A Remotely Based Evaluation of Urban Expansion and its Impact in Land Surface Temperature: A Case Study of Ogbomoso
Land Surface Temperature (LST) is a fundamental environmental parameter affected by land cover change. Over the years, Ogbomoso had experienced a rapid urban expansion has led to the increase of its surface temperature. This paper, therefore, investigates the urban expansion and its impact on land surface temperature (LST) of Ogbomoso in Oyo state of Nigeria, using Land Satellite (Landsat) images from 1991 to 2019. This is with the view of assessing the extent of the land use and land cover (LC) in Ogbomoso and estimating its land surface temperature. The images were subjected to digital Image Processing (DIP) and analysed using ERDAS Imagine 2014 and ArcGIS 10.6 software. Using these spatio-temporal images with their thermal bands, land cover and LST changes, the spatial patterns of LST and LC were derived to examine the response of LST to urban growth. The findings of this study indicate that previously known rural areas such as Agegunle, Imoji, Alapa and part of Ogbomoso South in 1991 have become urbanized by year 2019, hence, an increase in the LST of these areas over time. Built-up areas such Ajegunle, Lautech and Jagun reported high increase in its surface temperature from about 27°C to about 33°c. This result further showed that new growth areas in Ogbomoso had altered the surface thermal environment. This study therefore, provides reasonable evidence of heating up of our environment.
Argüeso, D., Evans, J. P., Pitman, A. J., Di Luca, A. (2015). Effects of city expansion on heat stress under climate change conditions. PLoS one, 10(2), e0117066.
Butuc, B. R. and Moldovean, G., (2011). Environmental impact scenario of an azimuthal tracked PV platform based on CO2emissions reduction. Environmental Engineering and Management, 10, 271-276.
Cummings, S. (2007). An Analysis of Surface Temperature in San Antonio, Texas. Term Project. EES5053/ES4093: Remote Sensing, UTSA.
Deng, Y., Wang, S., Bai, X., Tian, Y., Wu, L., Xiao, J., Chen, F. and Qian, Q. (2018). Relationship among land surface temperature and LUCC, NDVI in typical karst area. Scientific reports, 8(1), 1-12.
El-Fadel, M., Ghanimeh, S., Maroun, R., and Alameddine, I. (2012). Climate change and temperature rise: Implications on food-and water-borne diseases. Science of the Total Environment, 437, 15-21.
Franc, G. B., and Cracknell, A. P. (1994). Retrieval of land and sea surface temperature using NOAA-11 AVHRR· data in north-eastern Brazil. International Journal of Remote Sensing, 15(8), 1695-1712.
Georgescu, M., Morefield, P. E., Bierwagen, B. G., and Weaver, C. P. (2014). Urban adaptation can roll back warming of emerging megapolitan regions. Proceedings of the National Academy of Sciences, 111(8), 2909-2914.
Howard, L. (2007). The Climate of London. IAUC edition available at www.lulu.com in two volumes.
Kumar, K. S., Bhaskar, P. U., and Padmakumari, K. (2012). Estimation of land surface temperature to study urban heat island effect using Landsat ETM+ image. International journal of Engineering Science and technology, 4(2), 771-778.
Landsberg, H. (1981). The Urban Climate. 1st Edition, Volume 28, ISBN: 9780124359604, Academic Press
Lillesand, T., Kiefer, R. and Chipman, J. (2004). Remote sensing and image interpretation. Chichester: John Wiley.
Makinde, E., & Agbor, C. (2019). Geoinformatic assessment of urban heat island and land use/cover processes: a case study from Akure. Environmental Earth Sciences, 78(15), 483.
Oguz, H. (2013). LST Calculator: a program for retrieving land surface temperature from Landsat TM/ETM+ imagery. Environmental Engineering and Management,12(3), 549 –555
Oke, T. R. (1982). The energetic basis of the urban heat island. Q J. R. Meteorol. Soc.108, 1–24.
Schott, J. R. and Volchok W. J. (1985). Thematic Mapper thermal infrared calibration, Photogramm. Eng. Remote Sensing, 51, 1351-1357
Ugur, S., Sarıışık, M., Türkoğlu, G., Erkan, G. and Erden, E. (2016), Layer by layer assembly of antibacterial inclusion complexes, International Journal of Clothing Science and Technology, 28(3), 368-377. https://doi.org/10.1108/IJCST-03-2016-0032
Weng, Q., Lu, D., and Schubring, J. (2004). Estimation of land surface temperature –vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467 –483.
Whitford, V., Victoria, E., and Handley, J. F. (2001). "City form and natural process" - Indicators for the ecological performance of urban areas and their application to Merseyside, UK. Landscape and Urban Planning. 57, 91-103. https://doi.org/10.1016/S0169-2046(01)00192-X.
Xiao, R., Ouyang, Z., Zheng, H., Li, W., Schienke, E., and Wang, X. (2007). Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China. Journal of environmental sciences (China). 19(2), 250-256. https://doi.org/10.1016/S1001-0742(07)60041-2.
Zareie, S., Khosravi, H., and Nasiri, A. (2016). Derivation of Land Surface Temperature from Landsat Thematic Mapper (TM) sensor data and analysing relation between Land Use changes and Surface Temperature. Solid Earth. Discuss. 1-15.