THERMAL IMAGING FOR CANOPY TEMPERATURE MONITORING AND SMART IRRIGATION IN PRECISION AGRICULTURE: A SYSTEMATIC REVIEW WITH BIBLIOMETRIC ANALYSIS

Abstract

Increasing water scarcity and the growing demand for sustainable agricultural production have accelerated the adoption of precision irrigation technologies. Thermal imaging has emerged as a non-destructive and efficient approach for monitoring canopy temperature and assessing crop water status, thereby supporting irrigation scheduling and water-use efficiency. This study systematically reviews and bibliometrically analyses the evolution of thermal imaging for canopy temperature monitoring and smart irrigation in precision agriculture. A comprehensive literature search was conducted using the Scopus database following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. After applying predefined inclusion and exclusion criteria, 115 peer-reviewed publications published between 2005 and 2025 were selected for analysis. Bibliometric mapping was performed using VOSviewer to evaluate publication trends, author collaborations, keyword co-occurrence, bibliographic coupling, and co-citation networks. The findings reveal a clear technological transition from handheld infrared thermometers to unmanned aerial vehicle (UAV)-based thermal imaging integrated with multispectral, hyperspectral, LiDAR, and soil moisture sensing technologies. The Crop Water Stress Index (CWSI) remains the most widely adopted indicator for crop water stress assessment, while machine learning and deep learning techniques have significantly improved the accuracy of irrigation decision support. Bibliometric analysis identified canopy temperature, UAVs, remote sensing, thermal imaging, and precision irrigation as the dominant research themes, with China and Spain emerging as leading contributors to the field. Despite substantial technological progress, challenges remain in sensor calibration, model transferability, protocol standardization, economic feasibility, and integration with automated irrigation systems. Emerging research opportunities include explainable artificial intelligence, standardized thermal imaging protocols, multi-environment validation, and real-time closed-loop irrigation systems to facilitate the large-scale adoption of thermal imaging for sustainable water management in precision agriculture.