Mining place review

Already an IBA member? Sign in for a better website experience. Her central theses are timely and transformational, and they insightfully capture a growing constellation of international norms and instruments that she usefully indexes along with key cases from international tribunals at the start of her book. The book also considers the key challenges of meeting the goals of Agenda and the ongoing transition towards lower carbon economies. Bastida argues that a broader view is needed to understand multiple geographical levels of relations and legal orderings as a means of strengthening international cooperation as the way forward to addressing the profound political, economic, social and ecological issues of our age.

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• Crypto mining scams targeting tens of thousands of victims using hundreds of android apps
• Mining Risk Review 2020 (ungated)
• Либо искомый домен заблокирован по решению суда
• Nicehash Review: The Mining Power Marketplace
• Beware of Cryptocurrency Scams
• Coin Mining Central
• How to Choose a Cryptocurrency Mining Pool
• Kazakhstan is now the second-biggest bitcoin mining location globally

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Crypto mining scams targeting tens of thousands of victims using hundreds of android apps

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The area used for mineral extraction is a key indicator for understanding and mitigating the environmental impacts caused by the extractive sector. To date, worldwide data products on mineral extraction do not report the area used by mining activities. In this paper, we contribute to filling this gap by presenting a new data set of mining extents derived by visual interpretation of satellite images.

The polygons cover all mining above-ground features that could be identified from the satellite images, including open cuts, tailings dams, waste rock dumps, water ponds, and processing infrastructure. Global extraction of minerals grew at an unprecedented pace in the past decades, causing a wide range of social and environmental impacts around the world 1 , 2 , 3.

Growing demand for essential minerals and declining quality of ores 4 , 5 , 6 lead to larger volumes of unused material extracted and disposed 7 , increasing appropriation of land 8 , 9. The direct land used by mining is a crucial indicator of environmental pressure, which is closely associated with a range of negative impacts, including fragmentation and degradation of ecosystems and biodiversity loss 10 , 11 , 12 , 13 , Such an indicator supports the implementation and monitoring of several Sustainable Development Goals SDGs , as mining impacts on biodiversity and ecosystem services can be reduced by limiting mining areas Data on land use of mining is also important to further develop land footprint indicators that inform about land required along global supply chains to satisfy final consumption of products 16 , Yet, to date information about mining areas worldwide is not available.

Databases on the global mining sector are regularly updated by national geological services, mining industries, associations, and information services 18 , These databases, however, focus on commodities production, not on land use or other environmental aspects. They include, for example, commodity classifications, produced volumes, and approximate location of the sites, but not their geographic extents. These data sources alone are therefore not sufficient for a comprehensive assessment of the impacts related to the direct land use of global mining.

Satellite images are an important source of information on mining extents complementing surveys and statistics. Visual interpretation of satellite images 9 , for example, has been applied to map the most relevant mining sites in terms of commodities production across the world 20 , This approach is effective and precise but can be costly and time-intensive, therefore, posing challenges to producing comprehensive accounts of global mining areas. Alternatively, automated classification algorithms to monitor land-use changes have rapidly advanced due to the increasing availability of satellite images and computational infrastructure 22 , 23 , 24 , 25 , These developments have helped to map mining extents in many regions 27 , 28 , 29 , 30 , However, scaling automated classification is difficult, as current state-of-the-art algorithms require a large amount of labeled examples 32 , which are usually not available.

In this work, we contribute to filling this knowledge gap by presenting a new data set of mining extents derived by visual interpretation of satellite images. Our data set covers more than six thousand mining sites distributed across the entire globe. These mining sites have reported mineral extraction or activities between the years and , according to the SNL Metals and Mining database Within these regions, we delineated the mining areas i.

The overall accuracy, calculated from 1, stratified random points is This novel data set can help improving environmental impact assessments of the global mining sector, for example, regarding mining-induced deforestation or fragmentation and degradation of ecosystems.

It can also serve as a benchmark for further monitoring the temporal evolution of mining sites around the world and as training and validation data to support automated classification of mines using satellite images. We produced the global-scale data set on mining areas by visual interpretation of satellite images. This remote sensing technique is precise but also costly and time-intensive.

This was important to reduce the time spent inspecting the satellite images and delineating the mining extents.

Automated post-processing was also applied to check and correct possible invalid polygon geometries 34 , for instance polygons with self-intersections.

We defined our ROI as a buffer around the geographical coordinates georeferenced points of active mines reported in the SNL Metals and Mining database The SNL database provides production information on more than 35, mines across the globe.

Among many other variables, SNL reports the approximate geographic coordinates of the extraction sites, from which we selected all mines reporting activity i. This subset added up to 6, mining locations extracting 76 different commodities, with a focus on coal, metal ores and industrial minerals.

Note that many mines, particularly regarding metal ore extraction, report more than one commodity in the SNL database see full list in Table 1. The buffer around the selected SNL mines was necessary to increase the efficiency and systematize the interpretation of the satellite images.

The radius of the buffer should be as small as possible and cover all mining ground features, including open cuts, tailings dams, waste rock piles, water ponds, and processing infrastructure.

The polygons were delineated by two trained experts using an open-source web application 35 developed for this specific purpose. The web interface systematically displays buffers and markers with information about the mines. As background, the app offers three options of satellite layers: Google Satellite, Microsoft Bing Imagery, and Sentinel-2 cloudless These images allow identifying ground features related to mines with high confidence 9.

However, these data sources do not cover the whole globe with the same spatial resolution and contain out-of-date images for some regions The Sentinel-2 cloudless provides a mosaic built from Sentinel-2 images taken during the years and Combining these data layers, the experts identified and delineated the ground features related to mining.

All three satellite data sources were visually inspected before delineating the polygons. The majority of the inspected locations had at least two sources of clear images e. Only very few locations lacked images with sufficient quality to draw the polygons, for example, due to cloud cover or low spatial resolution. We used the source showing the largest mining extent for the delineation of the areas. This premise was taken because the largest extent of a mine is usually stable for several years as a long lifespan is intended due to economic reasons.

Besides, mining areas generally increase and could only reduce through ecological restoration, which can take a long time These conjectures do not ensure the temporal consistency of all delineated extents but helped to capture the largest and most up-to-date extent of the mines according to the available satellite images within our ROI.

In some cases, the mining polygons can also extend beyond the ROI. Mining features intersecting the buffer borders were delineated to account for their full extent, even if they extend beyond the buffer limits. Moreover, the mining polygons can contain isolated patches with forest or other land covers, which do not necessarily represent any mining feature on the ground.

These patches were included because we aim at accounting for the total area used by mining, including isolated spare areas that most probably cannot have other uses. The delineated polygons do not distinguish the different ground features within the mines, i. As a final product from the delineation we obtained a set of polygons covering the total land used by mining within the ROI. We applied geospatial and geometric operations to check and correct the raw data collection. This geoprocessing was performed to avoid double counting of mining areas, correct invalid geometries, and add attributes variables to the polygons.

To avoid double-counting, we dissolved polygons that possibly overlapped or shared a common boundary, i. After that, we removed sliver polygons unwanted small polygons and invalid polygon geometries, producing a consistent set of polygons. From this set of preprocessed polygons, we calculated the area of each feature and added information on the country where each polygon is located. We calculated the area in square kilometers by projecting each polygon to its respective Universal Transverse Mercator UTM zone.

The final set of polygons thus includes the geometries polygons covering the mining areas, their respective areas in square kilometers, country name, and ISO alpha-3 code of the corresponding country. This is useful because many modeling applications require standardized grid data The 30 arcsecond grid was derived from the percentage of area of the geometric intersection between each cell and the geometries of the mining polygons.

These percentages were rounded to zero decimal digits to reduce the size of the data set. Therefore, the percentage of the cell covered by mine should be greater than 0. To obtain the gridded mining area, we estimated the area of each cell in square kilometers and multiplied with the percentage of mining cover per cell, resulting in a 30 arcsecond global grid indicating the mining area within each cell.

The 5 arcminute and 30 arcminute grid resolutions were downsampled form the 30 arcsecond grid. All scripts used in the geoprocessing of data records are available with our open-source web application tool Our data records provide spatially explicit information on the direct land use of mining activities. The main data set consists of 21, mining polygons covering the extents of mining sites worldwide Grid data derived from the polygons is available at 30 arcsecond , 5 arcminute , and 30 arcminute spatial resolution, providing a ready-to-use data set for modeling purposes with the mining area in square kilometers per grid cell.

Figure 1 illustrates how the satellite images were used to delineate the mining extent. In this example, the area is used for coal mining in Mackenzie River, Queensland, Australia. The polygon in Fig.

The Sentinel-2 cloudless mosaic is composed by images from the years and 33 while Microsoft Bing Fig. Nevertheless, all three data sources contributed to providing pieces of evidence of mining in the mapped area. An example polygon delineated over a coal mine in Mackenzie River, Queensland, Australia.

The delineated polygons cover all infrastructure and land cover types directly related to mining activities. This can produce large polygons, such as in the case of the Salar de Atacama , Chile. Figure 2 shows the delineated polygon extent and a detailed view of one of the mining plants. We decided to map the whole area because the mining plants, in fact, have brine pumping and monitoring wells spreading over the entire salt flat far beyond the actual evaporation ponds Alternative assumptions mapping only the evaporation ponds estimated an area of only However, it is important to note that the case of Salar de Atacama was rather isolated; in most cases, no features such as pipelines and wells outside the main mining sites could be identified from the available satellite images.

Mine on the Salar de Atacama salt flat, Chile. The purple polygon on the left side was derived from the Sentinel-2 images shown in the background. The polygon covers all infrastructure spread over the salt flat, including water pipelines, wells, and the actual mining plants. The zoom boxes on the right side show Google Satellite images with a detailed view of water pipelines and wells over the salt flat as well as one of the mining plants.

In many cases, mines are located following the structure of mineral deposits, making it easy to map them from satellite images.

We selected three mines to illustrate these large-scale concentrated activities Fig. The first example Fig.

Figure 3b shows the Batu Hijau copper-gold mine.

Mining Risk Review 2020 (ungated)

Subscriber Account active since. Bitcoin mining is a crucial part of the cryptocurrency's underlying technology through which transactions are verified and added to the digital ledger known as blockchain. The owners and operators of the computer systems that make up the decentralized Bitcoin network, called miners, receive newly created bitcoins as a reward for this work. In this process, miners compete to solve highly complex mathematical equations. The first to figure it out receives the reward. Bitcoin is a cryptocurrency, meaning that it is a currency that leverages cryptography. It can be used to make payments without financial institutions or the government involved.

Либо искомый домен заблокирован по решению суда

Reviews are shared 'as is' in line with our community guidelines. They are not edited, verified or endorsed by either Seek. Let others know what it's like to work at Evolution Mining. Company Reviews published on our site are the views and opinions of their authors and do not represent the views and opinions of Seek. Company directory. Write a Review. Overview Reviews 86 Jobs. Top mentioned terms in reviews Positive comments. Challenging comments.

Nicehash Review: The Mining Power Marketplace

We developed the idea of this mining as a service and built the first mining in Europe. Let me finish this review with a summary of its pros and cons so you can see an overview of what the platform has to offer. Free Bitcoin Mining. Your security is our primary focus. They have facilities in Iceland and Georgia.

Beware of Cryptocurrency Scams

The cryptocurrency was invented in by an unknown person or group of people using the name Satoshi Nakamoto. Bitcoins are created as a reward for a process known as mining. They can be exchanged for other currencies, products, and services. Bitcoin has been criticized for its use in illegal transactions, the large amount of electricity and thus carbon footprint used by mining, price volatility , and thefts from exchanges. Some investors and economists have characterized it as a speculative bubble at various times. Others have used it as an investment, although several regulatory agencies have issued investor alerts about bitcoin.

Coin Mining Central

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How to Choose a Cryptocurrency Mining Pool

Today, Bitcoin consumes as much energy as a small country. This certainly sounds alarming — but the reality is a little more complicated. How much energy does an industry deserve to consume? Right now, organizations around the world are facing pressure to limit the consumption of non-renewable energy sources and the emission of carbon into the atmosphere.

Kazakhstan is now the second-biggest bitcoin mining location globally

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Companies such as those in jewelry, electronics, building and autos want assurance that the minerals they buy are mined responsibly. Civil society organizations and communities expect adherence to a standards system that is comprehensive, robust and accountable to all affected stakeholders. IRMA seeks to drive positive change in industrial-scale mining using credible third-party certification: a tool that has been proven to deliver better social and environmental outcomes in industries such as agriculture, forestry and fishing.