Simulating land use changes and environmental implications of transportation development in Barru Regency using cellular automata

Ali, Mukti; Basri, Yuni Andiyani; Haerani

doi:10.12912/27197050/200412

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Tytuł artykułu

Simulating land use changes and environmental implications of transportation development in Barru Regency using cellular automata

Autorzy

Ali Mukti , Basri Yuni Andiyani , Haerani

Treść / Zawartość

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DOI

10.12912/27197050/200412

Warianty tytułu

Języki publikacji

Abstrakty

The expansion of transportation infrastructure often induces significant changes in land use patterns within adjacent areas, accompanied by ecological impacts on natural landscapes and environmental sustainability. This study aims to project anticipated land use changes surrounding the construction zone of the Takkalasi-Bainange-Lawo road in Barru Regency, Indonesia, using the cellular automata (CA) approach integrated with geographic information systems (GIS). The simulation results reveal substantial land use transformations over the next two decades, including the conversion of six land use categories such as rice fields, mixed gardens, upland fields, and residential and industrial zones. Projections indicate a reduction in agricultural land, particularly rice fields, which also support local ecosystems, by approximately 6.2 hectares from 2023 to 2043, driven by increasing demands for residential and industrial development. Conversely, industrial zones are expected to expand significantly, with land converted from other categories such as rice fields and mixed gardens, potentially affecting biodiversity and ecological balance. This study provides critical insights for sustainable land use planning by addressing environmental impacts and the requirements of transportation infrastructure development.

Słowa kluczowe

land use changes cellular automata CA transportation infrastructure development geographic information system

Wydawca

Lubelski Oddział Polskiego Towarzystwo Inżynierii Ekologicznej
Lublin University of Technology
WNGB Wydawnictwo Naukowe

Czasopismo

Ecological Engineering & Environmental Technology

Rocznik

2025

Tom

Vol. 26, iss. 4

Strony

1--12

Opis fizyczny

Bibliogr. 36 poz., rys., tab.

Twórcy

autor

Ali Mukti

Department of Urban and Regional Planning, Faculty of Engineering, Hasanuddin University, Makassar, Indonesia

https://orcid.org/0000-0001-9587-3522

autor

Basri Yuni Andiyani

yuniandiya@gmail.com

Department Regional Planning and Development Planning, Graduate School, Hasanuddin University, Makassar, Indonesia

https://orcid.org/0009-0004-9775-7858

autor

Haerani

Department of Agricultural Technology, Faculty of Agriculture, Hasanuddin University, Makassar, Indonesia

https://orcid.org/0000-0002-4767-5406

Bibliografia

1. Aidi, M. N., & Maulana, S. I. (2020). a Spatial Model for Predicting the Occurences of Deforestation in the Island of Sumatra, Indonesia. Journal of Sustainability Science and Management, 15(6), 75–84. https://doi.org/10.46754/jbsd.2020.08.007
2. Al-Darwish, Y., Ayad, H., Taha, D., & Saadallah, D. (2018). Predicting the future urban growth and it’s impacts on the surrounding environment using urban simulation models: Case study of Ibb city – Yemen. Alexandria Engineering Journal, 57(4), 2887– 2895. https://doi.org/10.1016/j.aej.2017.10.009
3. Alemu, M., Warkineh, B., Lulekal, E., & Asfaw, Z. (2024). Analysis of land use land cover change dynamics in Habru District, Amhara Region, Ethiopia. Heliyon, 10(19), e38971. https://doi.org/10.1016/j. heliyon.2024.e38971
4. Badoe, D. A., & Miller, E. J. (2000). Transportation–land-use interaction: empirical findings in North America, and their implications for modeling. Transportation Research Part D: Transport and Environment, 5(4), 235–263. https://doi.org/10.1016/s1361-9209(99)00036-X
5. Barreira-González, P., Gómez-Delgado, M., & Aguilera-Benavente, F. (2015). From raster to vector cellular automata models: A new approach to simulate urban growth with the help of graph theory. Computers, Environment and Urban Systems, 54, 119–131. https://doi.org/https://doi.org/10.1016/j. compenvurbsys.2015.07.004
6. Bris, A., Wang, T. Y. H., Zatzick, C. D., Miller, D. J. P., Fern, M. J., Cardinal, L. B., Gregoire, D. A., Shepherd, D. A., Westphal, J. D., Shani, G., Troster, C., Van Quaquebeke, N., Lanaj, K., Hollenbeck, J. R., Ilgen, D. R., Barnes, C. M., Harmon, S. J., Feldman, E. R., DesJardine, M. R., … Sangiorgi, F. (2021). Knights, raiders, and targets - the impact of the hostile takeover - coffee, Jc, Lowenstein,L, Roseackerman, S. Journal Of Banking & Finance, 37(1).
7. Chen, Z., & Dong, H. (2024). Exploring urban and agricultural land use planning. Results in Engineering, 24(October), 103093. https://doi.org/10.1016/j. rineng.2024.103093
8. Csomós, G., Szalai, Á., & Farkas, J. Z. (2024). A sacrifice for the greater good? On the main drivers of excessive land take and land use change in Hungary. Land Use Policy, 147(September), 0–2. https://doi.org/10.1016/j.landusepol.2024.107352
9. Ge, K., Wang, Y., Liu, X., Ke, S., Jiang, X., & Lu, X. (2024). Impacts and threshold effects of urban–rural integration on the transition of arable land use functions. Ecological Indicators, 166(July), 112595. https://doi.org/10.1016/j.ecolind.2024.112595
10. Geng, J., Shen, S., Cheng, C., & Dai, K. (2022). A hybrid spatiotemporal convolution-based cellular automata model (ST-CA) for land-use/cover change simulation. International Journal of Applied Earth Observation and Geoinformation, 110(April), 102789. https://doi.org/10.1016/j.jag.2022.102789
11. Ghatak, M., & Mookherjee, D. (2014). Land acquisition for industrialization and compensation of displaced farmers. Journal of Development Economics, 110, 303–312. https://doi.org/10.1016/J. JDEVECO.2013.01.001
12. Jaeger, J. A. G., Bertiller, R., Schwick, C., Müller, K., Steinmeier, C., Ewald, K. C., & Ghazoul, J. (2008). Implementing landscape fragmentation as an indicator in the swiss monitoring system of sustainable development (Monet). Journal of Environmental Management, 88(4), 737–751. https://doi.org/10.1016/J.JENVMAN.2007.03.043
13. Jamaluddin, A. A., & Parung, H. (2024). Implementation of Aerotropolis Concept in the Development of the Areas Around Sultan Hasanuddin International Airport. X(X), 1–11.
14. Jia, K., Huang, X., Qiao, W., & Zhong, S. (2024). Unpacking divergent rural-urban land use dynamics in county urbanization: A comparative socio-spatial analytics approach. Cities, 154, 105343. https://doi.org/10.1016/J.CITIES.2024.105343
15. Jiang, Y., Long, H., Tang, Y. ting, & Deng, W. (2024). Deciphering how promoting land consolidation for village revitalization in rural China: A comparison study. Journal of Rural Studies, 110, 103349. https://doi.org/10.1016/J.JRURSTUD.2024.103349
16. Kasraian, D., Maat, K., Stead, D., & van Wee, B. (2016). Long-term impacts of transport infrastructure networks on land-use change: an international review of empirical studies. Transport Reviews, 36(6), 772–792. https://doi.org/10.1080/01441647 .2016.1168887
17. Lin, J., Li, X., Wen, Y., & He, P. (2023). Modeling urban land-use changes using a landscape-driven patch-based cellular automaton (LP-CA). Cities, 132(August 2021), 103906. https://doi.org/10.1016/j.cities.2022.103906
18. Liu, J., Liu, B., Wu, L., Miao, H., Liu, J., Jiang, K., Ding, H., Gao, W., & Liu, T. (2024). Prediction of land use for the next 30 years using the PLUS model’s multi-scenario simulation in Guizhou Province, China. Scientific Reports, 14(1), 1–12. https://doi.org/10.1038/s41598-024-64014-7
19. Ma, S., Wang, G., Xu, C., Zhang, X., Zhao, Y., & Cai, Y. (2024). Does the optimal land use pattern for cross-regional cooperation change at different stages of urbanization? Evidence from the trade-off between urban growth scenarios and SDGs indicators. Applied Geography, 167, 103294. https://doi.org/10.1016/J.APGEOG.2024.103294
20. Mamat, L., Basri, N. E. A., Zain, S. M., & Rahmah, E. (2016). Environmental sustainability indicators as impact tracker: A review. Journal of Sustainability Science and Management, 11(1), 29–42.
21. Molinero-Parejo, R., Aguilera-Benavente, F., Gómez-Delgado, M., & Shurupov, N. (2023). Combining a land parcel cellular automata (LP-CA) model with participatory approaches in the simulation of disruptive future scenarios of urban land use change. Computers, Environment and Urban Systems, 99(March 2022). https://doi.org/10.1016/j. compenvurbsys.2022.101895
22. Nguyen, T. H. T., Tran, V. T., Bui, Q. T., Man, Q. H., & Walter, T. de V. (2016). Socio-economic effects of agricultural land conversion for urban development: Case study of Hanoi, Vietnam. Land Use Policy, 54, 583–592. https://doi.org/10.1016/J. LANDUSEPOL.2016.02.032
23. Paddiyatu, N., Umar, F., Zainuddin, S., & Arista, M. A. Y. (2023). Model Perkembangan Permukiman Berbasis Cellular Automata di Kabupaten Takalar. Jurnal Pembangunan Wilayah Dan Kota, 19(3), 409–421. https://doi.org/10.14710/pwk.v19i3.45639
24. Pratomoatmojo, N. A. (2018). LanduseSim Algorithm: Land use change modelling by means of cellular automata and Geographic Information System. IOP Conference Series: Earth and Environmental Science, 202(1), 0–12. https://doi.org/10.1088/1755-1315/202/1/012020
25. Purwanto, A., & Andrasmoro, D. (2021). Land capability evaluation of former bauxite mining land for land use planning by integrating remote sensing and geographic information system in Sanggau West Kalimantan Indonesia. Journal of Sustainability Science and Management, 16(6), 214–227. https://doi.org/10.46754/jssm.2021.08.019
26. Qin, S., Wang, C., & Yan, Y. (2024). Identification of conflict and its evolution between land use and land suitability during urban expansion: A case of Guangzhou, China. Ecological Frontiers. https://doi.org/10.1016/J.ECOFRO.2024.08.006
27. Rakuasa, H., Salakory, M., & Latue, P. C. (2022). Analisis Dan prediksi perubahan tutupan lahan menggunakan model celular automata-Markov Chain Di Das Wae Ruhu Kota Ambon. Jurnal Tanah Dan Sumberdaya Lahan, 9(2), 285–295. https://doi.org/10.21776/ub.jtsl.2022.009.2.9
28. Sari, K. D. R., & Santoso, E. B. (2017). Analisis Keterkaitan Wilayah Peri Urban di Kabupaten Gresik dengan Wilayah Desa-Kota di Sekitarnya. Jurnal Teknik ITS, 6(2), 2–7. https://doi.org/10.12962/ j23373539.v6i2.24971
29. Shaw, S. L., & Xin, X. (2003). Integrated land use and transportation interaction: a temporal GIS exploratory data analysis approach. Journal of Transport Geography, 11(2), 103–115. https://doi.org/10.1016/S0966-6923(02)00070-4
30. Sun, P., Linghu, L., & Zhang, M. (2024). Relationship between regional economic development and its associated land use changes: A case study of Shaanxi province in China. World Development Sustainability, 4(September 2023), 100122. https://doi.org/10.1016/j.wds.2023.100122
31. von Groß, V., Sibhatu, K. T., Knohl, A., Qaim, M., Veldkamp, E., Hölscher, D., Zemp, D. C., Corre, M. D., Grass, I., Fiedler, S., Stiegler, C., Irawan, B., Sundawati, L., Husmann, K., & Paul, C. (2024). Transformation scenarios towards multifunctional landscapes: A multi-criteria land-use allocation model applied to Jambi Province, Indonesia. Journal of Environmental Management, 356, 120710. https://doi.org/10.1016/J.JENVMAN.2024.120710
32. Wenbo, X., Hengzhou, X., Xiaoyan, L., Hua, Q., & Ziyao, W. (2024). Ecosystem services response to future land use/cover change (LUCC) under multiple scenarios: A case study of the Beijing-Tianjin- Hebei (BTH) region, China. Technological Forecasting and Social Change, 205, 123525. https://doi.org/10.1016/J.TECHFORE.2024.123525
33. Xiao, C., Wang, Y., Yan, M., & Chiwuikem Chiaka, J. (2024). Impact of cross-border transportation corridors on changes of land use and landscape pattern: A case study of the China-Laos railway. Landscape and Urban Planning, 241, 104924. https://doi.org/10.1016/J.LANDURBPLAN.2023.104924
34. Yue, W., Qin, C., Su, M., Teng, Y., & Xu, C. (2024). Environmental and Sustainability Indicators Simulation and prediction of land use change in Dongguan of China based on ANN cellular automata - Markov chain model. Environmental and Sustainability Indicators, 22(July 2023), 100355. https://doi.org/10.1016/j.indic.2024.100355
35. Zhang, Z., & Li, J. (2022). Spatial suitability and multi-scenarios for land use: Simulation and policy insights from the production-living-ecological perspective. Land Use Policy, 119, 106219. https://doi.org/10.1016/J.LANDUSEPOL.2022.106219
36. Zong, S., Xu, S., Jiang, X., & Song, C. (2024). Identification and dynamic evolution of land use conflict potentials in China, 2000–2020. Ecological Indicators, 166(July), 112340. https://doi.org/10.1016/j. ecolind.2024.112340

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Bibliografia

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