Apply the soil nutrient prediction model based on topographic factors, use the soil nutrient tester to predict the spatial distribution of organic matter content, alkali-hydrolyzable nitrogen content, available phosphorus content and available potassium content, and adopt the lognormal Kriging method for interpolation mapping. . It can be seen that the distribution laws of soil organic matter content and alkali-hydrolysable nitrogen content are similar, and the distribution pattern is more obvious. High-value areas are mainly distributed in the valleys, low-value areas are mainly distributed on ridges, and the slopes between ridges and valleys are Transition zone. The accuracy of soil nutrient prediction model based on topographic factors is high, and it can well predict the distribution of soil nutrients.
The accuracy comparison between the soil nutrient prediction model based on topographic factors and the soil nutrient prediction model based on the combination of topographic factors and land use methods shows that adding the land use type to the forecasting variables does not improve the prediction accuracy of the model, and only using terrain factors to predict soil nutrients The spatial distribution is more convenient, so the model is chosen to predict the validation set data.
Through the above numerical model of soil nutrient tester, the average absolute error of soil nutrient prediction models combined with land-use types is slightly lower than that based on topographic factors, and the root mean square error (RMSE) also has the same trend. . It shows that increasing the type of land use in predicting variables has no obvious effect on improving the accuracy of spatial distribution of soil organic matter, alkali-hydrolysis nitrogen and available phosphorus content.
The soil nutrient tester compared the correlations between soil organic matter, alkali-hydrolyzable nitrogen, available phosphorus and available potassium and topographic factors in the study area. The topography of the study area had a significant effect on the spatial distribution of organic matter and alkali-hydrolyzable nitrogen content. The effect of phosphorus content and available potassium content is relatively weak. Through comparing the mean values ​​of organic matter, dissolved nitrogen, available phosphorus, and available potassium in paddy fields and dry lands, it was found that land use patterns have significant effects on the spatial variability of organic matter, dissolved nitrogen, and available phosphorus, but they have no effect on available potassium contents. obvious.
The accuracy comparison between the soil nutrient prediction model based on topographic factors and the soil nutrient prediction model based on the combination of topographic factors and land use methods shows that adding the land use type to the forecasting variables does not improve the prediction accuracy of the model, and only using terrain factors to predict soil nutrients The spatial distribution is more convenient, so the model is chosen to predict the validation set data.
Through the above numerical model of soil nutrient tester, the average absolute error of soil nutrient prediction models combined with land-use types is slightly lower than that based on topographic factors, and the root mean square error (RMSE) also has the same trend. . It shows that increasing the type of land use in predicting variables has no obvious effect on improving the accuracy of spatial distribution of soil organic matter, alkali-hydrolysis nitrogen and available phosphorus content.
The soil nutrient tester compared the correlations between soil organic matter, alkali-hydrolyzable nitrogen, available phosphorus and available potassium and topographic factors in the study area. The topography of the study area had a significant effect on the spatial distribution of organic matter and alkali-hydrolyzable nitrogen content. The effect of phosphorus content and available potassium content is relatively weak. Through comparing the mean values ​​of organic matter, dissolved nitrogen, available phosphorus, and available potassium in paddy fields and dry lands, it was found that land use patterns have significant effects on the spatial variability of organic matter, dissolved nitrogen, and available phosphorus, but they have no effect on available potassium contents. obvious.
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