Visualization Variable Rate Fertilization Decision-making System Based On Spatial Fuzzy Clustering

Data mining and visualization technology generated a large number of spatial data has been further applications for spatial decision analysis which provides technical support. We are in the implementation of the national "863" project, "Corn Research and Application of Precision operating system" in the process, accumulate a large amount of agricultural production of spatial data, conventional statistical analysis methods are difficult to handle these massive data; to organize and manage these data therefore, we based on GIS technology, data mining and visualization techniques to analyze existing data, collated from the access to appropriate knowledge in order to better precision in maize production management and decision-making, research and innovation, including the main:1.Spatial fuzzy clustering algorithm based on established soil classification map. In this paper, combined with the grid-based density clustering algorithm to determine the soil sampling points in the dense coverage of the largest regional unit based on the detailed coverage of the smallest connected region; cluster analysis and the method of combining fuzzy logic, implementation of fuzzy clustering of soil nutrients; the use of the study area, spatial characteristics of soil nutrients, the use of fuzzy clustering algorithm, the fuzzy membership clustering analysis the relevant parameters of the process and results to be processed as a visualization objects, using color difference obvious color illustrations depicting the different soil fertility levels to achieve the application of space visualization of spatial fuzzy clustering soil classification map.2.The application of visualization technology, soil nutrient spatial information visualization. Visualization than the traditional two-dimensional spatial variation on the three-dimensional data of thematic maps that more natural, clearer and more intuitive. In this paper, python language, the introduction of three-dimensional visualization library VTK, three-dimensional Kriging interpolation method to realize three-dimensional spatial distribution of soil nutrients interact.3.Based on the visualization of spatial fuzzy clustering variable fertilization system design and implementation decisions. The use of artificial intelligence, data mining, spatial analysis and visualization technology, technology, design and implementation of fuzzy clustering based on the visualization of spatial variable rate fertilizer decision-making system. The system integrates fuzzy clustering based on spatial visualization assessment and classification of soil fertility levels, based on visualization of spatial distribution of soil nutrients in three-dimensional visualization, spatial analysis related to the results of the inquiry, corn precise five-fertilization and system maintenancefunctional modules. Through consultation of the system can be divided into management areas of farmland, corn maize precision variable fertilization decision support operations.