AuBeSa

Automated detection, surveying and mineralogical classification of heaps and tailings ponds with satellite remote sensing

Motivation

Large volumes of high-quality economically strategic metals and rare earth elements are present in heaps and tailings ponds from abandoned mines. To conduct an assessment for the extraction of such secondary deposits, site information is required. Existing databases allow access to specific information, but they are incomplete and have insufficient data depth and accuracy. Therefore, the AuBeSa project aims to build a database that includes precise GPS data, material volume and mineral composition of heaps and tailings ponds to enable a cost-effective evaluation of the value potential for secondary resource extraction.

Approach

The cost-free Sentinel-1 and Sentinel-2 data and SRTM data from USGS Earth Explore serve as the data basis. For collecting the site data, a software is developed that automatically identifies heaps and tailings ponds on satellite imagery based on the machine learning (ML) approach. To estimate the volume of heaps and tailings ponds, a digital terrain model (DTM) is modelled before and after mining activities using SRTM data. This allows the volume of the object to be subsequently calculated. Material identification is performed with the analysis of multispectral data from Sentinel-2. To implement the project objectives, the possibilities and limitations of the applied methods for volume calculation and material identification are first analyzed, and any adjustments are made. Subsequently, an ML model will be developed to automatically identify heaps and tailings ponds on Sentinel-1 and Sentinel-2 satellite imagery. The MRE is responsible for preparing the satellite imagery datasets from which the ML model will be developed and performs the analysis of the spectral data.

Work packages

The project includes the following six work packages:

  • WP 1: Project coordination
  • WP 2: Analysis of known heaps and tailings ponds in a test region and in regions with similar topographies and climatic zones
  • WP 3: Volume calculation of known heaps and tailings ponds in the test region and in regions with similar topographies and climatic zones
  • WP 4: Analysis of known heaps and tailings ponds of different topographies and climatic zones (worldwide)
  • WP 5: Automatic identification of unknown heaps and tailings ponds
  • WP 6: Database development and provision of a user interface

Key Data

  • Level: National
  • Role: Project partner
  • Partners: 2
  • Volume: 210.000 € (MRE)
  • Duration: 30 months

Partner

dida Datenschmiede GmbH

www.dida.do

Project Funding

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