Wheat LAI (leaf area index) estimation method coupled with satellite-ground remote sensing

The invention relates to the field of agricultural vegetation remote sensing, particularly to a wheat LAI (leaf area index) estimation method coupled with satellite-ground remote sensing. The method comprises steps as follows: 1) acquiring two different scales of canopy spectrum information, namely, a wheat ground high-spectrum and an SPOT-5 image; 2) fitting a wheat canopy high-spectrum and a ridge high-spectrum with a satellite sensor wave spectrum response function; 3) extracting a pure satellite pixel spectrum on the basis of a mixed pixel linear decomposition model; 4) meanwhile, verifying the pure satellite pixel spectrum by the aid of a synchronous wheat simulation pixel spectrum; 5) constructing a wheat LAI monitoring model coupled with satellite-ground remote sensing with related statistical methods. The method overcomes defects of existing ground remote sensing point scales and satellite remote sensing mixed pixels and is higher in precision and accuracy of estimation of wheat LALs at different nitrogen application levels in different ecological regions in particular, wheat LAI growth information is acquired in real time, and wide application of remote sensing based crop growth remote sensing monitoring technologies is facilitated.