-
. Research Project: Joining a team of landscape and fire ecologists to learn about and support geospatial analysis of fire mitigation implementation in the highly fire prone lands of Kona and Kohala on Hawaii
-
information from a wide variety of sources to conduct epidemiological, ecological, economic, geospatial, and environmental analyses and other assessments of present, future, and emerging threats to animal
-
with deep learning models such as autoencoders and neural networks. Experience with ecological, geospatial, or movement data (e.g., GPS telemetry). Strong oral and written communication skills, including
-
phenotyping using both drone-based and ground based sensing platforms. Learn artificial intelligence and machine learning techniques to analyze image and geospatial data from diverse sources for crop monitoring
-
farming resulting in more nutrient-dense animal sourced protein products. Learning Objectives: The fellow will gain experience in planning and conducting data collection, remote sensing, geospatial modeling
-
analysis of large, diverse datasets including field experimental data, geospatial data, and time series data. Experience with machine learning and statistical learning. Familiarity with various management
-
imagery collected via UAV, integrating cutting-edge technology into agricultural research. Utilize geospatial and statistical tools to conduct analyses that quantify the relationship between ET, canopy