A brief overview and perspective of using airborne Lidar data for forest biomass estimation

ABSTRACT

Lidar data have been regarded as the most important data source for accurate forest biomass estimation. Different platforms such as terrestrial Laser scanning, unmanned aerial vehicle Laser scanning, airborne Laser scanning, and spaceborne Lidar (e.g. ICESat-1/2, GEDI, GF-7 Lidar) provide new opportunities to map forest biomass distribution at different scales. The ground-based Lidar data are mainly used for extracting individual tree parameters such as diameter at breast height (DBH) and tree height, attempting to replace or reduce field work, while spaceborne Lidar data are often used to extract canopy height data at national and global scales, but cannot provide wall-to-wall mapping. The airborne Lidar may be the most frequently used data for forest biomass estimation at local scale. Many studies have been conducted for mapping forest biomass distributions in different climate zones, but current research situations and challenges of using airborne Lidar data have not been fully overviewed. This paper attempts to provide an overview of using airborne Lidar data for forest biomass estimation and discuss current research problems and future directions, which will be valuable for professionals and practitioners to better understand the important role of using airborne Lidar data for forest biomass estimation at the local scale.

KEYWORDS:

• Airborne Lidar
• forest biomass
• modelling
• regression
• machine learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the National Natural Science Foundation of China [32271870], Fujian Provincial Science and Technology Department [2021R1002008] and China Scholarship Council [202108350072].