The invention discloses a
vegetation parameter fitting method based on middle-
high resolution remote sensing. Due to the facts that used coarse resolution
remote sensing data can be acquired easily,
time resolution is very high, free shared data and products can be obtained, and the growth and development law difference of different
vegetation types and the growth and development law difference in the
vegetation of the same type are also used, when a study urges for the vegetation parameter in certain time, however, only the
remote sensing data in another time can be acquired, through the method, the
vegetation remote sensing parameter in the needed time can be simulated, and remote sensing
study methods are enriched. For the reason that the middle-
high resolution remote sensing is used for regional scale study, through the method, remote
sensing data acquired at the study area in different time can be unified to the time which is needed by the study, and therefore the remote
sensing data covering the entire study area in the same time can be acquired. Cloudless middle-
high resolution remote
sensing data in the needed time can reappear, and thus necessary data support can be provided for
vegetation remote sensing correlation study work such as ecological remote sensing, environmental remote sensing and agricultural remote sensing.