Application of Gustafson-Kessel-like clustering algorithm in Delineation of management Zones in precision Agriculture

摘要

The main objective of the paper entitled' Application of Gustafson-Kessel-like clustering algorithm in delineation of management zones in precision agriculture' is to create clusters of agricultural field using GK clustering algorithms methodologies.Precision Agriculture is related to the application of current technology in the agricultural domain. Huge datasets are now days collected during standard farming operation. These data are fine-scale and available in high resolution, usually reflecting the heterogeneity of any natural field. The data may result from a Multitude of sensors and electronic equipment and can be used for several purposes which affect the efficiency and effectiveness in farming operations.Base fertilization is a crucial job in traditional agriculture. This phrase is generally employed to explain the procedure related to the extant potassium (K), phosphor (p) and magnesium (Mg) that the planted crops can use. Since generally the field is mixed, the issue is which portion of the field needs to be treated and in what manner the treatment needs to be undertaken. This is also generally linked with the subject of the management zone delineation. There have been several functions that have employed fine-scale data for sub-segregating the field into smaller areas. These methods generally need multi-year data sets and depend on low resolution sampling techniques to segregate the field into equal portions. Majority of the extant studies employ only portions of the extant data for the clustering technique. In the present study,the researchers recommend a new methodology which deals with the above problems. The approach uses GK clustering methodologies to create clusters of agricultural fields.Indian agriculture can be considered as the back bone of our economy. Many studies and developments are being done in the field of agriculture. Indian crop fields are much diversified in terms of soil, climate and other agricultural resources. Managementzones of agricultural planes have an important role in the cultivation of the yield. Proper delineation of Management zones help in the productivity of the yield. Base paper studies the delineation of management zones on basis of k means clustering on soil map. As k means algorithm is the basic clustering algorithm, it has some limitations over processing. So planned to work on GK clustering algorithms which is faster in computation than K means. Implemented both the algorithms on the same dataset of NPK of the soil and compared to base paper, GK clustering algorithm has some more performance criteria.