ANALISIS TINGKAT KERAPATAN VEGETASI MENGGUNAKAN CITRA LANDSAT 8 DI KAWASAN HUTAN LINDUNG KECAMATAN DOLO SELATAN KABUPATEN SIGI SULAWESI TENGAH

Authors

  • Mutmainnah Mutmainnah Fakultas Kehutanan Universitas Tadulako
  • Hasriani Muis Fakultas Kehutanan Universitas Tadulako
  • Akhbar Akhbar Fakultas Kehutanan Universitas Tadulako
  • Ida Arianingsih Fakultas Kehutanan Universitas Tadulako
  • Misrah Misrah Fakultas Kehutanan Universitas Tadulako
  • Rahmat Kurniadi Akhbar Fakultas Kehutanan Universitas Tadulako

Keywords:

Vegetation, Landsat 8, NDVI

Abstract

Conditions that occur in the Protected Forest Area of South Dolo District, Sigi Regency, Central Sulawesi have experienced degradation of the function of forest areas in several areas and there are also areas that have experienced critical or damaged land. The impact that occurs will increasingly affect the level of vegetation density of the area if it occurs continuously. Therefore, it is important to conduct a vegetation density research with a vegetation index analysis (NDVI) to find out how large the vegetation density level is due to forest degradation. This research was carried out for 3 (three) months, from April to June 2020. By analyzing the level of vegetation density in the Protected Forest Area of South Dolo District and using the error matrix method (Confusion Matrix) to determine the level of accuracy in the identification image with data in the field. From the study, 3 classes of vegetation density were obtained, namely the vegetation class rarely obtained a range of NDVI values of 0.05-0.31 with an area of 1,096.4 Ha and the percentage was around 2.90%. Medium vegetationobtained a range of 0.33-0.41 with an area of 10,615.97 Ha and the percentage is 28.12%. Meanwhile, dense vegetation obtained the NDVI range of 0.42-0.62 with a dominating area of 26,040.26 Ha and obtained a larger percentage of 68.98%. With the accuracy test, Landsat 8 Imagery resulted in a satisfactory percentage of accuracy value of 82.5% which was in accordance with the ≥ 80% confidence standard.

Published

06-01-2025