Abstract
The present study aims at investigating the impact of land cover features in enhancing or mitigating Land Surface Temperature (LST) in a semi-arid tropical metropolitan city of Bengaluru, India. Spatial distribution of LST and land cover types of the area were examined in the circumferential direction, and the contribution of land cover classes on LST was studied over 28 years. Urban growth and LST were modelled using Landsat and MODIS data for the years 1989, 2001, 2005 and 2017 based on the concentric ring approach. The study provides an efficient methodology for modelling and parameterisation of LST and urban growth by fitting an inverse S-curve into urban density (UD) and mean LST data. In addition, multiple linear regression models which could effectively predict the LST distribution based on land cover types were developed for both day and night time. Based on the analysis of remotely sensed data for LST, it is observed that over the years, urban core area has increased circumferentially from 5 to 10 km, and the urban growth has spread towards outskirts beyond 15 km from the city centre. As urban expansion occurs, the area under the study experiences an expansive cooling effect during day time; at night, an expansive heating effect is experienced in accordance with the growth in UD in the suburban area and outskirts. The regression models that were developed have relatively high accuracy with R2 value of more than 0.94 and could explain the relationship between LST and land cover types. The study also revealed that there exists a negative correlation between urban, vegetation, water body and LST during day time while a positive correlation is observed during night. Thus, this study could assist urban planners and policymakers in understanding the scientific basis for urban heating effect and predict LST for the future development for implementing green infrastructure. The proposed methodology could be applied to other urban areas for quantifying the distribution of LST and different land cover types and their interrelationships.
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Abbreviations
- f :
-
Modified sigmoid function
- r :
-
Distance from the urban centre (km)
- m and c :
-
Asymptotes of function f
- k S :
-
Slope of the function in the intermediate urban zone between urban core and urban fringe
- Q Cal :
-
Quantised calibrated pixel value
- G rescaled :
-
Rescaled gain
- B rescaled :
-
Rescaled bias
- L λ :
-
Spectral at-sensor radiance
- M L :
-
Radiance multiplicative scaling factor of the thermal band
- ∆L :
-
Radiance additive scaling factor of the thermal band
- P v :
-
Green coverage ratio
- NDVImax :
-
Maximum value of NDVI which corresponds to thick vegetation
- NDVImin :
-
Minimum value of NDVI corresponding to soil
- L d :
-
Downwelling radiance
- L u :
-
Upwelling radiance
- τ:
-
Atmospheric transmission
- ε:
-
Surface emissivity
- L T :
-
Surface leaving radiance
- T :
-
Surface temperature in Kelvin
- K1, K2 :
-
Calibration constants of Landsat images (K1 in watts/(m2*ster*μm) and K2 in Kelvin)
- L T :
-
Surface leaving radiance in watts/(m2*ster*μm)
- LSTn :
-
Normalised LST
- LST:
-
Land surface temperature value of each pixel in Kelvin
- LSTmax :
-
Maximum value of LST for a particular satellite image (Kelvin)
- LSTmin :
-
Minimum value of LST for a particular satellite image (Kelvin)
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Authors would like to thank the Department of Water Resources and Ocean Engineering, National Institute of Technology Karnataka Surathkal for providing the neccassary support to carry out this research work.
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Govind, N.R., Ramesh, H. Exploring the relationship between LST and land cover of Bengaluru by concentric ring approach. Environ Monit Assess 192, 650 (2020). https://doi.org/10.1007/s10661-020-08601-x
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DOI: https://doi.org/10.1007/s10661-020-08601-x