Lidar: Definition

Updated 2026-11-02 · 2 min read · By the akar.earth specialist team

What is lidar in forestry? How laser scanning measures canopy height and forest structure for biomass and carbon estimates, with Indonesia examples.

Lidar (light detection and ranging) is a remote sensing method that fires laser pulses and times their return to measure distances. In forestry it produces 3D point clouds that show canopy height, crown shape and the ground surface beneath trees.

Why it matters

Tree height and canopy structure are strong predictors of above-ground biomass. Optical satellite data saturates in dense tropical forest, so it stops telling high-biomass stands apart. Lidar does not saturate in the same way. That makes it one of the most accurate tools for wall-to-wall biomass maps, baseline stock estimates and checking degradation from selective logging.

How it is used

• Airborne laser scanning (ALS) from planes or helicopters covers whole landscapes at high point density.
• Drone lidar (UAV) covers project sites or sample blocks at lower cost per flight.
• Spaceborne lidar such as GEDI samples footprints across the tropics, which can calibrate wider satellite maps.

The typical workflow builds a digital terrain model and a canopy height model, extracts metrics such as mean height and canopy cover, and links them to field plot biomass with a regression. Our canopy height models guide covers this step.

Indonesia and Southeast Asia angle

Lidar is especially useful on Indonesian peatland and lowland dipterocarp forest, where biomass is high and logging damage is hard to see from optical satellites. It also helps map peat surface elevation and drainage. The main limits are cost, flight permits and the need for good GNSS ground control in remote areas.

Cost per hectare falls sharply with area flown, so lidar is most efficient when one campaign serves several purposes: baseline biomass, stratification, terrain models for planting design and an independent check on satellite estimates.

Common mistakes

• Expecting lidar to give species or wood density; it does not.
• Using a global height-to-biomass model instead of one calibrated on local plots.
• Mismatched dates between lidar flights and field plots in fast-growing plantations.

Compare options in lidar vs photogrammetry and GEDI lidar.