中文摘要：

利用星载高光谱遥感影像数据Hyperion并结合现场采样粒度分析资料,对潮间带表层沉积物类型的自动分类进行了研究。根据低潮位下沉积物的短波红外光谱反射率与沉积物组分（沙、粉砂、黏土）含量之间的强相关关系,选择2102 nm为特征波段,建立了高光谱定量遥感反演模型,获取初步的逐像元沙、粉砂和黏土含量,然后采用线性均衡化处理方法对初步反演结果进行修正,并结合Shepard三角分类法建立对照表,自动确定出每一像元对应的沉积物类型,得到研究区潮间带表层沉积物的空间分布特征,总体分类验证精度为87.9%。研究结果表明,研究区分布着三种沉积物,分别为粉砂质砂、砂质粉砂和粉砂,所占比例分别为18.9%,64.6%和16.5%,它们的空间分布趋势与研究区内的植被分布状况、水动力条件以及沉积物来源密切相关。

英文摘要：

Combining with in situ sedimentary sampling and survey, a satellite-based hyperspectral Hyperion image was successfully used for the surface sediment classification in a muddy intertidal region. Analysis indicated that under the low tidal level there were strong correlations between the surface spectrum reflectance in the shortwave infrared band and the contents of sand, silt and clay, respectively. For the 2 102 nm band, the correlation coefficient reached --0. 895 4, 0. 907 0 and 0. 654 7 correspondingly. So this band was chosen for the linear regression model construction and the sand, silt and clay contents were quantitatively reversed from their corresponding reflectance values. After that a linear equilibrium corrective method was applied for the amendment of these initial inversed content values. On the basis of these corrected sand, silt and clay contents, Shepard triangular graph method was used and the sediment classification for each pixel was automatically obtained with ENVI IDL program. The spatial distribution characteristics of the surface sediment type for the whole intertidal flat were then acquired with the total accuracy of 87.9%. Results indicated that there were three kinds of sediment distributed in the study area, namely, silty-sand, sandy-silt and silt with the percentage of 18.9%, 64.6% and 16.5%, respectively. The distribution trend of the three sediments was adaptive perfectly with the vegetation distribution patterns, hydrodynamic conditions and the sources of the sediments of this area.