Land-Unet: A deep learning network for precise segmentation and identification of non-structured land use types in rural areas for green urban space analysis

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103078 - 103078

Published: Feb. 1, 2025

Language: Английский

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Entropy guidance hierarchical rich-scale feature network for remote sensing image semantic segmentation of high resolution

Applied Intelligence, Journal Year: 2025, Volume and Issue: 55(6)

Published: March 13, 2025

Language: Английский

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YOLOTree-Individual Tree Spatial Positioning and Crown Volume Calculation Using UAV-RGB Imagery and LiDAR Data

Forests, Journal Year: 2024, Volume and Issue: 15(8), P. 1375 - 1375

Published: Aug. 6, 2024

Individual tree canopy extraction plays an important role in downstream studies such as plant phenotyping, panoptic segmentation and growth monitoring. Canopy volume calculation is essential part of these studies. However, existing methods based on LiDAR or UAV-RGB imagery cannot balance accuracy real-time performance. Thus, we propose a two-step individual volumetric modeling method: first, use RGB remote sensing images to obtain the crown information, then spatially aligned point cloud data height information automate volume. After introducing our method outperforms image-only 62.5% accuracy. The AbsoluteError decreased by 8.304. Compared with traditional 2.5D using only, proposed 93.306. Our also achieves fast vegetation over large area. Moreover, YOLOTree model more comprehensive than YOLO series detection, 0.81% improvement precision, ranks second whole for mAP50-95 metrics. We sample open-source TreeLD dataset contribute research migration.

Language: Английский

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A comprehensive review on tree detection methods using point cloud and aerial imagery from unmanned aerial vehicles

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 227, P. 109476 - 109476

Published: Oct. 1, 2024

Language: Английский

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