3]}.