| In order to solve the problem of satellite-aircraft coordination in remote sensing monitoring of crop growth, at the field scale, this study set up wheat nitrogen and irrigation gradient tests, measured SPAD, LAI and other growth indicators at each key growth period, obtained UAV remote sensing data, and built a wheat growth multi spectral monitoring model. The acquisition model was scaled up using the optimized band ratio correction method combined with Sentinel-2A image. The results showed that at jointing stage, booting stage, flowering stage and filling stage, the cubic function, exponential function, exponential function, and power function constructed by Clgreen, Clrededge, OSAVI, and OSAVI respectively were the best for SPAD fitting, and the accuracy of verification was better when scale up was applied to booting stage, flowering stage, and filling stage. The power function, quadratic function, exponential function, and exponential function constructed by Clgreen, Clrededge, DATT, and OSAVI in the above four growth periods are the best for LAI fitting, and the accuracy of scaling up application verification is good. According to the monitoring of the growth of winter wheat in Xianyang City based on the satellite computer coordination method, in 2021, the growth of wheat in Wugong County, Xingping City and Sanyuan County is better, while that in Yongshou County, Chunhua County and Binzhou City is worse. The improvement of the fusion method of unmanned aerial vehicle and satellite remote sensing image can improve the satellite-aircraft coordination in winter wheat growth monitoring. |
基本信息
