Climate-Resilient Agriculture and Environmental Foresight: Integrating Digital Technologies, Predictive Modeling, and Policy Innovation for Sustainable Food Systems

Abstract

Climate change poses an unprecedented threat to global food security, challenging the stability and productivity of agricultural
systems worldwide. As erratic rainfall, rising temperatures, and pest outbreaks intensify, conventional farming approaches are
proving inadequate to ensure resilience and sustainability. This review explores the emerging role of environmental foresight,
supported by digital agriculture, artificial intelligence (AI), and predictive modeling, in shaping climate-resilient farming
systems. It examines how data-driven foresight enables early warning systems, precision interventions, and adaptive
management strategies that strengthen the capacity of farmers and policymakers to anticipate risks rather than react to crises.
The integration of remote sensing, Internet of Things (IoT) devices, and AI-based analytics into agricultural decision-making
has revolutionized the monitoring of soil, water, and crop health at unprecedented spatial and temporal scales. Furthermore,
this review discusses policy and governance innovations necessary to operationalize foresight-based agriculture, emphasizing
participatory approaches that bridge science and local knowledge. The paper concludes by identifying the pathways toward a
digitally empowered, climate-smart agricultural future where technology, ecology, and foresight converge to ensure global
food security and sustainability.