LAND COVER CHANGE PREDICTION USING CELLULAR AUTOMATA AND MARKOV CHAIN MODELS

Authors

  • Amandus Jong Tallo Program Studi Teknik Perancangan Irigasi Dan Penanganan Pantai, Jurusan Teknik Sipil, Politeknik Negeri Kupang, Indonesia
  • Maria Gratiana Yudith Tallo rogram Studi Manajemen Perusahaan, Jurusan Adminsitrasi Bisnis, Politeknik Negeri Kupang, Indonesia
  • Antonius Leonardo Antjak Program Studi Teknik Perancangan Irigasi Dan Penanganan Pantai, Jurusan Teknik Sipil, Politeknik Negeri Kupang, Indonesia
  • Maria Imanuela Doko Program Studi Teknik Perancangan Irigasi Dan Penanganan Pantai, Jurusan Teknik Sipil, Politeknik Negeri Kupang, Indonesia
  • Maria Anita Christanti Lodang Program Studi Teknik Perancangan Irigasi Dan Penanganan Pantai, Jurusan Teknik Sipil, Politeknik Negeri Kupang, Indonesia

DOI:

https://doi.org/10.33480/techno.v20i2.7200

Keywords:

CA-Markov, Spatial Configuration, Kupang

Abstract

This research examines the impact of land use change on mobility. Spatial problems arise due to increased activity, population, and transportation in the same space, necessitating the development of modeling strategies. This aligns with SDG 11 on cities and settlements, as well as the PRN's focus on transportation innovation. The urgency of this research lies in its adaptive and sustainable spatial prediction efforts aimed at controlling future land use. This study aims to analyze land use change patterns using the Cellular Automata Markov Chain (CA-Markov) model in Kupang City until 2043. CA-Markov simulations efficiently evaluate land cover changes and movement. The quantitative research method was conducted based on spatial predictions and spatial configuration. Quantum GIS (QGIS) and GeoSOS-FLUS were used to obtain results from each stage. There are three research stages. First, identification of land cover (land use in 2018 and 2023), driving factors (distance to settlements, airports, highways, elevation, slope, slope orientation, rainfall, population density), and conservation areas. Second, standardisation of spatial data. Third, land cover prediction using GeoSOS software (five-year prediction) to identify patterns of land use change. These findings emphasize the importance of using CA-Markov-based spatial predictions as a foundation for adaptive spatial planning to control land-use conversion and maintain sustainable spatial connectivity in Kupang City until 2043.

Author Biography

Amandus Jong Tallo, Program Studi Teknik Perancangan Irigasi Dan Penanganan Pantai, Jurusan Teknik Sipil, Politeknik Negeri Kupang, Indonesia

URL Scopus: https://www.scopus.com/authid/detail.uri?authorId=57200984216

URL Google Scholar: https://scholar.google.com/citations?%20user=80Jw3_IAAAAJ&hl=id&user=Y5yUt_gAAAAJ

 

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Published

2025-09-25

How to Cite

Tallo, A. J., Tallo , M. G. Y. ., Antjak, A. L. ., Doko, M. I. ., & Lodang, M. A. C. . (2025). LAND COVER CHANGE PREDICTION USING CELLULAR AUTOMATA AND MARKOV CHAIN MODELS. Jurnal Techno Nusa Mandiri, 20(2), 135–142. https://doi.org/10.33480/techno.v20i2.7200

Issue

Vol. 20 No. 2 (2025): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of September 2025

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Articles

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Copyright (c) 2025 Amandus Jong Tallo, Maria Gratiana Yudith Tallo , Antonius Leonardo Antjak, Maria Imanuela Doko, Maria Anita Christanti Lodang

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