Texas A&M; AgriLife Research and Cropping Systems Program
Co-Principal Investigator
1 September 2015 – 31 August 2017
Total award $240,000
The overall goal of this project is to generate preliminary data necessary for effective utilization of UAS-based imaging techniques for crop production and weed management applications. UAS can be equipped to include multi-spectral sensors (3 to 4 bands in the visible and near-infrared/NIR range), hyperspectral sensors (Headwall’s Standard Micro-Hyperspec VNIR 380-1000 nm spectral range), thermal sensors and LIDAR (Light Detection And Ranging), among others. These sensors have a multitude of applications, in areas such as soil, crop, water and weed management in agriculture. However, interpretation of data collected using UAS-based remotely sensed images requires careful consideration of several factors. What is not known is the error estimates between UAS and ground-level data. Such knowledge is key to validate the utility of UAS-based data collection for various applications in agriculture. One of the major limitations so far is the labor-intensive ground data collection and biomass sampling, which will be addressed in this research. We believe that layering UAS data with field measurements would provide rigorous validation of UAS data and provide required knowledge base for widespread implementation of UAS-based data collection. The team will use the state-of-the-art manned/ unmanned ground platform (UGP) in collecting required ground-truthing information.
TECHNICAL OBJECTIVES
- Quantification of the growth and development of field crops as affected by soil, irrigation and crop management strategies
- Identification and differentiation of weed/plant species, patterns of infestation, and herbicide injury on crops
Working with me on this program are Research Assistants:
- James Henrickson, Ph.D student
- Cameron Rogers, Ph.D student
- Zeke Bowden, B.S. student