LiDAR Applications in Avian Habitat Assessment

Light Detection and Ranging (LiDAR) has emerged as a transformative tool for avian habitat assessment by providing high‐resolution, three‐dimensional data on vegetation structure across scales from local plots to entire landscapes. Airborne and terrestrial LiDAR systems generate dense point clouds that capture vertical profiles of canopy height, foliage density and understorey complexity, offering a means to quantify habitat features that are critical to nesting, foraging and movement of bird species. These metrics enable researchers to disentangle the relative importance of horizontal heterogeneity (patchiness, gap distributions) and vertical stratification (layer thickness, foliage height diversity) in shaping avian diversity, abundance and occupancy patterns. Integration of LiDAR‐derived structural covariates into species distribution or occupancy models has improved predictions of habitat suitability, particularly in regions where conventional field surveys are logistically challenging. Moreover, repeat LiDAR acquisitions allow monitoring of habitat change over time, informing conservation management by detecting canopy degradation, regeneration and responses to climate and land‐use change. Spaceborne LiDAR missions further extend these applications to global scales, facilitating comparative assessments of forest structure and its influence on avian communities across biomes. By linking fine‐scale structural information with ecological theory and demographic data, LiDAR offers a robust framework to support evidence‐based conservation planning for vulnerable and migratory bird populations worldwide.

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LiDAR Applications in Avian Habitat Assessment publication trend

The graph below shows the total number of articles in lidar applications in avian habitat assessment across all publications each year (not limited to Nature Index journals).

Technical terms

LiDAR: A remote‐sensing method that emits laser pulses to measure distances to terrestrial surfaces, generating detailed three‐dimensional point clouds of vegetation and terrain.

Point cloud: A dense collection of spatial coordinates representing the returns from individual LiDAR laser pulses, used to reconstruct three‐dimensional structures.

Canopy height model (CHM): A raster representation of the vertical distance between ground elevation and the top of the vegetation canopy, produced from LiDAR point clouds.

Foliage height diversity (FHD): A measure of the vertical distribution and evenness of foliage layers within the canopy, calculated from the frequency of LiDAR returns at different height bins.

Leaf area density (LAD): The amount of leaf surface area per unit volume of air within specified vegetation layers, derived from the vertical distribution of LiDAR returns and used to assess habitat complexity.

References

1. Feedback loops between 3D vegetation structure and ecological functions of animals. Ecology Letters (2023).
2. Consistent patterns of LiDAR-derived measures of savanna vegetation complexity between wet and dry seasons. Ecological Indicators (2025).
3. Integrating spaceborne estimates of structural diversity of habitat into wildlife occupancy models. Environmental Research Letters (2023).
4. Metrics of Lidar-Derived 3D Vegetation Structure Reveal Contrasting Effects of Horizontal and Vertical Forest Heterogeneity on Bird Species Richness. Remote Sensing (2019).