How hot is it? Communities collect heat data
About 25 cities this summer will work with the National Oceanic and Atmospheric Administration to collect data to identify neighborhoods with extreme heat.
Community-led campaigns in about 25 cities this summer will work with the National Oceanic and Atmospheric Administration to collect data to identify neighborhoods with extreme heat.
NOAA’s National Integrated Heatx Health Information System (NIHHIS) has partnered with cities including Albuquerque, New York and San Francisco to gather data that will be used to create interactive online maps that identify problem areas. This is the fourth year that NIHHIS and CAPA Strategies, a climate adaptation planning and analytics firm, have conducted Urban Heat Island mapping campaigns.
CAPA provides sensors it developed to volunteers called “community scientists,” who will walk, bike or drive specific areas of a city at a designated hour in the morning, afternoon and evening on a specific day. The National Weather Service helps determine the best time frame for collecting data through historical weather conditions about an area’s hottest and driest times, and then NOAA’s Climate Prediction Center and Weather Prediction Center provide threshold conditions for low cloud cover and winds.
The sensors record temperature and humidity measurements every second in addition to GPS locations and vehicle speed. The data is saved onto a local SD card that the community sends to CAPA on the campaign’s completion.
CAPA downloads the data in CSV format, cleans it and brings in imagery from the European Space Agency’s Sentinel II satellite.
“That provides several different bands at 10- or 20-meter resolution raster cell of land cover imagery,” said Joey Williams, manager at CAPA. “That is used to inform the variables for the model. In each cell, where we will be predicting temperature and heat index, we have 150 variables from the Sentinel satellite to use. And then in those where we have a temperature or humidity reading, that is the 151st variable that is used to train the model to then create a surface map of the full study area.”
CAPA then applies machine learning algorithms to the satellite imagery and temperature and humidity readings to produce interactive maps.
Data collection and analysis are two parts of the effort. The third is applying the results. CAPA and NOAA provide a summary report describing the campaign’s results, including maps, key observations and recommended next steps. CAPA also puts the data on the Open Science Framework and posts interactive maps online through Esri’s ArcGIS so that anyone can open a map and zoom in on the data, which is available for two years.
“By two years we expect that they’re bringing [maps] into their own systems and being able to present them in their own way,” Williams said.
Communities can use the information to make changes. For instance, when findings showed that areas of Richmond, Va., were hotter than others, city planners and officials wanted proof that the heat difference was problematic, said Vivek Shandas, a CAPA adviser and Portland State University climate adaptation professor.
“We ended up getting ambulance data on a hot set of days -- where were the largest number of ambulances responding -- and it almost one-to-one correspondent with the hottest parts of the city,” Shandas said.
CAPA built a fluid dynamics model that looks at the heat distribution for a city block and then studied how changes to the landscape would affect temperatures.
“We model those outputs through this simulation process where we can say, ‘Temperatures would go up X plus 10 degrees or X plus 2 degrees or they would drop by X minus 5 degrees’ with these different interventions that you can apply on these very localized site,” Shandas said.
Richmond used the data to put several heat mitigation planning processes in place, he said. For instance, it turned city-owned land into new community green spaces.
In August 2020, Houston conducted one of the largest campaigns to date. Most studies involve about eight to 10 sensors and cover 80 to 100 square miles, but Houston used 32 sensors and covered more than 330 square miles, Williams said. The effort was initiated by the Houston Advanced Research Center -- which had partnerships with the city resilience office, Harris County, local nonprofits and the Nature Conservancy -- to study day and nighttime temperature variations, energy use and affordability in the hottest areas.
CAPA lent participants Flir thermal imagery cameras that plugged into iOS and Android smartphones. “That allowed people to go out on the campaign and take thermal imagery photos with their iPhones and Androids of places along the campaign routes and look at ‘Why does this parking lot feel so much warmer? It’s reading 120 degrees Fahrenheit on my camera vs. the park I go to,’” Williams said.
Houston incorporated the heat mapping results into its Climate Action Plan, released April 2020. It includes a goal of planting 4.6 million new native shade trees by 2030.
Campaigns kick off in one of two ways: through a NOAA grant or as an independent effort. In 2019, NOAA started issuing requests for proposals for communities to apply to participate in the campaigns and get agency support, such as use of the sensors, construction of the maps and support from the CAPA team. NOAA can’t fund every city, however, so some work with CAPA directly, Shandas said, adding that about 60 cities have participated so far.
Typically, the studies end in one of three ways, he said. One is a massive collaborative effort with environmental groups in the communities. Another is interventions such as Houston and Richmond implemented. “Then there’s the community aspect of this, where there is a broader understanding of the concept of heat and its distribution in the area,” he said.
It’s important to know because extreme heat kills more Americans than any other weather event, according to NOAA. Within the same city, some neighborhoods can be up to 20 degrees warmer than others -- areas that tend to be home to poorer communities of color, NOAA states.