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All Journal Jurnal Alami : Jurnal Teknologi Reduksi Risiko Bencana
Melati, Dian Nuraini
Badan Pengkajian dan Penerapan Teknologi (BPPT)
Earth & Planetary Sciences

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Multi Temporal Remotely Sensed Image Modelling For Deforestation Monitoring Melati, Dian Nuraini
Jurnal Alami : Jurnal Teknologi Reduksi Risiko Bencana Vol 3, No 1 (2019)
Publisher : Badan Pengkajian dan Penerapan Teknologi (BPPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1383.249 KB) | DOI: 10.29122/alami.v3i1.3368

Abstract

Tropical rainforest in Indonesia faces critical issue related to deforestation. Human activities which convert forest cover into non-forest cover has been a major issue. In order to sustain the forest resources, monitoring on deforestation and forest cover prediction is necessary to be done. Remotely sensed data, Landsat images, with acquisition in 1996, 2000, and 2005 are used in this study. In this study area, forest cover decreased around 6 % in the period of 1996 - 2005. For the purpose of forest cover modelling, three model (i.e. Stochastic Markov Model, Cellullar Automata Markov (CA_Markov) Model, dan GEOMOD) were tested. Based upon the Kappa index, GEOMOD performed better with the highest Kappa index. Therefore, GEOMOD is recommended to forecast forest cover.
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