Assessing the impact of ecological security and forest fire susceptibility on carbon stocks in Bo Trach district, Quang Binh province, Vietnam

Abstract

An assessment index of landscape ecological security (LES), different from other ecological models namely Pressure-State-Response (PSR), will be more accurate to capture temporal and geographic changes in landscape as well as ecosystem resilience and resistance to interference. In the present study, the impact of ecological security and forest fires on the carbon stock of forests in Bo Trach district, Quang Binh province, central Vietnam was evaluated and analyzed based on remote sensing data and a hybrid model of ant colony optimization (ACO) and neuro-fuzzy system (NFS). The present study indicated that forest fires are generally high throughout the study area, concentrating on areas exposed to and affected by human reclamation and production activities. The artificial neural network (ANN) model based on principal component analysis (PCA) combined Sentinel-1A data performed a higher prediction accuracy (R2 = 0.74), being much greater than biomass estimation using optical data. It reveals that there is a reliability in estimating the aboveground carbon stocks (AGCs) from the aboveground biomass (AGB). The calculated data suggest the AGCs in the study area is high, but these parameters will loss severely in the coming years due to the nature and humans impacts. These results show that utilizing remote sensing combined with PCA-ANN model would have increased the accuracy of forest fire susceptibility, and detected assessment of the LES and forest fires on the AGCs. The above obtainings supply helpful information for managers and forest rangers to guard the forests in the study area better, and to limit human encroachment, thereby offering actions that contribute to sustainable development.