中文摘要：

在中尺度对地观测系统中,Landsat和ASTER数据无疑是使用得最多的遥感影像数据,但是长期以来二者植被指数之间的定量关系并不清楚。因此,利用三对同日过空的Landsat ETM＋和ASTER影像来考察二者植被指数（NDVI、SAVI）之间的定量关系,重点查明二者之间的差异。通过将ETM＋与ASTER影像的多光谱波段的灰度值转换成传感器处反射率,并对其进行回归分析来求出二者植被指数之间的定量关系和转换方程。研究发现,尽管ETM＋与ASTER的植被指数之间具有显著的线性正相关关系,但是二者在光谱响应函数上的不同造成ASTER影像的植被指数信号总体上弱于EMT＋的植被指数信号。利用所求的转换方程对两种传感器的植被指数进行互为转换,其转换的精度较高,RMSE都小于0.04。

英文摘要：

The present paper investigates the quantitative relationship between the NDVI and SAVI vegetation indices of Landsat and ASTER sensors based on three tandem image pairs.The study examines how well ASTER sensor vegetation observations replicate ETM＋ vegetation observations,and more importantly,the difference in the vegetation observations between the two sensors.The DN values of the three image pairs were first converted to at-sensor reflectance to reduce radiometric differences between two sensors,images.The NDVI and SAVI vegetation indices of the two sensors were then calculated using the converted reflectance.The quantitative relationship was revealed through regression analysis on the scatter plots of the vegetation index values of the two sensors.The models for the conversion between the two sensors,vegetation indices were also obtained from the regression.The results show that the difference does exist between the two sensors,vegetation indices though they have a very strong positive linear relationship.The study found that the red and near infrared measurements differ between the two sensors,with ASTER generally producing higher reflectance in the red band and lower reflectance in the near infrared band than the ETM＋ sensor.This results in the ASTER sensor producing lower spectral vegetation index measurements,for the same target,than ETM＋.The relative spectral response function differences in the red and near infrared bands between the two sensors are believed to be the main factor contributing to their differences in vegetation index measurements,because the red and near infrared relative spectral response features of the ASTER sensor overlap the vegetation ＂red edge＂ spectral region.The obtained conversion models have high accuracy with a RMSE less than 0.04 for both sensors＇ inter-conversion between corresponding vegetation indices.