Advances in UAV-Based Remote Sensing for Climate-Smart Agriculture

Dear Colleagues,

Unmanned Aerial Vehicles (UAVs) bridge the gap between satellite-derived data (with its broad spatiotemporal coverage) and ground-based point-scale measurements, offering unprecedented resolution for monitoring agricultural systems. Climate-Smart Agriculture (CSA), first proposed in 2010 by the FAO, aims to sustainably boost agricultural productivity, enhance resilience to climate changes, and reduce greenhouse gas emissions. Over the last decade, CSA has emerged as a critical framework to address food security and environmental challenges. By integrating multi-scale observations from satellites, UAVs, proximal sensing, and ground-based systems with advanced data analytics (e.g., data assimilation, artificial intelligence, and big data architecture), crop-growth models, and high-performance computing, UAVs are uniquely positioned to accelerate CSA’s transformative goals. These technologies enable real-time monitoring, precision agricultural practices, and adaptive, data-driven decision-making, thus empowering stakeholders to optimize resource use and mitigate environmental impacts in a rapidly changing climate.

This Special Issue aims to gather cutting-edge advances of UAV research and development to directly support CSA. The scope of this Special Issue includes, but is not limited to, the following areas:

1. Crop breeding and phenotyping:

Advanced approaches that leverage UAV data (e.g., hyperspectral, multispectral and LiDAR sensors) for real-time monitoring of phenotypic traits (e.g., leaf chlorophyll/nitrogen content, plant height, phenology and biomass) in breeding trails, accelerating the development of climate-resilient crop varieties.

2. Precision agricultural managements:

Investigations into the use of UAVs for site-specific managements and early detection of climate-induced stress (e.g., drought, flooding, pests, and lodging). This includes enabling variable-rate applications of seeding, fertilizer and water, and adaptations strategies of cover cropping and tillage, reducing cost and waste while maintaining/maximizing yield.

3. Emissions and environment impact assessments:

Applications that integrate UAV with radiative transfer models, process-based models, and AI for mapping soil carbon, monitoring methane emissions, and quantifying carbon sequestration.

We welcome interdisciplinary submissions that combine remote sensing, agronomy, climate science, and data science to support CSA at different scales.

You may choose our Joint Special Issue in Remote Sensing.

Dr. Hongquan Wang
Dr. Liming He
Dr. Taifeng Dong
Guest Editors

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• unmanned aerial vehicles
• remote sensing
• climate-smart agriculture
• crop phenotyping
• precision agriculture