Land Cover Modeling in 2034 in Waiheru Watershed, Ambon City, Indonesia Using CA-Markov

Authors

  • Heinrich Rakuasa Department of Geography, National Research Tomsk State University, Russian Federation
  • Vadim Khromykh Department of Geography, National Research Tomsk State University, Russian Federation

DOI:

https://doi.org/10.30871/jagi.v9i2.8580

Keywords:

Cellular automata, land cover, Markov Chain, Waiheru

Abstract

The increasing demand for land due to population growth and community activities in Ambon City certainly has an impact on land cover changes in the Waiheru Watershed. Therefore, it is important to model future land cover as a sustainable environmental planning material. This study aims to analyze land cover changes in 2014, 2019, 2024 and model land cover in 2034 with the Cellular Automata Markov Chain (CA-Markov) approach. This method integrates historical land cover data and factors driving land use change, elevation, slope, distance from road, distance from river, population, distance from point of interst. The results show a trend of conversion of mixed agricultural land into residential areas, which certainly has the potential to exacerbate ecosystem vulnerability in the Waiheru watershed. Settlement land cover continues to increase in area, namely 68.78 ha in 2014, 77.73 ha in 2019, 96.72 ha in 2024 and the modeling results in 2034 show that settlement land has an area of 138.65 ha, this is in contrast to the forest area which has decreased due to the expansion of population settlements.These findings are expected to provide insights for policy makers and urban planners in formulating sustainable land management strategies, as well as maintaining a balance between development needs and environmental conservation in the Waiheru watershed.

Downloads

Download data is not yet available.

References

Balist, Jahanbakhsh et al. 2021. ‘Detecting Land Use and Climate Impacts on Water Yield Ecosystem Service in Arid and Semi-Arid Areas. A Study in Sirvan River Basin-Iran’. Applied Water Science 12(1): 4. https://doi.org/10.1007/s13201-021-01545-8.

Beroho, Mohamed et al. 2023. ‘Future Scenarios of Land Use/Land Cover (LULC) Based on a CA-Markov Simulation Model: Case of a Mediterranean Watershed in Morocco’. Remote Sensing 15(4): 1162. https://www.mdpi.com/2072-4292/15/4/1162.

Fitriana, A. et al. 2021. ‘Land Change Prediction in Bondowoso Regency Using Automata Markov Method’. {IOP} Conference Series: Earth and Environmental Science 311(4): 100321. https://doi.org/10.1088/1755-1315/311/1/012073.

Ghosh, Pramit et al. 2017. ‘Application of Cellular Automata and Markov-Chain Model in Geospatial Environmental Modeling- A Review’. Remote Sensing Applications: Society and Environment 5: 64–77. https://www.sciencedirect.com/science/article/pii/S2352938516300258.

Ildoromi, A., Nori, H., Naderi, M., Amin, S. A., & Zeinivand, H. 2015. ‘Land Use Change Prediction Using Markov Chain and CA Markov Model (Case Study: Gareen Watershed)’. journal of watershed management research 8(16): 232–40. http://jwmr.sanru.ac.ir/article-1-919-en.html.

Jafarpour Ghalehteimouri, Kamran et al. 2022. ‘Predicting Spatial and Decadal of Land Use and Land Cover Change Using Integrated Cellular Automata Markov Chain Model Based Scenarios (2019–2049) Zarriné-Rūd River Basin in Iran’. Environmental Challenges 6: 100399. https://linkinghub.elsevier.com/retrieve/pii/S2667010021003735.

Kusratmoko, E, S D Y Albertus, 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. https://doi.org/10.1088/1755-1315/54/1/012103.

Latue, P. C., & Rakuasa, H. 2023. ‘Analysis of Land Cover Change Due to Urban Growth in Central Ternate District, Ternate City Using Cellular Automata-Markov Chain’. Journal of Applied Geospatial Information 7(1): 722–28.

Manakane, Susan E, Philia Christi Latue, Glendy Somae, and Heinrich Rakuasa. 2023. ‘Prediction of Land Cover Change in Wae Heru Watershed Ambon City Using Celular Automata Markov Chain’. Journal of Geographical Sciences and Education 1(1): 1–11. https://journal.pubsains.com/index.php/jgs/article/view/52.

Maurya, Nitesh Kumar, Sana Rafi, and Saima Shamoo. 2022. ‘Land Use/Land Cover Dynamics Study and Prediction in Jaipur City Using CA Markov Model Integrated with Road Network’. GeoJournal 88(1): 137–60. https://link.springer.com/10.1007/s10708-022-10593-9.

Rakuasa, Heinrich et al. 2022. ‘Spatial Dynamics Model of Earthquake Prone Area in Ambon City’. IOP Conference Series: Earth and Environmental Science 1039(1): 012057. https://iopscience.iop.org/article/10.1088/1755-1315/1039/1/012057.

Rakuasa, Heinrich, and Philia Christi Latue. 2023. ‘Analisis Spasial Daerah Rawan Banjir Di DAS Wae Heru, Kota Ambon’. Jurnal Tanah dan Sumberdaya Lahan 10(1): 75–82. https://jtsl.ub.ac.id/index.php/jtsl/article/view/845.

Salakory, M., Rakuasa, H. 2022. ‘Modeling of Cellular Automata Markov Chain for Predicting the Carrying Capacity of Ambon City’. Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL) 12(2): 372–87.

Selmy, Salman A. H. et al. 2023. ‘Detecting, Analyzing, and Predicting Land Use/Land Cover (LULC) Changes in Arid Regions Using Landsat Images, CA-Markov Hybrid Model, and GIS Techniques’. Remote Sensing 15(23): 5522. https://www.mdpi.com/2072-4292/15/23/5522.

Subiyanto, S, and F J Amarrohman. 2019. ‘Analysis of Changes Settlement and Fair Market Land Prices to Predict Physical Development Area Using Cellular Automata Markov Model and {SIG} in East Ungaran Distric’. {IOP} Conference Series: Earth and Environmental Science 313: 12002. https://doi.org/10.1088/1755-1315/313/1/012002.

Supriatna, Supriatna et al. 2022. ‘CA-Markov Chain Model-Based Predictions of Land Cover: A Case Study of Banjarmasin City’. Indonesian Journal of Geography 54(3). https://journal.ugm.ac.id/ijg/article/view/71721.

Weslati, Okba, Samir Bouaziz, and Mohamed Moncef Sarbeji. 2023. ‘Modelling and Assessing the Spatiotemporal Changes to Future Land Use Change Scenarios Using Remote Sensing and CA-Markov Model in the Mellegue Catchment’. Journal of the Indian Society of Remote Sensing 51(1): 9–29. https://link.springer.com/10.1007/s12524-022-01618-4.

Downloads

Published

2025-12-26

Issue

Vol. 9 No. 2 (2025): Journal of Applied Geospatial Information (JAGI)

Section

Articles

License

Copyright (c) 2026 Journal of Applied Geospatial Information

Creative Commons License

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

Copyright @2023. This is an open-access article distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License which permits unrestricted use, distribution, and reproduction in any medium. Copyrights of all materials published in JAGI are freely available without charge to users or / institution. Users are allowed to read, download, copy, distribute, search, or link to full-text articles in this journal without asking by giving appropriate credit, provide a link to the license, and indicate if changes were made. All of the remix, transform, or build upon the material must distribute the contributions under the same license as the original.