Effect Of Spatial Heterogeneity Of Soil Moisture On Quantitative Retrieval Of Soil Salinity

Soil salinity is one of the main reasons for soil quality and industrial productivity.The salt content in soil will seriously affect the growth and development of vegetation and the output of crops.In order to better deal with the threat of soil salinization,producers,land and water resources managers and policy makers need to make reliable,up-to-date and high-resolution assessment of soil salinity in large areas.However,due to the influence of a variety of environmental factors(rainfall,temperature,evapotranspiration,vegetation cover,etc.),the spectral reflectance of saline-alkali soil will change,which makes the monitoring results inaccurate,resulting in the inaccuracy of soil salinity inversion.Therefore,in order to ensure the sustainability and reliability of the grain production system,improving the accuracy of soil salinization inversion and more accurate acquisition of soil salinity has become an urgent problem to be solved.Soil moisture is an important factor affecting the spectral characteristics of saline-alkali soil,and its change is the comprehensive result of rainfall,air temperature,evapotranspiration and other factors,and under different seasonal or phenological conditions,the spatial difference of soil moisture will have a potential impact on the accuracy of the soil salinity inversion model.Therefore,it is of great significance to eliminate the influence of soil moisture on the remote sensing retrieval accuracy of soil salinity and alkalinity.In order to analyze the influence of spatial heterogeneity of soil moisture on the retrieval of soil salinity,this paper uses the method of temperature and vegetation drought index to model and retrieve the spatial distribution of soil salinity through Landsat8 OLI remote sensing satellite images.In addition,it was graded according to the soil relative humidity gradient,which was divided into five grades: no drought,mild drought,moderate drought,severe drought and special drought.Finally,based on the canopy response salinity index(CRSI),normalized difference vegetation index(NDVI)and automatic water extraction index(AWEI),based on Landsat8 OLI images,the soil salinity inversion model was established according to different soil relative humidity gradients,and 41 field sampled data were used to evaluate the inversion accuracy of the soil salinity model.The research results deeply excavate the data and information of saline-alkali soil in the study area,which is of great significance to increase crop yield,improve food security and maintain the ecological environment.at the same time,it provides scientific basis and theoretical support for relevant government agencies to prevent and control soil salinization in this area.The main research results of this paper are as follows:(1)The soil humidity of the Songnen Plains in the study area will exhibit a large spatial heterogeneity under different seasonal or beta conditions.In order to study the change characteristics of soil humidity in time and space,this study passed the temperature vegetation drought index method to model the soil relative humidity by During April 20,2015.Combined in the field acquisition of the field acquisition of the soil relative humidity in the field acquisition of the model,the decision coefficient is0.665,and the root mean square error is 3.76,which proves that the model of soil relative humidity by temperature vegetation drought index method is better.Accuracy,suitable for monitoring of soil surface moisture in the study area,and can also be used in the extraction of soil relative humidity data information on large scale range.(2)Affected by factors such as land use,soil type,evapotranspiration,rainfall,and vegetation coverage,the study area tends to become wet from the southwest to the northeast,then become dry and then wet.Most areas in the southwestern plain show a relatively short water shortage.In severe cases,most of the soil in the central plain is relatively humid.From different starting points and concerns,this study chooses "agricultural drought grade" as the drought grade classification standard of soil relative humidity in this area.In order to achieve the consistency of the classification standard,according to the drought grade standard stipulated by the Ministry of Water Resources of China,it is graded according to the soil relative humidity gradient.The soil relative humidity parameters and drought indexes used in this classification standard are consistent with those of domestic and foreign authorities.(3)The overall soil salinity model of the study area was established by the multiple linear regression method.In addition,five soil salinity models were established according to different soil moisture gradients to evaluate the influence of the spatial heterogeneity of soil moisture on the accuracy of soil salinization inversion.The results show that,compared with the traditional soil salinity model for the study area as a whole,building a soil salinity model according to the different soil moisture conditions can improve the accuracy of the model.In this study,we further studied the influence of soil relative humidity on the spectral characteristics of remote sensing images.After statistics and analysis of the results,we concluded that when the soil relative humidity exceeds 50%,the value obtained by the soil salinity inversion model will be underestimated.When the value is lower than or equal to 50%,the measured value will be overestimated.It shows that constructing the inversion model of soil salinity according to different soil moisture can eliminate the influence of the spatial difference of soil moisture on its inversion accuracy,and improve the inversion accuracy of the model.