Pemodelan Citra Penginderaan Jauh Multi Waktu untuk Pemantauan Deforestasi

Jurnal Alami

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Field Value
 
Title Pemodelan Citra Penginderaan Jauh Multi Waktu untuk Pemantauan Deforestasi
 
Creator Melati, Dian Nuraini
 
Description 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.
 
Publisher Agency for the Assessment and Application of Technology / Badan Pengkajian dan Penerapan Teknologi (BPPT)
 
Date 2019-05-31
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://ejurnal.bppt.go.id/index.php/Alami/article/view/3368
10.29122/alami.v3i1.3368
 
Source Jurnal ALAMI : Jurnal Teknologi Reduksi Risiko Bencana; Vol. 3 No. 1 (2019): Jurnal Alami; 43-51
2548-8635
10.29122/alami.v3i1
 
Language eng
 
Relation http://ejurnal.bppt.go.id/index.php/Alami/article/view/3368/pdf
10.29122/alami.v3i1.3368.g2967
 
Rights Copyright (c) 2019 Jurnal Alami : Jurnal Teknologi Reduksi Risiko Bencana
 

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