Monitoring the Impact of Land Cover Change on Urban Heat Island with Remote Sensing & GIS
Abstract
The increasing need for land has resulted in a higher rate of land conversion and urbanization, leading to a rise in urban density and the occurrence of an Urban Heat Island (UHI) effect. The application of remote sensing and GIS can serve as a substitute for data collection in monitoring the UHI phenomena. This work utilizes Landsat 8 OLI satellite image data, namely band 10, to analyze Land Surface Temperature (LST). Bands 5 and 4 are employed to assess the distribution of Normalized Difference Vegetation Index (NDVI) in Bekasi Regency during the years 2014 and 2020. The relationship between NDVI and LST is highly correlated as they can effectively forecast the influence of areas with sparse vegetation on temperature. The guided classification approach, employing the maximum likelihood algorithm and kappa validation, is utilized to evaluate alterations in land use. The kappa accuracy test yielded a score of 0.90% for 2014 and 0.99% for 2020. The research conducted between 2014 and 2020 revealed changes in land distribution. Specifically, the built-up land area increased by 99.92 Km2, empty land expanded by 280.82 Km2, bodies of water covered an additional 46.13 Km2, and vegetation expanded by 293.91 Km^2. According to the UHI research, it is evident that there has been a rise in surface temperature in Bekasi Regency from 2014 to 2020. In 2014, the minimum temperature reached 30 °C, and the maximum temperature reached 51 °C. In 2020, the minimum temperature was recorded at 34 °C, while the maximum temperature reached 52 °C.
References
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Zaitunah, A., Samsuri, S., Ahmad, A. G., & Safitri, R. A. (2018). Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia. IOP Conference Series: Earth and Environmental Science, 126(1). https://doi.org/10.1088/1755-1315/126/1/012112
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BPS (2021). Kabupaten Bekasi Dalam Angka 2021. BPS-Statistics Agency of Bekasi Regency.
Dangulla, M., Mundaf, L. A., & Mohammad, F. R. (2020). Spatio-temporal analysis of land use/land cover dynamics in Sokoto Metropolis using multi-temporal satellite data and Land Change Modeller. Indonesian Journal of Geography, 52(3), 306–316. https://doi.org/http://dx.doi.org/10.22146/ijg.46615
Fitriana, Z. E., Putra, Y. S., & Zulfian. (2021). Pengaruh Kerapatan Vegetasi terhadap Suhu Permukaan menggunakan Data Landsat 8 (Study Kasus : Kota Pontianak, Kalimantan Barat ). Prisma Fisika, 9(2), 152–159.
Florim, I., Albert, B., & Shpejtim, B. (2021). Measuring uhi using landsat 8 oli and tirs data with ndvi and ndbi in municipality of prishtina. Disaster Advances, 14(11), 25–36. https://doi.org/10.25303/1411da2536
Giofandi, E. A. (2020). Persebaran fenomena suhu tinggi melalui kerapatan vegetasi dan pertumbuhan bangunan serta distribusi suhu permukaan. Jurnal Geografi : Media Informasi Pengembangan Dan Profesi Kegeografian, 17(2), 56–62. https://doi.org/10.15294/jg.v17i2.24486.
Hanafi, F., Rahmadewi, D. P., & Setiawan, F. (2021). Land Cover Changes Based on Cellular Automata for Land Surface Temperature in Semarang Regency. Geosfera Indonesia, 6(3), 301. https://doi.org/10.19184/geosi.v6i3.23471
Hersperger, A., Ioja, C., Steiner, F., & Tudor, C. A. (2015). Comprehensive consideration of conflicts in the land-use planning process: a conceptual contribution. Carpathian journal of earth and environmental sciences, 10(4), 5-13.
Hoornweg, D., Sugar, L., & Gómez, C. L. T. (2018). Cities and greenhouse gas emissions: Moving forward. Planning for Climate Change: A Reader in Green Infrastructure and Sustainable Design for Resilient Cities, 62–71. https://doi.org/10.1177/2455747120923557
Kumar, A., Agarwal, V., Pal, L., Chandniha, S. K., & Mishra, V. (2021). Effect of Land Surface Temperature on Urban Heat Island in Varanasi City, India. J, 4(3), 420–429. https://doi.org/10.3390/j4030032
Lee, K., Kim, Y., Sung, H. C., Jang, R., Ryu, J., & Jeon, S. W. (2020). Trend analysis of urban heat island intensity according to urban area change in Asian mega cities. 40th Asian Conference on Remote Sensing, ACRS 2019: Progress of Remote Sensing Technology for Smart Future.
Maheng, D., Ducton, I., Lauwaet, D., Zevenbergen, C., & Pathirana, A. (2019). The sensitivity of urban heat island to urban green space-A model-based study of City of Colombo, Sri Lanka. Atmosphere, 10(3). https://doi.org/10.3390/atmos10030151
Manoli, G., Fatichi, S., Schläpfer, 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. https://doi.org/10.1038/s41586-019-1512-9
Nandi, N., & Dede, M. (2022). Urban Heat Island Assessment using Remote Sensing Data in West Java, Indonesia: From Literature Review to Experiments and Analyses. Indonesian Journal of Science and Technology, 7(1), 105–116. https://doi.org/10.17509/ijost.v7i1.44146
Nugroho, F., & Al-sanjary, O. I. (2018). A Review of Simulation Urban Growth Model. International Journal of Engineering & Technology, 7(11), 17–23. https://doi.org/10.14419/ijet.v7i4.11.20681
Oloke, O. C., Fayomi, O. S. I., Oluwatayo, A., Adagunodo, T. A., Akinwumi, I. I., & Amusan, L. M. (2021). The nexus of climate change, urban infrastructure and sustainable development in developing countries. IOP Conference Series: Earth and Environmental Science, 665(1). https://doi.org/10.1088/1755-1315/665/1/012051
Pontius, R. G. (2000). Quantification error versus location error in comparison of categorical maps. Photogrammetric Engineering and Remote Sensing, 66(8), 1011–1016.
Prastiwi, A. D. (2022). Urban Heat Island Di Kota Tangerang Selatan. Jurnal Geosaintek, 8(2), 182. https://doi.org/10.12962/j25023659.v8i2.11721
Priana, A., Nugroho, A., Purnamasari, E., Rais, M., & Perlambang, Y. A. (2020). The Pattern of Spatial Distribution of Agriculture Drought Using Landsat 8 OLI/TIRS in Bacukiki District, City of Parepare. In The 6th Geoinformation Science Symposium (Vol. 2019, p. 14). https://doi.org/10.13140/RG.2.2.26554.13767
Putra, C. D., Ramadhani, A., & Fatimah, E. (2021). Increasing Urban Heat Island area in Jakarta and it’s relation to land use changes. IOP Conference Series: Earth and Environmental Science, 737(1). https://doi.org/10.1088/1755-1315/737/1/012002
Ruthirako, P., Darnsawasdi, R., & Chatupote, W. (2015). Intensity and pattern of land surface temperature in Hat Yai City, Thailand. Walailak Journal of Science and Technology, 12(1), 83–94. https://doi.org/10.14456/977
Rwanga, S. S., & Ndambuki, J. M. (2017). Accuracy Assessment of Land Use/Land Cover Classification Using Remote Sensing and GIS. International Journal of Geosciences, 08(04), 611–622. https://doi.org/10.4236/ijg.2017.84033
Sajib, M. Q. U., & Wang, T. (2020). Estimation of land surface temperature in an agricultural region of Bangladesh from landsat 8: Intercomparison of four algorithms. Sensors (Switzerland), 20(6). https://doi.org/10.3390/s20061778
Sinabutar, J. J., Sasmito, B., & Sukmono, A. (2020). Studi cloud masking menggunakan band quality assessment, function of mask dan multi-temporal cloud masking pada citra landsat 8. Jurnal Geodesi Undip, 9(3), 51-60.
Syukri, M., R. (2018). Identification of Land Surface Temperature Using Geospatial Technology: Case Study in Bukittinggi City, West Sumatra Province. Jurnal Sains Informasi Geografi [JSIG], 1, 40–43. https://doi.org/10.31314/j
Tawfik, M., Elhifnawy, H., Ragab, A., & Hamza, E. (2017). The Effect of Image Resolution on the Geometric Correction of Remote Sensing Satellite Images. International Journal of Engineering and Applied Sciences, 4(5), 114–121.
Yin, C. L., Meng, F., & Yu, Q. R. (2020). Calculation of land surface emissivity and retrieval of land surface temperature based on a spectral mixing model. Infrared Physics and Technology, 108. https://doi.org/10.1016/j.infrared.2020.103333
Zaitunah, A., Samsuri, S., Ahmad, A. G., & Safitri, R. A. (2018). Normalized difference vegetation index (ndvi) analysis for land cover types using landsat 8 oli in besitang watershed, Indonesia. IOP Conference Series: Earth and Environmental Science, 126(1). https://doi.org/10.1088/1755-1315/126/1/012112
Zhou, D., Xiao, J., Bonafoni, S., Berger, C., Deilami, K., Zhou, Y., Frolking, S., Yao, R., Qiao, Z., & Sobrino, J. A. (2019). Satellite remote sensing of surface urban heat islands: Progress, challenges, and perspectives. Remote Sensing, 11(1), 1–36. https://doi.org/10.3390/rs11010048
Published
2023-12-21
How to Cite
NUGROHO, Feri et al.
Monitoring the Impact of Land Cover Change on Urban Heat Island with Remote Sensing & GIS.
Geosfera Indonesia, [S.l.], v. 8, n. 3, p. 301-315, dec. 2023.
ISSN 2614-8528.
Available at: <https://jurnal.unej.ac.id/index.php/GEOSI/article/view/27796>. Date accessed: 22 dec. 2024.
doi: https://doi.org/10.19184/geosi.v8i3.27796.
Section
Original Research Articles
