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Using Aerial LiDAR Data to Map Vegetation Structural Types in Arid and Semi-Arid Rangelands
Journal article   Open access   Peer reviewed

Using Aerial LiDAR Data to Map Vegetation Structural Types in Arid and Semi-Arid Rangelands

Jaume Ruscalleda-Alvarez, Gerald F. M. Page, Katherine Zdunic and Suzanne M. Prober
Remote sensing (Basel, Switzerland), Vol.18(10), 1641
2026
DOI: https://doi.org/10.3390/rs18101641
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Open Access CC BY V4.0

Abstract

rangelands ecological condition aerial LiDAR vegetation structure unsupervised classification
Rangelands occupy over half of the Earth’s terrestrial surface and play an important role in supporting biodiversity and livelihoods. However, widespread degradation—particularly in arid and semi-arid regions—has compromised their ecological function. Traditional monitoring approaches that rely on vegetation cover metrics from optical satellite imagery fail to capture the three-dimensional structure of vegetation, which is critical for assessing ecosystem condition and guiding restoration and management efforts. This study demonstrates the application of high-density airborne LiDAR (ALS) data (~15–20 points/m2) to identify and map vegetation structural types across 370,000 hectares of semi-arid rangelands in Western Australia. Using an unsupervised fuzzy c-means clustering algorithm on seven minimally correlated ALS-derived structural metrics, we identified eight statistically distinct vegetation structural classes. The resulting structural map revealed spatial heterogeneity in vegetation structure, including in areas with similar vegetation cover, with high confidence in structural attribution in 74.5% of the study area. The rangeland-specific structural classes developed in this study, which incorporate measures of classification certainty, offer a robust framework for vegetation structural mapping in field data-scarce environments. This framework can support ecological condition assessments and provide a basis for rangeland management and restoration planning.

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