This paper explored and discussed the cognition of informatization geomatics innovative talents cultivating laws and the basic principles and teaching system of informatization experiment teaching in the informatizati...This paper explored and discussed the cognition of informatization geomatics innovative talents cultivating laws and the basic principles and teaching system of informatization experiment teaching in the informatization experimental teaching innovation.展开更多
Geomatics is an interdisciplinary subject.Many disciplines have teaching demands in this field.A new course on“Geomatics Technology”has been suggested by the Weiyang College of Tsinghua University of China for the m...Geomatics is an interdisciplinary subject.Many disciplines have teaching demands in this field.A new course on“Geomatics Technology”has been suggested by the Weiyang College of Tsinghua University of China for the major of“Mathematical and Scientific Basic Science+Civil,Hydraulic and Marine Engineering”.This paper offers a data-led geomatics teaching mode,developing a customized teaching cloud platform,to explore the cross-integrated innovative teaching methods.Teachers and students can assign and submit assignments on this platform.The platform constitutes a data flow with the data download,data processing and result sharing.It encourages communication among students in various majors,grades and units using data as the medium,from data processing to application upstream and downstream.In the“Geomatics Technology”course,geospatial data has emerged as a vital element of the multidisciplinary approach.This kind of teaching mode has been used in the postgraduate remote sensing course offered by Tsinghua University’s Department of Civil Engineering and Construction Management.Furthermore,the mode will be used for the first time in the autumn semester of 2022 in the undergraduate teaching of Weiyang College and civil engineering,to offer a novel idea for the reform of courses linked to geospatial informatics.展开更多
Mining activities often cause dramatic changes in landscapes, particularly in the dump sites and its surrounding environment. Land rehabilitation is the process of renovating damaged land to some extent of its origina...Mining activities often cause dramatic changes in landscapes, particularly in the dump sites and its surrounding environment. Land rehabilitation is the process of renovating damaged land to some extent of its original shape and aims to minimize and mitigate the environmental effects to allow new land uses. The success of different rehabilitation strategy and newly suggested urban and architecture modeling depends on the landscape characterization (topography of the study area and its derivatives such as slope and aspects, geological and geomorphologic nature of the study area). The aim of this study is to demonstrate the utility of different methodologies based on geomatics techniques (Photogrammetry, Remote Sensing, Global Positioning System (GPS) and three dimensional Geographic Information System (GIS)) for highlighting landscape characterization which is needed for rehabilitation of Mahis area. Photogrammetric adjustment procedures were used to create digital elevation model and Orth-Photo model for the study area using aerial images. Remote sensing data were used for land classification to provide vital information for rehabilitation planning. GPS field observations were used to build spatial network for the study area based on ground control point collections. Finally, realistic representation of the study area with three dimensional GIS was prepared for the study area considering ease and flexible updating of the geo-spatial database.展开更多
The GRACE(Gravity Recovery and Climate Experiment)space mission recorded temporal variation characteristics of the global gravity field at decadal timescales.The gravity data have been shown to capture the dynamics of...The GRACE(Gravity Recovery and Climate Experiment)space mission recorded temporal variation characteristics of the global gravity field at decadal timescales.The gravity data have been shown to capture the dynamics of flows within the outer core and their effects on the core-mantle boundary.We first aim to remove global surface process gravity signals from the GRACE data.We then construct the global core magnetic field according to the CHAOS-7 model.Finally,we apply the blind source separation method to decompose the processed gravity signals and core magnetic signals and compute the power spectral density of the gravity and magnetic field signals by using the Lomb-Scargle periodogram approach.We have discovered a signal cycle(of~6 years)in the principal components of the core magnetic and gravity signals,potentially as a result of deep Earth processes.The main principal components of the core magnetic and gravity signals reveal that the variation trends in the second-order time derivative of the core magnetic field are similar to those in the gravity field.After 2014,the second-order time derivative of the core magnetic field exhibited linear and rapid change characteristics,which were the same as the change in the gravity field and are consistent with existing research results.展开更多
The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navi...The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navigational safety.Despite the availability of numerous SIC products in China,these datasets still lag behind mainstream international products in terms of data accuracy,spatiotemporal resolution,and time span.To enhance the accuracy of China's domestic SIC remote sensing data,this study used the SIC data derived from the passive microwave remote sensing dataset provided by the University of Bremen(BRM-SIC)as a reference to conduct a comprehensive evaluation and analysis of two additional SIC datasets:the dataset derived from the microwave radiation imager(MWRI)aboard the FY-3D satellite,provided by the National Satellite Meteorological Center(FY-SIC),and the dataset obtained through the DT-ASI algorithm from the microwave imager of the FY-3D satellite,provided by Ocean University of China(OUC-SIC).Based on the evaluation results,a TransUnet fusion correction model was developed.The performance of this model was then compared against Ordinary Least Squares(OLS),Random Forest(RF),and UNet correction models,through spatial and temporal analyses.Results indicate that,compared to FY-SIC data,the RMSE of the OUC-SIC data and the standard data is reduced by24.245%,while the R is increased by 12.516%.Overall,the accuracy of OUC-SIC data is superior to that of FY-SIC data.During the research period(2020–2022),the standard deviation(SD)and coefficient of variation(CV)of OUC-SIC were 3.877%and 10.582%,respectively,while those for FY-SIC were 7.836%and 7.982%,respectively.In the study area,compared with OUC-SIC data,FYSIC data exhibited a larger standard deviation of deviation and a smaller coefficient of variation of deviation across most sea areas.These results indicate that the OUC-SIC data exhibit better temporal and spatial stability,whereas the FY-SIC data show stronger relative dimensionless stability.Among the four correction models,all showed improvements over the original,unfused corrected data.The fusion corrections using the OLS,RF,UNet,and TransUnet models reduced RMSE by 5.563%,14.601%,42.927%,and48.316%,respectively.Correspondingly,R increased by 0.463%,1.176%,3.951%,and 4.342%,respectively.Among these models,TransUnet performed the best,effectively integrating the advantages of FY-SIC and OUC-SIC data and notably improving the overall accuracy and spatiotemporal stability of SIC data.展开更多
The diversion effect caused by the linked structure in a metro tunnel with cross-passage complicates the impact of longitudinal fire source location on the smoke backflow layering behavior that has not been clarified,...The diversion effect caused by the linked structure in a metro tunnel with cross-passage complicates the impact of longitudinal fire source location on the smoke backflow layering behavior that has not been clarified,despite the fact that the scenario exists in practice.A series of laboratory-scale experiments were conducted in this study to investigate the smoke back-layering length in a model tunnel with cross-passage.The heat release rate,the velocity of longitudinal air flow,and the location of the fire source were all varied.It was found that the behavior of smoke backflow for the fire source located at the upstream of bifurcation point resembles a single-hole tunnel fire.As the fire source’s position shifts downstream from the bifurcation point,the length of smoke back-layering progressively increases.A competitive interaction exists between airflow diversion and smoke diversion during smoke backflow,significantly affecting the smoke back-layering length in the main tunnel.The dimensionless smoke back-layering length model was formulated in a tunnel featuring a cross-passage,taking into account the positions of longitudinal fire sources.The dimensionless smoke back-layering length exhibits a positive correlation with the 17/18 power of total heat release rate Q and a negative correlation with the 5/2 power of longitudinal ventilation velocity V.展开更多
Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that empl...Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.展开更多
Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constrain...Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constraints,including relocated aftershocks,geological observations,and geophysical information,to adaptively model fault geometry and slip in diverse scenarios such as multi-segment and multi-event ruptures.The framework combines adaptive fault construction with a scenario-driven Bayesian joint inversion approach.Fault geometries are first built from prior constraints,such as surface ruptures and aftershocks,and then refined through probabilistic inference when such data are inadequate.To enhance computational efficiency,we introduce a Sequential Monte Carlo Fukuda-Johnson(SMC-FJ)strategy.This separates nonlinear parameters-including geometry,data weights,and smoothing factors-from linear slip parameters,which are conditionally solved via constrained least squares.Geometry updates follow a hierarchical adjustment scheme based on point,line,and structural units,enabling flexibility across rupture complexities.Synthetic tests and four case studies,including the 2022 Menyuan,2023 Türkiye,2022 Luding,and 2019 Ridgecrest earthquakes,demonstrate robustness under various constraints.For the Menyuan earthquake,full Bayesian inversion confirms that the fault geometry constrained by relocated aftershocks is highly accurate and needs only minor adjustment to match the observed surface deformation.The results further show that gradual changes in fault strike and dip modulated rupture arrest and postseismic stress accumulation,highlighting the critical role of inherited geometric structure in controlling rupture termination and delayed seismic activation.展开更多
Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although la...Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although land cover information has long been recognized as an essential component for monitoring SDGs,a standardized scientific framework for identifying and prioritizing land cover related essential variables does not exist.Therefore,we propose a novel expert-and data-driven framework for identifying,refining,and selecting a priority list of Essential Land cover-related Variables for SDGs(ELcV4SDGs).This framework integrates methods including expert knowledge-based analysis,clustering of variables with similar attributes,and quantified index calculation to establish the priority list.Applying the framework to 15 specific SDG indicators,we found that the ELcV4SDGs priority list comprises three main categories,type and structure,pattern and intensity,and process and evolution of land cover,which are further divided into 19 subcategories and ultimately encompass 50 general variables.The ELcV4SDGs will support detailed spatial monitoring and enhance their scientific applications for SDG monitoring and assessment,thereby guiding future SDG priority actions and informing decision-making to advance the 2030 SDGs agenda at local,national,and global levels.展开更多
The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab b...The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab ballastless track structure.This study sought to enhance technical standards for evaluating interfacial bonding properties by suggesting the use of the splitting tensile strength to evaluate the impact of bubble defects.Specimens were fabricated through on-site experiment.The percent of each area of 6 cm^(2)or more bubble defect was 0 in most of specimens.When the cumulative area of all bub-ble defects reached 12%,the splitting tensile strength value was 0.67 MPa,which exceeded the minimum required value of 0.5 MPa for ensuring bonding interface adhesion.Furthermore,when the cumulative area of all bubble defects reached 8%,the splitting tensile strength value was 0.85 MPa,which exceeded the minimum required value of 0.8 MPa,thereby over-coming the negative impact of each area of 10 cm^(2) or more bubble defect.Additionally,keeping the cumulative area of each area of 6 cm^(2) or more bubble defect below 6%ensured adequate bonding strength and reduced the occurrence of specimens with lower splitting tensile strength values.展开更多
The Yuncheng Basin,located in the southern part of the Fenwei Rift,North China,exhibits obvious crust thinning(Moho uplift of 6-8 km)and shallow Curie point depth(less than 18 km)and hence holds great potential for ge...The Yuncheng Basin,located in the southern part of the Fenwei Rift,North China,exhibits obvious crust thinning(Moho uplift of 6-8 km)and shallow Curie point depth(less than 18 km)and hence holds great potential for geothermal resources.However,geothermal exploration within the Yuncheng Basin typically faces significant challenges due to civil and industrial noise from dense populations and industrial activities.To address these challenges,both Controlled-Source Audio-frequency Magnetotellurics(CSAMT)and radon measurements were employed in Baozigou village to investigate the geothermal structures and identify potential geothermal targets.The CSAMT method effectively delineated the structure of the subsurface hydrothermal system,identifying the reservoir as Paleogene sandstones and Ordovician and Cambrian limestones at elevations ranging from−800 m to−2500 m.In particular,two concealed normal faults(F_(a)and F_(b))were newly revealed by the combination of CSAMT and radon profiling;these previously undetected faults,which exhibit different scales and opposing dips,are likely to be responsible for controlling the convection of thermal water within the Basin’s subsurface hydrothermal system.Moreover,this study developed a preliminary conceptual geothermal model for the Fen River Depression within the Yuncheng Basin,which encompasses geothermal heat sources,cap rocks,reservoirs,and fluid pathways,providing valuable insights for future geothermal exploration.In conjunction with the 3D geological model constructed from CSAMT resistivity structures beneath Baozigou village,test drilling is recommended in the northwestern region of the Baozigou area to intersect the potentially deep fractured carbonates that may contain temperature-elevated geothermal water.This study establishes a good set of guidelines for future geothermal exploration in this region,indicating that high-permeability faults in the central segments of the Fen River Depression are promising targets.展开更多
INTRODUCTION.On January 7,2025,at 9:05 AM BJT,a MS6.8 earthquake(CENC epicenter:28.50°N,87.45°E)struck Dingri County,Xizang Province(hereinafter referred to as the Dingri mainshock).The inferred moment magni...INTRODUCTION.On January 7,2025,at 9:05 AM BJT,a MS6.8 earthquake(CENC epicenter:28.50°N,87.45°E)struck Dingri County,Xizang Province(hereinafter referred to as the Dingri mainshock).The inferred moment magnitude,based on regional/teleseismic waveform inversion and back-projection,is approximately MW7.1.Focal mechanism solutions,aftershock distribution,and field surveys indicate that the Dingri mainshock was a normal-faulting event,with a nearly north-south strike and a westward-dipping fault plane.展开更多
0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,...0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,87.45°E,with a depth of~10 km.展开更多
Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppr...Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppritz equations to estimate Young's modulus,which can introduce cumulative errors and reduce the accuracy of inversion results.To address these issues,this paper introduces the analytical solution of the Zoeppritz equation into the inversion process.The equation is re-derived and expressed in terms of Young's modulus,Poisson's ratio,and density.Within the Bayesian framework,we construct an objective function for the joint inversion of PP and PS waves.Traditional gradient-based algorithms often suffer from low precision and the computational complexity.In this study,we address limitations of conventional approaches related to low precision and complicated code by using Circle chaotic mapping,Levy flights,and Gaussian mutation to optimize the quantum particle swarm optimization(QPSO),named improved quantum particle swarm optimization(IQPSO).The IQPSO demonstrates superior global optimization capabilities.We test the proposed inversion method with both synthetic and field data.The test results demonstrate the proposed method's feasibility and effectiveness,indicating an improvement in inversion accuracy over traditional methods.展开更多
Climate change caused by carbon emissions is a hot topic of concern.Enhancing carbon emission performance(CEP)emerges as a pivotal strategy to curtail carbon emissions,with the digital economy recognized as a crucial ...Climate change caused by carbon emissions is a hot topic of concern.Enhancing carbon emission performance(CEP)emerges as a pivotal strategy to curtail carbon emissions,with the digital economy recognized as a crucial instrument for bolstering CEP.Grounded in theoretical analysis,this article takes the Yangtze River Delta region(YRD)as the research object and conducts empirical analysis for the period from 2010 to 2021.The Super Epsilon-Based Measure(EBM)model was employed to assess CEP,while the entropy method was used to quantify the level of the digital economy.Baseline regression models and mediation effect models were constructed to test the research hypotheses.Additionally,the Spatial Durbin Model(SDM)was utilized to analyze the spatial spillover effects of the digital economy.Some conclusions were drawn as follows.Firstly,both the digital economy and CEP exhibit growing trends and demonstrate significant spatial distribution characteristics.Cities with high CEP are increasingly concentrated along the Yangtze River and coastal areas.Meanwhile,the digital economy generally demonstrates a spatial distribution pattern of being higher in the southeast and lower in the northwest.Secondly,the digital economy exerts a notable and consistent positive influence on CEP,but this impact is not primarily achieved through promoting green technology innovation.Instead,the digital economy exhibits a stronger intermediary effect on CEP by facilitating industrial structure upgrading and rationalization.Thirdly,the digital economy significantly enhancing local CEP but having an insignificant impact on neighboring cities'CEP.To address these findings,cities ought to invest in digital infrastructure,incentivize digital innovation through policy and financial backing,and harness advanced technologies like 5G and blockchain to promote low-carbon,intelligent production and lifestyles,while enhancing industrial structure and regional cooperation to foster a low-carbon digital economy network.展开更多
Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observat...Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observation data are missing.This study presents a combined machine learning-based modeling algorithm without hydrological model data.The TWSA time-series data for 11 large regions worldwide were divided into training and test sets.Autoregressive integrated moving average(ARIMA),long short-term memory(LSTM),and an ARIMA-LSTM combined model were used.The model predictions were compared with GRACE observations,and the model accuracy was evaluated using fi ve metrics:the Nash-Sutcliff e effi ciency coeffi cient(NSE),Pearson correlation coeffi cient(CC),root mean square error(RMSE),normalized RMSE(NRMSE),and mean absolute percentage error.The results show that at the basin scale,the mean CC,NSE,and NRMSE for the ARIMA-LSTM model were 0.93,0.83,and 0.12,respectively.At the grid scale,this study compared the spatial distribution and cumulative distribution function curves of the metrics in the Amazon and Volga River basins.The ARIMA-LSTM model had mean CC and NSE values of 0.89 and 0.61 and 0.92 and 0.61 in the Amazon and Volga River basins,respectively,which are superior to those of the ARIMA model(0.86 and 0.48 and 0.88 and 0.46,respectively)and the LSTM model(0.80 and 0.41 and 0.89 and 0.31,respectively).In the ARIMA-LSTM model,the proportions of grid cells with NSE>0.50 for the two basins were 63.3%and 80.8%,while they were 54.3%and 51.3%in the ARIMA model and 53.7%and 43.2%in the LSTM model.The ARIMA-LSTM model significantly improved the NSE values of the predictions while guaranteeing high CC values in the GRACE data reconstruction at both scales,which can aid in fi lling in discontinuous data in temporal gravity fi eld models..展开更多
The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmosphe...The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical direction.Current atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader applicability.This study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are unavailable.Validation with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,respectively.This corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,respectively.Additional validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,respectively.These accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical correction.The new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.展开更多
The implementation of long-term shelterbelt programs in the middle reaches of the Yellow River(MRYR),China not only has improved the overall ecological environment,but also has led to the changes of land use pattern,c...The implementation of long-term shelterbelt programs in the middle reaches of the Yellow River(MRYR),China not only has improved the overall ecological environment,but also has led to the changes of land use pattern,causing carbon storage exchanges.However,the relationship between carbon storage and land use change in the MRYR is not concerned,which results in the uncertainty in the simulation of carbon storage in this area.Land use changes directly affect the carbon storage capacity of ecosystems,and as an indicator reflecting the overall state of land use,land use degree has an important relationship with carbon storage.In this study,land use data and the integrated valuation of ecosystem services and trade-offs(InVEST)model were used to assess the trends in land use degree and carbon storage in the MRYR during 1980-2020.The potential impact index and the standard deviation ellipse(SDE)algorithm were applied to quantify and analyze the characteristics of the impact of land use changes on carbon storage.Subsequently,land use transitions that led to carbon storage variations and their spatial variations were determined.The results showed that:(1)the most significant periods of carbon storage changes and land use transitions were observed during 1990-1995 and 1995-2020,with the most changed areas locating in the east of Fenhe River and in northwestern Henan Province;(2)the positive impact of land use degree on carbon storage may be related to the environmental protection measures implemented along the Yellow River,while the negative impact may be associated with the expansion of construction land in plain areas;and(3)the conversion of other land use types to grassland was the primary factor affecting carbon storage changes during 1980-2020.In future land use planning,attention should be given to the direction of grassland conversion,and focus on reasonably limiting the development of construction land.To enhance carbon storage,it will be crucial to increase the area of high-carbon-density land types,such as forest land and grassland under the condition that the area of permanent farmland does not decrease.展开更多
Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecis...Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecision ZTD model.However,existing ZTD models only consider the impact of linear terms on ZTD estimation,whereas the nonlinear factors have rarely been investigated before and thus become the focus of this study.A real-time and high-precision ZTD model for large height difference area is proposed by considering the linear and nonlinear characteristics of ZTD spatiotemporal variations and is called the realtime linear and nonlinearity ZTD(RLNZ)model.This model uses the ZTD estimated from the Global Pressure and Temperature 3(GPT3)model as the initial value.The linear impacts of periodic term and height on the estimation of ZTD difference between GNSS and GPT3 model are first considered.In addition,nonlinear factors such as geographical location and time are further used to fit the remaining nonlinear ZTD residuals using the general regression neural network method.Finally,the RLNZ-derived ZTD is obtained at an arbitrary location.The western United States,with height difference ranging from-500 to 4000 m,is selected,and the hourly ZTD of 484 GNSS stations provided by the Nevada Geodetic Laboratory(NGL)and the data of 9 radiosonde(RS)stations in the year 2021 are used.Experiment results show that a better performance of ZTD estimation can be retrieved from the proposed RLNZ model when compared with the GPT3 model.Statistical results show the averaged root mean square(RMS),Bias,and mean absolute error(MAE)of ZTD from GPT3 and RLNZ models are 33.7/0.8/25.7 mm and 22.6/0.1/17.4 mm,respectively.The average improvement rate of the RLNZ model is 33% when compared to the GPT3 model.Finally,the application of the proposed RLNZ model in simulated real-time Precise Point Positioning(PPP)indicates that the accuracy of PPP in N,E and U components is improved by 8%,2%,and 6% when compared with that from the GPT3-based PPP.Meanwhile,the convergence time in N and U components is improved by 23% and 7%,respectively.Such results verify the superiority of the proposed RLNZ model in retrieving realtime ZTD maps for GNSS positioning and navigation applications.展开更多
Understanding the mesoscopic tensile fracture damage of rock is the basis of evaluating the deterioration process of mechanical properties of heat-damaged rock. For this, tensile tests of rocks under high-temperature ...Understanding the mesoscopic tensile fracture damage of rock is the basis of evaluating the deterioration process of mechanical properties of heat-damaged rock. For this, tensile tests of rocks under high-temperature treatment were conducted with a ϕ75 mm split Hopkinson tension bar (SHTB) to investigate the mesoscopic fracture and damage properties of rock. An improved scanning electron microscopy (SEM) experimental method was used to analyze the tensile fracture surfaces of rock samples. Qualitative and quantitative analyses were performed to assess evolution of mesoscopic damage of heat-damaged rock under tensile loading. A constitutive model describing the mesoscopic fractal damage under thermo-mechanical coupling was established. The results showed that the high temperatures significantly reduced the tensile strength and fracture surface roughness of the red sandstone. The three-dimensional (3D) reconstruction of the fracture surface of the samples that experienced tensile failure at 900 °C showed a flat surface. The standard deviation of elevation and slope angle of specimen fracture surface first increased and then decreased with increasing temperature. The threshold for brittle fracture of the heat-damaged red sandstone specimens was 600 °C. Beyond this threshold temperature, local ductile fracture occurred, resulting in plastic deformation of the fracture surface during tensile fracturing. With increase of temperature, the internal meso-structure of samples was strengthened slightly at first and then deteriorated gradually, which was consistent with the change of macroscopic mechanical properties of red sandstone. The mesoscopic characteristics, such as the number, mean side length, maximum area, porosity, and fractal dimension of crack, exhibited an initial decline, followed by a gradual increase. The development of microcracks in samples had significant influence on mesoscopic fractal dimension. The mesoscopic fractal characteristics were used to establish a mesoscopic fractal damage constitutive model for red sandstone, and the agreement between the theoretical and experimental results validated the proposed model.展开更多
文摘This paper explored and discussed the cognition of informatization geomatics innovative talents cultivating laws and the basic principles and teaching system of informatization experiment teaching in the informatization experimental teaching innovation.
基金Teaching Reform Project of Tsinghua University(No.DX0702)National Natural Science Foundation of China(No.41971379)。
文摘Geomatics is an interdisciplinary subject.Many disciplines have teaching demands in this field.A new course on“Geomatics Technology”has been suggested by the Weiyang College of Tsinghua University of China for the major of“Mathematical and Scientific Basic Science+Civil,Hydraulic and Marine Engineering”.This paper offers a data-led geomatics teaching mode,developing a customized teaching cloud platform,to explore the cross-integrated innovative teaching methods.Teachers and students can assign and submit assignments on this platform.The platform constitutes a data flow with the data download,data processing and result sharing.It encourages communication among students in various majors,grades and units using data as the medium,from data processing to application upstream and downstream.In the“Geomatics Technology”course,geospatial data has emerged as a vital element of the multidisciplinary approach.This kind of teaching mode has been used in the postgraduate remote sensing course offered by Tsinghua University’s Department of Civil Engineering and Construction Management.Furthermore,the mode will be used for the first time in the autumn semester of 2022 in the undergraduate teaching of Weiyang College and civil engineering,to offer a novel idea for the reform of courses linked to geospatial informatics.
文摘Mining activities often cause dramatic changes in landscapes, particularly in the dump sites and its surrounding environment. Land rehabilitation is the process of renovating damaged land to some extent of its original shape and aims to minimize and mitigate the environmental effects to allow new land uses. The success of different rehabilitation strategy and newly suggested urban and architecture modeling depends on the landscape characterization (topography of the study area and its derivatives such as slope and aspects, geological and geomorphologic nature of the study area). The aim of this study is to demonstrate the utility of different methodologies based on geomatics techniques (Photogrammetry, Remote Sensing, Global Positioning System (GPS) and three dimensional Geographic Information System (GIS)) for highlighting landscape characterization which is needed for rehabilitation of Mahis area. Photogrammetric adjustment procedures were used to create digital elevation model and Orth-Photo model for the study area using aerial images. Remote sensing data were used for land classification to provide vital information for rehabilitation planning. GPS field observations were used to build spatial network for the study area based on ground control point collections. Finally, realistic representation of the study area with three dimensional GIS was prepared for the study area considering ease and flexible updating of the geo-spatial database.
基金the National Natural Science Foundation of China(Grant Nos.42274003,41974007,and 41774019).
文摘The GRACE(Gravity Recovery and Climate Experiment)space mission recorded temporal variation characteristics of the global gravity field at decadal timescales.The gravity data have been shown to capture the dynamics of flows within the outer core and their effects on the core-mantle boundary.We first aim to remove global surface process gravity signals from the GRACE data.We then construct the global core magnetic field according to the CHAOS-7 model.Finally,we apply the blind source separation method to decompose the processed gravity signals and core magnetic signals and compute the power spectral density of the gravity and magnetic field signals by using the Lomb-Scargle periodogram approach.We have discovered a signal cycle(of~6 years)in the principal components of the core magnetic and gravity signals,potentially as a result of deep Earth processes.The main principal components of the core magnetic and gravity signals reveal that the variation trends in the second-order time derivative of the core magnetic field are similar to those in the gravity field.After 2014,the second-order time derivative of the core magnetic field exhibited linear and rapid change characteristics,which were the same as the change in the gravity field and are consistent with existing research results.
基金supported by the National Natural Science Foundation of China(No.41971339)the SDUST Research Fund(No.2019TDJH103)。
文摘The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navigational safety.Despite the availability of numerous SIC products in China,these datasets still lag behind mainstream international products in terms of data accuracy,spatiotemporal resolution,and time span.To enhance the accuracy of China's domestic SIC remote sensing data,this study used the SIC data derived from the passive microwave remote sensing dataset provided by the University of Bremen(BRM-SIC)as a reference to conduct a comprehensive evaluation and analysis of two additional SIC datasets:the dataset derived from the microwave radiation imager(MWRI)aboard the FY-3D satellite,provided by the National Satellite Meteorological Center(FY-SIC),and the dataset obtained through the DT-ASI algorithm from the microwave imager of the FY-3D satellite,provided by Ocean University of China(OUC-SIC).Based on the evaluation results,a TransUnet fusion correction model was developed.The performance of this model was then compared against Ordinary Least Squares(OLS),Random Forest(RF),and UNet correction models,through spatial and temporal analyses.Results indicate that,compared to FY-SIC data,the RMSE of the OUC-SIC data and the standard data is reduced by24.245%,while the R is increased by 12.516%.Overall,the accuracy of OUC-SIC data is superior to that of FY-SIC data.During the research period(2020–2022),the standard deviation(SD)and coefficient of variation(CV)of OUC-SIC were 3.877%and 10.582%,respectively,while those for FY-SIC were 7.836%and 7.982%,respectively.In the study area,compared with OUC-SIC data,FYSIC data exhibited a larger standard deviation of deviation and a smaller coefficient of variation of deviation across most sea areas.These results indicate that the OUC-SIC data exhibit better temporal and spatial stability,whereas the FY-SIC data show stronger relative dimensionless stability.Among the four correction models,all showed improvements over the original,unfused corrected data.The fusion corrections using the OLS,RF,UNet,and TransUnet models reduced RMSE by 5.563%,14.601%,42.927%,and48.316%,respectively.Correspondingly,R increased by 0.463%,1.176%,3.951%,and 4.342%,respectively.Among these models,TransUnet performed the best,effectively integrating the advantages of FY-SIC and OUC-SIC data and notably improving the overall accuracy and spatiotemporal stability of SIC data.
基金funded by the National Natural Science Foundation of China(NSFC)under Grant No.52278415the National Key Research and Development Program of China under Grant No.2022YFC3801104+2 种基金Hebei Provincial Department of Education Project under Grant No.QN2025304the Innovation Fund Project of Hebei University of Engineering under Grant No.SJ2401002066the Sichuan Science and Technology Program under Grant No.2023YFS0407。
文摘The diversion effect caused by the linked structure in a metro tunnel with cross-passage complicates the impact of longitudinal fire source location on the smoke backflow layering behavior that has not been clarified,despite the fact that the scenario exists in practice.A series of laboratory-scale experiments were conducted in this study to investigate the smoke back-layering length in a model tunnel with cross-passage.The heat release rate,the velocity of longitudinal air flow,and the location of the fire source were all varied.It was found that the behavior of smoke backflow for the fire source located at the upstream of bifurcation point resembles a single-hole tunnel fire.As the fire source’s position shifts downstream from the bifurcation point,the length of smoke back-layering progressively increases.A competitive interaction exists between airflow diversion and smoke diversion during smoke backflow,significantly affecting the smoke back-layering length in the main tunnel.The dimensionless smoke back-layering length model was formulated in a tunnel featuring a cross-passage,taking into account the positions of longitudinal fire sources.The dimensionless smoke back-layering length exhibits a positive correlation with the 17/18 power of total heat release rate Q and a negative correlation with the 5/2 power of longitudinal ventilation velocity V.
基金Project(42077244)supported by the National Natural Science Foundation of ChinaProject(2020-05)supported by the Open Research Fund of Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization,China。
文摘Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.
基金supported by the National Natural Science Foundation of China(Grant Nos.42130101,42474002,42374003&42564002)the Jiangxi Provincial Natural Science Foundation(Grant No.20252BAC240262).
文摘Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constraints,including relocated aftershocks,geological observations,and geophysical information,to adaptively model fault geometry and slip in diverse scenarios such as multi-segment and multi-event ruptures.The framework combines adaptive fault construction with a scenario-driven Bayesian joint inversion approach.Fault geometries are first built from prior constraints,such as surface ruptures and aftershocks,and then refined through probabilistic inference when such data are inadequate.To enhance computational efficiency,we introduce a Sequential Monte Carlo Fukuda-Johnson(SMC-FJ)strategy.This separates nonlinear parameters-including geometry,data weights,and smoothing factors-from linear slip parameters,which are conditionally solved via constrained least squares.Geometry updates follow a hierarchical adjustment scheme based on point,line,and structural units,enabling flexibility across rupture complexities.Synthetic tests and four case studies,including the 2022 Menyuan,2023 Türkiye,2022 Luding,and 2019 Ridgecrest earthquakes,demonstrate robustness under various constraints.For the Menyuan earthquake,full Bayesian inversion confirms that the fault geometry constrained by relocated aftershocks is highly accurate and needs only minor adjustment to match the observed surface deformation.The results further show that gradual changes in fault strike and dip modulated rupture arrest and postseismic stress accumulation,highlighting the critical role of inherited geometric structure in controlling rupture termination and delayed seismic activation.
基金supported by the Key Program of National Natural Science Foundation of China(Grant No.41930650)Young Scientists Fund of the National Natural Science Foundation of China(Grant No.42301310).
文摘Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although land cover information has long been recognized as an essential component for monitoring SDGs,a standardized scientific framework for identifying and prioritizing land cover related essential variables does not exist.Therefore,we propose a novel expert-and data-driven framework for identifying,refining,and selecting a priority list of Essential Land cover-related Variables for SDGs(ELcV4SDGs).This framework integrates methods including expert knowledge-based analysis,clustering of variables with similar attributes,and quantified index calculation to establish the priority list.Applying the framework to 15 specific SDG indicators,we found that the ELcV4SDGs priority list comprises three main categories,type and structure,pattern and intensity,and process and evolution of land cover,which are further divided into 19 subcategories and ultimately encompass 50 general variables.The ELcV4SDGs will support detailed spatial monitoring and enhance their scientific applications for SDG monitoring and assessment,thereby guiding future SDG priority actions and informing decision-making to advance the 2030 SDGs agenda at local,national,and global levels.
基金supported by a grant from China railway corporation science and technology research and development plan project(Grant No.2017G005-B)funding support by Wuyi University’s Hong Kong and Macao Joint Research and Development Fund(Grants No.2021WGALH15)funding support by the Innovation and Technology Commission of Hong Kong SAR Government to the Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center(Grant No.K-BBY1).
文摘The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab ballastless track structure.This study sought to enhance technical standards for evaluating interfacial bonding properties by suggesting the use of the splitting tensile strength to evaluate the impact of bubble defects.Specimens were fabricated through on-site experiment.The percent of each area of 6 cm^(2)or more bubble defect was 0 in most of specimens.When the cumulative area of all bub-ble defects reached 12%,the splitting tensile strength value was 0.67 MPa,which exceeded the minimum required value of 0.5 MPa for ensuring bonding interface adhesion.Furthermore,when the cumulative area of all bubble defects reached 8%,the splitting tensile strength value was 0.85 MPa,which exceeded the minimum required value of 0.8 MPa,thereby over-coming the negative impact of each area of 10 cm^(2) or more bubble defect.Additionally,keeping the cumulative area of each area of 6 cm^(2) or more bubble defect below 6%ensured adequate bonding strength and reduced the occurrence of specimens with lower splitting tensile strength values.
基金supported by the Shanxi Province Basic Research Program(No.20210302123374)Yuncheng University Doctoral Research Initiation Fund(No.YQ-2021008)+3 种基金Excellent doctors come to Shanxi to reward scientific research projects(No.QZX-2023020)Open Fund of State Key Laboratory of Precision Geodesy(No.SKLPG2025-1-1)Joint Open Fund of the Research Platforms of School of Computer Science,China University of Geosciences,Wuhan(No.PTLH2024-B-03)Hubei Provincial Natural Science Foundation Project(No.2025AFC095).
文摘The Yuncheng Basin,located in the southern part of the Fenwei Rift,North China,exhibits obvious crust thinning(Moho uplift of 6-8 km)and shallow Curie point depth(less than 18 km)and hence holds great potential for geothermal resources.However,geothermal exploration within the Yuncheng Basin typically faces significant challenges due to civil and industrial noise from dense populations and industrial activities.To address these challenges,both Controlled-Source Audio-frequency Magnetotellurics(CSAMT)and radon measurements were employed in Baozigou village to investigate the geothermal structures and identify potential geothermal targets.The CSAMT method effectively delineated the structure of the subsurface hydrothermal system,identifying the reservoir as Paleogene sandstones and Ordovician and Cambrian limestones at elevations ranging from−800 m to−2500 m.In particular,two concealed normal faults(F_(a)and F_(b))were newly revealed by the combination of CSAMT and radon profiling;these previously undetected faults,which exhibit different scales and opposing dips,are likely to be responsible for controlling the convection of thermal water within the Basin’s subsurface hydrothermal system.Moreover,this study developed a preliminary conceptual geothermal model for the Fen River Depression within the Yuncheng Basin,which encompasses geothermal heat sources,cap rocks,reservoirs,and fluid pathways,providing valuable insights for future geothermal exploration.In conjunction with the 3D geological model constructed from CSAMT resistivity structures beneath Baozigou village,test drilling is recommended in the northwestern region of the Baozigou area to intersect the potentially deep fractured carbonates that may contain temperature-elevated geothermal water.This study establishes a good set of guidelines for future geothermal exploration in this region,indicating that high-permeability faults in the central segments of the Fen River Depression are promising targets.
基金supported by the“CUG Scholar”Scientific Research Funds at China University of Geosciences(Wuhan)(No.2021230)supported by the National Natural Science Foundation of China(Nos.41922025,42204062)。
文摘INTRODUCTION.On January 7,2025,at 9:05 AM BJT,a MS6.8 earthquake(CENC epicenter:28.50°N,87.45°E)struck Dingri County,Xizang Province(hereinafter referred to as the Dingri mainshock).The inferred moment magnitude,based on regional/teleseismic waveform inversion and back-projection,is approximately MW7.1.Focal mechanism solutions,aftershock distribution,and field surveys indicate that the Dingri mainshock was a normal-faulting event,with a nearly north-south strike and a westward-dipping fault plane.
基金funded by the National Key R&D Program of China(No.2020YFC150071)partly supported by the Shaanxi Province Geoscience Big Data and Geohazard Prevention Innovation Team(2022)and the Research Funds for the Interdisciplinary Projects,CHU(No.300104240914)。
文摘0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,87.45°E,with a depth of~10 km.
基金supported by Fundamental Research Funds for the Central Universities,CHD300102264715National Key Research and Development Program of China under Grant 2021YFA0716902Natural Science Basic Research Program of Shaanxi 2024JCYBMS-199。
文摘Young's modulus and Poisson's ratio are crucial parameters for reservoir characterization and rock brittleness evaluation.Conventional methods often rely on indirect computation or approximations of the Zoeppritz equations to estimate Young's modulus,which can introduce cumulative errors and reduce the accuracy of inversion results.To address these issues,this paper introduces the analytical solution of the Zoeppritz equation into the inversion process.The equation is re-derived and expressed in terms of Young's modulus,Poisson's ratio,and density.Within the Bayesian framework,we construct an objective function for the joint inversion of PP and PS waves.Traditional gradient-based algorithms often suffer from low precision and the computational complexity.In this study,we address limitations of conventional approaches related to low precision and complicated code by using Circle chaotic mapping,Levy flights,and Gaussian mutation to optimize the quantum particle swarm optimization(QPSO),named improved quantum particle swarm optimization(IQPSO).The IQPSO demonstrates superior global optimization capabilities.We test the proposed inversion method with both synthetic and field data.The test results demonstrate the proposed method's feasibility and effectiveness,indicating an improvement in inversion accuracy over traditional methods.
基金Under the auspices of the National Natural Science Foundation of China(No.42101164)Major Project of Philosophy and Social Sciences in Colleges and Universities by Jiangsu Province(No.2024SJZD025)。
文摘Climate change caused by carbon emissions is a hot topic of concern.Enhancing carbon emission performance(CEP)emerges as a pivotal strategy to curtail carbon emissions,with the digital economy recognized as a crucial instrument for bolstering CEP.Grounded in theoretical analysis,this article takes the Yangtze River Delta region(YRD)as the research object and conducts empirical analysis for the period from 2010 to 2021.The Super Epsilon-Based Measure(EBM)model was employed to assess CEP,while the entropy method was used to quantify the level of the digital economy.Baseline regression models and mediation effect models were constructed to test the research hypotheses.Additionally,the Spatial Durbin Model(SDM)was utilized to analyze the spatial spillover effects of the digital economy.Some conclusions were drawn as follows.Firstly,both the digital economy and CEP exhibit growing trends and demonstrate significant spatial distribution characteristics.Cities with high CEP are increasingly concentrated along the Yangtze River and coastal areas.Meanwhile,the digital economy generally demonstrates a spatial distribution pattern of being higher in the southeast and lower in the northwest.Secondly,the digital economy exerts a notable and consistent positive influence on CEP,but this impact is not primarily achieved through promoting green technology innovation.Instead,the digital economy exhibits a stronger intermediary effect on CEP by facilitating industrial structure upgrading and rationalization.Thirdly,the digital economy significantly enhancing local CEP but having an insignificant impact on neighboring cities'CEP.To address these findings,cities ought to invest in digital infrastructure,incentivize digital innovation through policy and financial backing,and harness advanced technologies like 5G and blockchain to promote low-carbon,intelligent production and lifestyles,while enhancing industrial structure and regional cooperation to foster a low-carbon digital economy network.
基金financially supported by The National Natural Science Foundation of China (42374004)the Open Fund of Hubei Luojia Laboratory (220100045)the Natural Science Foundation of Sichuan Province (2022NSFSC1047)。
文摘Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observation data are missing.This study presents a combined machine learning-based modeling algorithm without hydrological model data.The TWSA time-series data for 11 large regions worldwide were divided into training and test sets.Autoregressive integrated moving average(ARIMA),long short-term memory(LSTM),and an ARIMA-LSTM combined model were used.The model predictions were compared with GRACE observations,and the model accuracy was evaluated using fi ve metrics:the Nash-Sutcliff e effi ciency coeffi cient(NSE),Pearson correlation coeffi cient(CC),root mean square error(RMSE),normalized RMSE(NRMSE),and mean absolute percentage error.The results show that at the basin scale,the mean CC,NSE,and NRMSE for the ARIMA-LSTM model were 0.93,0.83,and 0.12,respectively.At the grid scale,this study compared the spatial distribution and cumulative distribution function curves of the metrics in the Amazon and Volga River basins.The ARIMA-LSTM model had mean CC and NSE values of 0.89 and 0.61 and 0.92 and 0.61 in the Amazon and Volga River basins,respectively,which are superior to those of the ARIMA model(0.86 and 0.48 and 0.88 and 0.46,respectively)and the LSTM model(0.80 and 0.41 and 0.89 and 0.31,respectively).In the ARIMA-LSTM model,the proportions of grid cells with NSE>0.50 for the two basins were 63.3%and 80.8%,while they were 54.3%and 51.3%in the ARIMA model and 53.7%and 43.2%in the LSTM model.The ARIMA-LSTM model significantly improved the NSE values of the predictions while guaranteeing high CC values in the GRACE data reconstruction at both scales,which can aid in fi lling in discontinuous data in temporal gravity fi eld models..
基金supported by the National Natural Science Foundation of China(42304018)the National Natural Science Foundation of China(42330105,42064002,42074035)+3 种基金the Guangxi Natural Science Foundation of China(Guike AD23026177,2020GXNSFBA297145)the Foundation of Guilin University of Technology(GUTQDJJ6616032)Guangxi Key Laboratory of Spatial Information and Geomatics(21238-21-05)the Innovation Project of Guangxi Graduate Education(YCSW2023341)。
文摘The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical direction.Current atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader applicability.This study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are unavailable.Validation with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,respectively.This corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,respectively.Additional validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,respectively.These accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical correction.The new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.
基金funded by the National Natural Science Foundation of China(52079103)the Outstanding Youth Science Fund of Xi'an University of Science and Technology(2024YQ2-02).
文摘The implementation of long-term shelterbelt programs in the middle reaches of the Yellow River(MRYR),China not only has improved the overall ecological environment,but also has led to the changes of land use pattern,causing carbon storage exchanges.However,the relationship between carbon storage and land use change in the MRYR is not concerned,which results in the uncertainty in the simulation of carbon storage in this area.Land use changes directly affect the carbon storage capacity of ecosystems,and as an indicator reflecting the overall state of land use,land use degree has an important relationship with carbon storage.In this study,land use data and the integrated valuation of ecosystem services and trade-offs(InVEST)model were used to assess the trends in land use degree and carbon storage in the MRYR during 1980-2020.The potential impact index and the standard deviation ellipse(SDE)algorithm were applied to quantify and analyze the characteristics of the impact of land use changes on carbon storage.Subsequently,land use transitions that led to carbon storage variations and their spatial variations were determined.The results showed that:(1)the most significant periods of carbon storage changes and land use transitions were observed during 1990-1995 and 1995-2020,with the most changed areas locating in the east of Fenhe River and in northwestern Henan Province;(2)the positive impact of land use degree on carbon storage may be related to the environmental protection measures implemented along the Yellow River,while the negative impact may be associated with the expansion of construction land in plain areas;and(3)the conversion of other land use types to grassland was the primary factor affecting carbon storage changes during 1980-2020.In future land use planning,attention should be given to the direction of grassland conversion,and focus on reasonably limiting the development of construction land.To enhance carbon storage,it will be crucial to increase the area of high-carbon-density land types,such as forest land and grassland under the condition that the area of permanent farmland does not decrease.
基金supported by the National Natural Science Foundation of China(42274039)Shaanxi Provincial Innovation Capacity Support Plan Project(2023KJXX-050)+2 种基金The Open Grants of the State Key Laboratory of Severe Weather(2023LASW-B18)Scientific and technological research projects for major issues in military medicine and aviation medicine(2022ZZXM012)Local special scientific research plan project of Shaanxi Provincial Department of Education(22JE012)。
文摘Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecision ZTD model.However,existing ZTD models only consider the impact of linear terms on ZTD estimation,whereas the nonlinear factors have rarely been investigated before and thus become the focus of this study.A real-time and high-precision ZTD model for large height difference area is proposed by considering the linear and nonlinear characteristics of ZTD spatiotemporal variations and is called the realtime linear and nonlinearity ZTD(RLNZ)model.This model uses the ZTD estimated from the Global Pressure and Temperature 3(GPT3)model as the initial value.The linear impacts of periodic term and height on the estimation of ZTD difference between GNSS and GPT3 model are first considered.In addition,nonlinear factors such as geographical location and time are further used to fit the remaining nonlinear ZTD residuals using the general regression neural network method.Finally,the RLNZ-derived ZTD is obtained at an arbitrary location.The western United States,with height difference ranging from-500 to 4000 m,is selected,and the hourly ZTD of 484 GNSS stations provided by the Nevada Geodetic Laboratory(NGL)and the data of 9 radiosonde(RS)stations in the year 2021 are used.Experiment results show that a better performance of ZTD estimation can be retrieved from the proposed RLNZ model when compared with the GPT3 model.Statistical results show the averaged root mean square(RMS),Bias,and mean absolute error(MAE)of ZTD from GPT3 and RLNZ models are 33.7/0.8/25.7 mm and 22.6/0.1/17.4 mm,respectively.The average improvement rate of the RLNZ model is 33% when compared to the GPT3 model.Finally,the application of the proposed RLNZ model in simulated real-time Precise Point Positioning(PPP)indicates that the accuracy of PPP in N,E and U components is improved by 8%,2%,and 6% when compared with that from the GPT3-based PPP.Meanwhile,the convergence time in N and U components is improved by 23% and 7%,respectively.Such results verify the superiority of the proposed RLNZ model in retrieving realtime ZTD maps for GNSS positioning and navigation applications.
基金supported by The National Natural Science Foundation of China(Grant Nos.12272411 and 42007259).
文摘Understanding the mesoscopic tensile fracture damage of rock is the basis of evaluating the deterioration process of mechanical properties of heat-damaged rock. For this, tensile tests of rocks under high-temperature treatment were conducted with a ϕ75 mm split Hopkinson tension bar (SHTB) to investigate the mesoscopic fracture and damage properties of rock. An improved scanning electron microscopy (SEM) experimental method was used to analyze the tensile fracture surfaces of rock samples. Qualitative and quantitative analyses were performed to assess evolution of mesoscopic damage of heat-damaged rock under tensile loading. A constitutive model describing the mesoscopic fractal damage under thermo-mechanical coupling was established. The results showed that the high temperatures significantly reduced the tensile strength and fracture surface roughness of the red sandstone. The three-dimensional (3D) reconstruction of the fracture surface of the samples that experienced tensile failure at 900 °C showed a flat surface. The standard deviation of elevation and slope angle of specimen fracture surface first increased and then decreased with increasing temperature. The threshold for brittle fracture of the heat-damaged red sandstone specimens was 600 °C. Beyond this threshold temperature, local ductile fracture occurred, resulting in plastic deformation of the fracture surface during tensile fracturing. With increase of temperature, the internal meso-structure of samples was strengthened slightly at first and then deteriorated gradually, which was consistent with the change of macroscopic mechanical properties of red sandstone. The mesoscopic characteristics, such as the number, mean side length, maximum area, porosity, and fractal dimension of crack, exhibited an initial decline, followed by a gradual increase. The development of microcracks in samples had significant influence on mesoscopic fractal dimension. The mesoscopic fractal characteristics were used to establish a mesoscopic fractal damage constitutive model for red sandstone, and the agreement between the theoretical and experimental results validated the proposed model.
