Ai-enabled gis-powered plot segmentation for phenotyping
A cutting-edge solution utilizing AI and GIS for efficient plot segmentation in phenotyping. Leverages deep learning and alternative color spaces to enhance segmentation accuracy, reducing resource usage and improving data analysis.
Overview
This solution offers an innovative method for plot segmentation in high-throughput phenotyping by integrating AI and GIS technologies. The approach involves using drone-captured imagery and transforming it into alternative color spaces such as HSV, alongside vegetation indices like the excess green index (ExG), to enhance segmentation precision. By employing deep learning models like UNet, DeepLabv3+, and SegNet, this solution provides an efficient and accurate way to delineate plot boundaries, enabling better resource allocation and data collection.
Technical specifications
- One-time plot segmentation: Achieved through optimal timing of drone imagery capture, reducing repeated efforts.
- Enhanced color spaces and indices: Utilizes HSV and ExG to improve differentiation between plant areas and soil.
- Deep learning models: Customizes models like UNet, DeepLabv3+, and SegNet for precise boundary recognition and segmentation.
- GIS integration: Converts segmented plots into GIS shapefiles for spatial analysis and georeferences additional datasets for comprehensive trait extraction.
Technology readiness level
Currently at TRL 2, this technology is in the early stages of development with ongoing validation processes. The focus remains on optimizing imagery collection timing, model tuning, and performance evaluation to refine and advance the solution's capabilities.
About University of California, Davis
UC Davis is a comprehensive public research university in Northern California, combining a land-grant heritage with an integrated academic health system and a veterinary teaching hospital. Industry engages through co-located clinical and translational facilities in Sacramento, a campus-adjacent research park, pilot-scale food and bioprocessing facilities, and a statewide extension network for field-to-market deployment. Proximity to the Bay Area and California's Central Valley enables rapid collaboration with startups and established enterprises, while corporate relations staff streamline access to faculty, talent, and core labs. Research is supported by competitive federal funding from agencies such as NIH, NSF, USDA, and DOE. A dedicated technology transfer office and venture support programs provide IP management, licensing, and startup formation pathways for industry partnerships.
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