Estimation of land surface temperature for Coimbatore District using Landsat imagery
##plugins.themes.bootstrap3.article.main##
Abstract
The impact of climate change is visually witnessed in the present environment by various natural disasters. This phenomenon of land surface temperature is one of the significant aspects to be estimated for the study of climate change. The increase in Land Surface Temperature (LST) may be due to ongoing developments in the field of urbanization and globalization. The objective of the study was to estimate the increase in the LST in relation to the Normalized Difference Vegetation Index (NDVI) and assess the spatial variation in the LST due to land use/land cover change. The study utilized Landsat 8 data to assess the land-use changes and their relation with LST in one of the main urbanized cities, i.e. Coimbatore district of Tamil Nadu, using Landsat imagery due to the availability of various land cover types by using the mathematical expressions in ARCMAP software. This study compares the LST between 2015 and 2020 to observe the change in the NDVI and LST over a period of 5 years in the Coimbatore district. There was an increase of 1°C in 5 years and the area of high LST had been increased comparatively. The maximum LST was found to be 73°C in 2015, which increased to 74°C in the year 2020 ;and the minimum LST was found to be 15°C in 2015, which increased to 19°C in the year 2020 depicting the ongoing change in the land use of the district. The study findings will help promulgate sustainable urban land-use policies and can be used for mitigating climate change.
##plugins.themes.bootstrap3.article.details##
##plugins.themes.bootstrap3.article.details##
Keywords
Climate change, Land surface temperature, RS & GIS, Satellite images
References
Acharya, B. S., Hao, Y., Ochsner, T. E. & Zou, C. B. (2017). Woody plant encroachment alters soil hydrological properties and reduces downward flux of water in tallgrass prairie. Plant and Soil., 414(1), 379-391.
Adulkongkaew, T., Satapanajaru, T. Charoenhirunyingyos, S., & Singhirunnusorn, W. (2020). Effect of land cover composition and building configuration on land surface temperature in an urban-sprawl city, case study in Bangkok Metropolitan Area, Thailand. Heliyon., 6(8), e04485.
Ahmed, M., Else, B., Eklundh, L., Ardö, J. & Seaquist, J. (2017). Dynamic response of NDVI to soil moisture variations during different hydrological regimes in the Sahel region. International Journal of Remote Sensing., 38(19), 5408-5429.
Akhoondzadeh, M. & Saradjian, M. R. (2008). Comparison of land surface temperature mapping using MODIS and ASTER images in semiarid areas. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences., 37(B8), 873-876.
Aryalekshmi, B. N., Biradar, R. C. & Chandrasekar, K. (2020). Land Surface Temperature Estimation of Mandya district using LANDSAT-8 data. Journal of Applied Science and Engineering., 23(4), 583-591.
Dai Nguyen, V., Nguyen, H. H., Quyet, N. & Quang, P. D. (2021). Land surface temperature responses to vegetation and soil moisture index using Landsat-8 data in Luong Son District, Hoa Binh Province.
World Urbanization Prospects (2019). Department of Economic and Social Affairs, Population Division. World Urbanization Prospects: The 2018 Revision (ST/ESA/SER. A/420). New York: United Nations.
Estoque, R. C., Murayama, Y. & Myint, S. W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment., 577, 349-359.
Govind, N. R. & Ramesh, H. (2019). The impact of spatiotemporal patterns of land use land cover and land surface temperature on an urban cool island: a case study of Bengaluru. Environmental monitoring and assessment., 191(5), 1-20.
Guha, S., Govil, H., Dey, A., & Gill, N. (2018). Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy. European Journal of Remote Sensing., 51(1), 667-678.
Joshi, J. P. & Bhatt, B (2012) Estimating temporal land surface temperature using remote sensing: A study of Vadodara urban area, Gujarat. International Journal of Geology, Earth and Environmental Sciences., 2(1), 123-130.
Lim, H. S., Jafri. M, Abdullah, K. & Alsultan, S. (2012). Application of a simple mono window land surface temperature algorithm from Landsat ETM over Al Qassim, Saudi Arabia. SainsMalaysiana., 41 (7), 841-846.
Mukherjee, F. & Singh, D. (2020). Assessing land use–land cover change and its impact on land surface temperature using LANDSAT data: A comparison of two urban areas in India. Earth Systems and Environment., 4(2), 385-407.
Nikam, B. R., Ibragimov, F., Chouksey, A., Garg, V., & Aggarwal, S. P. (2016). Retrieval of land surface temperature from Landsat 8 TIRS for the command area of Mula irrigation project. Environmental Earth Sciences., 75(16), 1-17.
Pandapotan, J., Sugianto, S. & Darusman, D. (2016). Estimation of Carbon Stock Stands using EVI and NDVI Vegetation Index in Production Forest of LembahSeulawah Sub-District, Aceh Indonesia. Aceh Int. J. Sci.Tech., 5, 126-139.
Rajendran, P. & Mani, K (2015) Estimation of spatial variability of land surface temperature using Landsat 8 imagery. International Journal of Engineering and Science, 11(4), 19-23.
Rajeshwari, A. & Mani, N. D. (2014) Estimation of land surface temperature of Dindigul district using Landsat 8 data. International Journal of Research in Engineering and Technology., 3 (5): 122-126.
Roy, D.P., Wulder, M.A., Loveland, T.R., Woodcock, C.E., Allen, R.G., Anderson, M.C., Helder, D., Irons, J.R., Johnson, D.M., Kennedy, R., Scambos, T.A., Schaaf, C.B., Schott, J.R.,Sheng, Y., Vermote, E.F., Belward, A.S., Bindschadler, R., Cohen, W.B., Gao,F., Hipple, J.D., Hostert, P., Huntington, J., Justice, C.O., Kilic, A., Kovalskyy, V., Lee, Z.P., Lymburner, L., Masek, J.G., McCorkel, J., Shuai, Y., Trezza, R., Vogelmann, J., Wynne, R.H. & Zhu. Z. (2014). Landsat-8: Science and product vision for terrestrial global change research. Remote Sens. Environ., 145, 154–172.
Rozenstein, O., Qin, Z., Derimian, Y. & Karnieli, A. (2014). Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm. Sensors, 14(4), 5768-5780.
Sahana, M., Dutta, S. & Sajjad, H. (2019). Assessing land transformation and its relation with land surface temperature in Mumbai city, India using geospatial techniques. International Journal of Urban Sciences, 23(2), 205-225.
Salifu, T. & Agyare, W.A. (2012). Distinguishing Land use types using Surface Albedo and Normalized Vegetative Index Derived from the SEBAL Model for the Atankwidi and Afram Sub-Catchments in Ghana. ARPN J. Engg. App. Sci., 7(1), 69-80.
Sobrino, J. A., Jiménez-Muñoz, J. C., Sòria, G., Romaguera, M., Guanter, L., Moreno, J. & Martínez, P. (2008). Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE transactions on geoscience and remote sensing, 46(2), 316-327.
Suresh, S., Ajay, S. V. & Mani, K. (2016). Estimation of land surface temperature of high range mountain landscape of Devikulam Taluk using Landsat 8 data. International Journal of Research in Engineering and Technology, 5(1), 2321-7308.
Tran, D. X., Pla, F., Latorre-Carmona, P., Myint, S. W., Caetano, M. & Kieu, H. V. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119-132.
Walawender, J. P., Szymanowski, M., Hajto, M. J. & Bokwa, A. (2014). Land surface temperature patterns in the urban agglomeration of Krakow (Poland) derived from Landsat-7/ETM+ data. Pure and Applied Geophysics, 171(6), 913-940.
Zaitunah, A., Ahmad, A. G. & Safitri, R. A. (2018). Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia. In IOP Conference Series: Earth and Environmental Science (Vol. 126, No. 1, p. 012112). IOP Publishing.
Zhan, Z. Z., Liu, H. B., Li, H. M., Wu, W. & Zhong, B. (2012). The relationship between NDVI and terrain factors--a case study of Chongqing. Procedia Environmental Sciences, 12, 765-771.
Zhou, G., Wang, H., Chen, W., Zhang, G., Luo, Q. & Jia, B. (2020). Impacts of Urban land surface temperature on tract landscape pattern, physical and social variables. International Journal of Remote Sensing., 41(2), 683-703.
Adulkongkaew, T., Satapanajaru, T. Charoenhirunyingyos, S., & Singhirunnusorn, W. (2020). Effect of land cover composition and building configuration on land surface temperature in an urban-sprawl city, case study in Bangkok Metropolitan Area, Thailand. Heliyon., 6(8), e04485.
Ahmed, M., Else, B., Eklundh, L., Ardö, J. & Seaquist, J. (2017). Dynamic response of NDVI to soil moisture variations during different hydrological regimes in the Sahel region. International Journal of Remote Sensing., 38(19), 5408-5429.
Akhoondzadeh, M. & Saradjian, M. R. (2008). Comparison of land surface temperature mapping using MODIS and ASTER images in semiarid areas. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences., 37(B8), 873-876.
Aryalekshmi, B. N., Biradar, R. C. & Chandrasekar, K. (2020). Land Surface Temperature Estimation of Mandya district using LANDSAT-8 data. Journal of Applied Science and Engineering., 23(4), 583-591.
Dai Nguyen, V., Nguyen, H. H., Quyet, N. & Quang, P. D. (2021). Land surface temperature responses to vegetation and soil moisture index using Landsat-8 data in Luong Son District, Hoa Binh Province.
World Urbanization Prospects (2019). Department of Economic and Social Affairs, Population Division. World Urbanization Prospects: The 2018 Revision (ST/ESA/SER. A/420). New York: United Nations.
Estoque, R. C., Murayama, Y. & Myint, S. W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment., 577, 349-359.
Govind, N. R. & Ramesh, H. (2019). The impact of spatiotemporal patterns of land use land cover and land surface temperature on an urban cool island: a case study of Bengaluru. Environmental monitoring and assessment., 191(5), 1-20.
Guha, S., Govil, H., Dey, A., & Gill, N. (2018). Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy. European Journal of Remote Sensing., 51(1), 667-678.
Joshi, J. P. & Bhatt, B (2012) Estimating temporal land surface temperature using remote sensing: A study of Vadodara urban area, Gujarat. International Journal of Geology, Earth and Environmental Sciences., 2(1), 123-130.
Lim, H. S., Jafri. M, Abdullah, K. & Alsultan, S. (2012). Application of a simple mono window land surface temperature algorithm from Landsat ETM over Al Qassim, Saudi Arabia. SainsMalaysiana., 41 (7), 841-846.
Mukherjee, F. & Singh, D. (2020). Assessing land use–land cover change and its impact on land surface temperature using LANDSAT data: A comparison of two urban areas in India. Earth Systems and Environment., 4(2), 385-407.
Nikam, B. R., Ibragimov, F., Chouksey, A., Garg, V., & Aggarwal, S. P. (2016). Retrieval of land surface temperature from Landsat 8 TIRS for the command area of Mula irrigation project. Environmental Earth Sciences., 75(16), 1-17.
Pandapotan, J., Sugianto, S. & Darusman, D. (2016). Estimation of Carbon Stock Stands using EVI and NDVI Vegetation Index in Production Forest of LembahSeulawah Sub-District, Aceh Indonesia. Aceh Int. J. Sci.Tech., 5, 126-139.
Rajendran, P. & Mani, K (2015) Estimation of spatial variability of land surface temperature using Landsat 8 imagery. International Journal of Engineering and Science, 11(4), 19-23.
Rajeshwari, A. & Mani, N. D. (2014) Estimation of land surface temperature of Dindigul district using Landsat 8 data. International Journal of Research in Engineering and Technology., 3 (5): 122-126.
Roy, D.P., Wulder, M.A., Loveland, T.R., Woodcock, C.E., Allen, R.G., Anderson, M.C., Helder, D., Irons, J.R., Johnson, D.M., Kennedy, R., Scambos, T.A., Schaaf, C.B., Schott, J.R.,Sheng, Y., Vermote, E.F., Belward, A.S., Bindschadler, R., Cohen, W.B., Gao,F., Hipple, J.D., Hostert, P., Huntington, J., Justice, C.O., Kilic, A., Kovalskyy, V., Lee, Z.P., Lymburner, L., Masek, J.G., McCorkel, J., Shuai, Y., Trezza, R., Vogelmann, J., Wynne, R.H. & Zhu. Z. (2014). Landsat-8: Science and product vision for terrestrial global change research. Remote Sens. Environ., 145, 154–172.
Rozenstein, O., Qin, Z., Derimian, Y. & Karnieli, A. (2014). Derivation of land surface temperature for Landsat-8 TIRS using a split window algorithm. Sensors, 14(4), 5768-5780.
Sahana, M., Dutta, S. & Sajjad, H. (2019). Assessing land transformation and its relation with land surface temperature in Mumbai city, India using geospatial techniques. International Journal of Urban Sciences, 23(2), 205-225.
Salifu, T. & Agyare, W.A. (2012). Distinguishing Land use types using Surface Albedo and Normalized Vegetative Index Derived from the SEBAL Model for the Atankwidi and Afram Sub-Catchments in Ghana. ARPN J. Engg. App. Sci., 7(1), 69-80.
Sobrino, J. A., Jiménez-Muñoz, J. C., Sòria, G., Romaguera, M., Guanter, L., Moreno, J. & Martínez, P. (2008). Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE transactions on geoscience and remote sensing, 46(2), 316-327.
Suresh, S., Ajay, S. V. & Mani, K. (2016). Estimation of land surface temperature of high range mountain landscape of Devikulam Taluk using Landsat 8 data. International Journal of Research in Engineering and Technology, 5(1), 2321-7308.
Tran, D. X., Pla, F., Latorre-Carmona, P., Myint, S. W., Caetano, M. & Kieu, H. V. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119-132.
Walawender, J. P., Szymanowski, M., Hajto, M. J. & Bokwa, A. (2014). Land surface temperature patterns in the urban agglomeration of Krakow (Poland) derived from Landsat-7/ETM+ data. Pure and Applied Geophysics, 171(6), 913-940.
Zaitunah, A., Ahmad, A. G. & Safitri, R. A. (2018). Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia. In IOP Conference Series: Earth and Environmental Science (Vol. 126, No. 1, p. 012112). IOP Publishing.
Zhan, Z. Z., Liu, H. B., Li, H. M., Wu, W. & Zhong, B. (2012). The relationship between NDVI and terrain factors--a case study of Chongqing. Procedia Environmental Sciences, 12, 765-771.
Zhou, G., Wang, H., Chen, W., Zhang, G., Luo, Q. & Jia, B. (2020). Impacts of Urban land surface temperature on tract landscape pattern, physical and social variables. International Journal of Remote Sensing., 41(2), 683-703.
Section
Research Articles
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This work is licensed under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) © Author (s)
How to Cite
Estimation of land surface temperature for Coimbatore District using Landsat imagery. (2022). Journal of Applied and Natural Science, 14(SI), 8-15. https://doi.org/10.31018/jans.v14iSI.3557
