湖北农业科学2025，Vol.64Issue(4)：1-6,23,60,8.DOI:10.14088/j.cnki.issn0439-8114.2025.04.001
基于无人机高光谱和激光雷达数据的单木树种分类
Individual tree species classification based on UAV hyperspectral and LiDAR data
摘要
Abstract
UAV LiDAR data were used for individual tree segmentation to obtain tree crown boundaries,and UAV hyperspectral data within the crown boundaries were extracted.Feature fusion schemes were constructed based on band reflectance,vegetation indices,and texture indices,including scheme 1(band reflectance),scheme 2(vegetation indices),scheme 3(texture indices),scheme 4(band reflectance+vegetation indices),scheme 5(band reflectance+texture indices),scheme 6(vegetation indices+texture indi-ces),and scheme 7(band reflectance+vegetation indices+texture indices).The random forest algorithm was applied to classify indi-vidual tree species in the Gudao shelterbelt of the Yellow River Delta,achieving classification of four species:Robinia pseudoacacia,Sophora japonica,Ulmus pumila,and Fraxinus chinensis.The results showed that using only texture indices yielded the worst classifi-cation accuracy(0.333)and Kappa coefficient(0.056).Scheme 7 achieved the best classification results,with an accuracy of 0.917 and a Kappa coefficient of 0.887.Scheme 5 achieved a classification accuracy of 0.916 and a Kappa coefficient of 0.886.While main-taining classification accuracy,scheme 5 significantly reduced feature dimensionality.Therefore,the combination of spectral reflec-tance and spatial texture features was recommended as the optimal scheme.关键词
无人机/高光谱/激光雷达/单木尺度/树种分类Key words
UAV/hyperspectral/LiDAR/individual tree level/tree species classification分类
农业科技引用本文复制引用
章萌,王红,刘思思,杨文财..基于无人机高光谱和激光雷达数据的单木树种分类[J].湖北农业科学,2025,64(4):1-6,23,60,8.基金项目
国家自然科学基金项目(31971579) （31971579）
