Regular expression matching is playing an important role in deep inspection. The rapid development of SDN and NFV makes the network more dynamic, bringing serious challenges to traditional deep inspection matching eng...Regular expression matching is playing an important role in deep inspection. The rapid development of SDN and NFV makes the network more dynamic, bringing serious challenges to traditional deep inspection matching engines. However, state-of-theart matching methods often require a significant amount of pre-processing time and hence are not suitable for this fast updating scenario. In this paper, a novel matching engine called BFA is proposed to achieve high-speed regular expression matching with fast pre-processing. Experiments demonstrate that BFA obtains 5 to 20 times more update abilities compared to existing regular expression matching methods, and scales well on multi-core platforms.展开更多
In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflec...In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflect actual situations and facilitate their computation and analyses.Given the importance of model building, further processing methods about traditional seismic interpretation results from Landmark should be studied and the processed result can then be directly used in numerical simulation computations.Through this data conversion procedure, Landmark and FLAC(the international general stress software) are seamlessly connected.Thus, the format conversion between the two systems and the pre-and post-processing in simulation computation is realized.A practical application indicates that this method has many advantages such as simple operation, high accuracy of the element subdivision and high speed, which may definitely satisfy the actual needs of floor grid cutting.展开更多
The Low Earth Orbit(LEO)remote sensing satellite mega-constellation has the characteristics of large quantity and various types which make it have unique superiority in the realization of concurrent multiple tasks.How...The Low Earth Orbit(LEO)remote sensing satellite mega-constellation has the characteristics of large quantity and various types which make it have unique superiority in the realization of concurrent multiple tasks.However,the complexity of resource allocation is increased because of the large number of tasks and satellites.Therefore,the primary problem of implementing concurrent multiple tasks via LEO mega-constellation is to pre-process tasks and observation re-sources.To address the challenge,we propose a pre-processing algorithm for the mega-constellation based on highly Dynamic Spatio-Temporal Grids(DSTG).In the first stage,this paper describes the management model of mega-constellation and the multiple tasks.Then,the coding method of DSTG is proposed,based on which the description of complex mega-constellation observation resources is realized.In the third part,the DSTG algorithm is used to realize the processing of concurrent multiple tasks at multiple levels,such as task space attribute,time attribute and grid task importance evaluation.Finally,the simulation result of the proposed method in the case of constellation has been given to verify the effectiveness of concurrent multi-task pre-processing based on DSTG.The autonomous processing process of task decomposition and task fusion and mapping to grids,and the convenient indexing process of time window are verified.展开更多
In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. Ho...In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. However, the inter-block interference （IBI） and inter-carrier interference （ICI） in an OFDM system affect the performance. To mitigate IBI and ICI, some pre-processing approaches have been proposed based on full channel state information （CSI）, which improved the system performance. A pre-processing filter based on partial CSI at the transmitter is designed and investigated. The filter coefficient is given by the optimization processing, the symbol error rate （SER） is tested, and the computation complexity of the proposed scheme is analyzed. Computer simulation results show that the proposed pre-processing filter can effectively mitigate IBI and ICI and the performance can be improved. Compared with pre-processing approaches at the transmitter based on full CSI, the proposed scheme has high spectral efficiency, limited CSI feedback and low computation complexity.展开更多
The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1...The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.展开更多
High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system's evolution.Preprocessing of ice cor...High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system's evolution.Preprocessing of ice cores has direct impacts on the data quality control for further analysis since the conventional ice core processing is time-consuming,produces qualitative data,leads to ice mass loss,and leads to risks of potential secondary pollution.However,over the past several decades,preprocessing of ice cores has received less attention than the improvement of ice drilling,the analytical methodology of various indices,and the researches on the climatic and environmental significance of ice core records.Therefore,this papers reviews the development of the processing for ice cores including framework,design as well as materials,analyzes the technical advantages and disadvantages of the different systems.In the past,continuous flowanalysis(CFA)has been successfully applied to process the polar ice cores.However,it is not suitable for ice cores outside polar region because of high level of particles,the memory effect between samples,and the filtration before injection.Ice core processing is a subtle and professional operation due to the fragility of the nonmetallic materials and the random distribution of particles and air bubbles in ice cores,which aggravates uncertainty in the measurements.The future developments of CFA are discussed in preprocessing,memory effect,challenge for brittle ice,coupling with real-time analysis and optimization of CFA in the field.Furthermore,non-polluting cutters with many different configurations could be designed to cut and scrape in multiple directions and to separate inner and outer portions of the core.This system also needs to be coupled with streamlined operation of packaging,coding,and stacking that can be implemented at high resolution and rate,avoiding manual intervention.At the same time,information of the longitudinal sections could be scanned andidentified,and then classified to obtain quantitative data.In addition,irregular ice volume and weight can also be obtained accurately.These improvements are recorded automatically via user-friendly interfaces.These innovations may be applied to other paleomedias with similar features and needs.展开更多
Mathematical morphology is widely applicated in digital image procesing.Vari- ary morphology construction and algorithm being developed are used in deferent digital image processing.The basic idea of mathematical morp...Mathematical morphology is widely applicated in digital image procesing.Vari- ary morphology construction and algorithm being developed are used in deferent digital image processing.The basic idea of mathematical morphology is to use construction ele- ment measure image morphology for solving understand problem.The article presented advanced cellular neural network that forms mathematical morphological cellular neural network (MMCNN) equation to be suit for mathematical morphology filter.It gave the theo- ries of MMCNN dynamic extent and stable state.It is evidenced that arrived mathematical morphology filter through steady of dynamic process in definite condition.展开更多
There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analys...There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analysis. This paper proposes a data pre-processing model based on intelligent algorithms. Firstly, we introduce the integrated network platform of ocean observation. Next, the preprocessing model of data is presemed, and an imelligent cleaning model of data is proposed. Based on fuzzy clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means clustering. The proposed dynamic algorithm can automatically f＇md the new clustering center with the updated sample data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results through observation data analysis.展开更多
A signal pre-processing method based on optimal variational mode decomposition(OVMD)is proposed to improve the efficiency and accuracy of local data filtering and analysis of edge nodes in distributed electromechanica...A signal pre-processing method based on optimal variational mode decomposition(OVMD)is proposed to improve the efficiency and accuracy of local data filtering and analysis of edge nodes in distributed electromechanical systems.Firstly,the singular points of original signals are eliminated effectively by using the first-order difference method.Then the OVMD method is applied for signal modal decomposition.Furthermore,correlation analysis is conducted to determine the degree of correlation between each mode and the original signal,so as to accurately separate the real operating signal from noise signal.On the basis of theoretical analysis and simulation,an edge node pre-processing system for distributed electromechanical system is designed.Finally,by virtue of the signal-to-noise ratio(SNR)and root-mean-square error(RMSE)indicators,the signal pre-processing effect is evaluated.The experimental results show that the OVMD-based edge node pre-processing system can extract signals with different characteristics and improve the SNR of reconstructed signals.Due to its high fidelity and reliability,this system can also provide data quality assurance for subsequent system health monitoring and fault diagnosis.展开更多
The solution of linear equation group can be applied to the oil exploration, the structure vibration analysis, the computational fluid dynamics, and other fields. When we make the in-depth analysis of some large or ve...The solution of linear equation group can be applied to the oil exploration, the structure vibration analysis, the computational fluid dynamics, and other fields. When we make the in-depth analysis of some large or very large complicated structures, we must use the parallel algorithm with the aid of high-performance computers to solve complex problems. This paper introduces the implementation process having the parallel with sparse linear equations from the perspective of sparse linear equation group.展开更多
Microarray data is inherently noisy due to the noise contaminated from various sources during the preparation of microarray slide and thus it greatly affects the accuracy of the gene expression. How to eliminate the e...Microarray data is inherently noisy due to the noise contaminated from various sources during the preparation of microarray slide and thus it greatly affects the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Efficient denoising is often a necessary and the first step to be taken before the image data is analyzed to compensate for data corruption and for effective utilization for these data. Hence preprocessing of microarray image is an essential to eliminate the background noise in order to enhance the image quality and effective quantification. Existing denoising techniques based on transformed domain have been utilized for microarray noise reduction with their own limitations. The objective of this paper is to introduce novel preprocessing techniques such as optimized spatial resolution (OSR) and spatial domain filtering (SDF) for reduction of noise from microarray data and reduction of error during quantification process for estimating the microarray spots accurately to determine expression level of genes. Besides combined optimized spatial resolution and spatial filtering is proposed and found improved denoising of microarray data with effective quantification of spots. The proposed method has been validated in microarray images of gene expression profiles of Myeloid Leukemia using Stanford Microarray Database with various quality measures such as signal to noise ratio, peak signal to noise ratio, image fidelity, structural content, absolute average difference and correlation quality. It was observed by quantitative analysis that the proposed technique is more efficient for denoising the microarray image which enables to make it suitable for effective quantification.展开更多
Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively r...Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.展开更多
Hilly terrain pipeline is a common form of pipeline in oil and gas storage and transportation industry.Due to the hilly terrain influence, the liquid at the elbow of the gathering pipeline is easy to flow back and acc...Hilly terrain pipeline is a common form of pipeline in oil and gas storage and transportation industry.Due to the hilly terrain influence, the liquid at the elbow of the gathering pipeline is easy to flow back and accumulate to form slug flow, so it is necessary to remove the accumulated liquid by gas purging. In this paper, experiment is carried out in hilly terrain pipelines. Three flow patterns of stratified flow, slug flow and stratified entrained flow are observed. The process of gas purging accumulated liquid is divided into four stages, namely liquid accumulation, liquid rising, continuous outflow and tail outflow. At the same time, the flow pattern maps of each stage are drawn. The pressure drop signal is analyzed in time domain and frequency domain, and the contour map of pressure drop distribution is drawn. It is found that the ratio of range to average value can well distinguish the occurrence range of each flow pattern.Based on visualization, the transition process of slug flow to stratified flow and stratified entrained flow is studied, and the transition boundary prediction model is established. An image processing method is proposed to convert the image signal into a similarity curve, and PSD analysis is performed to calculate the slug frequency. The normal distribution is used to fit the slug frequency, and the predicted correlation is in good agreement with the experimental data.展开更多
Background Three-dimensional terrain models are essential in domains such as video game development and film production.Because surface color is often correlated with terrain geometry,capturing this relationship is cr...Background Three-dimensional terrain models are essential in domains such as video game development and film production.Because surface color is often correlated with terrain geometry,capturing this relationship is critical for generating realistic results.However,most existing methods synthesize either a heightmap or a texture without adequately modeling their inherent correlation.Methods We propose a method that jointly generates terrain heightmaps and textures using a latent diffusion model.First,we train the model in an unsupervised manner to randomly generate paired heightmaps and textures.Then,we perform supervised learning on an external adapter to enable user control via hand-drawn sketches.Results Experiments demonstrate that our approach supports intuitive terrain generation while preserving the correlation between heightmaps and textures.Conclusion Our method outperforms the two-stage and GAN-based baselines by ensuring structural coherence,in which textures naturally align with geometry,successfully accommodating both realistic landscapes and extreme user-defined shapes.展开更多
Unmanned aerial vehicle light detection and ranging(UAV–LiDAR)is a new method for collecting understory terrain data.The high estimation accuracy of understory terrain is crucial for accurate tree height measurement ...Unmanned aerial vehicle light detection and ranging(UAV–LiDAR)is a new method for collecting understory terrain data.The high estimation accuracy of understory terrain is crucial for accurate tree height measurement and forest resource surveys.The UAV–LiDAR flight altitude and forest canopy cover significantly impact the accuracy of understory terrain estimation.However,since no research examined their combined effects,we aimed to investigate this relationship.This will help optimize UAV–LiDAR flight parameters for understory terrain estimation and forest surveys across various canopy cover.This study analyzed the impacts of three flight altitudes and three canopy cover on the estimation accuracy of understory terrain.The results showed that when canopy cover exceeded a specific value,UAV–LiDAR flight altitudes significantly affected understory terrain estimation.Given a forest canopy cover,the reduction in ground point coverage increased significantly as the flight altitude increased;given a flight altitude,the higher the canopy cover,the more significant the reduction in ground point coverage.In forests with a canopy cover≥0.9,there were substantial differences in the accuracies of understory digital elevation models(DEMs)generated using UAV–LiDAR at different flight altitudes.For forests with a canopy cover<0.9,the mean absolute error(MAE)of understory DEMs from UAV–LiDAR at different flight altitudes was≤0.17 m and the root mean square error(RMSE)was≤0.24 m.However,for forests with a canopy cover≥0.9,the UAV–LiDAR flight altitude significantly affected the accuracy of understory DEMs.At the same flight altitude,the MAE and RMSE of the estimated elevation for forests with a canopy cover≥0.9 were approximately twice those of the estimated elevation for forests with a canopy cover<0.9.In forests with low canopy cover,it is possible to improve data collection efficiency by selecting a higher flight altitude.However,UAV–LiDAR flight altitudes significantly affected understory terrain estimation in forests with high canopy cover,it is essential to adopt terrain-following flight modes,reduce flight altitudes,and maintain a consistent flight altitude during longterm monitoring in high canopy cover forests.展开更多
Agricultural terraces are significant for food provision,environmental stability and sustainable resource management.However,the spatiotemporal evolution of terraces and their influence on food productivity in mountai...Agricultural terraces are significant for food provision,environmental stability and sustainable resource management.However,the spatiotemporal evolution of terraces and their influence on food productivity in mountainous landscapes remain poorly understood.Taking the Chinese Loess Plateau(LP)as an example,this study conducted multitemporal mapping of terraces and sloping croplands over three decades(1990-2020),systematically assessing their impacts on food output through terrain gradient analysis.The results indicated that:(1)the terraced area expanded in the past 30 years,particularly across steeper terrain gradients(third to fifth gradients);(2)sloping croplands predominantly occupied gentle slopes(first to second gradients),exhibiting area reduction correlating with urbanization processes;(3)the food provision increased extensively,with yield decreasing from southeast to northwest and regions of high yielding mainly in terraced fields;(4)over time,the variation of food provision correlated positively with the area of sloping cropland at low gradients,while at higher gradients,the expansion of terraces dominated the increase in food provision;(5)spatial clustering analysis revealed significant food productivity associated with high-density terrace distribution across steeper slope gradients.Low yields could be attributed to improper terrace management.This study clarified the impact of long-term terrace patterns on food provision and offered large-scale perspectives for terrace-based agriculture to enhance food security.Furthermore,the findings underscore the imperative of integrated land management in topographically complex regions,informing evidence-based policymaking for rational allocation and optimal utilization of terrace resources.展开更多
Terrain and geological formation are crucial natural environmental factors that constrain land use and land cover changes.Studying their regulatory role in regional land use and land cover changes is significant for g...Terrain and geological formation are crucial natural environmental factors that constrain land use and land cover changes.Studying their regulatory role in regional land use and land cover changes is significant for guiding regional land resource management.Taking the Danjiang River Basin in the Qinling Mountains of China as an example,this paper incorporates terrain(elevation,slope,and aspect)factors and geological formation to comprehensively analyse the differentiation characteristics of land use spatial patterns based on the examination of land use changes in 2000,2010,and 2020.Moreover,the geographical detector is employed to compare and analyse the effect of each factor on the spatial heterogeneity of land use.The results show that:(1)From 2000 to 2020,the areas of arable land and forestland in the Danjiang River Basin decreased while the areas of grassland,water areas,construction land,and unused land continuously increased.The comprehensive land use dynamics index was+0.09%,indicating a generally low level of land development.(2)Differences in the natural environmental factors of terrain and geological formation have a significant controlling effect on the spatial heterogeneity of land use.Specifically,there are notable differences in the advantageous distribution characteristics of various land use types across different levels of influencing factors.(3)The factor detection results reveal that geological formation has the strongest influence on the spatial heterogeneity of land use,followed by elevation and slope while aspect has the weakest influence.After the interaction among the factors,they nonlinearly enhance the explanation of spatial heterogeneity in land use.Overall,the influence of geological formation on the spatial heterogeneity of land use is greater than that of terrain factors.This study provides new geological evidence for natural resource management departments to conduct regional spatial planning,ecological and environmental protection and restoration,and land structure optimization and adjustment.展开更多
Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and ...Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and AW3D30 Digital Surface Model data,combined with three machine learning algorithms—Random Forest(RF),Back Propagation Neural Network(BPNN),and Extreme Gradient Boosting(XGBoost)—to evaluate the performance of canopy height inversion and understory terrain reconstruction.The analysis emphasizes the impact of topographic and vegetation-related factors on model accuracy.Results reveal that slope is the most influential variable,contributing three to five times more to model performance than other features.In low-slope areas,understory terrain tends to be underestimated,whereas high-slope areas often result in overestimation.Moreover,the Normalized Difference Vegetation Index(NDVI)and land cover types,particularly forests and grasslands,significantly affect prediction accuracy,with model performance showing heightened sensitivity to vegetation characteristics in these regions.Among the models tested,XGBoost demonstrated superior performance,achieving a canopy height bias of-0.06 m,a root mean square error(RMSE)of 4.69 m for canopy height,and an RMSE of 9.82 m for understory terrain.Its ability to capture complex nonlinear relationships and handle high-dimensional data underlines its robustness.While the RF model exhibited strong stability and resistance to noise,its accuracy lagged slightly behind XGBoost.The BPNN model,by contrast,struggled in areas with complex terrain.This study offers valuable insights into feature selection and optimization in remote sensing applications,providing a reference framework for enhancing the accuracy and efficiency of environmental monitoring practices.展开更多
Large-scale urban land expansion in mountainous and hilly areas(UEMH)has significantly altered the terrain in many Chinese cities,leading to various environmental and urban challenges.Despite its importance,there is l...Large-scale urban land expansion in mountainous and hilly areas(UEMH)has significantly altered the terrain in many Chinese cities,leading to various environmental and urban challenges.Despite its importance,there is limited nation-scale research that reveals the amount and the spatial variations of UEMH-induced terrain alteration.This research integrates the Global Annual Urban Dynamics dataset,the Global Basic Landform Unit dataset,the TanDEM-X DEM Change Map(DCM)dataset,Baidu Points-of-Interest(POI),and other auxiliary datasets to conduct a comprehensive analysis of terrain alteration induced by UEMH in China from 2012 to 2020.The results indicate that the country-wide UEMH-induced terrain alteration reached approximately 13 billion m^(3),which is about 100 times the volume of Hangzhou West Lake,and terrain alteration volume in over 300 counties exceeded 10 million m^(3).The Southwest and Southeast regions,which are ecologically sensitive and critical,feature the greatest alteration in terms of area and volume.The most significant terrain alteration in terms of intensity is observed in the Southwest and Hengduan Mountain Area.Additionally,there are significant spatial variations in the contributions of different urban functional zones to terrain alteration.Our findings indicate that urban land expansion in mountains and hills has significantly altered terrain in some regions of China,necessitating customized urban planning strategies for better managing mountainous urban land expansion and governance policies to address the geological,ecological,and urban development challenges.展开更多
Accurate digital terrain models(DTMs)are essential for a wide range of geospatial and environmental applications,yet their derivation in forested regions remains a significant challenge.Existing global DTMs,typically ...Accurate digital terrain models(DTMs)are essential for a wide range of geospatial and environmental applications,yet their derivation in forested regions remains a significant challenge.Existing global DTMs,typically generated from satellite stereo photogrammetry or interferometric synthetic aperture radar(InSAR),fail to accurately capture understory terrain due to limited penetration capabilities,resulting in elevation overestimation in densely vegetated areas.While airborne light detection and ranging(LiDAR)can provide high-accuracy DTMs,its limited spatial coverage and high acquisition cost hinder large-scale applications.Thus,there is an urgent need for a scalable and cost-effective approach to extract DTMs directly from satellite-derived digital surface models(DSMs).In this study,we propose a simple,interpretable understory terrain extraction method that utilizes canopy height data from Global Ecosystem Dynamics Investigation(GEDI)and Ice,Cloud,and Land Elevation Satellite-2(ICESat-2)to construct a tree height surface model,which is then subtracted from the stereo-derived DSM to generate the final DTM.By directly incorporating LiDAR constraints,the method avoids error propagation from multiple heterogeneous datasets and reduces reliance on ancillary inputs,ensuring ease of implementation and broad applicability.In contrast to machine learning-based terrain modeling methods,which are often prone to overfitting and data bias,the proposed approach is simple,interpretable,and robust across diverse forested landscapes.The accuracy of the resulting DTM was validated against airborne LiDAR reference data and compared with both the Copernicus Digital Elevation Model(DEM)and the forest and buildings removed DEM(FABDEM),a global bare-earth elevation model corrected for vegetation bias.The results indicate that the proposed DTM consistently outperforms the Copernicus DEM(CopDEM)and achieves accuracy comparable to FABDEM.In addition,its finer spatial resolution of 1 m,compared to the 30 m resolution of FABDEM,allows for more detailed terrain representation and better capture of fine-scale variation.This advantage is most pronounced in gently to moderately sloped areas,where the proposed DTM shows clearly higher accuracy than both the CopDEM and FABDEM.The results confirm that high-resolution DTMs can be effectively extracted from DSMs using spaceborne LiDAR constraints,offering a scalable solution for terrain modeling in forested environments where airborne LiDAR is unavailable.To illustrate the potential utility of the proposed DTM,we applied it to a fire risk mapping application based on topographic parameters such as slope,aspect,and elevation.This case highlights how improved terrain representation can support geospatial hazard assessments.展开更多
基金supported by the National Key Technology R&D Program of China under Grant No. 2015BAK34B00the National Key Research and Development Program of China under Grant No. 2016YFB1000102
文摘Regular expression matching is playing an important role in deep inspection. The rapid development of SDN and NFV makes the network more dynamic, bringing serious challenges to traditional deep inspection matching engines. However, state-of-theart matching methods often require a significant amount of pre-processing time and hence are not suitable for this fast updating scenario. In this paper, a novel matching engine called BFA is proposed to achieve high-speed regular expression matching with fast pre-processing. Experiments demonstrate that BFA obtains 5 to 20 times more update abilities compared to existing regular expression matching methods, and scales well on multi-core platforms.
基金Projects 50221402, 50490271 and 50025413 supported by the National Natural Science Foundation of Chinathe National Basic Research Program of China (2009CB219603, 2009 CB724601, 2006CB202209 and 2005CB221500)+1 种基金the Key Project of the Ministry of Education (306002)the Program for Changjiang Scholars and Innovative Research Teams in Universities of MOE (IRT0408)
文摘In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflect actual situations and facilitate their computation and analyses.Given the importance of model building, further processing methods about traditional seismic interpretation results from Landmark should be studied and the processed result can then be directly used in numerical simulation computations.Through this data conversion procedure, Landmark and FLAC(the international general stress software) are seamlessly connected.Thus, the format conversion between the two systems and the pre-and post-processing in simulation computation is realized.A practical application indicates that this method has many advantages such as simple operation, high accuracy of the element subdivision and high speed, which may definitely satisfy the actual needs of floor grid cutting.
基金supported by the National Natural Science Foundation of China(Nos.62003115 and 11972130)the Shenzhen Science and Technology Program,China(JCYJ20220818102207015)the Heilongjiang Touyan Team Program,China。
文摘The Low Earth Orbit(LEO)remote sensing satellite mega-constellation has the characteristics of large quantity and various types which make it have unique superiority in the realization of concurrent multiple tasks.However,the complexity of resource allocation is increased because of the large number of tasks and satellites.Therefore,the primary problem of implementing concurrent multiple tasks via LEO mega-constellation is to pre-process tasks and observation re-sources.To address the challenge,we propose a pre-processing algorithm for the mega-constellation based on highly Dynamic Spatio-Temporal Grids(DSTG).In the first stage,this paper describes the management model of mega-constellation and the multiple tasks.Then,the coding method of DSTG is proposed,based on which the description of complex mega-constellation observation resources is realized.In the third part,the DSTG algorithm is used to realize the processing of concurrent multiple tasks at multiple levels,such as task space attribute,time attribute and grid task importance evaluation.Finally,the simulation result of the proposed method in the case of constellation has been given to verify the effectiveness of concurrent multi-task pre-processing based on DSTG.The autonomous processing process of task decomposition and task fusion and mapping to grids,and the convenient indexing process of time window are verified.
基金supported by the National Natural Science Foundation of China(60902045)the National High-Tech Research and Developmeent Program of China(863 Program)(2011AA01A105)
文摘In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. However, the inter-block interference （IBI） and inter-carrier interference （ICI） in an OFDM system affect the performance. To mitigate IBI and ICI, some pre-processing approaches have been proposed based on full channel state information （CSI）, which improved the system performance. A pre-processing filter based on partial CSI at the transmitter is designed and investigated. The filter coefficient is given by the optimization processing, the symbol error rate （SER） is tested, and the computation complexity of the proposed scheme is analyzed. Computer simulation results show that the proposed pre-processing filter can effectively mitigate IBI and ICI and the performance can be improved. Compared with pre-processing approaches at the transmitter based on full CSI, the proposed scheme has high spectral efficiency, limited CSI feedback and low computation complexity.
文摘The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.
基金supported by the National Natural Science Foundation of China(Grant No.41630754)the State Key Laboratory of Cryospheric Science(SKLCS-ZZ-2017)CAS Key Technology Talent Program and Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering(2017490711)
文摘High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system's evolution.Preprocessing of ice cores has direct impacts on the data quality control for further analysis since the conventional ice core processing is time-consuming,produces qualitative data,leads to ice mass loss,and leads to risks of potential secondary pollution.However,over the past several decades,preprocessing of ice cores has received less attention than the improvement of ice drilling,the analytical methodology of various indices,and the researches on the climatic and environmental significance of ice core records.Therefore,this papers reviews the development of the processing for ice cores including framework,design as well as materials,analyzes the technical advantages and disadvantages of the different systems.In the past,continuous flowanalysis(CFA)has been successfully applied to process the polar ice cores.However,it is not suitable for ice cores outside polar region because of high level of particles,the memory effect between samples,and the filtration before injection.Ice core processing is a subtle and professional operation due to the fragility of the nonmetallic materials and the random distribution of particles and air bubbles in ice cores,which aggravates uncertainty in the measurements.The future developments of CFA are discussed in preprocessing,memory effect,challenge for brittle ice,coupling with real-time analysis and optimization of CFA in the field.Furthermore,non-polluting cutters with many different configurations could be designed to cut and scrape in multiple directions and to separate inner and outer portions of the core.This system also needs to be coupled with streamlined operation of packaging,coding,and stacking that can be implemented at high resolution and rate,avoiding manual intervention.At the same time,information of the longitudinal sections could be scanned andidentified,and then classified to obtain quantitative data.In addition,irregular ice volume and weight can also be obtained accurately.These improvements are recorded automatically via user-friendly interfaces.These innovations may be applied to other paleomedias with similar features and needs.
文摘Mathematical morphology is widely applicated in digital image procesing.Vari- ary morphology construction and algorithm being developed are used in deferent digital image processing.The basic idea of mathematical morphology is to use construction ele- ment measure image morphology for solving understand problem.The article presented advanced cellular neural network that forms mathematical morphological cellular neural network (MMCNN) equation to be suit for mathematical morphology filter.It gave the theo- ries of MMCNN dynamic extent and stable state.It is evidenced that arrived mathematical morphology filter through steady of dynamic process in definite condition.
基金Key Science and Technology Project of the Shanghai Committee of Science and Technology, China (No.06dz1200921)Major Basic Research Project of the Shanghai Committee of Science and Technology(No.08JC1400100)+1 种基金Shanghai Talent Developing Foundation, China(No.001)Specialized Foundation for Excellent Talent of Shanghai,China
文摘There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analysis. This paper proposes a data pre-processing model based on intelligent algorithms. Firstly, we introduce the integrated network platform of ocean observation. Next, the preprocessing model of data is presemed, and an imelligent cleaning model of data is proposed. Based on fuzzy clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means clustering. The proposed dynamic algorithm can automatically f＇md the new clustering center with the updated sample data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results through observation data analysis.
基金National Natural Science Foundation of China(No.61903291)Industrialization Project of Shaanxi Provincial Department of Education(No.18JC018)。
文摘A signal pre-processing method based on optimal variational mode decomposition(OVMD)is proposed to improve the efficiency and accuracy of local data filtering and analysis of edge nodes in distributed electromechanical systems.Firstly,the singular points of original signals are eliminated effectively by using the first-order difference method.Then the OVMD method is applied for signal modal decomposition.Furthermore,correlation analysis is conducted to determine the degree of correlation between each mode and the original signal,so as to accurately separate the real operating signal from noise signal.On the basis of theoretical analysis and simulation,an edge node pre-processing system for distributed electromechanical system is designed.Finally,by virtue of the signal-to-noise ratio(SNR)and root-mean-square error(RMSE)indicators,the signal pre-processing effect is evaluated.The experimental results show that the OVMD-based edge node pre-processing system can extract signals with different characteristics and improve the SNR of reconstructed signals.Due to its high fidelity and reliability,this system can also provide data quality assurance for subsequent system health monitoring and fault diagnosis.
文摘The solution of linear equation group can be applied to the oil exploration, the structure vibration analysis, the computational fluid dynamics, and other fields. When we make the in-depth analysis of some large or very large complicated structures, we must use the parallel algorithm with the aid of high-performance computers to solve complex problems. This paper introduces the implementation process having the parallel with sparse linear equations from the perspective of sparse linear equation group.
文摘Microarray data is inherently noisy due to the noise contaminated from various sources during the preparation of microarray slide and thus it greatly affects the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Efficient denoising is often a necessary and the first step to be taken before the image data is analyzed to compensate for data corruption and for effective utilization for these data. Hence preprocessing of microarray image is an essential to eliminate the background noise in order to enhance the image quality and effective quantification. Existing denoising techniques based on transformed domain have been utilized for microarray noise reduction with their own limitations. The objective of this paper is to introduce novel preprocessing techniques such as optimized spatial resolution (OSR) and spatial domain filtering (SDF) for reduction of noise from microarray data and reduction of error during quantification process for estimating the microarray spots accurately to determine expression level of genes. Besides combined optimized spatial resolution and spatial filtering is proposed and found improved denoising of microarray data with effective quantification of spots. The proposed method has been validated in microarray images of gene expression profiles of Myeloid Leukemia using Stanford Microarray Database with various quality measures such as signal to noise ratio, peak signal to noise ratio, image fidelity, structural content, absolute average difference and correlation quality. It was observed by quantitative analysis that the proposed technique is more efficient for denoising the microarray image which enables to make it suitable for effective quantification.
文摘Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.
基金supported by the Basic Science Center Program for Ordered Energy Conversion of the National Natural Science Foundation of China(No.52488201)the National Natural Science Foundation of China(No.52422606).
文摘Hilly terrain pipeline is a common form of pipeline in oil and gas storage and transportation industry.Due to the hilly terrain influence, the liquid at the elbow of the gathering pipeline is easy to flow back and accumulate to form slug flow, so it is necessary to remove the accumulated liquid by gas purging. In this paper, experiment is carried out in hilly terrain pipelines. Three flow patterns of stratified flow, slug flow and stratified entrained flow are observed. The process of gas purging accumulated liquid is divided into four stages, namely liquid accumulation, liquid rising, continuous outflow and tail outflow. At the same time, the flow pattern maps of each stage are drawn. The pressure drop signal is analyzed in time domain and frequency domain, and the contour map of pressure drop distribution is drawn. It is found that the ratio of range to average value can well distinguish the occurrence range of each flow pattern.Based on visualization, the transition process of slug flow to stratified flow and stratified entrained flow is studied, and the transition boundary prediction model is established. An image processing method is proposed to convert the image signal into a similarity curve, and PSD analysis is performed to calculate the slug frequency. The normal distribution is used to fit the slug frequency, and the predicted correlation is in good agreement with the experimental data.
文摘Background Three-dimensional terrain models are essential in domains such as video game development and film production.Because surface color is often correlated with terrain geometry,capturing this relationship is critical for generating realistic results.However,most existing methods synthesize either a heightmap or a texture without adequately modeling their inherent correlation.Methods We propose a method that jointly generates terrain heightmaps and textures using a latent diffusion model.First,we train the model in an unsupervised manner to randomly generate paired heightmaps and textures.Then,we perform supervised learning on an external adapter to enable user control via hand-drawn sketches.Results Experiments demonstrate that our approach supports intuitive terrain generation while preserving the correlation between heightmaps and textures.Conclusion Our method outperforms the two-stage and GAN-based baselines by ensuring structural coherence,in which textures naturally align with geometry,successfully accommodating both realistic landscapes and extreme user-defined shapes.
基金supported by the National Natural Science Foundation of China(No.32271876)the Research on Key Technologies of Intelligent Monitoring and Carbon Sink Metering of Forest Resources in Fujian Province(No.2022FKJ03)the Science and Technology Innovation Project of Fujian Agriculture and Forestry University(No.KFB23172A,KFB23173A).
文摘Unmanned aerial vehicle light detection and ranging(UAV–LiDAR)is a new method for collecting understory terrain data.The high estimation accuracy of understory terrain is crucial for accurate tree height measurement and forest resource surveys.The UAV–LiDAR flight altitude and forest canopy cover significantly impact the accuracy of understory terrain estimation.However,since no research examined their combined effects,we aimed to investigate this relationship.This will help optimize UAV–LiDAR flight parameters for understory terrain estimation and forest surveys across various canopy cover.This study analyzed the impacts of three flight altitudes and three canopy cover on the estimation accuracy of understory terrain.The results showed that when canopy cover exceeded a specific value,UAV–LiDAR flight altitudes significantly affected understory terrain estimation.Given a forest canopy cover,the reduction in ground point coverage increased significantly as the flight altitude increased;given a flight altitude,the higher the canopy cover,the more significant the reduction in ground point coverage.In forests with a canopy cover≥0.9,there were substantial differences in the accuracies of understory digital elevation models(DEMs)generated using UAV–LiDAR at different flight altitudes.For forests with a canopy cover<0.9,the mean absolute error(MAE)of understory DEMs from UAV–LiDAR at different flight altitudes was≤0.17 m and the root mean square error(RMSE)was≤0.24 m.However,for forests with a canopy cover≥0.9,the UAV–LiDAR flight altitude significantly affected the accuracy of understory DEMs.At the same flight altitude,the MAE and RMSE of the estimated elevation for forests with a canopy cover≥0.9 were approximately twice those of the estimated elevation for forests with a canopy cover<0.9.In forests with low canopy cover,it is possible to improve data collection efficiency by selecting a higher flight altitude.However,UAV–LiDAR flight altitudes significantly affected understory terrain estimation in forests with high canopy cover,it is essential to adopt terrain-following flight modes,reduce flight altitudes,and maintain a consistent flight altitude during longterm monitoring in high canopy cover forests.
基金supported by the National Natural Science Foundation of China(Grants No.U21A2011,41971129)the National Key Research and Development Program of China(Grant No.2022YFF1300403)the Distinguished Membership Project of the Youth Innovation Promotion Association of CAS(Grant No.Y201812)。
文摘Agricultural terraces are significant for food provision,environmental stability and sustainable resource management.However,the spatiotemporal evolution of terraces and their influence on food productivity in mountainous landscapes remain poorly understood.Taking the Chinese Loess Plateau(LP)as an example,this study conducted multitemporal mapping of terraces and sloping croplands over three decades(1990-2020),systematically assessing their impacts on food output through terrain gradient analysis.The results indicated that:(1)the terraced area expanded in the past 30 years,particularly across steeper terrain gradients(third to fifth gradients);(2)sloping croplands predominantly occupied gentle slopes(first to second gradients),exhibiting area reduction correlating with urbanization processes;(3)the food provision increased extensively,with yield decreasing from southeast to northwest and regions of high yielding mainly in terraced fields;(4)over time,the variation of food provision correlated positively with the area of sloping cropland at low gradients,while at higher gradients,the expansion of terraces dominated the increase in food provision;(5)spatial clustering analysis revealed significant food productivity associated with high-density terrace distribution across steeper slope gradients.Low yields could be attributed to improper terrace management.This study clarified the impact of long-term terrace patterns on food provision and offered large-scale perspectives for terrace-based agriculture to enhance food security.Furthermore,the findings underscore the imperative of integrated land management in topographically complex regions,informing evidence-based policymaking for rational allocation and optimal utilization of terrace resources.
基金supported by Geological survey project of China Geological Survey(DD20230481,DD20242461)。
文摘Terrain and geological formation are crucial natural environmental factors that constrain land use and land cover changes.Studying their regulatory role in regional land use and land cover changes is significant for guiding regional land resource management.Taking the Danjiang River Basin in the Qinling Mountains of China as an example,this paper incorporates terrain(elevation,slope,and aspect)factors and geological formation to comprehensively analyse the differentiation characteristics of land use spatial patterns based on the examination of land use changes in 2000,2010,and 2020.Moreover,the geographical detector is employed to compare and analyse the effect of each factor on the spatial heterogeneity of land use.The results show that:(1)From 2000 to 2020,the areas of arable land and forestland in the Danjiang River Basin decreased while the areas of grassland,water areas,construction land,and unused land continuously increased.The comprehensive land use dynamics index was+0.09%,indicating a generally low level of land development.(2)Differences in the natural environmental factors of terrain and geological formation have a significant controlling effect on the spatial heterogeneity of land use.Specifically,there are notable differences in the advantageous distribution characteristics of various land use types across different levels of influencing factors.(3)The factor detection results reveal that geological formation has the strongest influence on the spatial heterogeneity of land use,followed by elevation and slope while aspect has the weakest influence.After the interaction among the factors,they nonlinearly enhance the explanation of spatial heterogeneity in land use.Overall,the influence of geological formation on the spatial heterogeneity of land use is greater than that of terrain factors.This study provides new geological evidence for natural resource management departments to conduct regional spatial planning,ecological and environmental protection and restoration,and land structure optimization and adjustment.
基金funded by the National Key Research and Development Program(Grants No.2023YFE0207900)。
文摘Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and AW3D30 Digital Surface Model data,combined with three machine learning algorithms—Random Forest(RF),Back Propagation Neural Network(BPNN),and Extreme Gradient Boosting(XGBoost)—to evaluate the performance of canopy height inversion and understory terrain reconstruction.The analysis emphasizes the impact of topographic and vegetation-related factors on model accuracy.Results reveal that slope is the most influential variable,contributing three to five times more to model performance than other features.In low-slope areas,understory terrain tends to be underestimated,whereas high-slope areas often result in overestimation.Moreover,the Normalized Difference Vegetation Index(NDVI)and land cover types,particularly forests and grasslands,significantly affect prediction accuracy,with model performance showing heightened sensitivity to vegetation characteristics in these regions.Among the models tested,XGBoost demonstrated superior performance,achieving a canopy height bias of-0.06 m,a root mean square error(RMSE)of 4.69 m for canopy height,and an RMSE of 9.82 m for understory terrain.Its ability to capture complex nonlinear relationships and handle high-dimensional data underlines its robustness.While the RF model exhibited strong stability and resistance to noise,its accuracy lagged slightly behind XGBoost.The BPNN model,by contrast,struggled in areas with complex terrain.This study offers valuable insights into feature selection and optimization in remote sensing applications,providing a reference framework for enhancing the accuracy and efficiency of environmental monitoring practices.
基金supported by the National Natural Science Foundation of China(Grants No.42322110 and 42271415)。
文摘Large-scale urban land expansion in mountainous and hilly areas(UEMH)has significantly altered the terrain in many Chinese cities,leading to various environmental and urban challenges.Despite its importance,there is limited nation-scale research that reveals the amount and the spatial variations of UEMH-induced terrain alteration.This research integrates the Global Annual Urban Dynamics dataset,the Global Basic Landform Unit dataset,the TanDEM-X DEM Change Map(DCM)dataset,Baidu Points-of-Interest(POI),and other auxiliary datasets to conduct a comprehensive analysis of terrain alteration induced by UEMH in China from 2012 to 2020.The results indicate that the country-wide UEMH-induced terrain alteration reached approximately 13 billion m^(3),which is about 100 times the volume of Hangzhou West Lake,and terrain alteration volume in over 300 counties exceeded 10 million m^(3).The Southwest and Southeast regions,which are ecologically sensitive and critical,feature the greatest alteration in terms of area and volume.The most significant terrain alteration in terms of intensity is observed in the Southwest and Hengduan Mountain Area.Additionally,there are significant spatial variations in the contributions of different urban functional zones to terrain alteration.Our findings indicate that urban land expansion in mountains and hills has significantly altered terrain in some regions of China,necessitating customized urban planning strategies for better managing mountainous urban land expansion and governance policies to address the geological,ecological,and urban development challenges.
基金supported by the National Key Research and Development Program of China(Nos.SQ2022YFB3900026 and 2022YFB3903305)supported by the Leading Talents of Guangdong Pearl River Talent Program(No.2021CX02S024)the Guangdong S&T programme(No.2024B1212050011).
文摘Accurate digital terrain models(DTMs)are essential for a wide range of geospatial and environmental applications,yet their derivation in forested regions remains a significant challenge.Existing global DTMs,typically generated from satellite stereo photogrammetry or interferometric synthetic aperture radar(InSAR),fail to accurately capture understory terrain due to limited penetration capabilities,resulting in elevation overestimation in densely vegetated areas.While airborne light detection and ranging(LiDAR)can provide high-accuracy DTMs,its limited spatial coverage and high acquisition cost hinder large-scale applications.Thus,there is an urgent need for a scalable and cost-effective approach to extract DTMs directly from satellite-derived digital surface models(DSMs).In this study,we propose a simple,interpretable understory terrain extraction method that utilizes canopy height data from Global Ecosystem Dynamics Investigation(GEDI)and Ice,Cloud,and Land Elevation Satellite-2(ICESat-2)to construct a tree height surface model,which is then subtracted from the stereo-derived DSM to generate the final DTM.By directly incorporating LiDAR constraints,the method avoids error propagation from multiple heterogeneous datasets and reduces reliance on ancillary inputs,ensuring ease of implementation and broad applicability.In contrast to machine learning-based terrain modeling methods,which are often prone to overfitting and data bias,the proposed approach is simple,interpretable,and robust across diverse forested landscapes.The accuracy of the resulting DTM was validated against airborne LiDAR reference data and compared with both the Copernicus Digital Elevation Model(DEM)and the forest and buildings removed DEM(FABDEM),a global bare-earth elevation model corrected for vegetation bias.The results indicate that the proposed DTM consistently outperforms the Copernicus DEM(CopDEM)and achieves accuracy comparable to FABDEM.In addition,its finer spatial resolution of 1 m,compared to the 30 m resolution of FABDEM,allows for more detailed terrain representation and better capture of fine-scale variation.This advantage is most pronounced in gently to moderately sloped areas,where the proposed DTM shows clearly higher accuracy than both the CopDEM and FABDEM.The results confirm that high-resolution DTMs can be effectively extracted from DSMs using spaceborne LiDAR constraints,offering a scalable solution for terrain modeling in forested environments where airborne LiDAR is unavailable.To illustrate the potential utility of the proposed DTM,we applied it to a fire risk mapping application based on topographic parameters such as slope,aspect,and elevation.This case highlights how improved terrain representation can support geospatial hazard assessments.
