PT   EN

Mapping perception using Kobotoolbox and mobile sound measurements (NoiseCapture and OpeNoise apps).

This dataset integrates environmental noise measurements, perceptual responses, and urban visual characteristics collected in São Paulo. Acoustic data were obtained using smartphone sound level meter apps, perceptual data via KoboToolbox surveys, and visual metrics derived from Google Street View image segmentation. The dataset enables analysis of relationships between sound environment, human perception, and urban form.

You can search by a Kmz_point ranging from 1 to 301.

The visualization presents a selected subset of columns relevant for spatial interpretation. The complete dataset is publicly available in the Zenodo repository for further exploration and analysis 

Column Description

🔹 Identification

• Kmz_point: ID of each point

🔹Sound Measured Data (NoiseCapture / OpeNoise)

• device: Anonymous identification device used for recording 

• Date: Measurement date

• Time: Measurement time

• duration: Length of recording (seconds)

• latitude / longitude: Geographic coordinates

• LAeq: Equivalent continuous sound level (dBA)

• LA50: Median sound level (dBA)

🔹Perceptual Data (KoboToolbox)

• THERMAL SENSATION: Perceived thermal sensation (very cold, cold, neutral, warm, very warm)

• CONFORT_TERM: Thermal comfort level (confortable, unconfortable)

• LOUDNESS: Perceived loudness of environment (very low, low, neutral, cold, very cold)

• CONFORT_ACOUSTIC: Acoustic comfort level (confortable, unconfortable)

• NATURAL_SOUNDS: Presence of natural sounds (1 to 100)

• TECNHO_SOUNDS: Presence of technological/mechanical sounds (1 to 100)

• HUMAN_SOUNDS: Presence of human-related sounds (1 to 100)

• PLEASANT-ANNOYING: How eventful a soundscape is perceived  (1 = pleasant to 100 = annoying)

• EVENTFUL-UNEVENTFUL: How eventful a soundscape is perceived (1 = eventful to 100 = uneventful)

• VIBRANT-MONOTONOUS: How monotonous a soundscape is perceived (1 = vibrant to 100 = monotonous)

• CHAOTIC-CALM: How chaotic a soundscape is perceived (1 = calm to 100 = chaotic)

🔹Google Street View Semantic Segmentation

• pano_ID: Panorama image ID

• Data: Image capture date

• GREEN_view: Proportion of vegetation (1 to 100)

• BUILD_view: Proportion of buildings (1 to 100)

• TRAFFIC_view: Proportion of traffic elements (1 to 100)

• HUMAN_view: Proportion of people (1 to 100)

• SKY_view: Proportion of sky (1 to 100)