Fangfang Wu

TL;DR: A comparative shortest-path algorithm (CSP) for segmenting tree crowns scanned using terrestrial (T)-LiDAR and mobile LiDAR, inspired by the well-proved metabolic ecology theory and the ecological fact that vascular plants tend to minimize the transferring distance to the root.

TL;DR: Wang et al. as mentioned in this paper implemented a low-cost UAV-borne lidar system, including both a hardware system and a software system, to collect and process lidar data for biodiversity studies.

TL;DR: The results showed that the method combing deep leaning and regional growth algorithms was promising in individual maize segmentation, and the values of r, p, and F of the three testing sites with different planting density were all over 0.9.

TL;DR: A median normalized-vector growth (MNVG) algorithm, which can segment stem and leaf with four steps, i.e., preprocessing, stem growth, leaf growth, and postprocessing, is proposed, which may contribute to the study of LiDAR-based plant phonemics and precise agriculture.

TL;DR: The results demonstrate the feasibility of using terrestrial lidar to monitor 3D maize phenotypes under drought stress in the field and may provide new insights on identifying the key phenotypes and growth stages influenced by drought stress.