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Digital Soil Spectroscopy

Digital Soil Spectroscopy Abstract Digital spectroscopy is transforming the way we characterise soils. Spectroscopy from numerous electromagnetic ranges produce various types of digital spectra, which can provide soil information. This presentation will look into mathematical and statistical techniques to extract information from the spectra to predict soil information. We will discuss techniques from machine learning (large p, small n) to deep learning models (large p, large n) and the challenges and opportunities in analysing spectra data from the lab to the field. Bio Budiman Minasny is a professor in soil-landscape modelling at the University of Sydney. He is a soil scientist, previously awarded the QEII and the Future Fellowships from the Australian Research Council. He is recognised as a Highly Cited Researcher in 2021 by the Web of Science. He is passionate about the role of soil in managing climate change, food, water, energy security, and maintaining biodiversity. Along with colleagues from Sydney University, Budiman authored the book "Soil Spectral Inference with R" (Springer 2021).