There is a critical need for rapid, rigorous, reproducible and scalable forest inventory tools to support data-driven policies and management practices in response to challenges including deforestation and climate change. Lidar technology offers an alternative for automated forest inventory at various scales, but each platform has trade-offs in terms of cost, efficiency, coverage, resolution or more. So, what is the solution?
Forest inventory programmes are varied in their scope and quality around the world Therefore, there is a critical need for rapid, rigorous, reproducible and scalable inventory tools.
With advances in sensor and algorithmic technologies, remote/near-proximal/proximal sensing – including imaging and Lidar systems onboard space/aerial vehicles, stationary terrestrial laser scanners (TLS) and terrestrial mobile Lidar – has recently been explored as an alternative for automated forest inventory at various scales.
These sensors/platforms have trade-offs in terms of cost, field survey efficiency, spatial coverage, spatial resolution and level of detail of the acquired information. Figure 1 shows two examples of potential data acquisition systems (near proximal and proximal) for fine-scale forest inventory.
Space imagery and airborne Lidar
Space imagery and Lidar data facilitate global and national forest inventory. However, limited spatial and temporal resolution would not allow for fine-scale inventory at the single tree level. Photogrammetric processing of images acquired by spaceborne and crewed aerial systems has attracted the attention of the forestry research community for estimating inventory attributes such as tree height, stem volume and basal area.
However, image-based point cloud generation is challenged by the difficulty in identifying corresponding points in overlapping images over forest landscape during both leaf-on and leaf-off conditions. Moreover, derived point clouds from imagery only capture the outer envelope of the forest canopy. Airborne Lidar provides large spatial coverage, fine resolution and the ability to represent the outer envelope and below-canopy structure.
Lower canopy mapping is facilitated by the fact that Lidar energy can travel through gaps among the trees/leaves and derive returns from tree trunks and terrain. Such ability makes Lidar an attractive modality for deriving ground slope and aspect, stem map, canopy height, crown dimension and leaf area index (LAI), to name but a few traits.
The large majority of airborne Lidar systems are based on linear Lidar technology, which is characterized by a high-power signal emission and a low-sensitivity receiver for detecting echo returns. Linear Lidar is based on emitted laser pulses with some nanosecond pulse width at wavelengths from 500nm (for bathymetric Lidar) to 1.5μm (for topographic Lidar).
The echo returns are then digitized by the receiver. To discriminate signal return from noise, linear Lidar utilizes a single-detector receiver that requires a flux of hundreds or thousands of photons. Such characteristics of linear Lidar impose constraints on the flying height, platform speed and lateral distance between neighbouring flight lines to ensure the delivery of point clouds with reasonable point density.