John Deere - Estimating Soil Moisture Using Geospatial and Weather Data
 Open for Registration
  • Lecture time: Thursday: 12:30:00 - 13:20:00 ET
  • Lab time: Tuesday: 11:30:00 - 13:20:00 ET
  • Domain: Digital Agriculture
  • Keywords: Agronomy, Data Visualization, Feature Extraction, Geospatial Analysis, Weather Data
  • Tools: Data Cleansing, Data Exploration, Geospatial Data Analysis, Machine Learning, Python
  • Citizenship: Open to all students
Summary

The objective of this project is to create a dataset of key variables impacting soil moisture such as geographic location, elevation, and weather data. This dataset will then be used to create visualizations and create a model estimating soil moisture for a given location.

Description

***Please see the PDF for a detailed project description. When registering for this project in UniTime, look for 'John Deere' in the Note section, and select the appropriate CRN.***

AY 2023 - 2024 Last updated: April 14, 2023, 8:22 a.m.