The public opinion has a guiding role and significance for the construction and development of agriculture. The distribution characteristics of the public opinion data in the field are the basis for measuring and estimating the public opinion. The analysis and prediction of field soil moisture data can control appropriate irrigation of sprinkler irrigation equipment, thereby increasing the utilization rate of water resources and increasing the yield and income of crops. At present, with the development of soil moisture sensor technology, with the appearance of rapid measurement devices with GPS, the field public opinion can already be sampled by a large number of samples and complete spatial analysis on the GIS, in order to more accurately understand the distribution of field public opinion. Features provide the possibility. The soil moisture meter can be equipped with GPS positioning function to complete the determination of soil moisture better and provide a basis for agricultural production.
On the SPSS statistical software of soil moisture content measuring instrument, the volumetric water content data of 4 plots in Xuxinzhuang and the volumetric moisture content of 20cm below the surface of Xiaowangzhuang farm were taken for exploratory analysis of descriptive statistical analysis. The coefficient of variation of field plots ranged from 5.0% to 17.3%, indicating little variation. The full value of the quartiles is not large, indicating that the soil moisture content of each block is relatively concentrated. The corresponding histograms, skewness and kurtosis values ​​of each plot indicate that the volumetric water content of soil has a normal distribution trend.
The purpose of the soil moisture measuring instrument for the analysis of the public opinion trend is to reveal whether there is a relationship between the soil moisture content and the location. If there is a trend of change, the soil moisture content is also affected by the spatial position while the space conforms to a certain parameter distribution. The trend surface analysis method is: According to the spatial sampling data, fitting a mathematical surface, using the surface to reflect the spatial distribution changes. Mathematically, the mathematical model of trend surface analysis is the surface fitting problem. Polynomial functions are generally used as mathematical expressions, and surfaces represented by polynomials are fitted to data points according to the principle of least squares.
According to the statistical test of the soil moisture content data by the soil moisture meter, the distribution of soil moisture in the field is lognormally distributed, there is no obvious spatial trend, and the autocorrelation and anisotropy of the soil moisture in the field are displayed and confirmed by GIS. The resulting autocorrelation distance is 1.2m. These preliminary conclusions are the basis for carrying out public opinion forecasting on GIS.
On the SPSS statistical software of soil moisture content measuring instrument, the volumetric water content data of 4 plots in Xuxinzhuang and the volumetric moisture content of 20cm below the surface of Xiaowangzhuang farm were taken for exploratory analysis of descriptive statistical analysis. The coefficient of variation of field plots ranged from 5.0% to 17.3%, indicating little variation. The full value of the quartiles is not large, indicating that the soil moisture content of each block is relatively concentrated. The corresponding histograms, skewness and kurtosis values ​​of each plot indicate that the volumetric water content of soil has a normal distribution trend.
The purpose of the soil moisture measuring instrument for the analysis of the public opinion trend is to reveal whether there is a relationship between the soil moisture content and the location. If there is a trend of change, the soil moisture content is also affected by the spatial position while the space conforms to a certain parameter distribution. The trend surface analysis method is: According to the spatial sampling data, fitting a mathematical surface, using the surface to reflect the spatial distribution changes. Mathematically, the mathematical model of trend surface analysis is the surface fitting problem. Polynomial functions are generally used as mathematical expressions, and surfaces represented by polynomials are fitted to data points according to the principle of least squares.
According to the statistical test of the soil moisture content data by the soil moisture meter, the distribution of soil moisture in the field is lognormally distributed, there is no obvious spatial trend, and the autocorrelation and anisotropy of the soil moisture in the field are displayed and confirmed by GIS. The resulting autocorrelation distance is 1.2m. These preliminary conclusions are the basis for carrying out public opinion forecasting on GIS.
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