Estimating Above Ground Trees Biomass Of Forest Cover Using Field Measurement And QuickBird Image In Lore Lindu National Park-Central Sulawesi

Abstract

Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting (Muukkonen and Heiskanen, 2006). The biomass of forest provides estimates of the carbon pools in forest vegetation because about 50% of it is carbon. Direct measurement of biomass on the ground is time consuming (expensive), and repeated measurements, if they occur at all, are generally limited to 10 year interval. The possibility that above ground forest biomass can be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass is possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The method of this research use an approach of estimating the biomass that combines field studies (forest inventory data), analysis of multispectral satellite imagery, allometric equation and statistical analysis. Forest cover type classification was utilized for analyzing the biomass per pixel in each different cover type. The classifications for each cover type by using the region based different spectral value in each observation plot refer to QuickBird Image. The field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The correlation analysis resulted the main regression equation in estimating the tree biomass of tropical forest, biomass=6E-05DBH2.6705 and biomass= 0.0065e 13.615 NDVI. There are 4 forest cover types observed in this research. Forest cover type A is natural forest without timber extraction (closed canopy). Forest cover type B is natural forest with minor extraction. Forest cover type C is natural forest with major timber extraction. Forest cover type D is agroforestry system. Forest cover type A and B has the higher biomass than C and D, it is about 596.41-618.66 ton/ha and 583.94-622.19 ton/ha. Forest cover type C is 446.65-468.50 ton/ha. Forest cover type D has the lowest biomass is about 193.31-214.34 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees v heterogeneity with minimum disturbance. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass.