Innovations in Remote Sensing Techniques for Monitoring Agricultural Crops and Environmental Stress Conditions: A Review

Abstract

Latest remote sensing techniques developed for monitoring agricultural crops and environmental stress conditions. Remote sensing technologies have become essential tools for monitoring agricultural crops and detecting environmental stress conditions. Recent innovations, including hyperspectral imaging, thermal sensing, microwave systems, and data fusion techniques, have significantly improved the accuracy of detecting crop health, soil moisture, nutrient deficiencies, drought, heat stress, soil degradation, and water resource availability. CubeSats and UAVs improve spatial and temporal resolution for real-time agricultural monitoring. Integrating deep learning and artificial intelligence has further advanced predictive modelling capabilities, enhancing crop yield estimation and stress detection accuracy. Despite these advancements, various challenges persist, including data quality issues, sensor calibration errors, atmospheric interference, high computational requirements, and limited accessibility for small-scale farmers. Economic barriers and ethical concerns related to data security, ownership, and privacy also hinder the widespread adoption of remote sensing technologies. Addressing these challenges requires developing cost-effective sensors, improving data fusion techniques, optimizing AI-driven models, and promoting inclusive access to advanced technologies. Future research should focus on enhancing multi-source data integration, establishing standardized protocols for ethical data management, and improving predictive models for better agricultural decision-making. Incorporating cloud computing and high-performance data analytics will also play a critical role in making remote sensing applications more efficient and accessible. Recent innovations in remote sensing technologies and their applications in agricultural monitoring while identifying existing limitations and providing recommendations for future research. Effective utilization of these technologies can significantly enhance crop monitoring, environmental stress assessment, and precision agriculture practices, contributing to improved food security and sustainable resource management.