Hyperspectral and color-infrared imaging from ultralight aircraft: Potential to recognize tree species in urban environments

G. Mozgeris, S. Gadal, D. Jonikavicius, L. Straigytė, W. Ouerghemmi, Vytaute Juodkiene
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引用次数: 12

Abstract

Imaging system based on simultaneous use of Rikola hyperspectral and RGB/NIR cameras installed on a manned ultra-light aircraft is introduced in this study. Simultaneously acquired hyperspectral and color-infrared (CIR) images were tested for their potential to identify deciduous tree species and estimate tree health in Kaunas city, Lithuania. Six urban deciduous tree species were separated using tree crown level statistics, extracted from 16 visible-near infrared spectral band hyperspectral images, and discriminant analyses with an overall classification accuracy of 63.1 %. Classification accuracy increased by 3 percent when hyperspectral images were integrated with simultaneously acquired CIR images. The accuracy in identifying tree health using fused hyperspectral and CIR images, ranged from poor to moderate.
来自超轻型飞机的高光谱和彩色红外成像:在城市环境中识别树种的潜力
本文介绍了安装在载人超轻型飞机上的Rikola高光谱相机和RGB/NIR相机同时使用的成像系统。对立陶宛考纳斯市同时获得的高光谱和彩色红外(CIR)图像进行了测试,以确定其鉴定落叶树种和估计树木健康状况的潜力。利用树冠水平统计方法,从16幅可见光-近红外波段高光谱图像中提取6种城市落叶树,并进行判别分析,总体分类精度为63.1%。当高光谱图像与同时获取的CIR图像集成时,分类精度提高了3%。使用融合的高光谱和CIR图像识别树木健康状况的准确性从差到中等不等。
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