Earth Precision Agriculture
Join us at the Agricultural Remote Sensing Conference to discover innovative solutions in the field.
Agricultural Remote Sensing Conference Track
About the Remote Sensing for Agriculture Conference Track
The Agricultural Remote Sensing Conference track at the Earth Precision Agriculture Conference brings together global researchers, industry leaders, and practitioners to explore how satellite, UAV, and AI-driven Earth observation technologies are transforming sustainable agriculture, food security, and environmental stewardship.
The evolution of remote sensing technologies and platforms is transforming agriculture, offering unprecedented capabilities to monitor and manage agricultural systems with precision and scale. The Agricultural Remote Sensing Conference track explores cutting-edge technologies expanding the frontiers of agricultural remote sensing, from data acquisition strategies to innovative platforms that enhance data availability and accessibility. This track aims to foster a deeper understanding of the state-of-the-art and to chart a course for future innovations.
We convene researchers and practitioners working across the full spectrum of remote sensing technologies to share breakthroughs and discuss challenges in their application to sustainable agriculture. The track emphasizes the synergistic use of multi-modal data, edge AI, and the development of integrated systems that provide holistic and actionable insights for farmers, researchers, and policymakers. We invite submissions with focus on remote sensing in agriculture that explore research, including but not limited to:
AI-Driven Data Analytics
- AI for Remote Sensing Data Analysis: Application of machine learning and deep learning models for advanced analysis of remote sensing data, including automated feature extraction, time-series forecasting, and the development of predictive models for crop yield and disease risk.
- Large-Scale Soil Moisture Monitoring: Application of passive microwave sensors (e.g., SMAP, SMOS) for regional soil moisture mapping and drought monitoring at coarse spatial resolutions. We specifically encourage submissions on spatial downscaling algorithms that leverage high-resolution optical or SAR data to bridge the gap between coarse satellite footprints and actionable, field-level agricultural applications.
- Salinity and Freeze/Thaw State: Research on the use of passive microwave data for assessing soil salinity and monitoring the freeze/thaw state of soils in cold-region agriculture.
Optical and Fluorescence Remote Sensing Systems
- Hyperspectral and Multispectral Imaging: Advancements in sensor technology, data processing algorithms, and applications for detailed crop analysis, including the detection of subtle stress indicators, retrieval of biochemical parameters (e.g., chlorophyll, nitrogen), and differentiation of crop species.
- Thermal Infrared (TIR) Imaging: Research on the use of TIR sensors for crop water stress monitoring, evapotranspiration modeling, irrigation scheduling, and the detection of canopy temperature anomalies related to disease or other stressors.
- Solar-Induced Chlorophyll Fluorescence (SIF): Research on the remote sensing of SIF as a direct proxy for plant photosynthesis and productivity, including retrieval algorithms, its relationship with gross primary production (GPP), and its application in yield forecasting.
Active Microwave Remote Sensing (SAR)
- SAR for Crop and Soil Monitoring: Applications of Synthetic Aperture Radar (SAR) for crop classification, above-ground biomass estimation, growth stage monitoring, and the retrieval of soil moisture information using data from platforms like Sentinel-1, RADARSAT, and ALOS PALSAR.
- Advanced SAR Techniques: Use of Interferometric SAR (InSAR) for monitoring surface deformation related to irrigation and groundwater extraction, and the application of Polarimetric SAR (PolSAR) for detailed crop structure analysis and classification.
LiDAR (Light Detection and Ranging)
- Airborne and UAV-based LiDAR: Application of airborne and UAV-based LiDAR for high-resolution 3D mapping of crop height, canopy density, leaf area index (LAI), and the characterization of tree structure in orchards and plantations.
- Terrestrial LiDAR: Use of ground-based LiDAR for detailed plant phenotyping, individual plant structure analysis, and the validation of airborne and satellite-based remote sensing products.
Positioning and Navigation Technologies
- High-Precision GNSS: Research on the use of RTK (Real-Time Kinematic) and PPP (Precise Point Positioning) for centimeter-level accuracy in field operations, including auto-steering, variable rate application, and yield mapping.
- GNSS-Reflectometry: Emerging applications of GNSS signals for soil moisture and vegetation sensing.
Emerging Platforms and Constellations
- UAV/Drone Platforms: Development of novel UAV-based sensing systems, on-board data processing, and their integration into farm management workflows for on-demand, high-resolution data acquisition.
- Satellite Constellations and CubeSats: Use of high-revisit satellite constellations (e.g., PlanetScope) for daily crop monitoring, phenology tracking, and near-real-time change detection.
Prof. Yuxin Miao
Director
Precision Agriculture Center
Department of Soil, Water, and Climate
University of Minnesota
Dr. Jing Zhou
Assistant Professor
Department of Crop and Soil Science
Oregon State University
Prof. Ittai Herrmann
The Institute of Plant Sciences and Genetics in Agriculture
The Faculty of Agriculture, Food and Environment
The Hebrew University of Jerusalem
Dr. Mahendra Bhandari
Assistant Professor in Digital Agriculture
AgriLife Research and Extension Center
Texas A&M University
Dr. Keshav D. Singh
Research Scientist
Remote Sensing, Digital Phenomics and Smart Farming
Agriculture and Agri-Food Canada (AAFC)
Dr. Siddhartho (Sidd) Paul
Assistant Professor of Geospatial Science
Department of Agronomy
College of Agriculture
Purdue University
Dr. Johnny (Liujun) Li
Director of Precision Agriculture and Intelligent Robotics Laboratory
Department of Soil and Water Systems
College of Agricultural and Life Sciences
University of Idaho
Dr. Farhad Maleki
Director
Centre for Precision Agriculture
University of Calgary