Retrieval of Land Surface Temperature from Landsat-8 Thermal Infrared Sensor Data

Deepak Kumar, Anupriya Soni, Manish Kumar

Abstract


Remote sensing technology can be said to be an eye in the sky which provides detailed information on various parameters of the Earth, including climatic, vegetative, and forest variables. For many years, Landsat 8 has been used to study various natural phenomena on Earth. In the present study, Landsat 8 imagery has been used to retrieve land surface temperature (LST). For retrieving LST, TIRS (Thermal Infra-Red Sensor) Spectral Bands have been used. The LST map of Udhamsingh Nagar in Uttarakhand, India has been further prepared for the period 2018 to 2021 for the month of October. The result suggested that for the study area, LST varies from 24 oC to 39 oC for the month of October in the aforesaid study period. High temperatures have been observed in built-up areas like towns and residential areas, whereas in agricultural fields and forests, the LST is lower as compared to human-induced built-up areas. Further, the southeastern part of Udhamsingh Nagar has higher LST as compared to other regions of the study area.

 

Doi: 10.28991/HEF-2022-03-02-02

Full Text: PDF


Keywords


Landsat-8; Land Surface Temperature; Udhamsingh Nagar; TIRS.

References


Deoli, V., Kumar, D., Kumar, M., Kuriqi, A., & Elbeltagi, A. (2021). Water spread mapping of multiple lakes using remote sensing and satellite data. Arabian Journal of Geosciences, 14(21), 1–15. doi:10.1007/s12517-021-08597-9.

Deoli, V., & Kumar, D. (2020). Analysis of groundwater fluctuation using GRACE satellite data. Indian Journal of Ecology, 47(2), 299–302.

Kumar, D., Adamowski, J., Suresh, R., & Ozga-Zielinski, B. (2016). Estimating Evapotranspiration Using an Extreme Learning Machine Model: Case Study in North Bihar, India. Journal of Irrigation and Drainage Engineering, 142(9), 04016032. doi:10.1061/(asce)ir.1943-4774.0001044.

Kumar, M., Kumari, A., Kumar, D., Al-Ansari, N., Ali, R., Kumar, R., Kumar, A., Elbeltagi, A., & Kuriqi, A. (2021). The superiority of data-driven techniques for estimation of daily pan evaporation. Atmosphere, 12(6), 701. doi:10.3390/atmos12060701.

Niclòs, R., Valiente, J. A., Barberà, M. J., Estrela, M. J., Galve, J. M., & Caselles, V. (2009). Preliminary results on the retrieval of land surface temperature from MSG-SEVIRI data in Eastern Spain. EUMETSAT 2009: Proceedings of Meteorological Satellite Conference, January, 21–25, Darmstadt, Germany.

Prabhakara, C., Dalu, G., & Kunde, V. G. (1974). Estimation of sea surface temperature from remote sensing in the 11- to 13-μm window region. Journal of Geophysical Research, 79(33), 5039–5044. doi:10.1029/jc079i033p05039.

Idso, S. B., Reginato, R. J., & Jackson, R. D. (1977). Albedo measurement for remote sensing of crop yields. Nature, 266(5603), 625–628. doi:10.1038/266625a0.

Courel, M. F., Kandel, R. S., & Rasool, S. I. (1984). Surface albedo and the sahel drought. Nature, 307(5951), 528–531. doi:10.1038/307528a0.

Norman, J. M., Divakarla, M., & Goel, N. S. (1995). Algorithms for extracting information from remote thermal-IR observations of the earth’s surface. Remote Sensing of Environment, 51(1), 157–168. doi:10.1016/0034-4257(94)00072-U.

Pelgrum, H., Schmugge, T., Rango, A., Ritchie, J., & Kustas, B. (2000). Length-scale analysis of surface albedo, temperature, and normalized difference vegetation index in desert grassland. Water Resources Research, 36(7), 1757–1765. doi:10.1029/2000WR900028.

Stroeve, J. C., Box, J. E., Fowler, C., Haran, T., & Key, J. (2001). Intercomparison between in situ and AVHRR polar pathfinder-derived surface albedo over Greenland. Remote Sensing of Environment, 75(3), 360–374. doi:10.1016/S0034-4257(00)00179-6.

Crow, W. T., & Wood, E. F. (2003). The assimilation of remotely sensed soil brightness temperature imagery into a land surface model using Ensemble Kalman filtering: A case study based on ESTAR measurements during SGP97. Advances in Water Resources, 26(2), 137–149. doi:10.1016/S0309-1708(02)00088-X.

Kay, J. E., Gillespie, A. R., Hansen, G. B., & Pettit, E. C. (2003). Spatial relationships between snow contaminant content, grain size, and surface temperature from multispectral images of Mt. Rainier, Washington (USA). Remote Sensing of Environment, 86(2), 216–231. doi:10.1016/S0034-4257(03)00102-0.

Sun, Y. J., Wang, J. F., Zhang, R. H., Gillies, R. R., Xue, Y., & Bo, Y. C. (2005). Air temperature retrieval from remote sensing data based on thermodynamics. Theoretical and Applied Climatology, 80(1), 37–48. doi:10.1007/s00704-004-0079-y.

Sturm, M., Douglas, T., Racine, C., & Liston, G. E. (2005). Changing snow and shrub conditions affect albedo with global implications. Journal of Geophysical Research, 110(G1). doi:10.1029/2005jg000013.

Yuan, F., & Bauer, M. E. (2007). Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of Environment, 106(3), 375–386. doi:10.1016/j.rse.2006.09.003.

Hall, D. K., Nghiem, S. V., Schaaf, C. B., DiGirolamo, N. E., & Neumann, G. (2009). Evaluation of surface and near-surface melt characteristics on the Greenland ice sheet using MODIS and QuikSCAT data. Journal of Geophysical Research: Earth Surface, 114(4). doi:10.1029/2009JF001287.

Holmes, T. R. H., De Jeu, R. A. M., Owe, M., & Dolman, A. J. (2009). Land surface temperature from Ka band (37 GHz) passive microwave observations. Journal of Geophysical Research Atmospheres, 114(4). doi:10.1029/2008JD010257.

Patel, P. P. (2009). Estimation of Land Surface Temperature from Landsat Thermal Images towards Urban Heat Island Mapping of Kolkata. Asian Studies, 9(2), 110–200.

Qin, Z., Karnieli, A., & Berliner, P. (2001). A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing, 22(18), 3719–3746. doi:10.1080/01431160010006971.

Liang, S., Liang, S., Zhang, X., Wang, K., Zhang, X., & Wild, M. (2010). Review on Estimation of Land Surface Radiation and Energy Budgets From Ground Measurement, Remote Sensing and Model Simulations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(3), 225–240. doi:10.1109/JSTARS.2010.2048556.

Tedesco, M., Fettweis, X., van den Broeke, M. R., van de Wal, R. S. W., Smeets, C. J. P. P., van de Berg, W. J., … Box, J. E. (2011). The role of albedo and accumulation in the 2010 melting record in Greenland. Environmental Research Letters, 6(1), 014005. doi:10.1088/1748-9326/6/1/014005.

Niclos, R., Valiente, J. A., Barbera, M. J., & Caselles, V. (2014). Land surface air temperature retrieval from EOS-MODIS images. IEEE Geoscience and Remote Sensing Letters, 11(8), 1380–1384. doi:10.1109/LGRS.2013.2293540.

Rajeshwari, A., and 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. doi:10.15623/ijret.2014.0305025.

Sharma, R., Chakraborty, A., & Joshi, P. K. (2015). Geospatial quantification and analysis of environmental changes in urbanizing city of Kolkata (India). Environmental Monitoring and Assessment, 187(1), 4206. doi:10.1007/s10661-014-4206-7.

Ayad Ali Faris Beg, Ahmed H. Al-Sulttani, Adrian Ochtyra, Anna Jarocińska, & Adriana Marcinkowska. (2016). Estimation of Evapotranspiration Using SEBAL Algorithm and Landsat-8 Data—A Case Study: Tatra Mountains Region. Journal of Geological Resource and Engineering, 4(6), 257–270. doi:10.17265/2328-2193/2016.06.002.

Ytre-Eide, M., Christensen, T., Johnsen Istad, T. S., Nilsen, L. T., & Johnsen, B. (2017). Modeling Effective Albedo as a Function of Land Cover Type and Snow Type. In Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings 17(1): 10. doi:10.7275/R5FJ2F07.

Anandababu, D., Purushothaman, B.M., and Babu, S.S. (2018). Estimation of Land Surface Temperature using LANDSAT 8 Data. IJARIIT, 4(2), 312-350.

Bosco, N. J., & Thomas, M. (2019). Land Surface Temperature Analysis of Kigali City. Current Journal of Applied Science and Technology, 32(2), 1–11. doi:10.9734/cjast/2019/45426.

Winton, M. (2006). Amplified Arctic climate change: What does surface albedo feedback have to do with it? Geophysical Research Letters, 33(3). doi:10.1029/2005GL025244.

Peng, J., Fan, W., Xu, X., Wang, L., Liu, Q., Li, J., & Zhao, P. (2015). Estimating crop Albedo in the application of a physical model based on the law of energy conservation and spectral invariants. Remote Sensing, 7(11), 15536–15560. doi:10.3390/rs71115536.

Sánchez, J. M., Caselles, V., Niclòs, R., Coll, C., & Kustas, W. P. (2009). Estimating energy balance fluxes above a boreal forest from radiometric temperature observations. Agricultural and Forest Meteorology, 149(6–7), 1037–1049. doi:10.1016/j.agrformet.2008.12.009.

Tang, R., Li, Z. L., Jia, Y., Li, C., Chen, K. S., Sun, X., & Lou, J. (2013). Evaluating one- and two-source energy balance models in estimating surface evapotranspiration from Landsat-derived surface temperature and field measurements. International Journal of Remote Sensing, 34(9–10), 3299–3313. doi:10.1080/01431161.2012.716529.


Full Text: PDF

DOI: 10.28991/HEF-2022-03-02-02

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Deepak Kumar, Anupriya Soni, Manish Kumar