Abstract Scroll bars are curvilinear ridges of sediment deposited as meandering channels migrate laterally. It is unclear exactly which variables control the spacing, height, and curvature of scroll ridges, and in turn how these properties record channel migration histories. This study tests the relationship between channel and scroll bar geometries in river systems with laterally migrating chute channels that deposit their own scroll packages. LiDAR- and Shuttle Radar Topography Mission-derived digital elevation models (DEMs) are used to calculate the spacing, relief, wavelength, and curvature of scroll bars in eight different chute-channel-dominated river systems with a range of channel dimensions, slopes, and water and sediment discharge regimes. Seven of the eight rivers have statistically indistinguishable chute channel (CC) and main channel (MC) scroll spacings, even though the chute channels have smaller channel dimensions. Additionally, there is no correlation between scroll spacing and relief for main or chute channels. For LiDAR-derived DEMs, the ratio between median scroll spacing and median channel width is low and falls within a narrow range for MC scrolls (from 0.13 to 0.22; mean 0.16), but is higher with a wider range for CC scrolls (from 0.48 to 1.33; mean 0.8). CC scrolls are straighter overall than MC scrolls, but there is no correlation between curvature and scroll spacing. Overall, these results show that (1) chute channel scrolls are often indistinguishable from main channel scrolls based on spacing and relief, and (2) MC and CC scrolls have different relationships with formative channel widths, which suggests that other variables, such as lateral migration rate and flood inundation depth, are key controls on scroll bar geometries.

Abstract The record of igneous activity (magmatism and volcanism) can significantly affect natural resource exploration and exploitation, including the search for hydrocarbons, critical minerals, natural hydrogen and geothermal energy sources, as well as using mafic igneous rocks as storage sites for CO 2 . These effects will vary depending on the nature and timing of the activity, the structural framework and the crustal architecture of the affected country-rock. To understand these effects and the interplay with other factors, we must first know the igneous record's distribution, timing, and petrology. In this paper, we describe a new geospatial database of the igneous rock record designed to provide a baseline digital resource that is application-agnostic and can be applied across the broadest range of research and resource exploration activities. We discuss the challenges we have faced and solved at each of the three main stages of geospatial mapping: database design, database population and database visualization. This includes the importance of a comprehensive audit trail so that users can differentiate between well and poorly-constrained interpretations, helping identify areas requiring additional work and data acquisition. The result is a geospatial database that will facilitate a better understanding of the Earth system and natural resource exploration.

Abstract Native hydrogen and helium have been considered important resources in assisting the energy transition. Hydrogen and helium seeps have been reported worldwide, which may indicate large reserves within the subsurface. However, generation of hydrogen and helium is complex; poorly understood and constrained for both generation processes and migration. One source of native hydrogen is ultramafic rocks, which have experienced serpentinization together with water radiolysis. In contrast, helium generation occurs as the result of the radioactive decay of uranium and thorium present within radiogenically enriched basement. An exploration tool, dedicated to identifying areas with the geological settings and conditions favourable for native hydrogen and helium generation, has been developed and tested. Several databases have been created and integrated as part of this study (geological and geochemical generation models) to support and focus the search for both hydrogen and helium. Machine learning algorithms which extract value from geospatial data types for detecting various accumulations have been implemented. The first machine learning results demonstrate the significant value in integrating data and machine learning for high grading areas more conducive to accumulating hydrogen and helium.

Abstract A well-recognized characteristic of the World Stress Map (WSM) database is the continued presence of large spatial gaps in the distribution of the data records despite the more than 40-year development history of the database. The current release has more than 30 000 high-quality (A–C) data records (often referred to as ‘stress indicators’), but while some continental areas (such as Australia) have seen a significant increase in spatial converge with the latest release, other continental regions (Africa, central Asia, most of South America) remain markedly sparse. In this contribution we (1) review the current state of the spatial distribution of stress indicators in the continental regions (above sea-level); (2) quantify the clustering of the stress indicators in the latest WSM release using the Hopkins statistic as a way to explore the current spatial distribution of the indicators and assess future WSM releases; and (3) present three approaches (joint inversion, seismic anisotropy and InSAR) that provide a way to fill in the gaps (both in the S Hmax orientation and principal stress magnitudes) in regions that lack active seismicity and where borehole drilling is cost prohibitive. These three approaches have the potential to guide procedures for improving a priori estimates of the ambient stress field in the Earth's crust and reduce the uncertainty in predicting both the magnitude and orientation of the principal tectonic stresses.

Abstract This volume covers multidisciplinary Research and Development contributions on geology, geophysics, bathymetric and biologic aspects, towards data sampling and acquisition, data analysis and its results, and innovative ways of data access. It also presents the development of processes to map, harmonize and integrate marine data across EEZ boundaries, an impressive example of which is the European EMODnet (European Marine Observation and Data network) initiative. EMODnet assembles scattered and partially hidden marine data into continentally harmonized geospatial data products for public benefit and increasingly within overseas collaboration. The volume also aims to shed light on an evaluation of biological and mineral resources and environmental assessments at continental shelf to slope depths. Western Pacific examples provide excellent case studies for this topic.