RT Dissertation/Thesis
T1 Modelling of the topsoil organic carbon content by analysing the potential of spectroscopic techniques for digital soil mapping
A1 Rial Tubío, Marcela
K1 Spatial statistics
K1 Soil spectroscopy
K1 Soil organic carbon
K1 Machine learning
AB Soil organic carbon represents the largest terrestrial carbon pool, being one of the most relevant components in the carbon cycle budget and climate change feedbacks. The scientific community and policymakers expressed the need for spatially information about its distribution. This work aims to develop statistical methods to quantify topsoil organic carbon by using spectroscopic data as a tool for digital soil mapping. Firstly, it was explored the capacity of spectroscopy for map soil organic carbon content at regional scale using topsoil samples from Galicia (NW-Spain). Next, it was developed a spatially non-stationary approach that allows mapping soil organic carbon content and also identifying the factors more relevant for its accumulation in Europe. Finally, it was evaluated the capacity of digital soil mapping methods for monitoring the soil organic carbon stocks expected under different climate change scenarios using for such purpose legacy data from Santa Cruz Island (Galapagos).
YR 2017
FD 2017
LK http://hdl.handle.net/10347/16135
UL http://hdl.handle.net/10347/16135
LA eng
DS Minerva
RD 26 abr 2026