Density Based Clustering of Hotspots in Peatland with Road and River as Physical Obstacles

Prima Trie Wijaya, Imas Sukaesih Sitanggang, Lailan Syaufina

Abstract


Indonesia has the largest peatland area among tropical countries, covering about 21 milions ha, which spread mainly in Sumatera, Kalimantan, and Papua. Land and forest fires occur almost every year in peatland areas in Indonesia. One of indicators for forest and land fires is hotspot. The objective of this study is to group hotspots with road and river as obstacles using the CPO-WCC (Clustering in Presence of Obstacles with Computed number of Cells) algorithm. Clusters of hotspot data were analyzed based on peatland area distribution. This study also evaluates the results of clustering on peatlands in order to obtain the best clusters. Clustering using CPO-WCC algorithm produces three clusters of hotspot. The area of dense cluster is 10202.10 km2 with number of hotspots per km2 is 0.985. The higest number of hotspots occurrence is found in peatland with type of Hemists /Saprists (60/40) and depth greater than 400 cm.

Keywords


Data mining

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DOI: http://doi.org/10.11591/ijeecs.v3.i3.pp714-720

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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