timestamp

Time that the record occurs

High-Level Explanation

Year, month, day, hour, minute, second (plus fractional second), and time zone, in the format YYYY-MM-DDThh:mm:ss.sTZD. Example:

2022-12-09 07:53:23.497000+00:00

Where this record takes place on December 9th, 2022 at 7:53 AM (and 23.497 seconds). This record takes place at the coordinate (latitude, longitude): 42.307629, -83.714811, (in Ann Arbor, Michigan) which is in the "America/New_York" time zone. Since this record occurs during standard time (not daylight savings time), the time zone is UTC-05:00.

Enables

Conversion to local time. One potential source of time zone geospatial data is: https://common-data.carto.com/tables/ne_10m_time_zones/public. Note that tz_convert does indeed correct for daylight savings time.

import geopandas as gpd

tz = gpd.read_file('ne_10m_time_zones.geojson')
gdf['geometry'] = gpd.GeoSeries.from_xy(x=gdf['longitude'],y=gdf['latitude'])
gdf = gdf.sjoin(tz[['geometry','tz_name1st']])
gdf['timestamp'] = \
        gdf.apply(lambda row: row['timestamp'].tz_convert(row['tz_name1st']), \
                     axis=1)

Enabled By

Known Quirks

• It is important to note that this signal defaults to the UTC time zone and, if local time is important, the signal must be converted. See latitude and longitudefor discussion of the frequency of data collection.

• Vehicles sometimes lose cellular connection for data reporting, so there can be long gaps between timestamps due to potentially lost connection, but also possibly just lack of vehicle use.

Visualizations with Explanations