Remote Sensing Estimation Of Winter Wheat LAI And Its Application In Evaluation Of Saline Soil Improvement

Coastal saline soil is an important land resource and a potential base for increasing grain output.Quickly and accurately obtaining crop information in the saline soil area can provide data support for saline soil improvement and is of great significance for the sustainable use of cultivated land resources in the saline soil improvement area.In this study,the coastal saline soil improvement experiment area in the Bohai Grain silo in Wudi County was used as the research area,and the winter wheat was used as the research material during the jointing period.Winter wheat LAI remote sensing inversion model.The factor analysis method was used to evaluate the improvement effect of the sampling plots in the saline soil area,and the LAI evaluation model for the improvement effect of the saline soil was established.Based on the evaluation model,the saline soil improvement of the entire Bohai Granary experimental area was carried out on the two scales of plot and field Evaluation.The main research contents and conclusions of this article are as follows:(1)For the winter wheat LAI UAV remote sensing estimation,in different UAV image smoothing windows,the 5×5 mean smoothed spectral data corresponds best to the wheat leaf area index.Compared with the single wave band,the constructed vegetation index can better invert the leaf area index of winter wheat at jointing stage,and the correlation between RVI and the leaf area index of winter wheat at jointing stage is the highest.The correlation between GRVI,NDVI and other vegetation indices is relatively low.Among the established UAV remote sensing leaf area index inversion models,the model built with support vector machines has the highest accuracy.The R~2 of the modeling set is 0.85,and the R~2 of the verification set is 0.66.Using the second UAV image to test the inversion model of the leaf area index,its R~2 is 0.67,RMSE is 0.72,RPD is 1.51,absolute error(?)is 0.58,relative error(?)is 0.35.This shows that UAV multi-spectral remote sensing can accurately predict the winter wheat leaf area index at centimeter-level spatial resolution.(2)In the satellite remote sensing inversion leaf area index model,the model constructed using the ratio vegetation index(RVI)has the highest estimation accuracy of the joint area winter wheat leaf area index at the field block scale.y=1.1631×RVI-1.4053.Its modeling set has R~2 of 0.82 and RMSE of 0.37.The verification set has R~2 of 0.87 and RMSE of 0.31.It shows that satellite remote sensing can accurately estimate the winter wheat leaf area index at the jointing stage in saline soil area at a spatial resolution of 30 meters.(3)Based on the soil sample index method to evaluate the improvement effect of the experimental plot in the test area,construct a model for evaluating the improvement effect of the leaf area index at the plot scale:y=0.4177×ln(LAI)+0.0328.The improvement effect score calculated by the model shows a high consistency with the actual saline soil improvement evaluation result,and the map of the saline soil improvement effect under different scales in the whole test area is obtained.The plots with the best improvement effect at the plot scale are numbered 26,27,28,29,30,and 31.At the plot scale,the improvement effect of the plot in the southeast of the test field is better,and the optimal improvement methods are salt reduction and soil improvement Comprehensive improvement measures of nutrients.(4)Using remote sensing technology to take advantage of the advantages of drone flexibility,strong timeliness and the advantages of satellite remote sensing large-scale and integrity at different spatial resolutions to invert the leaf area index of winter wheat at the jointing stage in the saline soil area,based on LAI Evaluation of saline soil improvement effects locates the best improvement effect at different scales.Compared with traditional methods,the evaluation results of saline soil area by remote sensing method have high consistency with traditional methods.They have the advantages of low cost and high precision.The research results have broad prospects for promotion and can be used for the improvement of saline soil.Provide important technical support.