Abstract
Accurate forest biomass estimation at the individual tree scale is the foundation of timber industry and forest management. It plays an important role in explaining ecological issues and small-scale processes. Remotely sensed images, across a range of spatial and temporal resolutions, with their advantages of non-destructive monitoring, are widely applied in forest biomass monitoring at global, ecoregion or community scales. However, the development of remote sensing applications for forest biomass at the individual tree scale has been relatively slow due to the constraints of spatial resolution and evaluation accuracy of remotely sensed data. With the improvements in platforms and spatial resolutions, as well as the development of remote sensing techniques, the potential for forest biomass estimation at the single tree level has been demonstrated. However, a comprehensive review of remote sensing of forest biomass scaled at individual trees has not been done. This review highlights the theoretical bases, challenges and future perspectives for Light Detection and Ranging (LiDAR) applications of individual trees scaled to whole forests. We summarize research on estimating individual tree volume and aboveground biomass (AGB) using Terrestrial Laser Scanning (TLS), Airborne Laser Scanning (ALS), Unmanned Aerial Vehicle Laser Scanning (UAV-LS) and Mobile Laser Scanning (MLS, including Vehicle-borne Laser Scanning (VLS) and Backpack Laser Scanning (BLS)) data.
Highlights
Accurate forest biomass estimation is the foundation of timber industry and forest management.It is the key to ecological research and the basis for a range of fields including forest productivity, energy flux, carbon and nitrogen cycling, nutrient cycling and forest dynamics.it is a critical biophysical parameter to describe the characteristics of forest ecosystems [1,2,3,4]
The focus of forest biomass estimation has been on timber quality and quantity [5], but this has shifted to forest carbon sequestration under the impetus of global climate change [6]
Studying the impact of stand age, stand density and structure of understory vegetation on single tree detection and forest biomass at the individual tree scale based on Unmanned Aerial Vehicle (UAV) Light Detection and Ranging (LiDAR) is a promising research direction
Summary
Accurate forest biomass estimation is the foundation of timber industry (timber, fiber and bioenergy) and forest management (forest plantation and natural resources). Monitoring forest biomass at the individual tree scale has two strengths: (1) summing growth responses of individual trees can follow species shifts at multiple ecological scales [2], and (2) forest biomass estimation at the individual tree scale could reduce the bias arising from spatial and temporal heterogeneity [14], including species-specific forest biomass estimation [15], habitat-specific forest biomass estimation [16] and managementspecific forest biomass estimation [17] Both environmental factors and forest management polices influence variation among individual trees in the forest ecosystem [7] and global climate change is predicted to further affect the metabolism of individual trees [18,19]. To develop forest biomass models at the individual tree scale with high accuracy and wide application, researchers have made significant modifications to forest stand-specific and species-specific forest biomass models by adding tree species as dummy variables into allometric equations and enlarging samples to reduce the impact of heterogeneity within and among forest ecosystems. A fruitful future direction may be to analyze the habitat- and managementspecific allometric algorithms for forest biomass at the individual tree scale
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