scholarly journals Analysis Method of Surface Changes Due to Open-Pit Mining Activities - A Case Study of Pingshuo East Open-Pit Mine in China

Author(s):  
Wenbo Zhu ◽  
Wenbo Zhu ◽  
Jin Zhang ◽  
Jin Zhang ◽  
Jingtao Li ◽  
...  
2020 ◽  
Author(s):  
Jihyun Moon ◽  
Heejeong Seo ◽  
Hoonyol Lee

<p>Musan mine in North Korea is the largest open-pit iron mine in Asia with the proved reserves of about 2.06 billion tons and more than 9 square kilometers. Open-pit mining is one of the surface mining technique extracting minerals from the surface. Vegetation is rarely distributed at the mining site because the topsoil is removed and the ore is mined directly from the surface. Therefore, it is effective to observe surface displacement at the mining site using Interferometric Synthetic Aperture Radar (InSAR) technology. InSAR coherence detects random surface change that measures the activity or stability of the interferometric phase of InSAR data. High coherence will be maintained on the surface where there is no movement and only surface scattering. On the other hand, the surface where there is a lot of movement and volumetric scattering has low coherence value. Therefore, using 12-days InSAR coherence images from Sentinel-1 satellites, for example, it is possible to analyze how active the open-pit mine is during the 12 days. Sentinel-1A satellite images were acquired from June 11, 2015 to May 24, 2016, followed by Sentine-1B satellite images from September 27, 2016 to April 21, 2019. A total of 102 SAR images were downloaded from European Space Agency (ESA) portal. There is a gap between May 24 and September 27, 2016 due to the transition of the data acquisition plan. Over 100 12-days coherence data were obtained by applying InSAR. Stable spots and target spots were selected through average and standard deviation of the entire coherence time series data. Coherence values include not only the mining activity but also the effects of perpendicular baseline, temporal baseline, and weather. Therefore, NDAI (Normalized Difference Activity Index) was newly defined to remove the noise and only the coherence value due to the influence of the mining activity was extracted. The degree of activities can be observed by the time series coherence and NDAI images. This study needs other references related to mining activities in order to analyze the mining activities in more detail. This method can be applied to other open-pit mine.</p>


2020 ◽  
Vol 28 ◽  
pp. 764-769
Author(s):  
Snezana Kirin ◽  
Wei Li ◽  
Miodrag Brzaković ◽  
Igor Miljanović ◽  
Aleksandar Sedmak

2021 ◽  
Author(s):  
Mariia Kurylo ◽  
Ivan Virshylo

Uranium deposits and resources are considered as an important raw material base for the implementation of scenarios for the green and clean energy transition. Traditionally discussed risks of potential environmental impacts of Uranium projects development could be subdivided by deposit type. Surficial type mineralization connected to the calcretes in shallow paleovalleys or playas has many specific features which might be analysed separately. Case study of Oum Dheroua Uranium project in the Islamic Republic of Mauritania shows an unexpected lower estimation of environmental risks comparatively to conventional Uranium projects despite to open-pit mining technology. The reasons for such estimation, connected to geographic location, the inclusion of Uranium minerals in natural ecosystems and low scale of deposits (both in grade and size sense). Potential by-products (Vanadium and Strontium) are not part of environmental factors assessment.


Author(s):  
Mohanad F Jwaid, Husam K Salih Juboori

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancements coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. In addition to four other models we are proposing a decomposition-based restricted genetic dominance (DBCDP-NSGA-II) algorithm, which retains viable and non-facilitating solutions in small areas in order to improve the convergence, distribution and diversity of traditional high-dimensional multi-objective fast-dominated genetic sorting Algorithms (NSGA-II).


Sign in / Sign up

Export Citation Format

Share Document