Combining geomorphometry, feature extraction techniques and Earth-surface processes research: The way forward

In recent years, the wealth of technological development revolutionised our ability to collect data in geosciences. Due to the unprecedented level of detail of these datasets, geomorphologists are facing new challenges, giving more in-depth answers to a broad(er) range of fundamental questions across the full spectrum of the Earth's (and Planetary) processes. This contribution builds on the existing literature of geomorphometry (the science of quantitative land-surface analysis) and feature extraction (translate land surface parameters into extents of geomorphological elements). It provides evidence of critical themes as well as emerging fields of future research in the digital realm, supporting the likely effectiveness of geomorphometry and feature extractions as they are advancing the theoretical, empirical and applied dimension of geomorphology. The review further discusses the role of geomorphometric legacies, and scientific reproducibility, and how they can be implemented, in the hope that this will facilitate action towards improving the transparency, and efficiency of scientific research, and accelerate discoveries in geomorphology. In the current landscape, substantial changes in landforms, ecosystems, land use, hydrological routing, and direct anthropogenic modifications impact systems across the full spectrum of geomorphological processes. Although uncertainties in the precise nature and likelihood of changes exist, geomorphometry and feature extraction can aid exploring process regimes and landscape responses. Taken together, they can revolutionise geomorphology by opening the doors to improved investigations crossing space and time scales, blurring the boundaries between traditional approaches and computer modelling, and facilitating cross-disciplinary research. Ultimately, the exploitation of the available wealth of digital information can help to translate our understanding of geomorphic processes, which is often based on observations of past or current conditions, into the rapidly changing future. (C) 2020 Elsevier B.V. All rights reserved.