Abstract Reliable forest biomass assessments are becoming increasingly important, as Parties to the Climate Convention are required to report changes in multiple carbon pools, including both above- and belowground biomass. In some regions, use of remote sensing is the only viable option for obtaining such estimates, whereas in other regions it bears potential to improve the accuracy of ground inventory-based biomass estimates. However, statistically rigorous estimation through remote sensing poses several challenges. This study systematically and comprehensively reviews the methodological quality of large-area biomass assessment studies from 1992 to 2022, based on core survey elements for successful biomass surveying assisted by remote sensing. For each element, we reviewed the studies in relation to “ideal standards” derived from the literature, which served as evaluation criteria. Our review revealed an increasing trend in use of remote sensing for biomass surveys, coupled with gradual improvements in methodological quality for all survey elements evaluated. For example, advances in remote sensing techniques, particularly the increased use of Light Detection and Ranging, Radio Detection and Ranging, and digital aerial photogrammetry, all technologies able to capture information on forest structure, have enhanced the reliability of biomass estimates. However, several problems remain, such as field data scarcity for model calibration, signal saturation in high-biomass regions, and misconceptions about the use of statistical methods. We identified five remaining key challenges for improving remote sensing assisted large-area biomass assessments. These include (i) obtaining sensor data that correlate stronger with biomass, (ii) acquiring larger sets of harmonized field data at the level of trees and plots for calibrating models, (iii) adequate use of statistical principles, (iv) developing methods for domain estimation, and (v) improved quality assurance and quality control. While upcoming new airborne technologies and satellite missions may mitigate some challenges, continued methodological innovation and further enhancement of the rigor of statistical and other procedures will remain essential for advancing remote sensing-based biomass assessments.
Papucci et al. (Tue,) studied this question.