Lidar remote sensing of above‐ground biomass in three biomes

TLDR

Estimating forest carbon storage is essential for the global carbon cycle, yet conventional optical and radar sensors struggle with moderate‑to‑high biomass forests, and lidar, by capturing vertical forest structure, offers a promising remote‑sensing approach. This study compares lidar‑derived canopy structure with field measurements of above‑ground biomass across temperate deciduous, temperate coniferous, and boreal coniferous sites. A single regression model applied to all three sites is evaluated against site‑specific equations. The universal equation explains 84 % of the variance in above‑ground biomass (P < 0.0001) and shows no significant bias for any site.

Abstract

Abstract Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar ( li ght d etection and r anging) instruments measure the vertical structure of forests and thus hold great promise for remotely sensing the quantity and spatial organization of forest biomass. In this study, we compare the relationships between lidar‐measured canopy structure and coincident field measurements of above‐ground biomass at sites in the temperate deciduous, temperate coniferous, and boreal coniferous biomes. A single regression for all three sites is compared with equations derived for each site individually. The single equation explains 84% of variance in above‐ground biomass ( P &lt; 0.0001) and shows no statistically significant bias in its predictions for any individual site.