Remote sensing-based rice stress and health assessment: current and future perspectives

Abstract

Rice production and rice crop health underpin food security, yet monitoring stresses across diverse environments remains challenging. Remote sensing offers scalable solutions, but existing studies are fragmented across platforms, sensors, diverse rice growing environments, and stress types. This lack of synthesis limits the ability to scale remote sensing approaches for rice stress assessment and to inform policy and management decisions. This review synthesizes 373 studies published between 1987 and 2025, examines stressors, geographic coverage, remote sensing platforms, data sources, and analytical methods, consolidates these advances, and identifies gaps for operational monitoring. Our findings show that rice disease and pest dominate existing research among the reviewed 13 stress types, while abiotic stresses such as drought, flood, and heavy metal stress also received considerable attention. Most studies focused on a single stress type, rather than multi-stress interaction. Hyperspectral data are widely used on ground-based platforms, but rarely on airborne or spaceborne platforms. We outline three priorities for future work: i) expanding studies in underrepresented regions, where rice production is increasing, such as Africa; ii) integrating multi-source and multi-platform remote sensing data; iii) and improving data collection and sharing networks to support operational stress detection. These insights aim to guide research towards more comprehensive and policy-relevant monitoring strategies.