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Fathirizki Agsa Kamarati, Kiamah
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Pemetaan Sebaran Spasial Pohon di Areal Blok Miniatur PT.Timberdana Kecamatan Damai Kabupaten Kutai Barat: Mapping of the Spatial Distribution of Trees in the Miniature Blok Area of PT.Timberdana Damai District, West Kutai District Kardika, Adelia Juli; Aldi, Muhammad; Malaysia, Emi; Fathirizki Agsa Kamarati, Kiamah
HUTAN TROPIKA Vol 19 No 2 (2024): Volume 19 Nomor 2 Tahun 2024
Publisher : Jurusan Kehutanan, Fakultas Pertanian Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36873/jht.v19i2.15109

Abstract

This research is motivated by the fact that the natural forest in the miniature block area of PT. Timberdana is covered with various types of vegetation which is used as an educational forest area, research and a place for sustainable development. This area does not yet have a tree distribution map which can later be used as information for sustainable management. So the aim of this research is to identify the type, number of trees, coordinate the trees, and create a map of the distribution of trees in the PT miniature block area. Timberdana and identify its spatial distribution patterns. The research method involves field surveys to identify tree types, coordinate trees, and collect data on trees in the miniature block area. Measurement and identification of tree species is done with the help of botanists and appropriate reference guides. The collected data was analyzed using spatial analysis and mapping techniques using GIS (Geographic information system) software for data processing to visualize the distribution of tree species and identify their spatial distribution patterns. The results of the research show that there are many species of natural forest trees that are quite tall in the PT miniature block. Timberdana. The trees in the block area consist of 17 types with a total of 401 trees from 7 families. Based on the results of mapping the distribution of trees in the miniature block area of PT. Timberdana's spatial distribution pattern is random. This shows that random distribution patterns tend to be safer for plant management efforts