Abstract
Increased temperature is one of the signals of global warming. Trends in land surface temperature can be used to measure climate change. This research aimed to investigate the variation of land surface temperature in Borneo island using a cubic spline method and a multivariate regression model. The island was divided into 8 regions each comprising 9 subregions. Land surface temperatures for each subregion from 2000 to 2019 were obtained from the National Aeronautics and Space Administration Moderate Resolution Imaging Spectroradiometer database. The average increase in temperature was 0.2 °C/decade with a 95% confidence interval of (0.14, 0.27) °C. The changes differed by region; a significant increase was seen in Sarawak, North Kalimantan, West Kalimantan, West-central Kalimantan, and Central-east Kalimantan region; a slight decrease in Sabah and Brunei Darussalam (Sabah and Brunei) region; a slight increase in East Kalimantan; and a stable trend in South Kalimantan.
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The data that support the findings of this study and the command code are available in https://drive.google.com/drive/folders/1l4Jt9iWa5P8mI-1FMR5GwFj9lE6Ru0T-?usp=sharing.
References
Babalola O, Akinsanola A (2016) Change detection in land surface temperature and land use land cover over Lagos Metropolis. Nigeria Jorsg 5(3):2–7. https://doi.org/10.4172/2469-4134.1000171
Bell M, Greenberg MR (2018) Climate change and human health: links between history, policy, and science. Am J Public Health 108(S2):S54–S55. https://doi.org/10.2105/AJPH.2018.304437
Buyadi SNA, Mohd WMNW, Misni A (2014) Impact of vegetation growth on urban surface temperature distribution. IOP Conf Ser Environ Earth Sci 18(1):1–7. https://doi.org/10.1088/1755-1315/18/1/012104
Cleary MC, Lian FJ (1991) On the geography of Borneo. Prog Hum Geogr 15(2):163–177. https://doi.org/10.1177/030913259101500203
Coleman CM, Frieman MB (2014) Coronaviruses: important emerging human pathogens. J Virol 88(10):5209 LP – 5212. https://doi.org/10.1128/JVI.03488-13
De Jesus JB, Santana IDM (2017) Estimation of land surface temperature in Caatinga area using Landsat 8 Data. J Hum Reprod Sci 7(3):150–157. https://doi.org/10.29150/jhrs.v7i3.22766
Evans M (2020) Forest loss leads to local climate change effect in Borneo. Retrieved from Landscape News website: https://news.globallandscapesforum.org/27161/forest-loss-leads-to-local-climate-change-effect-in-borneo/
Fox M, Zuidema C, Bauman B, Burke T, Sheehan M (2019) Integrating public health into climate change policy and planning: State of practice update. Int J Environ Res 16(18):1–22. https://doi.org/10.3390/ijerph16183232
Gogoi PP, Vinoj V, Swain D, Roberts G, Dash J, Tripathy S (2019) Land use and land cover change effect on surface temperature over Eastern India. Sci Rep 9(1):1–10. https://doi.org/10.1038/s41598-019-45213-z
Gunarso P, Hartoyo ME, Agus F, Killeen TJ (2013) Oil palm and land use change in Indonesia, Malaysia and Papua New Guinea. Reports from the Technical Panels of RSPOs 2nd Greenhouse Gas Working Group, 29–64. Retrieved from http://www.rspo.org/file/GHGWG2/4_oil_palm_and_land_use_change_Gunarso_et_al.pdf
Heritage B (2020) About Borneo. Retrieved from The Borneo Project website: https://borneoproject.org/borneo-2
Himayah S, Ismail A, Nandi, Ridwana R, Arrasyid R, Affriani AR, Ihsan M (2019) Correlation between land surface temperature and vegetation greenness using multi-temporal images. IOP Conf Ser Environ Earth Sci 286(1). https://doi.org/10.1088/1755-1315/286/1/012043
Hua AK, Ping OW (2018) The influence of land-use/land-cover changes on land surface temperature: a case study of Kuala Lumpur metropolitan city. Eur J Remote Sens 51(1):1049–1069. https://doi.org/10.1080/22797254.2018.1542976
Hughes AC (2017) Understanding the drivers of Southeast Asian biodiversity loss. Ecosphere 8(1). https://doi.org/10.1002/ecs2.1624
Ismail NA, Zawiah W, Zin W, Ibrahim W, Yeun LC (2019) Eight-day daytime land surface temperature pattern over Peninsular Malaysia. Int J recent technol eng 8(4):11949–11955. https://doi.org/10.35940/ijrte.D9911.118419
Khorchani M, Martin-Hernandez N, Vicente-Serrano SM, Azorin-Molina C, Garcia M, Domínguez-Duran MAA, Domínguez-Castro F (2018) Average annual and seasonal land surface temperature. Spanish Peninsular J Maps 14(2):465–475. https://doi.org/10.1080/17445647.2018.1500316
Kottawa-Arachchi JD, Wijeratne MA (2017) Climate change impacts on biodiversity and ecosystems in Sri Lanka: a review. Nat Conserv 2(3):2–22. https://doi.org/10.24189/ncr.2017.042
Li Y, Zhang H, Kainz W (2012) Monitoring patterns of urban heat islands of the fast-growing Shanghai metropolis, China: using time-series of Landsat TM/ETM+ data. Int J Appl Earth Obs Geoinf 19:127–138. https://doi.org/10.1016/j.jag.2012.05.001
Lukas MA, De Hoog FR, Anderssen RS (2010) Efficient algorithms for robust generalized cross-validation spline smoothing. J Comput Appl 235(1):102–107. https://doi.org/10.1016/j.cam.2010.05.016
Majumder A, Kingra PK, Setia R, Singh SP, Pateriya B (2018) Influence of land use/land cover changes on surface temperature and its effect on crop yield in different agro-climatic regions of Indian Punjab. Geocarto Int: 1–24. https://doi.org/10.1080/10106049.2018.1520927
Mardia KV, Kent JT, Bibby JM (1979) Multivariate analysis, 10th edn. In: Birbaum ZW, Likacs E (eds). Academic Press, Inc., San Diego
Marks D (2011) Climate change and Thailand: impact and response. CSEA 33(2):229. https://doi.org/10.1355/cs33-2d
McAlpine CA, Johnson A, Salazar A, Syktus J, Wilson K, Meijaard E, Sheil D (2018) Forest loss and Borneo’s climate. Environ Res Lett 13(4):44009. https://doi.org/10.1088/1748-9326/aaa4ff
McNeil N, Chirtkiatsakul B (2016) Statistical models for the pattern of sea surface temperature in the North Atlantic during 1973–2008. Int J Climatol 36:3856–3863. https://doi.org/10.1002/joc.4598
Odindi JO, Bangamwabo V, Mutanga O (2015) Assessing the value of urban green spaces in mitigating multi-seasonal urban heat using MODIS land surface temperature (LST) and landsat 8 data. Int J Environ 9(1):9–18. https://doi.org/10.22059/ijer.2015.868
ORNL DAAC (2018) MODIS and VIIRS Land Products Global Subsetting and Visualization Tool. https://doi.org/10.3334/ornldaac/1379
Parmesan C, Hanley ME (2015) Plants and climate change: complexities and surprises. Ann Bot 116(6):849–864. https://doi.org/10.1093/aob/mcv169
Phan TN, Kappas M, Tran TP (2018) Land surface temperature variation due to changes in elevation in Northwest Vietnam. Clim 6(28):1–19. https://doi.org/10.3390/cli6020028
Rasul A, Balzter H, Smith C, Remedios J, Adamu B, Sobrino J, Weng Q (2017) A review on remote sensing of urban heat and cool islands. Land 6(2):38. https://doi.org/10.3390/land6020038
Prevedello JA, Winck GR, Weber MM, Nichols E, Sinervo B (2019) Impacts of forestation and deforestation on local temperature across the globe. PLoS ONE 14(3):1–18. https://doi.org/10.1371/journal.pone.0213368
R Core Team (2018) R: A Language and environment for statistical computing. Retrieved February 2, 2019, from https://www.r-project.org/
Scott CE, Monks SA, Spracklen DV et al (2018) Impact on short-lived climate forcers increases projected warming due to deforestation. Nat Commun 9(157):1–9. https://doi.org/10.1038/s41467-017-02412-4
Sheikhi A, Devi K (2018) Impact of land cover change on urban surface temperature in Iskandar Malaysia. Chem Eng Trans 63(lm):25–30. https://doi.org/10.3303/CET1863005
Singh RB, 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
Suherman A, Rahman MZA, Busu I (2014) Albedo and land surface temperature shift in hydrocarbon seepage potential area, case study in Miri Sarawak Malaysia Albedo and land surface temperature shift in hydrocarbon seepage potential area, case study in Miri Sarawak Malaysia. 8th International Symposium of the Digital Earth (ISDE8): 012148. https://doi.org/10.1088/1755-1315/18/1/012148
Tangang FT, Juneng L, Salimun E, Sei KM, Le LJ, Muhamad H (2012) Climate change and variability over Malaysia: gaps in science and research information. Sains Malays 41(11):1355–1366
Tol RSJ (2018) The economic impacts of climate change. Rev Environ Econ Policy 12(1):4–25. https://doi.org/10.1093/reep/rex027
Trenberth KE (2018) Climate change caused by human activities is happening and it already has major consequences. J Energy Nat Resour Law 36(4):463–481. https://doi.org/10.1080/02646811.2018.1450895
Venables WN, Ripley BD (2002) Modern Applied Statistics with S. Springer, Queensland
Wan Z (2008) New refinements and validation of the MODIS Land-Surface Temperature/Emissivity Products. In Remote Sensing of Environment (Vol. 140). https://doi.org/10.1016/j.rse.2006.06.026
Weigand M, Wurm M, Dech S, Taubenböck H (2019) Remote sensing in environmental justice research-a review. ISPRS Int J Geoinf 8(1). https://doi.org/10.3390/ijgi8010020
Wolff NH, Masuda YJ, Meijaard E, Wells JA, Game ET (2018) Impacts of tropical deforestation on local temperature and human well-being perceptions. Glob Environ Change 52(July):181–189. https://doi.org/10.1016/j.gloenvcha.2018.07.004
Wongsai N, Wongsai S, Huete AR (2017) Annual seasonality extraction using the cubic spline function and decadal trend in temporal daytime MODIS LST data. Remote Sens 9(12). https://doi.org/10.3390/rs9121254
Zhang Y, Liang S (2018) Impacts of land cover transitions on surface temperature in China based on satellite observations. Environ Res Lett 13(2):1–12. https://doi.org/10.1088/1748-9326/aa9e93
Acknowledgements
The authors gratefully acknowledge Professor Don McNeil for his invaluable assistance during this research. This study was supported by Thailand’s Education Hub for the Southern Region of ASEAN Countries (TEH-AC), Prince of Songkla University Graduate School Research Grant, and the Centre of Excellence in Mathematics, Commission on Higher Education, Thailand.
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Munawar Munawar and Tofan Agung Eka Prasetya obtained the data and performed statistical, and Rhysa McNeil and Rohana Jani contributed to statistical analyses, discussion, and interpretation of the results. All authors contributed through writing and editing the manuscript.
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Munawar, M., Prasetya, T.A.E., McNeil, R. et al. Statistical modeling for land surface temperature in Borneo island from 2000 to 2019. Theor Appl Climatol 147, 1627–1634 (2022). https://doi.org/10.1007/s00704-021-03891-8
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DOI: https://doi.org/10.1007/s00704-021-03891-8