NYC Street-Level Temperature Monitoring for Heat Risk Neighborhoods

Hourly average air temperature readings from approximately 475 sensor locations in New York City neighborhoods identified as high heat mortality risks. The data was collected by the NYC Parks Department, Mayor's Office of Resilience, and Department of Health and Mental Hygiene during the summers of 2018 and 2019. It provides hyperlocal measurements for specific city blocks.

Use Cases

• Analyze AirTemp fluctuations by Hour and Day to model diurnal heat patterns in specific Boroughs.
• Correlate hyperlocal temperature (AirTemp) with neighborhood identifiers (ntacode) to assess spatial disparities in heat exposure.
• Train time-series forecasting models to predict AirTemp using features like Hour, Year, and sensor metadata (Sensor.ID, Install.Type).
• Map heat island intensity by joining sensor locations (Latitude, Longitude) with demographic or health datasets using ntacode or geospatial coordinates.

Strengths

• Approximately 475 distinct sensor locations provide dense spatial coverage within target neighborhoods.
• Hourly temporal resolution for detailed diurnal analysis during summer months.
• Data includes precise geospatial coordinates (Latitude, Longitude) for mapping and spatial analysis.

Limitations

• Limited temporal coverage to only two summers (2018 and 2019), restricting longitudinal analysis.
• Spatial coverage is limited to a subset of high-risk NYC blocks, not representative of the entire city.
• Sample size and total row count are unknown, preventing assessment of data volume.

Provenance

Source

NYC Parks Department, Mayor's Office of Resilience, NYC Department of Health and Mental Hygiene via data.cityofnewyork.us

Collection Method

Street-level temperature monitoring via sensors installed on a subset of city blocks.

Time Range

Summers of 2018 and 2019

Freshness

Last updated in April 2023, but underlying data collection ended in 2019.

Geography

Selected neighborhoods within New York City boroughs with high heat mortality risk