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. [1] BCAM{Basque Center for Applied Mathematics
• Localización: Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain / Itziar Irigoien Garbizu (ed. lit.), Dae-Jin Lee (ed. lit.), Joaquín Martínez Minaya (ed. lit.), María Xosé Rodríguez Álvarez (ed. lit.), 2020, ISBN 978-84-1319-267-3, págs. 418-421
• Idioma: inglés
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• 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.