Exploring the relationship between LST and land cover of Bengaluru by concentric ring approach

dc.contributor.authorGovind, N.R.
dc.contributor.authorRamesh, H.
dc.date.accessioned2026-02-05T09:28:10Z
dc.date.issued2020
dc.description.abstractThe 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. © 2020, Springer Nature Switzerland AG.
dc.identifier.citationEnvironmental Monitoring and Assessment, 2020, 192, 10, pp. -
dc.identifier.issn1676369
dc.identifier.urihttps://doi.org/10.1007/s10661-020-08601-x
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/23686
dc.publisherSpringer Science and Business Media Deutschland GmbH info@springer-sbm.com
dc.subjectAtmospheric temperature
dc.subjectCurve fitting
dc.subjectInverse problems
dc.subjectLand surface temperature
dc.subjectLinear regression
dc.subjectCircumferential direction
dc.subjectConcentric rings
dc.subjectGreen infrastructure
dc.subjectMetropolitan cities
dc.subjectMultiple linear regression models
dc.subjectNegative correlation
dc.subjectPositive correlations
dc.subjectRemotely sensed data
dc.subjectUrban growth
dc.subjectland cover
dc.subjectland surface
dc.subjectLandsat
dc.subjectmetropolitan area
dc.subjectMODIS
dc.subjectsemiarid region
dc.subjectspatial distribution
dc.subjectsurface temperature
dc.subjecttropical environment
dc.subjecturban climate
dc.subjecturban growth
dc.subjectaquatic environment
dc.subjectArticle
dc.subjectbarren density
dc.subjectconcentric ring approach
dc.subjectcooling
dc.subjectcorrelational study
dc.subjectdensity
dc.subjectenvironmental aspects and related phenomena
dc.subjectenvironmental impact
dc.subjectenvironmental parameters
dc.subjectgeographic and geological phenomena
dc.subjectgeographic distribution
dc.subjectheating
dc.subjectIndia
dc.subjectinverse s curve
dc.subjectland surface temperature
dc.subjectland use
dc.subjectmeasurement accuracy
dc.subjectparameterization
dc.subjectseasonal variation
dc.subjectsuburban area
dc.subjectsurface area
dc.subjecttemperature
dc.subjecturban density
dc.subjecturban expansion
dc.subjecturbanization
dc.subjectvegetation
dc.subjectvegetation density
dc.subjectwater density
dc.subjectcity
dc.subjectenvironmental monitoring
dc.subjectBengaluru
dc.subjectKarnataka
dc.subjectCities
dc.subjectEnvironmental Monitoring
dc.subjectTemperature
dc.subjectUrbanization
dc.titleExploring the relationship between LST and land cover of Bengaluru by concentric ring approach

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