Mapping and monitoring tropical rainforests and quantifying their carbon stocks are important, both for devising strategies for their conservation and mitigating the effects of climate change. Airborne Laser Scanning (ALS) has advantages over other remote sensing techniques for describing the three-dimensional structure of forests. This study identifies forest patches using ALS-based structural attributes in a tropical rainforest in Sumatra, Indonesia. A method to group trees with similar attributes into forest patches based on Thiessen polygons and k-medoids clustering is developed, combining the advantages of both raster and individual tree–based methods. The structural composition of the patches could be an indicator of habitat type and quality. The patches could also be a basis for developing allometric models for more accurate estimation of carbon stock than is currently possible with generalised models.