Modelling agricultural drought: a review of latest advances in big data technologies
This article reviews the main recent applications of multi-sensor remote sensing and Artificial Intelligence techniques in multivariate modelling of agricultural drought. The study focused mainly on three fundamental aspects, namely descriptive modelling, predictive modelling, and spatial modelling...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Informa UK Limited
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/125344 |
Similar Items: Modelling agricultural drought: a review of latest advances in big data technologies
- Drought vulnerability of central Sahel agrosystems: a modelling-approach based on magnitudes of changes and machine learning techniques
- Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction
- Mining the gaps:using machine learning to map a million data points from agricultural research from the global south
- Ground reference dataset for crop type mapping and monitoring in four districts of Rwanda
- Hybrid-AI and Model Ensembling to Exploit UAV-Based RGB Imagery: An Evaluation of Sorghum Crop’s Nitrogen Content
- Foodgravity: understand food flows using classic gravity model and explainable artificial intelligence techniques