1. TRIM4Post-Mining: Transition Information Modelling for Attractive Post-Mining Landscapes—A Conceptual Framework
- Author
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Jörg Benndorf, Diego Alejandro Restrepo, Natalie Merkel, Andre John, Mike Buxton, Adriana Guatame-Garcia, Marinus Dalm, Bob de Waard, Hernan Flores, Stefan Möllerherm, Luis Alberto Pizano Wagner, Steffen Schmidt, Andreas Knobloch, Harm Nolte, and Martin Kreßner
- Subjects
geomonitoring ,geo-sensors ,data analytics ,ground movement modelling ,geochemical modelling ,Geo-Information Systems (GIS) ,Mining engineering. Metallurgy ,TN1-997 - Abstract
TRIM4Post-Mining is a H2020/RFCS-funded project that brings together a consortium of European experts from industry and academia to develop an integrated information modelling system. This is designed to support decision making and planning during the transition from coal exploitation to a revitalized post-mining landscape, enabling infrastructure development for agricultural and industrial utilization, and contributing to the recovery of energy and materials from coal mining dumps. The smart system will be founded upon a high-resolution spatiotemporal database, utilizing state-of-the-art multi-scale and multi-sensor monitoring technologies that characterize dynamic processes in coal waste dumps related to timely, dependent deformation and geochemical processes. It will integrate efficient methods for operational and post-mining monitoring, comprehensive spatiotemporal data analytics, feature extraction, and predictive modelling; this will allow for the identification of potential contamination areas and the forecasting of geotechnical risks and ground conditions. For the interactive exploration of alternative land-use planning scenarios—in terms of residual risks, technical feasibility, environmental and social impact, and affordability—up-to-date data and models will be embedded in an interactive planning system based on Virtual Reality and Augmented Reality technology, forming a TRIM—a Transition Information Modelling System. This contribution presents the conceptual approach and main constituents, and describes the state-of-the-art and detailed anticipated methodological approach for each of the constituents. This is supported by the presentation of the first results and a discussion of future work. An anticipated second contribution will focus on the main findings, technology readiness and a discussion of future work.
- Published
- 2022
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