Pyrite mine waste and water mapping using Hymap and Hyperion hyperspectral data

Riaza, A.; Buzzi, J.; García‐Meléndez, Eduardo; Vázquez, Icíar; Bellido, Eva; Carrère, V.; Müller, Andreas

doi:10.1007/s12665-011-1422-0

Cited by 23 publications

(22 citation statements)

References 18 publications

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“…The test site covers one of the gossanous ridges overlying a massive sulphide lens next to Riotinto River. Within the test site, different iron-bearing facies occur, such as the gossan itself, massive sulphide, altered shale and river sediments under the influence of acidic mine drainage (AMD) (Riaza et al [25]). The Iberian pyrite belt is hosted in a north -vergent fold and thrust belt of late Variscan age (Soriano and Casas [26], Donaire et al [27]) extending from east of Setubal/Portugal to north of Seville/Spain.…”

Section: Test Sitementioning

confidence: 99%

The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data

2017

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Drone-borne hyperspectral imaging is a new and promising technique for fast and precise acquisition, as well as delivery of high-resolution hyperspectral data to a large variety of end-users. Drones can overcome the scale gap between field and air-borne remote sensing, thus providing high-resolution and multi-temporal data. They are easy to use, flexible and deliver data within cm-scale resolution. So far, however, drone-borne imagery has prominently and successfully been almost solely used in precision agriculture and photogrammetry. Drone technology currently mainly relies on structure-from-motion photogrammetry, aerial photography and agricultural monitoring. Recently, a few hyperspectral sensors became available for drones, but complex geometric and radiometric effects complicate their use for geology-related studies. Using two examples, we first show that precise corrections are required for any geological mapping. We then present a processing toolbox for frame-based hyperspectral imaging systems adapted for the complex correction of drone-borne hyperspectral imagery. The toolbox performs sensor-and platform-specific geometric distortion corrections. Furthermore, a topographic correction step is implemented to correct for rough terrain surfaces. We recommend the c-factor-algorithm for geological applications. To our knowledge, we demonstrate for the first time the applicability of the corrected dataset for lithological mapping and mineral exploration.

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Section: Test Sitementioning

confidence: 99%

The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data

2017

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“…The upper coarse grain surfaces tend to oxidize rapidly, whereas fine grained sands and mud near the water underlie crusts with hydrated sulfate, and lose water easily during the dry season [38]. Areas of wider crust development display high spatial mineralogical heterogeneity, related to minor topographical features, such as cracks, boulders, or ponds which can be only several centimeters wide (Figure 11(d)).…”

Section: The Spatial Heterogeneity Of Coatings On Mine Sites and Rivementioning

confidence: 99%

Monitoring the Extent of Contamination from Acid Mine Drainage in the Iberian Pyrite Belt (SW Spain) Using Hyperspectral Imagery

et al. 2011

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Monitoring mine waste from sulfide deposits by hyperspectral remote sensing can be used to predict surface water quality by quantitatively estimating acid drainage and metal contamination on a yearly basis. In addition, analysis of the mineralogy of surface crusts rich in soluble salts can provide a record of annual humidity and temperature. In fact, temporal monitoring of salt efflorescence from mine wastes at a mine site in the Iberian Pyrite Belt (Huelva, Spain) has been achieved using hyperspectral airborne Hymap data. Furthermore, climate variability estimates are possible based on oxidation stages derived from well-known sequences of minerals, by tracing sulfide oxidation intensity using archive spectral libraries. Thus, airborne and spaceborne hyperspectral remote sensing data can be used to provide a short-term record of climate change, and represent a useful set of tools for assessing environmental geoindicators in semi-arid areas. Spectral and geomorphological indicators can be monitored on a regular basis through image processing, supported by field and laboratory spectral data. In fact, hyperspectral image analysis is one of the methods selected by the Joint Research Centre of the European OPEN ACCESS

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“…Numerous studies employ airborne imaging spectroscopy data [1][2][3] to map potential areas of acid mine drainage (AMD) generation, taking advantage of the abundance of specific secondary iron minerals that are stable in a specific pH range, indicating AMD generating conditions [1].…”

Section: Introductionmentioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

“…All of these aforementioned studies employed airborne hyperspectral data as the main source of imaging spectroscopic data in their work, except for [3], which also employed spaceborne hyperspectral data in their work of characterizing mine waste. Of these studies, the studies in Germany [5] and the Czech Republic [6,7] focused on acid mine drainage generation and the pH regime in coal mining; whilst the studies in the USA [1], Spain [4] , Canada [7] and Hungary [9] deal with mine waste from precious and base metal mining.…”

Section: Introductionmentioning

confidence: 99%

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Spaceborne Mine Waste Mineralogy Monitoring in South Africa, Applications for Modern Push-Broom Missions: Hyperion/OLI and EnMAP/Sentinel-2

et al. 2014

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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 OPEN ACCESS Remote Sens. 2014, 6 6791 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.

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Pyrite mine waste and water mapping using Hymap and Hyperion hyperspectral data

Cited by 23 publications

References 18 publications

The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data

The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data

Monitoring the Extent of Contamination from Acid Mine Drainage in the Iberian Pyrite Belt (SW Spain) Using Hyperspectral Imagery

Spaceborne Mine Waste Mineralogy Monitoring in South Africa, Applications for Modern Push-Broom Missions: Hyperion/OLI and EnMAP/Sentinel-2

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