Analisis Pengaruh Perubahan Kerapatan Vegetasi Terhadap Suhu Permukaan Karena Kegiatan Pertambangan Menggunakan Citra Satelit Multiwaktu (studi kasus: PT. AMMAN MINERAL NUSA TENGGARA)

Bayu Wisnu Putra; Djurdjani Djurdjani

doi:10.22146/jgise.54217

Analisis Pengaruh Perubahan Kerapatan Vegetasi Terhadap Suhu Permukaan Karena Kegiatan Pertambangan Menggunakan Citra Satelit Multiwaktu (studi kasus: PT. AMMAN MINERAL NUSA TENGGARA)

https://doi.org/10.22146/jgise.54217

Bayu Wisnu Putra⁽¹⁾, Djurdjani Djurdjani^(2*)

(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(*) Corresponding Author

Abstract

PT.Amman Mineral Nusa Tenggara (PT.AMNT) is an Indonesian mining company that operates the Batu Hijau mine. Mining activities can cause a decrease in vegetation cover and can have an impact on increasing surface temperature. This study aims to determine how the impact of mining activities on vegetation density and surface temperature. The change in vegetation density and surface temperature in the mining area can be detected by processing of remote sensing satellite imagery with different data recording times. The data used are five Landsat satellite imagery in 1998, 2004, 2008, 2014 and 2018. Vegetation index extraction process is carried out using the NDVI (Normalized Difference Vegetation Index) formula. While surface temperature extraction process is carried out using the Mono-window Brightness Temperature method. The results of the extraction process are then used to analyze the effect of vegetation density changes on surface temperature. The results of this study indicate that the vegetation density in the mining area has decreased and the average surface temperature has increased. The results of the correlation analysis showed that the decrease in the level of vegetation density caused the increase in surface temperature in the mining area of PT.AMNT.

Keywords

Remote Sensing, Mining, Landsat Satellite Imagery, Surface Temperature, Vegetation Index

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References

Balkau, F. dan Parsons, A. (1999). Emerging Environmental Issues For Mining In The PECC Region. Lima. "doi: 10.1017/CBO9781107415324.004.

Bobrinskaya M. (2012). Remote Sensing for Analysis of Relationships between Land Cover and Land Surface Temperature in Ten Megacities. Thesis in Geoinformatics. School of Architecture and the Built Environment Royal Institute of Technology (KTH) Stockholm, Sweden.

Connors J.P., Christopher S. Galletti, Winston T. L., Chow. (2013). Landscape configuration and urban heat island effects: Assessing the relationship between landscape characteristics and land surface temperature in Phoenix, Arizona. Landscape Ecology, 2013, vol. 28, pp. 271–283.

Fawzi, N. I. (2014). Pemetaan Emisivitas Menggunakan Indeks Vegetasi (Surface Emissivity Mapping Using Vegetation Indices). Majalah Ilmiah Globë, 16(2), hal. 133–140.

Indmira. (2015). Tahapan-Tahapan Kegiatan Usaha Pertambangan. Tersedia pada: http:/ /indmira.com/id/tahapan-tahapan-reklamasi-usaha-pertambangan/ (Diakses: 27 November 2018).

Jianga J dan Tiana G. (2010). Analysis of the impact of Land use/Land cover change on Land Surface Temperature with Remote Sensing. Procedia Environmental Sciences 2 (2010) 571–575.

Kementerian ESDM. (2017). Laporan Kinerja Kementerian ESDM 2017. Jakarta.

Lilly R. A, Monsingh D. Devadas. (2009). Analysis Of Land Surface Temperature And Land Use / Land Cover Types Using Remote Sensing Imagery - A Case In Chennai City, India. The seventh International Conference on Urban Climate, 29 June - 3 July 2009, Yokohama, Japan.

Mallick J., Yogesh Kant, B.D.Bharath. (2008). Estimation of land surface temperature over Delhi using Landsat-7 ETM+. J. Ind. Geophys. Union ( July 2008 ) Vol.12, No.3, hal.131-140.

Parmadi, W. T. dan Sukojo, B. M. (2016). Analisa Ketelitian Geometric Citra Pleiades Sebagai Penunjang Peta Dasar RDTR (Studi Kasus: Wilayah Kabupaten Bangkalan, Jawa Timur). 5(2).

PT. Amman Mineral Nusa Tenggara. (2018). TENTANG KAMI. Tersedia pada: http://www.amnt.co.id/ id/tentang-kami (Diakses: 26 November 2018).

Santosa, P. B. (2016). Evaluation of satellite image correction methods caused by differential terrain illumination. Jurnal Forum Geografi. Vol. 30, No. 1 (2016). doi:10.23917/forgeo.v30i1.1768

Qihao W., Dengsheng L., Jacquelyn S. (2004). Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89 (2004), hal. 467–483.

Rhee J., Seonyoung P., Zhenyu L. (2014). Relationship between Land Cover Patterns and SurfaceTemperature in Urban Areas. GIScience and Remote Sensing 51(5), hal. 521-536.

Rongali, G., Keshari, A. K., Gosain, A. K., dan Kosha, R. (2018). A mono-window algorithm for land surface temperature estimation from landsat 8 thermal infrared sensor data: A case study of the beas river basin, India. Pertanika Journal of Science and Technology, 26(2), hal. 829–840.

Sugiyono. (2007). Statistika Untuk Penelitian. Diedit oleh E. Mulyatiningsih. Bandung: ALFABETA.

Sun Q., Zhifeng Wu., Jianjun Tan. (2012). The relationship between land surface temperature and land use/land cover in Guangzhou, China. Environ Earth Sci (2012) 65:1687–1694

Susanto, A. (2013). Pengaruh Modifikasi Iklim Mikro dengan Vegetasi Ruang Terbuka Hijau (RTH) dalam Pengendalian Penyakit Malaria. Jurnal Sains dan Teknologi Lingkungan, 5(1), hal. 01-11. doi: 10.20885/jstl.vol5.iss1.art1.

Tariq A., Iqra R. Zulfiqar A., Bisheng Y., Muhammad A., Rukhsana K., Shaista A., Muhammad A.F., Muhammad R. (2020). Land surface temperature relation with normalized satellite indices for the estimation of spatio‑temporal trends in temperature among various land use land cover classes of an arid Potohar region using Landsat data. Environmental Earth Sciences (2020) 79:40

U.S. Geological Survey. (2018a). LANDSAT 7 (L7) DATA USERS HANDBOOK. 1.0. South Dakota: Department of the Interior U.S. Geological Survey. Tersedia pada: https://landsat.usgs.gov/sites/default/files/documents/LSDS-1927_L7_Data_Users_Handbook.pdf.

U.S. Geological Survey. (2018b). NDVI, the Foundation for Remote Sensing Phenology. Tersedia pada: https://www.usgs.gov/land-resources/eros/ phenology/science/ndvi-foundation-remote-sensing-phenology (Diakses: 6 Januari 2020).

U.S. Geological Survey. (2019). LANDSAT 8 (L8) DATA USERS HANDBOOK Version 4.0. South Dakota: Department of the Interior U.S. Geological Survey. Tersedia pada: https://www.usgs.gov/ media/files/landsat-8-data-users-handbook.

Valor, E. dan Caselles, V. (1996). Mapping land surface emissivity from NDVI: Application to European, African, and South American areas. Remote Sensing of Environment, 57(3), hal. 167–184.

DOI: https://doi.org/10.22146/jgise.54217