ANALISIS DAN PREDIKSI PERUBAHAN TUTUPAN LAHAN MENGGUNAKAN MODEL CELULAR AUTOMATA-MARKOV CHAIN DI DAS WAE RUHU KOTA AMBON

Heinrich Rakuasa; Melianus Salakory; Philia Christi  Latue

doi:10.21776/ub.jtsl.2022.009.2.9

Authors

Heinrich Rakuasa Departemen Geografi FMIPA Universitas Indonesia
Melianus Salakory Program Studi Pendidikan Geografi, FKIP, Universitas Pattimura
Philia Christi Latue Departemen Biologi, Fakultas Biologi, Universitas Pedagogis Negeri Herzen Rusia

DOI:

https://doi.org/10.21776/ub.jtsl.2022.009.2.9

Keywords:

Land Cover, Wae Ruhu, Cellular Automata, Markov Chain, Ambon City

Abstract

The geographical location of the Wae Ruhu watershed is in Sirimau District, which is the sub-district with the largest population in Ambon City and is also the center of economic, educational, and industrial activities; this creates economic and population growth that has the potential to trigger land conversion around this area. This study aimed to analyze land cover changes in Ambon City in 2012, 2017, 2022 and predict land cover in 2031. This study used Cellular Automata Markov Chains modeling to predict land cover changes in 2031. The results showed that the types of land cover are built and land cover. The open area continues to increase in area, while agricultural and non-agricultural areas continue to experience a decrease in area, and water bodies do not experience a decrease or increase in area. The results of land cover predictions in 2031 showed that the built-up area is 345.79 ha, open land is 121.18 ha, agricultural land is 657.35 ha, non-agricultural land is 507.65 ha, and water bodies are 11.46 ha. The results of this study are expected to be used as a reference in making policies related to spatial planning and utilization, especially the Wae Ruhu watershed and can optimize sustainable watershed management as the first step in efforts to mitigate natural disasters.

Author Biography

Heinrich Rakuasa, Departemen Geografi FMIPA Universitas Indonesia

Program Studi Pendidikan Geografi, FKIP, Universitas Pattimura

References

Badan Standarisasi Nasional. 2010. SNI 7645-2010 Tentang Klasifikasi Penutup Lahan.

BPS. 2021. Kota Ambon Dalam Angka 2021 (BPS Kota Ambon (ed.)). BPS Kota Ambon. https://ambonkota.bps.go.id/publication/2020/04/27/0072157fa7d7bf288ceb130a/kota-ambon-dalam-angka-2020.html#:~:text=Kota Ambon Dalam Angka 2020 merupakan seri publikasi tahunan BPS, demografi dan perekonomian di Indonesia.

Difanty, A. dan Supriatna, S. 2021. Spatial modeling for prediction agricultural land-use change in Jampandg Kulon, Sukabumi Regency. IOP Conference Series: Earth and Environmental Science 623:12084.

Ghosh, P., Mukhopadhyay, A., Chanda, A., Mondal, P., Akhand, A., Mukherjee, S., Nayak, S.K., Ghosh, S., Mitra, D., Ghosh, T. and Hazra, S. 2017. Application of Cellular automata and Markov-chain model in geospatial environmental modeling- A review. Remote Sensing Applications: Society and Environment 5:64-77.

Irawan, I.A., Supriatna, S., Manessa, M.D.M. and Ristya, Y. 2019. Prediction model of land cover changes using the cellular automata-Markov Chain affected by the BOCIMI toll road in Sukabumi Regency. KnE Engineering 4(3 SE-Articles).

Kim, I., Arnhold, S., Ahn, S., Le, Q.B., Kim, S.J., Park, S.J. and Koellner, T. 2019. Land use change and ecosystem services in mountainous watersheds: Predicting the consequences of environmental policies with cellular automata and hydrological modeling. Environmental Modelling & Software 122:103982.

Kusratmoko, E., Albertus, S.D.Y. and Supriatna. 2017. Modelling land use/cover changes with markov-cellular automata in Komering Watershed, South Sumatera. {IOP} Conference Series: Earth and Environmental Science 54:12103.

Lisanyoto, L., Supriatna, and Sumadio, W. 2019. Spatial Model of Settlement Expansion and its Suitability to the Landscapes in Singkawang City, West Kalimantan Province. IOP Conference Series: Earth and Environmental Science 338:12034.

Mohamed, A. and Worku, H. 2019. Quantification of the land use/land cover dynamics and the degree of urban growth goodness for sustainable urban land use planning in Addis Ababa and the surrounding Oromia special zone. Journal of Urban Management 8(1):145-158.

Mustafa, A., Ebaid, A., Omrani, H. and McPhearson, T. 2021. A multi-objective Markov Chain Monte Carlo cellular automata model: Simulating multi-density urban expansion in NYC. Computers, Environment and Urban Systems 87:101602, doi:10.1016/j.compenvurbsys.2021.101602.

Mwabumba, M., Yadav, B.K., Rwiza, M.J., Larbi, I. and Twisa, S. 2022. Analysis of land use and land-cover pattern to monitor dynamics of Ngorongoro world heritage site (Tanzania) using hybrid cellular automata-Markov model. Current Research in Environmental Sustainability 4:100126.

Näschen, K., Diekkrüger, B., Evers, M., Höllermann, B., Steinbach, S. and Thonfeld, F. 2019. The impact of land use/land cover change (LULCC) on water resources in a tropical catchment in Tanzania under different climate change scenarios. Sustainability 11(24):7083, doi:10.3390/su11247083.

Pratami, M., Susiloningtyas, D. and Supriatna. 2019. Modelling cellular automata for the development of settlement area Bengkulu City. IOP Conference Series: Earth and Environmental Science 311:012073.

Putri, R.A. and Supriatna, S. 2021. Land cover change modeling to identify critical land in the Ciletuh Geopark tourism area, Palabuhanratu, Sukabumi Regency. IOP Conference Series: Earth and Environmental Scienc, 623:012081.

Shang, C. and Wu, J. 2022. A legendary landscape in peril: Land use and land cover change and environmental impacts in the Wulagai River Basin, Inner Mongolia. Journal of Environmental Management 301:113816.

Supriatna, S., Pratiwi, S.F., Marko, K., Manessa, M.D.M. and Ristya, Y. 2020. Spatial Dynamics of Tsunami Prone Areas in Pariaman City, West Sumatera. Journal of Computational and Theoretical Nanoscience 17(2):1474-1491.

Tan, S., Liu, Q. and Han, S. 2022. Spatial-temporal evolution of coupling relationship between land development intensity and resources environment carrying capacity in China. Journal of Environmental Management 301:113778.

Tayane, Y.A., Boreel, A. dan Putuhena, J.D. 2021. Perubahan tutupan lahan di DAS Waeruhu Kota Ambon menggunakan citra satelit MultitempORAL. Jurnal Hutan Pulau-Pulau Kecil 5(2):139-151.

Teklay, A., Dile, Y.T., Asfaw, D.H., Bayabil, H.K. and Sisay, K. 2021. Impacts of climate and land use change on hydrological response in Gumara Watershed, Ethiopia. Ecohydrology & Hydrobiology 21(2).

Tentua, V. C., Gaspersz, E.J. dan Puturuhu, F. 2018. Evaluasi permukiman berdasarkan tingkat kerawanan banjir pada DAS Wae Ruhu. Jurnal Budidaya Pertanian 14(2):113-124.

Tian, G., Ma, B., Xu, X., Liu, X., Xu, L., Liu, X., Xiao, L. and Kong, L. 2016. Simulation of urban expansion and encroachment using cellular automata and multi-agent system model-A case study of Tianjin metropolitan region, China. Ecological Indicators 70:439-450.

Zadeh, L.A. 1994. Fuzzy logic, neural networks, and soft computing. Communications of the ACM 37(3):77-84.

Zheng, H.W., Shen, G.Q., Wang, H. and Hong, J. 2015. Simulating land use change in urban renewal areas: A case study in Hong Kong. Habitat International 46:23-34.