Integrating spatial heterogeneity to enhance spatial temporal crop yield predictions
Crop yield predictions and monitoring are important in understanding key challenges in crop production and management to ensure the effective utilization of resources to enhance food security. Over the years remote sensing data and machine learning models have been employed with the help of ground t...
| Main Author: | |
|---|---|
| Format: | Tesis |
| Language: | Inglés |
| Published: |
Universidade NOVA de Lisboa
2024
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/141816 |
Similar Items: Integrating spatial heterogeneity to enhance spatial temporal crop yield predictions
- Spatial and temporal changes of vegetable production in China
- Spatio-temporal dynamics of maize cropping system in Northeast China between 1980 and 2010 by using spatial production allocation model
- High spatial resolution seasonal crop yield forecasting for heterogeneous maize environments in Oromia, Ethiopia
- Spatial patterns of crop yields in Latin America and the Caribbean
- Integrated spatial modeling of fertilizer investment returns to guide strategic investments: Application of a spatial ex ante analytical framework to smallholder maize production in Nigeria
- Incidence, spatial pattern and temporal progress of Fusarium wilt of bananas