In order to realize an optimal balance between the efficiency and reliability requirements ofroad models,a road modeling method for digital maps based on cardinal spline is studied.First,the cardinal spline is chosen ...In order to realize an optimal balance between the efficiency and reliability requirements ofroad models,a road modeling method for digital maps based on cardinal spline is studied.First,the cardinal spline is chosen to establish an initial road model,which is specified by a series of control points and tension parameters.Then,in view of the initial road model,a gradual optimization algorithm,which can determine the reasonable control points and optimal tension parameters according to the degree of the change of road curvature,is proposed to determine the final road model.Finally,the proposed road modeling method is verified a d evaluated through experiments,and it is compared with the conventional method for digital maps based on the B-spline.The results show that the proposed method can resize a neaoptimal balance between the efficiency and reliability requirements.Compared with the conventional method based on the B-spline,this method occupies less data storage and achieves higher accuracy.展开更多
The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo ext...The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo extensive in-house tests and prolonged field tests for certification and approval before operational deployment,leading to high costs,delays,and operational disruptions.This paper introduces a GNSS-based train control localization framework which eliminates the need for on-site testing by leveraging train movement dynamics and 3D environment modeling to create a zero on-site testing platform.The proposed framework simulates train movement and the surrounding 3D environment using collected railway line location data and environmental attributes to generate realistic multipath signals and obscuration effects.This approach enables comprehensive laboratory-based case studies for train localization,reducing the huge amount test of needed for physical field trials.The framework is established in house,using the data collected at the Test Base of China Academy of Railway Sciences(Circular Railway).Results from the open area and cutting environment tests demonstrate high localization accuracy repeatability within the simulated environment,validating the feasibility and effectiveness of zero on-site testing for GNSS-based train control systems.This research highlights the potential of GNSS simulation platforms in enhancing cost efficiency,operational safety,and accuracy for future digital railways.展开更多
Sampling design(SD) plays a crucial role in providing reliable input for digital soil mapping(DSM) and increasing its efficiency.Sampling design, with a predetermined sample size and consideration of budget and spatia...Sampling design(SD) plays a crucial role in providing reliable input for digital soil mapping(DSM) and increasing its efficiency.Sampling design, with a predetermined sample size and consideration of budget and spatial variability, is a selection procedure for identifying a set of sample locations spread over a geographical space or with a good feature space coverage. A good feature space coverage ensures accurate estimation of regression parameters, while spatial coverage contributes to effective spatial interpolation.First, we review several statistical and geometric SDs that mainly optimize the sampling pattern in a geographical space and illustrate the strengths and weaknesses of these SDs by considering spatial coverage, simplicity, accuracy, and efficiency. Furthermore, Latin hypercube sampling, which obtains a full representation of multivariate distribution in geographical space, is described in detail for its development, improvement, and application. In addition, we discuss the fuzzy k-means sampling, response surface sampling, and Kennard-Stone sampling, which optimize sampling patterns in a feature space. We then discuss some practical applications that are mainly addressed by the conditioned Latin hypercube sampling with the flexibility and feasibility of adding multiple optimization criteria. We also discuss different methods of validation, an important stage of DSM, and conclude that an independent dataset selected from the probability sampling is superior for its free model assumptions. For future work, we recommend: 1) exploring SDs with both good spatial coverage and feature space coverage; 2) uncovering the real impacts of an SD on the integral DSM procedure;and 3) testing the feasibility and contribution of SDs in three-dimensional(3 D) DSM with variability for multiple layers.展开更多
Digital soil mapping (DSM) aims to produce detailed maps of soil properties or soil classes to improve agricultural management and soil quality assessment. Optimized sampling design can reduce the substantial costs an...Digital soil mapping (DSM) aims to produce detailed maps of soil properties or soil classes to improve agricultural management and soil quality assessment. Optimized sampling design can reduce the substantial costs and efforts associated with sampling, profile description, and laboratory analysis. The purpose of this study was to compare common sampling designs for DSM, including grid sampling (GS), grid random sampling (GRS), stratified random sampling (StRS), and conditioned Latin hypercube sampling (cLHS). In an agricultural field (11 ha) in Quebec, Canada, a total of unique 118 locations were selected using each of the four sampling designs (45 locations each), and additional 30 sample locations were selected as an independent testing dataset (evaluation dataset). Soil visible near-infrared (Vis-NIR) spectra were collected in situ at the 148 locations (1 m depth), and soil cores were collected from a subset of 32 locations and subdivided at 10-cm depth intervals, totaling 251 samples. The Cubist model was used to elucidate the relationship between Vis-NIR spectra and soil properties (soil organic matter (SOM) and clay), which was then used to predict the soil properties at all 148 sample locations. Digital maps of soil properties at multiple depths for the entire field (148 sample locations) were prepared using a quantile random forest model to obtain complete model maps (CM-maps). Soil properties were also mapped using the samples from each of the 45 locations for each sampling design to obtain sampling design maps (SD-maps). The SD-maps were evaluated using the independent testing dataset (30 sample locations), and the spatial distribution and model uncertainty of each SD-map were compared with those of the corresponding CM-map. The spatial and feature space coverage were compared across the four sampling designs. The results showed that GS resulted in the most even spatial coverage, cLHS resulted in the best coverage of the feature space, and GS and cLHS resulted in similar prediction accuracies and spatial distributions of soil properties. The SOM content was underestimated using GRS, with large errors at 0–50 cm depth, due to some values not being captured by this sampling design, whereas larger errors for the deeper soil layers were produced using StRS. Predictions of SOM and clay contents had higher accuracy for topsoil (0–30 cm) than for deep subsoil (60–100 cm). It was concluded that the soil sampling designs with either good spatial coverage or feature space coverage can provide good accuracy in 3D DSM, but their performances may be different for different soil properties.展开更多
Digital maps of soil properties are now widely available.End-users now can access several digital soil mapping(DSM)products of soil properties,produced using different models,calibration/training data,and covariates a...Digital maps of soil properties are now widely available.End-users now can access several digital soil mapping(DSM)products of soil properties,produced using different models,calibration/training data,and covariates at various spatial scales from global to local.Therefore,there is an urgent need to provide easy-to-understand tools to communicate map uncertainty and help end-users assess the reliability of DSM products for use at local scales.In this study,we used a large amount of hand-feel soil texture(HFST)data to assess the performance of various published DSM products on the prediction of soil particle size distribution in Central France.We tested four DSM products for soil texture prediction developed at various scales(global,continental,national,and regional)by comparing their predictions with approximately 3200 HFST observations realized on a 1:50000 soil survey conducted after release of these DSM products.We used both visual comparisons and quantitative indicators to match the DSM predictions and HFST observations.The comparison between the low-cost HFST observations and DSM predictions clearly showed the applicability of various DSM products,with the prediction accuracy increasing from global to regional predictions.This simple evaluation can determine which products can be used at the local scale and if more accurate DSM products are required.展开更多
The geolocation of ground targets by airborne image sensors is an important task for unmanned aerial vehicles or surveillance aircraft.This paper proposes an Iterative Geolocation based on Cross-view Image Registratio...The geolocation of ground targets by airborne image sensors is an important task for unmanned aerial vehicles or surveillance aircraft.This paper proposes an Iterative Geolocation based on Cross-view Image Registration(IGCIR)that can provide real-time target location results with high precision.The proposed method has two key features.First,a cross-view image registration process is introduced,including a projective transformation and a two-stage multi-sensor registration.This process utilizes both gradient information and phase information of cross-view images.This allows the registration process to reach a good balance between matching precision and computational efficiency.By matching the airborne camera view to the preloaded digital map,the geolocation accuracy can reach the accuracy level of the digital map for any ground target appearing in the airborne camera view.Second,the proposed method uses the registration results to perform an iteration process,which compensates for the bias of the strap-down initial navigation module online.Although it is challenging to provide cross-view registration results with high frequency,such an iteration process allows the method to generate real-time,highly accurate location results.The effectiveness of the proposed IGCIR method is verified by a series of flying-test experiments.The results show that the location accuracy of the method can reach 4.18 m(at 10 km standoff distance).展开更多
It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimens...It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.展开更多
To deal with the global and regional issues including food security, climate change, land degradation, biodiversity loss, water resource management, and ecosystem health, detailed accurate spatial soil information is ...To deal with the global and regional issues including food security, climate change, land degradation, biodiversity loss, water resource management, and ecosystem health, detailed accurate spatial soil information is urgently needed. This drives the worldwide development of digital soil mapping. In recent years, significant progresses have been made in different aspects of digital soil mapping. The main purpose of this paper is to provide a review for the major progresses of digital soil mapping in the last decade. First, we briefly described the rise of digital soil mapping and outlined important milestones and their influence, and main paradigms in digital soil mapping. Then, we reviewed the progresses in legacy soil data, environmental covariates, soil sampling, predictive models and the applications of digital soil mapping products. Finally, we summarized the main trends and future prospect as revealed by studies up to now. We concluded that although the digital soil mapping is now moving towards mature to meet various demands of soil information, challenges including new theories, methodologies and applications of digital soil mapping, especially for highly heterogeneous and human-affected environments, still exist and need to be addressed in the future.展开更多
Selecting a proper set of covariates is one of the most important factors that influence the accuracy of digital soil mapping(DSM).The statistical or machine learning methods for selecting DSM covariates are not avail...Selecting a proper set of covariates is one of the most important factors that influence the accuracy of digital soil mapping(DSM).The statistical or machine learning methods for selecting DSM covariates are not available for those situations with limited samples.To solve the problem,this paper proposed a case-based method which could formalize the covariate selection knowledge contained in practical DSM applications.The proposed method trained Random Forest(RF)classifiers with DSM cases extracted from the practical DSM applications and then used the trained classifiers to determine whether each one potential covariate should be used in a new DSM application.In this study,we took topographic covariates as examples of covariates and extracted 191 DSM cases from 56 peer-reviewed journal articles to evaluate the performance of the proposed case-based method by Leave-One-Out cross validation.Compared with a novices’commonly-used way of selecting DSM covariates,the proposed case-based method improved more than 30%accuracy according to three quantitative evaluation indices(i.e.,recall,precision,and F1-score).The proposed method could be also applied to selecting the proper set of covariates for other similar geographical modeling domains,such as landslide susceptibility mapping,and species distribution modeling.展开更多
Soil type maps at the scale of I Z 1 000 000 are used extensively to provide soil spatial distribution information for soil erosion assessment and watershed management models in China. However, the soil property maps ...Soil type maps at the scale of I Z 1 000 000 are used extensively to provide soil spatial distribution information for soil erosion assessment and watershed management models in China. However, the soil property maps produced through conventional direct linking method usually suffer low accuracy as well as the lack of spatial details within a soil type polygon. This paper presents an effective method to produce detailed soil property map based on representative samples which were extracted from each polygon on the 1 ： 1 000 000 soil type map. The representative sample of each polygon is defined as the location that can represent the largest area within the polygon. The representativeness of a candidate sample is determined by calculating the soil-forming environment condition similarities between the sample and other locations. Once the representative sample of each polygon has been chosen, the property values of the existing typical samples are assigned to the corresponding representative samples with the same soil type. Finally, based on these representative samples, the detailed soil property map could be produced by using existing digital soil mapping methods. The case study in XuanCheng City, Anhui Province of China, demonstrated the proposed method could produce soil property map at a higher level of spatial details and accuracy： 1） The soil organic matter （SOM） map produced based on the representative samples can not only depict the detailed spatial distribution of SOM within a soil type polygon but also largely reduce the abrupt change of soil property at the boundaries of two adjacent polygons. 2） The Root Mean Squared Error （RMSE） of the SOM map based on the representative samples is 1.61, and it is 1.37 for the SOM map produced by using conventional direct linking method. Therefore, the proposed method is an effective approach to produce spatial detailed soil property map with higher accuracy for environment simulation models.展开更多
Soil salinization is one of the most important causes of land degradation and desertification,especially in arid and semi-arid areas.The dynamic monitoring of soil salinization is of great significance to land managem...Soil salinization is one of the most important causes of land degradation and desertification,especially in arid and semi-arid areas.The dynamic monitoring of soil salinization is of great significance to land management,agricultural activities,water quality,and sustainable development.The remote sensing images taken by the synthetic aperture radar(SAR)Sentinel-1 and the multispectral satellite Sentinel-2 with high resolution and short revisit period have the potential to monitor the spatial distribution of soil attribute information on a large area;however,there are limited studies on the combination of Sentinel-1 and Sentinel-2 for digital mapping of soil salinization.Therefore,in this study,we used topography indices derived from digital elevation model(DEM),SAR indices generated by Sentinel-1,and vegetation indices generated by Sentinel-2 to map soil salinization in the Ogan-Kuqa River Oasis located in the central and northern Tarim Basin in Xinjiang of China,and evaluated the potential of multi-source sensors to predict soil salinity.Using the soil electrical conductivity(EC)values of 70 ground sampling sites as the target variable and the optimal environmental factors as the predictive variable,we constructed three soil salinity inversion models based on classification and regression tree(CART),random forest(RF),and extreme gradient boosting(XGBoost).Then,we evaluated the prediction ability of different models through the five-fold cross validation.The prediction accuracy of XGBoost model is better than those of CART and RF,and soil salinity predicted by the three models has similar spatial distribution characteristics.Compared with the combination of topography indices and vegetation indices,the addition of SAR indices effectively improves the prediction accuracy of the model.In general,the method of soil salinity prediction based on multi-source sensor combination is better than that based on a single sensor.In addition,SAR indices,vegetation indices,and topography indices are all effective variables for soil salinity prediction.Weighted Difference Vegetation Index(WDVI)is designated as the most important variable in these variables,followed by DEM.The results showed that the high-resolution radar Sentinel-1 and multispectral Sentinel-2 have the potential to develop soil salinity prediction model.展开更多
Ice and snow domint the land features in Antarctica. The great brightness and poorcontrast of ice and snow and streaking noise in satellite image make the procedure of image processing difficult. On the other hand ho...Ice and snow domint the land features in Antarctica. The great brightness and poorcontrast of ice and snow and streaking noise in satellite image make the procedure of image processing difficult. On the other hand however, the contrast between bare rock land/sea water and ice/snow is so high that the details of image will be overcompressed.In the light of characteristics of satellite image in Antarctica, a filtering to remove streaking noise has adn discussed. Based on automatic identify classification to enhance the details of objects and the method and theory of digital rectification of satellite image with ground control points measured from field survey are also presented.展开更多
Digital geological mapping fundamentally broke through the traditional working pattern,successfully carried out the geological mapping digitalization.By using the RGMAP system to field digital geological mapping,the a...Digital geological mapping fundamentally broke through the traditional working pattern,successfully carried out the geological mapping digitalization.By using the RGMAP system to field digital geological mapping,the authors summarized the method of work and the work flow of the RGMAPGIS during the field geological survey.First,we prepared material,set up the PRB gallery,then put the geographic base map under the background maplayer and organizing the field hand map,forming the field factual datum map.At last,the geological space database is formed.展开更多
OBJECTIVE： To construct a protein-protein interaction（PPI） network in hypertension patients with blood-stasis syndrome（BSS） by using digital gene expression（DGE） sequencing and database mining techniques.METHOD...OBJECTIVE： To construct a protein-protein interaction（PPI） network in hypertension patients with blood-stasis syndrome（BSS） by using digital gene expression（DGE） sequencing and database mining techniques.METHODS： DGE analysis based on the Solexa Genome Analyzer platform was performed on vascular endothelial cells incubated with serum of hypertension patients with BSS. The differentially expressed genes were f iltered by comparing the expression levels between the different experimental groups. Then functional categories and e nriched pathways of the unique genes for BSS were analyzed using Database for Annotation, Visualization and Integrated Discovery（DAVID） to select those in the enrichment pathways. I nterologous Interaction Database（I2D） was used to construct PPI networks with the selected genes for hypertension patients with BSS. The potential candidate genes related to BSS were identif ied by comparing the number of relationships among genes. Confi rmed by quantitative reverse transcription-polymerase chain reaction（q RTPCR）, gene ontology（GO） analysis was used to infer the functional annotations of the potential candidate genes for BSS.RESULTS： With gene enrichment analysis using DAVID, a list of 58 genes was chosen from the unique genes. The selected 58 genes were analyzed using I2 D, and a PPI network was constructed. Based on the network analysis results, candidate genes for BSS were identifi ed：DDIT3, JUN, HSPA8, NFIL3, HSPA5, HIST2H2 BE, H3F3 B, CEBPB, SAT1 and GADD45 A. Verif ied through qRT-PCR and analyzed by GO, the functional annotations of the potential candidate genes were explored.CONCLUSION： Compared with previous methodologies reported in the literature, the present DGE analysis and data mining method have shown a great improvement in analyzing BSS.展开更多
The components of map information are analyzed theoretically in this paper,and the map information includes mainly the spatial information,attributive information and temporal characteristics information.Then the digi...The components of map information are analyzed theoretically in this paper,and the map information includes mainly the spatial information,attributive information and temporal characteristics information.Then the digital map entity is defined according to construction characteristics of the map information.Finally,on the basis of the analyses of the construction characteristics of digital map entity and present conceptual model of digital map database,an abstracted conceptual model of digital map database is presented.And the Normal Form theory of relational database is discussed particularly.展开更多
A new lane-level road modeling method based on cardinal spline is proposed for the special intersections which are covered by vegetation or artificial landscape in their central regions.First,cardinal spline curves ar...A new lane-level road modeling method based on cardinal spline is proposed for the special intersections which are covered by vegetation or artificial landscape in their central regions.First,cardinal spline curves are used to fit the virtual lanes inside special intersections,and an initial road model is established using a series of control points and tension parameters.Then,the progressive optimization algorithm is proposed to determine the final road model based on the initial model.The algorithm determines reasonable control points and optimal tension parameters according to the degree of road curvature changes,so as to achieve a balance between the efficiency and reliability of the road model.Finally,the proposed intersection model is verified and evaluated through experiments.The results show that this method can effectively describe the lane-level topological relationship and geometric details of this kind of special intersection where the central area is covered by vegetation or artificial landscape,and can achieve a good balance between the efficiency and reliability of the road model.展开更多
The colorful satellite image maps with the scale of 1∶100000 were made by processing the parameters-on-satellite under the condition of no data of field surveying.The purpose is to ensure the smooth performance of th...The colorful satellite image maps with the scale of 1∶100000 were made by processing the parameters-on-satellite under the condition of no data of field surveying.The purpose is to ensure the smooth performance of the choice of expedition route,navigation and research task before the Chinese National Antarctic Research Expedition(CHINARE)first made researches on the Grove Mountains.Moreover,on the basis of the visual interpretation of the satellite image,we preliminarily analyze and discuss the relief and landform,blue ice and meteorite distribution characteristics in the Grove Mountains.展开更多
Since 1894,the Geological Survey of Western Australia(GSWA)has released 14 versions of the‘Geological Map of Western Australia’.The latest in this series,published in December 2015,is the first bedrock geology map
The first Ukrainian using experience of multispectral space scanning for digital soil mapping is described in this paper. Methodical approaches for detailed soil observation of Ukrainian forest regions are elaborated ...The first Ukrainian using experience of multispectral space scanning for digital soil mapping is described in this paper. Methodical approaches for detailed soil observation of Ukrainian forest regions are elaborated based on modem mapping principles. For the first time in Ukraine, digital soil maps based on GIS （geographic information system） were obtained for individual farms. In GIS based on space images and digital relief models, the medium-scale and large-scale soil maps were created by geo-statistical methods. According to elaborated methods, modem digital soil mapping should provide all combined works： remote sensing and traditional soil observations. The modem digital soil mapping should be based just on quantitative principles： on remote sensing data, geomorphologic field parameters, and chemical analyses. The methodological approaches, which were used for the first time in Ukraine during digital soil mapping by remote sensing methods, are described in this paper.展开更多
The continuous development of science and technology has promoted the basic of surveying and mapping technology. More and more advanced surveying and mapping technology has been applied to geological engineering surve...The continuous development of science and technology has promoted the basic of surveying and mapping technology. More and more advanced surveying and mapping technology has been applied to geological engineering survey. The traditional geological survey technology has many defects, which affect the normal development of geological engineering survey. Therefore, we must actively apply digital surveying and mapping technology to improve the quality and efficiency of the survey. This paper first discusses the digital surveying and mapping technology, then analyzes the digital surveying and mapping technology, and finally puts forward some suggestions on the specific application of unmanned aerial vehicle remote sensing surveying and mapping technology in geological engineering survey, hoping to promote the progress of geological engineering survey.展开更多
基金The National Natural Science Foundation of China(No.61273236)the National Key Research and Development Plan of China(No.2016YFC0802706,2017YFC0804804)+1 种基金the Program for Special Talents in Six Major Fields of Jiangsu Province(No.2017JXQC-003)the Project of Beijing Municipal Science and Technology Commission(No.Z161100001416001)
文摘In order to realize an optimal balance between the efficiency and reliability requirements ofroad models,a road modeling method for digital maps based on cardinal spline is studied.First,the cardinal spline is chosen to establish an initial road model,which is specified by a series of control points and tension parameters.Then,in view of the initial road model,a gradual optimization algorithm,which can determine the reasonable control points and optimal tension parameters according to the degree of the change of road curvature,is proposed to determine the final road model.Finally,the proposed road modeling method is verified a d evaluated through experiments,and it is compared with the conventional method for digital maps based on the B-spline.The results show that the proposed method can resize a neaoptimal balance between the efficiency and reliability requirements.Compared with the conventional method based on the B-spline,this method occupies less data storage and achieves higher accuracy.
基金supported by the National Natural Science Foundation of China(62027809,U2268206,T2222015,U2468202).
文摘The integration of Global Navigation Satellite System(GNSS)technology into railway train control systems is a crucial step toward achieving the vision of a digital railway.Traditional train control systems undergo extensive in-house tests and prolonged field tests for certification and approval before operational deployment,leading to high costs,delays,and operational disruptions.This paper introduces a GNSS-based train control localization framework which eliminates the need for on-site testing by leveraging train movement dynamics and 3D environment modeling to create a zero on-site testing platform.The proposed framework simulates train movement and the surrounding 3D environment using collected railway line location data and environmental attributes to generate realistic multipath signals and obscuration effects.This approach enables comprehensive laboratory-based case studies for train localization,reducing the huge amount test of needed for physical field trials.The framework is established in house,using the data collected at the Test Base of China Academy of Railway Sciences(Circular Railway).Results from the open area and cutting environment tests demonstrate high localization accuracy repeatability within the simulated environment,validating the feasibility and effectiveness of zero on-site testing for GNSS-based train control systems.This research highlights the potential of GNSS simulation platforms in enhancing cost efficiency,operational safety,and accuracy for future digital railways.
基金funded by the Natural Science and Engineering Research Council (NSERC) of Canada (No. RGPIN-2014-04100)
文摘Sampling design(SD) plays a crucial role in providing reliable input for digital soil mapping(DSM) and increasing its efficiency.Sampling design, with a predetermined sample size and consideration of budget and spatial variability, is a selection procedure for identifying a set of sample locations spread over a geographical space or with a good feature space coverage. A good feature space coverage ensures accurate estimation of regression parameters, while spatial coverage contributes to effective spatial interpolation.First, we review several statistical and geometric SDs that mainly optimize the sampling pattern in a geographical space and illustrate the strengths and weaknesses of these SDs by considering spatial coverage, simplicity, accuracy, and efficiency. Furthermore, Latin hypercube sampling, which obtains a full representation of multivariate distribution in geographical space, is described in detail for its development, improvement, and application. In addition, we discuss the fuzzy k-means sampling, response surface sampling, and Kennard-Stone sampling, which optimize sampling patterns in a feature space. We then discuss some practical applications that are mainly addressed by the conditioned Latin hypercube sampling with the flexibility and feasibility of adding multiple optimization criteria. We also discuss different methods of validation, an important stage of DSM, and conclude that an independent dataset selected from the probability sampling is superior for its free model assumptions. For future work, we recommend: 1) exploring SDs with both good spatial coverage and feature space coverage; 2) uncovering the real impacts of an SD on the integral DSM procedure;and 3) testing the feasibility and contribution of SDs in three-dimensional(3 D) DSM with variability for multiple layers.
基金the National Science and Engineering Research Council of Canada(No.RGPIN-2014-04100)for funding this project.
文摘Digital soil mapping (DSM) aims to produce detailed maps of soil properties or soil classes to improve agricultural management and soil quality assessment. Optimized sampling design can reduce the substantial costs and efforts associated with sampling, profile description, and laboratory analysis. The purpose of this study was to compare common sampling designs for DSM, including grid sampling (GS), grid random sampling (GRS), stratified random sampling (StRS), and conditioned Latin hypercube sampling (cLHS). In an agricultural field (11 ha) in Quebec, Canada, a total of unique 118 locations were selected using each of the four sampling designs (45 locations each), and additional 30 sample locations were selected as an independent testing dataset (evaluation dataset). Soil visible near-infrared (Vis-NIR) spectra were collected in situ at the 148 locations (1 m depth), and soil cores were collected from a subset of 32 locations and subdivided at 10-cm depth intervals, totaling 251 samples. The Cubist model was used to elucidate the relationship between Vis-NIR spectra and soil properties (soil organic matter (SOM) and clay), which was then used to predict the soil properties at all 148 sample locations. Digital maps of soil properties at multiple depths for the entire field (148 sample locations) were prepared using a quantile random forest model to obtain complete model maps (CM-maps). Soil properties were also mapped using the samples from each of the 45 locations for each sampling design to obtain sampling design maps (SD-maps). The SD-maps were evaluated using the independent testing dataset (30 sample locations), and the spatial distribution and model uncertainty of each SD-map were compared with those of the corresponding CM-map. The spatial and feature space coverage were compared across the four sampling designs. The results showed that GS resulted in the most even spatial coverage, cLHS resulted in the best coverage of the feature space, and GS and cLHS resulted in similar prediction accuracies and spatial distributions of soil properties. The SOM content was underestimated using GRS, with large errors at 0–50 cm depth, due to some values not being captured by this sampling design, whereas larger errors for the deeper soil layers were produced using StRS. Predictions of SOM and clay contents had higher accuracy for topsoil (0–30 cm) than for deep subsoil (60–100 cm). It was concluded that the soil sampling designs with either good spatial coverage or feature space coverage can provide good accuracy in 3D DSM, but their performances may be different for different soil properties.
文摘Digital maps of soil properties are now widely available.End-users now can access several digital soil mapping(DSM)products of soil properties,produced using different models,calibration/training data,and covariates at various spatial scales from global to local.Therefore,there is an urgent need to provide easy-to-understand tools to communicate map uncertainty and help end-users assess the reliability of DSM products for use at local scales.In this study,we used a large amount of hand-feel soil texture(HFST)data to assess the performance of various published DSM products on the prediction of soil particle size distribution in Central France.We tested four DSM products for soil texture prediction developed at various scales(global,continental,national,and regional)by comparing their predictions with approximately 3200 HFST observations realized on a 1:50000 soil survey conducted after release of these DSM products.We used both visual comparisons and quantitative indicators to match the DSM predictions and HFST observations.The comparison between the low-cost HFST observations and DSM predictions clearly showed the applicability of various DSM products,with the prediction accuracy increasing from global to regional predictions.This simple evaluation can determine which products can be used at the local scale and if more accurate DSM products are required.
基金supported by the National Level Project of China(No.52-L0D01-0613-20/22)。
文摘The geolocation of ground targets by airborne image sensors is an important task for unmanned aerial vehicles or surveillance aircraft.This paper proposes an Iterative Geolocation based on Cross-view Image Registration(IGCIR)that can provide real-time target location results with high precision.The proposed method has two key features.First,a cross-view image registration process is introduced,including a projective transformation and a two-stage multi-sensor registration.This process utilizes both gradient information and phase information of cross-view images.This allows the registration process to reach a good balance between matching precision and computational efficiency.By matching the airborne camera view to the preloaded digital map,the geolocation accuracy can reach the accuracy level of the digital map for any ground target appearing in the airborne camera view.Second,the proposed method uses the registration results to perform an iteration process,which compensates for the bias of the strap-down initial navigation module online.Although it is challenging to provide cross-view registration results with high frequency,such an iteration process allows the method to generate real-time,highly accurate location results.The effectiveness of the proposed IGCIR method is verified by a series of flying-test experiments.The results show that the location accuracy of the method can reach 4.18 m(at 10 km standoff distance).
基金supported by grants from the Human Resources Development program (Grant No.20204010600250)the Training Program of CCUS for the Green Growth (Grant No.20214000000500)by the Korea Institute of Energy Technology Evaluation and Planning (KETEP)funded by the Ministry of Trade,Industry,and Energy of the Korean Government (MOTIE).
文摘It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.
基金supported by the National Natural Science Foundation of China (91325301, 41571130051)
文摘To deal with the global and regional issues including food security, climate change, land degradation, biodiversity loss, water resource management, and ecosystem health, detailed accurate spatial soil information is urgently needed. This drives the worldwide development of digital soil mapping. In recent years, significant progresses have been made in different aspects of digital soil mapping. The main purpose of this paper is to provide a review for the major progresses of digital soil mapping in the last decade. First, we briefly described the rise of digital soil mapping and outlined important milestones and their influence, and main paradigms in digital soil mapping. Then, we reviewed the progresses in legacy soil data, environmental covariates, soil sampling, predictive models and the applications of digital soil mapping products. Finally, we summarized the main trends and future prospect as revealed by studies up to now. We concluded that although the digital soil mapping is now moving towards mature to meet various demands of soil information, challenges including new theories, methodologies and applications of digital soil mapping, especially for highly heterogeneous and human-affected environments, still exist and need to be addressed in the future.
基金supported by grants from the National Natural Science Foundation of China(41431177 and 41871300)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD),China+4 种基金the Innovation Project of State Key Laboratory of Resources and Environmental Information System(LREIS),China(O88RA20CYA)the Outstanding Innovation Team in Colleges and Universities in Jiangsu Province,ChinaSupports to A-Xing Zhu through the Vilas Associate Awardthe Hammel Faculty Fellow Awardthe Manasse Chair Professorship from the University of Wisconsin-Madison。
文摘Selecting a proper set of covariates is one of the most important factors that influence the accuracy of digital soil mapping(DSM).The statistical or machine learning methods for selecting DSM covariates are not available for those situations with limited samples.To solve the problem,this paper proposed a case-based method which could formalize the covariate selection knowledge contained in practical DSM applications.The proposed method trained Random Forest(RF)classifiers with DSM cases extracted from the practical DSM applications and then used the trained classifiers to determine whether each one potential covariate should be used in a new DSM application.In this study,we took topographic covariates as examples of covariates and extracted 191 DSM cases from 56 peer-reviewed journal articles to evaluate the performance of the proposed case-based method by Leave-One-Out cross validation.Compared with a novices’commonly-used way of selecting DSM covariates,the proposed case-based method improved more than 30%accuracy according to three quantitative evaluation indices(i.e.,recall,precision,and F1-score).The proposed method could be also applied to selecting the proper set of covariates for other similar geographical modeling domains,such as landslide susceptibility mapping,and species distribution modeling.
基金Under the auspices of Program of International Science & Technology Cooperation,Ministry of Science and Technology of China(No.2010DFB24140)National Natural Science Foundation of China(No.41023010,41001298)National High Technology Research and Development Program of China(No.2011AA120305)
文摘Soil type maps at the scale of I Z 1 000 000 are used extensively to provide soil spatial distribution information for soil erosion assessment and watershed management models in China. However, the soil property maps produced through conventional direct linking method usually suffer low accuracy as well as the lack of spatial details within a soil type polygon. This paper presents an effective method to produce detailed soil property map based on representative samples which were extracted from each polygon on the 1 ： 1 000 000 soil type map. The representative sample of each polygon is defined as the location that can represent the largest area within the polygon. The representativeness of a candidate sample is determined by calculating the soil-forming environment condition similarities between the sample and other locations. Once the representative sample of each polygon has been chosen, the property values of the existing typical samples are assigned to the corresponding representative samples with the same soil type. Finally, based on these representative samples, the detailed soil property map could be produced by using existing digital soil mapping methods. The case study in XuanCheng City, Anhui Province of China, demonstrated the proposed method could produce soil property map at a higher level of spatial details and accuracy： 1） The soil organic matter （SOM） map produced based on the representative samples can not only depict the detailed spatial distribution of SOM within a soil type polygon but also largely reduce the abrupt change of soil property at the boundaries of two adjacent polygons. 2） The Root Mean Squared Error （RMSE） of the SOM map based on the representative samples is 1.61, and it is 1.37 for the SOM map produced by using conventional direct linking method. Therefore, the proposed method is an effective approach to produce spatial detailed soil property map with higher accuracy for environment simulation models.
基金This work was financially supported by the National Natural Science Foundation of China(41771470)the China Postdoctoral Science Foundation(2020M672776).
文摘Soil salinization is one of the most important causes of land degradation and desertification,especially in arid and semi-arid areas.The dynamic monitoring of soil salinization is of great significance to land management,agricultural activities,water quality,and sustainable development.The remote sensing images taken by the synthetic aperture radar(SAR)Sentinel-1 and the multispectral satellite Sentinel-2 with high resolution and short revisit period have the potential to monitor the spatial distribution of soil attribute information on a large area;however,there are limited studies on the combination of Sentinel-1 and Sentinel-2 for digital mapping of soil salinization.Therefore,in this study,we used topography indices derived from digital elevation model(DEM),SAR indices generated by Sentinel-1,and vegetation indices generated by Sentinel-2 to map soil salinization in the Ogan-Kuqa River Oasis located in the central and northern Tarim Basin in Xinjiang of China,and evaluated the potential of multi-source sensors to predict soil salinity.Using the soil electrical conductivity(EC)values of 70 ground sampling sites as the target variable and the optimal environmental factors as the predictive variable,we constructed three soil salinity inversion models based on classification and regression tree(CART),random forest(RF),and extreme gradient boosting(XGBoost).Then,we evaluated the prediction ability of different models through the five-fold cross validation.The prediction accuracy of XGBoost model is better than those of CART and RF,and soil salinity predicted by the three models has similar spatial distribution characteristics.Compared with the combination of topography indices and vegetation indices,the addition of SAR indices effectively improves the prediction accuracy of the model.In general,the method of soil salinity prediction based on multi-source sensor combination is better than that based on a single sensor.In addition,SAR indices,vegetation indices,and topography indices are all effective variables for soil salinity prediction.Weighted Difference Vegetation Index(WDVI)is designated as the most important variable in these variables,followed by DEM.The results showed that the high-resolution radar Sentinel-1 and multispectral Sentinel-2 have the potential to develop soil salinity prediction model.
文摘Ice and snow domint the land features in Antarctica. The great brightness and poorcontrast of ice and snow and streaking noise in satellite image make the procedure of image processing difficult. On the other hand however, the contrast between bare rock land/sea water and ice/snow is so high that the details of image will be overcompressed.In the light of characteristics of satellite image in Antarctica, a filtering to remove streaking noise has adn discussed. Based on automatic identify classification to enhance the details of objects and the method and theory of digital rectification of satellite image with ground control points measured from field survey are also presented.
基金Supported by National Oil-gas Project:No XQ-2004-07
文摘Digital geological mapping fundamentally broke through the traditional working pattern,successfully carried out the geological mapping digitalization.By using the RGMAP system to field digital geological mapping,the authors summarized the method of work and the work flow of the RGMAPGIS during the field geological survey.First,we prepared material,set up the PRB gallery,then put the geographic base map under the background maplayer and organizing the field hand map,forming the field factual datum map.At last,the geological space database is formed.
基金supported by the National Natural Science Foundation of China (No. 81173157)the Guangdong Natural Science Foundation (No. 10151063201000045)
文摘OBJECTIVE： To construct a protein-protein interaction（PPI） network in hypertension patients with blood-stasis syndrome（BSS） by using digital gene expression（DGE） sequencing and database mining techniques.METHODS： DGE analysis based on the Solexa Genome Analyzer platform was performed on vascular endothelial cells incubated with serum of hypertension patients with BSS. The differentially expressed genes were f iltered by comparing the expression levels between the different experimental groups. Then functional categories and e nriched pathways of the unique genes for BSS were analyzed using Database for Annotation, Visualization and Integrated Discovery（DAVID） to select those in the enrichment pathways. I nterologous Interaction Database（I2D） was used to construct PPI networks with the selected genes for hypertension patients with BSS. The potential candidate genes related to BSS were identif ied by comparing the number of relationships among genes. Confi rmed by quantitative reverse transcription-polymerase chain reaction（q RTPCR）, gene ontology（GO） analysis was used to infer the functional annotations of the potential candidate genes for BSS.RESULTS： With gene enrichment analysis using DAVID, a list of 58 genes was chosen from the unique genes. The selected 58 genes were analyzed using I2 D, and a PPI network was constructed. Based on the network analysis results, candidate genes for BSS were identifi ed：DDIT3, JUN, HSPA8, NFIL3, HSPA5, HIST2H2 BE, H3F3 B, CEBPB, SAT1 and GADD45 A. Verif ied through qRT-PCR and analyzed by GO, the functional annotations of the potential candidate genes were explored.CONCLUSION： Compared with previous methodologies reported in the literature, the present DGE analysis and data mining method have shown a great improvement in analyzing BSS.
文摘The components of map information are analyzed theoretically in this paper,and the map information includes mainly the spatial information,attributive information and temporal characteristics information.Then the digital map entity is defined according to construction characteristics of the map information.Finally,on the basis of the analyses of the construction characteristics of digital map entity and present conceptual model of digital map database,an abstracted conceptual model of digital map database is presented.And the Normal Form theory of relational database is discussed particularly.
基金The National Natural Science Foundation of China(No.61973079,61273236)the Program for Special Talents in Six Major Fields of Jiangsu Province(No.2017JXQC-003)。
文摘A new lane-level road modeling method based on cardinal spline is proposed for the special intersections which are covered by vegetation or artificial landscape in their central regions.First,cardinal spline curves are used to fit the virtual lanes inside special intersections,and an initial road model is established using a series of control points and tension parameters.Then,the progressive optimization algorithm is proposed to determine the final road model based on the initial model.The algorithm determines reasonable control points and optimal tension parameters according to the degree of road curvature changes,so as to achieve a balance between the efficiency and reliability of the road model.Finally,the proposed intersection model is verified and evaluated through experiments.The results show that this method can effectively describe the lane-level topological relationship and geometric details of this kind of special intersection where the central area is covered by vegetation or artificial landscape,and can achieve a good balance between the efficiency and reliability of the road model.
文摘The colorful satellite image maps with the scale of 1∶100000 were made by processing the parameters-on-satellite under the condition of no data of field surveying.The purpose is to ensure the smooth performance of the choice of expedition route,navigation and research task before the Chinese National Antarctic Research Expedition(CHINARE)first made researches on the Grove Mountains.Moreover,on the basis of the visual interpretation of the satellite image,we preliminarily analyze and discuss the relief and landform,blue ice and meteorite distribution characteristics in the Grove Mountains.
文摘Since 1894,the Geological Survey of Western Australia(GSWA)has released 14 versions of the‘Geological Map of Western Australia’.The latest in this series,published in December 2015,is the first bedrock geology map
文摘The first Ukrainian using experience of multispectral space scanning for digital soil mapping is described in this paper. Methodical approaches for detailed soil observation of Ukrainian forest regions are elaborated based on modem mapping principles. For the first time in Ukraine, digital soil maps based on GIS （geographic information system） were obtained for individual farms. In GIS based on space images and digital relief models, the medium-scale and large-scale soil maps were created by geo-statistical methods. According to elaborated methods, modem digital soil mapping should provide all combined works： remote sensing and traditional soil observations. The modem digital soil mapping should be based just on quantitative principles： on remote sensing data, geomorphologic field parameters, and chemical analyses. The methodological approaches, which were used for the first time in Ukraine during digital soil mapping by remote sensing methods, are described in this paper.
文摘The continuous development of science and technology has promoted the basic of surveying and mapping technology. More and more advanced surveying and mapping technology has been applied to geological engineering survey. The traditional geological survey technology has many defects, which affect the normal development of geological engineering survey. Therefore, we must actively apply digital surveying and mapping technology to improve the quality and efficiency of the survey. This paper first discusses the digital surveying and mapping technology, then analyzes the digital surveying and mapping technology, and finally puts forward some suggestions on the specific application of unmanned aerial vehicle remote sensing surveying and mapping technology in geological engineering survey, hoping to promote the progress of geological engineering survey.
