Abstract
Remote sensing analysis is a crucial tool for monitoring the extent of mine waste surfaces and their mineralogy in countries with a long mining history, such as South Africa, where gold and platinum have been produced for over 90 years. These mine waste sites have the potential to contain problematic trace element species (e.g., U, Pb, Cr). In our research, we aim to combine the mapping and monitoring capacities of multispectral and hyperspectral spaceborne sensors. This is done to assess the potential of existing multispectral and hyperspectral spaceborne sensors (OLI and Hyperion) and future missions, such as Sentinel-2 and EnMAP (Environmental Mapping and Analysis Program), for mapping the spatial extent of these mine waste surfaces. For this task we propose a new index, termed the iron feature depth (IFD), derived from Landsat-8 OLI data to map the 900-nm absorption feature as a potential proxy for monitoring the spatial extent of mine waste. OLI was chosen, because it represents the most suitable sensor to map the IFD over large areas in a multi-temporal manner due to its spectral band layout; its (183 km × 170 km) scene size and its revisiting time of 16 days. The IFD is in good agreement with primary and secondary iron-bearing minerals mapped by the Material Identification and Characterization Algorithm (MICA) from EO-1 Hyperion data and illustrates that a combination of hyperspectral data (EnMAP) for mineral identification with multispectral data (Sentinel-2) for repetitive area-wide mapping and monitoring of the IFD as mine waste proxy is a promising application for future spaceborne sensors. A maximum, absolute model error is used to assess the ability of existing and future multispectral sensors to characterize mine waste via its 900-nm iron absorption feature. The following sensor-signal similarity ranking can be established for spectra from gold mining material: EnMAP 100% similarity to the reference, ALI 97.5%, Sentinel-2 97%, OLI and ASTER 95% and ETM+ 91% similarity.
Highlights
Mapping and monitoring mine waste has been identified as a crucial application in the field of imaging spectroscopy and remote sensing
The aim of this paper is to explore the potential of spaceborne imaging spectrometers, such as Hyperion, to map and monitor the spatial extent of mine waste surface material in areas with mine tailings and to find common links between hyperspectral and multispectral systems, such as the Landsat program or the generation Sentinel program of the European Space Agency (ESA), both designed as mapping missions
This is an important fact, because here, the pyroxenes may be used as a proxy for the presence of mine waste associated with platinum mining, as the XRD analysis in Table 2 by Reid [53] and the Material Identification and Characterization Algorithm (MICA) analysis of field spectra show
Summary
Mapping and monitoring mine waste has been identified as a crucial application in the field of imaging spectroscopy and remote sensing. The formation of AMD results from the oxidation of sulfides under environmental conditions that promote the contact of water and oxygen with the mine waste material. This produces acid and ferrous iron [1,2,3]. Secondary iron minerals that are generated during this process and that can be discriminated by spectroscopy are jarosite, ferrihydrite, goethite and copiapite, for example [1,2] This enables qualitative mapping of zones of potential AMD generation and provides a semi-quantitative measure for the magnitude of pollution in a specific area [1]. AMD is in this regard a challenging problem, because it can mobilize potentially problematic trace elements from tailings disposal sites, such as uranium, chromium, arsenic, copper and lead, amongst others
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