粉尘污染是城市大气污染的主要来源之一，城市植物可吸收或滞留空气中的粉尘从而减轻大气污染，改善空气质量。因此，植物滞尘能力已经成为城市引种和筛选绿化植物的一个重要指标。本项目从监测城市植物粉尘污染和评估滞尘能力出发，以上海市常见绿化植物为研究对象，采用实验遥感技术，基于不同粉尘污染强度下不同滞尘植物的实验室和野外观测的高光谱数据、理化参数和滞尘量数据，采用多种光谱处理技术和多种特征光谱提取方法，分析不同粉尘污染强度下滞尘植物的高光谱响应规律，研究城市植物粉尘污染的高光谱遥感探测方法。进而分析不同滞尘植物不同滞尘量的光谱差异特征及其与滞尘量的关系，提出一套植物滞尘量的高光谱估算方法与模型，实现对城市植物滞尘能力的光谱评估。通过本研究，为城市植物粉尘污染监测及植物滞尘效应评估提供一种科学、快速无损的新方法，可为城市环境管理、城市绿化植物的合理配置、引种和筛选，以及城市空气质量的监测提供科学依据。

Dust pollution is one of main sources of urban environment pollution, and it is the most harmful air pollutant to human health. Urban plant can reduce dust pollution by retention effect. Therefore, it is very important for the maintenance of urban plant and the improvement of ecological environment by evaluating the dust retention effect and pollution status.In this project,we aim to study the methods for hyperspectral remote sensing-based diagnosis and retrieval of dust-retention capacity and dust pollution stress of urban plant by using ground-based remote sensing. We will choose the common greening plants as the study samples in Shanghai. On the selected regional testing area, according to the status of dust pollution stress of urban plant, we synchronized obtained the chlorophyll contents, carotenoid contents, water contents, leaf area index and retention effect quantity, taking advantage of easured ASD hyperspectral data of typical urban plant samples at leaf and canopy. And then, the response relationships between potential sensitive spectrum remote sensing indices and physiological ecology parameters in urban plant dust pollution stress were analyzed,such as leaf pigment concentration,water content and leaf area index. After that we select the relatively sensitive bands and parameters. Based on them, we set up remote sensing detection method and inversion model of dust-retention quantity and dust pollution. Our research will provide a new and rapid method for evaluating dust-retention and pollution monitor on urban plant.