NOAA Urban Heat Island Mapping

Storymap Data

This notebook utilizes data featured in NOAA's "Urban Heat Island mapping campaign cities" project.

NOAA makes available datasets for a selection of US cities from their 2017, 2018 and 2019 campaigns as map services, allowing us to create dynamic, interactive, intelligent maps.

Predicted afternoon (3PM), morning (6AM), and evening (7PM) ambient temperatures or heat indexes where available. The data retrieved from sensors was analyzed using a machine-learning algorithm that also incorporates local data and satellite imagery. The resulting maps show heat distribution for the entire city.

Traverses that were conducted by volunteer community citizens by mounting sensor equipment on the car and driving the designated routes at 7 a.m., 3 p.m., and 7 p.m. on a hot, clear day. These sensors tracked GPS location, temperature, and humidity at one-second intervals throughout each one-hour traverse. After completion, sensors were shipped back to the CAPA team for analysis.

This is intended to be a collaborative notebook.

The motivation for creating this notebook comes from our recent conversation, "Data Science for Environmental Research (and Advocacy)". All the heavy lifting getting these data layers to render is thanks to @mootari, who generously invested several hours into debugging (and being sucessful).

Boston, MA

Morning (6 am) - https://gis.nnvl.noaa.gov/arcgis/rest/services/HINDZ/Morning_Heat_Index_in_Cities/ImageServer

Afternoon (3 pm) - https://gis.nnvl.noaa.gov/arcgis/rest/services/HINDZ/Afternoon_Heat_Index_in_Cities/ImageServer

Evening (7 pm) - https://gis.nnvl.noaa.gov/arcgis/rest/services/HINDZ/Evening_Heat_Index_in_Cities/ImageServer

Helpers

thanks @mootari!