Lidar technology for scalable forest inventory

Friday 10 May 2024

Evaluating the trade-offs between the various platforms.

When considering Lidar technology for forest inventory, it is essential to evaluate the trade-offs of each platform. This article provides some pointers.

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?

Forests are a globally dominant ecosystem, covering nearly 40% of the Earth’s land area. They provide critical services such as fibre, timber, fuel, carbon dioxide removal, water supply filtering, flood erosion control, recreation and biodiversity sustenance. However, they are constantly challenged by various stressors. As the human population continues to grow, deforestation activities are on the rise to meet the need for material, agricultural land and urban developments.

Such stressors are exacerbated by intensified climate change. These challenges are calling for immediate attention, which was raised by the United Nations Department of Economic and Social Affairs in its Global Forest Goals Report, 2021. In this report, six goals are set to ensure global forest sustainability. It was emphasised that meeting these goals requires data-driven policies and management practices, powered by accurate/comprehensive inventory.

Examples of essential forest data for proper management include tree count, species, health, height, stem diameter, straightness, taper effect, branch number and branching order/angle. This information is essential for forecasting wood production, timber value, and carbon sequestration rates. Traditionally, inventory of such traits has been conducted manually, which is expensive and time-consuming.

Just as an example, the United States Forest Inventory and Analysis (FIA) programme spends close to US$100 million annually to inventory 18,000 acres, which corresponds to only 0.002% of the total US forest area. Other than the USA and EU, forest inventory programmes are almost non-existent around the globe. 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.

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Source: gim-international

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