遥感技术已成为大尺度植被分类的重要手段，而地面植物群落特征与其光谱特征之间的关系是解译遥感影像的关键。该研究选择上海崇明东滩自然保护区的盐沼植物群落为对象，应用ASD地物光谱仪测定其植物群落的光谱反射率，并采用10个小型机载成像光谱仪 （CASI）默认植被波段组，应用主分量分析法和相关分析分析了不同群落光谱特征与生态环境因子之间的关系。分析结果表明，间接排序法PCA能够识别盐沼植被中光滩、海三棱藨草 (Scirpus mariqueter)群落、芦苇(Phragmites australis)群落和互花米草(Spartina al terniflora)等群落的光谱特征，绝大多数盐沼湿地植物群落组成与光谱特征之间有显著的相关，识别效果最好的波段组是736～744 nm、746～753 nm、775～784 nm、8 15～824 nm和860～870 nm；对光谱反射率影响最大的生态环境因子分别是植物群落的高度和盖度，高程和其它环境因子的影响次之。研究成果可为遥感监测崇明东滩自然保护区内入侵种互花米草的空间分布和扩散规律提供技术支撑，为高光谱遥感影像的影像判读和解译分类以及盐沼湿地植被制图提供科学依据。
Remote sensing is a major source of spatial information of the attributes of the earth‘s surface, and remote sensing technology has become a primary tool for vegetation classification at large scales. The relationship between vegetation and their spectral characteristics is key for interpreting remote sensing images. This study related characteristics of saltmarsh vegetation at the intertidal zone of Chongming Dongtan Nature Reserve, Shanghai, to patterns of their spectral reflectance. Paired measurements of saltmarsh community and spectral cha racteristics were carried out along three transects covering the major variations in vegetation and environment within the study area. The spectral characteristics were measured by a ground FieldSpec Pro JR spectroradiometer and the spectral data were converted to simulate the 10 bands of Compact Airborne Spectrogr aphic Imager (CASI) bandset. The spectral data sets were then ordinated using Pr incipal Component Analysis (PCA), an indirect ordination technique. The eigenvalue of the first PCA axis was 19.9, which represented 98.5% of the variation in the spectral data. A sequence of bare mudflat, Scirpus mariqueter community, Spartina alterniflora community and Phragmites australis community changed along the first ordination axis showed a strong correspondence with variation in the bands six to ten, i.e. the simulated CASI wavebands covering the 736 to 870 nm wavel engths. A significant relationship between the first axis PCA scores for the spectral data of quadrats and their percentage community cover and height also was identified. The second axis accounted for only 1.4% of the variation in the spectral data and it proved impossible to demonstrate any close link between any specific plant community type and a distinct set of spectral characteristics because of its low representation of the variation in the spectral data. Our study has demonstrated that the variation in the spectral data of saltmarsh vegetation at Chongming Dongtan Nature Reserve can be identified using the indirect ordination technique of PCA and then applying correlation and regression analyses to explain the relationships between the variation in the spectral data with the vegetation and ecological data. Our results indicate that PCA is of value for identifying relationships between community types and the spectral data of CASI bandsets for saltmarsh vegetation. This could provide an effective and practical approach for classification of saltmarsh vegetation at large scales and for monitoring spatio_temporally dynamic patterns of saltmarshes at Chongming Dong tan Nature Reserve. Further work is required in order to test these conclusions. The method has been evaluated for a single season with a limited sample of salt marsh plant communities, and the application of PCA and spectral data of CASI bandsets to other saltmarsh vegetation as well as multi_seasonal spectral data are necessary to determine whether similar patterns emerge and whether the approach has more general applicability in terms of characterizing remote sensing/spectral imagery and community types in saltmarsh vegetation.