Analysis of data from vessel monitoring systems and automated identification systems in large-scale fisheries is used to describe the spatial distribution of effort, impact on habitats, and location of fishing grounds. To identify when and where fishing activities occur, analysis needs to take account of different fishing practices in different fleets. Small-scale fisheries (SSFs) vessels have generally been exempted from positional reporting requirements, but recent developments of compact low-cost systems offer the potential to monitor them effectively. To characterize the spatial distribution of fishing activities in SSFs, positions should be collected with sufficient frequency to allow detection of different fishing behaviours, while minimizing demands for data transmission, storage, and analysis. This study sought to suggest optimal rates of data collection to characterize fishing activities at appropriate spatial resolution. In a SSF case study, on-board observers collected Global Navigation Satellite System (GNSS) position and fishing activity every second during each trip. In analysis, data were re-sampled to lower temporal resolutions to evaluate the effect on the identification of number of hauls and area fished. The effect of estimation at different spatial resolutions was also explored. Consistent results were found for polling intervals <60 s in small vessels and <120 in medium and large vessels. Grid cell size of 100 × 100 m resulted in best estimations of area fished. Remote collection and analysis of GNSS or equivalent data at low cost and sufficient resolution to infer small-scale fisheries activities. This has significant implications globally for sustainable management of these fisheries, many of which are currently unregulated.