Abstract
Urban growth is known to be the main factor of urban heat islands (UHI), an important indicator of global warming. However, another anomaly was where the temperature decreased without reducing the urban settlement during the COVID-19 pandemic. This study aims to compare the UHI in the Sleman Regency in contrast to urban growth and the COVID-19 pandemic time-lapse result through the pattern using Geographic Information System (GIS) and Remote Sensing (RS). Sleman Regency, Yogyakarta, Indonesia, was the area of interest for the case study in 2018, 2020, and 2022. In this research, the author observed the pattern of UHI following urbanization in a region that grows as a study and tourism destination in Indonesia. Landsat TIRS level 2 product has an ST (surface temperature) band that had been corrected using TOA reflectance, TOA brightness temperature, ASTER global emissivity dataset and ASTER NDVI data, and atmospheric profiles of geopotential height, specific humidity, and air temperature extracted from reanalysis data. The land surface temperature (LST) data were converted in Celcius to be extracted into the spatiotemporal model of UHI for the Sleman Regency. Moran’s index spatial autocorrelation showed the temporal variation of the UHI and built-up areas in the Sleman area during the chosen time. While the built-up area presented 0,21% growth from 2018 to 2022 based on NDBI, the UHI in the Sleman Regency was depleted by approximately 50% in 2020. However, the UHI nearly doubled by approximately 49,17% by 2022, after the pandemic. This result depicts another factor of land surface temperature other than urbanization. Human activity related to transportation during the pandemic lockdown indicated the influence of gas emissions on the land surface temperature.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
All of the data related to this research are available on request.
References
Abdullah S, Barua D (2022) Modeling land surface temperature with a mono-window algorithm to estimate urban heat island intensity in an expanding urban area. Environ Process. https://doi.org/10.1007/s40710-021-00554-8
Adriane R, Hilly G, Roa A, Frandel Q, Dagoc L, Guihawan J, Suson P (2023) Modeling the influence of land cover dynamics on spatio—temporal variations in land surface temperature in Cagayan de Oro River basin, Mindanao, Philippines. Model Earth Syst Environ. https://doi.org/10.1007/s40808-023-01834-y
Ahdika A, Primandari AH, Adlin FN (2022) Considering the temporal interdependence of human mobility and COVID-19 concerning Indonesia’s large-scale social distancing policies. Qual Quant. https://doi.org/10.1007/s11135-022-01497-4
Ahmed G, Zan M (2022) Impact of COVID-19 restrictions on air quality and surface urban heat island effect within the main urban area of Urumqi China. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-022-23159-6
BPS (2001) Kabupaten Sleman dalam Angka 2001, Indonesia
BPS (2006) Kabupaten Sleman dalam Angka 2006, Indonesia
BPS (2011) Kabupaten Sleman dalam Angka 2011, Indonesia
BPS (2016) Kabupaten Sleman dalam Angka 2016, Indonesia
BPS (2018) Kabupaten Sleman dalam Angka 2018, Indonesia
BPS (2020) Kabupaten Sleman dalam Angka 2020, Indonesia
BPS (2021) Kabupaten Sleman dalam Angka 2021, Indonesia
Braak C (1929) The Climate of The Netherlands Indies. Proc. Royal Magnetic Meteor. Observ. Batavia
de Brito AA, de Araújo HA, Zebende GF (2019) Detrended multiple cross-correlation coefficient applied to solar radiation, air temperature and relative humidity. Sci Rep 9(1):1–11. https://doi.org/10.1038/s41598-019-56114-6
Devi MK, Gorman YH, Hidayati SR (2020) Spatial transformation in urban periphery: the case of Yogyakarta. IOP Conf Ser: Earth Environ Sci. https://doi.org/10.1088/1755-1315/592/1/012022
Dubé J, Legros D (2014) Spatial econometrics using microdata. ISTE Ltd (issue Sep). https://doi.org/10.1002/9781119008651.ch3
Gu C, Hu L, Cook IG (2017) China’s urbanization in 1949–2015: processes and driving forces. Chin Geogra Sci 27(6):847–859. https://doi.org/10.1007/s11769-017-0911-9
Hidayati IN, Suharyadi R, Danoedoro P (2018) Developing an extraction method of urban built-up area based on remote sensing imagery transformation index. Forum Geografi. https://doi.org/10.23917/forgeo.v32i1.5907
Hepinstall-Cymerman J, Coe S, Hutyra LR (2013) Urban growth pattern and growth management boundaries in the Central Puget Sound, Washington 1986-2007. Urban Ecosyst 16(1):109–129. https://doi.org/10.1007/s11252-011-0206-3
Imran HM, Hossain A, Islam AS, Rahman A, Bhuiyan MA, Paul S, Alam A (2021) Impact of land cover changes on land surface temperature and human thermal comfort in Dhaka city of Bangladesh. Earth Syst Environ 5(3):667–693. https://doi.org/10.1007/s41748-021-00243-4
Knox PL, McCarthy L (2012) Urbanization An introduction to urban geography, Upper Saddle River, NJ: Pearson Prentice Hall
Kurniawan A, Prakoso BSE (2008) The influence of spatial urbanization to regional condition in Periurban Areas of Yogyakarta. Forum Geografi 22(1):27. https://doi.org/10.23917/forgeo.v22i1.4924
Liping C, Yujun S, Saeed S (2018) Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—a case study of a hilly area, Jiangle. China PloS One 13(7):1–23. https://doi.org/10.1371/journal.pone.0200493
Mcgranahan G, Satterthwaite D (2014) Urbanisation concepts and trends. International Institute for Environment and Development, June, 1–27
Miller EA, Vorob’eva EA, Kadygrov EN (2009) Analysis of seasonal and annual peculiarities of the temperature stratification of an urban heat island. Atmospheric Ocean Opt 22(4):435–440. https://doi.org/10.1134/S1024856009040083
Moser-Reischl A, Uhl E, Rötzer T, Biber P, van Con T, Tan NT, Pretzsch H (2018) Effects of the urban heat Island and climate change on the growth of Khaya senegalensis in Hanoi, Vietnam. For Ecosyst. https://doi.org/10.1186/s40663-018-0155-x
Muhaimin M, Fitriani D, Adyatma S, Arisanty D (2022) Mapping build-up area density using Normalized Difference Built-Up Index (Ndbi) and Urban Index (Ui) wetland in the City Banjarmasin. IOP Conf Ser: Earth Environ Sci. https://doi.org/10.1088/1755-1315/1089/1/012036
Myint SW, Wentz EA, Brazel AJ, Quattrochi DA (2013) The impact of distinct anthropogenic and vegetation features on urban warming. Landscape Ecol 28(5):959–978. https://doi.org/10.1007/s10980-013-9868-y
Palme M, Lobato A, Carrasco C (2016) Quantitative analysis of factors contributing to urban heat island effect in cities of Latin-American Pacific Coast. Procedia Eng 169:199–206. https://doi.org/10.1016/j.proeng.2016.10.024
Parida BR, Bar S, Roberts G, Mandal SP, Pandey AC, Kumar M, Dash J (2021) Improvement in air quality and its impact on land surface temperature in major urban areas across India during the first lockdown of the pandemic. Environ Res. https://doi.org/10.1016/j.envres.2021.111280
Politis I, Georgiadis G, Nikolaidou A, Kopsacheilis A, Fyrogenis I, Sdoukopoulos A, Verani E, Papadopoulos E (2021) Mapping travel behavior changes during the COVID-19 lock-down: a socioeconomic analysis in Greece. Eur Transport Res Rev. https://doi.org/10.1186/s12544-021-00481-7
Rahajeng A, Jaya WK, Pangaribowo E, Darwin M (2022) Transformation of yogyakarta regional development: a shifting perception of economic power among the regions. GeoJournal. https://doi.org/10.1007/s10708-022-10708-2
Sachindra DA, Ullah S, Zaborski P, Nowosad M, Dobek M (2022) Temperature and urban heat island effect in Lublin city in Poland under changing climate. Theor Appl Climatol. https://doi.org/10.1007/s00704-022-04285-0
Sahana M, Dutta S, Sajjad H (2019) Assessing land transformation and its relation with land surface temperature in Mumbai city, India using geospatial techniques. Int J Urban Sci 23(2):205–225. https://doi.org/10.1080/12265934.2018.1488604
Sailor DJ (2011) A review of methods for estimating anthropogenic heat and moisture emissions in the urban environment. Int J Climatol 31(2):189–199. https://doi.org/10.1002/joc.2106
Salleh SA, AbdLatif Z, Mohd WMNW, Chan A (2013) Factors contributing to the formation of an urban heat Island in Putrajaya, Malaysia. Procedia Soc Behav Sci 105:840–850. https://doi.org/10.1016/j.sbspro.2013.11.086
Santamouris M (2020) Recent progress on urban overheating and heat island research integrated assessment of the energy, environmental, vulnerability and health impact synergies with the global climate change. Energy Build. https://doi.org/10.1016/j.enbuild.2019.109482
Sato K (2015) Anthropogenic climate change in an integrated energy balance model of global and urban warming. J Econ Struct 4(1):3–10. https://doi.org/10.1186/s40008-014-0009-9
Sekertekin A, Abdikan S, Marangoz AM (2018) The acquisition of impervious surface area from LANDSAT 8 satellite sensor data using urban indices: a comparative analysis. Environ Monit Assess. https://doi.org/10.1007/s10661-018-6767-3
Sihayuardhi ER, Brontowiyono W, Maziya FB, Hakim L (2021) The effect of the COVID-19 pandemic on ambient air quality in Yogyakarta urban area parameters SO2, CO and NO2 with inverse distance weighting (IDW). IOP Conf Ser: Earth Environ Sci. https://doi.org/10.1088/1755-1315/933/1/012013
Siregar JP (2019) Heritage and the change of meaning: understanding the urban heritage in Yogyakarta, Indonesia. IOP Conf Ser: Earth Environ Sci. https://doi.org/10.1088/1755-1315/340/1/012025
Stewart ID, Oke TR (2012) Local climate zones for urban temperature studies. Bull Am Meteorol Soc 93(12):1879–1900. https://doi.org/10.1175/BAMS-D-11-00019.1
Subkhi WB, Mardiansjah FH (2019) Pertumbuhan dan Perkembangan Kawasan Perkotaan di Kabupaten: Studi Kasus Kabupaten Sleman Daerah Istimewa Yogyakarta. Jurnal Wilayah Dan Lingkungan 7(2):105–120. https://doi.org/10.14710/jwl.72.105-120
Suharyadi R, Umarhadi DA, Awanda D, Widyatmanti W (2022) Exploring built-up indices and machine learning regressions for multi-temporal building density monitoring based on landsat series. Sensors. https://doi.org/10.3390/s22134716
Tol RSJ (2017) Population and trends in the global mean temperature. Atmosfera 30(2):121–135. https://doi.org/10.20937/ATM.2017.30.02.04
Trimarstuti J, Nuraini R (2020) Rural-urban area as a new growth center: problem or challenge? Int J Innov Sci Technol 5(12):211–214
USGS (2021) Landsat 4-7 Level 2 Science Product (L2SP) Guide September 2021 2. Sioux Falls, South Dakota
USGS (2022) Landsat 9 data users handbook version 10 Nasa, February. Sioux Falls, South Dakota
Verburg PH, Neumann K, Nol L (2011) Challenges in using land use and land cover data for global change studies. Glob Change Biol. https://doi.org/10.1111/j.1365-2486.2010.02307.x
Voogt JA (2004) Urban heat island: hotter cities. American Institute of Biological Sciences
Wang K, Aktas YD, Stocker J, Carruthers D, Hunt J, Malki-Epshtein L (2019) Urban heat island modelling of a tropical city: case of kuala lumpur. Geosci Lett 6(1):1–11. https://doi.org/10.1186/s40562-019-0134-2
Watik N, Jaelani LM (2019) Flood evacuation routes mapping based on derived- flood impact analysis from Landsat 8 imagery using network analyst method. XLII(September): 3–6
Wijayanto AK, Rushayati SB, Hermawan R, Setiawan Y, Prasetyo LB (2020) Jakarta and Surabaya land surface temperature before and during the COVID-19 pandemic 1,2 12(3): 213–221 http://www.aesbioflux.com.ro
Wilder-Smith A, Freedman DO (2020) Isolation, quarantine, social distancing and community containment: Pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. J Travel Med 27(2):1–4. https://doi.org/10.1093/jtm/taaa020
Yasin MY, Abdullah J, Noor NM, Yusoff MM, Noor NM (2022) Landsat observation of urban growth and land use change using NDVI and NDBI analysis. IOP Conf Ser: Earth Environ Sci 1067(1):012037. https://doi.org/10.1088/1755-1315/1067/1/012037
Ye X, Niyogi D (2022) Resilience of human settlements to climate change needs the convergence of urban planning and urban climate science. Comput Urban Sci 2(1):4–7. https://doi.org/10.1007/s43762-022-00035-0
Zha Y, Gao J, Ni S (2003) Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int J Remote Sens 24(3):583–594. https://doi.org/10.1080/01431160304987
Zhou B, Rybski D, Kropp JP (2017) The role of city size and urban form in the surface urban heat island. Sci Rep 7(1):1–9. https://doi.org/10.1038/s41598-017-04242-2
Acknowledgements
The author would like to acknowledge the Central Agency on Statistics of Indonesia for the open-access statistical data that were needed in this study. The author was also grateful to Geospatial Information Agency Indonesia and Fajrun Wahidil Muharram for supporting data to enhance the regional analysis.
Funding
Not applicable.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author declares that there are no competing interest regarding the publication of this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Sari, M.I. Urban heat island (UHI) spatiotemporal pattern in comparison with NDBI before–after COVID-19 pandemic in Sleman Regency, Indonesia. Model. Earth Syst. Environ. 10, 2855–2867 (2024). https://doi.org/10.1007/s40808-023-01924-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40808-023-01924-x