The Pliocene Lillo, Poederlee, Merksplas, Mol and Kieseloolite Formations in northern Belgium: a synthesis

The Pliocene of Belgium subcrops in the northern part of the country and for more than a century has been the subject of many palaeontological and stratigraphical studies thanks to numerous temporary excavations that became accessible during the civil works for the expansion of the Antwerp Harbour. It was only during subsurface mapping from the 1980s onwards, in combination with cored and geophysical logged drillings, that these data became integrated which has led to new stratigraphical insights. The data relating to the current stratigraphy have now been inventoried, assessed, synthesized and a refined stratigraphical framework and correlation scheme is presented.

A review of the lower and middle Miocene of northern Belgium

The stratigraphy, sedimentology and paleogeography of the lower and middle Miocene Berchem and Bolderberg Formations from northern Belgium have been extensively studied during the last decades, a.o. in the framework of doctoral research, as parts of subsurface mapping and interregional geological correlation initiatives by governmental organizations. The last formal stratigraphical revision on formation level, however, almost dates from two decades ago, notwithstanding the fact that a wealth of new data has become available. A compilation and assessment of the stratigraphical data of the lower and middle Miocene has been carried out and a refined stratigraphical framework—based on dinoflagellate cyst stratigraphy—is presented. Recommendations for the National Commission for Stratigraphy of Belgium are proposed. A new member, the Molenbeersel member, is proposed for the glauconite-bearing silts and fine sands in the upper part of the Bolderberg Formation in the Roer Valley Graben.

Automated Discontinuity Detection and Reconstruction in Subsurface Environment of Mars Using Deep Learning: A Case Study of SHARAD Observation

Machine learning (ML) algorithmic developments and improvements in Earth and planetary science are expected to bring enormous benefits for areas such as geospatial database construction, automated geological feature reconstruction, and surface dating. In this study, we aim to develop a deep learning (DL) approach to reconstruct the subsurface discontinuities in the subsurface environment of Mars employing the echoes of the Shallow Subsurface Radar (SHARAD), a sounding radar equipped on the Mars Reconnaissance Orbiter (MRO). Although SHARAD has produced highly valuable information about the Martian subsurface, the interpretation of the radar echo of SHARAD is a challenging task considering the vast stocks of datasets and the noisy signal. Therefore, we introduced a 3D subsurface mapping strategy consisting of radar echo pre-processors and a DL algorithm to automatically detect subsurface discontinuities. The developed components the of DL algorithm were synthesized into a subsurface mapping scheme and applied over a few target areas such as mid-latitude lobate debris aprons (LDAs), polar deposits and shallow icy bodies around the Phoenix landing site. The outcomes of the subsurface discontinuity detection scheme were rigorously validated by computing several quality metrics such as accuracy, recall, Jaccard index, etc. In the context of undergoing development and its output, we expect to automatically trace the shapes of Martian subsurface icy structures with further improvements in the DL algorithm.