Above Ground Biomass Estimation Methods and Challenges: A Review

Abstract

Forest ecosystems play an important role in global change on the earth. However, continued forest degradation and deforestation will results in the loss of forest biomass or carbon stock. Hence, current concerns for global change and ecosystem functioning require accurate biomass estimation and examination of its dynamics. In this end we reviewed the present scenarios of above ground biomass estimation, focusing predominantly on field measurement (destructive and non-destructive) and remote sensing (optical remote sensing, radar and light detection and ranging (LiDAR)) biomass estimation methods and identifying some important point or research findings  in detail. In addition, we discuss the critical uncertainties or the source of errors in all methods.  In the field methods the source of error encountered  mainly  from sampling error, measurement error and statistical or model error. In the remote sensing methods; optical sensor data is not suitable for estimation of vertical vegetation structures such as canopy height, Radar have the following uncertainty: costly data, no time-composite data as the case for optical data, limited area coverage and LiDAR also faces the following challenges spatially limited, data intensive, and expensive, can't applied extensively to larger areas, limited usage in harsh weather. Finally, we suggest that using both field measurement and remote sensing methods will increase the accuracy of biomass estimation.

Keywords: biomass, estimation,  remote sensing, uncertainty,  LiDAR, Radar and optical

DOI: 10.7176/JETP/9-8-02

Publication date: November 30^th 2019