{"id":"c9e70f3f-0c81-4388-8146-019f7b7b6d36","uri":"https://catalogue.ceh.ac.uk/id/c9e70f3f-0c81-4388-8146-019f7b7b6d36","type":"dataset","title":"LiDAR-derived canopy height model and digital terrain model of Sabah Biodiversity Experiment, Malaysia, 2020","description":"This dataset contains raster layers at 1-m resolution representing the canopy height model (CHM) and digital terrain model (DTM) of the Sabah Biodiversity Experiment (SBE), Sabah, Malaysia. CHM and DTM were created from airborne LiDAR point cloud data collected at SBE in 2020. The data were collected to assess the effectiveness of different restoration interventions for speeding up the recovery of logged tropical forests in SE Asia.","metadataDate":"2026-03-27T11:53:17","resourceIdentifiers":[{"code":"https://catalogue.ceh.ac.uk/id/c9e70f3f-0c81-4388-8146-019f7b7b6d36"},{"code":"10.5285/c9e70f3f-0c81-4388-8146-019f7b7b6d36","codeSpace":"doi:"}],"lineage":"CHM and DTM (1-m resolution rasters) were created from the LiDAR point cloud data using the processing pipeline described by Fischer et al. (2024, https://doi.org/10.1111/2041-210X.14416). This processing pipeline first uses the lasground_new algorithm implemented in LasTools to classify ground returns and create the DTM, after which a spike-free algorithm is used to generate the CHM. 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J., Jackson, T., Vincent, G., & Jucker, T. (2024). Robust characterisation of forest structure from airborne laser scanning-A systematic assessment and sample workflow for ecologists. 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