Study On Farmland Quality Evaluation Based On Incomplete Spatial Data Fusion

Cultivated land is an important resource for social sustainable development,which is related to the development of national economy and national food security.At present,less attention is paid to the processing of incomplete spatial data in the evaluation of cultivated land quality.As one of the main data in the evaluation of cultivated land quality,the study on the processing method of incomplete spatial data is of great significance for improving the data accuracy.Guiping is a county with a large population in guangxi,with more people and less land,and the contradiction between people and land is increasingly prominent.How to protect the balance between the quantity and quality of cultivated land under the severe situation is particularly important for carrying out the evaluation of cultivated land quality.Taking guiping as the research object,on the basis of the land change database,soil sampling data and statistical yearbook in 2015 as the main data,a total of11 index factors including natural factors and social factors were selected to form the cultivated land quality evaluation index system of guiping.The spatial interpolation method was used to preprocess the incomplete spatial data,and the combined weighting method was used to assign weights to the evaluation indexes.Finally,the weighted comprehensive index method was used to comprehensively evaluate the quality of cultivated land in guiping,and the main results were as follows:(1)from the two aspects of natural factors and social economic factors selected the landscape type,terrain slope,soil organic matter,soil texture,soil PH,top layer thickness,field shape index,irrigation,drainage condition,road access,center town and affect a total of 11 indicators,is established in guigang city of cultivated land quality evaluation index system.(2)the accuracy of several different spatial interpolation methods was verified.Finally,the Completely Regularized Spline(CRS)was found to have higher accuracy in predicting soil organic matter,soil texture and drainage conditions.Universal Kriging(UK)has a high prediction accuracy for soil PH value and surface layer thickness.The Local Polynomial Interpolation(LPI)is more accurate in predicting irrigation capacity.(3)evaluate the quality of cultivated land in guiping under natural factors,social factors and comprehensive factors,and get the following results.Under the natural factors,the quality of cultivated land was evaluated,among which the first-level land was 15098.06hm~2,accounting for 11.77%of the cultivated land area.The secondary land is 33911.04hm~2,accounting for 26.44%of the cultivated land area.The third-level land is 52390.72hm~2,accounting for 40.84%of the cultivated land area.The fourth-level is 26870.77hm~2,accounting for 20.95%of the cultivated land area.Under the social and economic factors,the quality of cultivated land was evaluated,among which the first-level land was 11194.98hm~2,accounting for8.74%of the cultivated land area.The secondary land area is 13894.75hm~2,accounting for 10.84%of the cultivated land area.The third-level land is62967.50hm~2,accounting for 49.13%of the cultivated land area.The fourth-level is 4,0101.66 hm~2,accounting for 31.29%of the cultivated land area.Comprehensive evaluation was conducted on the quality of cultivated land,of which the first-level land was 26200.06hm~2,accounting for 20.45%of the cultivated land area.Secondary land is 49417.10hm~2,accounting for 38.56%of the cultivated land area;The third-level land is 33749.48hm~2,accounting for 26.34%of the cultivated land area.The fourth-level is 18778.38hm~2,accounting for 14.65%of the cultivated land area.The result of grade division accords with the actual situation of guiping and puts forward some Suggestions to improve the quality of cultivated land.