Spatial bayesian geo-additive modelling and prediction soil texture mapping in the Basque Country
- Miguel Rua del Barrio 1
- Joaquín Martínez Minaya
- Lore Zumeta Olaskoaga
- Ainara Artetxe Aranaz
- Nahia Gartzia Bengoetxea
- Ander Arias González
- Dae-Jin Lee
- 1 BCAM{Basque Center for Applied Mathematics
- Itziar Irigoien (ed. lit.)
- Dae-Jin Lee (ed. lit.)
- Joaquín Martínez-Minaya (ed. lit.)
- María Xosé Rodríguez- Álvarez (ed. lit.)
Editorial: Servicio Editorial = Argitalpen Zerbitzua ; Universidad del País Vasco = Euskal Herriko Unibertsitatea
ISBN: 978-84-1319-267-3
Año de publicación: 2020
Páginas: 418-421
Congreso: International Workshop on Statistical Modelling (35. 2020. Bilbao)
Tipo: Aportación congreso
Resumen
High-resolution soil maps are important for land use planning, agriculture crop production, forest management, hydrological analysis and environmental protection. In this work, we consider the analysis of soil texture samples in the Basque Country (i.e. the relative proportions of sand, silt, or clay in soil) and use covariate information to predict a high-resolution soil map. We propose the use of geo-additive models for modelling and predicting the spatial distribution of soil texture in a Bayesian framework for compositional data.