Analysis of Land Cover Change: Case Study in Concession Area of PT. GRUTI Unit Tele I North Sumatra
DOI:
https://doi.org/10.32734/jsi.v9i01.20138Keywords:
Forest, GIS, Land Cover, Supervised Classification, TeleAbstract
Changes in cover are the result of human activities and natural phenomena. Land cover in an area always changes over time. This study aims to identify and analyze the condition of land cover in 2013 and 2023 in the concession area of PT. GRUTI Unit Tele I obtained through guided classification using ArcGIS 10.4 software and Microsoft Excel. The results of the study showed that throughout 2013-2023 in Unit Tele I there was a change in the area of forest from 14,468.85 ha to 14,138.91 ha. In non-forest areas, there is an increase in area from 443.43 ha to 874.98 ha, and open areas have decreased from 410.22 ha to 402.21 ha. Changes in land cover are dominated by land occupation by the community due to a lack of supervision from concession managers and the absence of production activities in the area.
Downloads
References
1. Kesaulija, S. E., Moeljono, S., & Murdjoko, A. (2020). Analysis of land cover changes in South Manokwari Regency. Cassowary, 3(2), 141–152.
2. Dzakiyah, I. F., & Prasasti, I. (2019). Analysis of land cover changes due to natural disasters using Landsat 8 imagery. In Proceedings of the National Seminar on Sustainable Infrastructure 2019 in the Era of the Industrial Revolution 4.0 (pp. 19–26). National Institute of Technology Malang.
3. Abebe, G., Getachew, D., & Ewunetu, A. (2022). Analyzing land use/land cover changes and its dynamics using remote sensing and GIS in Gubalafito District, Northeastern Ethiopia. SN Applied Sciences, 4(1).
4. Tsujino, R., Yumoto, T., Kitamura, S., Djamaluddin, I., & Darnaedi, D. (2016). History of forest loss and degradation in Indonesia. Land Use Policy, 57, 335–347.
5. Hao, B., Ma, M., Li, S., Li, Q., Hao, D., Huang, J., Ge, Z., Yang, H., & Han, X. (2019). Land use change and climate variation in the Three Gorges Reservoir catchment from 2000 to 2015 based on Google Earth Engine. Sensors, 19(9).
6. Permatasari, R., Arwin, & Natakusumah, D. K. (2017). The effect of land use change on the hydrological regime of the watershed (Case study: Komering Watershed). Civil Engineering Journal, 24(1), 91–98.
7. Setiawan, G., Syaufina, L., & Puspaningsih, N. (2015). Estimation of carbon stock loss from land use changes in Bogor Regency. Journal of Natural Resources and Environmental Management, 5(2), 141–147.
8. Dewa, D. D., & Sejati, A. W. (2019). The effect of land cover changes on GHG emissions in fast-growing areas in Semarang City. Indonesian Journal of Remote Sensing, 1(1), 24–31.
9. Madasa, A., Orimoloye, I. R., & Ololade, O. O. (2021). Application of geospatial indices for mapping land cover/use change detection in a mining area. Journal of African Earth Sciences, 175, 104–108.
10. Phiri, D., & Morgenroth, J. (2017). Developments in Landsat land cover classification methods: A review. Remote Sensing, 9(9), 1–25.
11. Agoes, H. F., Irawan, F. A., & Marlianisya, R. (2018). Interpretation of remote sensing digital imagery for making rice field maps and estimating rice harvest results. INTEKNA Journal: Technical and Commercial Information, 18(1), 24–30.
12. Sulistiyono, N., Nifrody, T., Patana, P., & Susilowati, A. (2019). Estimation of forest degradation distribution using Landsat satellite imagery in Besitang forest landscape. IOP Conference Series: Earth and Environmental Science, 374(1), 012031.
13. Latifah, S., Samsuri, & Rahmawaty. (2018). Introduction to spatial analysis with ArcGIS. USU Press.
14. Soeprihanto, P. (2022). Forestry business – Forestry multi-enterprise. STANDARD: Better Standard Better Living, 1(4), 38–43.
15. Kosasih, D., Saleh, M. B., & Prasetyo, L. B. (2022). Interpretasi visual dan digital untuk klasifikasi tutupan lahan di Kabupaten Kuningan, Jawa Barat. Jurnal Ilmu Pertanian Indonesia (JIPI), 24(2), 101–108.
16. Purwanto, Latifah, Yonariza, Akhsani, F., Sofiana, E. I., & Ferdiansah, M. R. (2022). Land cover change assessment using random forest and CA-Markov from remote sensing images in the protected forest of South Malang, Indonesia. Remote Sensing Applications: Society and Environment, 32, 101061.
17. Latifah, S., Purwoko, A., & Siregar, J. W. (2023). Exploration of species and spatial distribution of non-timber forest products using geographic information systems (GIS). Journal of Sylva Indonesiana, 6(1), 1–9.
18. Latifah, S., Yonariza, & Purwanto. (2023). Study of community forest management (HKm) on socio-economic sustainability in several regions of Indonesia. IOP Conference Series: Earth and Environmental Science, 1188, 012026.
19. Sinaga, S. H., Suprayogi, A., & Haniah. (2018). Analysis of green open space availability using NDVI and SAVI methods based on Sentinel-2A imagery (Case study: Demak Regency). Undip Geodesy Journal, 7(1), 202–211.
20. Rwanga, S. S., & Ndambuki, J. M. (2017). Accuracy assessment of land use/land cover classification using remote sensing and GIS. International Journal of Geosciences, 8, 611–622.
21. Mabrur, A. Y., Noraini, A., & Kumala, I. S. (2023). Making WebGIS as a village potential information visualization. ENMAP (Environment & Mapping) Journal, 4(1), 1–6.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
