This case study evaluates the seasonal variability of the Pearson's linear correlation coefficient of land surface temperature (LST) with some spectral indices like NDVI, NDWI, NDBI, and NDBaI by using a series of Landsat images for 1991–92, 1995–96, 1999–00, 2004–05, 2009–10, 2014–15, and 2018–19. The results from the average correlation of the entire period of all-season show that the LST builds a positive correlation with NDBI (0.71) and NDBaI (0.52) while it builds a negative correlation with NDVI (−0.44). The LST-NDWI correlation is insignificant. The best correlation is noticed in the post-monsoon period, while the least correlation is observed in the winter season. This study can support the environmental planning to build a sustainable city under a similar environment.
P. Fu, Q. Weng, A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery, Remote Sens. Environ. 175 (2016) 205-214.
N.B. Grimm, S.H. Faeth, N.E. Golubiewski, C.L. Redman, J. Wu, X. Bai, J.M. Briggs, N. Grimm, Global change and the ecology of cities, Science 319 (2008) 756-760.
D. Zhou, J. Xiao, S. Bonafoni, C. Berger, K. Deilami, Y. Zhou, S. Frolking, R. Yao, Z. Qiao, J.A. Sobrino, Satellite remote sensing of surface urban heat islands: progress, challenges, and perspectives, Rem. Sens. 11 (2019) 48.
S. Guha, H. Govil, M. Besoya, An investigation on seasonal variability between LST and NDWI in an urban environment using Landsat satellite data, Geomatics, Nat. Hazards Risk 11 (1) (2020a) 1319-1345, https://doi.org/10.1080/19475705.2020.1789762.
Q. Weng, Thermal infrared remote sensing for urban climate and environmental studies: methods, applications, and trends, ISPRS J Photogramm Sens 64 (2009) 335-344.
C.J. Tomlinson, L. Chapman, J.E. Trones, C. Baker, Remote sensing land surface temperature for meteorology and climatology: a review, Meteorol. Appl. 18 (2011) 296-306.
X. Hao, W. Li, H. Deng, The oasis effect and summer temperature rise in arid regions-case study in Tarim Basin, Sci. Rep. 6 (2016) 35418, https://doi.org/10.1038/srep35418.
D.X. Tran, F. Pla, P. Latorre-Carmona, S.W. Myint, M. Caetano, H.V. Kieu, Characterizing the relationship between land use land cover change and land surface temperature, ISPRS J Photogramm Sens 124 (2017) 119-132.
Z.N. Li, S.B. Duan, B.H. Tang, H. Wu, H.G. Ren, G.J. Yan, Review of methods for land surface temperature derived from thermal infrared remotely sensed data, J Remote Sens 20 (2016) 899-920.
R.C. Estoque, Y. Murayama, S.W. Myint, Effects of landscape composition and pattern on land surface temperature: an urban heat island study in the megacities of Southeast Asia, Sci. Total Environ. 577 (2017) 349-359.
S. Guha, H. Govil, N. Gill, A. Dey, A long-term seasonal analysis on the relationship between LST and NDBI using Landsat data, Quat. Int. (2020b), https://doi.org/10.1016/j.quaint.2020.06.041.
K.J. Gohain, P. Mohammad, A. Goswami, Assessing the impact of land use land cover changes on land surface temperature over Pune city, India, Quat. Int. 575–576 (2021) 259-269, https://doi.org/10.1016/j.quaint.2020.04.052.
X.L. Chen, H.M. Zhao, P.X. Li, Z.Y. Yi, Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes, Remote Sens. Environ. 104 (2) (2006) 133-146, https://doi.org/10.1016/j.rse.2005.11.016.
E. Kalnay, M. Cai, Impact of urbanization and land-use change on climate, Nat Cell Boil 423 (2003) 528-531.
J.A. Voogt, T.R. Oke, Thermal remote sensing of urban climates, Remote Sens. Environ. 86 (2003) 370-384. https://doi:10.1016/S0034-4257(03)00079-8.
S. Farooq, H. Govil, Mapping regolith and gossan for mineral exploration in the eastern kumaon himalaya, India using hyperion data and object oriented image classification, Adv. Space Res. 53 (12) (2013) 1676-1685.
A. Mondal, S. Guha, P.K. Mishra, S. Kundu, Land use/Land cover changes in Hugli Estuary using Fuzzy C-Mean algorithm, Int. J. Geomatics Geosci. 2 (2) (2011) 613-626.
S. Guha, Capability of NDVI technique in detecting mangrove vegetation, Int J Adv Biol Res 6 (2) (2016) 253-258.
S. Du, Z. Xiong, Y. Wang, L. Guo, Quantifying the multilevel effects of landscape composition and configuration on land surface temperature, Remote Sens. Environ. 178 (2016) 84-92.
C. Berger, J. Rosentreter, M. Voltersen, C. Baumgart, C. Schmullius, S. Hese, Spatio-Temporal analysis of the relationship between 2D/3D urban site characteristics and land surface temperature, Remote Sens. Environ. 193 (2017) 225-243.
B.J. He, Z.Q. Zhao, L.D. Shen, H.B. Wang, L.G. Li, B.J. He, An approach to examining performances of cool/hot sources in mitigating/enhancing land surface temperature under different temperature backgrounds based on Landsat 8 image, Sustain Cities Soc 44 (2019) 416-427.
T.N. Carlson, D.A. Ripley, On the relation between NDVI, fractional vegetation cover, and leaf area index, Remote Sens. Environ. 62 (1997) 241-252, https://doi.org/10.1016/S0034-4257(97)00104-1.
J.A. Sobrino, J.C. Jimenez-Munoz, L. Paolini, Land surface temperature retrieval from Landsat TM5, Remote Sens. Environ. 9 (2004) 434-440. https://doi:10.1016/j.rse.2004.02.003.
G. Gutman, A. Ignatov, The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models, Int. J. Rem. Sens. 19 (8) (1998) 1533-1543. https://doi:10.1080/014311698215333.
S. Guha, H. Govil, Land surface temperature and normalized difference vegetation index relationship: a seasonal study on a tropical city, SN Appl Sci 2 (2020a) 1661, https://doi.org/10.1007/s42452-020-03458-8.
S. Guha, H. Govil, Seasonal impact on the relationship between land surface temperature and normalized difference vegetation index in an urban landscape, Geocarto Int. (2020b). https://doi:10.1080/10106049.2020.1815867.
W. Essa, B. Verbeiren, J. Van der Kwast, T. Van de Voorde, O. Batelaan, Evaluation of the DisTrad thermal sharpening methodology for urban areas, Int. J. Appl. Earth Obs. Geoinf. 19 (2012) 163-172, https://doi.org/10.1016/j.jag.2012.05.010.
S. Guha, H. Govil, Relationship between land surface temperature and normalized difference water index on various land surfaces: a seasonal analysis, Int J Eng Geosci 6 (3) (2021b) 165-173, https://doi.org/10.26833/ijeg.821730.
A.K. Taloor, D.S. Manhas, G.C. Kothyari, Retrieval of land surface temperature, normalized difference moisture index, normalized difference water index of the Ravi basin using Landsat data, Appl Comp Geosci 9 (2021) 100051, https://doi.org/10.1016/j.acags.2020.100051.
Y. Zha, J. Gao, S. Ni, Use of normalized difference built-up index in automatically mapping urban areas from TM imagery, Int. J. Rem. Sens. 24 (3) (2003) 583-594, https://doi.org/10.1080/01431160304987.
H.M. Zhao, X.L. Chen, Use of normalized difference bareness index in quickly mapping bare areas from TM/ETM+, Geoscience and Remote Sensing Symposium 3 (25–29) (2005) 1666-1668, https://doi.org/10.1109/IGARSS.2005.1526319.
S. Guha, H. Govil, Annual Assessment on the Relationship between Land Surface Temperature and Six Remote Sensing Indices Using Landsat Data from 1988 to 2019, Geocarto Int. (2021a), https://doi.org/10.1080/10106049.2021.1886339.
D.A. Artis, W.H. Carnahan, Survey of emissivity variability in thermography of urban areas, Remote Sens. Environ. 12 (4) (1982) 313-329.
J.A. Sobrino, N. Raissouni, Z. Li, A comparative study of land surface emissivity retrieval from NOAA data, Remote Sens. Environ. 75 (2) (2001) 256-266, https://doi.org/10.1016/S0034-4257(00)00171-1.
Q.H. Weng, D.S. Lu, J. Schubring, Estimation of land surface temperature–vegetation abundance rela-tionship for urban heat island studies, Remote Sens. Environ. 89 (2004) 467-483. https://doi:10.1016/j.rse.2003.11.005.
H. Govil, S. Guha, A. Dey, N. Gill, Seasonal evaluation of downscaled land surface temperature: a case study in a humid tropical city, Heliyon 5 (6) (2019), e01923. https://doi:10.1016/j.heliyon.2019.e01923.
C.J. Tucker, Red and photographic infrared linear combinations for monitoring vegetation, Remote Sens. Environ. 8 (2) (1979) 127-150.
S.K. McFeeters, The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features, Int. J. Rem. Sens. 17 (7) (1996) 1425-1432, https://doi.org/10.1080/01431169608948714.
W. Yue, J. Xu, W. Tan, L. Xu, The relationship between land surface temperature and NDVI with remote sensing. Application to shanghai Landsat 7 ETM+ data, Int. J. Rem. Sens. 28 (2007) 3205-3226, https://doi.org/10.1080/01431160500306906.
F. Marzban, S. Sodoudi, R. Preusker, The influence of land-cover type on the relationship between LST-NDVI and LST-Tair, Int. J. Rem. Sens. 39 (5) (2018) 1377-1398, https://doi.org/10.1080/01431161.2017.1462386.
C. Wu, J. Li, C. Wang, C. Song, Y. Chen, M. Finka, D.L. Rosa, Understanding the relationship between urban blue infrastructure and land surface temperature, Sci. Total Environ. 694 (2019) 133742, https://doi.org/10.1016/j.scitotenv.2019.133742.
G. Nimish, H.A. Bharath, A. Lalitha, Exploring temperature indices by deriving relationship between land surface temperature and urban landscape, Remote Sens Appl Soc Environ 18 (2020) 100299, https://doi.org/10.1016/j.rsase.2020.100299.
T.D. Mushore, J. Odindi, T. Dube, O. Mutanga, Prediction of future urban surface temperatures using medium resolution satellite data in Harare metropolitan city, Zimbabwe, Build. Environ. 122 (2017) 397-410, https://doi.org/10.1016/j.buildenv.2017.06.033.