Big Data Analysis on Geographical Segmentations and Resource Constrained Scheduling of Production of Agricultural Commodities for Better Yield

• Published in: Procedia computer science 2016, Vol.87, p.80-85
• Main Authors: Senthilvadivu, S., Kiran, S. Vinu, Devi, S. Prasanna, Manivannan, S.
• Format: Article
• Language: English
• ISSN: 1877-0509; 1877-0509
• DOI: 10.1016/j.procs.2016.05.130

Agricultural geography is one of the subportion of human and our economic geography which examines the primary, secondary, tertiary and quaternary yield types activities that are carried out in agriculture. In this paper, we are examining the spatial distribution and concentration of crops and their yields along with their crop periods using Big data Analytics to find out the cropping patterns and combinations that varies in space and time. Our primary objective is to findout the crop associations and patterns under climatic influence for each geographical segmentation, to give better yeilds. The Big data analytic based association won’t to last as many of the farmers and scientists are rightly challenging over the agricultural sustainability. However, there is a strong possibility of the farmers to adopt a new combination in the coming decades as the Big data analytic based crop pattern decision facilitates the farmers, always try to optimize their agricultural re-turns and adopt new innovations which gives better yeilds since we are performing factual data centric analytics.