Land Cover Changes Based on Cellular Automata for Land Surface Temperature in Semarang Regency
Abstract
Land cover changes based on cellular automata for surface temperature in Semarang Regency has increased significantly due to the continuous rise in its population. Therefore, this study aims to identify, analyze and predict multitemporal land cover changes and surface temperature distribution in 2028. Data on the land cover map were obtained from Landsat 7 and 8 based on supervised classification, while Land Surface Temperature (LST) was calculated from its thermal bands. The collected data were analyzed for accuracy through observation, while Cellular Automata - Markov Chain was used to predict the associated changes in 2028. The result showed that there are 4 land cover maps with 5-year intervals from 2003 to 2018 at an accuracy of more than 85%. Furthermore, the existing land covers were dominated by forest with decreasing trend, while the built-up area continuously increased. The existing Land surface temperature range from 20.6°C to 36.6°C, at an average of 28.2°C and a yearly increase of 0.07°C. The temperature changes are positively correlated with the occurrence of land conversion. Land cover predictions for 2028 show similar forest dominance, with a 23,4% built-up area at a surface temperature of 28.9°C.
Keywords: Land cover change; Cellular Automata-Markov Chain; Land Surface Temperature
Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember
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References
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Susanti, N.I., Sanjoto T.B., & Tjahjono H. (2012). Aplikasi penginderaan jauh untuk analisis perubahan penggunaan lahan tahun 2002-2011 di Daerah Aliran Sungai Juana. Geo-Image, 1 (1), 69-74. https://doi.org/10.15294/geoimage.v1i1.949.
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United Nations (2018). 2018 Revision of world urbanization prospects. New York: Department of Economic and Social Affairs.
Wang, S., Ma, Q., Ding, H., & Liang, H. (2018). Detection of urban expansion and land surface temperature change using multi-temporal landsat images. Resources, Conservation and Recycling, 128, 526-534. https://doi.org/10.1016/j.resconrec.2016.05.011.
Yuliati, A. (2018). Hasil Survei Pertanian Antar Sensus (SUTAS) 2018 Kabupaten Semarang (A1 ed.). Kabupaten Semarang: Badan Pusat Statistik Kabupaten Semarang.
Apriliyana, D. (2015). Pengaruh perubahan penggunaan lahan Sub DAS Rawapening terhadap erosi dan sedimentasi Danau Rawapening. Jurnal Pembangunan Wilayah Dan Kota, 11 (1), 103-116. https://doi.org/10.14710/pwk.v11i1.8661.
Artis, D.A., & Carnahan, W. H. (1982). Survey of emissivity variability in thermography of urban areas. Remote Sensing of Environment, 12, 313–329. https://doi.org/10.1016/0034-4257(82)90043-8.
BMKG. (2019). Ekstrem Perubahan Iklim. Retrieved from https://www.bmkg.go.id/.
BPS. (2015). Luas Penggunaan Lahan Menurut Kabupaten/Kota di Jawa Tengah Tahun 2010. Retrieved from https://www.bps.go.id/.
BPS (2017a). Kabupaten Semarang Dalam Angka 2017. Retrieved from https://www.bps.go.id/.
BPS (2017b). Luas Lahan Kritis Menurut Kecamatan di Kabupaten Semarang 2011-2016. Retrieved from https://www.bps.go.id/.
Coll, C., Galve, J M., Sanchez, J.M., & Casellez, V. (2010). Validation of landsat-7/ETM+ thermal band calibration and atmospheric correction with ground-based measurements. IEEE, 48, 547–555. https://doi.org/10.1109/TGRS.2009.2024934.
Dadras, M., Shafri, H.Z.M., Ahmad, N., Pradhan, B., & Safarpour, S. (2015). Spatio-temporal analysis of urban growth from remote sensing data in Bandar Abbas City, Iran, Egypt. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 35-52. https://doi.org/10.1016/j.ejrs.2015.03.005.
Danoedoro, P. (2006). Versatile Land-Use Information For Local Planning In Indonesia: Contents, Extraction Methods And Integration Based On Moderate- And Highspatial Resolution Satellite Imagery. Doctoral dissertation. University of Queensland.
Estoque, R. C., Murayama, Y., & Myint, S. W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment, 577, 349-359. https://doi.org/10.1016/j.scitotenv.2016.10.195.
Fadlurrahman, M. M. (2018). Pengaruh Naungan Pohon Dengan Perbedaan Bentuk Tajuk dan Jarak dari Pohon Terhadap Kenyamanan Termal di Puspiptek Serpong. Doctoral dissertation. Institut Pertanian Bogor.
Fariz, T.R. (2016). Pemanfaatan citra satelit dan sistem informasi geografis untuk pengembangan RTH berdasarkan estimasi suhu permukaan daratan di Kota Pekalongan. Jurnal Geo-Image, 5(1). https://doi.org/10.15294/geoimage.v5i1.11320.
Fu P. & Weng Q. (2016). A Time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with landsat imagery. Remote Sensing of Environment, 175, 205–214. https://doi.org/10.1016/j.rse.2015.12.040.
Igun, E., & Williams M. (2018). Impact of urban land cover change on land surface temperature. Global J. Environ. Sci. Manage, 4(1),47–58. https://doi.org/10.22034/GJESM.2018.04.01.005.
Kalinda, I. O. P., Sasmito, B., & Sukmono, A. (2018). Analisis pengaruh koreksi atmosfer terhadap deteksi land surface temperature menggunakan citra landsat 8 di Kota Semarang. Jurnal Geodesi Undip, 7 (3), 66-76.
Khandelwal, S., Goyal, R., Kaul, N., & Mathew, A. (2018). Assessment of land surface temperature variation due to change in elevation of area surrounding Jaipur, India. Egyptian Journal of Remote Sensing and Space Science, 21(1),87–94. https://doi.org/10.1016/j.ejrs.2017.01.005.
Lal, R., & Shukla, M. K. (2004). Principles of soil physics. Florida: CRC Press.
Li, Z. L., Tang, B. H., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F., & Sobrino, J. A. (2013). Satellite-derived land surface temperature: current status and perspectives. Remote sensing of environment, 131, 14-37. https://doi.org/10.1016/j.rse.2012.12.008.
Lillesand, T.M., Kiefer R.W. & Chipman, J. W. (2004). Remote sensing and image interpretation (Fifth Edit). New Jersey: John Wiley & Sons, Inc.
Lin, X.-C., & Yu, S.-Q. (2005). Interdecadal changes of temperature in the Beijing Region and its heat island effect. Chinese Journal of Geophysics, 48(1), 47–54. https://doi.org/10.1002/cjg2.624.
Nugraha, S. B., Sidiq, W. A. B. N., & Hanafi, F. (2016). Landsat image analysis for open spaces change monitoring to temperature changes in Semarang City. Paper presented at the lst International Conference on Geography and Education (ICGE 2016), Malang, Indonesia.
Nuroniah, H. S., & Putri, K. P. (2013). Manual budidaya sengon. Jakarta: Pusat Penelitian dan Pengembangan Peningkatan Produktivitas Hutan, Badan Penelitian dan Pengembangan Kehutanan.
Pal, S., & Ziaul, S. (2017). Detection of land use and land cover change and land surface temperature in English Bazar Urban Center. The Egyptian Journal of Remote Sensing and Space Sciences, 20, 125–145. https://doi.org/10.1016/j.ejrs.2016.11.003.
Pangi, P., Ramadhan M., Astuti K.D., Harjanti I.M. & Yesiana R. (2017). Pola perkembangan ruang di Kabupaten Semarang dengan memanfaatkan data citra landsat. Jurnal Pengembangan Kota, 5(1), 58-68. https://doi.org/10.14710/jpk.5.1.58-68.
Pu, R., Gong, P., Michisita, R., & Sasagawa, T. (2006). Assessment of multi-resolution and multi-sensor data for urban surface temperature retrieval. Remote Sensing of Environment, 104, 211–225. https://doi.org/10.1016/j.rse.2005.09.022.
Pudjiono, S. (2014). Produksi Bibit Jati Unggul dari Klon dan Budidayanya. Yogyakarta : Balai Besar Penelitian Bioteknologi dan Pemuliaan Tanaman Hutan, Direktorat Jenderal Bina Usaha Kehutanan.
Sarwono, J. (2006). Metode penelitian kuantitatif dan kualitatif (1st ed.). Sleman: Graha Ilmu.
Sukresno, B., Jatisworo, D., & Kusuma, D. W. (2018). Analisis multilayer variabilitas upwelling di perairan Selatan Jawa. Jurnal Kelautan Nasional, 13(1), 15.
Susanti, N.I., Sanjoto T.B., & Tjahjono H. (2012). Aplikasi penginderaan jauh untuk analisis perubahan penggunaan lahan tahun 2002-2011 di Daerah Aliran Sungai Juana. Geo-Image, 1 (1), 69-74. https://doi.org/10.15294/geoimage.v1i1.949.
Tran, D.X., Pla F., Latorre-Carmona P., Myint, S. W., Caetano, M., & Kieu, H. V. (2017). Characterizing the relationship between land use and land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119–132. https://doi.org/10.1016/j.isprsjprs.2017.01.001.
Wang, S.Q, Zheng, X. Q., & Zang, X. B. (2012). Accuracy assessment of land use change simulation based on markov-cellular automata model. Procedia Environmental Sciences, 13, 1238–1245. https://doi.org/10.1016/j.proenv.2012.01.117.
United Nations (2018). 2018 Revision of world urbanization prospects. New York: Department of Economic and Social Affairs.
Wang, S., Ma, Q., Ding, H., & Liang, H. (2018). Detection of urban expansion and land surface temperature change using multi-temporal landsat images. Resources, Conservation and Recycling, 128, 526-534. https://doi.org/10.1016/j.resconrec.2016.05.011.
Yuliati, A. (2018). Hasil Survei Pertanian Antar Sensus (SUTAS) 2018 Kabupaten Semarang (A1 ed.). Kabupaten Semarang: Badan Pusat Statistik Kabupaten Semarang.
Published
2021-12-20
How to Cite
HANAFI, Fahrudin; RAHMADEWI, Dinda Putri; SETIAWAN, Fajar.
Land Cover Changes Based on Cellular Automata for Land Surface Temperature in Semarang Regency.
Geosfera Indonesia, [S.l.], v. 6, n. 3, p. 301-318, dec. 2021.
ISSN 2614-8528.
Available at: <https://jurnal.unej.ac.id/index.php/GEOSI/article/view/23471>. Date accessed: 20 nov. 2024.
doi: https://doi.org/10.19184/geosi.v6i3.23471.
Section
Original Research Articles
