Remote sensing technique often analyzes the thermal characteristics of any area. Our study focuses on estimating land surface temperature (LST) of Raipur City, emphasizing the urban heat island (UHI) and non-UHI inside the city boundary and the relationships of LST with four spectral indices (normalized difference vegetation index, normalized difference water index, normalized difference built-up index, and normalized multiband drought index). Mono-window algorithm is used as LST retrieval method on Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data, which needs spectral radiance and emissivity of TIRS bands. The entire study is performed on 11 multidate Landsat 8 OLI and TIRS images taken from four different seasons; premonsoon, monsoon, postmonsoon, and winter, in a single-year time period. The Landsat 8 data derived LST is validated significantly with Moderate Resolution Imaging Spectroradiometer (MOD11A1) data. The results show that the UHI zones are mainly developed along the northern and southern portions of the city. The common area of UHI for four different seasons is developed mainly in the northwestern parts of the city, and the value of LST in the common UHI area varies from 26.45°C to 36.51°C. Moreover, the strongest regression between LST and these spectral indices is observed in monsoon and postmonsoon seasons, whereas winter and premonsoon seasons revealed comparatively weak regression. The results also indicate that landscape heterogeneity reduces the reliability of the regression between LST with these spectral indices.
Spatial–temporal distribution of the urban heat islands (UHI) and their changes over Raipur city have been analyzed using multitemporal Landsat satellite data from 1995 to 2016. Land surface temperature (LST) was retrieved through a mono-window algorithm. Some selected land use/land cover (LU–LC) indices were analyzed with LST using linear regression. The urban thermal field variance index (UTFVI) was applied to measure the thermal comfort level of the city. Results show that during the observed period, the study area experienced a gradual increasing rate in mean LST (>1% per annum). The UHI developed especially along the north-western industrial area and south-eastern bare land of the city. A difference in mean LST between UHI and non-UHI for different time periods (2.6°C in 1995, 2.85°C in 2006, 3.42°C in 2009, and 3.63°C in 2016) reflects the continuous warming status of the city. The LST map also shows the existence of a few urban hot spots near the industrial areas, metal roofs, and high density transport parking lots, which are more abundant in the north-western part of the city. The UTFVI map associated with UHI indicates that the inner parts of the city are ecologically more comfortable than the outer peripheries.
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