Abstract
Accurate estimation of aircraft takeoff weight (TOW) and landing weight (LW) is critical for assessing fuel consumption, emissions, noise impacts, and other analyses, yet these parameters are typically unavailable in surveillance data such as Automatic Dependent Surveillance-Broadcast (ADS-B). This study presents a method for estimating aircraft takeoff and landing weights using stabilized airspeed segments from ADS-B surveillance data. The approach is derived by relating lift, weight, and airspeed during stabilized flight phases. The method outlined is validated using one year of operations at Seattle-Tacoma International Airport, analyzing over 10,000 flights across three narrow-body aircraft types: B737-800, B737-900, and A320. Weight estimated from ADS-B airspeed profiles was matched to weight records provided by an airline, achieving mean absolute errors of 5.0–7.4% of maximum takeoff weight (MTOW) for departures and 6.0–7.0% of MTOW for arrivals. The method exhibits minimal systematic bias, with absolute distribution mean errors below 0.4% MTOW in magnitude. The demonstrated accuracy enables applications such as fleet-wide fuel consumption modeling, emissions inventories, and aircraft noise impact assessments, providing a valuable tool for data-driven modeling of aviation operations using existing surveillance infrastructure.