2. What is Urban Heat Island?
Urban areas are warmer, like an “island” of heat surrounded by
cooler rural areas.
Urban heat island is the occurrence of higher temperatures in
metropolitan
areas in comparison to temperatures of suburban and rural
areas, which means the higher the urbanization level the more
prominent the UHI process.
The research focused on:
• Mapping of urban green areas through photointerpretation
• Mono Window Algorithm to obtain Land Surface Temperature
(LST)
• Coorelation between LST & NDVI and LST & NDBI
• Ecological Assessment
3. This study was conducted in
the municipality of Vila
Velha, located
on the coast of Espirito Santo
state, between latitudes 20°
19′ and 20°
32′ south and longitude 40°
16′ and 40° 28′ west, using
mono window algorithm of
LST.
4. Spatial and temporal distribution of UHI
Here, for the study of spatial distribution of urban heat
islands, 16 images are acquired from the Landsat 5
Thematic Mapper (TM) sensor, which are freely on the
United States Geological Survey (USGS) website. The images
were distributed between the years 2008–2011 in different
seasons and had no cloud cover interference.
5. Based on the thermal radiation transfer equation, the mono-window
algorithm requires three parameters: 1) emissivity; 2) transmittance;
and 3) atmospheric air average temperature.
Methodology is describing in the following:
Step 1: Digital number (DN) conversion to spectral radiance
Li = Lmin + (Lmax − Lmin) Qdn/Qmax
Step 2: Conversion of spectral radiance (Li) to reflectance
Step 3: Conversion of spectral radiance (Li) to brightness temperature
at the sensor
Tensors = K2/ ln (1 / K1 / Li)
6. Step 4: Estimated emissivity (ε)
where NDVI is the Normalized Difference Vegetation Index, ρ4 is the reflectance
in the near infrared band, and ρ3 is the reflectance in the red band.
Step 5: Estimation of atmospheric transmittance (τ)
where w is the water vapor content of the atmosphere (gcm−2), T0 is
the air temperature near the surface (K), and RH is the relative humidity
(%).
Step 6: Estimating average atmospheric temperature (Ta)
Step 7: Spatial distribution of Earth's surface temperature
This is the last step after performing all the steps described above and acquiring
all necessary variables, the mono-window algorithm is applied, thereby obtaining
the spatial distribution of LST for 16 images from the Landsat-5 TM for Vila
Velha, ES.
7. Determination of normalized difference build-up index (NDBI)
where NDBI is the normalized difference build-up index, MIR is band 5 -
mid-infrared, and NIR is band 4 - near infrared.
The urban thermal field variance index (UTFVI)
A number of thermal comfort indices are available for evaluating the UHI
impacts on the quality of urban life. In this study, the UTFVI has been used
for the ecological evaluation of UHI zones of study area. UTFVI has been
estimated using the following equation.
8. In this study, the results of the
spatial and temporal distribution
of LST in degrees Celsius (°C) for
the years 2008–2011.
The results demonstrate the
existence of the UHI effect in Vila
Velha, especially in areas of
dense urbanization, such as in
the north and north-west part.
In 2008, the extreme level of LST
occurred on spring season,
In 2009, the extreme level of LST
occurred on winter season,
In 2010, the extreme level of LST
occurred on summer and winter
season,
In 2011, the extreme level of LST
occurred on summer and spring
season.
9. According to the results, LST is fluctuating inter annually and monthly in this
study area.
In 2008, the high percentage of areas with temperatures above 34 °C in winter
and spring season. In 2009, the high percentage of areas with temperatures
above 34 °C in summer and winter season. As 2009, similar case is seen with in
the year 2010. And then in 2011, the high percentage of areas with temperatures
above 34 °C in summer and spring season.
Pearson Coorelation
In the correlation analysis, the results show negative relationship between LST
and NDVI and positive relationship between LST and NDBI.
10. UTFVI is calculated for ecological
assessment. The two extremes of
ecological assessment are excellent
and worst. After seeing all images,
here we can interpret that
concentration of urban development
indicates environmental and
ecological degradation which shows
“worst” in the index. “Excellent” is
also seen all over the area between
2008 and 2011.
11. As LST is fluctuating annually and monthly, in which highest LST values
occur in the summer and lowest occur in the autumn season.
Concentration of urban areas classified as “worst” in the ecological index
while the presence of green areas as natural vegetation indicate
“excellent”.
So, the methods are adopted for measuring the better distribution of
urban areas along with vegetation to mitigate the effect of urban heat
island.
