11.04.2021 - 15.04.2021 – Orlando, Florida, USA Download iCal

Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VI

SPIE conference on Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping

The use of optics and photonics in agriculture is a rapidly emerging and promising area of study, given the potential impact these technologies offer for rapid crop improvement through breeding and genetics as well optimization of on-farm crop production. The field is in an exciting period of exploration and expansion, as the use of ground- and air-based sensor platforms now permits revolutionizing the measurement of plant traits by adding great detail, high throughput, and concomitantly large data volumes. This conference brings together researchers and practitioners in this field to discuss the latest technologies, methods and findings.

Proximal and remote sensing systems including point and array detectors and automated ground-based and aerial vehicles applied to agriculture and high-throughput phenotyping are within the scope of this conference. Both active and passive sensing methods as well as sensors based on material reflectance and transmission and such physical phenomena as fluorescence and Raman scattering are pertinent to this conference. Optical sensing extending from the UV through the IR where thermal imaging becomes an important methodology is yet another area of active research of interest.

This conference will place emphasis on the use of unmanned aerial vehicles (UAVs) and ground-based robotic platforms equipped with various sensing technologies for the purpose of plant and crop phenotyping studies as applied to improving crop characteristics including yield, drought tolerance, stress detection, etc.. Contributions are sought on sensing technologies; sensor platforms; and data collection, analysis and visualization schemes.

Contributions are welcome which contain results from field studies on topics such as, but not limited to:
• UAVs for remote sensing in agriculture, including autonomous control
issues, imaging workflow issues, and imaging software issues
• Ground-based robots for phenotyping
• Hyperspectral imaging
• Multispectral imaging
• Lidar
• Thermal-infrared cameras
• Fluorescence cameras
• Mobile Raman spectrometers
• Image analysis, data management and data visualization
• Theoretical and empirical estimation techniques including machine


Conference website & abstract submission

Call (PDF)