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https://repository.unej.ac.id/xmlui/handle/123456789/97081
Title: | The Rate of Land Cover Change using Landsat Data in Coal Mining Area of Sawah Lunto City, Indonesia |
Authors: | Cahyono, Bowo Eko Frahma, Yazella Feni Nugroho, Agung Tjahjo |
Keywords: | Sawahlunto coal mining Landsat land cover degradation supervised classification |
Issue Date: | 1-Dec-2019 |
Citation: | JurnalPenelitianFisika dan Aplikasinya (JPFA), Volume 09, Issue 02, December 2019 |
Abstract: | 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. |
URI: | http://repository.unej.ac.id/handle/123456789/97081 |
Appears in Collections: | LSP-Jurnal Ilmiah Dosen |
Files in This Item:
File | Description | Size | Format | |
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F. MIPA_Jurnal_Bowo Eko C_The Rate of Land Cover Change using Landsat Data.pdf | 1.97 MB | Adobe PDF | View/Open |
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