Big GIS analytics framework for agriculture supply chains: A literature review identifying the current trends and future perspectives

Rohit Sharma, Sachin S. Kamble, Angappa Gunasekaran

Research output: Contribution to journalReview articlepeer-review

39 Scopus citations

Abstract

The world population is estimated to reach nine billion by 2050. Many challenges are adding pressure on the current agriculture supply chains that include shrinking land sizes, ever increasing demand for natural resources and environmental issues. The agriculture systems need a major transformation from the traditional practices to precision agriculture or smart farming practices to overcome these challenges. Geographic information system (GIS) is one such technology that pushes the current methods to precision agriculture. In this paper, we present a systematic literature review (SLR) of 120 research papers on various applications of big GIS analytics (BGA) in agriculture. The selected papers are classified into two broad categories; the level of analytics and GIS applications in agriculture. The GIS applications viz., land suitability, site search and selection, resource allocation, impact assessment, land allocation, and knowledge-based systems are considered in this study. The outcome of this study is a proposed BGA framework for agriculture supply chain. This framework identifies big data analytics to play a significant role in improving the quality of GIS application in agriculture and provides the researchers, practitioners, and policymakers with guidelines on the successful management of big GIS data for improved agricultural productivity.

Original languageEnglish (US)
Pages (from-to)103-120
Number of pages18
JournalComputers and Electronics in Agriculture
Volume155
DOIs
StatePublished - Dec 2018

All Science Journal Classification (ASJC) codes

  • Forestry
  • Agronomy and Crop Science
  • Computer Science Applications
  • Horticulture

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