Pendekatan Spasial Cellular Automata-Markov Chain Untuk Prediksi Tutupan Lahan Dan Analisis Bahaya Banjir
Abstract
Land cover change is an important environmental issue because it affects the hydrological cycle and increases the risk of flooding, especially in urban areas experiencing rapid urbanization. This study aims to predict land cover change and measure its impact on flood hazard in the Surakarta Metropolitan Area in 2030 and 2040. The method used is a combination of Cellular Automata-Markov Chain (CA-MC) to predict land cover change and flood hazard analysis methods. The results of the study show that in the 2020-2030 period, the area with the highest flood hazard increased by 3.42 hectares, while in the 2030-2040 period it increased by 1.35 hectares. This increase in flood hazard is mainly due to significant deforestation. In the period 2020-2030, deforestation of forests into built-up land and agricultural land reached 29,530.89 hectares and 6,224.76 hectares, while in the period 2030-2040, deforestation of forests into built-up land and agricultural land amounted to 25,109.73 hectares and 8,651.16 hectares. The conclusion of this study is that continued deforestation reduces the roughness of the land surface, thereby expanding the flood hazard area. Therefore, a more sustainable land management policy is needed to reduce the negative impact on the danger of flood disasters in the future.
Full text article
References
Adnan, N. A., & Atkinson, P. M. (2011). Exploring the impact of climate and land use changes on streamflow trends in a monsoon catchment. International Journal of Climatology, 31(6). https://doi.org/10.1002/joc.2112
Akbar, F., & Supriatna. (2019). Land cover modelling of Pelabuhanratu City in 2032 using celullar automata-markov chain method. IOP Conference Series: Earth and Environmental Science, 311(1). https://doi.org/10.1088/1755-1315/311/1/012071
Al-sharif, A. A. A., & Pradhan, B. (2014). Monitoring and predicting land use change in Tripoli Metropolitan City using an integrated Markov chain and cellular automata models in GIS. Arabian Journal of Geosciences, 7(10). https://doi.org/10.1007/s12517-013-1119-7
Andualem, T. G., Belay, G., & Guadie, A. (2018). Land Use Change Detection Using Remote Sensing Technology. Journal of Earth Science & Climatic Change, 9(10). https://doi.org/10.4172/2157-7617.1000496
Aneesha Satya, B., Shashi, M., & Deva, P. (2020). Future land use land cover scenario simulation using open source GIS for the city of Warangal, Telangana, India. Applied Geomatics, 12(3). https://doi.org/10.1007/s12518-020-00298-4
Anna, A. N., Priyana, Y., Fikriyah, V. N., Ibrahim, M. H., Ismail, K., Pamekar, M. S., & Asshodiq, A. D. T. (2021). Spatial Modelling of Local Flooding for Hazard Mitigation in Surakarta, Indonesia. International Journal of GEOMATE, 21(87), 145–152. https://doi.org/10.21660/2021.87.j2306
Araya, Y. H., & Cabral, P. (2010). Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal. Remote Sensing, 2(6). https://doi.org/10.3390/rs2061549
Awotwi, A., Anornu, G. K., Quaye-Ballard, J. A., & Annor, T. (2018). Monitoring land use and land cover changes due to extensive gold mining, urban expansion, and agriculture in the Pra River Basin of Ghana, 1986–2025. Land Degradation and Development, 29(10). https://doi.org/10.1002/ldr.3093
Berryman, K. (2006). Review of Tsunami Hazard and Risk in New Zealand. In Institute of Geological and Nuclear Sciences (Issue September).
BPBD. (2020). Laporan Akhir Penyusunan Rencana Kontingensi Bencana Banjir Kota Surakarta Tahun 2020.
Bunyangha, J., Majaliwa, M. J. G., Muthumbi, A. W., Gichuki, N. N., & Egeru, A. (2021). Past and future land use/land cover changes from multi-temporal Landsat imagery in Mpologoma catchment, eastern Uganda. Egyptian Journal of Remote Sensing and Space Science, 24(3). https://doi.org/10.1016/j.ejrs.2021.02.003
Fata Robbany, I., Gharghi, A., & Traub, K.-P. (2019). Land Use Change Detection and Urban Sprawl Monitoring in Metropolitan Area of Jakarta (Jabodetabek) from 2001 to 2015. KnE Engineering. https://doi.org/10.18502/keg.v4i3.5862
Fuadina, L. N., Rustiadi, E., & Pravitasari, A. E. (2020). The Dynamic of Land Use Changes and Regional Development in Bandung Metropolitan Area. IOP Conference Series: Earth and Environmental Science, 556(1). https://doi.org/10.1088/1755-1315/556/1/012002
Ghosh, P., Mukhopadhyay, A., Chanda, A., Mondal, P., Akhand, A., Mukherjee, S., Nayak, S. K., Ghosh, S., Mitra, D., Ghosh, T., & Hazra, S. (2017). Application of Cellular automata and Markov-chain model in geospatial environmental modeling- A review. In Remote Sensing Applications: Society and Environment (Vol. 5). https://doi.org/10.1016/j.rsase.2017.01.005
Gidey, E., Dikinya, O., Sebego, R., Segosebe, E., & Zenebe, A. (2017). Cellular automata and Markov Chain (CA_Markov) model-based predictions of future land use and land cover scenarios (2015–2033) in Raya, northern Ethiopia. Modeling Earth Systems and Environment, 3(4). https://doi.org/10.1007/s40808-017-0397-6
Grace, U. M., Sawa, B. A., & Jaiyeoba, I. A. (2015). Multi-Temporal Remote Sensing of Landuse Dynamics in Zaria, Nigeria. Journal of Environment and Earth Scienc, 5(9), 121–138. www.iiste.org
Guo, A., Zhang, Y., & Hao, Q. (2020). Monitoring and Simulation of Dynamic Spatiotemporal Land Use/Cover Changes. Complexity, 2020. https://doi.org/10.1155/2020/3547323
Halmy, M. W. A., Gessler, P. E., Hicke, J. A., & Salem, B. B. (2015). Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA. Applied Geography, 63. https://doi.org/10.1016/j.apgeog.2015.06.015
Hardin, P. J., Jackson, M. W., & Otterstrom, S. M. (2007). Mapping, measuring, and modeling Urban growth. In Geo-Spatial Technologies in Urban Environments (Second Edition): Policy, Practice, and Pixels. https://doi.org/10.1007/978-3-540-69417-5_8
Hemati, M., Hasanlou, M., Mahdianpari, M., & Mohammadimanesh, F. (2021). A systematic review of landsat data for change detection applications: 50 years of monitoring the earth. In Remote Sensing (Vol. 13, Issue 15). https://doi.org/10.3390/rs13152869
Huang, Y., Yang, B., Wang, M., Liu, B., & Yang, X. (2020). Analysis of the future land cover change in Beijing using CA–Markov chain model. Environmental Earth Sciences, 79(2). https://doi.org/10.1007/s12665-019-8785-z
Indraprahasta, G. S., & Derudder, B. (2019). World City-ness in a historical perspective: Probing the long-term evolution of the Jakarta metropolitan area. Habitat International, 89. https://doi.org/10.1016/j.habitatint.2019.102000
Karimi, H., Jafarnezhad, J., Khaledi, J., & Ahmadi, P. (2018). Monitoring and prediction of land use/land cover changes using CA-Markov model: a case study of Ravansar County in Iran. Arabian Journal of Geosciences, 11(19). https://doi.org/10.1007/s12517-018-3940-5
Khawaldah, H. A., Farhan, I., & Alzboun, N. M. (2020). Global Journal of Environmental Science and Management Simulation and prediction of land use and land cover change using GIS, remote sensing and CA-Markov model ARTICLE INFO. Global Journal of Environmental Science and Management, 6(2).
Kiggundu, N., Anaba, L. A., Banadda, N., Wanyama, J., & Kabenge, I. (2018). Assessing Land Use and Land Cover Changes in the Murchison Bay Catchment of Lake Victoria Basin in Uganda. Journal of Sustainable Development, 11(1). https://doi.org/10.5539/jsd.v11n1p44
Koko, A. F., Yue, W., Abubakar, G. A., Hamed, R., & Alabsi, A. A. N. (2020). Monitoring and predicting spatio-temporal land use/land cover changes in Zaria City, Nigeria, through an integrated cellular automata and markov chain model (CA-Markov). Sustainability (Switzerland), 12(24). https://doi.org/10.3390/su122410452
Kugu, A. S. (2018). Urban Sprawl Pattern and Its Implications for Urban Management ( Case Study : Zaria Urban Area , Nigeria ). International Journal of Architecture and Urban Development, 8(4).
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). https://doi.org/10.1371/journal.pone.0200493
Mardiansjah, F. H., Handayani, W., & Setyono, J. S. (2018). Pertumbuhan Penduduk Perkotaan dan Perkembangan Pola Distribusinya pada Kawasan Metropolitan Surakarta. Jurnal Wilayah Dan Lingkungan, 6(3). https://doi.org/10.14710/jwl.6.3.215-233
Martinez, R., & Masron, I. N. (2020). Jakarta: A city of cities. Cities, 106. https://doi.org/10.1016/j.cities.2020.102868
Munthali, M. G., Mustak, S., Adeola, A., Botai, J., Singh, S. K., & Davis, N. (2020). Modelling land use and land cover dynamics of Dedza district of Malawi using hybrid Cellular Automata and Markov model. Remote Sensing Applications: Society and Environment, 17. https://doi.org/10.1016/j.rsase.2019.100276
NGCC. (2014). 30-Meter Global Land Cover Dataset Product Discription.
Noori, N., Kalin, L., Sen, S., Srivastava, P., & Lebleu, C. (2016). Identifying areas sensitive to land use/land cover change for downstream flooding in a coastal Alabama watershed. Regional Environmental Change, 16(6). https://doi.org/10.1007/s10113-016-0931-5
Pontius, R. G., & Millones, M. (2011). Death to Kappa: Birth of quantity disagreement and allocation disagreement for accuracy assessment. In International Journal of Remote Sensing (Vol. 32, Issue 15). https://doi.org/10.1080/01431161.2011.552923
Pradoto, W., Setiyono, B., Wahyono, H., & Joong Choi, M. (2024). Peri-urbanisation in Surakarta City and Economic Transformation in the Fast-Growing Region of Sukoharjo Regency. Forum Geografi, 38(2), 203–221. https://doi.org/10.23917/forgeo.v38i2.5497
Pramitha, A. A. S., Utomo, R. P., & Miladan, N. (2020). Efektivitas infrastruktur perkotaan dalam penanganan risiko banjir di Kota Surakarta. Region : Jurnal Pembangunan Wilayah Dan Perencanaan Partisipatif, 15(1). https://doi.org/10.20961/region.v15i1.23258
Pratama, A. P., Yudhistira, M. H., & Koomen, E. (2022). Highway expansion and urban sprawl in the Jakarta Metropolitan Area. Land Use Policy, 112. https://doi.org/10.1016/j.landusepol.2021.105856
R. Yudarwati. (2017). Perubahan Penggunaan Lahan Dan Arahan Pengendaliannya Di Kabupaten Bogor Dan Cianjur. In Analisis pendapatan dan tingkat kesejahteraan rumah tangga petani (Vol. 53, Issue 9).
Radianti, J., Tasrif, M., & Rostiana, E. (2003). A dynamic model for spatial planning in metropolitan areas. International Conference of the System Dynamics Society.
Rakuasa, H., Helwend, J. K., & Sihasale, D. A. (2022). Pemetaan Daerah Rawan Banjir di Kota Ambon Menggunakan Sistim Informasi Geografis. Jurnal Geografi : Media Informasi Pengembangan Dan Profesi Kegeografian, 19(2). https://doi.org/10.15294/jg.v19i2.34240
Rakuasa, H., Wahab, W. A., Kamiludin, K., Jaelani, A., Ramdhani, R., & Rinaldi, M. (2023). Pemetaan Genangan Banjir di Jalan TB. Simatupang, Jakarta Selatan oleh Unit Pengelola, Penyelidikan, Pengukuran dan Pengujian (UP4) Dinas Sumber Daya Air DKI Jakarta. Jurnal Altifani Penelitian Dan Pengabdian Kepada Masyarakat, 3(2). https://doi.org/10.59395/altifani.v3i2.379
Rustiadi, E., Pravitasari, A. E., Setiawan, Y., Mulya, S. P., Pribadi, D. O., & Tsutsumida, N. (2021). Impact of continuous Jakarta megacity urban expansion on the formation of the Jakarta-Bandung conurbation over the rice farm regions. Cities, 111. https://doi.org/10.1016/j.cities.2020.103000
Singh, S. K., Mustak, S., Srivastava, P. K., Szabó, S., & Islam, T. (2015). Predicting Spatial and Decadal LULC Changes Through Cellular Automata Markov Chain Models Using Earth Observation Datasets and Geo-information. Environmental Processes, 2(1). https://doi.org/10.1007/s40710-015-0062-x
Sinnakaudan, S. K., Ab Ghani, A., Ahmad, M. S. S., & Zakaria, N. A. (2003). Flood risk mapping for Pari River incorporating sediment transport. Environmental Modelling and Software, 18(2). https://doi.org/10.1016/S1364-8152(02)00068-3
Subedi, P., Subedi, K., & Thapa, B. (2013). Application of a Hybrid Cellular Automaton – Markov (CA-Markov) Model in Land-Use Change Prediction: A Case Study of Saddle Creek Drainage Basin, Florida. Applied Ecology and Environmental Sciences, 1(6). https://doi.org/10.12691/aees-1-6-5
Sugandhi, N., Rakuasa, H., Zainudin, Wahab, W. A., Kamiludin, Jaelani, A., Ramdhani, & Rinaldi, M. (2023). Pemodelan Spasial Limpasan Genangan Banjir dari DAS Ciliwung di Kel. Kebon Baru dan Kel. Bidara Cina DKI Jakarta. Ulil Albab : Jurnal Ilmiah Multidisiplin, 2(5).
Sulaeman, A., Suhartanto, E., Litbang Sungai, B., Sumber Daya Air, P., & Pekerjaan Umum dan Perumahan Rakyat, K. (2017). Analisis Genangan Banjir Akibat Luapan Bengawan Solo Untuk Mendukung Peta Risiko Bencana Banjir Di Kabupaten Bojonegoro. Jurnal Teknik Pengairan, 8(2), 146–157. https://doi.org/https://doi.org/10.21776/ub.pengairan.2017.008.02.1
Supriatna, Mukhtar, M. K., Wardani, K. K., Hashilah, F., & Manessa, M. D. M. (2022). CA-Markov Chain Model-based Predictions of Land Cover: A Case Study of Banjarmasin City. Indonesian Journal of Geography, 54(3). https://doi.org/10.22146/IJG.71721
Vázquez-Quintero, G., Solís-Moreno, R., Pompa-García, M., Villarreal-Guerrero, F., Pinedo-Alvarez, C., & Pinedo-Alvarez, A. (2016). Detection and projection of forest changes by using the Markov Chain model and cellular automata. Sustainability (Switzerland), 8(3). https://doi.org/10.3390/su8030236
Viera, A. J., & Garrett, J. M. (2005). Understanding interobserver agreement: The kappa statistic. Family Medicine, 37(5).
Warrens, M. J. (2015). Relative quantity and allocation disagreement measures for category-level accuracy assessment. International Journal of Remote Sensing, 36(23). https://doi.org/10.1080/01431161.2015.1110265
Wells, J., Meijaard, E., Abram, N., & Wich, S. (2013). Forests, floods, people and wildlife on Borneo (Vol. 11). UNEP.
Wu, X., Shen, Z., Liu, R., & Ding, X. (2008). Land use/cover dynamics in response to changes in environmental and socio-political forces in the upper reaches of the Yangtze river, China. Sensors, 8(12). https://doi.org/10.3390/s8128104
Wulder, M. A., Loveland, T. R., Roy, D. P., Crawford, C. J., Masek, J. G., Woodcock, C. E., Allen, R. G., Anderson, M. C., Belward, A. S., Cohen, W. B., Dwyer, J., Erb, A., Gao, F., Griffiths, P., Helder, D., Hermosilla, T., Hipple, J. D., Hostert, P., Hughes, M. J., … Zhu, Z. (2019). Current status of Landsat program, science, and applications. Remote Sensing of Environment, 225. https://doi.org/10.1016/j.rse.2019.02.015
Zhang, X. Q. (2016). The trends, promises and challenges of urbanisation in the world. Habitat International, 54. https://doi.org/10.1016/j.habitatint.2015.11.018
Authors

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.