Management Zone Analyst (MZA)
By J. Fridgen, Newell R. Kitchen, Kenneth A. Sudduth, S. Drummond, W. Wiebold, C. Fraisse. Agronomy Journal, 2004
377 citations recorded by the source corpus.
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.
Subfields: Environmental Engineering, Management, Monitoring, Policy and Law, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/1f27bf9add2951998672bd3dfa5add1ca0e52d56
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In Environmental Engineering
- Francesca Guastaferro
- D. Sollitto
- Barbara Cafarelli
- Antonella Troccoli
- Daniela De Benedetto
- Annamaria Castrignanò
In Statistics and Probability
- Bruno Basso
- Francesca Guastaferro
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- Barbara Cafarelli
- P. Rubino
- Antonella Troccoli
- Daniela De Benedetto
- M. Diacono
Citations in the corpus
- Spatial and temporal variability of wheat grain yield and quality in a Mediterranean environment: A multivariate geostatistical approach (2012, background): “Within a management class, more or less uniform effects of eather, soil and farm management are expected on the crop Castrignanò et al., 2008; Fridgen et al., 2004; Lark, 1998).”
- A comparison of different algorithms for the delineation of management zones (2010, methodology): “2) indicate that grouping the data into two classes allowed both the FPI and NCE indices to be minimized, and the agreement between the indices indicates the goodness of classification (Fridgen et al. 2004) (Fig.”