scholarly journals Integrated geological-geophysical and UAS proximal sensing approach to the study of ground water movement between two open-pit pools in an abandoned mine area.

Author(s):  
Stefano Cara ◽  
Silvana Fais ◽  
Paola Ligas ◽  
Carlo Matzuzzi ◽  
Federica Podda

<p>The aim of this work is to combine geological/geophysical techniques with proximal sensing based on Unmanned Aerial System (UAS) for advanced 3D modeling, in a possible post-mining landscape recovery of abandoned mine sites. In this framework a test area in central Sardinia (Italy) was studied. In this area, several talc-chlorite-feldspar bodies have long been mined in open pit operation greatly modifying the original landscape. At present the rearrangement of the mining site and particularly the open pit works that have been occupied by newly formed pools filled with waters from aquifers can be considered an overall project of landscape recovery. The project team have focused on developing a UAS proximal sensing technique for the acquisition of high-definition digital images and by means of photogrammetric algorithms (CMPMVS) in order to generate a dense 3D point cloud and successively high-resolution digital models (DSM and DTM). The proximal sensing survey was performed at different flight heights to obtain a Ground Sample Distance (GSD) according to the scale of investigation. The availability of a detailed topographic dataset is fundamental to characterize a complex morphology and is a basic support for integration with the data resulting from the geological-geophysical survey conducted in the abandoned mine area. Based on this a geophysical investigation by the electromagnetic very low frequency (VLF) method was carefully planned and carried out to localize potential structural discontinuities that can guide groundwater circulation between the newly formed pools encased in the crystalline basement rocks. The VLF method has a high-resolution power in detecting lateral variations in the electrical properties (i.e., conductivity) of the rock formations related to the presence of underground geological structures. To facilitate the interpretation of the VLF-EM anomalies the Karous–Hjelt linear filter was applied on the EM data. Thanks to the application of this filtering procedure, it was possible to obtain the current density pseudosections along the profiles crossing the basement rocks. The pseudosections provide a representation of the various current concentrations in depth and hence the spatial arrangement of subsurface geological features such as faults, fracture zones and geological contacts. The VLF data were also quantitatively interpreted with a 2D code for the VLF data inversion. Both in the pseudosections and in the 2D resistivity models two main conductive zones are present. These conductive zones could be the signature of a preferential path of the water circulation between the newly formed pools encased in the basement rocks. The application of the integrated geological-geophysical and UAV photogrammetric survey approach proved successful in characterizing the basement rocks of the investigated area and allowed to localize structural discontinuities that can guide the groundwater circulation. The results of this study can represent the indispensable knowledge base to contribute to constraining the hydrogeology numerical model needed for the mine site rehabilitation and reasonable planning of the possible post-mining landscape recovery. The methodological sequence used in this study can be reproduced in other similar abandoned mining sites thus giving an important contribution to an efficient and cost-effective performance of the restoration project.</p>

2001 ◽  
Vol 12 (4) ◽  
pp. 211-217
Author(s):  
Makoto OMURA ◽  
Toshihide ITO ◽  
Ryuichi KIMURA ◽  
Takashi NISHIYAMA

2020 ◽  
Vol 12 (14) ◽  
pp. 2283
Author(s):  
Rushikesh Battulwar ◽  
Garrett Winkelmaier ◽  
Jorge Valencia ◽  
Masoud Zare Naghadehi ◽  
Bijan Peik ◽  
...  

High-resolution terrain models of open-pit mine highwalls and benches are essential in developing new automated slope monitoring systems for operational optimization. This paper presents several contributions to the field of remote sensing in surface mines providing a practical framework for generating high-resolution images using low-trim Unmanned Aerial Vehicles (UAVs). First, a novel mobile application was developed for autonomous drone flights to follow mine terrain and capture high-resolution images of the mine surface. In this article, case study is presented showcasing the ability of developed software to import area terrain, plan the flight accordingly, and finally execute the area mapping mission autonomously. Next, to model the drone’s battery performance, empirical studies were conducted considering various flight scenarios. A multivariate linear regression model for drone power consumption was derived from experimental data. The model has also been validated using data from a test flight. Finally, a genetic algorithm for solving the problem of flight planning and optimization has been employed. The developed power consumption model was used as the fitness function in the genetic algorithm. The designed algorithm was then validated using simulation studies. It is shown that the offered path optimization can reduce the time and energy of high-resolution imagery missions by over 50%. The current work provides a practical framework for stability monitoring of open-pit highwalls while achieving required energy optimization and imagery performance.


Author(s):  
Wenmin Hu ◽  
Lixin Wu

Recognition and extraction of mining ground deformation can help us understand the deformation process and space distribution, and estimate the deformation laws and trends. This study focuses on the application of ground deformation detection and extraction combining with high resolution visible stereo imagery, LiDAR observation point cloud data and historical data. The DEM in large mining area is generated using high-resolution satellite stereo images, and ground deformation is obtained through time series analysis combined with historical DEM data. Ground deformation caused by mining activities are detected and analyzed to explain the link between the regional ground deformation and local deformation. A district of covering 200 km<sup>2</sup> around the West Open Pit Mine in Fushun of Liaoning province, a city located in the Northeast China is chosen as the test area for example. Regional and local ground deformation from 2010 to 2015 time series are detected and extracted with DEMs derived from ZY-3 images and LiDAR point DEMs in the case study. Results show that the mean regional deformation is 7.1 m of rising elevation with RMS 9.6 m. Deformation of rising elevation and deformation of declining elevation couple together in local area. The area of higher elevation variation is 16.3 km<sup>2</sup> and the mean rising value is 35.8 m with RMS 15.7 m, while the deformation area of lower elevation variation is 6.8 km<sup>2</sup> and the mean declining value is 17.6 m with RMS 9.3 m. Moreover, local large deformation and regional slow deformation couple together, the deformation in local mining activities has expanded to the surrounding area, a large ground fracture with declining elevation has been detected and extracted in the south of West Open Pit Mine, the mean declining elevation of which is 23.1 m and covering about 2.3 km<sup>2</sup> till 2015. The results in this paper are preliminary currently; we are making efforts to improve more precision results with invariant ground control data for validation.


Author(s):  
T. Krauss ◽  
P. d'Angelo ◽  
G. Kuschk ◽  
J. Tian ◽  
T. Partovi

In this paper we show the pre-processing and potential for environmental applications of very high resolution (VHR) satellite stereo imagery like these from WorldView-2 or Pl´eiades with ground sampling distances (GSD) of half a metre to a metre. To process such data first a dense digital surface model (DSM) has to be generated. Afterwards from this a digital terrain model (DTM) representing the ground and a so called normalized digital elevation model (nDEM) representing off-ground objects are derived. Combining these elevation based data with a spectral classification allows detection and extraction of objects from the satellite scenes. Beside the object extraction also the DSM and DTM can directly be used for simulation and monitoring of environmental issues. Examples are the simulation of floodings, building-volume and people estimation, simulation of noise from roads, wave-propagation for cellphones, wind and light for estimating renewable energy sources, 3D change detection, earthquake preparedness and crisis relief, urban development and sprawl of informal settlements and much more. Also outside of urban areas volume information brings literally a new dimension to earth oberservation tasks like the volume estimations of forests and illegal logging, volume of (illegal) open pit mining activities, estimation of flooding or tsunami risks, dike planning, etc. In this paper we present the preprocessing from the original level-1 satellite data to digital surface models (DSMs), corresponding VHR ortho images and derived digital terrain models (DTMs). From these components we present how a monitoring and decision fusion based 3D change detection can be realized by using different acquisitions. The results are analyzed and assessed to derive quality parameters for the presented method. Finally the usability of 3D information fusion from VHR satellite imagery is discussed and evaluated.


2015 ◽  
pp. 191-198 ◽  
Author(s):  
F.A. Rodrigues ◽  
I. Ortiz-Monasterio ◽  
P.J. Zarco-Tejada ◽  
U. Schulthess ◽  
B. Gérard

2015 ◽  
Vol 159 ◽  
pp. 33-47 ◽  
Author(s):  
E. Ferreira da Silva ◽  
N. Durães ◽  
P. Reis ◽  
C. Patinha ◽  
J. Matos ◽  
...  

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