Identifying the uneven distribution of health and education services in China using open geospatial data

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.

Kenyan Counties Geospatial Data Knowledge to Monitor Crop Production

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.

A holistic approach to aligning geospatial data with multidimensional similarity measuring

Semantically aligning the heterogeneous geospatial datasets(GDs)produced by different organizations demands efficient similarity matching methods.However,the strategies employed to align the schema(concept and property)and instances are usually not reusable,and the effects of unbalanced information tend to be neglected in GD alignment.To solve this problem,a holistic approach is presented in this paper to integrally align the geospatial entities(concepts,properties and instances)simultaneously.Spatial,lexical,structural and extensional similarity metrics are designed and automatically aggregated by means of approval voting.The presented approach is validated with real geographical semantic webs,Geonames and OpenStreetMap.Compared with the well-known extensional-based aligning system,the presented approach not only considers more information involved in GD alignment,but also avoids the artificial parameter setting in metric aggregation.It reduces the dependency on specific information,and makes the alignment more robust under the unbalanced distribution of various information.

Multidimensional and quantitative interlinking approach for Linked Geospatial Data

Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data.However,data interlinking,which is the most valuable contribution of Linked Data,remains incomplete and inaccurate.This study proposes a multidimensional and quantitative interlinking approach for Linked Data in the geospatial domain.According to the characteristics and roles of geospatial data in data discovery,eight elementary data characteristics are adopted as data interlinking types.These elementary characteristics are further combined to form compound and overall data interlinking types.Each data interlinking type possesses one specific predicate to indicate the actual relationship of Linked Data and uses data similarity to represent the correlation degree quantitatively.Therefore,geospatial data interlinking can be expressed by a directed edge associated with a relation predicate and a similarity value.The approach transforms existing simple and qualitative geospatial data interlinking into complete and quantitative interlinking and promotes the establishment of high-quality and trusted Linked Geospatial Data.The approach is applied to build data intra-links in the Chinese National Earth System Scientific Data Sharing Network(NSTI-GEO)and data-links in NSTI-GEO with the Chinese Meteorological Data Network and National Population and Health Scientific Data Sharing Platform.

Geospatial data ontology:the semantic foundation of geospatial data integration and sharing

Effective integration and wide sharing of geospatial data is an important and basic premise to facilitate the research and applications of geographic information science.However,the semantic heterogeneity of geospatial data is a major problem that significantly hinders geospatial data integration and sharing.Ontologies are regarded as a promising way to solve semantic problems by providing a formalized representation of geographic entities and relationships between them in a manner understandable to machines.Thus,many efforts have been made to explore ontology-based geospatial data integration and sharing.However,there is a lack of a specialized ontology that would provide a unified description for geospatial data.In this paper,with a focus on the characteristics of geospatial data,we propose a unified framework for geospatial data ontology,denoted GeoDataOnt,to establish a semantic foundation for geospatial data integration and sharing.First,we provide a characteristics hierarchy of geospatial data.Next,we analyze the semantic problems for each characteristic of geospatial data.Subsequently,we propose the general framework of GeoDataOnt,targeting these problems according to the characteristics of geospatial data.GeoDataOnt is then divided into multiple modules,and we show a detailed design and implementation for each module.Key limitations and challenges of GeoDataOnt are identified,and broad applications of GeoDataOnt are discussed.

The TripleSat constellation:a new geospatial data service model

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.

A feasibility study of seabed cover classification standard in generating related geospatial data

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.

A geospatial search engine for discovering multi-format geospatial data across the web

The volume of publically available geospatial data on the web is rapidly increasing due to advances in server-based technologies and the ease at which data can now be created.However,challenges remain with connecting individuals searching for geospatial data with servers and websites where such data exist.The objective of this paper is to present a publically available Geospatial Search Engine(GSE)that utilizes a web crawler built on top of the Google search engine in order to search the web for geospatial data.The crawler seeding mechanism combines search terms entered by users with predefined keywords that identify geospatial data services.A procedure runs daily to update map server layers and metadata,and to eliminate servers that go offline.The GSE supports Web Map Services,ArcGIS services,and websites that have geospatial data for download.We applied the GSE to search for all available geospatial services under these formats and provide search results including the spatial distribution of all obtained services.While enhancements to our GSE and to web crawler technology in general lie ahead,our work represents an important step toward realizing the potential of a publically accessible tool for discovering the global availability of geospatial data.

A case-based reasoning approach for task-driven spatial-temporally aware geospatial data discovery through geoportals

There is a critical need to develop a means for fast,task-driven discovery of geospatial data found in geoportals.Existing geoportals,however,only provide metadata-based means for discovery,with little support for task-driven discovery,especially when considering spatial–temporal awareness.To address this gap,this paper presents a Case-Based Reasoning-supported Geospatial Data Discovery(CBR-GDD)method and implementation that accesses geospatial data by tasks.The advantages of the CBR-GDD approach is that it builds an analogue reasoning process that provides an internal mechanism bridging tasks and geospatial data with spatial–temporal awareness,thus providing solutions based on past tasks.The CBR-GDD approach includes a set of algorithms that were successfully implemented via three components as an extension of geoportals:ontology-enhanced knowledge base,similarity assessment model,and case retrieval nets.A set of experiments and case studies validate the CBR-GDD approach and application,and demonstrate its efficiency.

Fundamental aspects of access control for geospatial data

In recent years,geographical information systems have been employed in a wide variety of application domains,and as a result many research efforts are being devoted to those upcoming problems.Geospatial data security,especially access control,has attracted increased research interests within the academic community.The tendency towards sharing and interoperability of geospatial data and applications makes it common to acquire and integrate geospatial data from multiple organisations to accomplish a complex task.Meanwhile,many organisations have the requirement for securing access to possessed sensitive or proprietary geospatial data.In this heterogeneous and distributed environment,consistent access control functionality is crucial to promote controlled accessibility.As an extension of general access control mechanisms in the IT domain,the mechanism for geospatial data access control has its own requirements and characteristics of granularity and geospatial logic.In this paper,we address several fundamental aspects concerning the design and implementation of an access control system for geospatial data,including the classification,requirements,authorisation models,storage structures and management approaches for authorisation rules,matching and decision-making algorithms between authorisation rules and access requests,and its policy enforcement mechanisms.This paper also presents a system framework for realising access control functionality for geospatial data,and explain access control procedures in detail.

Creation of Data Specification for Geospatial Information in Albania on the Theme:“Geology”

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.

THE SCHEME FOR THE DATABASE BUILDING AND UPDATING OF 1∶10 000 DIGITAL ELEVATION MODELS

The National Bureau of Surveying and Mapping of China has planned to speed up the development of spatial data infrastructure (SDI) in the coming few years.This SDI consists of four types of digital products,i.e.,digital orthophotos,digital elevation models, digital line graphs and digital raster graphs.For the DEM,a scheme for the database building and updating of 1∶10 000 digital elevation models has been proposed and some experimental tests have also been accomplished.This paper describes the theoretical (and/or technical) background and reports some of the experimental results to support the scheme.Various aspects of the scheme such as accuracy,data sources,data sampling,spatial resolution,terrain modeling,data organization,etc are discussed.

Statewide GNSS-RTN Systems: Current Practices

The applications of geospatial technologies and positioning data embrace every sphere of modern-day science and industry. With technological advancement, the demands for highly accurate positioning services in real-time led to the development of the Global Navigation Satellite System—Real-Time Network (GNSS-RTN). While there is numerous published information on the technical aspects of the GNSS-RTN technology, information on the best practices or guidelines in building, operating, and managing the GNSS-RTN networks is lacking in practice. To better understand the current practice in establishing and operating the GNSS-RTN systems, an online questionnaire survey was sent to the GNSS-RTN system owners/operators across the U.S. Additionally, a thorough review of available literature on business models and interviews with representatives of two major manufacturers/vendors of GNSS-RTN products and services were conducted. Study results revealed a great deal of inconsistency in current practices among states in the way the GNSS-RTN systems are built, operated, and managed. Aspects of the diversity in state practices involved the business models for the GNSS-RTN systems besides the technical attributes of the network and system products. The information gathered in this study is important in helping state agencies make informed decisions as they build, expand or manage their own GNSS-RTN systems.

Using Semantic Web Technologies to Improve the Extract Transform Load Model

Semantic Web(SW)provides new opportunities for the study and application of big data,massive ranges of data sets in varied formats from multiple sources.Related studies focus on potential SW technologies for resolving big data problems,such as structurally and semantically heterogeneous data that result from the variety of data formats(structured,semi-structured,numeric,unstructured text data,email,video,audio,stock ticker).SW offers information semantically both for people and machines to retain the vast volume of data and provide a meaningful output of unstructured data.In the current research,we implement a new semantic Extract Transform Load(ETL)model that uses SW technologies for aggregating,integrating,and representing data as linked data.First,geospatial data resources are aggregated from the internet,and then a semantic ETL model is used to store the aggregated data in a semantic model after converting it to Resource Description Framework(RDF)format for successful integration and representation.The principal contribution of this research is the synthesis,aggregation,and semantic representation of geospatial data to solve problems.A case study of city data is used to illustrate the semantic ETL model’s functionalities.The results show that the proposed model solves the structural and semantic heterogeneity problems in diverse data sources for successful data aggregation,integration,and representation.

Data democracy–increased supply of geospatial information and expanded participatory processes in the production of data

The global landscape in the supply,co-creation and use of geospatial data is changing very rapidly with new satellites,sensors and mobile devices reconfiguring the traditional lines of demand and supply and the number of actors involved.In this paper we chart some of these technology-led developments and then focus on the opportunities they have created for the increased participation of the public in generating and contributing information for a wide range of uses,scientific and non.Not all this information is open or geospatial,but sufficiently large portions of it are to make it one of the most significant phenomena of the last decade.In fact,we argue that while satellite and sensors have exponentially increased the volumes of geospatial information available,the participation of the public is transformative because it expands the range of participants and stakeholders in society using and producing geospatial information,with opportunities for more direct participation in science,politics and social action.

GEOSS Platform data content and use

The GEOSS Platform is a key contribution to the goal of building the Global Earth Observation System of Systems(GEOSS).It enables a harmonized discovery and access of Earth observation data,shared online by heterogeneous organizations worldwide.This work analyzes both what is made available in the GEOSS Platform by the data providers and how users are utilizing it including multiyear trends,updating a previous analysis published in 2017.The present statistics derive from a 2021 EOValue report funded by the European Commission.The offer of GEOSS Platform data has been the object of various analyses,including data provider characterization,data sharing trends,and data characterization(comprising metadata quality analysis,thematic analysis,responsible party identification,spatial–temporal coverage).GEOSS data demand has also been the object of several analyses,including data consumer characterization,utilization trends,and requested data characterization(comprising thematic analysis,spatial–temporal coverage,and popularity).Among thefindings,a large amount of shared data,mostly from satellite sources,emerges with an issue of low metadata quality and related discovery match.Moreover,the trend in usage is decreasing.Therefore,the progressive disconnection of the GEOSS platform from its data Providers and Users and other possible causes are also reported.

Assessment of distortion in watermarked geospatial vector data using different wavelets

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.

The future of geospatial intelligence

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.

A Low-Cost Mobile Mapping System (LCMMS) for field data acquisition: a potential use to validate aerial/satellite building damage assessment

Among the major natural disasters that occurred in 2010,the Haiti earthquake was a real turning point concerning the availability,dissemination and licensing of a huge quantity of geospatial data.In a few days several map products based on the analysis of remotely sensed data-sets were delivered to users.This demonstrated the need for reliable methods to validate the increasing variety of open source data and remote sensing-derived products for crisis management,with the aim to correctly spatially reference and interconnect these data with other global digital archives.As far as building damage assessment is concerned,the need for accurate field data to overcome the limitations of both vertical and oblique view satellite and aerial images was evident.To cope with the aforementioned need,a newly developed Low-Cost Mobile Mapping System(LCMMS)was deployed in Port-au-Prince(Haiti)and tested during a five-day survey in FebruaryMarch 2010.The system allows for acquisition of movies and single georeferenced frames by means of a transportable device easily installable(or adaptable)to every type of vehicle.It is composed of four webcams with a total field of view of about 180 degrees and one Global Positioning System(GPS)receiver,with the main aim to rapidly cover large areas for effective usage in emergency situations.The main technical features of the LCMMS,the operational use in the field(and related issues)and a potential approach to be adopted for the validation of satellite/aerial building damage assessments are thoroughly described in the article.

Virtual globes for UAV-based data integration:Sputnik GIS and Google Earth^(TM) applications

The integration of local measurements and monitoring via global-scale Earth observations has become a new challenge in digital Earth science.The increasing accessibility and ease of use of virtual globes(VGs)represent primary advantages of this integration,and the digital Earth scientific community has adopted this technology as one of the main methods for disseminating the results of scientific studies.In this study,the best VG software for the dissemination and analysis of highresolution UAV(Unmanned Aerial Vehicle)data is identified for global and continuous geographic scope support.The VGs Google Earth and Sputnik Geographic Information System(GIS)are selected and compared for this purpose.Google Earth is a free platform and one of the most widely used VGs,and one of its best features its ability to provide users with quality visual results.The proprietary software Sputnik GIS more closely approximates the analytical capacity of a traditional GIS and provides outstanding advantages,such as DEM overlapping and visualization for its dissemination.