摘要
开发有效的城市植被胁迫监测方法对于林业资源管理和营造良好的城市生态环境具有重要意义。采用EO-1卫星过境广州市东边建成区所采集的Hyperion高光谱影像,通过选取合适的植被指数进行分类,以及混合像元分解获得植被丰度这两种方法进行植被胁迫的识别,对比两者实验结果表明:在植被信息提取中植被丰度的方法要比指数法可靠且精度高;通过地面光谱测量,说明基于植被光谱理论的丰度分析能更好地表示植被胁迫的特征,为城市林业管理提供定性和定量的研究应用。
Developing effective methods for urban vegetation stress detection should be an important part of urban forestry resources management,and also for the favorable urban ecology and environment construction.In this paper we use Hyperion hyperspectral images in the eastern Guangzhou city,China,which is captured by the EO-1 satellite.Based on satellite-borne hyperspectral data,we want to conduct the vegetation stress identification,through these two methods：on one hand we selecting the appropriate vegetation indices for image classification;on the other hand we through ＂Spectral Mixture Analyst＂ to obtain vegetation abundance,and conduct several experiment steps as well.These two methods are both based on atmospheric correction preprocessing.Comparing these experimental results,it shows that in the feature extraction of vegetation,the vegetation abundance analysis methods is higher precision than the vegetation index method,which non vegetation feature spectral is excluded;and we through field spectrum measurement for validation,the result supports that the abundance analysis which is vegetation spectral theory base is better to characterize the vegetation stress feature,image spectral and field measurement have certain similarity.This research above will be for the application in urban forestry management by qualitatively and quantitatively.
出处
《遥感技术与应用》
CSCD
北大核心
2012年第1期68-76,共9页
Remote Sensing Technology and Application
基金
国家自然科学基金项目(40801034)
广州市高校科技计划项目(08C025)
关键词
高光谱遥感
城市植被
胁迫监测
植被指数
植被丰度
光谱
Hyperspectral remote sensing
Urban vegetation
Stress monitoring
Vegetation indices
Vegetation abundance
Spectrum
