Statistical and Remote Sensing Tools in Soil Modelling and Monitoring

Dear Colleagues,

This special issue welcomes contributions that focus on the application of geostatistical and other mathematical tools as matching learning and neuronal networks to describe and predict spatial variation and perform spatial interpolation of soil data. Special attention will be paid to novel technologies to measure soil properties, such as spectroscopy and proximal and remote sensing systems to map and monitor the soil and  GIS and LiDAR technology to include digital elevation models in soil modelling.

The following are examples of suitable topics: soil data modelling, soil GIS for the computation of algebraic functions using the (semi) variogram to quantify the spatial variation of a regionalized variable, digital soil mapping, application of soil information in specific sectors (e.g. agriculture, natural resource management, soil degradation,  climate change mitigation, frozen soil monitoring (permafrost) or archaeology exploration)

Manuscripts may consider the collection of baseline soil data or more advanced models of soil properties.

Prof. Dr. Susana del Carmen Fernández Menedez
Prof. Celestino Ordóñez Galán
Dr. Javier Fernández Calleja
Guest Editors

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