Optical and Radar Images in Modeling the forests Biomass in North of Iran

Careful assessment of biomass for forest management and understanding the role of forests as carbon sources is very important. Since 50% of forest biomass contains Carbon، estimating the forest biomass in terms of the amount of energy stored in the review of forests and climatic change is highly regarded. The best way for estimating biomass is the developed models which are (based upon) the local collected data. Recently the remote sensing techniques with minimum ground measurements have been played an important role in forest biomass estimation. Lack of the local equations for estimating biomass and ambiguity precision of the global equations، Leads the study toward the development of biomass equations for the forests of Guilan region، in northern Iran. To develop these equations، in a field work، 28 plots (each plot 30*30m) have been selected and the various parameters such as height and diameter of trees have been measured. Non-destructive method is used to estimate the biomass of plots. Then، by using the optical and radar ALOS satellite images، the relationship between remote sensing data and the estimated biomass of plots are determined. The multivariate regression analyses are used to establish the mentioned relationship. The best model based on the highest coefficient (R^2= 0. 731 and the lowest Root Mean Squared Error (RMSE= 13. 88(ton/he)) are determined.