Investigation of Unmanned Aerial Vehicles-Based Photogrammetry for Large Mine Subsidence Monitoring

Stupar, Danijela; Rošer, Janez; Vulić, Milivoj

doi:10.3390/min10020196

Cited by 25 publications

(6 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can extract long-term time series of surface deformation and has been successfully applied to the monitoring of land subsidence due to exploitation of underground resources, including mining development. It is important for sustainable mine development to monitor and analyze land subsidence caused by mining, and thus prevent hazardous incidents (Asadi et al, 2004;Woo et al, 2013;Sun et al, 2016;He et al, 2017;Sedlak et al, 2018;Huang et al, 2019;Ilieva et al, 2019;Ignjatović Stupar et al, 2020). Hence, during the mining activities, the mine area and its vicinity must be monitored continuously to avoid possible damage.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal subsidence over Pabdana coal mine Kerman Province, central Iran using time-series of Sentinel-1 remote sensing imagery

et al. 2023

View full text Add to dashboard Cite

Environmental monitoring of mining regions using satellite imagery is crucial for sustainable exploitation and preventing geohazards. Movements due to the failure of the roof in underground coal mining, by migrating upwards and outwards from the seam being mined, could eventually appear as ground deformation. To investigate the matter further, the surface deformation that occurred over the Pabdana mining area was monitored in three time periods, between October 2, 2014, and July 27, 2019. Persistent scatterer interferometry (PSI) was used based on 150 ascending and descending Sentinel-1A images. The maximum mining subsidence rate during the studied periods was about 30 to 35 mm/yr. The PSI analysis shows that the subsidence rate varied both temporally and spatially during the three studied periods. The time series and the displacement rate for various cross-sections highlight a clear quantitative relationship between coal extraction progress and subsidence, which proceeded southward throughout the three study periods. So, considering coal mining subsidence as a geohazard, land developments and structures over the mining area may be safeguarded. The approach used in this investigation can be implemented in other similar coal mining zones.

show abstract

Section: Introductionmentioning

confidence: 99%

Spatiotemporal subsidence over Pabdana coal mine Kerman Province, central Iran using time-series of Sentinel-1 remote sensing imagery

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Under a photogrammetric UAV campaign, the resulting orthomaps can be locally or globally georeferenced, according to the UAV locations during image capturing or using a series of georeferenced ground control points (GCPs). There are relevant studies demonstrating UAV-based photogrammetry in various applications, 13 – 16 as well as studies that propose specific placement of GCP configurations to obtain optimal mapping results 17 – 19 Moreover, RTK GNSS measurements attempt to improve georeference accuracy of the produced surface area model 20 …”

Section: Introductionmentioning

confidence: 99%

Real-time unmanned aerial vehicle surveying using spatial criteria: a simulated study

Chatziparaschis

Partsinevelos

2023

J. Appl. Rem. Sens.

View full text Add to dashboard Cite

Precise coordinate estimation is a fundamental engineering challenge in many mapping applications. Conventional surveying techniques based on global navigation satellite system (GNSS), light detection and ranging (LiDAR), or total stations involve costly equipment and time-consuming methodologies and may suffer from restrictions, such as occlusions and low satellite availability. In this study, a surveying approach, based on a custom-equipped unmanned aerial vehicle (UAV) and ArUco markers distributed in an unknown area as the potential target mapping points, is proposed and evaluated through simulation. The UAV incorporates a real-time kinematic GNSS receiver and a gimbal unit, with a simple camera and an electronic rangefinder module. The system demonstrates a real-time hierarchy targeting system that allows the UAV to engage with the ground targets through the camera, measure corresponding distances, record UAV coordinates, and then perform a multilateration-based target coordinate estimation. To evaluate the flexibility, efficiency, and onboard performance of the proposed target positioning approach, the method was developed as a robotic operating system software package and tested in the Gazebo robotic simulator on an NVIDIA Jetson TX2. Several mapping environments, along with varying flight type scenarios, were created to evaluate the resulting coordinate estimation errors. The achieved positioning accuracy is very promising and demonstrates a possible use for circular flying trajectories. Along these lines, the proposed methodology may pave the way toward a precise surveying alternative, as it may establish the main surveying method for common mapping applications in the near future and even provide coordinate estimations in demanding and, until now, unattainable areas.

show abstract

“…UAV oblique photogrammetry can obtain the three-dimensional (3D) coordinate information of ground features [10][11][12][13][14]. Many scholars have tried to use oblique photogrammetry to detect the surface subsidence of mining areas [15][16][17][18]. However, the 3D point cloud generated by UAV oblique images includes a large number of vegetation points [19], which leads to limited accuracy without control points.…”

Section: Introductionmentioning

confidence: 99%

An Accurate Digital Subsidence Model for Deformation Detection of Coal Mining Areas Using a UAV-Based LiDAR

et al. 2022

View full text Add to dashboard Cite

Coal mine surface subsidence detection determines the damage degree of coal mining, which is of great importance for the mitigation of hazards and property loss. Therefore, it is very important to detect deformation during coal mining. Currently, there are many methods used to detect deformations in coal mining areas. However, with most of them, the accuracy is difficult to guarantee in mountainous areas, especially for shallow seam mining, which has the characteristics of active, rapid, and high-intensity surface subsidence. In response to these problems, we made a digital subsidence model (DSuM) for deformation detection in coal mining areas based on airborne light detection and ranging (LiDAR). First, the entire point cloud of the study area was obtained by coarse to fine registration. Second, noise points were removed by multi-scale morphological filtering, and the progressive triangulation filtering classification (PTFC) algorithm was used to obtain the ground point cloud. Third, the DEM was generated from the clean ground point cloud, and an accurate DSuM was obtained through multiple periods of DEM difference calculations. Then, data mining was conducted based on the DSuM to obtain parameters such as the maximum surface subsidence value, a subsidence contour map, the subsidence area, and the subsidence boundary angle. Finally, the accuracy of the DSuM was analyzed through a comparison with ground checkpoints (GCPs). The results show that the proposed method can achieve centimeter-level accuracy, which makes the data a good reference for mining safety considerations and subsequent restoration of the ecological environment.

show abstract

Investigation of Unmanned Aerial Vehicles-Based Photogrammetry for Large Mine Subsidence Monitoring

Cited by 25 publications

References 16 publications

Spatiotemporal subsidence over Pabdana coal mine Kerman Province, central Iran using time-series of Sentinel-1 remote sensing imagery

Spatiotemporal subsidence over Pabdana coal mine Kerman Province, central Iran using time-series of Sentinel-1 remote sensing imagery

Real-time unmanned aerial vehicle surveying using spatial criteria: a simulated study

An Accurate Digital Subsidence Model for Deformation Detection of Coal Mining Areas Using a UAV-Based LiDAR

Contact Info

Product

Resources

About