DOI: https://doi.org/10.14710/tpwk.2023.35966

Prediksi Tutupan Lahan dalam Melihat Perkembangan Lahan Sawah di Kota Gorontalo Menggunakan Permodelan Cellular Automata

*Muhammad Ghozali Pulukadang  -  Departemen Perencanaan Wilayah dan Kota Fakultas Teknik Universitas Diponegoro, Indonesia
Bitta Pigawati  -  Departemen Perencanaan Wilayah dan Kota Fakultas Teknik Universitas Diponegoro, Indonesia

Citation Format:
Abstract
Land development in Indonesia currently tends to have a significant impact on land use change. Gorontalo City is one of the provincial capitals which currently still has an area of more than 800 ha of rice fields. The growing issue related to rice fields is that 50% of the currently identified rice fields will become built up land because they have accessibility and facilities that support the development of built up land. The purpose of this study is to predict the development of land cover in the City of Gorontalo and to analyze the conversion of paddy fields into built-up land. Rice fields are productive lands that are quite important in Gorontalo City, so it is necessary to know how much the reduction is due to the development of built-up land. The dynamics of land cover changes spatially will be analyzed using the Cellular Automata (CA) model with a period of 10 years. The results obtained from this study indicate that the prediction of land cover development with a validation value of 0.55 (Accuracy of Moderate), especially built-up land in 2030 increases by 592 Ha and the conversion of paddy fields into built-up land in 2030 covers an area of 300 Ha in the District North City. The results of this study can be used as recommendations and considerations for Gorontalo City government policies in controlling land in order to achieve a sustainable city.
Fulltext View|Download
Keywords: Development of Crop Land; Suitability; Land Cover; Cellular Automata

Article Metrics:

Article Info
Section: Articles
Language : EN
Recent articles
Dampak Kebijakan Penanganan Pandemi Covid 19 Berdasarkan Persepsi Masyarakat Kota Lama Semarang Sebagai Ruang Terbuka Publik Prediksi Tutupan Lahan dalam Melihat Perkembangan Lahan Sawah di Kota Gorontalo Menggunakan Permodelan Cellular Automata Preferensi Pengguna Gang Terhadap Peletakan Signage Sebagai Respons Terhadap Pandemi COVID-19 di Kampung Sekayu Kota Semarang More recent articles
  1. Aithal, B. H., & Ramachandra, T. V. (2020). Urban Growth Patterns in India: Spatial Analysis for Sustainable Development. CRC Press
  2. Cengiz, S., Görmüş, S., & Oğuz, D. (2022). Analysis of the urban growth pattern through spatial metrics; Ankara City. Land Use Policy, 112(September 2021). https://doi.org/10.1016/j.landusepol.2021.105812
  3. Cheng, H., Liu, Y., He, S., & Shaw, D. (2017). From development zones to edge urban areas in China: A case study of Nansha, Guangzhou City. Cities, 71, 110–122
  4. Doxiadis, C. A., & others. (1968). Ekistics; an introduction to the science of human settlements
  5. Ghozali, I. (2016). Aplikasi Analisis Multivariate dengan Program IBM SPSS 23 (Edisi 8). Semarang: Semarang: Badan Penerbit Universitas Diponegoro
  6. Han, H., Yang, C., & Song, J. (2015). Scenario simulation and the prediction of land use and land cover change in Beijing, China. Sustainability, 7(4), 4260–4279
  7. Hilmansyah, H., & Rudiarto, I. (2015). Kajian perkembangan dan kesesuaian lahan permukiman eksisting di Kecamatan Indramayu. Teknik PWK (Perencanaan Wilayah Kota), 4(1), 54–65
  8. Manson, S. (2006). Land use in the southern Yucatán in Peninsular Region Of Mexico. Computers, Environment and Urban Systems, 230–253
  9. 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), 215. https://doi.org/10.14710/jwl.6.3.215-233
  10. Permana, D. P., Suprayogi, A., & Prasetyo, Y. (2017). Identifikasi kesesuaian lahan untuk relokasi permukiman menggunakan sistem informasi geografis (studi kasus: Kabupaten Banjarnegara). Jurnal Geodesi Undip, 6(4), 391–401
  11. Pigawati, B., Yuliastuti, N., & Mardiansjah, F. H. (2017). Pembatasan Perkembangan Permukiman Kawasan Pinggiran Sebagai Upaya Pengendalian Perkembangan Kota Semarang. Tataloka, 19(4), 306–319
  12. Rosytha, A. (2016). Studi Dampak Pengembangan Pemukiman di Wilayah Pesisir Surabaya Timur. Agregat, 1(2), 38–43
  13. Sahana, M., Hong, H., & Sajjad, H. (2018). Analyzing urban spatial patterns and trend of urban growth using urban sprawl matrix: A study on Kolkata urban agglomeration, India. Science of the Total Environment, 628–629, 1557–1566. https://doi.org/10.1016/j.scitotenv.2018.02.170
  14. Sejati, A. W., Buchori, I., & Rudiarto, I. (2019). The spatio-temporal trends of urban growth and surface urban heat islands over two decades in the Semarang Metropolitan Region. Sustainable Cities and Society, 46(July 2018), 101432. https://doi.org/10.1016/j.scs.2019.101432
  15. Tian, G., Ma, B., Xu, X., Liu, X., Xu, L., Liu, X., … 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. https://doi.org/10.1016/j.ecolind.2016.06.021
  16. Wunarlan, I. (2019). Adaptasi Penduduk Terhadap Bencana Banjir Di Kota Gorontalo. Prosiding SEMSINA, I–7

Last update:

No citation recorded.

Last update:

No citation recorded.