scholarly journals WSN Localization Algorithm on Underground Mining Area

2021 ◽  
Vol 23 (06) ◽  
pp. 464-475
Author(s):  
Shailendra Kumar Rawat ◽  
◽  
Dr. Prof. S. K. Singh ◽  
Dr. Ajay Kumar Bharti ◽  
◽  
...  
Keyword(s):  
Network Formation ◽  
Underground Mining ◽  
Research Work ◽  
Mining Area ◽  
Localization Algorithm ◽  
Mining Areas ◽  
Localization Scheme ◽  
Recent Developments ◽  
The Difference ◽  
Outdoor Localization

The main aim or goal of our research work is to localize the workers working in the mining area exactly or with minimum localization error. Network formation in mining areas is always very crucial. Laborers working in mining areas need strong availability of network as when they go down or deep in a mining area they can be rescued easily. It can only be possible when we know the exact location of the worker working in the particular area. For this, we need a better localization scheme. Many recent developments have been made in the field of the mining area. Random forest scheme, SVM-based regressive localization, Wi-Fi-based localization, and these are some schemes developed so far. RSSI and Trilateration work for both indoor and outdoor localization. The difference is only in terms of temperature because indoor temperature is different from outdoor temperature. When we are working on the basis of distance and signal strength then the proposed localization algorithm is suitable for hill areas too. From the results of the simulation, the new localization algorithm proposed in the paper with error checking and correction increases the accuracy of the localization in the X direction is 99.98 and in Y direction is 99.97 algorithms based on RSSI and dual prediction.

Tracking the Land Use/Land Cover Change in an Area with Underground Mining and Reforestation via Continuous Landsat Classification

2019 ◽  
Vol 11 (14) ◽  
pp. 1719 ◽  
Author(s):  
Jiaxin Mi ◽  
Yongjun Yang ◽  
Shaoliang Zhang ◽  
Shi An ◽  
Huping Hou ◽  
...  
Keyword(s):  
Land Use ◽  
Random Forest ◽  
Land Cover ◽  
Large Scale ◽  
Underground Mining ◽  
Mining Area ◽  
Random Forest Classifier ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Mining Areas

Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas.

scholarly journals Slope ranking and geohazards correlation analysis for combined open-underground mining area

2018 ◽  
Author(s):  
Zhang Jin
Keyword(s):  
Correlation Analysis ◽  
Water Conservation ◽  
Laser Scanning ◽  
Underground Mining ◽  
Mining Area ◽  
Open Pit ◽  
Ground Subsidence ◽  
Data Sets ◽  
Mining Areas ◽  
Factor Data

Geohazards in mining areas are mainly ground subsidence, slope landslides and ground cracks, surface cover degradation and environmental ecological pattern destruction. The classification and rank of terrain slope and the feature area extraction of the slope are the important content for the correlation analysis with the geohazards. The slope classification and rank index system for soil and water conservation, land use and man-made ground disasters was analyzed. According to the characteristics of open pit and underground associated mining area, we comprehensively analyzed the spatial correlation between different ground disaster and terrain features and landform types, and propose a new slope ranking index, dividing slope zones and forming slope classification map. Especially slope area of 35-45 degrees and more than 45 degrees was extracted, and the relationship between regional geohazards and slope zone was analyzed. The application of terrestrial laser scanning technology to establish open-pit high precision digital elevation model, extraction of slope, slope type, gully density characteristic factor, topography factor data sets are established, and correlation analysis, to enhance disaster information content.

scholarly journals InSAR monitoring surface deformation induced by underground mining using Sentinel-1 images

2020 ◽  
Vol 382 ◽  
pp. 237-240
Author(s):  
Ling Zhang ◽  
Daqing Ge ◽  
Xiaofang Guo ◽  
Bin Liu ◽  
Man Li ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Surface Deformation ◽  
Underground Mining ◽  
Deformation Gradient ◽  
Mining Area ◽  
Interferometric Synthetic Aperture Radar ◽  
Mining Areas ◽  
Temporal Decorrelation ◽  
Land Deformation ◽  
Small Baseline

Abstract. Land subsidence can be caused by underground mining activities. Interferometric Synthetic Aperture Radar (InSAR) has became an economic, effective and accurate technique for land deformation survey and monitoring. In mining areas, there may be several factors to overcome for the succsessful application of InSAR, such as temporal decorrelation and detectable deformation gradient, that limit the ability of InSAR to monitoring rapid land subsidence. In this paper, images obtained by the Sentinel-1 satellite with 6 or 12 d revisiting time are used to improve the ability to detect a deformation gradient, and reduce the influence of temporal decorrelation. By combining Small Baseline Subsets (SBAS) and Interferometric Point Target Analysis (IPTA) methods, using the Nanhu mining area in Tangshan as an example, the spatial continuous results of land subsidence in this mining area are obtained with a 70 cm per year maximum rate, which clearly characterizes the deformation field and its deformation process. The results show that InSAR is a useful way to monitor land subsidence in a mining area and provides further data for environment mine restoration.

Ground motion detection in a salt solution mining area, an application of Multi-Temporal Satellite Interferometry

2021 ◽  
Author(s):  
Lorenzo Solari ◽  
Roberto Montalti ◽  
Anna Barra ◽  
Oriol Monserrat ◽  
Silvia Bianchini ◽  
...  
Keyword(s):  
Ground Motion ◽  
Salt Solution ◽  
Underground Mining ◽  
Central Italy ◽  
Mining Area ◽  
Mining Activity ◽  
Groundwater Depletion ◽  
Solution Mining ◽  
Mining Areas ◽  
Multi Temporal

<p>Subsurface mining is one of the human activities with the highest impact in terms of induced ground motion. The excavation of the mining layers creates a geotechnically and hydrogeologically unstable context. The generation of chimney collapses and sinkholes is the most evident surface consequence of underground mining which, in general, creates the optimal conditions for the development of subsidence bowls. Considering this, the need for ground motion monitoring tools is evident. Topographic measurements have been the obvious choice for many years. Nowadays, the flourishing of Multi-Temporal Satellite Interferometry (MTInSAR) algorithms and techniques offers a new way to measure ground motion in mining areas. MTInSAR fully covers the accuracy requirements asked by mining companies and authorities, adding new potentialities in term of area coverage and number of measurement points. The technique has some intrinsic limitations in mining areas, e.g. coherence loss, but the algorithms are being pushed to their technical limits in order to provide the best coverage and quality of measures.</p><p>This work presents a detailed scale MTInSAR approach designed to characterize ground deformation in the salt solution mining area of Saline di Volterra (Tuscany Region, central Italy). In summary, salt solution mining consists in the injection at the depth of interest of a dissolving fluid and in the extraction of the resultant saturated brine. In Saline di Volterra, this mining activity created ground motion, sinkholes and groundwater depletion. The MTInSAR processing approach used is based on the direct integration of interferograms derived from Sentinel-1 images and on the phase splitting between low and high frequency components. Phase unwrapping is separately performed for the two components that are then recombined to avoid error accumulation. Before generating the final deformation map, a classical atmospheric phase filtering is applied to remove the residual low frequency signal. The results obtained reveal the presence of several subsidence bowls, sometimes corresponding to sinkholes formed in the recent past. These moving areas register velocities up to -250 mm/yr with different spatial and temporal patterns according to the distribution and age of formation of sinkholes. This is the first time an interferometric analysis is performed here. It is hoped that such information could increase the awareness of local entities on the ground effects induced by this mining activity.</p>

Phase unwrapping issue in DInSAR measurements in the aspect of surface displacements on the mining areas

2020 ◽  
Author(s):  
Anna Kopeć ◽  
Dariusz Głąbicki ◽  
Wojciech Milczarek ◽  
Natalia Bugajska ◽  
Karolina Owczarz
Keyword(s):  
Network Flow ◽  
Underground Mining ◽  
Continuous Phase ◽  
Poor Quality ◽  
Phase Unwrapping ◽  
Quality Of Data ◽  
Mining Areas ◽  
Surface Displacements ◽  
The Difference ◽  
The Impact

<p>InSAR become more and more popular technique for monitoring mining excavation influence on terrain surface. Nowadays, research on the accuracy of InSAR measurements focuses on impact of external factors on SAR signal and process of phase unwrapping. SAR interferogram include information about a displacement in wrapped form – modulo 2π. Demodulation of phase (phase unwrapping) enable to restore true phase values and then correct interpretation of acquired information. Poor quality of data (low coherency) and large surface deformations cause phase discontinuities that make unwrapping process difficult and may generate incorrect results. Underground mining excavation, especially shallow or inducing seismic activity, may lead to large and abrupt surface displacements. Majority of unwrapping algorithms assume that the difference between any two adjacent samples in the continuous phase signal should not exceed a value of π. However, this assumption may be incorrect for large and abrupt surface displacements and lead to errors in the phase unwrapping and then to determination of incorrect values of surface displacements. Studies were conducted for areas where both natural and mining-induced seismic shocks occurred. DInSAR technique was used to create interferograms. Phase unwrapping processes were performed using Statistical-Cost, Network-Flow Algorithm for Phase Unwrapping (SNAPHU) for conventional parameters, modified discontinuity parameters and taking into account theoretical shock models (Mogi model). Research allowed to determine the impact of abrupt, large displacements on the phase unwrapping process.</p>

scholarly journals A Semi-Supervised Transfer Learning with Grid Segmentation for Outdoor Localization over LoRaWans

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2640
Author(s):  
Yuh-Shyan Chen ◽  
Chih-Shun Hsu ◽  
Chan-Yin Huang
Keyword(s):  
Transfer Learning ◽  
Outdoor Environment ◽  
Localization Algorithm ◽  
Target Domain ◽  
Location Accuracy ◽  
Localization Scheme ◽  
Signal Features ◽  
Unlabelled Data ◽  
Outdoor Localization ◽  
Relationship Of

During the training phase of the supervised learning, it is not feasible to collect all the datasets of labelled data in an outdoor environment for the localization problem. The semi-supervised transfer learning is consequently used to pre-train a small number of labelled data from the source domain to generate a kernel knowledge for the target domain. The kernel knowledge is transferred to a target domain to transfer some unlabelled data into the virtual labelled data. In this paper, we have proposed a new outdoor localization scheme using a semi-supervised transfer learning for LoRaWANs. In the proposed localization algorithm, a grid segmentation concept is proposed so as to generate a number of virtual labelled data through learning by constructing the relationship of labelled and unlabelled data. The labelled-unlabelled data relationship is repeatedly fine-tuned by correctly adding some more virtual labelled data. Basically, the more the virtual labelled data are added, the higher the location accuracy will be obtained. In the real implementation, three types of signal features, RSSI, SNR, and timestamps, are used for training to improve the location accuracy. The experimental results illustrate that the proposed scheme can improve the location accuracy and reduce the localization error as opposed to the existing outdoor localization schemes.

scholarly journals Slope ranking and geohazards correlation analysis for combined open-underground mining area

2018 ◽  
Author(s):  
Zhang Jin
Keyword(s):  
Correlation Analysis ◽  
Water Conservation ◽  
Laser Scanning ◽  
Underground Mining ◽  
Mining Area ◽  
Open Pit ◽  
Ground Subsidence ◽  
Data Sets ◽  
Mining Areas ◽  
Factor Data

Geohazards in mining areas are mainly ground subsidence, slope landslides and ground cracks, surface cover degradation and environmental ecological pattern destruction. The classification and rank of terrain slope and the feature area extraction of the slope are the important content for the correlation analysis with the geohazards. The slope classification and rank index system for soil and water conservation, land use and man-made ground disasters was analyzed. According to the characteristics of open pit and underground associated mining area, we comprehensively analyzed the spatial correlation between different ground disaster and terrain features and landform types, and propose a new slope ranking index, dividing slope zones and forming slope classification map. Especially slope area of 35-45 degrees and more than 45 degrees was extracted, and the relationship between regional geohazards and slope zone was analyzed. The application of terrestrial laser scanning technology to establish open-pit high precision digital elevation model, extraction of slope, slope type, gully density characteristic factor, topography factor data sets are established, and correlation analysis, to enhance disaster information content.

scholarly journals INSAR COLLABORATIVE MONITORING MODE AND MULTI-MODE COMPUTING SERVICES FOR GEOHAZARDS IDENTIFICATION IN OPEN-PIT MINING AREA

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 241-247
Author(s):  
J. Zhang
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Underground Mining ◽  
Mining Area ◽  
Deformation Monitoring ◽  
High Density ◽  
Open Pit ◽  
Open Pit Mining ◽  
Mining Areas ◽  
Wide Range

Abstract. InSAR has developed a variety of methods, such as D-InSAR, PS-InSAR, MBAS, CT, SqueeSAR, POT, etc., which have been widely used in land subsidence monitoring. For open pit mining areas, there are usually mining activity, complex terrain features, low coherence, and local large deformation gradients, which makes it difficult for time series InSAR technology to obtain high-density surface deformation information in open pit mining areas. Traditional methods usually only monitor the linear deformation of the surface caused by the mining of a few working zone above the underground mining area, and the temporal and spatial resolution is lower. How to obtain high-precision, high-density, and time-sensitive deformation information is the main difficulty of InSAR monitoring in open pit mining areas. Make full use of the geosensor network monitoring system, optimize monitoring mode of collaborated satellite-to-ground based InSAR, further realize whole calculation and geographic information services, to achieve early identification and discovery of abnormal in large-area macro-monitoring, and accurate monitoring of local areas in real-time early warning, which is the development direction of ground deformation monitoring of mining areas. The study area is Pingshuo open pit mining area. we fully study the application mode and services of InSAR monitoring for geohazards in open-pit mining area, through the establishment of satellite InSAR technology system for large-scale macro-monitoring and forecasting, and GBSAR and GSN for local precision monitoring. The effective mode of InSAR monitoring of geohazard in open-pit mines is summarized. A combination of D-InSAR, POT (Pixel offset tracking), Time Series-InSAR and GB-SAR is used in a wide range, and high-resolution optical images are used to identify localized changes in subsidence areas and open-pit mining areas.

scholarly journals Effect of Assumed Boundary Conditions in Numerical Model of Road Pavement-Mining Subsoil System on Criterial Values Used in Design Using Mechanistic Methods

2021 ◽  
Vol 1203 (3) ◽  
pp. 032021
Author(s):  
Beata Parkasiewicz ◽  
Marta Kadela
Keyword(s):  
Boundary Conditions ◽  
Design Process ◽  
Underground Mining ◽  
Ground Surface ◽  
Mining Area ◽  
Mining Operations ◽  
Wheel Load ◽  
The Road ◽  
Mining Areas ◽  
Road Pavement

Abstract Underground mining brings benefits in the form of the extracted mineral. The negative effects of mining exploration are deformations of the rock mass, which also cause deformations on the ground surface. There are continuous deformations, discontinuous deformations and mining-induced tremors. Recommendations regarding the protection of the structure of cubature building against the negative effect of mining operations are discussed in detail, for example, in the recommendation published by the Building Research Institute (ITB) in Warsaw. In the case of road structures, the situation is different. Firstly, there are no general rules that would provide clear guidelines for the procedure for designing road pavement in mining areas, similarly to cubature buildings. Secondly, in the computer programs used for the individual design of road pavement, it is not possible to assign additional actions, including mining impact. Therefore, in order to analyze the behavior of the pavement-mining subsoil system, an advanced numerical analyze should be carried out. In this case, the subsoil thickness, the boundary conditions and the constitutive relationships of the materials of the road pavement layers and subsoil should be determined. This paper presents an attempt to select kinematic boundary conditions for the FEM model of the road pavement-mining subsoil system, analogically to the model of the building-mining subsoil system. The paper is aimed at assessment of the influence of kinematic boundary conditions selection on the criterial values that are taken into account during the design process of road pavement using mechanistic methods. For this purpose, three cases were considered: (i) horizontal mining strain (εdesign ), (ii) curvature of surface (Kdesign ), (iii) combined impact of these actions. In these cases, each time vehicle wheel load was assumed. Based on the analyzes, the computational horizontal strain of the mining area εcomp is decisive when assessing the criterial values taken into account in the design process of road pavement structures.

scholarly journals Deformation and damage to buildings caused by ground movements in mining areas (case study)

2021 ◽  
pp. 52-63
Author(s):  
Lucyna FLORKOWSKA ◽  
Izabela BRYT-NITARSKA ◽  
Janusz KRUCZKOWSKI
Keyword(s):  
Underground Mining ◽  
Ground Deformation ◽  
Soil Surface ◽  
Mining Area ◽  
Ground Movement ◽  
Near Surface ◽  
Mining Areas ◽  
Mining Works ◽  
Masonry Tower ◽  
The Impact

Human activity causes transformations in the near-surface layers of the rock mass, which result in long-term impacts on buildings and engineering infrastructure. Mining activities are particularly disadvantageous in this context, as they trigger severe deformation processes that reach the soil surface as a result of the excavation of deposits. The prevention of accidents and disasters caused by these impacts is based on knowledge derived from observation. Therefore, the aim of this study was to acquire and update knowledge on the impact of mining-related ground deformation and tremors on buildings.  The paper presents the results of measurements carried out on a group of buildings located in an underground mining area. The buildings have been affected by mining impacts since their construction in the 1980s. Despite the implementation of appropriate structural protection, the structures have been suffering deformation and damage. For the purposes of the study, two two-axis inclinometers were installed on the 15.2 m high bell tower, taking measurements at 6-hour intervals. Over a period of 10 months, changes in the leaning of the tower were measured and the condition of the other buildings observed.The study resulted in obtaining: values for the change in tilt of the two perpendicular walls of the tower (over a period of 10 months), correlation of the results with tremors measurements and periodic surveying measurements of the inclination of the vertical edge of the tower, image of damage to buildings caused by mining deformation of the ground. On the basis of an analysis of the location and timing of minefields excavation, the occurrence of real ground movement in the mining areas, continuing even after the end of mining works, was confirmed and irregular deformation of the originally perpendicular walls of the masonry tower building was demonstrated. The tower did not behave as a rigid body; its horizontal profile was deformed.

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