AUTHOR=Delgado Jorge A. , Short Nicholas M. , Roberts Daniel P. , Vandenberg Bruce TITLE=Big Data Analysis for Sustainable Agriculture on a Geospatial Cloud Framework JOURNAL=Frontiers in Sustainable Food Systems VOLUME=3 YEAR=2019 URL=https://www.frontiersin.org/journals/sustainable-food-systems/articles/10.3389/fsufs.2019.00054 DOI=10.3389/fsufs.2019.00054 ISSN=2571-581X ABSTRACT=

Humanity is confronted with the grand challenge of how to increase agricultural production to achieve food security during the 21st century and feed a population that is expected to grow to 10 billion people. This needs to be done while maintaining sustainable agricultural systems and simultaneously facing challenges such as a changing climate, depletion of water resources, and the potential for increased erosion and loss of productivity due to the occurrence of extreme weather events. Precision Agriculture emerged out of the advances in the 1980s because of the development of several key technologies like GPS and satellite imagery. This paper argues that with the increasing impact of climate change, the next revolution in precision agriculture and agriculture in general will be driven by Sustainable Precision Agriculture and Environment (SPAE, similar to the 7 Rs), which could leverage past technologies combined with Big Data analysis. This new, technology-focused SPAE transitions from a site-specific management focus to the notion of global sustainability. To accomplish this transition, we introduced the WebGIS framework as an organizing principle that connects local, site-specific data generators called smart farms to a regional and global view of agriculture that can support both the agricultural industry and policymakers in government. This will help integrate databases located in networks of networks into a system of systems to achieve the needed SPAE management and connect field, watershed, national, and worldwide sustainability. Automation and the use of artificial intelligence (AI), internet of things (IoT), drones, robots, and Big Data serve as a basis for a global “Digital Twin,” which will contribute to the development of site-specific conservation and management practices that will increase incomes and global sustainability of agricultural systems.