ESTIMASI DEGRADASI DAN DEFORESTASI HUTAN RAWA GAMBUT DENGAN CITRA PENGINDERAAN JAUH DI PROVINSI KALIMANTAN TENGAH Estimation of Degradation and Deforestation of Peat Swamp Forests with Remote Sensing Imagery in Central Kalimantan Province

Authors

  • Raden Mas Sukarna Jurusan Kehutanan Fakultas Pertanian Universitas Palangka Raya
  • Cakra Birawa Prodi Kehutanan, Fakultas Pertanian UPR

DOI:

https://doi.org/10.36873/aev.v12i02.124

Keywords:

Peat swamp forest, remote sensing, ecology, degradation and deforestation

Abstract

The changed in 1995 – 1998 when a programme of massive Peat Swamp Forest (PSF) conversion, the so-called Mega Rice Project (MRP) in Central Kalimantan was initiated to develop rice field has been impact both deforestation and forest degradation. The aim of this research is to classify forest degradation rates of PSF accurately using multi-stage remote sensing methods through (1) Forest Canopy Density model (FCD) LANDSAT 5 TM image acquired 2010 and supported by aerial photos interpretation, (2) inventoryineach forest cluster were determined by purposive sampling using 5 plotswith size of 20m x 20m.The results showed that there was asignificant correlation(r)=0.82 between FCD and Canopy Area Index (CAI). Significant correlation was also shown between CAI and stand density, dominance andfrequency respectively with the value of r = 0.974; r = 0.937 and r = 0.871. Based on these correlation, predicted that PSF on the researcharea has been changed become deforestation 53.68%, very high degradation 3.37%, moderate high degradation 11.21%, middle degradation 15.30%, moderate low degradation 15,45% and low degradation 0.99%.The conclusion thatthe PSF ecosystem of MRP largely has been transformed intodegradation and deforetation areas.

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Published

2018-12-23

How to Cite

Sukarna, R. M. . ., & Birawa, C. (2018). ESTIMASI DEGRADASI DAN DEFORESTASI HUTAN RAWA GAMBUT DENGAN CITRA PENGINDERAAN JAUH DI PROVINSI KALIMANTAN TENGAH Estimation of Degradation and Deforestation of Peat Swamp Forests with Remote Sensing Imagery in Central Kalimantan Province. Agrienvi: Jurnal Ilmu Pertanian, 12(02), 1–7. https://doi.org/10.36873/aev.v12i02.124