The Rate of Land Cover Change using Landsat Data in Coal Mining Area of Sawah Lunto City, Indonesia
DOI:
https://doi.org/10.26740/jpfa.v9n2.p189-203Keywords:
Sawahlunto, coal mining, Landsat, land cover degradation, supervised classificationAbstract
Sawahlunto city is well-known for coal mining region. As in 2010, there have been at least 12 mining companies exploring coal resources in the region. As time passes, land cover conditions have gradually decreased due to mining activities. This region on which was originally covered by various vegetation and ecosystem have systematically transformed into open areas for coal mining. The use of remote sensing technology for land cover monitoring has been commonly well-developed in accordance with the need for improvement of detailed information about the changes of land use coverage. This study examines the land cover changes using supervised classification method based on Landsat data. The method focuses on four dominant classes of land cover in the region, namely forest, mining, settlement, and water resources. The classification processes were performed based on true-color composite satellite images. The results show that the overall accuracies of classification are 91.68 %, 92.49 %, 93.69 %, and 93.74 % in 2000, 2006, 2011, and 2016 respectively. It was also found that forest is the largest area in the coal mining area which, in some sense, tends to continuously decrease in terms of land cover in the last 15 years. The rate of forest area degradation achieved its maximum between 2006 and 2011.References
Media Garda Asakota. Pertambangan Sumbang Kontribusi Besar APBN; 2017. Available from: http://www.gardaasakota.com/2011/04/pertambangan-sumbang-kontribusi-besar.html.
Syahrir I. Kebijakan Hilirisasi Mineral: Reformasi Kebijakan untuk Meningkatkan Penerimaan Negara. Kajian Ekonomi Keuangan. 2017; 1(1): 42-67. DOI: http://doi.org/10.31685/kek.v1i1.259.
Martokusumo W. The Ex-Coal Mining City of Sawahlunto Revisited. Nakhara: Journal of Environmental Design and Planning 2010; 6: 107-118. Available from: https://www.tci-thaijo.org/index.php/nakhara/article/view/104992.
Fishback PV. The Economics of Company Housing: Historical Perspectives from the Coal Fields. The Journal of Law, Economics, and Organization. 1992; 8(2): 346-365. Available from: https://www.jstor.org/stable/765084.
Mishra UC. Environmental Impact of Coal Industry and Thermal Power Plants in India. Journal of Environmental Radioactivity. 2004; 72(1-2): 35-40. DOI: https://doi.org/10.1016/s0265-931x(03)00183-8.
Kementrian Perindustrian Republik Indonesia. Pemerintah Dorong Industri Gunakan Batubara Sebagai Energi Alternatif. Jakarta: Kementrian Perindustrian Republik Indonesia; 2005.
Prakash A and Gupta RP. Land-Use Mapping and Change Detection in a Coal Mining Area - a Case Study in the Jharia Coalfield, India. International Journal of Remote Sensing. 1998; 19(3): 391-410. DOI: https://doi.org/10.1080/014311698216053.
Schwärzel K, Renger M, Sauerbrey R, and Wessolek G. Soil Physical Characteristics of Peat Soils. Journal of Plant Nutrition and Soil Science. 2002; 165(4): 479-486. DOI: https://doi.org/10.1002/1522-2624(200208)165:4<479::AID-JPLN479>3.0.CO;2-8
Suprayoga GB. Identitas Kota Sawahlunto Paska Kejayaan Pertambangan Batu Bara. Jurnal Perencanaan Wilayah dan Kota. 2008; 19(2): 1-21. Available from: http://journals.itb.ac.id/index.php/jpwk/article/view/4198.
Santoso B and Daulay B. Vitrinite Reflectance Variation of Ombilin Coal According to Its Petrographic Analysis. Indonesian Mining Journal. 2005; 8(1): 9-20. Available from: https://jurnal.tekmira.esdm.go.id/index.php/imj/article/view/207
Pemerintah Daerah Sawahlunto. Sawahlunto. Sawahlunto: Pemerintah Daerah Sawahlunto; 2014.
Arif and Rahmat. 12 Perusahaan Tambang Batubara di Sawahlunto Dilaporkan ke KPK; 2016. Available from: https://hariansinggalang.co.id/12-perusahaan-tambang-di-sawahlunto-dilaporkan-ke-kpk/.
Badan Pusat Statistik. Sawahlunto. Sawahlunto: Badan Pusat Statistik Sawahlunto; 2015.
Nugroho AW, Widuri SA, and Sayektiningsih T. Earthworm Population at The Post Coal Mining Field in East Kalimantan, Indonesia. Indonesian Journal of Forestry Research 2018; 5(2): 81-93. DOI: http://dx.doi.org/10.20886/ijfr.2018.5.2.81-93.
Rawat JS and Kumar M. Monitoring Land Use/Cover Change Using Remote Sensing and GIS Techniques: a Case Study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science. 2015; 18(1): 77-84. DOI: https://doi.org/10.1016/j.ejrs.2015.02.002.
Ghamisi P, Benediktsson JA, and Phinn S. Land-Cover Classification Using Both Hyperspectral and Lidar Data. International Journal of Image and Data Fusion. 2015; 6(3): 189-215. DOI: https://doi.org/10.1080/19479832.2015.1055833.
Xiao J, Shen Y, Ge J, Tateish R, Tang C, Liang Y, and Huang Z. Evaluating Urban Expansion and Land Use Change in Shijiazhuang, China, by Using GIS and Remote Sensing. Landscape and Urban Planning. 2006; 75(1-2): 69-80. DOI: http://dx.doi.org/10.1016/j.landurbplan.2004.12.005.
Sabins FF. Remote Sensing: Principles and Interpretation. 2nd Edition. New York: W.H. Freeman and Company; 1987.
Lillesand TM and Keifer RW. Remote Sensing and Image Interpretation. 4th Edition. New York: John Wiley & Sons, Inc; 2004.
Jensen JR. Remote Sensing of the Environment: An Earth Resource Perspective. 2nd Edition. Upper Saddle River: Pearson Prentice Hall; 2007.
Thenkabail PS, Lyon JG, and Huete A. Hyperspectral Remote Sensing of Vegetation. Boca Raton: CRC Press; 2012.
Sudiana D and Diasmara E. Analisis Indeks Vegetasi Menggunakan Data Satelit NOAA/AVHRR dan TERRA/AQUA-MODIS. Proceedings of Seminar on Intelligent Technology and Its Applications (SITIA). 2008; 423-428. Available from: http://staff.ui.ac.id/system/files/users/dodi.sudiana/publication/dodi2.pdf
Chuvieco E, Cocero D, Riaño D, Martin P, MartÃnez-Vega J, de la Riva J, and Pérez F. Combining NDVI and Surface Temperature for the Estimation of Live Fuel Moisture Content in Forest Fire Danger Rating. Remote Sensing of Environment. 2004; 92(3): 322-331. DOI: https://doi.org/10.1016/j.rse.2004.01.019.
Panuju DR, Trisasongko BH, Susetyo B, Raimadoya MA, and Lees BG. Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia. ITB Journal of Science. 2010; 42A(1): 49-66. DOI: http://dx.doi.org/10.5614%2Fitbj.sci.2010.42.1.5.
Al-Ahmadi FS and Hames AS. Comparison of Four Classification Methods to Extract Land Use and Land Cover from Raw Satellite Images for Some Remote Arid Areas, Kingdom of Saudi Arabia. Journal of King Abdulaziz University; Earth Science. 2009; 20(1): 167-191. Available from: https://prod.kau.edu.sa/centers/spc/jkau/Doc/ear/20_1/Comparison%20of%20Four%20Classification%20Methods%20to%20Extract.pdf
Irawan JF and Indarto. Application of a Multispectral SPOT Image for Land Use Classification in Sampean Watershed. Journal Tropical Soils. 2011; 16(2): 175-181. Available from https://journal.unila.ac.id/index.php/tropicalsoil/article/view/137\.
Suwarsono and Khomarudin MR. Detecting The Spatial Distribution of Settlements on Volcanic Region Using Image Landsat-8 OLI Imagery. International Journal of Remote Sensing and Earth Sciences. 2014; 11(1): 63-72. DOI: http://dx.doi.org/10.30536/j.ijreses.2014.v11.a2602.
Catur U, Susanto, Yudhatama D, and Mukhoriyah. Identifikasi Lahan Tambang Timah Menggunakan Metode Klasifikasi Terbimbing Maximum Likelihood pada Citra LANDSAT-8. Majalah Ilmiah Globë. 2015; 17(1): 9-15. Available from: http://jurnal.big.go.id/index.php/GL/article/view/213.
Muchlisin A, Orbita R, Julzarika A, Siti H, and Teguh P. Inventarisasi Tutupan Lahan Menggunakan Satelit Penginderaan Jauh ALOS dengan Metode Klasifikasi Tetangga Terdekat Study Kasus: Jawa Barat. Majalah Sains dan Teknologi Dirgantara. 2010; 5(4): 174-182. Available from: http://jurnal.lapan.go.id/index.php/majalah_sains_tekgan/article/view/1389.
Curran PJ. Principles of Remote Sensing. London: Longman Scientific & Technical; 1985.
Liew SC, Shen C, Low J, Lim A, and Kwoh LK. Validation of MODIS fire product over Sumatra and Borneo using High Resolution SPOT Imagery. Proceedings of 24th Asian Conference on Remote Sensing & 2003 International Symposium on Remote Sensing. 2003; 1: 671-673. Available from: http://www.koreascience.or.kr/article/CFKO200322941410653.page
Syahrir I. Kebijakan Hilirisasi Mineral: Reformasi Kebijakan untuk Meningkatkan Penerimaan Negara. Kajian Ekonomi Keuangan. 2017; 1(1): 42-67. DOI: http://doi.org/10.31685/kek.v1i1.259.
Martokusumo W. The Ex-Coal Mining City of Sawahlunto Revisited. Nakhara: Journal of Environmental Design and Planning 2010; 6: 107-118. Available from: https://www.tci-thaijo.org/index.php/nakhara/article/view/104992.
Fishback PV. The Economics of Company Housing: Historical Perspectives from the Coal Fields. The Journal of Law, Economics, and Organization. 1992; 8(2): 346-365. Available from: https://www.jstor.org/stable/765084.
Mishra UC. Environmental Impact of Coal Industry and Thermal Power Plants in India. Journal of Environmental Radioactivity. 2004; 72(1-2): 35-40. DOI: https://doi.org/10.1016/s0265-931x(03)00183-8.
Kementrian Perindustrian Republik Indonesia. Pemerintah Dorong Industri Gunakan Batubara Sebagai Energi Alternatif. Jakarta: Kementrian Perindustrian Republik Indonesia; 2005.
Prakash A and Gupta RP. Land-Use Mapping and Change Detection in a Coal Mining Area - a Case Study in the Jharia Coalfield, India. International Journal of Remote Sensing. 1998; 19(3): 391-410. DOI: https://doi.org/10.1080/014311698216053.
Schwärzel K, Renger M, Sauerbrey R, and Wessolek G. Soil Physical Characteristics of Peat Soils. Journal of Plant Nutrition and Soil Science. 2002; 165(4): 479-486. DOI: https://doi.org/10.1002/1522-2624(200208)165:4<479::AID-JPLN479>3.0.CO;2-8
Suprayoga GB. Identitas Kota Sawahlunto Paska Kejayaan Pertambangan Batu Bara. Jurnal Perencanaan Wilayah dan Kota. 2008; 19(2): 1-21. Available from: http://journals.itb.ac.id/index.php/jpwk/article/view/4198.
Santoso B and Daulay B. Vitrinite Reflectance Variation of Ombilin Coal According to Its Petrographic Analysis. Indonesian Mining Journal. 2005; 8(1): 9-20. Available from: https://jurnal.tekmira.esdm.go.id/index.php/imj/article/view/207
Pemerintah Daerah Sawahlunto. Sawahlunto. Sawahlunto: Pemerintah Daerah Sawahlunto; 2014.
Arif and Rahmat. 12 Perusahaan Tambang Batubara di Sawahlunto Dilaporkan ke KPK; 2016. Available from: https://hariansinggalang.co.id/12-perusahaan-tambang-di-sawahlunto-dilaporkan-ke-kpk/.
Badan Pusat Statistik. Sawahlunto. Sawahlunto: Badan Pusat Statistik Sawahlunto; 2015.
Nugroho AW, Widuri SA, and Sayektiningsih T. Earthworm Population at The Post Coal Mining Field in East Kalimantan, Indonesia. Indonesian Journal of Forestry Research 2018; 5(2): 81-93. DOI: http://dx.doi.org/10.20886/ijfr.2018.5.2.81-93.
Rawat JS and Kumar M. Monitoring Land Use/Cover Change Using Remote Sensing and GIS Techniques: a Case Study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science. 2015; 18(1): 77-84. DOI: https://doi.org/10.1016/j.ejrs.2015.02.002.
Ghamisi P, Benediktsson JA, and Phinn S. Land-Cover Classification Using Both Hyperspectral and Lidar Data. International Journal of Image and Data Fusion. 2015; 6(3): 189-215. DOI: https://doi.org/10.1080/19479832.2015.1055833.
Xiao J, Shen Y, Ge J, Tateish R, Tang C, Liang Y, and Huang Z. Evaluating Urban Expansion and Land Use Change in Shijiazhuang, China, by Using GIS and Remote Sensing. Landscape and Urban Planning. 2006; 75(1-2): 69-80. DOI: http://dx.doi.org/10.1016/j.landurbplan.2004.12.005.
Sabins FF. Remote Sensing: Principles and Interpretation. 2nd Edition. New York: W.H. Freeman and Company; 1987.
Lillesand TM and Keifer RW. Remote Sensing and Image Interpretation. 4th Edition. New York: John Wiley & Sons, Inc; 2004.
Jensen JR. Remote Sensing of the Environment: An Earth Resource Perspective. 2nd Edition. Upper Saddle River: Pearson Prentice Hall; 2007.
Thenkabail PS, Lyon JG, and Huete A. Hyperspectral Remote Sensing of Vegetation. Boca Raton: CRC Press; 2012.
Sudiana D and Diasmara E. Analisis Indeks Vegetasi Menggunakan Data Satelit NOAA/AVHRR dan TERRA/AQUA-MODIS. Proceedings of Seminar on Intelligent Technology and Its Applications (SITIA). 2008; 423-428. Available from: http://staff.ui.ac.id/system/files/users/dodi.sudiana/publication/dodi2.pdf
Chuvieco E, Cocero D, Riaño D, Martin P, MartÃnez-Vega J, de la Riva J, and Pérez F. Combining NDVI and Surface Temperature for the Estimation of Live Fuel Moisture Content in Forest Fire Danger Rating. Remote Sensing of Environment. 2004; 92(3): 322-331. DOI: https://doi.org/10.1016/j.rse.2004.01.019.
Panuju DR, Trisasongko BH, Susetyo B, Raimadoya MA, and Lees BG. Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia. ITB Journal of Science. 2010; 42A(1): 49-66. DOI: http://dx.doi.org/10.5614%2Fitbj.sci.2010.42.1.5.
Al-Ahmadi FS and Hames AS. Comparison of Four Classification Methods to Extract Land Use and Land Cover from Raw Satellite Images for Some Remote Arid Areas, Kingdom of Saudi Arabia. Journal of King Abdulaziz University; Earth Science. 2009; 20(1): 167-191. Available from: https://prod.kau.edu.sa/centers/spc/jkau/Doc/ear/20_1/Comparison%20of%20Four%20Classification%20Methods%20to%20Extract.pdf
Irawan JF and Indarto. Application of a Multispectral SPOT Image for Land Use Classification in Sampean Watershed. Journal Tropical Soils. 2011; 16(2): 175-181. Available from https://journal.unila.ac.id/index.php/tropicalsoil/article/view/137\.
Suwarsono and Khomarudin MR. Detecting The Spatial Distribution of Settlements on Volcanic Region Using Image Landsat-8 OLI Imagery. International Journal of Remote Sensing and Earth Sciences. 2014; 11(1): 63-72. DOI: http://dx.doi.org/10.30536/j.ijreses.2014.v11.a2602.
Catur U, Susanto, Yudhatama D, and Mukhoriyah. Identifikasi Lahan Tambang Timah Menggunakan Metode Klasifikasi Terbimbing Maximum Likelihood pada Citra LANDSAT-8. Majalah Ilmiah Globë. 2015; 17(1): 9-15. Available from: http://jurnal.big.go.id/index.php/GL/article/view/213.
Muchlisin A, Orbita R, Julzarika A, Siti H, and Teguh P. Inventarisasi Tutupan Lahan Menggunakan Satelit Penginderaan Jauh ALOS dengan Metode Klasifikasi Tetangga Terdekat Study Kasus: Jawa Barat. Majalah Sains dan Teknologi Dirgantara. 2010; 5(4): 174-182. Available from: http://jurnal.lapan.go.id/index.php/majalah_sains_tekgan/article/view/1389.
Curran PJ. Principles of Remote Sensing. London: Longman Scientific & Technical; 1985.
Liew SC, Shen C, Low J, Lim A, and Kwoh LK. Validation of MODIS fire product over Sumatra and Borneo using High Resolution SPOT Imagery. Proceedings of 24th Asian Conference on Remote Sensing & 2003 International Symposium on Remote Sensing. 2003; 1: 671-673. Available from: http://www.koreascience.or.kr/article/CFKO200322941410653.page
Downloads
Published
2019-12-31
How to Cite
Cahyono, B. E., Frahma, Y. F. and Nugroho, A. T. (2019) “The Rate of Land Cover Change using Landsat Data in Coal Mining Area of Sawah Lunto City, Indonesia”, Jurnal Penelitian Fisika dan Aplikasinya (JPFA), 9(2), pp. 189–203. doi: 10.26740/jpfa.v9n2.p189-203.
Issue
Section
Articles
License
Author(s) who wish to publish with this journal should agree to the following terms:
- Author(s) retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-Non Commercial 4.0 License (CC BY-NC) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal for noncommercial purposes.
- Author(s) are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
The publisher publish and distribute the Article with the copyright notice to the JPFA with the article license CC-BY-NC 4.0.
Abstract views: 564
,
PDF Downloads: 348
