1. The study aims to evaluate how Austin's rapid growth will impact residents' quality of life by examining the city's surface urban heat island (UHI) effect using satellite data and thermal imaging. 2. Factors that affect UHI severity include location, building materials, population density, vegetation cover, bodies of water, and sky access. No prior studies have evaluated Austin's surface UHI. 3. The researchers will analyze how land use changes over time relate to land surface temperature, conduct sensitivity analyses to identify the most influential factors on Austin's UHI, and create models to predict future UHI patterns and consequences.

1. Too Hot to Handle?
Modeling Austin’s Surface Urban Heat Island
Gitanjali Bhattacharjeea
, Lauryn Altena, Tarek El Afifi, Lilian Gonzalez-Arechaga, Raul Olvera, Dr. Lance Manuel
Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin; g.bhattacharjee@utexas.edua
The observation that urban temperatures tend to be higher than
rural ones was first documented in early 19th century London1
.
Since then, urban heat islands (UHI) have been the focus of a
growing body of scientific literature, particularly in Europe and parts
of Asia, because of their potentially deadly effects.
UHI contribute to2
:
- uncomfortable outdoor conditions that can result in heat stroke
- increase in amount of ground-level ozone, causing lung damage
- increased peak energy demand and associated pollution
- damaging aquatic ecosystems by thermal pollution of runoff
Factors that affect the extent and severity of UHI include2
:
- geographic location and altitude
- building material properties
- population
- vegetation versus impervious cover
- cloud cover
- bodies of water
- the layout of buildings, quantified as sky-view factor (SVF)
Though Austin is one of the fastest growing cities in the US3
, no
studies of its surface UHI have yet been published in the literature.
We have planned a multi-phase investigation to evaluate how Aus-
tin’s growth will impact residents’ quality of life.
1. Examine how vegetation, impervious cover, bodies of water,
and SVF relate to land surface temperature (LST) in Austin and
nearby areas, both historically and currently
2. Examine surface heat island gradients by accounting for
changing land use types
3. Conduct a sensitivity analysis to determine which factors im-
pact Austin’s surface UHI the most
4. Create a probabilistic model to predict how Austin’s surface
UHI will manifest in future
5. Choose an acceptable range of values for the diurnal tempera-
ture swing, and use the probabilistic model to determine when
and how often the tem perature change is unacceptable over
the course of a year
6. Evaluate the consequences of Austin’s surface UHI for energy
demand and life safety
Background
Research Questions
Using satellite images is standard practice in UHI studies be-
cause of the accuracy and comprehensiveness of resulting data-
sets4
. NASA’s Moderate Resolution Imaging Spectroradiometer
(MODIS) is often used in UHI analysis because it includes historical
datasets of the temperatures of a specific coordinate.
Using MODIS images, LST can be plotted against spatial position
and time. Then, a thermal pattern analysis can be carried out to un-
derstand the effects of albedo, vegetation, and time of day on the
temperature differential of the Austin’s surface UHI.
The sky-view factor (the percentage of sky than can be seen at a
given location), of various locations will be determined using a com-
bination of softwares5
:
- RayMan creates 3D layout of buildings and trees
- SkyHelios creates a virtual fish-eye image from RayMan data
- SVF can be calculated from the fish-eye image
A thermal imaging sensor (Seek Thermal XR Extended Range
Thermal Imager, iOS) will also be used at selected points in and
around Austin to measure LST - validating satellite data - and to
measure the temperatures of buildings and other features, as in the
image above.
Materials and Methods
We would like to thank Dr. Lance Manuel for his dedication to provid-
ing research opportunities to undergraduates, Dr. Sudhanshu Panda
and Dr. Sukanta Basu for their invaluable guidance on processing satel-
lite data, and Dr. Joshua Apte for his guidance on poster design.
1. Stewart, I. D. “A Systematic Review and Scientific Critique of Methodology in Mod-
ern Urban Heat Island Literature.” International Journal of Climatology 31.2 (2011):
200-17. Web.
2. Reducing Urban Heat Islands: Compendium of Strategies. Washington, DC: Cli-
mate Protection Partnership Division, U.S. Environmental Protection Agency, 2008.
U.S. Environmental Protection Agency. Web. <http://www.epa.gov/heatisland/resourc-
es/pdf/BasicsCompendium.pdf>.
3. Carlyle, Erin. “America’s Fastest-Growing Cities 2015.” Forbes. Forbes Magazine,
27 Jan. 2015. Web. <http://www.forbes.com/pictures/emeg45eegeg/2-austin-texas/>.
4. Keramitsoglou, Iphigenia, Chris T. Kiranoudis, Giulio Ceriola, Qihao Weng, and
Umamaheshwaran Rajasekar. “Identification and Analysis of Urban Surface Tempera-
ture Patterns in Greater Athens, Greece, Using MODIS Imagery.” Remote Sensing of
Environment 115.12 (2011): 3080-090. Web.
5. Matzarakis, Andreas, and Olaf Matuschek. “Sky View Factor as a Parameter in
Applied Climatology – Rapid Estimation by the SkyHelios Model.” Meteorologische
Zeitschrift 20.1 (2011): 39-45. Web.
Acknowledgements
References
Thermal image of the UT Tower, taken with the SEEK camera.
Profile of an urban heat island. (EPA) Contributing factors to UHI. (Alexandre Affonso)