Land Cover Change Prediction Modeling in Tanjungpinang City in 2043

Arie Afriadi; Nefriwati Hilmi; Hoki Apriyenson; Zuleriwati AS

doi:10.24036/eksakta/vol26-iss03/604

EKSAKTA: Berkala Ilmiah Bidang MIPA

Open Access

Land Cover Change Prediction Modeling in Tanjungpinang City in 2043

Arie Afriadi ¹

, Nefriwati Hilmi ¹

, Hoki Apriyenson ¹

, Zuleriwati AS ¹

¹ Department of Urban and Regional Planning, Faculty of Engineering and Marine Technology, Universitas Maritim Raja Ali Haji, Tanjungpinang, Indonesia

Published 2025-09-30

Vol. 26 No. 03 (2025) PAGES 271-287

DOI 10.24036/eksakta/vol26-iss03/604

Views / Downloads 174 160

Download PDF

Abstract

Land cover changes reflect the pressure of development and increased human activities that have an impact on environmental imbalance. As a strategic coastal city, Tanjungpinang faces challenges in maintaining the sustainability of its regional ecosystem. This study aims to analyze the dynamics of land cover changes and predict their conditions until 2043 using remote sensing technology and geographic information systems (GIS), incorporating Cellular Automata and logistic regression methods. The results of the study showed that land cover changes between 2003 and 2023 increased built-up area by 27.15 km² and decreased Vegetation by 14.02 km². Bare Land increased by 1.45 km² at the beginning of the period, then reduced to a total of 12.74 km². Water bodies decreased by 0.39 km². Predictions for 2043 indicate that built-up area increased by 5.12 square kilometres, while Vegetation decreased by 6.33 square kilometres. Bare land increased by 1.34 km², while water bodies declined by 0.14 km². This pattern indicates a trend of converting vegetative land into built-up areas due to the increasing demand for regional space.

References

1

Afuye, G. A., Nduku, L., Kalumba, A. M., Santos, C. A. G., Orimoloye, I. R., Ojeh, V. N., Thamaga, K. H., & Sibandze, P. (2024). Global trend assessment of land use and land cover changes: A systematic approach to future research, development, and planning. Journal of King Saud University - Science.

2

[2] Rustiadi, E., Pravitasari, A. E., Setiawan, Y., Mulya, S. P., Pribadi, D. O., & Tsutsumida, N. (2020). Impact of continuous Jakarta megacity urban expansion on the formation of the Jakarta–Bandung conurbation over the rice farm regions. Cities. Retrieved from

3

[3] Sugianto, S., Deli, A., Miswar, E., Rusdi, M., & Irham, M. (2022). The Effect of Land Use and Land Cover Changes on Flood Occurrence in the Teunom Watershed, Aceh Jaya. Land, 11(8), 1271.

4

[4] Afriyadi, A., Wulandari, A., Panjaitan, D. M., Saputra, E., Handoko, H., Isrania, I., Meilin, M., & Ernantonio, N. (2024). Memahami dinamika ekonomi Tanjung Pinang: Potensi pengembangan dan rekomendasi kebijakan untuk kesejahteraan masyarakat. Jurnal Inovasi Ekonomi Syariah dan Akuntansi (JIESA), 1(4), 65–74.

5

[5] Armayani, R. R., Lubis, H. K., & Sari, N. (2022). Hubungan antara ekonomi dengan lingkungan hidup: Suatu kajian literatur. SINOMIKA Journal, 1(2), 175.

6

[6] Siswanto, S., Nuryanto, D. E., Ferdiansyah, M. R., Prastiwi, A. D., Dewi, O. C., Gamal, A., & Dimyati, M. (2023). Spatio-temporal characteristics of the urban heat island in the Jakarta metropolitan area. Remote Sensing Applications: Society and Environment, 32, 101062.

7

[7] Hasyim, A. W., Sukojo, B. M., Anggraini, I. A., Fatahillah, E. R., & Isdianto, A. (2025). Urban heat island effect and sustainable planning: Analysis of land surface temperature and Vegetation in Malang City. International Journal of Sustainable Development and Planning, 20(2), 683–697.

8

[8] Dinas Lingkungan Hidup dan Kehutanan Provinsi Kepulauan Riau. (2021). Rencana Strategis Dinas Lingkungan Hidup dan Kehutanan Provinsi Kepulauan Riau Tahun 2021–2026. Dinas Lingkungan Hidup dan Kehutanan Provinsi Kepulauan Riau.

9

[9] Jawarneh, R. N., Abulibdeh, A., Hashem, N., Awawdeh, M., Al-Awadhi, T., Abdullah, M. M., & El Kenawy, A. M. (2024). Assessing and predicting land cover dynamics for environmental sustainability in Jordan's arid ecosystems using the CA-Markov model. Remote Sensing Applications: Society and Environment, 33, 101262.

10

[10] Dewi, C. C., Pravitasari, A. E., & Pribadi, D. O. (2023). Arahan pengembangan kawasan permukiman di Kota Tanjungpinang, Provinsi Kepulauan Riau. Jurnal Ilmu Tanah dan Lingkungan (J. Il. Tan. Lingk.), 25(1), 7–18.

11

[11] Ramadhan, G. F., & Hidayati, I. N. (2022). Prediction and simulation of land use and land cover changes using open source QGIS: A case study of Purwokerto, Central Java, Indonesia. Indonesian Journal of Geography, 54(2), 172–180.

12

[12] Nguyen, A., Kovyazin, V., & Pham, C. (2025). Application of remote sensing and GIS in monitoring forest cover changes in Vietnam based on natural zoning. Land, 14(5), 1037.

13

[13] Allan, A., Soltani, A., Abdi, M. H., & Zarei, M. (2022). Driving forces behind land use and land cover change: A systematic and bibliometric review. Land, 11(8), 1222.

14

[14] Lin, J., Li, X., Wen, Y., & He, P. (2022). Modelling urban land-use changes using a landscape-driven patch-based cellular automaton (LP-CA). Cities, 129, 103906.

15

[15] Laksmana, M. B., Zakaria, A., Novianti, T. C., & Armijon. (2024). Analisis prediksi perubahan tutupan lahan tahun 2033 menggunakan metode Cellular Automata dan Logistic Regression. Journal of Plano Studies, 1(2), Desember. ISSN Online: 3047-2857.

16

[16] Badan Pusat Statistik Kota Tanjungpinang. (2024). Kecamatan Tanjungpinang Kota Dalam Angka 2024 / Tanjungpinang Kota Subdistrict in Figures 2024 (Vol. 21, Katalog: 1102001.2172010). BPS-Statistics Tanjungpinang Municipality.

17

[17] Putra, R. D., Napitupulu, H. S., Nugraha, A. H., Suhana, M. P., Ritonga, A. R., & Sari, T. E. Y. (2022). Pemetaan luasan hutan mangrove dengan menggunakan citra satelit di Pulau Mapur, Provinsi Kepulauan Riau. Jurnal Kelautan Tropis, 25(1), 20–30.

18

[18] Vollrath, A., Mullissa, A., & Reiche, J. (2020). Angular-based radiometric slope correction for Sentinel-1 on Google Earth Engine. Remote Sensing, 12(11), 1867.

19

[19] Qiu, S., Zhu, Z., Olofsson, P., Woodcock, C. E., & Jin, S. (2021). Evaluation of Landsat image compositing algorithms. Remote Sensing of Environment, 256, 112307.

20

[20] Arinta, S. P. (2015). Penggunaan citra satelit multi-temporal untuk kajian perubahan pola sungai dan lahan di sekitar aliran sungai pasca erupsi gunung api (Studi kasus: Sub DAS Konto) (Tugas Akhir, Institut Teknologi Sepuluh Nopember). Jurusan Teknik Geomatika, Fakultas Teknik Sipil dan Perencanaan, ITS Surabaya.

21

[21] Egorov, A. V., Hansen, M. C., Roy, D. P., Kommareddy, A., & Potapov, P. V. (2015). Image interpretation-guided supervised classification using nested segmentation. Remote Sensing of Environment, 165, 135–147.

22

[22] Septiani, R., Citra, I. P. A., & Nugraha, A. S. A. (2019). Perbandingan metode supervised classification dan unsupervised classification terhadap penutup lahan di Kabupaten Buleleng. Jurnal Geografi, 16(2).

23

[23] Lu, D., Mausel, P., Batistella, M., & Moran, E. (2004). Comparison of land-cover classification methods in the Brazilian Amazon Basin. International Journal of Remote Sensing, 25(21), 5403–5417.

24

[24] Li, H., Wang, C., Zhong, C., Zhang, Z., & Liu, Q. (2017). Mapping typical urban LULC from Landsat imagery without training samples or self-defined parameters. Remote Sensing, 9(7), 700.

25

[25] García-Rodríguez, D., Pérez-Hoyos, A., Martínez, B., Catret Ruber, P., Samper-Zapater, J. J., López-Baeza, E., & Martínez Durá, J. J. (2025). Comparative analysis of different algorithms for VAS station land cover classification with limited training points. International Journal of Applied Earth Observation and Geoinformation, 139, 104537.

26

[26] Febianti, V., Sasmito, B., & Bashit, N. (2022). Pemodelan perubahan tutupan lahan berbasis penginderaan jauh (Studi kasus: Kota Semarang). Jurnal Geodesi Undip, Oktober, Departemen Teknik Geodesi, Fakultas Teknik, Universitas Diponegoro.

27

[27] Tiede, D. (2014). A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modelling concepts. Cartography and Geographic Information Science, 41(3), 227–234.

28

[28] Hapsary, M. S. A., Subiyanto, S., & Firdaus, H. S. (2021). Analisis Prediksi Perubahan Penggunaan Lahan dengan Pendekatan Artificial Neural Network dan Regresi Logistik di Kota Balikpapan. Jurnal Geodesi Undip, April 2021. Departemen Teknik Geodesi, Fakultas Teknik, Universitas Diponegoro.

29

[29] Fardani, I., Mohmed, F. A. J., & Chofyan, I. (2020). Pemanfaatan Prediksi Tutupan Lahan Berbasis Cellular Automata-Markov dalam Evaluasi Rencana Tata Ruang. MKG, 21(2), 157–169. P-ISSN: 0216-8138 | E-ISSN: 2580-0183.

30

[30] Juniyanti, L., Prasetyo, L. B., Aprianto, D. P., Purnomo, H., & Kartodihardjo, H. (2020). Perubahan penggunaan dan tutupan lahan, serta faktor penyebabnya di Pulau Bengkalis, Provinsi Riau (periode 1990–2019). Journal of Natural Resources and Environmental Management, 10(3), 419–435. E-ISSN: 2460-5824.

31

[31] Hariyati, E. (2024). Prediksi perubahan tutupan/penggunaan lahan tahun 2036 di Kecamatan Kotabumi Utara menggunakan model Cellular Automata (Skripsi Sarjana). Fakultas Keguruan dan Ilmu Pendidikan, Universitas Lampung, Bandar Lampung.

32

[32] Waśniewski, A., Hościło, A., & Aune-Lundberg, L. (2023). The impact of the selection of reference samples and DEM on the accuracy of land cover classification based on Sentinel-2 data. Remote Sensing Applications: Society and Environment, 32, 101035.

33

[33] Demessie, S. F., Dile, Y. T., Bedadi, B., Tarkegn, T. G., Bayabil, H. K., & Sintayehu, D. W. (2024). Assessing and projecting land use land cover changes using machine learning models in the Guder watershed, Ethiopia. Environmental Challenges, 9, 101074.

34

[34] Bodner, G. S., & Robles, M. D. (2017). Enduring a decade of drought: Patterns and drivers of vegetation change in a semi-arid grassland. Journal of Arid Environments, 136, 1–14.

35

[35] Pamungkas, G. B., & Andriani, V. (2023). Contribution of land use change and land cover to climate change coastal areas and their impacts: Evidence in Jayapura City, Papua Province, Indonesia. Jurnal Wilayah dan Lingkungan, 11(1), 36–46.

36

[36] Nofirman, N., Harahap, M. A. K., & Andiani, P. (2023). Studi geomorfologi dan perubahan lanskap dalam konteks perubahan lingkungan di Pulau Jawa. Jurnal Geosains West

37

[37] Selmy, S. A. H., Kucher, D. E., Mozgeris, G., Moursy, A. R. A., Jimenez-Ballesta, R., Kucher, O. D., Fadl, M. E., & Mustafa, A. A. (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.

38

[38] Putra, R. A., Dewi, A. R., & Prasetyo, L. B. (2022). Analisis perubahan tutupan lahan untuk mendukung perencanaan tata ruang wilayah pesisir berbasis geospasial. Jurnal Perencanaan Wilayah dan Kota, 19(1), 55–66.

39

[39] Sofyan, A., & Ridwan, M. (2023). Integrasi pembelajaran geospasial dalam kurikulum sekolah menengah: Studi kasus perubahan lahan di Kota Padang. Jurnal Pendidikan Geografi, 11(2), 93–107.

Land Cover Change Prediction Modeling in Tanjungpinang City in 2043

Abstract

References

How to Cite

Cite Article

Article Update