Spatial Interpolation to Predict Mangrove above-Ground Carbon in Loh Buaya, Komodo National Park, Indonesia

Mangrove is an essential coastal vegetation with multiple abilities to protect the land from any hazards that come from the sea, also provides a contribution to combat global climate change by sequestering the carbon in the atmosphere on its stem and root system. Measuring the amount of carbon that can be stored by mangroves using terrestrial surveys is relatively challenging due to the harsh environment. Therefore, an optional method using satellite remote sensing and spatial modeling using Geographic Information Systems (GIS) is needed. This research will combine field sampling and a GIS approach to estimate how much mangroves can store in the research area with spatial interpolation techniques i.e., kriging, spline, topo to raster, and nearest neighbor. To check the accuracy, Root Mean Square Error (RMSE) was used. The most accurate model among others is Spline With Barrier with an RMSE of about 1.82 Mg C Ha-1 with a range of Above-Ground Carbon (AGC) values from 13.94 Mg C Ha-1 to 142.43 Mg C Ha-1. In conclusion, spatial interpolation may assist the mangrove’s carbon spatial modelling with promising accuracy.