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Understanding the dynamics of urban heat island as a function of development regulations

    Vandana Srivastava Affiliation
    ; Alok Sharma Affiliation
    ; Sanjay Singh Jadon Affiliation

Abstract

This study is the first-ever attempt to relate the tools of development control like Floor Space Index (FSI/FAR), ground area covered by building footprints (BFs), and proportions/configurations of open areas, with their impact on the surface urban heat island (SUHI) which modulates the air temperatures. In the case of the Indian megacity Mumbai, statistical analysis of the land surface temperatures (LST) and its correlation with the selected development indicators, reveals that for an FSI increase of 1.0 to 1.8 the SUHI is found to be–2.5 °C less and when BFs reduced from 90% to 42% SUHI was also reduced by –2.5 °C. Highrise development with a large plot size is desirable whereas low-rise development with FSI 1.0 on small plot sizes exhibits the highest SUHI. Open spaces without vegetation do not reduce SUHI. The correlation of development regulations with SUHI intensity will help urban planners to make more informed decisions.

Keyword : sustainable development, urban heat island, land development regulations, remote sensing, urban environment, resilient planning

How to Cite
Srivastava, V., Sharma, A., & Jadon, S. S. (2024). Understanding the dynamics of urban heat island as a function of development regulations. Journal of Environmental Engineering and Landscape Management, 32(2), 93–103. https://doi.org/10.3846/jeelm.2024.20969
Published in Issue
Mar 4, 2024
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Agathangelidis, I., Cartalis, C., & Santamouris, M. (2020). Urban morphological controls on surface thermal dynamics: A comparative assessment of major European cities with a focus on Athens, Greece. Climate, 8(11), 1–33. https://doi.org/10.3390/cli8110131

Avdan, U., & Jovanovska, G. (2016). Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data. Journal of Sensors, 2016, Article 1480307. https://doi.org/10.1155/2016/1480307

Chen, Y., Yang, J., Yu, W., Ren, J., Xiao, X., & Xia, J. C. (2023). Relationship between urban spatial form and seasonal land surface temperature under different grid scales. Sustainable Cities and Society, 89, Article 104374. https://doi.org/10.1016/j.scs.2022.104374

Climate Data. (n.d.). Mumbai climate: Average temperature by month, Mumbai water temperature. Retrieved February 22, 2023, from https://en.climate-data.org/asia/india/maharashtra/mumbai-29/

de Almeida, C. R., Teodoro, A. C., & Gonçalves, A. (2021). Study of the urban heat island (UHI) using remote sensing data/techniques: A systematic review. Environments, 8(10), Article 105. https://doi.org/10.3390/environments8100105

Department of the Interior U.S. Geological Survey. (2016, June). Landsat 8 data users handbook. Nasa, 8, 97. https://landsat.usgs.gov/documents/Landsat8DataUsersHandbook.pdf

Farid, N., Moazzam, M. F. U., Ahmad, S. R., Coluzzi, R., & Lanfredi, M. (2022). Monitoring the impact of rapid urbanization on land surface temperature and assessment of surface urban heat island using Landsat in megacity (Lahore) of Pakistan. Frontiers in Remote Sensing, 3, 1–12. https://doi.org/10.3389/frsen.2022.897397

Gkatzioura, P. E., & Perakis, K. (2022, October 19–21). SES 2022 analysis of Urban Heat Island (UHI) through climate engine and ArcGIS Pro in different cities of Bulgaria. In SES 2022, Eighteenth International Scientific Conference, Space, Ecology, Safety (pp. 187–197), Sofia, Bulgaria. https://www.researchgate.net/publication/365374762

Grover, A., & Singh, R. B. (2015). Analysis of urban heat island (UHI) in relation to normalized difference vegetation index (NDVI): A comparative study of Delhi and Mumbai. Environments, 2(2), 125–138. https://doi.org/10.3390/environments2020125

Han, D., An, H., Cai, H., Wang, F., Xu, X., Qiao, Z., Jia, K., Sun, Z., & An, Y. (2023). How do 2D/3D urban landscapes impact diurnal land surface temperature: Insights from block scale and machine learning algorithms. Sustainable Cities and Society, 99, Article 104933. https://doi.org/10.1016/j.scs.2023.104933

Han, D., An, H., Wang, F., Xu, X., Qiao, Z., Wang, M., Sui, X., Liang, S., Hou, X., Cai, H., & Liu, Y. (2022). Understanding seasonal contributions of urban morphology to thermal environment based on boosted regression tree approach. Building and Environment, 226, Article 109770. https://doi.org/10.1016/j.buildenv.2022.109770

He, S., Wang, X., Dong, J., Wei, B., Duan, H., Jiao, J., & Xie, Y. (2019). Three-dimensional urban expansion analysis of valley-type cities: A case study of Chengguan District, Lanzhou, China. Sustainability, 11(20), Article 5663. https://doi.org/10.3390/su11205663

Huang, X., & Wang, Y. (2019). Investigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data: A case study of Wuhan, Central China. ISPRS Journal of Photogrammetry and Remote Sensing, 152, 119–131. https://doi.org/10.1016/j.isprsjprs.2019.04.010

Ishola, K. A., Okogbue, E. C., & Adeyeri, O. E. (2016). A quantitative assessment of surface urban heat islands using satellite multitemporal data over Abeokuta, Nigeria. International Journal of Atmospheric Sciences, 2016, Article 3170789. https://doi.org/10.1155/2016/3170789

Kalota, D. (2017). Exploring relation of land surface temperature with selected variables using geographically weighted regression and ordinary least square methods in Manipur State, India. Geocarto International, 32(10), 1105–1119. https://doi.org/10.1080/10106049.2016.1195883

Keeratikasikorn, C., & Bonafoni, S. (2018). Urban heat island analysis over the land use zoning plan of Bangkok by means of Landsat 8 imagery. Remote Sensing, 10(3), Article 440. https://doi.org/10.3390/rs10030440

Koko, A. F., Yue, W., Abubakar, G. A., Alabsi, A. A. N., & Hamed, R. (2021). Spatiotemporal influence of land use/land cover change dynamics on surface urban heat island: A case study of Abuja metropolis, Nigeria. ISPRS International Journal of Geo-Information, 10(5), Article 272. https://doi.org/10.3390/ijgi10050272

Leal Filho, W., Wolf, F., Castro-Díaz, R., Li, C., Ojeh, V. N., Gutiérrez, N., Nagy, G. J., Savić, S., Natenzon, C. E., Al-Amin, A. Q., Maruna, M., & Bönecke, J. (2021). Addressing the urban heat islands effect: A cross-country assessment of the role of green infrastructure. Sustainability, 13(2), 1–20. https://doi.org/10.3390/su13020753

Lesado, A. (2018). Clay roofing tile: A cool roof? Open Journal of Science and Technology, 1(1), 1–3. https://doi.org/10.31580/ojst.v1i1.151

Li, F., Sun, W., Yang, G., & Weng, Q. (2019). Investigating spatiotemporal patterns of surface urban heat islands in the Hangzhou Metropolitan area, China, 2000–2015. Remote Sensing, 11(13), Article 1553. https://doi.org/10.3390/rs11131553

Moazzam, M. F. U., Doh, Y. H., & Lee, B. G. (2022). Impact of urbanization on land surface temperature and surface urban heat Island using optical remote sensing data: A case study of Jeju Island, Republic of Korea. Building and Environment, 222, Article 109368. https://doi.org/10.1016/j.buildenv.2022.109368

Mondal, A., Guha, S., & Kundu, S. (2021). Dynamic status of land surface temperature and spectral indices in Imphal city, India from 1991 to 2021. Geomatics, Natural Hazards and Risk, 12(1), 3265–3286. https://doi.org/10.1080/19475705.2021.2008023

Morabito, M., Crisci, A., Guerri, G., Messeri, A., Congedo, L., & Munafò, M. (2021). Surface urban heat islands in Italian metropolitan cities: Tree cover and impervious surface influences. Science of the Total Environment, 751, Article 142334. https://doi.org/10.1016/j.scitotenv.2020.142334

Mukherjee, F., & Singh, D. (2020). Assessing land use–land cover change and its impact on land surface temperature using LANDSAT data: A comparison of two urban areas in India. Earth Systems and Environment, 4(2), 385–407. https://doi.org/10.1007/s41748-020-00155-9

Mumbai Metropolitan Region Development Authority. (n.d.). Regional plan. Retrieved February 22, 2023, from https://mmrda.maharashtra.gov.in/planning/regional-plan/final-rp-for-mmr

Naim, Md. N. H., & Kafy, A.-A. (2021). Assessment of urban thermal field variance index and defining the relationship between land cover and surface temperature in Chattogram city: A remote sensing and statistical approach. Environmental Challenges, 4, Article 100107. https://doi.org/10.1016/j.envc.2021.100107

Nor Afzan Buyadi, S., Mohd Naim Wan Mohd, W., & Misni, A. (2014). Quantifying green space cooling effects on the urban microclimate using remote sensing and GIS techniques. https://www.researchgate.net/publication/325170006

Ogashawara, I., & Bastos, V. (2012). A quantitative approach for analyzing the relationship between urban heat islands and land cover. Remote Sensing, 4(11), 3596–3618. https://doi.org/10.3390/rs4113596

Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24. https://doi.org/10.1002/qj.49710845502

Pan, J. (2016). Area delineation and spatial-temporal dynamics of urban heat island in Lanzhou city, China using remote sensing imagery. Journal of the Indian Society of Remote Sensing, 44(1), 111–127. https://doi.org/10.1007/s12524-015-0477-x

Pandey, A., Mondal, A., Guha, S., Upadhyay, P. K., & Rashmi. (2022a). A seasonal investigation on land surface temperature and spectral indices in Imphal City, India. Journal of Landscape Ecology, 15(3), 1–18. https://doi.org/10.2478/jlecol-2022-0015

Pandey, A., Mondal, A., Guha, S., Upadhyay, P. K., & Singh, D. (2022b). Land use status and its impact on land surface temperature in Imphal city, India. Geology, Ecology, and Landscapes. https://doi.org/10.1080/24749508.2022.2131962

Pandey, A., Mondal, A., Guha, S., Upadhyay, P. K., & Singh, D. (2023). A long-term analysis of the dependency of land surface temperature on land surface indexes. Papers in Applied Geography, 9(3), 279–294. https://doi.org/10.1080/23754931.2023.2187314

Parvez, I. M., Aina, Y. A., & Balogun, A.-L. (2021). The influence of urban form on the spatiotemporal variations in land surface temperature in an arid coastal city. Geocarto International, 36(6), 640–659. https://doi.org/10.1080/10106049.2019.1622598

Rahaman, S., Jahangir, S., Haque, M. S., Chen, R., & Kumar, P. (2021). Spatio-temporal changes of green spaces and their impact on urban environment of Mumbai, India. Environment, Development and Sustainability, 23(4), 6481–6501. https://doi.org/10.1007/S10668-020-00882-z

Roy, B., & Kasemi, N. (2021). Monitoring urban growth dynamics using remote sensing and GIS techniques of Raiganj Urban Agglomeration, India. Egyptian Journal of Remote Sensing and Space Science, 24(2), 221–230. https://doi.org/10.1016/j.ejrs.2021.02.001

Sajjad, S. H., Shirazi, S. A., Ahmed Khan, M., & Raza, A. (2009). Urbanization effects on temperature trends of Lahore during 1950-2007. International Journal of Climate Change Strategies and Management, 1(3), 274–281. https://doi.org/10.1108/17568690910977483

Schwarz, N., Schlink, U., Franck, U., & Großmann, K. (2012). Relationship of land surface and air temperatures and its implications for quantifying urban heat island indicators–An application for the city of Leipzig (Germany). Ecological Indicators, 18, 693–704. https://doi.org/10.1016/j.ecolind.2012.01.001

Shahfahad, Rihan, M., Naikoo, M. W., Ali, M. A., Usmani, T. M., & Rahman, A. (2021). Urban heat island dynamics in response to land-use/land-cover change in the coastal city of Mumbai. Journal of the Indian Society of Remote Sensing, 49(9), 2227–2247. https://doi.org/10.1007/s12524-021-01394-7

Shahfahad, Talukdar, S., Rihan, M., Hang, H. T., Bhaskaran, S., & Rahman, A. (2022). Modelling urban heat island (UHI) and thermal field variation and their relationship with land use indices over Delhi and Mumbai metro cities. Environment, Development and Sustainability, 24(3), 3762–3790. https://doi.org/10.1007/S10668-021-01587-7

Sharma, R., Ghosh, A., & Joshi, P. K. (2013). Analysing spatio-temporal footprints of urbanization on environment of Surat city using satellite-derived bio-physical parameters. Geocarto International, 28(5), 420–438. https://doi.org/10.1080/10106049.2012.715208

Singh, R. B., Grover, A., & Zhan, J. (2014). Inter-seasonal variations of surface temperature in the urbanized environment of Delhi using Landsat thermal data. Energies, 7(3), 1811–1828. https://doi.org/10.3390/en7031811

Suresh, S., Ajay Suresh, V., & Mani, K. (2016). Estimation of land surface temperature of high range mountain landscape of Devikulam Taluk using Landsat 8 data. International Journal of Research in Engineering and Technology, 5(1), 92–96. https://doi.org/10.15623/ijret.2016.0501017

Unger, J., Gál, T., Rakonczai, J., Mucsi, L., Szatmári, J., Tobak, Z., van Leeuwen, B., & Fiala, K. (2009, June 29–July 3). Air temperature versus surface temperature in urban environment [Conference presentation]. The Seventh International Conference on Urban Climate, Okohama, Japan.

Xu, H. (2015). Assessment of changes in green space of Nanjing city using 1998 and 2007 Landsat satellite data. Open House International, 40(4), 63–70. https://doi.org/10.1108/ohi-04-2015-b0011

Zhang, R., Yang, J., Ma, X., Xiao, X., & Xia, J. (Cecilia). (2023). Optimal allocation of local climate zones based on heat vulnerability perspective. Sustainable Cities and Society, 99, Article 104981. https://doi.org/10.1016/j.scs.2023.104981