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Pit-Free Canopy Height Models from LiDAR by 030Uttriantics Arianto is a document available to read on EtoBox.
Zhang et al. (2020) present a novel algorithm based on cloth simulation to construct pit-free canopy height models (CHMs) from airborne LiDAR data, addressing the issue of data pits that negatively affect forest inventory accuracy. The proposed method effectively fills data pits while preserving canopy details, demonstrating superior performance compared to existing algorithms with the lowest average root mean square error and improved tree height estimation. This algorithm shows high potential for various
- Author
- 030Uttriantics Arianto
- Language
- EN