地理空间信息2024，Vol.22Issue(5)：70-73,4.
利用无人机多光谱影像分类电力廊道树种
Tree Species Classification in Power Corridor Using UAV Multi-spectral Images
摘要
Abstract
Bamboo and eucalyptus have become one of the main tree barrier threats faced by high-voltage transmission lines in densely vegetated areas due to their fast growth and high canopy.The identification of bamboo and eucalyptus is the key to early tree barrier warning.We used the multi-rotor UAV to obtain the multi-spectral images of high-voltage transmission corridor area,and made full use of the advantages of red edge band to extract the spectral features and vegetation index features at first.And then,we used the random forest(RF)algorithm to optimize the vegetation index features.Finally,we compared the maximum likelihood and support vector machine classification methods.Feature optimiza-tion based on RF can not only reduce the dimension of feature variables,but also maintain the original classification accuracy,so as to improve the efficiency of classification.关键词
树种识别/无人机多光谱影像/红边波段/植被指数/RFKey words
tree species identificaion/UAV multi-spectral image/red edge band/vegetation index/RF分类
天文与地球科学引用本文复制引用
胡娜,曹原野,何勇,陈启浩,原瀚杰,董丽梦,刘修国..利用无人机多光谱影像分类电力廊道树种[J].地理空间信息,2024,22(5):70-73,4.基金项目
国家自然科学基金资助项目(41771467) （41771467）
南方电网公司科技资助项目(031200KK52190099、GDKJXM20198220). （031200KK52190099、GDKJXM20198220）
