The high resolution Terra SAR-X dataset was employed with DIn SAR and persistent scatterer interferometry（PSI） technique for subsidence monitoring in a mountainous area. For DInS AR technique, the generally used SRT...The high resolution Terra SAR-X dataset was employed with DIn SAR and persistent scatterer interferometry（PSI） technique for subsidence monitoring in a mountainous area. For DInS AR technique, the generally used SRTM and relief-DEM, which was derived from aerial topographic map, were used to evaluate the influence of external DEM. The results show that SRTM could not fully compensate the complex topography of the research area. The corner reflectors installed during the acquisition of SAR dataset were used to estimate the accuracy of geocoding. The terrain corrected geocoding results based on relief-DEM were much better than using SRTM, with the root mean square error（RMSE） being 6.35 m in X direction and 11.65 m in Y direction（both in UTM projection）, around one pixel of the multilooked intensity image to be geocoded. For PSI technique, the results from time-series analysis of multi-baseline differential interferograms were integrated to restrict only persistent scatterer candidates near the boundary of subsiding area for regression analysis. The results demonstrate that PSI can refine the boundary of subsidence, which could then be used to derive some angular parameters to help people to learn the law of subsidence caused by repeated excavation in this area.展开更多
Traditional positioning methods,such as conventional Real Time Kinematic(cRTK)rely upon local reference networks to enable users to achieve high-accuracy positioning.The need for such relatively dense networks has sig...Traditional positioning methods,such as conventional Real Time Kinematic(cRTK)rely upon local reference networks to enable users to achieve high-accuracy positioning.The need for such relatively dense networks has significant cost implications.Precise Point Positioning(PPP)on the other hand is a positioning method capable of centimeter-level positioning without the need for such local networks,hence providing significant cost benefits especially in remote areas.This paper presents the state-of-the-art PPP method using both GPS and GLONASS measurements to estimate the float position solution before attempting to resolve GPS integer ambiguities.Integrity monitoring is carried out using the Imperial College Carrier-phase Receiver Autonomous Integrity Monitoring method.A new method to detect and exclude GPS base-satellite failures is developed.A base-satellite is a satellite whose measurements are differenced from other satellite’s measurements when using between-satellite-differenced measurements to estimate position.The failure detection and exclusion methods are tested using static GNSS data recorded by International GNSS Service stations both in static and dynamic processing modes.The results show that failure detection can be achieved in all cases tested and failure exclusion can be achieved for static cases.In the kinematic processing cases,failure exclusion is more difficult because the higher noise in the measurement residuals increases the difficulty to distinguish between failures associated with the base-satellite and other satellites.展开更多
Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to a datadriven machine learning approach for tungsten mineralisation.The method emphasises the importance of appropriat...Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to a datadriven machine learning approach for tungsten mineralisation.The method emphasises the importance of appropriate model evaluation and develops a new Confidence Metric to generate spatially refined and robust exploration targets.The data-driven Random ForestTM algorithm is employed to model tungsten mineralisation in SW England using a range of geological,geochemical and geophysical evidence layers which include a depth to granite evidence layer.Two models are presented,one using standardised input variables and a second that implements fuzzy set theory as part of an augmented feature extraction step.The use of fuzzy data transformations mean feature extraction can incorporate some user-knowledge about the mineralisation into the model.The typically subjective approach is guided using the Receiver Operating Characteristics(ROC)curve tool where transformed data are compared to known training samples.The modelling is conducted using 34 known true positive samples with 10 sets of randomly generated true negative samples to test the random effect on the model.The two models have similar accuracy but show different spatial distributions when identifying highly prospective targets.Areal analysis shows that the fuzzy-transformed model is a better discriminator and highlights three areas of high prospectivity that were not previously known.The Confidence Metric,derived from model variance,is employed to further evaluate the models.The new metric is useful for refining exploration targets and highlighting the most robust areas for follow-up investigation.The fuzzy-transformed model is shown to contain larger areas of high model confidence compared to the model using standardised variables.Finally,legacy mining data,from drilling reports and mine descriptions,is used to further validate the fuzzy-transformed model and gauge the depth of potential deposits.Descriptions of mineralisation corroborate that the targets generated in these models could be undercover at depths of less than 300 m.In summary,the modelling workflow presented herein provides a novel integration of knowledge-driven feature extraction with data-driven machine learning modelling,while the newly derived Confidence Metric generates reliable mineral exploration targets.展开更多
OpenStreetMap(OSM)data are widely used but their reliability is still variable.Many contributors to OSM have not been trained in geography or surveying and consequently their contributions,including geometry and attri...OpenStreetMap(OSM)data are widely used but their reliability is still variable.Many contributors to OSM have not been trained in geography or surveying and consequently their contributions,including geometry and attribute data inserts,deletions,and updates,can be inaccurate,incomplete,inconsistent,or vague.There are some mechanisms and applications dedicated to discovering bugs and errors in OSM data.Such systems can remove errors through user-checks and applying predefined rules but they need an extra control process to check the real-world validity of suspected errors and bugs.This paper focuses on finding bugs and errors based on patterns and rules extracted from the tracking data of users.The underlying idea is that certain characteristics of user trajectories are directly linked to the type of feature.Using such rules,some sets of potential bugs and errors can be identified and stored for further investigations.展开更多
Unmitigated tropospheric delay is one of the major error sources in precise point positioning(PPP).Precise Slant Tropospheric Delay(STD)estimation could help to provide cleaner observables for PPP,and improve its conv...Unmitigated tropospheric delay is one of the major error sources in precise point positioning(PPP).Precise Slant Tropospheric Delay(STD)estimation could help to provide cleaner observables for PPP,and improve its convergence,accuracy,and stability.STD is difficult to model accurately due to the rapid spatial and temporal variation of the water vapor in the troposphere.In the traditional approach,the STD is mapped from the zenith direction,which assumes a spherically symmetric local tropospheric profile and has limitations.In this paper,a new approach of directly estimating the STD from high resolution numerical weather modeling(NWM)products is introduced.This approach benefits from the best available meteorological information to improve real time STD estimation,with the RMS residual lower than 3.5 cm above 15°elevation,and 2 cm above 30°.Therefore,the new method can provide sufficient accuracy to improve PPP convergence time.To improve the performance of the new method in highly variable tropospheric conditions,a correction scheme is proposed which combines NWM information with multi-GNSS observations from a network of local continuously operating reference stations.It is demonstrated through a case study that this correction scheme is quite effective in reducing the STD estimation residuals and PPP convergence time.展开更多
The compressibility of shale matrix reflects the effects of reservoir lithology, material composition, pore structure and tectonic deformation. It is important to understand the factors that influence shale matrix com...The compressibility of shale matrix reflects the effects of reservoir lithology, material composition, pore structure and tectonic deformation. It is important to understand the factors that influence shale matrix compressibility(SMC) and their effects on pore size distribution(PSD) heterogeneity in order to evaluate the properties of unconventional reservoirs.In this study, the volumes of pores whose diameters were in the range 6–100 nm were corrected for SMC for 17 shale samples from basins in China using high-pressure mercury intrusion and low-temperature nitrogen gas adsorption analyses,in order to investigate the factors influencing the SMC values. In addition, the variations in fractal dimensions before and after pore volume correction were determined, using single and multifractal models to explain the effects of SMC on PSD heterogeneity. In this process, the applicability of each fractal model for characterizing PSD heterogeneity was determined using statistical analyses. The Menger and Sierpinski single fractal models, the thermodynamic fractal model and a multifractal model were all used in this study. The results showed the following. The matrix compression restricts the segmentation of the fractal dimension curves for the single fractal Menger and Sierpinski models, which leads to a uniformity of PSD heterogeneity for different pore diameters. However, matrix compression has only a weak influence on the results calculated using a thermodynamic model. The SMC clearly affects the multifractal value variations, showing that the fractal dimension values of shale samples under matrix compression are small. Overall PSD heterogeneity becomes small for pores with diameters below 100 nm and the SMC primarily affects the PSD heterogeneity of higher pore volume areas. The comparison of fractal curves before and after correction and the variance analysis indicate that the thermodynamic model is applicable to quantitatively characterize PSD heterogeneity of shale collected from this sampling area. The results show that PSD heterogeneity increases gradually as micro-pore volumes increase.展开更多
Precise point positioning(PPP)is famous for its capability of high-precision positioning with just one station as long as the receiver can receive global navigation satellite system(GNSS)signals.With the rapid develop...Precise point positioning(PPP)is famous for its capability of high-precision positioning with just one station as long as the receiver can receive global navigation satellite system(GNSS)signals.With the rapid development of BDS and Galileo,the number of available satellites for positioning has increased significantly.In addition,GPS III,GLONASS-K,BDS,and Galileo satellites can transmit triple-frequency signals.The potentials of multi-constellation GNSS PPP requires further analysis on a global scale.Therefore,we selected 96 multi-GNSS experiment(MGEX)stations with a global distribution and used 1 week’s data to assess the PPP performance.The results show that the PPP based on multi-frequency raw observations with spatial and temporal constraints has better performance than PPP using dual-frequency ionospheric-free observations.The main contribution of multi-constellation GNSS PPP is to shorten the convergence time.The convergence time for GPS PPP is approximately 40 min,which can be shortened to less than 20 min in multi-GNSS PPP.After convergence,the positioning accuracy of multi-GNSS PPP is improved by 0.5 to 1.0 cm compared with GPS or GLONASS PPP.The positioning accuracy of multi-GNSS could be further improved in the future with the BDS and Galileo precise products of orbits,clock and phase center offset/variation.展开更多
The last satellite of BeiDou Navigation Satellite System with Global Coverage(BDS-3)constellation was successfully launched on June 23rd,2020,and the entire system began to provide Positioning,Navigation,and Timing(PN...The last satellite of BeiDou Navigation Satellite System with Global Coverage(BDS-3)constellation was successfully launched on June 23rd,2020,and the entire system began to provide Positioning,Navigation,and Timing(PNT)services worldwide.We evaluated the performance of location services using BDS with a smartphone that can track the Global Navigation Satellite System(GNSS)satellites in Nottingham,UK.The static and kinematic experiments were conducted in an open meadow and a lakeside route covered by trees,respectively.Experimental results show that BDS has good visibility,and its overall signal carrier-to-noise density ratio(C/N0)is comparable to that of Global Positioning System(GPS).The average C/N0 of BDS-3 satellites with elevation angles above 45°on B1 band is the highest among all systems,reaching 40.0 dB·Hz.The noise level of the BDS pseudorange measurements is within 0.5 m,and it has a good consistency among satellites.In the static experiment,the standard deviations of BDS position-ing in the east,north and up directions are 1.09,1.16,and 3.02 m,respectively,and the R95 value of the horizontal position is 2.88 m.In harsh environments,the number of BDS satellites tracked by the smartphone is susceptible to environmental factors.The bias Root Mean Squares(RMS)in the three directions of the whole kinematic positioning are 6.83,6.68,11.67 m,in which the positioning bias RMS values in a semi-open environment are only 2.81,1.11,3.29 m.Furthermore,the inclusion of BDS in multiple GNSS systems can significantly improve the positioning precision.This study intends to provide a reference for the further improvements of BDS global PNT services,particularly for Location-Based Services(LBS).展开更多
基金Project(51174191)supported by the National Natural Science Foundation of ChinaProject(2013CB227904)supported by the National Basic Research Program of ChinaProject(2012QNB09)supported by Fundamental Research Funds for the Central Universities,China
文摘The high resolution Terra SAR-X dataset was employed with DIn SAR and persistent scatterer interferometry（PSI） technique for subsidence monitoring in a mountainous area. For DInS AR technique, the generally used SRTM and relief-DEM, which was derived from aerial topographic map, were used to evaluate the influence of external DEM. The results show that SRTM could not fully compensate the complex topography of the research area. The corner reflectors installed during the acquisition of SAR dataset were used to estimate the accuracy of geocoding. The terrain corrected geocoding results based on relief-DEM were much better than using SRTM, with the root mean square error（RMSE） being 6.35 m in X direction and 11.65 m in Y direction（both in UTM projection）, around one pixel of the multilooked intensity image to be geocoded. For PSI technique, the results from time-series analysis of multi-baseline differential interferograms were integrated to restrict only persistent scatterer candidates near the boundary of subsiding area for regression analysis. The results demonstrate that PSI can refine the boundary of subsidence, which could then be used to derive some angular parameters to help people to learn the law of subsidence caused by repeated excavation in this area.
文摘Traditional positioning methods,such as conventional Real Time Kinematic(cRTK)rely upon local reference networks to enable users to achieve high-accuracy positioning.The need for such relatively dense networks has significant cost implications.Precise Point Positioning(PPP)on the other hand is a positioning method capable of centimeter-level positioning without the need for such local networks,hence providing significant cost benefits especially in remote areas.This paper presents the state-of-the-art PPP method using both GPS and GLONASS measurements to estimate the float position solution before attempting to resolve GPS integer ambiguities.Integrity monitoring is carried out using the Imperial College Carrier-phase Receiver Autonomous Integrity Monitoring method.A new method to detect and exclude GPS base-satellite failures is developed.A base-satellite is a satellite whose measurements are differenced from other satellite’s measurements when using between-satellite-differenced measurements to estimate position.The failure detection and exclusion methods are tested using static GNSS data recorded by International GNSS Service stations both in static and dynamic processing modes.The results show that failure detection can be achieved in all cases tested and failure exclusion can be achieved for static cases.In the kinematic processing cases,failure exclusion is more difficult because the higher noise in the measurement residuals increases the difficulty to distinguish between failures associated with the base-satellite and other satellites.
基金funded by the British Geological Survey,United Kingdom(S267)the Natural Environment Research Council(NERC),United Kingdom。
文摘Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to a datadriven machine learning approach for tungsten mineralisation.The method emphasises the importance of appropriate model evaluation and develops a new Confidence Metric to generate spatially refined and robust exploration targets.The data-driven Random ForestTM algorithm is employed to model tungsten mineralisation in SW England using a range of geological,geochemical and geophysical evidence layers which include a depth to granite evidence layer.Two models are presented,one using standardised input variables and a second that implements fuzzy set theory as part of an augmented feature extraction step.The use of fuzzy data transformations mean feature extraction can incorporate some user-knowledge about the mineralisation into the model.The typically subjective approach is guided using the Receiver Operating Characteristics(ROC)curve tool where transformed data are compared to known training samples.The modelling is conducted using 34 known true positive samples with 10 sets of randomly generated true negative samples to test the random effect on the model.The two models have similar accuracy but show different spatial distributions when identifying highly prospective targets.Areal analysis shows that the fuzzy-transformed model is a better discriminator and highlights three areas of high prospectivity that were not previously known.The Confidence Metric,derived from model variance,is employed to further evaluate the models.The new metric is useful for refining exploration targets and highlighting the most robust areas for follow-up investigation.The fuzzy-transformed model is shown to contain larger areas of high model confidence compared to the model using standardised variables.Finally,legacy mining data,from drilling reports and mine descriptions,is used to further validate the fuzzy-transformed model and gauge the depth of potential deposits.Descriptions of mineralisation corroborate that the targets generated in these models could be undercover at depths of less than 300 m.In summary,the modelling workflow presented herein provides a novel integration of knowledge-driven feature extraction with data-driven machine learning modelling,while the newly derived Confidence Metric generates reliable mineral exploration targets.
基金This research was supported financially by EU FP7 Marie Curie Initial Training Network MULTI-POS(Multi-technology Positioning Professionals)[grant number 316528].
文摘OpenStreetMap(OSM)data are widely used but their reliability is still variable.Many contributors to OSM have not been trained in geography or surveying and consequently their contributions,including geometry and attribute data inserts,deletions,and updates,can be inaccurate,incomplete,inconsistent,or vague.There are some mechanisms and applications dedicated to discovering bugs and errors in OSM data.Such systems can remove errors through user-checks and applying predefined rules but they need an extra control process to check the real-world validity of suspected errors and bugs.This paper focuses on finding bugs and errors based on patterns and rules extracted from the tracking data of users.The underlying idea is that certain characteristics of user trajectories are directly linked to the type of feature.Using such rules,some sets of potential bugs and errors can be identified and stored for further investigations.
基金This study is carried out as part of the project Innovative Navigation using new GNSS Signals with Hybridized Technologies(iNsight),which is funded by the UK Engineering and Physical Sciences Research Council(EPSRC).
文摘Unmitigated tropospheric delay is one of the major error sources in precise point positioning(PPP).Precise Slant Tropospheric Delay(STD)estimation could help to provide cleaner observables for PPP,and improve its convergence,accuracy,and stability.STD is difficult to model accurately due to the rapid spatial and temporal variation of the water vapor in the troposphere.In the traditional approach,the STD is mapped from the zenith direction,which assumes a spherically symmetric local tropospheric profile and has limitations.In this paper,a new approach of directly estimating the STD from high resolution numerical weather modeling(NWM)products is introduced.This approach benefits from the best available meteorological information to improve real time STD estimation,with the RMS residual lower than 3.5 cm above 15°elevation,and 2 cm above 30°.Therefore,the new method can provide sufficient accuracy to improve PPP convergence time.To improve the performance of the new method in highly variable tropospheric conditions,a correction scheme is proposed which combines NWM information with multi-GNSS observations from a network of local continuously operating reference stations.It is demonstrated through a case study that this correction scheme is quite effective in reducing the STD estimation residuals and PPP convergence time.
基金funded by grants from the Natural Science Foundation of Shandong Province, China (Nos. ZR2021QD072 and ZR2020QD040)。
文摘The compressibility of shale matrix reflects the effects of reservoir lithology, material composition, pore structure and tectonic deformation. It is important to understand the factors that influence shale matrix compressibility(SMC) and their effects on pore size distribution(PSD) heterogeneity in order to evaluate the properties of unconventional reservoirs.In this study, the volumes of pores whose diameters were in the range 6–100 nm were corrected for SMC for 17 shale samples from basins in China using high-pressure mercury intrusion and low-temperature nitrogen gas adsorption analyses,in order to investigate the factors influencing the SMC values. In addition, the variations in fractal dimensions before and after pore volume correction were determined, using single and multifractal models to explain the effects of SMC on PSD heterogeneity. In this process, the applicability of each fractal model for characterizing PSD heterogeneity was determined using statistical analyses. The Menger and Sierpinski single fractal models, the thermodynamic fractal model and a multifractal model were all used in this study. The results showed the following. The matrix compression restricts the segmentation of the fractal dimension curves for the single fractal Menger and Sierpinski models, which leads to a uniformity of PSD heterogeneity for different pore diameters. However, matrix compression has only a weak influence on the results calculated using a thermodynamic model. The SMC clearly affects the multifractal value variations, showing that the fractal dimension values of shale samples under matrix compression are small. Overall PSD heterogeneity becomes small for pores with diameters below 100 nm and the SMC primarily affects the PSD heterogeneity of higher pore volume areas. The comparison of fractal curves before and after correction and the variance analysis indicate that the thermodynamic model is applicable to quantitatively characterize PSD heterogeneity of shale collected from this sampling area. The results show that PSD heterogeneity increases gradually as micro-pore volumes increase.
基金China Scholarship Council(CSC).Under the foundation of CSC,the first author was given the opportunity to study at the University of Nottingham,UK to complete this research with Prof.Meng and Prof.Jiang.
文摘Precise point positioning(PPP)is famous for its capability of high-precision positioning with just one station as long as the receiver can receive global navigation satellite system(GNSS)signals.With the rapid development of BDS and Galileo,the number of available satellites for positioning has increased significantly.In addition,GPS III,GLONASS-K,BDS,and Galileo satellites can transmit triple-frequency signals.The potentials of multi-constellation GNSS PPP requires further analysis on a global scale.Therefore,we selected 96 multi-GNSS experiment(MGEX)stations with a global distribution and used 1 week’s data to assess the PPP performance.The results show that the PPP based on multi-frequency raw observations with spatial and temporal constraints has better performance than PPP using dual-frequency ionospheric-free observations.The main contribution of multi-constellation GNSS PPP is to shorten the convergence time.The convergence time for GPS PPP is approximately 40 min,which can be shortened to less than 20 min in multi-GNSS PPP.After convergence,the positioning accuracy of multi-GNSS PPP is improved by 0.5 to 1.0 cm compared with GPS or GLONASS PPP.The positioning accuracy of multi-GNSS could be further improved in the future with the BDS and Galileo precise products of orbits,clock and phase center offset/variation.
基金the National Natural Science Foundation of China(41774027)the National Key Research and Development Program(2016YFB0502101)+1 种基金the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX19_0067)the CoDRIVE demonstration project funded under the European Space Agency’s Business Applications initiatives(ESA CoDRIVE Contract Number:4000126688/19/NL/FGL).
文摘The last satellite of BeiDou Navigation Satellite System with Global Coverage(BDS-3)constellation was successfully launched on June 23rd,2020,and the entire system began to provide Positioning,Navigation,and Timing(PNT)services worldwide.We evaluated the performance of location services using BDS with a smartphone that can track the Global Navigation Satellite System(GNSS)satellites in Nottingham,UK.The static and kinematic experiments were conducted in an open meadow and a lakeside route covered by trees,respectively.Experimental results show that BDS has good visibility,and its overall signal carrier-to-noise density ratio(C/N0)is comparable to that of Global Positioning System(GPS).The average C/N0 of BDS-3 satellites with elevation angles above 45°on B1 band is the highest among all systems,reaching 40.0 dB·Hz.The noise level of the BDS pseudorange measurements is within 0.5 m,and it has a good consistency among satellites.In the static experiment,the standard deviations of BDS position-ing in the east,north and up directions are 1.09,1.16,and 3.02 m,respectively,and the R95 value of the horizontal position is 2.88 m.In harsh environments,the number of BDS satellites tracked by the smartphone is susceptible to environmental factors.The bias Root Mean Squares(RMS)in the three directions of the whole kinematic positioning are 6.83,6.68,11.67 m,in which the positioning bias RMS values in a semi-open environment are only 2.81,1.11,3.29 m.Furthermore,the inclusion of BDS in multiple GNSS systems can significantly improve the positioning precision.This study intends to provide a reference for the further improvements of BDS global PNT services,particularly for Location-Based Services(LBS).
