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Land Surface Temperature and Thermal Radiation Estimate from Remote Sensed Data: Implications for Human Health in Owo, Ondo State, Nigeria

The use of remote sensing data to study the spatial distribution of land surface temperature (LST) and thermal radiation has revealed the negative impact of urban heat islands on human health. As an increase in LST and thermal radiation can have serious health consequences, it is important to constantly evaluate and gather information on the extent of these changes in a given region. Such information is crucial for public health and environmental epidemiology, as it enables emergency response planners and public health specialists to identify the areas most at risk and use scientific findings to improve the health of the affected populations. Remote sensing data from the Landsat Thematic Mapper (LANDSAT 7) image of 2002 and the Operational Land Imager and Thermal Infrared Sensor (LANDSAT 8) images of 2014 and 2018 were utilized to estimate the spatial distribution of land surface temperature and thermal radiation in Owo, Ondo State, Nigeria. The study found that the rapid urbanization and modification of the vegetation cover and natural surfaces in Owo had contributed to an increase in land surface temperature and thermal radiation. The research also noted that areas with low vegetation cover had higher surface temperatures, while areas with high vegetation cover had lower surface temperatures. Additionally, the study found that areas with higher surface temperatures were associated with increased thermal radiation, following a similar pattern to that of the spatial distribution of land surface temperature. In particular, regions with higher land surface temperatures emitted more thermal radiation compared to regions with lower land surface temperatures. The results of this study can provide valuable insights for the public health department of Ondo State in terms of understanding, managing, and taking action to improve the health and well-being of residents, particularly those residing in areas that are most impacted by the urban heat island effect.

Land Surface Temperature, Thermal Radiation, Remote Sensing, Human Health

Oluwadare Ayoola Olamitomi, Oluwadare Esolomo John, Olofin Emmanuel Oluwafemi. (2023). Land Surface Temperature and Thermal Radiation Estimate from Remote Sensed Data: Implications for Human Health in Owo, Ondo State, Nigeria. Journal of Health and Environmental Research, 9(2), 67-75.

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Effat, H. A. and Hassan, O. A. K. (2014). Change detection of urban heat islands and some related parameters using multi-temporal Landsat images; a case study of Cairo city, Egypt. Urban Climate, 10: 171-188.
2. Voogt, J. A. and Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote Sens Environ, vol. 86, pp. 370–384.
3. Akinbode, O. M., Eludoyin, A. O. and Fashae, O. A. (2008). Temperature and relative humidity distributions in a medium-size administrative town in southwest Nigeria. Journal of Environmental Management, 87: 95–105.
4. Yue, W., Xu, J., Tan, W. and Xu, L. (2007). The relationship between land surface temperature and NDVI with remote sensing: Application to Shanghai Landsat 7 ETM+ data. Int. J. Remote Sens, vol. 28, pp. 3205–3226.
5. Singh, R. B., Grover, A. and Zhan, J. (2014). Inter-Seasonal Variations of Surface Temperature in the Urbanized Environment of Delhi Using Landsat Thermal Data. Energie, vol. 7, pp. 1811–1828.
6. Ige, S. O., Ajayi, V. O., Adeyeri, O. E. and Oyekan, K. S. (2017). Assessing remotely sensed temperature humidity index as human comfort indicator relative to landuse landcover change in Abuja, Nigeria. Spat Inf Res, 25 (4) 523–533.
7. Weng, Q., Lu, D. and Schubring J. (2004). Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sens Environ, 89 (4), 467–483.
8. Orimoloye, I. R., Mazinyo, S. P., Nel, W. and Kalumba, A. M. (2018). Spatiotemporal monitoring of land surface temperature and estimated radiation using remote sensing: human health implications for East London South Africa. Enviromental. Earth Sciences. 77 (3), 1-10.
9. Oluwadare A. O., Oluwadare E. J. and Fagbemi S. (2019). Satellite Derived Estimate of Land Surface Temperature and Thermal Radiation: Human Health Implication for Akure, Ondo State, Nigeria. Journal of the Nigerian Association of Mathematical Physics. Vol. 50, pp. 303–310.
10. Tan, T., Zheng, Y. and Tang, X. (2010). The urban heat island and its impact on heat waves and human health in Shanghai. Int J Biometeorol 54, 75–84.
11. Tursilowati, L. and Djundjunan, J. D. (2007). Use of remote sensing and GIS to compute temperature humidity index as human comfort indicator relate with land use-land cover change (LULC) in Surabaya. Proceedings of the 73rd international symposium on sustainable Humanosphere, Bandung, Indonesia, pp. 160-166.
12. Peng, S. S., Piao, S., Zeng, Z., Ciais, P., Zhou, L., Li, L. Z. and Zeng H. (2014). Afforestation in China cools local land surface temperature. Proc Natl Acad Sci, 111 (8), 2915–2919.
13. Cheong, K. W. D., Djunaedy, E., Chua, Y. L., Tham, K. W., Sekhar, S. C. and Wong N. H. (2003). Thermal comfort study of an air-conditioned lecture theatre in the tropics. Building and Environment, 38 (1) 63–73.
14. Xu, H., Hu, X., Guan, H. and He, G. (2017). Development of a fine-scale discomfort index map and its application in measuring living environments using remotely-sensed thermal infrared imagery. Energy Build, vol. 150, pp. 598–607.
15. Oluwadare, A. O., Okogbue, E. C., Kunstmann, H., Akinluyi, F., Arnault, J., Tayari, S., Hingerl, L. and Bliefernicht J. (2018). Comparison of Sebal Estimated Heat Fluxes and Evapotranspiration using Field and Remote Sensing Data in the Sudanian Savanna in West Africa. International Journal of agriculture and Environmental Research, 4 (2) 352–374.
16. Emmanuel Oluwafemi Olofin and Ayoola Olamitomi Oluwadare (2022). Settlement Growth and Its Impact on Land Surface Temperature in Ado-Ekiti, Ekiti State, Nigeria. Frontiers, 2 (2) Vol. 2, No. 2, pp. 88-97. doi: 10.11648/j.frontiers.20220202.12.
17. Adeola, A. M., Botai, J. O., Rautenbach, C. D., Kalumba, A. M., Tsela, P. L. and Adisa O. M. (2017). Landsat satellite derived environmental metric for mapping mosquitoes breeding habitats in the Nkomazi municipality, Mpumalanga Province, South Africa. South African Geographical Journal, Suid-Afrikaanse Geografiese Tydskrif, 99 (1) 14–28.
18. Eke, E. E., Oyinloye, M. A. and Olamiju, I. O. (2017). Analysis of the Urban Expansion for the Akure, Ondo State, Nigeria. International Letters of Social and Humanistic Sciences, vol. 75, pp. 41–55. doi: 10.18052/
19. Johnson, D. P. and Wilson, J. S. (2009). The socio-spatial dynamics of extreme urban heat events: The case of heat-related deaths in Philadelphia. Appl Geogr, vol. 29, no. 3, pp. 419–434.
20. Akeju Tolulope J., Oladehinde Gbenga J. and Abubakar Kasali (2018). An Analysis of Willingness to Pay (WTP) for Improved Water Supply in Owo Local Government, Ondo State, Nigeria. Asian Research Journal of Arts & Social Sciences, 5 (3): 1-15.
21. National Population Commission (NPC), The 1991 and 2006 Population Census Reports.
22. Chander, C. and Markham H. (2003). Revised Landsat-5 TM radio- metric calibration procedures and post-calibration dynamic ranges, IEEE Trans Geosci Remote, vol. 41, pp. 2674–2677.
23. USGS. Using the USGS Landsat Level-1 Data Product. Accessed from in May 2022
24. Allen, R. G., Pereira, L. A., Raes, D. and Smith, M. (1998). Crop evapotranspiration guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper No. 56, FAO, Rome.
25. Bastiaanssen, W. G. M, Menenti, C., Feddes, R. A. and Holtslag, A. A. M. (1998). A remote sensing surface energy balance algorithm for land (SEBAL), Part I Formulation. Journal of Hydrology, vol. 212-213, pp. 198–212.
26. Tasumi, M., Allen, R. G. and Bastiaanssen W. G. M. (2000). The theoretical basis of SEBAL, Application of the SEBAL methodology for estimating consumptive use of water and stream flow depletion in the Bear River Basin of Idaho through remote sensing. Raytheon Systems Company, Earth Observation System Data and Information System Project, pp. 46–69.
27. Olofin, E. O. and Adebayo, W. O. (2017). Effects of Deforestation on Land Degradation. Saarbrucken, Germany. LAMBERT Academic Publishing, 63.
28. Wang, C., Myint, S. W., Wang, Z. and Song J. (2016). Spatio-temporal modeling of the urban heat island in the Phoenix metropolitan area: land use change implications. Remote Sens Environ, 8 (3): 185.
29. Hu, X., Zhou, W., Qian, Y. and Yu W. (2017). Urban expansion and local landcover change both significantly contribute to urban warming, but their relative importance changes over time. Landsc Ecol, vol. 32, pp. 763–780.
30. Wilker, E. H., Yeh, G., Wellenius, G. A., Davis, R. B., Phillips, R. S. and Mittleman, M. A. (2012). Ambient temperature and biomarkers of heart failure: a repeated measures analysis. Environ Health Perspect, 120 (8) 1083-7.
31. Crimmins, A., Balbus, J., Gamble, J. L., Beard, C. B., Bell, J. E., Dodgen, D., Eisen, R. J., Fann, N., Hawkins, M. D., Herring, S. C., Jantarasami, L., Mills, D. M., Saha, S., Sarofim, M. C., Trtanj, J. and Ziska L. (2016). Impacts of Climate Change on Human Health in the United States: A Scientific Assessment. U. S Global Change Research Program, Washington, DC, 312 pp.
32. Patz, J., Lendrum, D. C., Holloway, T. and Foley J. (2005). Impact of regional climate change on human health. Nature, vol. 438, pp. 310–317.
33. Ropo, O. I., Perez, M. S., Werner, N. and Enoch, T. I. (2017). Climate variability and heat stress index have increasing potential III-health and environmental impacts in the East London, South Africa. Int J Appl Eng Res, 12 (17) 6910–6918.
34. Oke T. R. (1978). Boundary layer climates. Methuen & Co., London.
35. Shuttleworth W. J. (2012). Terrestrial Hydrometeorology. First edition, published by John Wisel & Sons, Ltd, pp. 51–63.
36. Environmental Protection Agency (2010). Methane and Nitrous Oxide Emissions from Natural Sources. Washington, DC: US Environmental Protection Agency.
37. Spickett, J. T., Brown, H. L. and Rumchev K. (2011). Climate change and air quality: the potential impact on health. Asia Pac J Public Health, 23 (2): 37S–45.
38. Olabode Abiodun Daniel (2015). Urban Extreme Weather: A Challenge for a Healthy Living Environment in Akure, Ondo State, Nigeria. Climate, vol. 3, pp. 775–791. doi: 10.3390/cli3040775.