• Energy Research

AbstractRemote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large‐scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.

In this paper we present a study on the estimation of the aboveground biomass in tropical forests at single tree level using airborne laser scanning (ALS) data. Individual tree crowns (ITCs) are firstly detected using a method based on an adaptive window that change its size according to tree height. The diameter at breast height (DBH) and the aboveground biomass (AGB) of each ITC then are predicted using standard allometric models. Lastly, the AGB values are aggregated at plot level, and compared with field measured values. The results show that it is possible to accurately predict the aboveground biomass of tropical forests at single tree level using ALS data.

Abstract Background Forests are a key component of the global carbon cycle, and research is needed into the effects of human-driven and natural processes on their carbon pools. Airborne laser scanning (ALS) produces detailed 3D maps of forest canopy structure from which aboveground carbon density can be estimated. Working with a ALS dataset collected over the 8049-km2 Wellington Region of New Zealand we create maps of indigenous forest carbon and evaluate the influence of wind by examining how carbon storage varies with aspect. Storms flowing from the west are a common cause of disturbance in this region, and we hypothesised that west-facing forests exposed to these winds would be shorter than those in sheltered east-facing sites. Methods The aboveground carbon density of 31 forest inventory plots located within the ALS survey region were used to develop estimation models relating carbon density to ALS information. Power-law models using rasters of top-of-the-canopy height were compared with models using tree-level information extracted from the ALS dataset. A forest carbon map with spatial resolution of 25 m was generated from ALS maps of forest height and the estimation models. The map was used to evaluate the influences of wind on forests. Results Power-law models were slightly less accurate than tree-centric models (RMSE 35% vs 32%) but were selected for map generation for computational efficiency. The carbon map comprised 4.5 million natural forest pixels within which canopy height had been measured by ALS, providing an unprecedented dataset with which to examine drivers of carbon density. Forests facing in the direction of westerly storms stored less carbon, as hypothesised. They had much greater above-ground carbon density for a given height than any of 14 tropical forests previously analysed by the same approach, and had exceptionally high basal areas for their height. We speculate that strong winds have kept forests short without impeding basal area growth. Conclusion Simple estimation models based on top-of-the canopy height are almost as accurate as state-of-the-art tree-centric approaches, which require more computing power. High-resolution carbon maps produced by ALS provide powerful datasets for evaluating the environmental drivers of forest structure, such as wind.

AbstractTropical peat swamp forests (PSFs) are globally important carbon stores under threat. In Southeast Asia, 35% of peatlands had been drained and converted to plantations by 2010, and much of the remaining forest had been logged, contributing significantly to global carbon emissions. Yet, tropical forests have the capacity to regain biomass quickly and forests on drained peatlands may grow faster in response to soil aeration, so the net effect of humans on forest biomass remains poorly understood. In this study, two lidar surveys (made in 2011 and 2014) are compared to map forest biomass dynamics across 96 km2 of PSF in Kalimantan, Indonesia. The peatland is now legally protected for conservation, but large expanses were logged under concessions until 1998 and illegal logging continues in accessible portions. It was hypothesized that historically logged areas would be recovering biomass while recently logged areas would be losing biomass. We found that historically logged forests were recovering biomass near old canals and railways used by the concessions. Lidar detected substantial illegal logging activity—579 km of logging canals were located beneath the canopy. Some patches close to these canals have been logged in the 2011–2104 period (i.e. substantial biomass loss) but, on aggregate, these illegally logged regions were also recovering. Unexpectedly, rapid growth was also observed in intact forest that had not been logged and was over a kilometre from the nearest known canal, perhaps in response to greater aeration of surface peat. Comparing these results with flux measurements taken at other nearby sites, we find that carbon sequestration in above‐ground biomass may have offset roughly half the carbon efflux from peat oxidation. This study demonstrates the power of repeat lidar survey to map fine‐scale forest dynamics in remote areas, revealing previously unrecognized impacts of anthropogenic global change.

Abstract. Borneo contains some of the world’s most biodiverse and carbon dense tropical forest, but this 750 000-km2 island has lost 62 % of its old-growth forests within the last 40 years. Efforts to protect and restore the remaining forests of Borneo hinge on recognising the ecosystem services they provide, including their ability to store and sequester carbon. Airborne Laser Scanning (ALS) is a remote sensing technology that allows forest structural properties to be captured in great detail across vast geographic areas. In recent years ALS has been integrated into state-wide assessment of forest carbon in Neotropical and African regions, but not yet in Asia. For this to happen, new regional models, need to be developed for estimating carbon stocks from ALS in tropical Asia, as the forests of this region are structurally and compositionally distinct from those found elsewhere in the tropics. By combining ALS imagery with data from 173 permanent forest plots spanning the lowland rain forests of Sabah, on the island of Borneo, we develop a simple-yet-general model for estimating forest carbon stocks using ALS-derived canopy height and canopy cover as input metrics. An advanced feature of this new model is the propagation of uncertainty in both ALS- and ground-based data, allowing uncertainty in hectare-scale estimates of carbon stocks to be quantified robustly. We show that the model effectively captures variation in aboveground carbons stocks across extreme disturbance gradients spanning tall dipterocarp forests and heavily logged regions, and clearly outperforms existing ALS-based models calibrated for the tropics, as well as currently available satellite-derived products. Our model provides a simple, generalised and effective approach for mapping forest carbon stocks in Borneo, and underpins ongoing efforts to safeguard and facilitate the restoration of its unique tropical forests.