Ibadan has experienced a rapid urbanization over the past few decades due to heavy influx of people from different parts of the country as a result of improved economy of the region. This development induced a great change in land use and land cover over the region which has become a major environmental concern recently. This study assessed Land Surface Temperature (LST) and its spatio-temporal relationship with land cover type over Ibadan. Land use/Land cover dynamics were assessed using index maps generated from Landsat Satellite data (TM, ETM+ and OLI) of Ibadan. The corrected thermal Infrared bands of the Landsat data were used to retrieve LST. The results revealed a notable increase in built-up areas from 5.64% of the total land cover area in 1984 to 14.05% in 2014. This change has caused increase in surface temperature of Ibadan from 3.56?C to 8.54?C between 1984 and 2014 respectively. The study recorded a continuous decrease in the vegetal part of Ibadan (from 43.28% in 1984 to 14.76 in 2014) which could be attributed to anthropogenic activities as the vegetated land area lost was been converted to other form of land use. The change was found to be positively correlated to the surface temperature intensity over the region with correlation coefficient, r value of 0.9251, 0.8256 and 0.7017 in 1984, 2000 and 2014 respectively. It is recommended that Policies should be considered for planting trees, new guidelines for urban landscape design and construction.
References
[1]
Kafi, K.M., Shafri, H.Z.M. and Shariff, A.B.M. (2014) An Analysis of LULC Change Detection Using Remotely Sensed Data; A Case Study of Bauchi City. IOP Conference Series: Earth and Environmental Science, 20, 12-56.
[2]
Landsberg, H.E. (1981) The Urban Climate. Academic Press, New York.
[3]
Denman, K.L., Brasseur, G., Chidthaisong, A., Ciais, P., Cox, P.M. and Dickinson, R.E. (2007) Couplings between Changes in the Climate System and Biogeochemistry. In: Solomon, S., Qin, D. and Manning, M., Eds., Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the 4th Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, 499-587.
[4]
Bonan, G.B. (2008) Forests and Climate Change: Forcings, Feedbacks and the Climate Benefits of Forests. Science, 320, 1444-1449. https://doi.org/10.1126/science.1155121
[5]
McCarthy, M.P., Best, M.J. and Betts, R.A. (2010) Climate Change in Cities Due to Global Warming and Urban Effects. Geophysical Research Letters, 37, L09705. https://doi.org/10.1029/2010GL042845
[6]
Weng, Y.C. (2007) Spatiotemporal Changes of Landscape Pattern in Response to Urbanization. Landscape and Urban Planning, 81, 341-353. https://doi.org/10.1016/j.landurbplan.2007.01.009
[7]
Turkoglu, N. (2010) Analysis of Urban Effects on Soil Temperature in Ankara. Environmental Monitoring and Assessment, 169, 439-450. https://doi.org/10.1007/s10661-009-1187-z
[8]
Mosammam, H.M., Nia, J.T., Khani, H., Teymouri, A. and Kazemi, M. (2016) Monitoring Land Use Change and Measuring Urban Sprawl Based on Its Spatial Forms: The Case of Qom City. The Egyptian Journal of Remote Sensing and Space Science, 20, 103-116. https://doi.org/10.1016/j.ejrs.2016.08.002
[9]
Weng, Q., Lub, D. and Schubring, J. (2004) Estimation of Land Surface Temperature-Vegetation Abundance Relationship for Urban Heat Island Studies. Remote Sensing of Environment, 89, 467-483. https://doi.org/10.1016/j.rse.2003.11.005
[10]
Khandelwal, S., Goyal, R. and Mathew, A. (2017) Assessment of Land Surface Temperature Variation Due to Change in Elevation of Area Surrounding Jaipur, India. The Egyptian Journal of Remote Sensing and Space Science, 21, 87-94. https://doi.org/10.1016/j.ejrs.2017.01.005
[11]
Oluseyi, O.F. (2006) Urban Land Use Change Analysis of a Traditional City from Remote Sensing Data: The Case of Ibadan Metropolitan Area, Nigeria. Humanities and Social Sciences Journal, 1, 42-64.
[12]
Pu, R., Gong, P., Michishita, R. and Sasagawa, T. (2006) Assessment of Multi-Resolution and Multi-Sensor Data for Urban Surface Temperature Retrieval. Remote Sensing of Environment, 104, 211-225. https://doi.org/10.1016/j.rse.2005.09.022
[13]
Voogt, J.A. and Oke, T.R. (2003) Thermal Remote Sensing of Urban Climates. Remote Sensing of Environment, 86, 370-384. https://doi.org/10.1016/S0034-4257(03)00079-8
[14]
Running, S.W., Justice, C., Salomonson, V., Hall, D., Braker, J., Kaufman, Y., Strahler, A., Huete, A., Muller, J.P., Vanderbilt, V., Wan, Z. and Teillet, P. (1994) Terrestrial Remote Sensing Science and Algorithms Planned for EOS/MODIS. International Journal of Remote Sensing, 15, 3587-3620. https://doi.org/10.1080/01431169408954346
[15]
Vining, R.C. and Blad, B.L. (1992) Estimation of Sensible Heat Flux from Remotely Sensed Canopy Temperatures. Journal of Geophysical Research, 97, 18951-18954. https://doi.org/10.1029/92JD01626
[16]
Diak, G.R. and Whipple, M.S. (1995) Note on Estimating Surface Sensible Heat Fluxes Using S, L Measured from a Geostationary Satellite during FIFE 1989. Journal of Geophysical Research, 100, 25453-25461. https://doi.org/10.1029/95JD00729
[17]
Crago, R., Sugita, M. and Brutsaert, W. (1995) Satellite-Derived Surface Temperatures with Boundary Layer Temperatures and Geostrophic Winds to Estimate Surface Energy Fluxes. Journal of Geophysical Research, 100, 25447-25451. https://doi.org/10.1029/95JD00724
[18]
Kimura, F. and Shimiru, A.P. (1994) Estimation of Sensible and Latent Heat Fluxes from Soil Surface Temperatures Using a Linear Air Land Heat Transfer Model. Journal of Applied Meteorology, 33, 477-489. https://doi.org/10.1175/1520-0450(1994)033<0477:EOSALH>2.0.CO;2
[19]
Weng, Q. and Fu, P. (2014) Modelling Annual Parameters of Land Surface Temperature Variations and Evaluating the Impact of Cloud Cover Using Time Series of Landsat TIR Data. Remote Sensing of Environment, 140, 267-278. https://doi.org/10.1016/j.rse.2013.09.002
[20]
Hu, L. and Brunsell, N.A. (2013) The Impact of Temporal Aggregation of Land Surface Temperature Data for Surface Urban Heat Island (SUHI) Monitoring. Remote Sensing of Environment, 134, 162-174. https://doi.org/10.1016/j.rse.2013.02.022
[21]
Deng, C. and Wu, C. (2013) Examining the Impacts of Urban Biophysical Compositions on Surface Urban Heat Island: A Spectral Unmixing and Thermal Mixing Approach. Remote Sensing of Environment, 131, 262-274. https://doi.org/10.1016/j.rse.2012.12.020
[22]
Mathew, A., Sreekumar, S., Khandelwal, S., Kaul, N. and Kumar, R. (2016) Prediction of Surface Temperatures for the Assessment of Urban Heat Island Effect over Ahmedabad City Using Linear Time Series Model. Energy and Buildings, 128, 605-616. https://doi.org/10.1016/j.enbuild.2016.07.004
[23]
Fan, X.M., Liu, H.G., Liu, G.H. and Li, S.B. (2014). Reconstruction of MODIS Land-Surface Temperature in a Flat Terrain and Fragmented Landscape. International Journal of Remote Sensing, 35, 7857-7877. https://doi.org/10.1080/01431161.2014.978036
[24]
Lloyd, P.C., Mabogunje, A.L. and Awe, B. (1967) The City of Ibadan. Cambridge University Press, Cambridge.
[25]
Areola, O. (1994) The Spatial Growth of Ibadan City and Its Impact on the Rural Hinterland. In: Filani, M.O., Akintola, F.O. and Ikporukpo, C.O., Eds., Ibadan Region, Rex Charles Publication, Ibadan, 72-84.
[26]
Landsat Project Science Office (2002) Landsat 7 Science Data User’s Handbook. Goddard Space Flight Center, NASA, Washington DC. https://landsat.usgs.gov/landsat-7-data-users-handbook
[27]
Chander, G. and Markham, B. (2003) Revised Landsat-5 TM Radiometric Calibration Procedures and Post Calibration Dynamic Ranges. IEEE Transactions on Geoscience and Remote Sensing, 41, 2674-2677. https://doi.org/10.1109/TGRS.2003.818464
[28]
USGS (2013) Using the USGS Landsat 8 Product. https://landsat.usgs.gov/using-usgs-landsat-8-product
[29]
Seema, J. and Kavita, S. (2014) Spatio-Temporal Assessment of Land Use/Land Cover Dynamics and Urban Heat Island of Jaipur City Using Satellite Data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 40, 767-772.
[30]
Sobrino, J.A., Jimenez-munoz, J.C., El-kharraz, J., Gomez, M., Romaguera, M. and Soria, G. (2004) Single-Channel and Two-Channel Methods for Land Surface Temperature Retrieval from DAIS Data and Its Application to the Barrax Site. International Journal of Remote Sensing, 25, 215-230. https://doi.org/10.1080/0143116031000115210
[31]
Rouse, J.W., Hass, R.H., Schell, J.A. and Deering, D.W. (1974) Monitoring Vegetation Systems in the Great Plains with ERTS. Proceedings of the 3rd ERTS Symposium, Washington DC, date, 309-317.
[32]
Sobrino, J.A., Caselles, V. and Becker, F. (1990) Significance of the Remotely Sensed Thermal Infrared Measurements Obtained over a Citrus Orchard. ISPRS Photogrammetric Engineering and Remote Sensing, 44, 343-354. https://doi.org/10.1016/0924-2716(90)90077-O
[33]
Sobrino, J.A., Jiménez-Muñoz, J.C., Sòria, G., Romaguera, M., Guanter, L. and Moreno, J. (2008) Land Surface Emissivity Retrieval from Different VNIR and TIR Sensors. IEEE Transactions on Geoscience and Remote Sensing, 46, 316-327.
[34]
Artis, D.A. and Carnahan, W.H. (1982) Survey of Emissivity Variability in Thermography of Urban Areas. Remote Sensing of Environment, 12, 313-329. https://doi.org/10.1016/0034-4257(82)90043-8
[35]
Markham, B.L. and Barker, J.L. (1985) Spectral Characterization of the Landsat Thematic Mapper Sensors. International Journal of Remote Sensing, 6, 697-716. https://doi.org/10.1080/01431168508948492
[36]
Almorox, J., Bocco, M. and Willington, E. (2013) Estimation of Daily Global Solar Radiation from Measured Temperatures at Cañada de Luque, Córdoba, Argentina. Renewable Energy, 60, 382-387. https://doi.org/10.1016/j.renene.2013.05.033
[37]
Ouali, K. and Alkama, R. (2014) A New Model of Global Solar Radiation Based on Meteorological Data in Bejaia City (Algeria). Energy Procedia, 50, 670-676. https://doi.org/10.1016/j.egypro.2014.06.082
[38]
Jensen, J.R. (2000) Remote Sensing of the Environment: An Earth Resource Perspective. Pearson Education, Inc., Delhi, 361-365.
[39]
Zhang, Y., Odeh, I.O.A. and Han, C. (2009) Bi-Temporal Characterization of Land Surface Temperature in Relation to Impervious Surface Area, NDVI and NDBI Using a Subpixel Image Analysis. International Journal of Applied Earth Observation and Geoinformation, 11, 256-264. https://doi.org/10.1016/j.jag.2009.03.001
[40]
Griffiths, T.L., Chater, N., Kemp, C., Perfors, A. and Tenenbaum, B. (2010) Probabilistic Models of Cognition: Exploring Representations and Inductive Biases. Trends in Cognitive Sciences, 14, 357-364. https://doi.org/10.1016/j.tics.2010.05.004
[41]
Gallo, K.P. and Tarpley, J.D. (1996) The Comparison of Vegetation Index and Surface Temperature Composites of Urban Heat-Island Analysis. International Journal of Remote Sensing, 17, 3071-3076. https://doi.org/10.1080/01431169608949128
[42]
Weng, Q. (2001) A Remote Sensing-GIS Evaluation of Urban Expansion and Its Impact on Surface Temperature in the Zhujiang Delta, China. International Journal of Remote Sensing, 22, 1999-2014.
[43]
Balogun, A.A., Balogun, I.A., Adefisan, A.E. and Abatan, A.A. (2009) Observed Characteristics of the Urban Heat Island during the Harmattan and Monsoon in Akure, Nigeria. 8th Conferences on the Urban Environment, AMS 89th Annual Meeting, Phoenix, 11-15 January 2009, Paper JP4.6.
