High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional...

Descripción completa

Detalles Bibliográficos
Autores principales: Forkuor, Gerald, Hounkpatin, Ozias K. L., Welp, Gerhard, Thiel, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5256943/
https://www.ncbi.nlm.nih.gov/pubmed/28114334
http://dx.doi.org/10.1371/journal.pone.0170478

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5256943/
https://www.ncbi.nlm.nih.gov/pubmed/28114334
http://dx.doi.org/10.1371/journal.pone.0170478

Ejemplares similares