Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/75955
Title: Fuzzy C-means for Deforestation Identification Based on Remote Sensing Image
Authors: Afandi, Setia Darmawan
Herdiyeni, Yeni
Prasetyo, Lilik B
Issue Date: 2013
Publisher: IEEE Indonesia Section
Abstract: This research report about Fuzzy CMeans for Deforestation Identification Based On Remote Sensing Image. Deforestation means that changes forest area into another functions. Clustering is a method of classify objects into related groups (clusters). While, Fuzzy C-Means clustering is a technique that each data is determined by the degree of membership. In this research, the data used are MODIS EVI 250 m in 2000 and 2012 to identify deforestation rate in Java island. MODIS EVI is one of kind MODIS image which is able to detect vegetation based on photosynthesis rate and vegetation density. The number of clusters used were 13 clusters. This research had succeeded to classify areas based on the value of EVI like areas who had a high EVI values (forests, plantations, grass land), moderate values (agricultural area), and low values (build up area, mining area, pond, and other land cover). But, EVI value is only influenced by photosynthesis rate and vegetation density. Thus, EVI value is not well to identify forest areas. this is because the value of EVI in forest areas are almost same with plantations, savanna, etc.
URI: http://repository.ipb.ac.id/handle/123456789/75955
ISBN: 978-979-1421-22-5
Appears in Collections:Proceedings

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