Remote Sensing for Forest Biomass Estimation

Abstract

Accurate estimation of forest biomass is essential for the quantification of global carbon stocks and the assessment of climate change impacts. In the last 3 decades, remote sensing technologies, both airborne and spaceborne, have become the primary source for biomass estimation at large scales. Either optical, LiDAR or SAR sensors are commonly used to retrieve biomass estimation with each sensor type having its advantages and disadvantages. LiDAR delivers highly accurate results but cannot observe forest continuously over large areas, while optical sensors and SAR have a very good coverage but lack accuracy when the biomass exceeds the saturation level. To overcome these problems, in recent years great attention has been paid to the development of methods for fusing two or more sensors, and several global- to continental-scale forest biomass maps are developed. This paper also discusses several planned LiDAR and SAR satellite missions which are expected to greatly advance the global biomass research in the near future.