Document Type
Poster
Publication Date
Summer 9-10-2024
Abstract
This research explores the application of geospatial techniques for global agricultural monitoring, integrating satellite imagery and soil data to assess crop health and soil conditions. Our approach provides actionable insights to improve agricultural productivity and sustainability, addressing food security challenges through advanced machine learning models.
Keywords
big data, geospatial, crop health, satellite imagery
Rights
© 2024 The Authors.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Department/Center
Materials Science & Engineering
Recommended Citation
Akanbi, Olatunde D.; Mandayam, Vibha S.; Barcelos, Erika I.; Nihar, Arafath; Wu, Yinghui; Yarus, Jeffrey; and French, Roger H., "Big Geospatiotemporal Data Approaches to Monitoring and Mitigating Environmental Impacts in Agriculture" (2024). Student Scholarship. 20.
https://commons.case.edu/studentworks/20
Included in
Data Science Commons, Engineering Commons, Soil Science Commons