Estimation of above ground carbon stock using multiple vegetation index on Sentinel-2 imagery (case study: Samarinda, East Kalimantan)

Samarinda is one of the big cities on Kalimantan Island, which is also the capital of East Kalimantan, Indonesia. The proximity with the prospective new Indonesia State Capital, Penajam Paser Utara, and increasingly massive urban activities can potentially increase considerable changes in green open space in the future. The availability of trees in green open spaces has an important role in mitigating climate change because of its ability to store carbon stock. Therefore, it is necessary to carry out an inventory, monitoring, and evaluate the above ground carbon stock value in Samarinda. This study aims to find a suitable vegetation index for carbon stock estimation, as well as determine the total and spatial distribution of carbon stocks using the best vegetation index in green open space vegetation in Samarinda City using Sentinel-2 imagery. Sentinel-2 L2 MSI imagery was utilized to build a carbon stock model based on field sample calculation. Empirical modeling with the allometric equation was carried out, wherein carbon stocks at points of samples correlate with the index value of each transformation selected by the ability to assess vegetation (DVI, EVI2, GNDVI, NDVI, OSAVI, SARVI, and SARVI). Statistical analysis performed is normality test, correlation analysis with Pearson Product Moment method, and regression using simple linear analysis. The significance test was carried out using the ANOVA Test and Partial T-Test, while the accuracy-test used the Standard error of estimate (SEE) method on independent validation samples. The results showed that the best vegetation indices were GNDVI with the highest coefficient of determination of 0.552. Moreover, the significance test shows that all indices significantly affect the estimation of carbon stocks in Samarinda. The accuracy test shows that GNDVI has a maximum accuracy of 55.816 by an estimated error of 1.775 tons/pixel. © 2021 SPIE.