Application of landsat 8 sattelite imagery for estimated distribution of above ground carbon in Percut Sei Tuan forest landscape

The use of remote sensing technology has been widely used to estimate carbon stocks above ground level, including in mangrove forest landscapes. This study aims to obtain information on the spatial distribution of above-ground carbon using Landsat 8 satellite imagery in the Percut Sei Tuan mangrove forest landscape. Ordinary least square (OLS) regression method is used to build a model of estimating the spatial distribution of above-ground carbon based on vegetation index values of normalize different vegetation index (NDVI) and green normalize different vegetation index (GNDVI). The results showed the average carbon content above ground level in the Percut Sei Tuan forest landscape was 23.55 tons ha−1. The power regression model is the best estimator model for the distribution of carbon content above ground level with the equation y = 205.9 x4.2713 and R2 of 72.4%.

• Publication year

  2020

• Venue

  IOP Conference Series: Earth and Environment

• Publication date

  2020-04-15

• Fields of study

  Physics, Environmental Science

• Identifiers
  DOI 10.1088/1755-1315/454/1/012080
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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