Authors - Laura Alma Diaz-Torres, Alma Delia Torres-Rivera, Mario Leonardo Nieto Antolinez, Fabian Leonardo Alfonso Sabogal Abstract - Mexico City faces a constant need for high-quality public transport systems capable of reducing passenger waiting times, improving travel comfort, and maintaining the economic viability of private operators. In this context, demand studies are essential both before the concession stage and during service operation, since they support route planning, fleet allocation, schedule adjustments, and operational decision-making. Two similar but distinct methodologies are compared for the estimation of load polygons. The first methodology assigns telemetry events to official stops using spatial proximity and route reconstruction through directed graphs. This approach provides higher operational traceability, since demand is linked to formal routes, directions, and stops. Nevertheless, it may underestimate demand that occurs outside the official route structure. The second methodology uses heat maps and 300-meter-radius polygons to identify functional demand areas based on observed passenger activity. This approach captures real operational behaviour more flexibly, but may lose direct correspondence with formal stops, especially when polygons overlap or include stops from different directions. The comparison shows that neither methodology is sufficient on its own. The graph-based method is useful for formal operational analysis, while the heat-map method is more sensitive to actual demand behaviour. Based on these findings, the paper proposes, as future work, the development of a multicriteria integration approach that combines both methods. Such an approach could reduce structural and observational biases, improve the processing of boarding and alighting data, and generate clearer maps, graphics, and analytical outputs to support expert decision-making in public transport operations.
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