Spatial Statistics Modeling of Aircraft Noise Complaints
- Renata Cavion
- Michelle Carvalho Galvão da Silva Pinto Bandeira
- Simone Becker Lopes
Federal University of Santa Catarina (UFSC) · Federal University of Goiás (UFG)
- Event
- XXII SITRAER – Brasília, DF, Brasil, October 22–24, 2025
- Volume
- Anais do XXII Simpósio de Transporte Aéreo – SITRAER 2025 · ISBN 978-65-272-2024-4 · DOI 10.29327/9786527220244
- Publisher
- Even3 Publicações
- Editors
- Fabiana Serra de Arruda, Camila Lucena, Giovanna Miceli Ronzani Borille, Evandro José da Silva
Abstract
This study employed spatial statistical modeling to analyze the distribution of aircraft noise complaints around São Paulo's Congonhas Airport, validating a detailed geographic approach for this phenomenon. The methodology followed three main steps, including the construction of a spatial weight matrix (1575 cells of 0.5km×0.5km), followed by Exploratory Spatial Data Analysis (ESDA). This analysis revealed a strong and statistically significant positive spatial autocorrelation in complaints, with a Global Moran's I of 0.565 indicating the geographic clustering of incidents (hotspots). Although Ordinary Least Squares (OLS) regression was globally significant (F=37.5909, p<0.0001), its low explanatory power (R2 of 0.177752) reinforces the inadequacy of non-spatial models and suggests the existence of unmodeled factors. The identified determinants include residential land use, presence within specific noise contour zones (e.g., 65dB,70dB), and proximity to landing routes. The main research limitation lies, however, in the exclusion of socioeconomic and perceptual variables, which are known to influence complaint behavior, due to the unavailability of data at the cell level. To make the study more comprehensive and in-depth, it is recommended that future investigations incorporate spatial regression models and a broader spectrum of variables, such as socioeconomic, biological, climatic, and psychological data, aimed at enhancing predictive power and the integral understanding of the annoyance phenomenon.
Keywords: Aircraft Noise; Spatial Statistics; Urban Areas; Spatial Autocorrelation; Noise Complaints; Geographical Information Systems (GIS)