Estimation Model of Mangrove Carbon Stock Using LDCM Imagery

Abstract

Mangroves are one of the forest ecosystems with the capacity to reduce greenhouse effect. However, there is limited data on thecarbon absorbent properties, and, a fast as well as accurate method of estimating the stock in mangrove is needed. The objective of this research, therefore, was to obtain an estimation model of mangrove carbon stocks, using LDCM satellite imagery. Thisdevelopment involved a hybrid method,where information obtainedfrom LDCM satellite imagery were combined with the field data. The result of this studyidentified the best model to estimate carbon stock. This involvedthe combination of total vegetation stock, using the VARI vegetation index (power regression/ geometry) and soil composition, basedon six variables multiple regression.The%RMSE test result was determined to be 9.58%. In addition, field data was not required in modelsinvolving two variables (MSAVI vegetation index and average sediment depth 100.6 cm), and the % RMSE determined was 34.18%.