Publication | Closed Access
Management Zone Analyst (MZA)
265
Citations
24
References
2004
Year
Search OptimizationEngineeringSmart ManufacturingSoftware EngineeringManagement Zone AnalystMining MethodsDecision AnalyticsData ScienceData MiningManagementCultural PlanningSystems EngineeringManagement AnalysisFuzzy LogicSite‐specific Crop ManagementOperations ManagementManagement TechniqueCluster DevelopmentManagement AnalyticsClassificationFuzzy ClusteringManagement Zones
Producers using site‑specific crop management need quick, automated methods to delineate management zones within fields. Management Zone Analyst, built in Microsoft Visual Basic 6.0, applies fuzzy c‑means clustering to field data, computes descriptive statistics, and outputs performance indices (FPI and NCE) across a range of cluster numbers. In two Missouri claypan fields, MZA’s indices suggested dividing one field into two or four zones and the other into four zones, demonstrating its ability to guide zone selection.
Producers using site‐specific crop management (SSCM) have a need for strategies to delineate areas within fields to which management can be tailored. These areas are often referred to as management zones Quick and automated procedures are desirable for creating management zones and for testing the question of the number of zones to create. A software program called Management Zone Analyst (MZA) was developed using a fuzzy c ‐means unsupervised clustering algorithm that assigns field information into like classes, or potential management zones. An advantage of MZA over many other software programs is that it provides concurrent output for a range of cluster numbers so that the user can evaluate how many management zones should be used. Management Zone Analyst was developed using Microsoft Visual Basic 6.0 and operates on any computer with Microsoft Windows (95 or newer). Concepts and theory behind MZA are presented as are the sequential steps of the program. Management Zone Analyst calculates descriptive statistics, performs the unsupervised fuzzy classification procedure for a range of cluster numbers, and provides the user with two performance indices [fuzziness performance index (FPI) and normalized classification entropy (NCE)] to aid in deciding how many clusters are most appropriate for creating management zones. Example MZA output is provided for two Missouri claypan soil fields using soil electrical conductivity, slope, and elevation as clustering variables. Management Zone Analyst performance indices indicated that one field should be divided into either two (using NCE) or four (using FPI) management zones and the other field should be divided into four (using NCE or FPI) management zones.
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