Assessment of urban heat model

1. ASSESSMENT OF URBAN HEAT ISLAND
EFFECT IN VARANASI CITY OF UTTAR
PRADESH
Presented BY Kumar Ankit
KSRDPU, Gadag

2. Introduction
• Land Surface Temperature (LST) is a global scale
land surface process. LST is the combination of
all surface atmosphere interaction and energy.
LST is not a constant parameter as it kept on
changing due to climatic conditions and human
activities.
• Urbanization has resulted in many critical issues
like increase in pollution levels, sudden climatic
changes and the rise of temperatures in urban area
that is the formation of Urban Heat Islands (
UHI).

3. INTRODUCTION
• Urban Heat Island effect is a kind of heat
accumulation phenomenon within urban area due
to urban construction and human activities.
• remote-sensing- and GIS-based techniques are
highly efficient to study the interdependency of
the urban landscape pattern, LST, and UHIs.
• Remote-sensing and GIS techniques provide
better accuracy and spatial resolution and are less
time-consuming and more economical compared
to other traditional methods of monitoring large
areas.

4. The temperature profile in different areas, with the formation of
the UHI

5. Study Area
• Varanasi is located in the Gangetic plain of
north Indian state of Uttar Pradesh.
• The temperature typically varies between 22
0C and 46 0C .
• total area covered is around 209.7 Km2.

6. Data Used in the Study
• Landsat 8 Operational Land Imager and Thermal
Infrared Sensor (Landsat 8 OLI/TIRS) images were
used.
• The images were acquired from https://earthexplorer.
usgs.gov/ (accessed on 25 February 2022).
• images have 11 bands, containing 8 multispectral bands
(band 1st–7th and 9th), one panchromatic (band 8th),
and two thermal bands (band 10th and 11th) .
• The radiometric resolution of Landsat 8 is 16m and the
swath is 185 km.

8. METHODOLOGY Used

9. FORMULA USED
• Top of Atmosphere (TOA) Using radiance rescaling
factor from meta data, Thermal Infra-Red Digital
Numbers converted to TOA spectral radiance.
• Brightness Temperature Spectral radiance data
converted to brightness temperature using the thermal
constant values in Meta data file.
• Normalized Differential Vegetation Index (NDVI)
The Normalized Differential Vegetation Index (NDVI)
is a standardized vegetation index which calculated
using Near Infra-red (Band 5) and Red (Band 4) bands.
• NDVI = (BAND5-BAND4) / (BAND5+BAND4)

10. • Proportion of Vegetation
• Pv = [(NDVI – NDVI min) / (NDVI max + NDVI min)]
Where Pv is Proportion of Vegetation.
• Land surface emissivity (LSE) calculated to estimate
LST.
• Eλ=EV PV+ES (1-PV)
• Land Surface Temperature (LST) The Land Surface
Temperature (LST) is the radiance temperature which is
calculated using Top of atmosphere, brightness
temperature, NDVI, Land Surface Emissivity.
• LST = BT{1 + [(λBT/p ) ln Eλ ]}

11. Result and Discussion
• It can found that the LST value has been
increased to 6°F in Varanasi from 2013 to
2021.
• LST values has been increased in built up area
and decreased in vegetation area.

15. Conclusion
• The interpretation, it can found that the LST value has been
decreased in Varanasi from 2013 to 2017
• When we analysis the LST image by using LU/LC map we found
that the LST values has been increased in built up area and
decreased in vegetation area.
• After 2017 to 2021 LST values increases due to more urbanization
and decrease in vegetation in the area.
• It is observed that with change in land use and land cover area, the
LST values also gets changed it reflects its dependency on land use
and land cover patterns.
• The central zone consist of high population density, low vegetation
cover and high anthropogenic activities. Temperature of central zone
of Varanasi is increased by the influences of above factors.

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17. THANK YOU