In order to analyze and detect wheat stripe rust disease quantitatively, a Feature Position and Parameter Mode (FPPM) of spectral responses and disease detection is built based on the airborne wheat PHI(Pushbroom hyperspectral imager) images, and a new adjustable Multi-Temporal Normalized Difference Vegetation Index (MT-NDVI) is provided to extract the disease information in terms of the temporal spectral features. The results show that the FPPM can well response and monitor the disease occurring during the wheat growing, and the MT-NDVI method integrating Spectral Angle Mapper(SAM) technique can represent clearly the disease where is serious, slight or not influential, distinguish and extract the disease information accurately from health wheat and soil.