High-Rate Monitoring of Satellite Clocks Using Two Methods of Averaging Time

Maciuk, Kamil; Lewińska, Paulina

doi:10.3390/rs11232754

Cited by 12 publications

(4 citation statements)

References 47 publications

(50 reference statements)

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“…The results indicate that the grid size of 0.1 m is suitable for the study area (Table 3, Figure 8). Compared to the results of Yu H. et al [26], the average error of DEM generated by UAV-based LiDAR increased from 0.32 to 0.039 m. Although UAV oblique photogrammetry can achieve centimeter-level accuracy by arranging high-density ground control points [43], it is not applicable in coal mining subsidence monitoring due to the difficulty of setting ground control points in the coal mining area. The proposed method can achieve centimeter accuracy without ground control points.…”

Section: Discussionmentioning

confidence: 72%

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

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 72%

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

et al. 2022

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“…The results of this research allow for an unambiguous assessment that the main source of land deformations is underground mining. Observations of both areas were performed using UAVs and classic surveying techniques such as static and kinematic GNSS measurements [40], total station measurements, and precise leveling.…”

Section: Methodsmentioning

confidence: 99%

UAV Applications for Determination of Land Deformations Caused by Underground Mining

et al. 2020

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This article presents a case study that demonstrates the applicability of unmanned aerial vehicle (UAV) photogrammetric data to land surface deformation monitoring in areas affected by underground mining. The results presented include data from two objects located in the Upper Silesian Coal Basin in Poland. The limits of coordinate and displacement accuracy are determined by comparing UAV-derived photogrammetric products to reference data. Vertical displacements are determined based on differences between digital surface models created using UAV imagery from several measurement series. Interpretation problems related to vegetation growth on the terrain surface that significantly affect vertical displacement error are pointed out. Horizontal displacements are determined based on points of observation lines established in the field for monitoring purposes, as well as based on scattered situational details. The use of this type of processing is limited by the need for unambiguous situational details with clear contours. Such details are easy to find in urbanized areas but difficult to find in fields and meadows. In addition, various types of discontinuous deformations are detected and their development over time is presented. The results are compared to forecasted land deformations. As a result of the data processing, it has been estimated that the accuracy of the determination of XY coordinates and the horizontal displacements (RMS) in best case scenario is on the level of 1.5–2 GSD, and about 2–3 GSD for heights and subsidence.

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“…An absolute positioning method, which is able to obtain high accuracy for geodetic purposes, is the precise point positioning technique (PPP) (Zumberge et al, 1997). This technique is "precise" because it takes advantage of accurate a priori information, such as satellite orbits and clock errors (Maciuk et al, 2019), which are used during processing for elimination and/or mitigation of various sources of errors, thus resulting in precise and accurate position coordinates. Also, different precise models such as antenna phase center variations for both receiver and satellites, tidal and non-tidal effects, Earth rotation parameters with full statistical information which are improved steadily and many other parameters are needed to obtain reliable estimates.…”

Section: Introductionmentioning

confidence: 99%

The impact of tropospheric mapping function on PPP determination for one-month period

Nistor¹

2020

Acta Geodynamica Et Geomaterialia

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When using the PPP method, it is recommended to take into account the tropospheric influences for obtaining reliable estimates. Global Navigation Satellite System (GNSS) observations taken at low elevation suffer more strongly from atmospheric, antenna phase center variation and multipath effects, hence the observations are noisier than those at higher elevation angle, but they are essential to decorrelate the estimated station height and tropospheric zenith delay (ZTD). To relate the ZTD in the direction of an observation, the so-called mapping function (MF) are used. In this article the influence of different mapping function was studieds such as: Niell mapping function (NMF), Global Mapping Function (GMF) in conjunction with the Global Pressure and Temperature 2 -GPT2, Vienna Mapping Function 1 and no mapping function. The MF were used at different elevation cutoff angles -5 0 , 7 0 , 10 0 and 15 0 . The impact was analyzed: a) on the postfit residuals of the ionospheric free combination for phase (LC) and for pseudorange (PC), b) daily variability for North, East and Up component; c) evaluation of coordinates repeatability and how they are affected by the changes of the cutoff elevation angle and mapping function. The analyzed data was taken from 4 EUREF stations for a period of one month -October 2015. By using the VMF1 mapping function, the lowest value was obtained for the postfit residuals of the LC combination for all the stations. The difference in daily variation between each individual solution for the horizontal component is at the level of ~0.3 ÷ 0.5 mm, with smaller effect on the East component compared to North, whereas the Up component is at the level of ~1.0 ÷ 1.5 mm. The standard deviation (SD) is used as a measure of station position repeatability and the results suggested that for high precision determination a cutoff elevation angle of 10 0 should be used. Although at low elevation -5 0 and 7 0 -the VMF1 performs better than the GMF/GPT2 and NMF, after 10 0 the GMF/GPT2 is strongly in agreement with VMF1 and after 15 0 the NMF shows similar results as VMF1 and GMF/GPT2.

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High-Rate Monitoring of Satellite Clocks Using Two Methods of Averaging Time

Cited by 12 publications

References 47 publications

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

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

UAV Applications for Determination of Land Deformations Caused by Underground Mining

The impact of tropospheric mapping function on PPP determination for one-month period

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