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Insanul Putri
Student of the D3 Remote Sensing Technology Study Program
Astronomy Computer Science & IT Earth & Planetary Sciences Education

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ESTIMATION OF MANGROVE FOREST CARBON STOCK USING THE VEGETATION INDEX METHOD IN PADANG PARIAMAN DISTRICT Insanul Putri; Yudi Antomi; Febriandi Febriandi; Azhari Syarief
International Remote Sensing Applied Journal Vol 4 No 1 (2023): International Remote Sensing Application Journal (June Edition 2023)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v4i1.43

Abstract

Padang Pariaman Regency is categorized as a coastal district because it has a coastline of 42.11 km. Padang Pariaman Regency has resources, one of which is mangrove forests. Mangrove forests are scattered in several sub-districts in Padang Pariaman Regency. This study aims to determine the estimated carbon stock value of mangrove forests in Padang Pariaman District using the Geographic Information System and Landsat 8 imagery, and to determine the accuracy of the carbon stock estimation results from the Landsat 8 imagery vegetation index. The method used in this study isNormalized Difference Vegetation Index (NDVI). Based on the estimation results of the above surface biomass values ​​obtained from the calculation of the correlation and regression equations in band 6 Landsat 8 imagery shows that the estimation results of the above surface biomass of mangrove forests in Padang Pariaman District obtain a maximum value of 644.85 tons/ha and a minimum value of 487, 92 tons/ha to obtain an estimated carbon stock value of 46% of the biomass value and an estimated maximum carbon stock value of 296.63 tons/ha and a minimum of 224.44 tons/ha.
Co-Authors Azhari Syarief Febriandi Febriandi Yudi Antomi