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Abstract
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%.
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Details
1 Department of Forest Conservation, Faculty of Forestry, Universitas Sumatera Utara, Medan, Sumatera Utara, Indonesia.; Center of Excellence for Mangrove, Universitas Sumatera Utara, Medan, Sumatera Utara, Indonesia.
2 Department of Forest Conservation, Faculty of Forestry, Universitas Sumatera Utara, Medan, Sumatera Utara, Indonesia.