Analysis of Changes in Green Land Cover of North Minahasa Gold Mine With Landsat 8 Images using the Normalized Difference Vegetation Index

Feni Bahat; Winsy Weku; Chriestie Montolalu

doi:10.47194/orics.v2i4.182

Authors

Feni Bahat
Teni.suriani1988@gmail.com
Winsy Weku
Chriestie Montolalu

Abstract

Mining is an activity of extracting non-renewable natural resources, including coal, whose management cannot be separated from the company. In realizing mining activities, they must be managed optimally, so it is necessary to supervise and monitor their activities effectively and efficiently. North Minahasa Mining Toka Tindung is a gold mine that has been operating since 2009, with the first gold production in 2011, and has gold reserves of 122 tons at the end of 2020. Toka Tindung has a mining area of 8,986 hectares (400 thousand square km), or 1.3 percent of the planned contract of work which is 741,000 hectares. This research was conducted by monitoring mining land cover using remote sensing technology based on Landsat 8 satellite imagery. related to vegetation. NDVI has a range of values between -1 to +1, the results of the transformation have different percentages of land use. The greater or positive the NDVI value, the better the vegetation density in the area. This study aims to analyze changes in green land cover in the mining area of North Minahasa in 2013 to 2021 based on variations in the greenness of the vegetation index. The results of the study obtained that Variations in the greenery index of vegetation ranged from 0.0 - 0.4 in 2013 and -0.2 - 0.6 in 2021. Where the mining area environment in 2013 had a vegetation class in the form of rocks, vacant land, meadows, shrubs and dense forests and in 2021 had a vegetation class in the form of rocks, vacant land, grasslands, shrubs, dense forests and water. In 2021 it has a vegetation value of -0.2 whose vegetation class is water due to the loss of Ground Cover Vegetation due to digging too deep to form ponds. on the ground surface. Thus the level of vegetation density in the mining area of North Minahasa has changed from 2013 to 2021. The area without vegetation has generally increased. Replacing the green area and the area with vegetation cover, dense green land cover has decreased.

References

Ardli, E., R. & Wolff, M. (2009). Land use and land cover change affecting habitat distribution in the Segara Anakan lagoon, Java, Indonesia. Regional Environmental Change, 9(4), 235-243.

Bell, L., C. (2001). Establishment of native ecosystems after miningâ€”Australian experience across diverse biogeographic zones. Ecological Engineering, 17(2-3), 179-186.

Dassot, M., Constant, T. & Fournier, M. (2011). The use of terrestrial LiDAR technology in forest science: application fields, benefits and challenges. Annals of forest science, 68(5), 959-974.

Delarizka, A., and Sasmito, B. (2016). and others, Analisis Fenomena Pulau Bahang (Urban Heat Island) di Kota Semarang Berdasarkan Hubungan antara Perubahan Tutupan Lahan xii dengan Suhu Permukaan Menggunakan Citra Multi Temporal Landsat. Jurnal Geodesi Undip, 5(4), 165â€“177.

Hatulesila, J., W. and Mardiatmoko, G. (2019). and I. Irwanto, Analisis Nilai Indeks Kehijauan (Ndvi) Pada Pola Ruang Kota Ambon, Provinsi Maluku Jurnal Fakultas Pertanian Universitas Pattimura Ambon, pp.60-65.

Hussain, M., Chen, D., Cheng, A., Wei, H., & Stanley, D. (2013). Change detection from remotely sensed images: From pixel-based to object-based approaches. ISPRS Journal of photogrammetry and remote sensing, 80, 91-106.

Jianya, G., Haigang, S., Guorui, M., & Qiming, Z. (2008). A review of multi-temporal remote sensing data change detection algorithms. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B7), 757-762.

Khairawan, A., Falih, N., & Handoko, T. D. (2020). Analisis Perubahan Indeks Kerapatan Vegetasi Memanfaatkan Citra Landsat (Studi Kasus: Provinsi DKI Jakarta). Senamika, 1(2), 62-72.

Nugroho, A. (2016). â€•Analisis Kerapatan Vegetasi Di Kecamatan Ngaglik Tahun 2006 Dan 2016 Menggunakan Teknik Penginderaan Jauh,â€– pp. 306â€“320.

Rogan, J., & Chen, D. (2004). Remote sensing technology for mapping and monitoring land-cover and land-use change. Progress in planning, 61(4), 301-325.

Sampurno, R. M., & Thoriq, A. (2016). Klasifikasi tutupan lahan menggunakan citra landsat 8 operational land imager (OLI) di Kabupaten Sumedang (land cover classification using landsat 8 operational land imager (OLI) data in Sumedang Regency). Jurnal Teknotan, 10(2).

Sharma, R., Nehren, U., Rahman, S., A. Meyer, M., Rimal, B., Aria Seta, G., & Baral, H. (2018). Modeling land use and land cover changes and their effects on biodiversity in Central Kalimantan, Indonesia. Land, 7(2), 57.

Syam, T., Darmawan A., Banuwa, I., S. and Ningsih, K. (2012). Utilization of Satellite Imagery in Identifying of Land Cover Changes : Case Study of Protected Forest of Register 22 Way Waya Central Lampung, Globe Volume, 4(2), hal. 146â€“156 .

Waru, A., T. Bayanuddin, A., A. Nugroho, F., S. Rukminasari, N. (2021). Analisis Temporal Perubahan Hutan Mangrove Menggunakan Citra Satelit Sentinel-2 Studi Kasus Di Pulau Tanakeke, Kabupaten Takalar Jurnal Ilmu Kelautan dan Perikanan, Universitas Hasanuddin, pp. 782-784.

Wibowo, A., Raditya, A., Harmantyo, D., Semedi, J. M. (2015). Land Surface Temperature as Urban Hazard in Education Area (A Case Study: University of Indonesia) Proceeding the First International Conference of Indonesian Society for Remote Sensing