1. LAND SURFACE TEMPERATURE OF
BUILDINGS IN CEDAR FALLS, IA
Joel Heilman

2. Introduction
Atma Bharathi Mani conducted his thesis on “Building Heat Loss Detection and Surface
Temperature Mapping of the City of Cedar Falls Using Aerial Thermal Images and Web-GIS”
Land Surface Temperature (LST) can detect what buildings lose heat during colder months due to
poor insulation
◦ This can help us minimize heat loss
Atma did not look at how demographics affect this heat loss from buildings

3. Research Goals
Determine which buildings in Cedar Falls have extreme LST values
Compare mean LST of residential buildings in Cedar Falls with demographic variables to see if
there is any correlation
◦ Hypothesis: Higher income homes will have better insulation and lower LST values

4. Study Area: Cedar Falls, IA
Population of about 39,000
◦ 93.4% white, 2.3% Asian, 2.1% African American
◦ 29.7% are between ages 18 and 24
Home of the University of Northern Iowa
◦ Enrollment is about 12,000

5. Data
LST for Cedar Falls calculated by Atma
◦ Aerial images using Rochester Institute of Technology’s
(RIT) Wildfire Airborne Sensor Program (WASP) instrument
which is a FLIR Phoenix imager
◦ Long-wavelength infrared (LWIR: 8-9.2µm) thermal band
collected on the nights of November 18th and 19th, 2010
was used for calculations

6. Data
Dry Run Creek land use data
◦ Covers most of Cedar Falls
2010 US Census data at block group level
◦ Demographic information included race, age, median
household income, occupancy, and tenure
Summer 2010 reference photograph
◦ From Iowa State University Geographic Information
Systems Support & Research Facility
Software: ArcMap 10.3.1 Dry Run Creek land use data

7. Methodology

8. Zonal Statistics as a Table

9. Methodology

10. Results
Both the hottest and coldest buildings
owned by the City of Cedar Falls
Most of the extreme buildings are
industrial buildings

11. Methodology

12. Results

13. Results

14. Conclusions
Extreme LST values are mostly industrial buildings
LST of residential buildings had little correlation with age, household median income, occupancy,
and tenure
◦ Most correlated variable to LST was total population, followed by racial variables
In the future:
◦ Use mid-wavelength infrared (MWIR: 3-5µm) band to calculate LST
◦ Compare to other demographic variables
◦ Compare to demographics at the census block level
◦ Building footprints for all of Cedar Falls