旨在寻找叶绿素a的高光谱遥感敏感波段并建立其定量估算模型。通过对太湖水体的连续监测,获得了从2004年6月到8月3个月的太湖水体高光谱数据和水质化学分析数据。利用实测的高光谱数据分析计算太湖水体的离水辐亮度和遥感反射比;然后,通过相关分析寻找反演叶绿素a浓度的高光谱敏感波段,进而建立反演太湖水体叶绿素a浓度的高光谱遥感定量估算模型,并用相关数据对模型进行精度分析。研究发现,水体的遥感反射比光谱在719nm和725nm存在两个峰,其中719nm处的峰更明显且稳定。通过模型的对比分析,发现用这两个峰值处的遥感反射比参与建模可以提高叶绿素a的估算精度;并且认为由反射比比值变量R719/R670所建立的线性模型对叶绿素a浓度的估算精度最理想。
The study aims to search for the hyperspectral remote sensing bands most sensitive to chlorophyll-a concentration. Through repeated measurements in Taihu Lake, a large quantity of hyperspectral reflectance data and water quality data of the Lake were obtained from June to August of 2004. Those data acquired in unfavorable or abnormal monitoring conditions were removed from the dataset. The remaining ones were analyzed to calculate water-leaving radiance and reflectance of water in Taihu Lake. Chlorophyll-a ooncentration was then regressed against the reflectance data to identify the most sensitive hyperspectral bands. The established regression model was then used to estimate chlorophyll-a concentration in the Lake. Finally, accuracy of the model was assessed using other independent data. The result generated with the given monitoring method indicates that there are two reflectance peaks at 719nm & 725nm. Of them, the one at 719nm is more enhanced and stable. Through comparative analysis it is found that hyperspectral reflectance at these two peaks can improve the accuracy of estimating chlorophyll-a. Moreover, the accuracy of estimation is the highest using the ratio R719/R670 as the independent variable in the linear model.