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README.md
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└── results/
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├── sector_classification.txt
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├── site_detection_10k_rand.txt
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└── site_detection.txt
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📘 **Caption:** The structure of the project folder, including annotations, image data, metadata, and results files.
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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<!-- Motivation for the creation of this dataset. -->
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[More Information Needed]
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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#### Data Collection and Processing
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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[More Information Needed]
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└── results/
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├── sector_classification.txt
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├── site_detection_10k_rand.txt
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└── site_detection.txt
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📘 **Caption:** The structure of the project folder, including annotations, image data, metadata, and results files.
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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<!-- Motivation for the creation of this dataset. -->
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Large-Scale Mining (LSM) operations play a crucial role in the economic development of many nations. However, their activities are a major driver of land-use change, high energy consumption, and a range of environmental impacts such as soil erosion, deforestation, and water pollution. The influence of LSM often extends far beyond the boundaries of the mine itself, affecting surrounding ecosystems and communities. Monitoring these large-scale operations is therefore essential to assess their environmental footprint and to distinguish them from small-scale or artisanal mining activities. Remote sensing-based observation of LSM sites enables continuous tracking of changes in land cover, infrastructure expansion, and waste management practices. Such monitoring not only supports the detection of unregulated or illegal activities but also contributes to a better understanding of how specific mine characteristics—such as commodity type, extraction methods, and processing techniques—relate to their environmental consequences.
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[More Information Needed]
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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**Metadata sources**
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http://www.andeangeology.cl/
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http://www.cegmining.com/
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http://www.colegiodegeologos.cl/
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https://elpinguino.com/
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https://infofirma.sea.gob.cl/
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https://kghm.com/
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https://maps.mineriaabierta.cl/
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https://minedocs.com/
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https://miningdataonline.com/
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https://pilotaje.cl/
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https://s28.q4cdn.com/
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https://sec.report/
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https://thediggings.com/
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https://www.alertaislariesco.cl/
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https://www.alxar.cl/
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https://www.aminerals.cl/
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https://www.angloamerican.com/
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https://www.annualreports.com/
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https://www.antofagasta.co.uk/
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https://www.barrick.com/
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https://www.britannica.com/
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https://www.cap.cl/
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https://www.cenizas.cl/
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https://www.cmp.cl/
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https://www.codelco.com/
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https://www.fluor.com/
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https://www.guiaminera.cl/
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https://www.lundinmining.com/
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https://www.mch.cl/
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https://www.minainvierno.cl/
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https://www.mining-technology.com/
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https://www.miningnewsfeed.com/
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https://www.miningweekly.com/
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https://www.teck.com/
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https://www.yamana.com/
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https://www.youtube.com/
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https://xtractresources.com/
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#### Data Collection and Processing
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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**Mining Site Detection (binary semantic segmentation)**
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- selection of 150 mid-sized mining sites in Chile with ~1000km²
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- get location of known mining sites from https://doi.pangaea.de/10.1594/PANGAEA.942325
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- take the 35 spatially most isolated mining sites as TestSet, the remaining 104 mining sites as TrainingSet
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(note: a few mining sites were merged due to overlap)
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- cut the mining sites with a fair amount of surroundings from cloudless Sentinel-2 imagery
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- split imagery into 256x256 sized raster patches
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- create mask files according to geojson annotation files
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**Mine Sector Classification (multiclass semantic segmentation)**
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[More Information Needed]
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