Estimating Soil Carbon Stocks in a Dry Miombo Ecosystem Using Remote Sensing

The total carbon pool in dry Miombo ecosystems is often underestimated. This study sought to close this gap by modelling the relationship between the above ground fresh woody biomass carbon pool and the soil carbon pool using both ground based methods and remote sensing methods. A total of thirty (30 m × 30 m) plots were randomly selected within the study area. Tree height and diameter at breast height (dbh) are the vegetation characteristics, which were measured in the present study. These variables were later used to calculate the above ground fresh biomass carbon per hectare. Soil samples were randomly collected from five points within the plots. The soil samples were analyzed for soil organic carbon (SOC). Three remotely sensed vegetation indices are-Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), and the Soil Adjusted Vegetation Index (SAVI), which were calculated using geometrically and radiometrically corrected Landsat 8 Operational Land Imager (OLI) satellite images. Correlation and regression analysis were used to quantify the relationship between SOC, above ground fresh woody biomass carbon and remotely sensed vegetation indices. Results showed that, above ground fresh woody biomass carbon was significantly related to SOC in the top soil layer (0-15 cm) and not the deeper soil layer (15-30 cm). The significant positive relationship between above ground fresh woody biomass carbon and SOC suggests that, above ground fresh woody biomass carbon can be used as a proxy to estimate SOC in the top soil layer (0-15 cm) in dry Miombo ecosystems. Remotely sensed vegetation indices were not significantly (p>0.05) related to the SOC regardless of depth. This result implies that further work is needed before multi-spectral optical remote sensing can be used as a tool to estimate SOC in dry Miombo ecosystems.