مرکز منطقه ای اطلاع رساني علوم و فناوري - MODELING ABOVE GROUND BIOMASS IN CALABRIAN PINE FORESTS OF DÜZLERÇAMI (ANTALYA)

Abstract :

Estimation of forest biomass is needed for monitoring the changes in carbon stocks as well as other purposes. This study reports on a test of the ability to estimate above ground biomass of Calabrian pine forests of Düzlerçamı, Antalya, Turkey using Landsat and ICESat/GLAS data. The field data has been collected in 2017 and plot-level estimates were calculated using the allometric equations. GLAS parameters and various Landsat vegetation indices were modeled using multiple regression analysis to estimate above ground biomass. In the first model (ModelA) height of median energy (HOME) and the ratio of HOME to maximum vegetation height (%HOME) parameter of GLAS showed relation with field based estimates of above ground biomass with a coefficient of determination (R^2) of 0.87. Above ground biomass derived from ModelA and the variables obtained from Landsat indices has been used at the second model (ModelB) had a R^2 of 0.52 meaning the GLAS data is poorly correlated with Landsat at the study area. A better statistical relationship has been found with Landsat data and AGB with a R^2 of 0.91 in ModelC that uses Landsat pixel values of each bands and pixel values of the indices are used as independent variable to explain above ground biomass. The results demonstrate a current potential for above ground biomass estimation of forests using optical sensor data and satellite lidar where airborne lidar data is not widely available.