A comprehensive analysis of machine learning and remote sensing techniques in studying climate hazards-induced crop yield variations
| Main Authors: | , , , |
|---|---|
| Format: | Poster |
| Language: | Inglés |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/163479 |
Similar Items: A comprehensive analysis of machine learning and remote sensing techniques in studying climate hazards-induced crop yield variations
- A critical synthesis of remote sensing and machine learning approaches for climate hazard impact on crop yield
- Spatio-temporal patterns of dry and wet spells in Ghana's Savanna and Transitional Zones: a 40-year analysis
- Urban flash flood hazard mapping using machine learning, Bahir Dar, Ethiopia
- Remote sensing and machine learning for food crop production data in Africa post-COVID-19
- Machine Learning-Driven Remote Sensing Applications for Agriculture in India—A Systematic Review
- A scalable crop yield estimation framework based on remote sensing of solar-induced chlorophyll fluorescence (SIF)