This study presents a methodology to integrate drone operations into urban environments by applying existing noise regulations within urban acoustic plans. These regulations define acceptable noise levels based on land use, with specific thresholds for different zones and times of day. By employing a regression equation that assesses noise generation based on drone weight, this work creates a spatial data layer to identify suitable areas for drone activities, guaranteeing regulatory compliance. The presented approach not only facilitates the creation of a detailed map but also provides a comprehensive framework for strategically positioning drone infrastructures like vertiports and air corridors. Applied in the pilot site of Bologna (Emilia-Romagna region, Italy), the methodology demonstrates its effectiveness in harmonizing drone operations with urban noise management, enhancing quality of life and ensuring societal acceptance.

Spatial Analysis for Urban Noise Management: Evaluating Respect Zones for Drone Operations

Stefano Cunietti;Ilaria Ferrando;Domenico Sguerso
2024-01-01

Abstract

This study presents a methodology to integrate drone operations into urban environments by applying existing noise regulations within urban acoustic plans. These regulations define acceptable noise levels based on land use, with specific thresholds for different zones and times of day. By employing a regression equation that assesses noise generation based on drone weight, this work creates a spatial data layer to identify suitable areas for drone activities, guaranteeing regulatory compliance. The presented approach not only facilitates the creation of a detailed map but also provides a comprehensive framework for strategically positioning drone infrastructures like vertiports and air corridors. Applied in the pilot site of Bologna (Emilia-Romagna region, Italy), the methodology demonstrates its effectiveness in harmonizing drone operations with urban noise management, enhancing quality of life and ensuring societal acceptance.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1224282
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