Remote Sensing Indexes Of Winter Wheat Growth And Soil Salinity Inversion In The Coastal Area Of The Yellow River Delta

The Yellow River Delta is one of the youngest new lands in China,and the coastal saline soil widely distributed in the Yellow River Delta is typical all over the country.For nearly half a century,the unreasonable phenomenon of heavy irrigation and light drainage and heavy planting and light breeding has existed in the local agricultural production mode for a long time.In addition,the local groundwater level is too shallow and the salinity is too high,resulting in the increasingly serious problem of soil secondary salinization in this area,which has gradually become the most serious environmental problem affecting the production and life of the people in the yellow triangle.Therefore,efficient and accurate access to saline soil salinity information has long-term value for curbing soil salinity degradation in the Yellow River Delta and ensuring the sustainable development of agriculture.In order to explore a feasible method for predicting soil salt content based on remote sensing indicators of winter wheat growth,the typical coastal area of the Yellow River Delta,Kenli District,Dongying City,Shandong Province,was selected as the study area.The method of combining the field measured data of winter wheat returning to green period with the sentinel-2b satellite multispectral remote sensing image data obtained by the Copernicus program of the European Space Agency was adopted,The ground growth index based on winter wheat chlorophyll and plant height is constructed,the best growth index and model of winter wheat in the study area based on remote sensing image are screened,the distribution and growth information of winter wheat in the study area are extracted,and then the remote sensing model of soil salt in wheat field based on the best growth index is constructed,Finally,the inversion and analysis of soil salt in the distribution area of winter wheat in the study area are carried out.The main research contents and conclusions are as follows:Firstly,using the processed satellite image data and field survey data,the phenological calendar of crops and spectral differences of main ground features in the study area are analyzed,and the suitable phase and spectral characteristics of winter wheat are proved.Based on the decision tree normalized vegetation index greater than or equal to 0.3,the distribution of winter wheat in reclamation area is extracted.In 2019,the planting area of winter wheat in Kenli District was 15943.37 hectares,and the extraction accuracy was 95.47%compared with the actual planting area of 16700 hectares in Kenli District.At the same time,the distribution and growth of winter wheat in Kenli wheat area are analyzed.The growth trend of winter wheat in the study area is better in the southwest than in the northeast.Secondly,the relationship between spectral information such as image vegetation index and field measured winter wheat growth parameters in the study area is analyzed,the best remote sensing indicators of winter wheat growth are selected,and the growth model is constructed.Firstly,the ground growth index based on chlorophyll and plant height of winter wheat was constructed;Then,the remote sensing sensitive spectral parameters reflecting the growth of winter wheat were constructed and divided into three groups:growth sensitive band index group,growth vegetation index group and growth band composite index group.By using the correlation analysis method,the best remote sensing image quantitative index NIR/(R^0.33B^0.67)reflecting the growth of winter wheat was determined,and its correlation coefficient was 0.806;Finally,the best growth model of winter wheat was constructed,that is,y=7.106+11.226×(NIR/(R^0.33B^0.67))-0.621×(NIR/(R^0.33B^0.67))²,the coefficient of determination(R²)is 0.652 and the root mean square error(RMSE)is 3.2964.Thirdly,based on the selected best growth index,the best inversion model of soil salt in the coastal research area of the Yellow River Delta is constructed,that is,the quadratic regression model y=0.87-0.216 x+0.017 x²,the determination coefficient(R²)of the model is 0.871 and the root mean square error(RMSE)is 0.023.Using this model,the distribution grade of soil salt in wheat field in the study area is obtained,and its spatial characteristics are analyzed.The soil salt content of wheat field in Kenli District is the highest in the central region,followed by the northeast region,and the lowest in the southwest region.This study screened the best remote sensing image spectral index of winter wheat growth,constructed the remote sensing inversion model of soil salt in wheat area,and better found out the distribution of winter wheat growth and soil salt in the study area,which provided an effective method for remote sensing monitoring of soil salt in wheat field,and was of positive significance to the production and management of winter wheat in the coastal area of the Yellow River Delta.