Statistical and Remote Sensing Tool in Soil Modelling and Monitoring

Dear Colleagues,

This Special Issue welcomes contributions that focus on the application of geostatistical and other mathematical tools such 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 for measuring 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 modeling.

The following are examples of suitable topics: soil data modeling, soil GIS for the computation of algebraic functions using (semi)variograms 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.

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

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