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 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
Surveying and mapping work is often disturbed by the surrounding environment, geographical location and other factors, resulting in surveying and mapping difficulty and the obtained data is not accurate. In order to e...Surveying and mapping work is often disturbed by the surrounding environment, geographical location and other factors, resulting in surveying and mapping difficulty and the obtained data is not accurate. In order to ensure the efficiency of data collection, we should strengthen the use of digital mapping software, and integrate the industry and off-industry work together, so that the industry and outside work groups can be carried out simultaneously. Due to the limitations of technology, professional ability and other aspects, some surveying and mapping personnel can not quickly master the application skills of digital mapping software, can not control the quality scientifically, so in the future work period to strengthen the attention to these two aspects.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
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 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
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
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
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
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
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
Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effect...Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effective management policies.As a spatial information prediction technique,digital soil mapping(DSM)has been widely used to spatially map soil information at different scales.However,the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance.To overcome this limitation,this study systematically assessed a framework of“information extractionfeature selection-model averaging”for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou,China in 2021.The results showed that using the framework of dynamic information extraction,feature selection and model averaging could efficiently improve the accuracy of the final predictions(R^(2):0.48 to 0.53)without having obviously negative impacts on uncertainty.Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM,which improved the R^(2)of random forest from 0.44 to 0.48 and the R^(2)of extreme gradient boosting from 0.37to 0.43.Forward recursive feature selection(FRFS)is recommended when there are relatively few environmental covariates(<200),whereas Boruta is recommended when there are many environmental covariates(>500).The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty.When the structures of initial prediction models are similar,increasing in the number of averaging models did not have significantly positive effects on the final predictions.Given the advantages of these selected strategies over information extraction,feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales,so this approach can provide more reliable references for soil conservation policy-making.展开更多
The alpine terrestrials of the Maloti-Drakensberg in southern Africa play crucial roles in ecosystem functions and livelihoods,yet they face escalating degradation from various factors including overgrazing and climat...The alpine terrestrials of the Maloti-Drakensberg in southern Africa play crucial roles in ecosystem functions and livelihoods,yet they face escalating degradation from various factors including overgrazing and climate change.This study employs advanced Digital Soil Mapping(DSM)techniques coupled with remote sensing to map and assess wetland coverage and degradation in the northern Maloti-Drakensberg.The model achieved high accuracies of 96%and 92%for training and validation data,respectively,with Kappa statistics of 0.91 and 0.83,marking a pioneering automated attempt at wetland mapping in this region.Terrain attributes such as terrain wetness index(TWI)and valley depth(VD)exhibit significant positive correlations with wetland coverage and erosion gully density,Channel Network Depth and slope were negative correlated.Gully density analysis revealed terrain attributes as dominant factors driving degradation,highlighting the need to consider catchment-specific susceptibility to erosion.This challenge traditional assumptions which mainly attribute wetland degradation to external forces such as livestock overgrazing,ice rate activity and climate change.The sensitivity map produced could serve as a basis for Integrated Catchment Management(ICM)projects,facilitating tailored conservation strategies.Future research should expand on this work to include other highland areas,explore additional covariates,and categorize wetlands based on hydroperiod and sensitivity to degradation.This comprehensive study underscores the potential of DSM and remote sensing in accurately assessing and managing wetland ecosystems,crucial for sustainable resource management in alpine regions.展开更多
Soil phosphorus (P) plays a vital role in both ecological and agricultural ecosystems, where total P (TP) in soil serves as a crucial indicator of soil fertility and quality. Most of the studies covered in the literat...Soil phosphorus (P) plays a vital role in both ecological and agricultural ecosystems, where total P (TP) in soil serves as a crucial indicator of soil fertility and quality. Most of the studies covered in the literature employ a single or narrow range of soil databases, which largely overlooks the impact of utilizing multiple mapping scales in estimating soil TP, especially in hilly topographies. In this study, Fujian Province, a subtropical hilly region along China’s southeast coast covered by a complex topographic environment, was taken as a case study. The influence of the mapping scale on soil TP storage (TPS)estimation was analyzed using six digital soil databases that were derived from 3 082 unique soil profiles at different mapping scales, i.e., 1:50 000 (S5),1:200 000 (S20), 1:500 000 (S50), 1:1 000 000 (S100), 1:4 000 000 (S400), and 1:10 000 000 (S1000). The regional TPS in the surface soil (0–20 cm) based on the S5, S20, S50, S100, S400, and S1000 soil maps was 20.72, 22.17, 23.06, 23.05, 22.04, and 23.48 Tg, respectively, and the corresponding TPS at0–100 cm soil depth was 80.98, 80.71, 85.00, 84.03, 82.96, and 86.72 Tg, respectively. By comparing soil TPS in the S20 to S1000 maps to that in the S5map, the relative deviations were 6.37%–13.32%for 0–20 cm and 0.33%–7.09%for 0–100 cm. Moreover, since the S20 map had the lowest relative deviation among different mapping scales as compared to S5, it could provide additional soil information and a richer soil environment than other smaller mapping scales. Our results also revealed that many uncertainties in soil TPS estimation originated from the lack of detailed soil information, i.e., representation and spatial variations among different soil types. From the time and labor perspectives, our work provides useful guidelines to identify the appropriate mapping scale for estimating regional soil TPS in areas like Fujian Province in subtropical China or other places with similar complex topographies. Moreover, it is of tremendous importance to accurately estimate soil TPS to ensure ecosystem stability and sustainable agricultural development, especially for regional decision-making and management of phosphate fertilizer application amounts.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.
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Surveying and mapping work is often disturbed by the surrounding environment, geographical location and other factors, resulting in surveying and mapping difficulty and the obtained data is not accurate. In order to ensure the efficiency of data collection, we should strengthen the use of digital mapping software, and integrate the industry and off-industry work together, so that the industry and outside work groups can be carried out simultaneously. Due to the limitations of technology, professional ability and other aspects, some surveying and mapping personnel can not quickly master the application skills of digital mapping software, can not control the quality scientifically, so in the future work period to strengthen the attention to these two aspects.
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.
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.
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.
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.
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the National Natural Science Foundation of China(U1901601)the National Key Research and Development Program of China(2022YFB3903503)。
文摘Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effective management policies.As a spatial information prediction technique,digital soil mapping(DSM)has been widely used to spatially map soil information at different scales.However,the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance.To overcome this limitation,this study systematically assessed a framework of“information extractionfeature selection-model averaging”for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou,China in 2021.The results showed that using the framework of dynamic information extraction,feature selection and model averaging could efficiently improve the accuracy of the final predictions(R^(2):0.48 to 0.53)without having obviously negative impacts on uncertainty.Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM,which improved the R^(2)of random forest from 0.44 to 0.48 and the R^(2)of extreme gradient boosting from 0.37to 0.43.Forward recursive feature selection(FRFS)is recommended when there are relatively few environmental covariates(<200),whereas Boruta is recommended when there are many environmental covariates(>500).The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty.When the structures of initial prediction models are similar,increasing in the number of averaging models did not have significantly positive effects on the final predictions.Given the advantages of these selected strategies over information extraction,feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales,so this approach can provide more reliable references for soil conservation policy-making.
基金The Afromontane Research Unit of the University of the Free State partially funded this project.
文摘The alpine terrestrials of the Maloti-Drakensberg in southern Africa play crucial roles in ecosystem functions and livelihoods,yet they face escalating degradation from various factors including overgrazing and climate change.This study employs advanced Digital Soil Mapping(DSM)techniques coupled with remote sensing to map and assess wetland coverage and degradation in the northern Maloti-Drakensberg.The model achieved high accuracies of 96%and 92%for training and validation data,respectively,with Kappa statistics of 0.91 and 0.83,marking a pioneering automated attempt at wetland mapping in this region.Terrain attributes such as terrain wetness index(TWI)and valley depth(VD)exhibit significant positive correlations with wetland coverage and erosion gully density,Channel Network Depth and slope were negative correlated.Gully density analysis revealed terrain attributes as dominant factors driving degradation,highlighting the need to consider catchment-specific susceptibility to erosion.This challenge traditional assumptions which mainly attribute wetland degradation to external forces such as livestock overgrazing,ice rate activity and climate change.The sensitivity map produced could serve as a basis for Integrated Catchment Management(ICM)projects,facilitating tailored conservation strategies.Future research should expand on this work to include other highland areas,explore additional covariates,and categorize wetlands based on hydroperiod and sensitivity to degradation.This comprehensive study underscores the potential of DSM and remote sensing in accurately assessing and managing wetland ecosystems,crucial for sustainable resource management in alpine regions.
基金supported by the National Natural Science Foundation of China(Nos.41971050 and 42207271)the Provincial Natural Science Foundation of Fujian,China(No.2022J05036)the Open Project Program of the State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry,Institute of Atmospheric Physics,Chinese Academy of Sciences(No.LAPC-KF-2022-08)。
文摘Soil phosphorus (P) plays a vital role in both ecological and agricultural ecosystems, where total P (TP) in soil serves as a crucial indicator of soil fertility and quality. Most of the studies covered in the literature employ a single or narrow range of soil databases, which largely overlooks the impact of utilizing multiple mapping scales in estimating soil TP, especially in hilly topographies. In this study, Fujian Province, a subtropical hilly region along China’s southeast coast covered by a complex topographic environment, was taken as a case study. The influence of the mapping scale on soil TP storage (TPS)estimation was analyzed using six digital soil databases that were derived from 3 082 unique soil profiles at different mapping scales, i.e., 1:50 000 (S5),1:200 000 (S20), 1:500 000 (S50), 1:1 000 000 (S100), 1:4 000 000 (S400), and 1:10 000 000 (S1000). The regional TPS in the surface soil (0–20 cm) based on the S5, S20, S50, S100, S400, and S1000 soil maps was 20.72, 22.17, 23.06, 23.05, 22.04, and 23.48 Tg, respectively, and the corresponding TPS at0–100 cm soil depth was 80.98, 80.71, 85.00, 84.03, 82.96, and 86.72 Tg, respectively. By comparing soil TPS in the S20 to S1000 maps to that in the S5map, the relative deviations were 6.37%–13.32%for 0–20 cm and 0.33%–7.09%for 0–100 cm. Moreover, since the S20 map had the lowest relative deviation among different mapping scales as compared to S5, it could provide additional soil information and a richer soil environment than other smaller mapping scales. Our results also revealed that many uncertainties in soil TPS estimation originated from the lack of detailed soil information, i.e., representation and spatial variations among different soil types. From the time and labor perspectives, our work provides useful guidelines to identify the appropriate mapping scale for estimating regional soil TPS in areas like Fujian Province in subtropical China or other places with similar complex topographies. Moreover, it is of tremendous importance to accurately estimate soil TPS to ensure ecosystem stability and sustainable agricultural development, especially for regional decision-making and management of phosphate fertilizer application amounts.
