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GEOSTATISTICAL MODELLING OF URBAN HEAT ISLAND EFFECT: ANALYSING THE RELATIONSHIP BETWEEN LAND USE PATTERNS AND LAND SURFACE TEMPERATURE IN LAGOS, NIGERIA
Abstract
Rapid urbanization across Lagos, Nigeria has driven extensive land cover modifications with significant climatic impacts. This study analyzed interlinkages between land use land cover (LULC) transformations and land surface temperature (LST) shifts in the intensely developing Lagos suburb of Ikorodu from 1991-2021 utilizing robust geospatial techniques. Multi-spectral Landsat 5, 7 and 8 data enabled reliable LULC classification into five covers using a Random Forest algorithm. Subsetting the Ikorodu area facilitated localized change analyses across 1991, 2001, 2011 and 2021. LULC changes significantly impacted regional microclimates by altering surface energy budgets. Replacing vegetation with constructed materials increased LSTs while diminishing humidity via lower transpiration. Quantifying alteration magnitudes and spatial patterns provided crucial historical perspectives on urban expansion and climatic changes. Over 30 years, built-up area rose from 14% to 65% while vegetation declined from 52% to 9%, with LST increasing from 23.13-C to 27.21-C. Statistical analyses indicated LST strongly, and positively correlated with a Built-Up Index. Cooling prevailed on semi-rural peripheries with more intact vegetation. This research demonstrates and models LULC-LST interlinkages over years of swift development around Lagos, delivering a framework for crafting sustainable growth policies and balancing modernization goals with ecological stability. Explicit urban heat island effect mitigation strategies combining infrastructural adaptations and green space retention are recommended to promote regional climate resilience.
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References20
Stewart, I. D., & Oke, T. R. (2012). Local climate zones for urban temperature studies. Bulletin of the American Meteorological Society, 93(12), 1879-1900. DOI: 10.1175/BAMS-D-11-00019.1
Voogt, J. A., & Oke, T. R. (2003). Thermal remote sensing of urban climates. Remote sensing of environment, 86(3), 370-384. DOI: 10.1016/S0034-4257(03)00079-8
Ramachandra, T. V., Bharath, H. A., & Durgappa, D. S. (2012). Insights into urban dynamics through landscape spatial pattern analysis. International Journal of Applied Earth Observation and Geoinformation, 18, 329-343. DOI: 10.1016/j.jag.2012.03.005
Oyinloye, M. A., & Adesina, F. A. (2011). Urbanization: Challenges in Modern Africa. Asian Economic and Financial Review, 1(1), 1.
Adeyeri, O. E., Akinsanola, A. A., Ishola, K. A., Arason, T., & Ebhuoma, E. E. (2017). Assessing the relationship between land surface temperature and land use land cover of Lagos Nigeria. Journal of Applied Geography, 86, 177-193. DOI: 10.1016/j.jag.2017.01.020
Jensen, J. R., & Cowen, D. C. (1999). Remote sensing of urban/suburban infrastructure and socio-economic attributes. Photogrammetric engineering and remote sensing, 65(5), 611-622. DOI: 10.14358/PERS.65.5.611
Chander, G., Markham, B. L., & Helder, D. L. (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote sensing of environment, 113(5), 893-903. DOI: 10.1016/j.rse.2009.01.007
Adeoye, N. O., Adeyemo, A. B., & Oladapo, O. D. (2018). Spatio-temporal dynamics of urban expansion in Lagos state. Journal of Sustainable Development Studies, 12(1), 1-23.
Akinsanola, A. A., & Ogunjobi, K. O. (2014). Analysis of rainfall and temperature variability over Nigeria. Global Journal of Human-Social Science Research.
World Population Review. (2022). Ikorodu, Nigeria Population 2022. World Population Review. https://worldpopulationreview.com/world-cities/ikorodu-population
Breiman, L. (2001). Random forests. Machine learning, 45(1), 5-32. DOI: 10.1023/A:1010933404324
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. biometrics, 159-174. DOI: 10.2307/2529310
Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1974). Monitoring vegetation systems in the Great Plains with ERTS. NASA special publication, 351, 309.
Zha, Y., Gao, J., & Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24(3), 583-594. DOI: 10.1080/01431160304987
USGS (2016). Landsat 8 (L8) Data Users Handbook. Department of the Interior U.S. Geological Survey. https://www.usgs.gov/centers/eros/landsat-8-l8-data-users-handbook
Markham, B. L., & Barker, J. L. (1986). Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. EOSAT Landsat technical notes, 1(1), 3-8.
Ayanlade, A. (2017). Assessing influences of city growth dynamics on urban heat island phenomena. Climate, 5(4), 79. DOI: 10.3390/cli5040079
Ullah, S., You, Z. J., Ullah, W., Zhang, H., & Wang, T. (2019). Factors influencing surface urban heat islands in South Asia. Science of the Total Environment, 658, 1346-1356. DOI: 10.1016/j.scitotenv.2018.12.206
Gui, X., Wang, L., Yao, R., & Yu, D. (2019). Investigating the urbanization process and its impact on vegetation change and urban heat island in Wuhan, China. Environmental Science and Pollution Research, 26(30), 30808�30825. DOI: 10.1007/s11356-019-05725-x https://doi.org/10.1007/s11356-019-06273-w
Deilami, K., Kamruzzaman, M., & Liu, Y. (2018). Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures. International journal of applied earth observation and geoinformation, 67, 30-42. DOI: 10.1016/j.jag.2017.12.009
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