Using Random Forest to Improve the Downscaling of Global Livestock Census Data
Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the livestock sector. This has been the major motivation behind the development of the Gridded Livestock of the W...
| Autores principales: | , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Public Library of Science
2016
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/129347 |
Ejemplares similares: Using Random Forest to Improve the Downscaling of Global Livestock Census Data
- Downscaling livestock census data using multivariate predictive models: Sensitivity to modifiable areal unit problem
- Ruminant livestock [in Atlas of African agriculture research and development]
- The global livestock sector: Trends and health implications
- Generating characteristic daily weather data using downscaled climate model data from the IPCC's fourth assessment
- Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions
- Spatial random downscaling of rainfall signals in Andean heterogeneous terrain