同济大学学报（自然科学版）2024，Vol.52Issue(6)：970-981,12.DOI:10.11908/j.issn.0253-374x.22359
结合星载激光和多光谱影像的城市树种分类
Urban Tree Species Classification Combining Spaceborne LiDAR and Multispectral Imagery
摘要
Abstract
The urban tree species are an important factor affecting the ability of carbon sequestration by urban forest and the maintenance of ecosystem stability.However,due to the wide spatial distribution and complex environment of urban trees,there is a lack of tree species classification models applicable to cities.In this paper,the spaceborne LiDAR is introduced into tree species classification.Considering the vegetation canopy structure,horizontal spectra and spatial environment characteristics,the optimal feature set is constructed by quantitatively measuring the contribution of each parameter through feature space analysis.Finally,an urban tree species classification model combining spaceborne LiDAR and optical images is established using support vector machine(SVM)algorithm.Four representative regions in Shanghai are selected for validation,and the results show that the proposed fusion model has a high accuracy with the Kappa coefficient reaching 0.82 and the overall classification accuracy of 87.04％.The spaceborne LiDAR plays an important role in the urban tree species classification,and its retrieved 3D structural variables of vegetation together with spatial environmental characteristics play a major contribution to urban tree species classification.关键词
城市树种分类/星载激光/光谱影像/支持向量机(SVM)算法Key words
urban tree species classification/spaceborne LiDAR/spectral imagery/support vector machine(SVM)algorithm分类
信息技术与安全科学引用本文复制引用
王书凡,刘春,吴杭彬,李巍岳..结合星载激光和多光谱影像的城市树种分类[J].同济大学学报（自然科学版）,2024,52(6):970-981,12.基金项目
国家自然科学基金(42130106) （42130106）
上海市科委"科技创新行动计划"优秀学术带头人项目(20XD1403800) （20XD1403800）
