Abstract
Recent studies have made significant advancements in understanding the localized effects of urban warming in cities in the South Asian context. Taking the case of Khulna city, Bangladesh, in this paper we follow a two-pronged approach. First, we use remote sensing techniques to analyze the changing land use and land cover patterns (LULC) and their relationship with emerging land surface temperature (LST) change, that results in urban heat islands (UHI). Second, we follow up on the emergent results from the remote sensing analysis to draw key links with the existing UHI spatio-temporal variations with existing and future planning pathways. Our findings suggest that rapidly reducing green spaces and increased built-up areas are contributing strongly towards increasing UHI. The overall increase of LST in the city is nearly 2 °C in the past 5 years, which calls for more urgent climate adaptive planning and action. Document analysis of the Khulna city master plan demonstrates that several mitigation strategies were initiated through the Khulna Master Plan 2001, yet key implementation barriers continue to persist. We conclude by arguing for a holistic approach to green space planning in the city (through strategic action and institutional planning approaches), coupled with local scaled adaptation and mitigation strategies, that can help the planning process to deal with the challenges associated with UHI increase in urban areas.
Similar content being viewed by others
Data availability
Further data will be made available upon request to the first author.
References
Abir FA, Saha R (2021) Assessment of land surface temperature and land cover variability during winter: a spatio-temporal analysis of Pabna municipality in Bangladesh. Environ Chall. https://doi.org/10.1016/J.ENVC.2021.100167
Abutaleb K, Ngie A, Darwish A, Ahmed M, Arafat S, Ahmed F (2015) Assessment of urban heat island using remotely sensed imagery over Greater Cairo, Egypt. Adv Rem Sens 4:35–47. https://doi.org/10.4236/ars.2015.41004
Ahmed B (2011a) Modelling Spatio-temporal urban land cover growth dynamics using remote sensing and GIS techniques: a case study of Khulna City. J Bangladesh Inst Plann 4:15–32
Ahmed B (2011b) Urban land cover change detection analysis and modeling spatio-temporal growth dynamics using remote sensing and GIS Techniques: a case study of Dhaka, Bangladesh. Dhaka, Bangladesh. In: M.Sc. Thesis, University College London, London. https://doi.org/10.13140/2.1.1413.5364
Ahmed S (2018) Assessment of urban heat islands and impact of climate change on socioeconomic over Suez Governorate using remote sensing and GIS techniques. Egypt J Rem Sens Space Sci 21:15–25. https://doi.org/10.1016/J.EJRS.2017.08.001
Ahmed B, Kamruzzaman MD, Zhu X, Rahman M, Choi K (2013) Simulating land cover changes and their impacts on land surface temperature in Dhaka, Bangladesh. Rem Sens 5:5969–5998. https://doi.org/10.3390/RS5115969
Ahmed B, Rahman M, Sammonds P, Islam R, Uddin K (2020) Application of geospatial technologies in developing a dynamic landslide early warning system in a humanitarian context: the Rohingya refugee crisis in Cox’s Bazar, Bangladesh. Geomat Nat Haz Risk 11:446–468. https://doi.org/10.1080/19475705.2020.1730988
Akher SK, Chattopadhyay S (2017) Impact of urbanization on land surface temperature-a case study of Kolkata New Town. Int J Eng Sci. https://doi.org/10.9790/1813-0601027181
Akter T, Gazi M, Mia M (2021) Assessment of land cover dynamics, land surface temperature, and heat island growth in Northwestern Bangladesh using satellite imagery. Environ Process 8:661–690. https://doi.org/10.1007/S40710-020-00491-Y
Awais M, Li W, Hussain S, Cheema MJ, Li W, Song R (2022) Liu C (2022) Comparative evaluation of land surface temperature images from unmanned aerial vehicle and satellite observation for agricultural areas using in situ data. Agriculture 12:184. https://doi.org/10.3390/AGRICULTURE12020184
BBS (2011) Bangladesh Bureau of Statistics—Government of the People’s Republic of Bangladesh-Statistical-Yearbook. Bangladesh Bureau of Statistics
Bokaie M, Zarkesh MK, Arasteh PD, Hosseini A (2016) Assessment of urban heat island based on the relationship between land surface temperature and land use/ land cover in Tehran. Sustain Cities Soc 23:94–104. https://doi.org/10.1016/J.SCS.2016.03.009
Campbell S, Remenyi TA, White CJ, Johnston FH (2018) Heatwave and health impact research: a global review. Health Place 53:210–218. https://doi.org/10.1016/J.HEALTHPLACE.2018.08.017
Cramer VA, Hobbs RJ, Standish RJ (2008) What’s new about old fields? Land abandonment and ecosystem assembly. Trends Ecol Evol 23:104–112. https://doi.org/10.1016/J.TREE.2007.10.005
Dewan A, Corner R (2013) Dhaka Megacity: Geospatial Perspectives on Urbanisation, Environment and Health. Springer, Berlin
Dewan A, 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. Environ Monit Assess 150:237–249. https://doi.org/10.1007/S10661-008-0226-5
Dewan A, Kiselev G, Botje D (2021a) Diurnal and seasonal trends and associated determinants of surface urban heat islands in large Bangladesh cities. Applied Geography, vol 135. Elsevier Ltd. https://doi.org/10.1016/J.APGEOG.2021.102533
Dewan A, Kiselev G, Botje D, Mahmud GI, Bhuian H, Hassan QK (2021b) Surface urban heat island intensity in five major cities of Bangladesh: patterns, drivers and trends. Sustainable Cities and Society, vol 71. Elsevier Ltd. https://doi.org/10.1016/J.SCS.2021.102926
Dhar RB, Chakraborty S, Chattopadhyay R, Sikdar PK (2019) Impact of land-use/land-cover change on land surface temperature using satellite data: a case study of Rajarhat Block, North 24-Parganas District, West Bengal. J Indian Soc Rem Sens 47:331–348. https://doi.org/10.1007/S12524-019-00939-1
Dragomir LO, Petrosani PD, Oncia S (2012) Using satellite images Landsat tm for calculating normalized difference indexes for the landscape of Parang mountains. http://revcad.uab.ro/upload/32_292_Paper12_RevCAD13_2012.pdf
El-Hattab M, Amany SM, Lamia GE (2018) Monitoring and assessment of urban heat islands over the Southern region of Cairo Governorate, Egypt. Egypt J Rem Sens Space Sci 21:311–323. https://doi.org/10.1016/j.ejrs.2017.08.008
Estoque RC, Murayama Y, Myint SW (2017) Effects of landscape composition and pattern on land surface temperature: an urban heat island study in the megacities of Southeast Asia. Sci Total Environ 577:349–359. https://doi.org/10.1016/J.SCITOTENV.2016.10.195
Foster D, Swanson F, Aber J, Burke I, Brokaw N, Tilman D, Knapp A (2003) The importance of land-use legacies to ecology and conservation. Bioscience 53:77–88
Grigsby SP, Hulley GC, Roberts DA, Scheele C, Ustin SL, Alsina MM (2015) Improved surface temperature estimates with MASTER/AVIRIS sensor fusion. Rem Sens Environ 167:53–63. https://doi.org/10.1016/j.rse.2015.05.019
Gunawardena KR, Wells MJ, Kershaw T (2017) Utilising green and bluespace to mitigate urban heat island intensity. Sci Total Environ 584–585:1040–1055. https://doi.org/10.1016/J.SCITOTENV.2017.01.158
Hassan MM (2017) Monitoring land use/land cover change, urban growth dynamics and landscape pattern analysis in five fastest urbanized cities in Bangladesh. Rem Sens Appl Soc Env 7:69–83. https://doi.org/10.1016/J.RSASE.2017.07.001
Innes JE, Booher DE (2010) Planning with complexity: an introduction to collaborative rationality for public policy. In: Planning with complexity: an introduction to collaborative rationality for public policy. Routledge. https://doi.org/10.4324/9780203864302
IPCC (2013) Climate Change 2013—the physical science basis summary for policymakers: a report of working Group I of the IPCC
IPCC (2018) Global Warming of 1.5°C. In: An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty
Isaya NM, Avdan U (2016) Application of open source coding technologies in the production of land surface temperature (LST) maps from Landsat: a PyQGIS plugin. Rem Sens 8:413. https://doi.org/10.3390/RS8050413
Islam MD, Islam KS, Ahasan R, Mia MR, Haque ME (2021) A data-driven machine learning-based approach for urban land cover change modeling: a case of Khulna City Corporation area. Rem Sens Appl Soc Env 24:100634. https://doi.org/10.1016/J.RSASE.2021.100634
Jain S, Sannigrahi S, Sen S, Bhatt S, Chakraborti S, Rahmat S (2019) Urban heat island intensity and its mitigation strategies in the fast-growing urban area. J Urban Manag 9:54–63. https://doi.org/10.1016/J.JUM.2019.09.004
Jalan S, Sharma K (2014) Spatio-temporal assessment of land use/ land cover dynamics and urban heat island of jaipur city using satellite data. Int Arch Photogram Rem Sens Spat Inf Sci. https://doi.org/10.5194/isprsarchives-XL-8-767-2014
Jin M, Liang S (2006) An improved land surface emissivity parameter for land surface models using global remote sensing observations. J Clim 19:2867–2881. https://doi.org/10.1175/JCLI3720.1
Kafy AA, Faisal AA, Hasan MM, Sikdar S, Khan MH, Rahman M, Islam R (2020) Impact of LULC Changes on LST in Rajshahi district of Bangladesh: a remote sensing approach. J Geogr Stud 3:11–23. https://doi.org/10.21523/GCJ5.19030102
Kaplan G, Avdan U, Avdan ZY (2018) Urban heat island analysis using the Landsat 8 satellite data: a case study in Skopje, Macedonia. Proceedings 2:358. https://doi.org/10.3390/ECRS-2-05171
Karanam HK, Neela VB (2018) Study of normalized difference built-up (NDBI) index in automatically mapping urban areas from Landsat tm imagery. Int J Sci Res Rev 2018:7
KDA (2002a) Khulna Master Plan 2001 prepared by Khulna Development Authority. Khulna, Bangladesh
KDA (2002b) Khulna Urban Strategy Plan 2000–2020 prepared by Khulna Development Authority. Khulna, Bangladesh
KDA (2002c) Khulna Urban Structure Plan 2000–2020 prepared by Khulna Development Authority. Khulna, Bangladesh
KDA (2012) Khulna Detailed Area Development Plan 2012 prepared by Khulna Development Authority. Khulna, Bangladesh
Khan F, Das B, Mishra RK (2022) An automated land surface temperature modelling tool box designed using spatial technique for ArcGIS. Earth Sci Inf 1:3. https://doi.org/10.1007/s12145-021-00722-2
Kim JP, Guldmann JM (2014) Land-use planning and the urban heat island. Environ Plann B Plann Des 41:1077–1099. https://doi.org/10.1068/B130091P
Kotharkar R, Ramesh A, Bagade A (2018) Urban heat island studies in South Asia: a critical review. Urban Climate 24:1011–1026. https://doi.org/10.1016/J.UCLIM.2017.12.006
Kuehn L, McCormick S (2017) Heat exposure and maternal health in the face of climate change. Int J Environ Res Public Health. https://doi.org/10.3390/IJERPH14080853
Levermore G, Parkinson J, Lee K, Laycock P, Lindley S (2018) The increasing trend of the urban heat island intensity. Urban Clim 24:360–368. https://doi.org/10.1016/J.UCLIM.2017.02.004
Li H, Zhou Y, Li X, Meng L, Wang X, Wu S, Sodoudi S (2018) A new method to quantify surface urban heat island intensity. Sci Total Environ 624:262–272. https://doi.org/10.1016/J.SCITOTENV.2017.11.360
Lillesand T, Kiefer RW, Chhipman J (2015) Remote Sensing and image interpretation, 7th edn. Wiley, Cambridge
Liu Y, Hiyama T, Yamaguchi Y (2006) Scaling of land surface temperature using satellite data: a case examination on ASTER and MODIS products over a heterogeneous terrain area. Rem Sens Environ 105:115–128. https://doi.org/10.1016/J.RSE.2006.06.012
Mallick J, Kant Y, Bharath BD (2008) Estimation of land surface temperature over Delhi using Landsat-7 ETM+. J Ind Geophys Union 12:131–140. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.585.9524&rep=rep1&type=pdf
McFeeters SK (1996) The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int J Rem Sens 17:1425–1432. https://doi.org/10.1080/01431169608948714
McFeeters SK (2013) Using the normalized difference Water Index (NDWI) within a geographic information system to detect swimming pools for mosquito abatement: a practical approach. Rem Sens 5:3544–3561. https://doi.org/10.3390/RS5073544
Mitchell D, Heaviside C, Vardoulakis S, Huntingford C, Masato G, Guillod BP, Frumhoff P, Bowery A, Wallom D, Allen M (2016) Attributing human mortality during extreme heat waves to anthropogenic climate change. Environ Res Lett. https://doi.org/10.1088/1748-9326/11/7/074006
Mohan M, Kikegawa Y, Gurjar BR, Bhati S, Kandya A, Ogawa K (2012) Urban heat island assessment for a tropical urban Airshed in India. Atmos Clim Sci 2012:127–138. https://doi.org/10.4236/ACS.2012.22014
MoHPW (2002) Structure plan, master plan and detailed area plan (2001–2020) for Khulna city. Khulna, Bangladesh
Moniruzzaman M, Roy A, Bhatt CM, Gupta A, An NT, Hassan MR (2018) Impact analysis of urbanization on land use land cover change for Khulna city, Bangladesh using temporal landsat imagery. Int Arch Photogramm Rem Sens Spatial Inf Sci 5:757–760. https://doi.org/10.5194/isprs-archives-XLII-5-757-2018
Naserikia M, Shamsabadi EA, Rafieian M, Filho WL (2019) The urban heat island in an urban context: a case study of Mashhad, Iran. Int J Environ Res Public Health. https://doi.org/10.3390/IJERPH16030313
Nichol J (2005) Remote sensing of urban heat islands by day and night. Photogramm Eng Rem Sens 71:613–621. https://doi.org/10.14358/PERS.71.5.613
Oke TR (1982) The energetic basis of the urban heat island. Q J R Met Soc 108:551
Olofsson P, Foody GM, Herold M, Stehman SV, Woodcock CE, Wulder MA (2014) Good practices for estimating area and assessing accuracy of land change. Rem Sens Environ 148:42–57. https://doi.org/10.1016/J.RSE.2014.02.015
Palb S, Ziaul SK (2017) Detection of land use and land cover change and land surface temperature in English Bazar urban centre. Egypt J Rem Sens Space Sci 20:125–145. https://doi.org/10.1016/J.EJRS.2016.11.003
Puppala H, Singh AP (2021) Analysis of urban heat island effect in Visakhapatnam, India, using multi-temporal satellite imagery: causes and possible remedies. Environ Dev Sustain 23:11475–11493. https://doi.org/10.1007/s10668-020-01122-0
Ramachandra TV, Uttam KK (2009) Land surface temperature with land cover dynamics: multi-resolution, spatio-temporal data analysis of Greater Bangalore. Int J Geoinform 5:43–53. http://wgbis.ces.iisc.ac.in/energy/paper/IJGEO/IJGeo_TVR17Sep2009.pdf
Rousta I, Sarif MO, Gupta RD, Olafsson H, Ranagalage M, Murayama Y, Zhang H, Mushore TD (2018) Spatiotemporal analysis of land use/land cover and its effects on surface urban heat island using Landsat data: a case study of metropolitan city Tehran (1988–2018). Sustainability 10:4433. https://doi.org/10.3390/SU10124433
Roy S, Pandit S, Eva EA, Bagmar MS, Papia M, Banik L, Dube T, Rahman F, Razi MA (2020) Examining the nexus between land surface temperature and urban growth in Chattogram Metropolitan Area of Bangladesh using long term Landsat series data. Urban Clim. https://doi.org/10.1016/J.UCLIM.2020.100593
Scheffer M, Carpenter S, Foley JA, Folke C, Walker B (2001) Catastrophic shifts in ecosystems. Nature 413:591–596. https://doi.org/10.1038/35098000
Singh P, Kikon N, Verma P (2017) Impact of land use change and urbanization on urban heat island in Lucknow city, Central India. A remote sensing based estimate. Sustain Cities Soc 32:100–114. https://doi.org/10.1016/J.SCS.2017.02.018
Tan KC, Lim HS, MatJafri MZ, Abdullah K (2010) Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island, Malaysia. Environ Earth Sci 60:1509–1521. https://doi.org/10.1007/S12665-009-0286-Z
USGS (2019) Landsat 8 (L8) Data Users Handbook. https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/atoms/files/LSDS-1574_L8_Data_Users_Handbook-v5.0.pdf
Van Oldenborgh GJ, Philip S, Kew S, Van WM, Uhe P, Otto F, Singh R, Pai I, Cullen H, Achutarao K (2018) Extreme heat in India and anthropogenic climate change. Nat Hazard 18:365–381. https://doi.org/10.5194/NHESS-18-365-2018
World Bank (2017) NLTA to support implementation of Orissa state climate change action plan, India. https://documents1.worldbank.org/curated/en/765331498601425141/pdf/P147522-Output-NLTA-Odisha-State-Climate-Change-Action-Plan.pdf
Yasir M, Hui S, Rahman SU, Ilyas M, Zafar A, Mehmood A (2020) Estimation of land surface temperature using LANDSAT-8 data-A case study of district Malakand, Khyber Pakhtunkhwa, Pakistan. J Liberal Arts Humanities 1:140–148
Funding
There is no funding source for conducting this study.
Author information
Authors and Affiliations
Contributions
Conceptualization and methodology, Rabeya Sultana Leya (RSL), Pankaj Kanti Jodder (PKJ), Khan Rubayet Rahman (KRR), and Md. Arif Chowdhury (MAC); Data collection, processing, and summarization, RSL, PKJ, KRR, MAC, and Debadutta Parida (DP); Writing drafts, RSL, KRR, PKJ, and MAC; Editing, Revisions and Finalizing, RSL, KRR, and DP; Supervised, KRR.
Corresponding author
Ethics declarations
Conflict of interests
The authors declare that they have no conflict of interest.
Rights and permissions
About this article
Cite this article
Leya, R.S., Jodder, P.K., Rahaman, K.R. et al. Spatial Variations of Urban Heat Island Development in Khulna City, Bangladesh: Implications for Urban Planning and Development. Earth Syst Environ 6, 865–884 (2022). https://doi.org/10.1007/s41748-022-00309-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41748-022-00309-x