Although big data are widely used in various fields,its application is still rare in the study of mining subsidence prediction(MSP)caused by underground mining.Traditional research in MSP has the problem of oversimpli...Although big data are widely used in various fields,its application is still rare in the study of mining subsidence prediction(MSP)caused by underground mining.Traditional research in MSP has the problem of oversimplifying geological mining conditions,ignoring the fluctuation of rock layers with space.In the context of geospatial big data,a data-intensive FLAC3D(Fast Lagrangian Analysis of a Continua in 3 Dimensions)model is proposed in this paper based on borehole logs.In the modeling process,we developed a method to handle geospatial big data and were able to make full use of borehole logs.The effectiveness of the proposed method was verified by comparing the results of the traditional method,proposed method,and field observation.The findings show that the proposed method has obvious advantages over the traditional prediction results.The relative error of the maximum surface subsidence predicted by the proposed method decreased by 93.7%and the standard deviation of the prediction results(which was 70 points)decreased by 39.4%,on average.The data-intensive modeling method is of great significance for improving the accuracy of mining subsidence predictions.展开更多
Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’...Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’Sus-tainable Development Goals(SDGs),yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies.This means that such studies lack accessibility metrics for large-scale quantitative evaluations.To address this deficiency,we evaluated the accessibility of health and education ser-vices in China's Mainland in 2021 using point-of-interest data,OpenStreetMap road data,land cover data,and WorldPop spatial demographic data.The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h.On the basis of the road network and land cover information,the overall average time costs of reaching hospital and school were 20 and 22 min,respectively.In terms of population coverage,94.7%and 92.5%of the population in China has a time cost of less than 1 h in obtaining hospital and school services,respectively.Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions,with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas.Furthermore,the cumulative time cost incurred by the bottom 20%of counties(by GDP)from access to hospital and school services reached approximately 80%of the national total.Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties.The accessibil-ity metrics proposed in this study are highly related to SDGs 3 and 4,and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes.The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.展开更多
With the increase of different sensors,applications and customers,the demand from data providers and users is for a new geospatial data service model,which supports low cost,high dexterity,and which would provide a co...With the increase of different sensors,applications and customers,the demand from data providers and users is for a new geospatial data service model,which supports low cost,high dexterity,and which would provide a comprehensive service.Based on such requirements and demands,the 21AT TripleSat constellation terminal and data delivery and management system has been developed by a Beijing based high-tech enterprise,Twenty First Century Aerospace Technology Co.,Ltd.(21AT).The company is the first commercial Earth observation satellite operator and service provider in China.This new geospatial data service model allows the user to directly access multi-source satellite data,manage the data order,and carry out automatic massive data production and delivery.The solution also implements safe and hierarchical user management,statistical data analysis,and automatic information reports.In addition,a mobile application is also available for users to easily access system functions.This new geospatial solution has already been successfully applied and installed in many customer sites in China,and is now available globally for international clients interested in fast geospatial solutions.It enables the success of customers’operational services.Besides providing TripleSat Constellation images,the multi-source data access system also allows the users to access other satellite data sources,based on customized agreement.This paper describes and discusses this new geospatial data service model.展开更多
This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continuous fie...This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continuous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continuous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzziness significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN(triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution.展开更多
On the basis of the authors’ experiences of setting up an NGDC Web site,this paper attempts to present some significant aspects about the security of NGDC based on ASP.They include data storing,database maintenance,n...On the basis of the authors’ experiences of setting up an NGDC Web site,this paper attempts to present some significant aspects about the security of NGDC based on ASP.They include data storing,database maintenance,new technical support and so on.Firstly,this paper discusses how to provide the security of data which is saved in the hosts of NGDC.The security model of "Networks_DB Server_DB_DB Object" is also presented.In Windows NT Server,Internet Information Server (i.e.,IIS) is in charge of transferring message and the management of Web sites.ASP is also based on IIS.The advantages of virtual directory technique provided by IIS are emphasized. An NGDC Web site,at the Research Center of GIS in Wuhan Technical University of Surveying and Mapping is also mentioned in this paper.Because it is only an analoge used for case study,the transmission of digital spatial products is not included in the functions in this NGDC Web site.However,the management of spatial metadata is more important and some functions of metadata query are implemented in it.It is illustrated clearly in the functional diagram of the NGDC Web site.展开更多
Extreme weather conditions can adversely impact transport networks and driver behaviour,leading to variations in traffic volumes and travel times and increased accident rates.Emergency services that need to navigate t...Extreme weather conditions can adversely impact transport networks and driver behaviour,leading to variations in traffic volumes and travel times and increased accident rates.Emergency services that need to navigate to an accident site in the shortest possible time require real-time location-based weather and traffic information to coordinate their response.We therefore require historical and high-resolution temporal real-time data to identify districts and roads that are prone to different types of incidents during inclement weather and to better support emergency services in their decision-making.However,real-time assessment of the current transport network requires a dense sensor network that can provide high-resolution data using internet-enabled technology.In this research,we demonstrate how we obtain historical time-series and real-time data from sensors oper-ated by the Tyne and Wear Urban Traffic and Management Control Centre and the Urban Observatory based at Newcastle upon Tyne,UK.In the study,we assess the impact of rainfall on traffic volume and travel time,and the cascading impacts during a storm event in Newcastle during early October 2021.We also estimate the economic cost of the storm,with regards to transport disruption,as the cost of travel,using the“value of time”based on Department for Transport guidelines(2021).Using spatial-temporal analysis,we chose three locations to demonstrate how traffic parameters varied at different times throughout the storm.We identified increases in travel times of up to 600%and decreases in traffic volume of up to 100%when compared to historical data.Further,we assessed cascading impacts at important traffic locations and their broader implications for city areas.We estimated that the storm’s economic impact on one sensor location increased by up to 370%of the reference value.By analysing historical and real-time data,we detected and explained patterns in the data that would have remained uncovered if they had been examined individually.The combination of different data sources,such as traffic and weather,helps explain temporal fluctuations at locations where incidents were recorded near traffic detectors.We anticipate our study to be a starting point for stakeholders involved in incident response to identify bottleneck locations in the network to help prepare for similar future events.展开更多
This article assesses the feasibility of generating the geospatial data from a national classification standard.In this case,the National Standardization Agency(Badan Standardisasi Nasional)of Indonesia created and pu...This article assesses the feasibility of generating the geospatial data from a national classification standard.In this case,the National Standardization Agency(Badan Standardisasi Nasional)of Indonesia created and published a national seabed cover classification standard called SNI 7987–2014 but has not developed corresponding geospatial data.Geospatial data on seabed cover can be generated by integrating related thematic data,such as those on seafloor surficial sediments,coastal ecosystems,and coastal infrastructure.With consideration for these issues,this research evaluated the feasibility of using SNI 7987–2014 as a means of generating seabed cover geospatial data at scales of 1:250,000 and 1:50,000.To this end,the documentation accompanying the standard was evaluated via descriptive quantitative analysis through weighted scoring,and logical testing,after which overlay,feature selection based on the scored method and remote sensing analysis were carried out to develop the geospatial data prototypes.Results showed that the feasibility levels of using the prototypes for generating data at scales of 1:250,000 and 1:50,000 were 87.5%and 86.5%,respectively,indicating that SNI 7987–2014 can be fully used as the basis for generating geospatial data on seabed cover.展开更多
Accurate geospatial data are essential for geographic information systems(GIS),environmental monitoring,and urban planning.The deep integration of the open Internet and geographic information technology has led to inc...Accurate geospatial data are essential for geographic information systems(GIS),environmental monitoring,and urban planning.The deep integration of the open Internet and geographic information technology has led to increasing challenges in the integrity and security of spatial data.In this paper,we consider abnormal spatial data as missing data and focus on abnormal spatial data recovery.Existing geospatial data recovery methods require complete datasets for training,resulting in time-consuming data recovery and lack of generalization.To address these issues,we propose a GAIN-LSTM-based geospatial data recovery method(TGAIN),which consists of two main works:(1)it uses a long-short-term recurrent neural network(LSTM)as a generator to analyze geospatial temporal data and capture its temporal correlation;(2)it constructs a complete TGAIN network using a cue-masked fusion matrix mechanism to obtain data that matches the original distribution of the input data.The experimental results on two publicly accessible datasets demonstrate that our proposed TGAIN approach surpasses four contemporary and traditional models in terms of mean absolute error(MAE),root mean square error(RMSE),mean square error(MSE),mean absolute percentage error(MAPE),coefficient of determination(R2)and average computational time across various data missing rates.Concurrently,TGAIN exhibits superior accuracy and robustness in data recovery compared to existing models,especially when dealing with a high rate of missing data.Our model is of great significance in improving the integrity of geospatial data and provides data support for practical applications such as urban traffic optimization prediction and personal mobility analysis.展开更多
In general, geospatial data can be divided into two formats, raster and vector formats. A raster consists of a matrix of cells where each cell contains a value representing quantitative information, such as temperatur...In general, geospatial data can be divided into two formats, raster and vector formats. A raster consists of a matrix of cells where each cell contains a value representing quantitative information, such as temperature, vegetation intensity, land use/cover, elevation, etc. A vector data consists of points, lines and polygons representing location or distance or area of landscape features in graphical forms. Many raster data are derived from remote sensing techniques using sophisticated sensors by quantitative approach and many vector data are generated from GIS processes by qualitative approach. Among them, land use/cover data is frequently used in many GIS analyses and spatial modeling processes. However, proper use of quantitative and qualitative geospatial data is important in spatial modeling and decision making. In this article, we discuss common geospatial data formats, their origins and proper use in spatial modelling and decision making processes.展开更多
With the rapid growth of the Internet,the copyright protection problem occurs frequently,and unauthorized copying and distributing of geospatial data threaten the investments of data producers.Digital watermarking is ...With the rapid growth of the Internet,the copyright protection problem occurs frequently,and unauthorized copying and distributing of geospatial data threaten the investments of data producers.Digital watermarking is a possible solution to solve this issue.However,watermarking causes modifications in the original data resulting in distortion and affects accuracy,which is very important to geospatial vector data.This article provides distortion assessment of watermarked geospatial data using wavelet-based invisible watermarking.Eight wavelets at different wavelet decomposition levels are used for accuracy evaluation with the help of error measures such as maximum error and mean square error.Normalized correlation is used as a similarity index between original and extracted watermark.It is observed that the increase in the strength of embedding increases visual degradation.Haar wavelet outperforms the other wavelets,and the third wavelet decomposition level is proved to be optimal level for watermarking.展开更多
The development of technology and the demands of groups of interest for standardized digital geospatial information are increasing daily.The necessity for referred geospatial information,according to a Referencing Coo...The development of technology and the demands of groups of interest for standardized digital geospatial information are increasing daily.The necessity for referred geospatial information,according to a Referencing Coordinating System and European Standards,through a national GIS(Geographic Information System)system,requires a decision making of national and institutional importance.ASIG(State Authority for Geospatial Information)is the institution that administrates,implements,and maintains the NSDI(National Spatial Data Infrastructure).It is calculated that 80%of decision-making by public or private institutions uses geospatial data with a well-organized structure that enables efficiency.Thus,standardization of geospatial data by topic is one of the main objectives of implementing the NSDI in Albania.This is a complex task for the standard and the harmonization of geospatial data,which can be a good opportunity for professional awareness.This study shows in detail the methodology for the creation and implementation of data specification for geospatial information in Albania on the theme:Geology,adoption of the technical specification of the INSPIRE directive as well as the importance of ASIG as an institution that builds and maintains NSDI in Albania.展开更多
Climate change effects have had negative effects on most farmers, both small and large-scale, with weather patterns increasingly becoming unpredictable, such that farmers are unable to plan well for their farming, res...Climate change effects have had negative effects on most farmers, both small and large-scale, with weather patterns increasingly becoming unpredictable, such that farmers are unable to plan well for their farming, resulting in reduced harvests and sometimes losses for farmers. Better availability of information such as weather patterns, suitable crops, nutrient requirements based on soil types and conditions would greatly alleviate these challenges. While geospatial information is being developed and improved continuously by researchers, its accessibility and use by the counties has not been established and cannot be identified as contributing to better crop production outcomes. The aim of this study, therefore, was to assess the awareness and status of geospatial data availability and use for crop production, and the level of the relevant capacities, both human and infrastructural, in selected Counties of Kenya. A survey was conducted in the four counties of Vihiga, Kilifi, Wajir and Nyeri and key informant interviews were conducted with both management and technical County Agricultural Officers, as well as sub-county agricultural extension officers. From the results of the survey, out of the four counties, only one has adequate infrastructure in terms of hard-ware, software and connectivity to conduct useful geospatial data acquisition and processing. While most indicated awareness of the existence of geospatial data, limited resources, low skills and knowledge have restricted any meaningful sourcing of and access to data, with only 38% moderately or highly skilled in acquisition, 48% in processing and 57% in interpretation and use of geospatial data. The study concludes that moderate skills and capacities available within the counties have considerable potential to make use the available geospatial data to inform farmers accordingly and improve their farming outcomes.展开更多
Morphological(e.g.shape,size,and height)and function(e.g.working,living,and shopping)information of buildings is highly needed for urban planning and management as well as other applications such as city-scale buildin...Morphological(e.g.shape,size,and height)and function(e.g.working,living,and shopping)information of buildings is highly needed for urban planning and management as well as other applications such as city-scale building energy use modeling.Due to the limited availability of socio-economic geospatial data,it is more challenging to map building functions than building morphological information,especially over large areas.In this study,we proposed an integrated framework to map building functions in 50 U.S.cities by integrating multi-source web-based geospatial data.First,a web crawler was developed to extract Points of Interest(POIs)from Tripadvisor.com,and a map crawler was developed to extract POIs and land use parcels from Google Maps.Second,an unsupervised machine learning algorithm named OneClassSVM was used to identify residential buildings based on landscape features derived from Microsoft building footprints.Third,the type ratio of POIs and the area ratio of land use parcels were used to identify six non-residential functions(i.e.hospital,hotel,school,shop,restaurant,and office).The accuracy assessment indicates that the proposed framework performed well,with an average overall accuracy of 94%and a kappa coefficient of 0.63.With the worldwide coverage of Google Maps and Tripadvisor.com,the proposed framework is transferable to other cities over the world.The data products generated from this study are of great use for quantitative city-scale urban studies,such as building energy use modeling at the single building level over large areas.展开更多
The 2030 Agenda for Sustainable Development provides a new global policy to guide the way countries collectively manage and transform the social,economic,and environmental dimensions of people and the planet over the ...The 2030 Agenda for Sustainable Development provides a new global policy to guide the way countries collectively manage and transform the social,economic,and environmental dimensions of people and the planet over the next 15 years.Achieving sustainable development presents all countries and the global policy community with a set of significant development challenges that are almost entirely geographic in nature.Many of the issues impacting sustainable development can be analyzed,modeled,and mapped within a geographic context,which in turn can provide the integrative framework necessary for global collaboration,consensus and evidence-based decision-making.However,and despite significant advances in geospatial information technologies,there is a lack of awareness,understanding and uptake,particular at the policy and decision-making level,of the vital and integrative role of geospatial information and related enabling architectures such as National Spatial Data Infrastructures.This paper reasons that the role of geospatial information in contributing to sustainable development has not adequately been described by either the sustainable development policy practice or by the geospatial professional community.This lack of policy and guidance,with commensurate critical gaps and connection points with national geospatial frameworks,is a visible impediment to developing countries and those most affected by the challenges and need to achieve sustainable development.The global geospatial community now has a unique opportunity to integrate and connect geospatial information into the global development agenda in a more holistic and sustainable manner,specifically in contributing their data resources toward measuring and monitoring the 17 Sustainable Development Goals,and their 169 associated targets,through the global indicator framework that anchors the 2030 Agenda for Sustainable Development.This paper introduces and discusses a new strategic framework for linking a global policy to national geospatial capabilities.展开更多
For centuries,humans’capacity to capture and depict physical space has played a central role in industrial and societal development.However,the digital revolution and the emergence of networked devices and services a...For centuries,humans’capacity to capture and depict physical space has played a central role in industrial and societal development.However,the digital revolution and the emergence of networked devices and services accelerate geospatial capture,coordination,and intelligence in unprecedented ways.Underlying the digital transformation of industry and society is the fusion of the physical and digital worlds-‘perceptality’-where geospatial perception and reality merge.This paper analyzes the myriad forces that are driving perceptality and the future of geospatial intelligence and presents real-world implications and examples of its industrial application.Applications of sensors,robotics,cameras,machine learning,encryption,cloud computing and other software,and hardware intelligence are converging,enabling new ways for organizations and their equipment to perceive and capture reality.Meanwhile,demands for performance,reliability,and security are pushing compute‘to the edge’where real-time processing and coordination are vital.Big data place new restraints on economics,as pressures abound to actually use these data,both in real-time and for longer term strategic analysis and decision-making.These challenges require orchestration between information technology(IT)and operational technology(OT)and synchronization of diverse systems,data-sets,devices,environments,workflows,and people.展开更多
The research presented in this thesis reveals the level of rightness of the recurrence Prediction systems by correlated with geospatial effect. The Geospatial technology elements split up: Geographic Information Syste...The research presented in this thesis reveals the level of rightness of the recurrence Prediction systems by correlated with geospatial effect. The Geospatial technology elements split up: Geographic Information System (GIS), Remote Sensing (RS) and Global Positioning System (GPS) consolidated into this technique in light of the fact that the vast majority of the components in radio wave propagation are geographic highlights. In this exploration, ICEPAC remote arranging programming is tried in a field test completed in Tigray and Afar district. The consequence show that, the Prediction programming doesn’t put, day by day, regular and month to month topographical marvels into thought. Moreover, it doesn’t demonstrate the correct area of the radio stations. Furthermore, the new proposed ICEPAC Calibration algorithm anticipates a good Signal quality for frequencies in the vicinity of 1.5 MHz up to 30 MHz. The total result showed that Geographical Information Systems (GIS) are getting to be noticeably valuable apparatuses in accumulation, stockpiling, control and portrayal of Geo spatial information and also the RS and GIS situated Signal quality forecast can essentially enhance forecast quality contrasted with the hypothetical free space demonstration which does not consider any Geo spatial and neighborhood landscape highlights impacts.展开更多
The mobile geospatial information service involves the domain of mobile communication, mobile computing, geospatial information service and other techniques. This paper focuses on the integration of spatial informatio...The mobile geospatial information service involves the domain of mobile communication, mobile computing, geospatial information service and other techniques. This paper focuses on the integration of spatial information and mobile communication technologies. The author proposes the architecture of mobile geospatial information service based on the Ad Hoc network. On the basis of this architecture, a system is developed, and applied in correlative fields.展开更多
文摘Although big data are widely used in various fields,its application is still rare in the study of mining subsidence prediction(MSP)caused by underground mining.Traditional research in MSP has the problem of oversimplifying geological mining conditions,ignoring the fluctuation of rock layers with space.In the context of geospatial big data,a data-intensive FLAC3D(Fast Lagrangian Analysis of a Continua in 3 Dimensions)model is proposed in this paper based on borehole logs.In the modeling process,we developed a method to handle geospatial big data and were able to make full use of borehole logs.The effectiveness of the proposed method was verified by comparing the results of the traditional method,proposed method,and field observation.The findings show that the proposed method has obvious advantages over the traditional prediction results.The relative error of the maximum surface subsidence predicted by the proposed method decreased by 93.7%and the standard deviation of the prediction results(which was 70 points)decreased by 39.4%,on average.The data-intensive modeling method is of great significance for improving the accuracy of mining subsidence predictions.
基金This work was supported by the National Natural Science Foundation for Distinguished Young Scholars of China(Grant No.41725006).
文摘Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’Sus-tainable Development Goals(SDGs),yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies.This means that such studies lack accessibility metrics for large-scale quantitative evaluations.To address this deficiency,we evaluated the accessibility of health and education ser-vices in China's Mainland in 2021 using point-of-interest data,OpenStreetMap road data,land cover data,and WorldPop spatial demographic data.The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h.On the basis of the road network and land cover information,the overall average time costs of reaching hospital and school were 20 and 22 min,respectively.In terms of population coverage,94.7%and 92.5%of the population in China has a time cost of less than 1 h in obtaining hospital and school services,respectively.Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions,with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas.Furthermore,the cumulative time cost incurred by the bottom 20%of counties(by GDP)from access to hospital and school services reached approximately 80%of the national total.Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties.The accessibil-ity metrics proposed in this study are highly related to SDGs 3 and 4,and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes.The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.
基金supported by the project of Beijing Municipal Science and Technology Commission and Science and Technology Innovation Base of Cultivating and Developing Engineering[grant number Z161100005016069]the National High Technology Research and Development Program[grant number 2013AA12A303].
文摘With the increase of different sensors,applications and customers,the demand from data providers and users is for a new geospatial data service model,which supports low cost,high dexterity,and which would provide a comprehensive service.Based on such requirements and demands,the 21AT TripleSat constellation terminal and data delivery and management system has been developed by a Beijing based high-tech enterprise,Twenty First Century Aerospace Technology Co.,Ltd.(21AT).The company is the first commercial Earth observation satellite operator and service provider in China.This new geospatial data service model allows the user to directly access multi-source satellite data,manage the data order,and carry out automatic massive data production and delivery.The solution also implements safe and hierarchical user management,statistical data analysis,and automatic information reports.In addition,a mobile application is also available for users to easily access system functions.This new geospatial solution has already been successfully applied and installed in many customer sites in China,and is now available globally for international clients interested in fast geospatial solutions.It enables the success of customers’operational services.Besides providing TripleSat Constellation images,the multi-source data access system also allows the users to access other satellite data sources,based on customized agreement.This paper describes and discusses this new geospatial data service model.
基金Project supported by a Young Teacher Research Foundation Award and a National Bureau of Surveying and Mapping Grant(No.97013)
文摘This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continuous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continuous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzziness significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN(triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution.
文摘On the basis of the authors’ experiences of setting up an NGDC Web site,this paper attempts to present some significant aspects about the security of NGDC based on ASP.They include data storing,database maintenance,new technical support and so on.Firstly,this paper discusses how to provide the security of data which is saved in the hosts of NGDC.The security model of "Networks_DB Server_DB_DB Object" is also presented.In Windows NT Server,Internet Information Server (i.e.,IIS) is in charge of transferring message and the management of Web sites.ASP is also based on IIS.The advantages of virtual directory technique provided by IIS are emphasized. An NGDC Web site,at the Research Center of GIS in Wuhan Technical University of Surveying and Mapping is also mentioned in this paper.Because it is only an analoge used for case study,the transmission of digital spatial products is not included in the functions in this NGDC Web site.However,the management of spatial metadata is more important and some functions of metadata query are implemented in it.It is illustrated clearly in the functional diagram of the NGDC Web site.
基金supported by the United Kingdom’s Engineering and Physical Sciences Research Council(EPSRC)under grant number EP/S023577/1,and Ordnance Survey of Great Britain.
文摘Extreme weather conditions can adversely impact transport networks and driver behaviour,leading to variations in traffic volumes and travel times and increased accident rates.Emergency services that need to navigate to an accident site in the shortest possible time require real-time location-based weather and traffic information to coordinate their response.We therefore require historical and high-resolution temporal real-time data to identify districts and roads that are prone to different types of incidents during inclement weather and to better support emergency services in their decision-making.However,real-time assessment of the current transport network requires a dense sensor network that can provide high-resolution data using internet-enabled technology.In this research,we demonstrate how we obtain historical time-series and real-time data from sensors oper-ated by the Tyne and Wear Urban Traffic and Management Control Centre and the Urban Observatory based at Newcastle upon Tyne,UK.In the study,we assess the impact of rainfall on traffic volume and travel time,and the cascading impacts during a storm event in Newcastle during early October 2021.We also estimate the economic cost of the storm,with regards to transport disruption,as the cost of travel,using the“value of time”based on Department for Transport guidelines(2021).Using spatial-temporal analysis,we chose three locations to demonstrate how traffic parameters varied at different times throughout the storm.We identified increases in travel times of up to 600%and decreases in traffic volume of up to 100%when compared to historical data.Further,we assessed cascading impacts at important traffic locations and their broader implications for city areas.We estimated that the storm’s economic impact on one sensor location increased by up to 370%of the reference value.By analysing historical and real-time data,we detected and explained patterns in the data that would have remained uncovered if they had been examined individually.The combination of different data sources,such as traffic and weather,helps explain temporal fluctuations at locations where incidents were recorded near traffic detectors.We anticipate our study to be a starting point for stakeholders involved in incident response to identify bottleneck locations in the network to help prepare for similar future events.
文摘This article assesses the feasibility of generating the geospatial data from a national classification standard.In this case,the National Standardization Agency(Badan Standardisasi Nasional)of Indonesia created and published a national seabed cover classification standard called SNI 7987–2014 but has not developed corresponding geospatial data.Geospatial data on seabed cover can be generated by integrating related thematic data,such as those on seafloor surficial sediments,coastal ecosystems,and coastal infrastructure.With consideration for these issues,this research evaluated the feasibility of using SNI 7987–2014 as a means of generating seabed cover geospatial data at scales of 1:250,000 and 1:50,000.To this end,the documentation accompanying the standard was evaluated via descriptive quantitative analysis through weighted scoring,and logical testing,after which overlay,feature selection based on the scored method and remote sensing analysis were carried out to develop the geospatial data prototypes.Results showed that the feasibility levels of using the prototypes for generating data at scales of 1:250,000 and 1:50,000 were 87.5%and 86.5%,respectively,indicating that SNI 7987–2014 can be fully used as the basis for generating geospatial data on seabed cover.
基金supported by the National Natural Science Foundation of China(No.62002144)Ministry of Education Chunhui Plan Research Project(Nos.202200345,HZKY20220125).
文摘Accurate geospatial data are essential for geographic information systems(GIS),environmental monitoring,and urban planning.The deep integration of the open Internet and geographic information technology has led to increasing challenges in the integrity and security of spatial data.In this paper,we consider abnormal spatial data as missing data and focus on abnormal spatial data recovery.Existing geospatial data recovery methods require complete datasets for training,resulting in time-consuming data recovery and lack of generalization.To address these issues,we propose a GAIN-LSTM-based geospatial data recovery method(TGAIN),which consists of two main works:(1)it uses a long-short-term recurrent neural network(LSTM)as a generator to analyze geospatial temporal data and capture its temporal correlation;(2)it constructs a complete TGAIN network using a cue-masked fusion matrix mechanism to obtain data that matches the original distribution of the input data.The experimental results on two publicly accessible datasets demonstrate that our proposed TGAIN approach surpasses four contemporary and traditional models in terms of mean absolute error(MAE),root mean square error(RMSE),mean square error(MSE),mean absolute percentage error(MAPE),coefficient of determination(R2)and average computational time across various data missing rates.Concurrently,TGAIN exhibits superior accuracy and robustness in data recovery compared to existing models,especially when dealing with a high rate of missing data.Our model is of great significance in improving the integrity of geospatial data and provides data support for practical applications such as urban traffic optimization prediction and personal mobility analysis.
文摘In general, geospatial data can be divided into two formats, raster and vector formats. A raster consists of a matrix of cells where each cell contains a value representing quantitative information, such as temperature, vegetation intensity, land use/cover, elevation, etc. A vector data consists of points, lines and polygons representing location or distance or area of landscape features in graphical forms. Many raster data are derived from remote sensing techniques using sophisticated sensors by quantitative approach and many vector data are generated from GIS processes by qualitative approach. Among them, land use/cover data is frequently used in many GIS analyses and spatial modeling processes. However, proper use of quantitative and qualitative geospatial data is important in spatial modeling and decision making. In this article, we discuss common geospatial data formats, their origins and proper use in spatial modelling and decision making processes.
文摘With the rapid growth of the Internet,the copyright protection problem occurs frequently,and unauthorized copying and distributing of geospatial data threaten the investments of data producers.Digital watermarking is a possible solution to solve this issue.However,watermarking causes modifications in the original data resulting in distortion and affects accuracy,which is very important to geospatial vector data.This article provides distortion assessment of watermarked geospatial data using wavelet-based invisible watermarking.Eight wavelets at different wavelet decomposition levels are used for accuracy evaluation with the help of error measures such as maximum error and mean square error.Normalized correlation is used as a similarity index between original and extracted watermark.It is observed that the increase in the strength of embedding increases visual degradation.Haar wavelet outperforms the other wavelets,and the third wavelet decomposition level is proved to be optimal level for watermarking.
文摘The development of technology and the demands of groups of interest for standardized digital geospatial information are increasing daily.The necessity for referred geospatial information,according to a Referencing Coordinating System and European Standards,through a national GIS(Geographic Information System)system,requires a decision making of national and institutional importance.ASIG(State Authority for Geospatial Information)is the institution that administrates,implements,and maintains the NSDI(National Spatial Data Infrastructure).It is calculated that 80%of decision-making by public or private institutions uses geospatial data with a well-organized structure that enables efficiency.Thus,standardization of geospatial data by topic is one of the main objectives of implementing the NSDI in Albania.This is a complex task for the standard and the harmonization of geospatial data,which can be a good opportunity for professional awareness.This study shows in detail the methodology for the creation and implementation of data specification for geospatial information in Albania on the theme:Geology,adoption of the technical specification of the INSPIRE directive as well as the importance of ASIG as an institution that builds and maintains NSDI in Albania.
文摘Climate change effects have had negative effects on most farmers, both small and large-scale, with weather patterns increasingly becoming unpredictable, such that farmers are unable to plan well for their farming, resulting in reduced harvests and sometimes losses for farmers. Better availability of information such as weather patterns, suitable crops, nutrient requirements based on soil types and conditions would greatly alleviate these challenges. While geospatial information is being developed and improved continuously by researchers, its accessibility and use by the counties has not been established and cannot be identified as contributing to better crop production outcomes. The aim of this study, therefore, was to assess the awareness and status of geospatial data availability and use for crop production, and the level of the relevant capacities, both human and infrastructural, in selected Counties of Kenya. A survey was conducted in the four counties of Vihiga, Kilifi, Wajir and Nyeri and key informant interviews were conducted with both management and technical County Agricultural Officers, as well as sub-county agricultural extension officers. From the results of the survey, out of the four counties, only one has adequate infrastructure in terms of hard-ware, software and connectivity to conduct useful geospatial data acquisition and processing. While most indicated awareness of the existence of geospatial data, limited resources, low skills and knowledge have restricted any meaningful sourcing of and access to data, with only 38% moderately or highly skilled in acquisition, 48% in processing and 57% in interpretation and use of geospatial data. The study concludes that moderate skills and capacities available within the counties have considerable potential to make use the available geospatial data to inform farmers accordingly and improve their farming outcomes.
基金supported by the National Science Foundation[grant numbers 1854502 and 1855902]Publication was made possible in part by support from the HKU Libraries Open Access Author Fund sponsored by the HKU Libraries.USDA is an equal opportunity provider and employer.Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S.Department of Agriculture.
文摘Morphological(e.g.shape,size,and height)and function(e.g.working,living,and shopping)information of buildings is highly needed for urban planning and management as well as other applications such as city-scale building energy use modeling.Due to the limited availability of socio-economic geospatial data,it is more challenging to map building functions than building morphological information,especially over large areas.In this study,we proposed an integrated framework to map building functions in 50 U.S.cities by integrating multi-source web-based geospatial data.First,a web crawler was developed to extract Points of Interest(POIs)from Tripadvisor.com,and a map crawler was developed to extract POIs and land use parcels from Google Maps.Second,an unsupervised machine learning algorithm named OneClassSVM was used to identify residential buildings based on landscape features derived from Microsoft building footprints.Third,the type ratio of POIs and the area ratio of land use parcels were used to identify six non-residential functions(i.e.hospital,hotel,school,shop,restaurant,and office).The accuracy assessment indicates that the proposed framework performed well,with an average overall accuracy of 94%and a kappa coefficient of 0.63.With the worldwide coverage of Google Maps and Tripadvisor.com,the proposed framework is transferable to other cities over the world.The data products generated from this study are of great use for quantitative city-scale urban studies,such as building energy use modeling at the single building level over large areas.
文摘The 2030 Agenda for Sustainable Development provides a new global policy to guide the way countries collectively manage and transform the social,economic,and environmental dimensions of people and the planet over the next 15 years.Achieving sustainable development presents all countries and the global policy community with a set of significant development challenges that are almost entirely geographic in nature.Many of the issues impacting sustainable development can be analyzed,modeled,and mapped within a geographic context,which in turn can provide the integrative framework necessary for global collaboration,consensus and evidence-based decision-making.However,and despite significant advances in geospatial information technologies,there is a lack of awareness,understanding and uptake,particular at the policy and decision-making level,of the vital and integrative role of geospatial information and related enabling architectures such as National Spatial Data Infrastructures.This paper reasons that the role of geospatial information in contributing to sustainable development has not adequately been described by either the sustainable development policy practice or by the geospatial professional community.This lack of policy and guidance,with commensurate critical gaps and connection points with national geospatial frameworks,is a visible impediment to developing countries and those most affected by the challenges and need to achieve sustainable development.The global geospatial community now has a unique opportunity to integrate and connect geospatial information into the global development agenda in a more holistic and sustainable manner,specifically in contributing their data resources toward measuring and monitoring the 17 Sustainable Development Goals,and their 169 associated targets,through the global indicator framework that anchors the 2030 Agenda for Sustainable Development.This paper introduces and discusses a new strategic framework for linking a global policy to national geospatial capabilities.
基金supported by Hexagon AB,a global provider of information technologies for geospatial and industrial enterprises.
文摘For centuries,humans’capacity to capture and depict physical space has played a central role in industrial and societal development.However,the digital revolution and the emergence of networked devices and services accelerate geospatial capture,coordination,and intelligence in unprecedented ways.Underlying the digital transformation of industry and society is the fusion of the physical and digital worlds-‘perceptality’-where geospatial perception and reality merge.This paper analyzes the myriad forces that are driving perceptality and the future of geospatial intelligence and presents real-world implications and examples of its industrial application.Applications of sensors,robotics,cameras,machine learning,encryption,cloud computing and other software,and hardware intelligence are converging,enabling new ways for organizations and their equipment to perceive and capture reality.Meanwhile,demands for performance,reliability,and security are pushing compute‘to the edge’where real-time processing and coordination are vital.Big data place new restraints on economics,as pressures abound to actually use these data,both in real-time and for longer term strategic analysis and decision-making.These challenges require orchestration between information technology(IT)and operational technology(OT)and synchronization of diverse systems,data-sets,devices,environments,workflows,and people.
文摘The research presented in this thesis reveals the level of rightness of the recurrence Prediction systems by correlated with geospatial effect. The Geospatial technology elements split up: Geographic Information System (GIS), Remote Sensing (RS) and Global Positioning System (GPS) consolidated into this technique in light of the fact that the vast majority of the components in radio wave propagation are geographic highlights. In this exploration, ICEPAC remote arranging programming is tried in a field test completed in Tigray and Afar district. The consequence show that, the Prediction programming doesn’t put, day by day, regular and month to month topographical marvels into thought. Moreover, it doesn’t demonstrate the correct area of the radio stations. Furthermore, the new proposed ICEPAC Calibration algorithm anticipates a good Signal quality for frequencies in the vicinity of 1.5 MHz up to 30 MHz. The total result showed that Geographical Information Systems (GIS) are getting to be noticeably valuable apparatuses in accumulation, stockpiling, control and portrayal of Geo spatial information and also the RS and GIS situated Signal quality forecast can essentially enhance forecast quality contrasted with the hypothetical free space demonstration which does not consider any Geo spatial and neighborhood landscape highlights impacts.
文摘The mobile geospatial information service involves the domain of mobile communication, mobile computing, geospatial information service and other techniques. This paper focuses on the integration of spatial information and mobile communication technologies. The author proposes the architecture of mobile geospatial information service based on the Ad Hoc network. On the basis of this architecture, a system is developed, and applied in correlative fields.
