Feasibility Study on the Classification of Persimmon Trees’ Components Based on Hyperspectral LiDAR

• DOI: 10.3390/s23063286
• Publication Date: 2023-03-21T06:36:22Z
• Authors: Hui Shao; Fuyu Wang; Wei Li; Peilun Hu; Long Sun; Chong Xu; Changhui Jiang; Yuwei Chen
• Keywords: Tree (set theory); Feature (linguistics)

Intelligent management of trees is essential for precise production in orchards. Extracting components’ information from individual fruit critical analyzing and understanding their general growth. This study proposes a method to classify persimmon tree components based on hyperspectral LiDAR data. We extracted nine spectral feature parameters the colorful point cloud data performed preliminary classification using random forest, support vector machine, backpropagation neural network methods. However, misclassification edge points with reduced accuracy classification. To address this, we introduced reprogramming strategy by fusing spatial constraints information, which increased overall 6.55%. completed 3D reconstruction results coordinates. The proposed sensitive shows excellent performance classifying components.