Modelling the relationship between tree canopy projection area and above ground carbon stock using high resolution GeoEye satellite images

Carbon stock estimation of above ground tree biomass is important for 'reducing emission from deforestation and forest degradation' (REDD) credit to mitigate climate change due to anthropogenic causes. Automatic delineation of individual tree crown (ITC) techniques results in a substantial error due to presence of intermingled canopy trees in the estimation of above ground carbon stock. The aim of this study was to establish regression models for the relationship of canopy projection area (CPA) with forest tree parameters, i.e., diameter at breast height (DBH), basal area (BA), biomass and carbon stock of standalone and intermingled canopy trees of dominant species for the prediction of above ground carbon stock. This study was carried out in subtropical broadleaf forest in Chitwan, Nepal. High resolution GeoEye satellite image was used for manual delineation of CPA of standalone and intermingled canopy trees of the dominant species. Above ground tree dry biomass was calculated from the field measured DBH using allometric equation. Above ground tree carbon stock was obtained by multiplying their dry biomass with the factor 0.47. Individual basal area of intermingled canopy trees was calculated separately and was summed up (ΣBA) along with the summation of their carbon stock (Σcarbon). Correlation analysis was carried out to assess the linear relationship between CPA, DBH, BA, biomass, and carbon stock. Four types of functions, i.e., simple linear, quadratic, logarithmic and power, were used to fit the data using least square regression method. Shorea robusta, Schima wallichii and Terminalia alata were found dominant tree species in the study area forest. The relationship of CPA with DBH of standalone trees was found linear with coefficient of determination (R 2) ranging from 0.63 for Schima wallichii to 0.69 for Shorea robusta and 0.74 for Terminalia alata. The relationship of CPA with biomass or carbon stock of standalone trees was also revealed linear with R 2 ranging from 0.53 for Schima wallichii to 0.62 for Terminalia alata and 0.65 for Shorea robusta. The relationship of CPA with ΣBA and Σcarbon of intermingled canopy trees of Shorea robusta was also found linear with R 2 of 0.29 and 0.25 respectively. Simple linear regression model resulted in the least error for the prediction of carbon stock of standalone and intermingled canopy trees.