International remote sensing application journal
Vol 4 No 1 (2023): International Remote Sensing Application Journal (June Edition 2023)

ESTIMATION OF MANGROVE FOREST CARBON STOCK USING THE VEGETATION INDEX METHOD IN PADANG PARIAMAN DISTRICT

Insanul Putri (Student of the D3 Remote Sensing Technology Study Program)
Yudi Antomi (Lecturer Study Program D3 Remote Sensing Technology)
Febriandi Febriandi (Lecturer Study Program D3 Remote Sensing Technology)
Azhari Syarief (Lecturer Study Program D3 Remote Sensing Technology)



Article Info

Publish Date
28 Jun 2023

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.

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Journal Info

Abbrev

IRSAJ

Publisher

Subject

Astronomy Computer Science & IT Earth & Planetary Sciences Education

Description

This journal covers the scope of remote sensing which includes: (1) data acquisition; (2) processing data; (3) data storage and distribution; (4) application and utilization of information from remote sensing data. The focus of this journal includes: 1. Remote sensing applications 2. Multi-spectral ...