Exploring the Role of Population Dynamics in Surface Urban Heat Island Hotspots in Peri-Urban Dhaka
DOI:
https://doi.org/10.23917/forgeo.v39i1.6648Keywords:
Land surface temperature, Land use land cover, population dynamics, Surface urban heat island, Urban expansionAbstract
This study investigates the hotspots of surface urban heat island (SUHI) in the peri-urban areas of Dhaka based on the nexus of population dynamics, urban expansion, and land surface temperature. The respective land use land cover (LULC) classification and land surface temperature (LST) estimation were derived for 2000 and 2022 using images from Landsat-5 and Landsat-8, respectively, by applying established equations. Urban growth and its relation to LST were estimated using the classification based on the random forest and normalised difference built-up index (NDBI). The latter are directly associated with economic activities. The results indicated increased LST over time with urban sprawl and population increase, and hotspots were typical in high male-dominated migration rates and highly dense industrial activity. This study gives insight into the sustainable approach to urban planning and managing populations through clarity on the prevailing relationships among population growth and urbanisation with changing temperature.
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Agarwal, R., Sharma, U., & Taxak, A. (2014). Remote sensing Based Assessment of Urban Heat Island Phenomenon in Nagpur Metropolitan Area. International Journal of Information & Computation Technology, 4(11), 1069–1074. [Google Scholar]
Ahmed, B., & Ahmed, R. (2012). Modeling Urban Land Cover Growth Dynamics Using Multi‑Temporal Satellite Imag-es: A Case Study of Dhaka, Bangladesh. ISPRS International Journal of Geo-Information, 1(1), 3–31. doi: 10.3390/ijgi1010003 [Google Scholar] [CrossRef]
Ahmed, B. (2011). Urban land cover change detection analysis and modeling spatiotemporal Growth dynamics using Remote Sensing and GIS Techniques: A case study of Dhaka, Bangladesh (Master’s Thesis, Erasmus Mundus Program,Universidade Nova de Lisboa (UNL), Instituto Superior de Estatística e Gestão de Informação (ISE-GI), Lisbon, Portugal). Retrieved From https://run.unl.pt/handle/10362/8298
Ahmed, B., Kamruzzaman, M., Zhu, X., Rahman, M., & Choi, K. (2013). Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh. Remote Sensing, 5(11), 5969–5998. doi: 10.3390/rs5115969 [Google Scholar] [CrossRef]
Ahmed, F., Bibi, M. H., Monsur, M. H., & Ishiga, H. (2005). Present environment and historic changes from the record of lake sediments, Dhaka City, Bangladesh. Environmental Geology, 48(1), 25–36. doi: /10.1007/s00254-005-1248-8 [Google Scholar] [CrossRef]
Artis, D. A., & Carnahan, W. H. (1982). Survey of Emissivity Variability in thermography of Urban Areas. Remote Sens-ing of Environment, 12(4), 313–329. doi: 10.1016/0034-4257(82)90043-8 [Google Scholar] [CrossRef]
Asgarian, A., Amiri, B. J., & Sakieh, Y. (2014). Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach. Urban Ecosystems, 18(1), 209–222. doi: 10.1007/s11252-014-0387-7 [Google Scholar] [CrossRef]
BBS. (2012). Bangladesh Population and Housing Census 2011 (Community Series). Bangladesh Bureau of Statistics, Statistics an Informatics Division, Ministry of Planning. Government of the People’s Republic of Bangladesh, Dhaka.
BBS. (2017). Bangladesh Statistics. Bangladesh Bureau of Statistics, Statistics an Informatics Division, Ministry of Planning. Government of the People’s Republic of Bangladesh, Dhaka.
BBS. (2017). Population Distribution and Internal Migration in Bangladesh. Bangladesh Bureau of Statistics, Statis-tics and Informatics Division, Ministry of Planning. Government of The People’s Republic of Bangladesh, Dhaka.
Brown, S., Versace, V. L., Laurenson, L., Ierodiaconou, D., Fawcett, J., & Salzman, S. (2011). Assessment of Spatio-temporal Varying Relationships Between Rainfall, Land Cover and Surface Water Area Using Geographically Weighted Regression. Environmental Modeling & Assessment, 17(3), 241–254. doi: 10.1007/s10666- 011-9289-8 [Google Scholar] [CrossRef]
Chen, X., Zhao, H., Li, P., & Yin, Z. (2006). Remote Sensing Image-Based Analysis of The Relationship between Urban Heat Island and Land Use / Cover Changes. Remote Sensing of Environment, 104(2), 133-146. doi: 10.1016/j.rse.2005.11.016 [Google Scholar] [CrossRef]
Chun, B., & Guldmann, J. M. (2018). Impact of greening on the urban heat island: Seasonal variations and mitigation strategies. Computers, Environment and Urban Systems, 71, 165–176. [Google Scholar]
Dadhich, A., Goyal, R., & Dadhich, P. (2017). An Assessment of Urban Space Expansion and Its Impact on Air. Jour-nal of Urban and Environmental Engineering, 11(1), 79–87. doi: 10.4090/juee.2017.v11n1.079087 [Google Scholar] [CrossRef]
Deilmai, B. R., Ahmad, B. B., & Zabihi, H. (2014). Comparison of two Classification methods (MLC and SVM) to ex-tract land use and land cover in Johor Malaysia. IOP Conference Series: Earth and Environmental Science, 20, 012052. Retrieved From https://iopscience.iop.org/article/10.1088/1755-1315/20/1/012052/pdf[Google Scholar] [CrossRef]
Deosthali, V. (2000). Impact of rapid urban growth on heat and moisture islands in Pune City, India. Atmospheric Envi-ronment, 34(17), 2745–2754. doi: 10.1016/S1352-2310(99)00370-2 [Google Scholar] [CrossRef]
Department of the Interior U.S. Geological Survey. (2016). Landsat 8 (L8) Data User Handbook (Vol. 8).
Dewan, A. M., & Yamaguchi, Y. (2009). Using Remote Sensing and GIS to Detect and Monitor Land Use and Land Cover Change in Dhaka Metropolitan of Bangladesh During 1960-2005. Environmental Monitoring and As-sessment, 150(1–4), 237–249. doi: 10.1007/s10661-008-0226-5 [Google Scholar] [CrossRef]
Dewan, A. M & Yamaguchi, Y. (2009). Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Applied Geography, 29(3), 390-401 [Google Scholar]
Dewan, A., Kiselev, G., & Botje, D. (2021). Diurnal and seasonal trends and associated determinants of surface urban heat islands in large Bangladesh cities. Applied Geography, 135, 102533. doi: 10.1016/j.apgeog.2021.102533 [Google Scholar] [CrossRef]
Dewan, A., Kiselev, G., Botje, D., Mahmud, G. I., Bhuian, Md. H., & Hassan, Q. K. (2021). Surface urban heat island in-tensity in five major cities of Bangladesh: Patterns, drivers and trends. Sustainable Cities and Society, 71, 102926. doi: 10.1016/j.scs.2021.102926 [Google Scholar] [CrossRef]
Feizizadeh, B., & Blaschke, T. (2013). Examining Urban heat Island Relations to Land Use and Air Pollution: Multiple Endmember Spectral Mixture Analysis for Thermal Remote Sensing. IEEE Journal of Selected Topics in Ap-plied Earth Observations and Remote Sensing, 6(3), 1749–1756. doi: 10.1109/JSTARS.2013.2263425 [Google Scholar] [CrossRef]
Foley, J. A. (2005). Global Consequences of Land Use. Science, 309(5734), 570–574. doi: 10.1126/science.1111772 [Google Scholar] [CrossRef]
Gallo, K. P., & Owen, T. W. (1998). Assessment of urban heat Islands: A multi‐sensor perspective for the Dallas‐Ft. worth, USA region. Geocarto International, 13(4), 35–41. doi: 10.1080/10106049809354662 [Google Scholar] [CrossRef]
GALLO, K. P., & TARPLEY, J. D. (1996). The comparison of vegetation index and surface temperature composites for urban heat-island analysis. International Journal of Remote Sensing, 17(15), 3071–3076. doi: 10.1080/01431169608949128 [Google Scholar] [CrossRef]
Grover, A., & Singh, R. B. (2015). Analysis of Urban Heat Island (UHI) in Relation to Normalized Difference Vegeta-tion Index (NDVI): A Comparative Study of Delhi and Mumbai. Environments, 125–138. doi: 10.3390/environments2020125 [Google Scholar] [CrossRef]
Haashemi, S., Weng, Q., Darvishi, A., & Alavipanah, S. K. (2016). Seasonal variations of The Surface Urban Heat Is-land in A Semi-Arid City. Remote Sensing, 8(4). doi: 10.3390/rs8040352 [Google Scholar] [CrossRef]
Haque, M. M., Ahmed, F., Anam, S., & Kabir, M. R. (2012). Future Population Projection of Bangladesh by Growth Rate Modelling Using Logistic Population Model. Annals of Pure and Applied Mathematics, 1(2), 192–202. [Google Scholar]
Hart, M. A., & Sailor, D. J. (2009). Quantifying the Influence of Land-Use and Surface Characteristics on Spatial Vari-ability in The Urban Heat Island. Theoretical and Applied Climatology, 95(3-4), 397–406. doi: 10.1007/s00704-008-0017-5 [Google Scholar] [CrossRef]
Hassan, M. M. (2017). Monitoring land use/land cover change, urban growth dynamics and landscape pattern analysis in five fastest urbanized cities in Bangladesh. Remote Sensing Applications: Society and Environment, 7, 69–83. doi: 10.1016/j.rsase.2017.07.001 [Google Scholar] [CrossRef]
Hassan, M. M., & Nazem, M. N. I. (2015). Examination of land use/land cover changes, urban growth dynamics, and environmental sustainability in Chittagong city, Bangladesh. Environment, Development and Sustainability, 18(3), 697–716. doi: 10.1007/s10668-015-9672-8 [Google Scholar] [CrossRef]
Hassan, M., & Southworth, J. (2017). Analyzing Land Cover Change and Urban Growth Trajectories of the Mega-Urban Region of Dhaka Using Remotely Sensed Data and an Ensemble Classifier. Sustainability, 10(2), doi: 10.3390/su10010010 [Google Scholar] [CrossRef]
Hongmei Zhao, & Xiaoling Chen. (2005). Use of normalized difference bareness index in quickly mapping bare areas from TM/ETM+. Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS ,’05. doi:10.1109/igarss.2005.1526319 [Google Scholar] [CrossRef]
Huang, F., Zhan, W., Voogt, J., Hu, L., Wang, Z., Quan, J., Ju, W., & Guo, Z. (2016). Temporal upscaling of surface ur-ban heat island by incorporating an annual temperature cycle model: A tale of two cities. Remote Sensing of Environment, 186, 1–12. [Google Scholar]
Hu, Y., Hou, M., Jia, G., Zhao, C., Zhen, X., & Xu, Y. (2019). Comparison of surface and canopy urban heat islands within megacities of eastern China. ISPRS Journal of Photogrammetry and Remote Sensing, 156, 160–168. [Google Scholar]
Imhoff, M. L., Zhang, P., Wolfe, R. E., & Bounoua, L. (2019). Remote Sensing of the Urban Heat Island Effect Across Biomes in the Continental USA. Remote Sensing of Environment, 114(3), 504–513. doi: 10.1016/j.rse.2009.10.008 [Google Scholar] [CrossRef]
Ishtiaque, A., Shrestha, M., Chhetri, N. (2017). Rapid urban growth in the Kathmandu Valley, Nepal: Monitoring land use land cover dynamics of a Himalayan City with Landsat imageries. Environments. 4 (4), 1–16. doi: 10.3390/environments4040072. [Google Scholar] [CrossRef]
Jesus, J. B. De, & Santana, I. D. M. (2017). Estimation of Land Surface Temperature in Caatinga Area Using Landsat 8 Data. Journal of Hyperspectral Remote Sensing, 7(3), 150–157. doi: 10.29150/jhrs.v7.3.p150-157 [Google Scholar] [CrossRef]
Karl, T. R., Diaz, H. F., & Kukla, G. (1988). Urbanization: Its Detection and Effect in the United States Climate Record. Journal of Climate, 1(11), 1099–1123. doi: 10.1175/1520-0442(1988)001<1099:UIDAEI>2.0.CO;2 [Google Scholar] [CrossRef]
Kant, Y., Azim, S., & Mitra, D. (2018). Analyzing the influence of urban growth on thermal environment through demo-graphic, environmental, and physical parameters in Bangladesh. Land-atmospheric research applications in South and Southeast Asia, 613-639.
Kibert, C.J. (2012). Sustainable Construction: Green Building Design and Delivery; 3rd ed.; John Wiley and Sons, Inc: Hoboken, NJ, USA, p. 236.
Lambin, E. F., & Meyfroidt, P. (2011). Global land use change, economic globalization, and the looming land scarcity. Proceedings of the National Academy of Sciences, 108(9), 3465–3472. doi: 10.1073/pnas.1100480108 [Google Scholar] [CrossRef]
Li, L., Zha, Y., & Zhang, J. (2020). Spatially non-stationary effect of underlying driving factors on surface urban heat islands in global major cities. International Journal of Applied Earth Observation and Geoinformation, 90, Ar-ticle 102131. [Google Scholar]
Liu, L., & Zhang, Y. (2011). Urban Heat Island Analysis Using the Landsat TM Data and ASTER Data: A Case Study in Hong Kong. Remote Sensing, 3(7), 1535–1552. doi: 10.3390/rs3071535 [Google Scholar] [CrossRef]
Lo, C. P., & Quattrochi, D. A. (2003). Land-Use and Land-Cover Change, Urban Heat Island Phenomenon, and Health Implications. Photogrammetric Engineering & Remote Sensing, 69(9), 1053–1063. doii: 10.14358/PERS.69.9.1053 [Google Scholar] [CrossRef]
Lowry, W. P. (1977). Empirical Estimation of Urban Effects on Climate: A Problem Analysis. Journal of Applied Mete-orology, 16(2), 129–135. doi: 10.1175/1520- 0450(1977)016<0129:EEOUEO>2.0.CO;2 [Google Scholar] [CrossRef]
Mahmood, R., Ahmed, N., Zhang, L., & Li, G. (2020). Coastal vulnerability assessment of Meghna estuary of Bangla-desh using integrated geospatial techniques. International Journal of Disaster Risk Reduction, 42, 101374. doi: 10.1016/j.ijdrr.2019.101374 [Google Scholar] [CrossRef]
Manoli, G., Fatichi, S., Schl ̈ apfer, M., Yu, K., Crowther, T. W., Meili, N., Burlando, P., Katul, G. G., & Bou-Zeid, E. (2019). Magnitude of urban heat islands largely explained by climate and population. Nature, 573(7772), 55–60. [Google Scholar]
Matthew, M.W., Adler-Golden, S.M., Berk, A., Felde, G., Anderson, G.P., Gorodetzky, D., Paswaters, S., Shippert, M. (2002). Atmospheric correction of spectral imagery: Evaluation of the FLAASH algorithm with AVIRIS data. In: Proceedings of Presented at the Applied Imagery Pattern Recognition Workshop, pp. 157–163. doi: 10.1109/AIPR.2002.1182270. [Google Scholar] [CrossRef]
Mirzaei, P. A., & Haghighat, F. (2010). Approaches to study Urban Heat Island - Abilities and limitations. Building and Environment, 45(10), 2192–2201. doi: 10.1016/j.buildenv.2010.04.001 [Google Scholar] [CrossRef]
Mondol, H., Mallick, U. K., & Biswas, M. H. A. (2018). Mathematical Modelling and Predicting the Current Trends of Human Population Growth in Bangladesh. Modelling, Measurement and Control D. 39(1), 1–7.
Montávez, J. P., Rodríguez, A., & Jiménez, J. I. (2000). A Study of the Urban Heat Island of Granada. International Journal of Climatology, 20(8), 899–911. doi: 10.1002/1097-0088(20000630)20:8<899::AID-JOC433>3.0.CO;2-I [Google Scholar] [CrossRef]
NASA. (1998). Landsat 7 Science Data Users Handbook.
Oke T.R. (1995). The Heat Island of the Urban Boundary Layer: Characteristics, Causes and Effects. In: Cermak J.E., Davenport A.G., Plate E.J., Viegas D.X. (eds) Wind Climate in Cities. NATO ASI Series (Series E: Applied Sci-ences), 277, 81-107. Springer, Dordrecht
Omran, F. (2012). Detection of land use and land surface temperature change at different resolution. Soil and water de-partment faculty of agriculture Suez corner university Ismalia, Egypt. Journal GIS. 4 (3), 189–203. doi: 10.4236/jgis.2012.43024. [Google Scholar] [CrossRef]
Parvin, M. (2013). Projecting the Population Size of Dhaka City with Migration using Growth Rate Method. IOSR Jour-nal of Mathematics, 8(5), 29–37. [Google Scholar]
Parvin, N. S., & Abudu, D. (2017). Estimating Urban Heat Island Intensity using Remote Sensing Techniques in Dhaka City. International Journal of Scientific & Engineering Research, 8(4), 289–298. doi: 10.14299/ijser.2017.04.009 [Google Scholar] [CrossRef]
Rabbani, G. (2019). Climate Change Implications for Dhaka City: A Need for Immediate Measure to Reduce Vulnera-bility. Adaptation to Climate Change- Proceedings of the Global Forum. Local Sustainability, (10), 1–6. doi: 10.1002/9781118568446.eurs0426 [Google Scholar] [CrossRef]
Raj, S., Paul, S. K., Chakraborty, A., & Kuttippurath, J. (2020). Anthropogenic forcing exacerbating the urban heat is-lands in India. Journal of environmental management, 257, 110006. [Google Scholar]
Raja, D. R. (2012). Spatial Analysis of Land Surface Temperature in Dhaka Metropolitan Area. Journal of Bangladesh Institute of Planners, 5, 151-167 [Google Scholar]
RAJUK. (2015). Dhaka Structure Plan 2016-2035. Retrieved From http://www.rajukdhaka.gov.bd/rajuk/image/slideshow/Dhaka_Structural_Plan.html
RAJUK. (2006). Preparation of Detailed Area Plan (DAP) for DMDP.
Ren, G. Y., Chu, Z. Y., Chen, Z. H., & Ren, Y. Y. (2007). Implications of temporal change in urban heat island intensity observed at Beijing and Wuhan stations. Geophysical Research Letters, 34(5). doi: 10.1029/2006gl027927 [Google Scholar] [CrossRef]
Roy, S. & Mahmood, R. (2016). Monitoring shoreline dynamics using landsat and hydrological data: A case study of Sandwip Island of Bangladesh. Pennsylvania Geographer, 54, 20-41. [Google Scholar]
Rinner, C., & Hussain, M. (2011). Toronto’s Urban Heat Island—Exploring the Relationship between Land Use and Surface Temperature. Remote Sensing, 3(6), 125 1265. doi: 10.3390/rs3061251 [Google Scholar] [CrossRef]
Rossi, R.C., and Peterson, L. (2015). Appendix D - Urban Heat Island Protocol for Mapping Temperature Projections in Climate Change Vulnerability Assessment (CCAV) Report – Part-1.
Schatz, J., & Kucharik, C. J. (2014). Seasonality of the Urban Heat Island Effect in Madison, Wisconsin. Journal of Applied Meteorology and Climatology, 53(10), 2371– 2386. doi: 10.1175/jamc-d-14-0107.1 [Google Scholar] [CrossRef]
Schatz, J., & Kucharik, C. J. (2015). Urban climate effects on extreme temperatures in Madison, Wisconsin, USA. Envi-ronmental Research Letters, 10(9), 094024. Retrieved From https://iopscience.iop.org/article/10.1088/1748-9326/10/9/094024/pdf[Google Scholar] [CrossRef]
Serneels, S., Linderman, M., & Lambin, E. F. (2007). A Multilevel Analysis of the Impact of Land Use on Interannual Land-Cover Change in East Africa. Ecosystems, 10(3), 402–418. doi: 10.1007/s10021-007-9026-y [Google Scholar] [CrossRef]
Shastri, H., Barik, B., Ghosh, S., Venkataraman, C., & Sadavarte, P. (2017). Flip flop of day-night and summer-winter surface urban heat island intensity in India. Scientific reports, 7(1), 40178. [Google Scholar]
Sobrino, J. A., Jiménez-Muñoz, J. C., & Paolini, L. (2004). Land surface temperature retrieval from Labdsat TM 5. Re-mote Sensing of Environment, 90(4), 434–440. doi: 10.1016/j.rse.2004.02.003 [Google Scholar] [CrossRef]
Streutker, D. (2003). Satellite-measured growth of the urban heat island of Houston, Texas. Remote Sensing of Envi-ronment, 85(3), 282–289. doi: 10.1016/S0034- 4257(03)00007-5 [Google Scholar] [CrossRef]
Streutker, D. R. (2017). A Remote Sensing Study of the Urban Heat Island of Hong Kong. Geomatics Science and Technology, 05(02), 23–33. doi: 10.12677/gst.2017.52004 [Google Scholar] [CrossRef]
Su, S., Xiao, R., Jiang, Z., & Zhang, Y. (2012). Characterizing landscape pattern and ecosystem service value changes for urbanization impacts at an eco-regional scale. Applied Geography, 34, 295–305. doi: 10.1016/j.apgeog.2011.12.001 [Google Scholar] [CrossRef]
Sun, R., Chen, A., Chen, L., Lü, Y. (2012). Cooling effects of wetlands in an urban region: The case of Beijing. Eco. In-di., 20, 57–64. doi: 10.1016/j.ecolind.2012.02.006. [Google Scholar] [CrossRef]
Tabassum, A., Park, K., Seo, J. M., Han, J. Y., & Baik, J. J. (2024). Characteristics of the urban heat island in Dhaka, Bangladesh, and its interaction with heat waves. Asia-Pacific Journal of Atmospheric Sciences, 1-15.
Tewolde, M. G., & Cabral, P. (2011). Urban Sprawl Analysis and Modeling in Asmara, Eritrea. Remote Sensing, 3(10), 2148–2165. doi: 10.3390/rs3102148 [Google Scholar] [CrossRef]
Uddin, A. S., Khan, N., Islam, A. R. M. T., Kamruzzaman, M., & Shahid, S. (2022). Changes in urbanization and urban heat island effect in Dhaka city. Theoretical and Applied Climatology, 147(3), 891-907 [Google Scholar]
UNFPA. (2016). Urbanization and Migration in Bangladesh. United Nations Population Fund, Dhaka, Bangladesh
UNICEF. (2012). The State of the World’s Children 2012: Children in an increasingly urban world. In Demographic Yearbook 2005, 4. doi: 10.1007/978-1- 4020-4385-7_3 [Google Scholar] [CrossRef]
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. [Google Scholar] [CrossRef]
Wang, J. W., Chow, W. T., & Wang, Y. C. (2020). A global regression method for thermal sharpening of urban land sur-face temperatures from MODIS and Landsat. International Journal of Remote Sensing, 41(8), 2986–3009. [Google Scholar]
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(10), 1999–2014. doi: 10.1080/713860788 [Google Scholar] [CrossRef]
Weng, Q. (2012). Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends. Re-mote Sensing of Environment, 117, 34–49. doi:10.1016/j.rse.2011.02.030 [Google Scholar] [CrossRef]
Weng, Q., & Yang, S. (2004). Managing the adverse thermal effects of urban development in a densely populated Chi-nese city. Journal of Environmental Management, 70(2), 145–156. doi: 10.1016/j.jenvman.2003.11.006 [Google Scholar] [CrossRef]
Weng, Q., Lu, D., & Liang, B. (2006). Urban Surface Biophysical Descriptors and Land Surface Temperature Varia-tions. Photogrammetric Engineering & Remote Sensing, 72(11), 1275–1286. doi: 10.14358/PERS.72.11.1275 [Google Scholar] [CrossRef]
Weng, Q., Lu, D., & Schubring, J. (2004). Estimation of land surface temperature – vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89, 467–483. doi: 10.1016/j.rse.2003.11.005 [Google Scholar] [CrossRef]
WHO. (2005). Health & Environment. World Health Organization, Geneva, Switzerland
Witting, L. (1997). A General Theory of Evolution: By Means of Selection by Density Dependent Competitive Interac-tion. Peregrine Publisher. Arhus, Denmark.
Xiong, Y., Huang, S., Chen, F., Ye, H., Wang, C., & Zhu, C. (2012). The Impacts of Rapid Urbanization on the Thermal Environment: A Remote Sensing Study of Guangzhou, South China. Remote Sensing, 4(7), 2033–2056. doi: 10.3390/rs4072033 [Google Scholar] [CrossRef]
Yao, R., Wang, L., Huang, X., Niu, Z., Liu, F., & Wang, Q. (2017). Temporal trends of surface urban heat islands and associated determinants in major Chinese cities. Science of the Total Environment, 609, 742-754. [Google Scholar]
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: 10.1029/2006JG000217 [Google Scholar] [CrossRef]
United Nations, Department of Economic and Social Affairs, Population Division (2015). World Urbanization Pro-spects: The 2014 Revision, (ST/ESA/SER.A/366). Retrieved From https://esa.un.org/unpd/wup/Publications/Files/WUP2014-Report.pdf
UN-Habitat. (2016). Urbanization and Development—Emerging Futures. World Cities Report 2016. Retrieved From http://wcr.unhabitat.org/wp-content/uploads/2017/02/WCR- 2016-Full- Report.pdf
World Bank (2012). Bangladesh-Towards Accelerated, Inclusive and Sustainable Growth: Opportunities and Challeng-es: Overview; Volume II. Retrieved From http://documents.worldbank.org/curated/en/132321468014348379/Overview
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 [Google Scholar] [CrossRef]
Zhi-qiang, L., Qi-gang, Z., (2011). Utility of Landsat image in the study of land cover and land surface temperature change. 3rd International Conference on Environmental Science and Information Application Technology (ESIAT 2011). Procedia Environ. Sci. 10, 1287–1292. doi: 10.1016/j.proenv.2011.09.206. [Google Scholar] [CrossRef]
Zhou, B., Rybski, D., & Kropp, J. P. (2017). The role of city size and urban form in the surface urban heat is-land. Scientific reports, 7(1), 4791. [Google Scholar]
Hassan, M.M., Nazem, M.N.I., (2016). Examination of land use/land cover changes, urban growth dynamics, and envi-ronmental sustainability in Chittagong city, Bangladesh. Environ. Dev. Sustain. 18, 697–716. doi: 10.1007/s10668-015-9672-8. [Google Scholar] [CrossRef]
Sarwar, M.I., Billa, M., Paul, A., (2016). Urban land use change analysis using RS and GIS in Sulakbahar ward in Chit-tagong city, Bangladesh. Int. J. Geomat. Geosci. 7, 1–10.
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