Machine Learning-Driven Remote Sensing Applications for Agriculture in India—A Systematic Review
In India, agriculture serves as the backbone of the economy, and is a primary source of employment. Despite the setbacks caused by the COVID-19 pandemic, the agriculture and allied sectors in India exhibited resilience, registered a growth of 3.4% during 2020–2121, even as the overall economic growt...
| Autores principales: | , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
MDPI
2024
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/152182 |
Ejemplares similares: Machine Learning-Driven Remote Sensing Applications for Agriculture in India—A Systematic Review
- Mapping major land use types in Nandi County using remote sensing and machine learning
- Developing automated machine learning approach for fast and robust crop yield prediction using a fusion of remote sensing, soil, and weather dataset
- Remote sensing and machine learning integration to detect and forecast floods in Lodwar Town, Turkwel Basin, Kenya
- Watershed scale soil moisture estimation model using machine learning and remote sensing in a data-scarce context
- Predicting turbidity dynamics in small reservoirs in Central Kenya using remote sensing and machine learning
- Pixels to pasture: Using machine learning and multispectral remote sensing to predict biomass and nutrient quality in tropical grasslands