Journal articles: 'Geospatial data sharing'

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Kay, Sissiel E. "Challenges in sharing of geospatial data by data custodians in South Africa." Proceedings of the ICA 1 (May 16, 2018): 1–6. http://dx.doi.org/10.5194/ica-proc-1-60-2018.

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As most development planning and rendering of public services happens at a place or in a space, geospatial data is required. This geospatial data is best managed through a spatial data infrastructure, which has as a key objective to share geospatial data. The collection and maintenance of geospatial data is expensive and time consuming and so the principle of “collect once &ndash; use many times” should apply. It is best to obtain the geospatial data from the authoritative source &ndash; the appointed data custodian. In South Africa the South African Spatial Data Infrastructure (SASDI) is the means to achieve the requirement for geospatial data sharing. This requires geospatial data sharing to take place between the data custodian and the user. All data custodians are expected to comply with the Spatial Data Infrastructure Act (SDI Act) in terms of geo-spatial data sharing. Currently data custodians are experiencing challenges with regard to the sharing of geospatial data. This research is based on the current ten data themes selected by the Committee for Spatial Information and the organisations identified as the data custodians for these ten data themes. The objectives are to determine whether the identified data custodians comply with the SDI Act with respect to geospatial data sharing, and if not what are the reasons for this. Through an international comparative assessment it then determines if the compliance with the SDI Act is not too onerous on the data custodians. The research concludes that there are challenges with geospatial data sharing in South Africa and that the data custodians only partially comply with the SDI Act in terms of geospatial data sharing. However, it is shown that the South African legislation is not too onerous on the data custodians.

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Zhang, C., W. Li, and T. Zhao. "Geospatial data sharing based on geospatial semantic web technologies." Journal of Spatial Science 52, no. 2 (December 2007): 35–49. http://dx.doi.org/10.1080/14498596.2007.9635121.

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Sun, Kai, Yunqiang Zhu, Peng Pan, Zhiwei Hou, Dongxu Wang, Weirong Li, and Jia Song. "Geospatial data ontology: the semantic foundation of geospatial data integration and sharing." Big Earth Data 3, no. 3 (July 3, 2019): 269–96. http://dx.doi.org/10.1080/20964471.2019.1661662.

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Zhang, Shuai, Manchun Li, Zhenjie Chen, Tao Huang, Sumin Li, Wenbo Li, and Yun Chen. "Parallel Spatial-Data Conversion Engine: Enabling Fast Sharing of Massive Geospatial Data." Symmetry 12, no. 4 (April 1, 2020): 501. http://dx.doi.org/10.3390/sym12040501.

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Large-scale geospatial data have accumulated worldwide in the past decades. However, various data formats often result in a geospatial data sharing problem in the geographical information system community. Despite the various methodologies proposed in the past, geospatial data conversion has always served as a fundamental and efficient way of sharing geospatial data. However, these methodologies are beginning to fail as data increase. This study proposes a parallel spatial data conversion engine (PSCE) with a symmetric mechanism to achieve the efficient sharing of massive geodata by utilizing high-performance computing technology. This engine is designed in an extendable and flexible framework and can customize methods of reading and writing particular spatial data formats. A dynamic task scheduling strategy based on the feature computing index is introduced in the framework to improve load balancing and performance. An experiment is performed to validate the engine framework and performance. In this experiment, geospatial data are stored in the vector spatial data defined in the Chinese Geospatial Data Transfer Format Standard in a parallel file system (Lustre Cluster). Results show that the PSCE has a reliable architecture that can quickly cope with massive spatial datasets.

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Zhu, Yunqiang, and Jie Yang. "Automatic data matching for geospatial models: a new paradigm for geospatial data and models sharing." Annals of GIS 25, no. 4 (October 2, 2019): 283–98. http://dx.doi.org/10.1080/19475683.2019.1670735.

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Yang, Yu Bo, Cheng Qi Cheng, and Ji Gang Hao. "Geospatial Data Organization Method Based on GeoSOT Model." Applied Mechanics and Materials 263-266 (December 2012): 1420–23. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1420.

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In order to solve the problem of the hardness of utilization and sharing of geospatial data, a new organization method of mass geospatial data based on global subdivision model was proposed in this study. First, the organization method of mass geospatial data based on GeoSOT was discussed in three aspects. Second, the unified organization framework and system platform was designed. This approach offers an effective way to implement management, organization and use of mass geospatial data.

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Zhai, X., L. Jiang, and P. Yue. "Web-Based Geospatial Resource Sharing Through GeoPW." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-6 (April 23, 2014): 131–35. http://dx.doi.org/10.5194/isprsarchives-xl-6-131-2014.

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As Web-related technologies have matured in recent years, an increasing amount of geospatial resources (e.g. geospatial services, workflows, and geospatial data) are available in the distributed Web environment. Consequently, effective and efficient sharing and management of geospatial resources on the Web are necessary for better utilizing these resources for education and scientific research. This matches the vision of Geoprocessing Web, which emphasizes the sharing and access of geoprocessing utilities from the perspectives of communication, collaboration, and participation. Previous work on GeoPW has provided a large number of geoprocessing services over the Web. In this paper, GeoPW goes further to offer a Web platform for sharing geospatial resources. The paper presents the design, implementation, and functions of the platform, which offers a user-friendly environment for publication, discovery, and communication of geospatial data, services, and workflows.

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Rosly, M. A., A. Ahmad, and Z. Tarmidi. "Collaboration for enabling coastal geospatial data sharing: a review." IOP Conference Series: Earth and Environmental Science 169 (July 31, 2018): 012018. http://dx.doi.org/10.1088/1755-1315/169/1/012018.

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Li, H., W. Huang, Z. Zha, and J. Yang. "APPLICATION AND PLATFORM DESIGN OF GEOSPATIAL BIG DATA." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2021 (June 30, 2021): 293–300. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2021-293-2021.

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Abstract. With the wide application of Big Data, Artificial Intelligence and Internet of Things in geographic information technology and industry, geospatial big data arises at the historic moment. In addition to the traditional "5V" characteristics of big data, which are Volume, Velocity, Variety, Veracity and Valuable, geospatial big data also has the characteristics of "Location Attribute". At present, the study of geospatial big data are mainly concentrated in: knowledge mining and discovery of geospatial data, Spatiotemporal big data mining, the impact of geospatial big data on visualization, social perception and smart city, geospatial big data services for government decision-making support four aspects. Based on the connotation and extension of geospatial big data, this paper comprehensively defines geospatial big data comprehensively. The application of geospatial big data in location visualization, industrial thematic geographic information comprehensive service and geographic data science and knowledge service is introduced in detail. Furthermore, the key technologies and design indicators of the National Geospatial Big Data Platform are elaborated from the perspectives of infrastructure, functional requirements and non-functional requirements, and the design and application of the National Geospatial Public Service Big Data Platform are illustrated. The challenges and opportunities of geospatial big data are discussed from the perspectives of open resource sharing, management decision support and data security. Finally, the development trend and direction of geospatial big data are summarized and prospected, so as to build a high-quality geospatial big data platform and play a greater role in social public application services and administrative management decision-making.

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Cheng, Quanying, Yunqiang Zhu, Hongyun Zeng, Jia Song, Shu Wang, Jinqu Zhang, Lang Qian, and Yanmin Qi. "A Method for Identifying Geospatial Data Sharing Websites by Combining Multi-Source Semantic Information and Machine Learning." Applied Sciences 11, no. 18 (September 18, 2021): 8705. http://dx.doi.org/10.3390/app11188705.

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Geospatial data sharing is an inevitable requirement for scientific and technological innovation and economic and social development decisions in the era of big data. With the development of modern information technology, especially Web 2.0, a large number of geospatial data sharing websites (GDSW) have been developed on the Internet. GDSW is a point of access to geospatial data, which is able to provide a geospatial data inventory. How to precisely identify these data websites is the foundation and prerequisite of sharing and utilizing web geospatial data and is also the main challenge of data sharing at this stage. GDSW identification can be regarded as a binary website classification problem, which can be solved by the current popular machine learning method. However, the websites obtained from the Internet contain a large number of blogs, companies, institutions, etc. If GDSW is directly used as the sample data of machine learning, it will greatly affect the classification precision. For this reason, this paper proposes a method to precisely identify GDSW by combining multi-source semantic information and machine learning. Firstly, based on the keyword set, we used the Baidu search engine to find the websites that may be related to geospatial data in the open web environment. Then, we used the multi-source semantic information of geospatial data content, morphology, sources, and shared websites to filter out a large number of websites that contained geospatial keywords but were not related to geospatial data in the search results through the calculation of comprehensive similarity. Finally, the filtered geospatial data websites were used as the sample data of machine learning, and the GDSWs were identified and evaluated. In this paper, training sets are extracted from the original search data and the data filtered by multi-source semantics, the two datasets are trained by machine learning classification algorithms (KNN, LR, RF, and SVM), and the same test datasets are predicted. The results show that: (1) compared with the four classification algorithms, the classification precision of RF and SVM on the original data is higher than that of the other two algorithms. (2) Taking the data filtered by multi-source semantic information as the sample data for machine learning, the precision of all classification algorithms has been greatly improved. The SVM algorithm has the highest precision among the four classification algorithms. (3) In order to verify the robustness of this method, different initial sample data mentioned above are selected for classification using the same method. The results show that, among the four classification algorithms, the classification precision of SVM is still the highest, which shows that the proposed method is robust and scalable. Therefore, taking the data filtered by multi-source semantic information as the sample data to train through machine learning can effectively improve the classification precision of GDSW, and comparing the four classification algorithms, SVM has the best classification effect. In addition, this method has good robustness, which is of great significance to promote and facilitate the sharing and utilization of open geospatial data.

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Gong, J., H. Wu, W. Jiang, W. Guo, X. Zhai, and P. Yue. "Geospatial Service Platform for Education and Research." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-6 (April 23, 2014): 31–36. http://dx.doi.org/10.5194/isprsarchives-xl-6-31-2014.

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We propose to advance the scientific understanding through applications of geospatial service platforms, which can help students and researchers investigate various scientific problems in a Web-based environment with online tools and services. The platform also offers capabilities for sharing data, algorithm, and problem-solving knowledge. To fulfil this goal, the paper introduces a new course, named "Geospatial Service Platform for Education and Research", to be held in the ISPRS summer school in May 2014 at Wuhan University, China. The course will share cutting-edge achievements of a geospatial service platform with students from different countries, and train them with online tools from the platform for geospatial data processing and scientific research. The content of the course includes the basic concepts of geospatial Web services, service-oriented architecture, geoprocessing modelling and chaining, and problem-solving using geospatial services. In particular, the course will offer a geospatial service platform for handson practice. There will be three kinds of exercises in the course: geoprocessing algorithm sharing through service development, geoprocessing modelling through service chaining, and online geospatial analysis using geospatial services. Students can choose one of them, depending on their interests and background. Existing geoprocessing services from OpenRS and GeoPW will be introduced. The summer course offers two service chaining tools, GeoChaining and GeoJModelBuilder, as instances to explain specifically the method for building service chains in view of different demands. After this course, students can learn how to use online service platforms for geospatial resource sharing and problem-solving.

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Fu, Jian Chun, and Song Yan. "Geospatial Data Organization and Realization of Three-Dimensional Terrain Visualization in Yuntai Mountain Landscape." Applied Mechanics and Materials 170-173 (May 2012): 2794–98. http://dx.doi.org/10.4028/www.scientific.net/amm.170-173.2794.

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After making deep analysis of the geospatial data organization mode, data clipping, data extraction, data mosaic of terrain original data, which are based on geospatial database theories such as ArcGis, GeoDataBase, are studied in detail. This research, beneficial for sharing and inter-operation of spatial information, makes it possible the realization of the three-dimensional visualization in Yuntai Mountain area of Jiaozuo.

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Jozefowicz, Suzanne, Merlin Stone, and Eleni Aravopoulou. "Geospatial data in the UK." Bottom Line 33, no. 1 (October 21, 2019): 27–41. http://dx.doi.org/10.1108/bl-09-2019-0115.

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Purpose The purpose of this paper is to explain the rise of geospatial data, its importance for business and some of the problems associated with its development and use. Design/methodology/approach The paper reviews a certain amount of previously published literature but is based mainly on analysis of the very large number of responses to a consultation paper on geospatial data published by the UK Government. Findings The findings are that while there is strong appreciation of the potential benefits of using geospatial data, there are many barriers to the development, sharing and use of geospatial data, ranging from problems of incompatibility in data definitions and systems to regulatory issues. The implication for governments and for providers and users of geospatial data relates to the need to take a long-term approach to planning in resolving the issues identified. Research limitations/implications The research findings are limited to the UK, but similar findings would be likely in any other large Western country. Practical implications This paper confirms the need for a strong and coherent approach to the planning of geospatial data and systems for the establishment of a clear basis for the different parties to work together and the need to clearly separate the roles of the government in establishing frameworks and standards and the role of the private sector in developing applications and solutions. Social implications Society is increasingly dependent on the use of geospatial data, in improving living standards and dealing with social problems. The recommendations identified in this paper, if followed, will facilitate these improvements. Originality/value The value of this paper is the tight synthesis that it provides of a wide ranging and complex range of responses to the UK Government consultation and placing these responses in the wider context of the development of geospatial data.

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Lee, Sanghoon. "IMPREMENTATION OF VGI-BASED GEOPORTAL FOR EMPOWERING CITIZEN’S GEOSPATIAL OBSERVATORIES RELATED TO URBAN DISASTER MANAGEMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 621–23. http://dx.doi.org/10.5194/isprsarchives-xli-b2-621-2016.

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The volunteered geospatial information (VGI) will be efficient and cost-effective method for generating and sharing large disasterrelated geospatial data. The national mapping organizations have played the role of major geospatial collector have been moving toward the considering public participation data collecting method. Due to VGI can conduct to encourage public participation and empower citizens, mapping agency could make a partnership with members of the VGI community to help to provide well-structured geospatial data. In order to effectively be understood and sharing the public semantics, datasets and action model of the public participation GeoPortal, the implemented VGI-GeoPortal designated as the basis of ISO 19154, ISO 19101 and OGC Reference Model. The proof of concepts of VGI-GeoPortal has been implemented urban flooding use-case in Republic of Korea to collect from the public, and analyze disaster-related geospatial data including high-disaster potential information such as the location of poor drainage sewer, small signs of occurring landslide, flooding vulnerability of urban structure, and etc.

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Lee, Sanghoon. "IMPREMENTATION OF VGI-BASED GEOPORTAL FOR EMPOWERING CITIZEN’S GEOSPATIAL OBSERVATORIES RELATED TO URBAN DISASTER MANAGEMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 621–23. http://dx.doi.org/10.5194/isprs-archives-xli-b2-621-2016.

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The volunteered geospatial information (VGI) will be efficient and cost-effective method for generating and sharing large disasterrelated geospatial data. The national mapping organizations have played the role of major geospatial collector have been moving toward the considering public participation data collecting method. Due to VGI can conduct to encourage public participation and empower citizens, mapping agency could make a partnership with members of the VGI community to help to provide well-structured geospatial data. In order to effectively be understood and sharing the public semantics, datasets and action model of the public participation GeoPortal, the implemented VGI-GeoPortal designated as the basis of ISO 19154, ISO 19101 and OGC Reference Model. The proof of concepts of VGI-GeoPortal has been implemented urban flooding use-case in Republic of Korea to collect from the public, and analyze disaster-related geospatial data including high-disaster potential information such as the location of poor drainage sewer, small signs of occurring landslide, flooding vulnerability of urban structure, and etc.

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Waterman, Luke, Mónica Rivas Casado, Emma Bergin, and Gary McInally. "A Mixed-Methods Investigation into Barriers for Sharing Geospatial and Resilience Flood Data in the UK." Water 13, no. 9 (April 29, 2021): 1235. http://dx.doi.org/10.3390/w13091235.

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With increases in average temperature and rainfall predicted, more households are expected to be at risk of flooding in the UK by 2050. Data and technologies are increasingly playing a critical role across public-, private- and third-sector organisations. However, barriers and constraints exist across organisations and industries that limit the sharing of data. We examine the international context for data sharing and variations between data-rich and data-sparse countries. We find that local politics and organisational structures influence data sharing. We focus on the case study of the UK, and on geospatial and flood resilience data in particular. We use a series of semi-structured interviews to evaluate data sharing limitations, with particular reference to geospatial and flood resilience data. We identify barriers and constraints when sharing data between organisations. We find technological, security, privacy, cultural and commercial barriers across different use cases and data points. Finally, we provide three long-term recommendations to improve the overall accessibility to flood data and enhance outcomes for organisations and communities.

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Ivánová, I., N. Brown, R. Fraser, N. Tengku, and E. Rubinov. "FAIR AND STANDARD ACCESS TO SPATIAL DATA AS THE MEANS FOR ACHIEVING SUSTAINABLE DEVELOPMENT GOALS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W20 (November 15, 2019): 33–39. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w20-33-2019.

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Abstract. FAIR, which stands for Findable, Accessible, Interoperable and Reusable, are the main principles adopted for sharing scientific data across communities. Implementing FAIR principles in publishing increases the value of digital resources, and the reuse of these by humans as well as machines. Introducing FAIR practices to the geospatial domain is especially relevant for the foundation geospatial data, such as precise positioning data. Within the next five years, Global Navigation Satellite Systems (GNSS), with corrections from internet or satellite communications, will permit national coverage of positioning services with real-time accuracy of several centimetres or better. However, implementing FAIR principles is not yet common practice in the geospatial domain. There are dozens of standards available for defining and sharing geospatial data. These include the ISO 19100 series of standards, OGC specifications and several community profiles and best practice. However, in most cases these standards fall short in ensuring the FAIR distribution of geospatial resources. As our preliminary findings show, current geodetic metadata and data are not yet fully FAIR and data discovery and access is still very challenging. In this paper we discuss the concept of FAIR and its meaning for geodetic data, explore the needs of precise positioning users and their requirement for metadata and present preliminary results on the FAIRness of current geodetic standards.

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Ngereja, Z. R., E. J. Liwa, and F. Buberwa. "ADOPTION OF GEOSPATIAL GOVERNANCE IN THE CONTEXT OF E-GOVERMENT IN TANZANIA: ADDRESSING BOTTLENECKS IN SPATIAL DATA INFRASTRUCTURE DEVELOPMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W8 (July 11, 2018): 163–70. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w8-163-2018.

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Abstract. This study has developed a framework for adoption of geospatial governance in the context of e-government in Tanzania. After examining the governance of geospatial data, identify factors affecting governance of geospatial data, and proposed a framework that integrates e-governance and e-government. The research was undertaken to examine the understandings of geospatial governance, its challenges and to develop an institutional framework to guide the management of geospatial resources. Using documentary analysis, strategically designed interviews and questionnaire, and Focus Group Discussions, data was collected from a range of spatial data user community. Upon simple analysis of the data the following were the findings: First, the findings revealed that spatial data is not well managed, reused and shared. Second, geospatial data it is not easily and readily available and accessible. Third, there is lack of coordination and collaboration among spatial data users and custodian. The study revealed that coordination and collaboration is very important if a nation wants to utilize effectively the massive amount of data scattered in various organizations. There is an urgent need of having common gateway for spatial data discovery and sharing, and to have a mechanism that ensures spatial data is collected, processed and analyzed with acceptable standards and having metadata. In view of the findings, the study recommends that geospatial governance integration with e-Government is indispensable. The study has come out with the SPOTES framework for geospatial governance in the context of e-government; the Government should adopt the framework and establish the National Spatial Data Infrastructure. This will ensure the institutional set-up for the governance of geospatial data in the country and key players, i.e. the private sector, government institutions, and NGOs should collaborate in data sharing to benefit the country’s sustainable development.

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Miao, Lizhi, Chengliang Liu, Li Fan, and Mei-Po Kwan. "An OGC web service geospatial data semantic similarity model for improving geospatial service discovery." Open Geosciences 13, no. 1 (January 1, 2021): 245–61. http://dx.doi.org/10.1515/geo-2020-0232.

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Abstract Open Geospatial Consortium (OGC) Web Services (OWS) are highly significant for geospatial data sharing and widely used in many scientific fields. However, those services are hard to find and utilize effectively. Focusing on addressing the big challenge of OWS resource discovery, we propose a measurement model that integrates spatiotemporal similarity and thematic similarity based on ontology semantics to generate a more efficient search method: OWS Geospatial Data Semantic Similarity Model (OGDSSM)-based search engine for semantically enabled geospatial data service discovery that takes into account the hierarchy difference of geospatial service documents and the number of map layers. We implemented the proposed OGDSSM-based semantic search algorithm on United States Geological Survey mineral resources geospatial service discovery. The results show that the proposed search method has better performance than the existing search engines that are based on keyword-based matching, such as Lucene, when recall, precision, and F-measure are taken into consideration. Furthermore, the returned results are ranked based on semantic similarity, which makes it easier for users to find the most similar geospatial data services. Our proposed method can thus enhance the performance of geospatial data service discovery for a wide range of geoscience applications.

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Balbo, S., P. Boccardo, S. Dalmasso, and P. Pasquali. "A PUBLIC PLATFORM FOR GEOSPATIAL DATA SHARING FOR DISASTER RISK MANAGEMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5/W3 (January 7, 2014): 189–95. http://dx.doi.org/10.5194/isprsarchives-xl-5-w3-189-2013.

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Liu, Junnan, Haiyan Liu, Xiaohui Chen, Xuan Guo, Qingbo Zhao, Jia Li, Lei Kang, and Jianxiang Liu. "A Heterogeneous Geospatial Data Retrieval Method Using Knowledge Graph." Sustainability 13, no. 4 (February 12, 2021): 2005. http://dx.doi.org/10.3390/su13042005.

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Information resources have increased rapidly in the big data era. Geospatial data plays an indispensable role in spatially informed analyses, while data in different areas are relatively isolated. Therefore, it is inadequate to use relational data in handling many semantic intricacies and retrieving geospatial data. In light of this, a heterogeneous retrieval method based on knowledge graph is proposed in this paper. There are three advantages of this method: (1) the semantic knowledge of geospatial data is considered; (2) more information required by users could be obtained; (3) data retrieval speed can be improved. Firstly, implicit semantic knowledge is studied and applied to construct a knowledge graph, integrating semantics in multi-source heterogeneous geospatial data. Then, the query expansion rules and the mappings between knowledge and database are designed to construct retrieval statements and obtain related spatial entities. Finally, the effectiveness and efficiency are verified through comparative analysis and practices. The experiment indicates that the method could automatically construct database retrieval statements and retrieve more relevant data. Additionally, users could reduce the dependence on data storage mode and database Structured Query Language syntax. This paper would facilitate the sharing and outreach of geospatial knowledge for various spatial studies.

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Arias Muñoz, C., A. Oggioni, and M. A. Brovelli. "Geospatial web services for limnological data: a case study of sensor observation service for ecological observations." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-4 (April 23, 2014): 9–14. http://dx.doi.org/10.5194/isprsannals-ii-4-9-2014.

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The present work aims at designing and implementing a spatial data infrastructure for storing and sharing ecological data through geospatial web services. As case study, we concentrated on limnological data coming from the drainage basin of Lake Maggiore in the Northern of Italy. In order to establish the infrastructure, we started with two basic questions: (1) What type of data is the ecological dataset? (2) Which are the geospatial web services standards most suitable to store and share ecological data? In this paper we describe the possibilities for sharing ecological data using geospatial web services and the difficulties that can be encountered in this task. In order to test actual technological solutions, we use real data of a limnological published study.We concluded that limnological data can be considered observational data, composed by biological (species) data and environmental data, and it can be modeled using Observation and Measurement (O&M) specification. With the actual web service implementation the geospatial web services that could potentially be used to publish limnological data are Sensor Observation Services (SOS) and Web Feature Services (WFS). SOS holds the essential components to represent time series observations, while WFS is a simple model that requires profiling. Both, SOS and WFS are not perfectly suitable to publish biological data, so other alternatives must be considered, as linked data.

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Merodio Gómez, Paloma, Macarena Pérez García, Gabriela García Seco, Andrea Ramírez Santiago, and Catalina Tapia Johnson. "The Americas’ Spatial Data Infrastructure." ISPRS International Journal of Geo-Information 8, no. 10 (September 29, 2019): 432. http://dx.doi.org/10.3390/ijgi8100432.

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During the last decade, the production of geospatial information has increased considerably; however, managing and sharing this information has become increasingly difficult for the organizations that produce it, because it comes from different data sources and has a wide variety of users. In this sense, to have a better use of geospatial information, several countries have developed national spatial data infrastructures (SDIs) to improve access, visualization, and integration of their data and in turn, have the need to cooperate with other countries to develop regional SDIs, which allow better decision making with regional impact. However, its design and development plan requires, as a starting point, to knowing the level of development of the national SDIs to identify the strengths and gaps that exist in the region. This document presents the methodology developed and the results obtained from the evaluation of the status of implementation of the SDI components in each of the member countries of the Regional Committee of United Nations on Global Geospatial Information Management for the Americas (UN-GGIM: Americas), which will contribute to the equal development of SDIs in an integrated and collaborative way in the Americas.

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Li, Chao, Huimei Lu, Yong Xiang, Zhuoqun Liu, Wanli Yang, and Ruilin Liu. "Bringing Geospatial Data Closer to Mobile Users: A Caching Approach Based on Vector Tiles for Wireless Multihop Scenarios." Mobile Information Systems 2018 (May 8, 2018): 1–18. http://dx.doi.org/10.1155/2018/5186495.

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Mobile applications based on geospatial data are nowadays extensively used to support people’s daily activities. Despite the potential overlap among nearby users’ geospatial data demands, it has not been feasible to share geospatial data with peer wireless devices directly. To address this issue, we designed a scheme based on vector tiles to organize spatial data and proposed a system named GeoTile for geospatial data caching and sharing. In GeoTile, a tile request from the mobile client relies on multihop communication over intermediate nodes to reach the server. Since GeoTile enables all network nodes to cache and process geospatial data tiles, requests may be handled before they actually reach the server. We implement the GeoTile prototype system and conduct comprehensive real-world experiments to evaluate the performance. The result shows that the GeoTile system can serve vector tiles for users conveniently and friendly. In addition, the caching mechanism based on vector tiles can substantially reduce the response time and network throughput under the wireless multihop scenarios.

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He, Ming Xiang, Guan Li, and Xin Ming Lu. "A Method of Geospatial Data Files Conversion Based on Semantic." Applied Mechanics and Materials 303-306 (February 2013): 2221–26. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.2221.

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Data conversion is a necessary step to establish a unified data storage and management mode. Based on the analysis of the structure of Shapefile and the principle of semantic conversion, this paper proposes a method of geospatial data files conversion based on semantic. This method to a relational database file shape file conversion, the application of this method can not only increase the data read speed, and ease of data management and sharing.

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Gong, J., H. Wu, P. Yue, X. Zhu, and W. Gao. "GEOSPATIAL SERVICE WEB: FROM DATA, INFORMATION, AND KNOWLEDGE SHARING TO WEB GEOINTELLIGENCE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-4/W25 (August 30, 2012): 19–22. http://dx.doi.org/10.5194/isprsarchives-xxxviii-4-w25-19-2011.

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Chakraborty, Debasish, Debanjan Sarkar, Shubham Agarwal, Dibyendu Dutta, and Jaswant R. Sharma. "Web Based GIS Application using Open Source Software for Sharing Geospatial Data." International Journal of Advanced Remote Sensing and GIS 4, no. 1 (September 11, 2015): 1224–28. http://dx.doi.org/10.23953/cloud.ijarsg.109.

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Kong, Ningning Nicole. "One store has all? - the backend story of managing geospatial information toward an easy discovery." IASSIST Quarterly 42, no. 4 (February 22, 2019): 1–14. http://dx.doi.org/10.29173/iq927.

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Geospatial data includes many formats, varying from historical paper maps, to digital information collected by various sensors. Many libraries have started the efforts to build a geospatial data portal to connect users with the various information. For example, GeoBlacklight and OpenGeoportal are two open-source projects that initiated from academic institutions which have been adopted by many universities and libraries for geospatial data discovery. While several recent studies have focused on the metadata, usability and data collection perspectives of geospatial data portals, not many have explored the backend stories about data management to support the data discovery platform. The objective of this paper is to provide a summary about geospatial data management strategies involved in the geospatial data portal development by reviewing case studies. These data management strategies include managing the historical paper maps, scanned maps, aerial photos, research generated geospatial information, and web map services. This paper focuses on the data organization, storage, cyberinfrustracture configuration, preservation and sharing perspectives of these efforts with the goal to provide a range of options or best management practices for information managers when curating geospatial data in their own institutions.

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Gaillard, J., A. Peytavie, and G. Gesquière. "DATA STRUCTURE FOR PROGRESSIVE VISUALISATION AND EDITION OF VECTORIAL GEOSPATIAL DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W1 (October 5, 2016): 201–9. http://dx.doi.org/10.5194/isprs-annals-iv-2-w1-201-2016.

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3D mock-ups of cities are becoming an increasingly common tool for urban planning. Sharing the mock-up is still a challenge since the volume of data is so high. Furthermore, the recent surge in low-end, mobile devices requires developers to carefully control the amount of data they process. In this paper, we present a hierarchical data structure that allows the streaming of vectorial data. Loosely based on a quadtree, the structure stores the data in tiles and is organised following a weight function which allows the most relevant data to be displayed first. The relevance of a feature can be measured by its geometry and semantic attributes, and can vary depending on the application or client type. Tiles can be limited in size (number of features or triangles) for the client to be able to control resource consumption. The article also presents algorithms for the addition or removal of features in the data structure, opening the path for the interactive edition of city data stored in a database.

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Li, Chao, Huimei Lu, Yong Xiang, and Rui Gao. "Geo-DMP: A DTN-Based Mobile Prototype for Geospatial Data Retrieval." ISPRS International Journal of Geo-Information 9, no. 1 (December 20, 2019): 8. http://dx.doi.org/10.3390/ijgi9010008.

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Geospatial information is gaining immense interest and importance as we enter the era of highly developed transportation and communication. Despite the proliferation of cellular network and WiFi, on some occasions, users still face barriers to accessing geospatial data. In this paper, we design and implement a distributed prototype system with a delay/disruption tolerant network (DTN), named Geo-DMP, for cooperatively and opportunistically sharing and exchanging named geospatial contents in a device-to-device fashion. First of all, we construct a lightweight “content agent” module to bridge the gap between the application layer and the underlying DTN protocol stack. Afterwards, to profile the mobility history of users in practical geospatial environments, we present a map segmentation scheme based on road network and administrative subdivision information. Subsequently, we associate the regional movement history information with the content retrieval process to devise a hierarchical and region-oriented DTN routing scheme for both requests and responses. Finally, we conduct extensive experiments with real-world trajectories and complete implementations on the emulation platform composed of virtual machines. The experiments corroborate that Geo-DMP has the capability of successfully retrieving geospatial contents for users for most of the time under mobile circumstances with episodic connectivity. Moreover, en-route caches can be efficiently exploited to provision contents from multiple sources with less network resource consumption and shorter user-perceived latencies.

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Nawa, Yuji, Go Urakawa, Hiro Ikemi, Ryota Hamamoto, and Haruo Hayashi. "Geography Network for Sharing Geospatial Information in Disaster Management." Journal of Disaster Research 5, no. 1 (February 1, 2010): 108–16. http://dx.doi.org/10.20965/jdr.2010.p0108.

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The Chuetsu earthquake restoration and revival support geographic information system (GIS) project was launched after the 2004 Chuetsu earthquake. It was the first project to gather disaster GIS data at one place, and provide them by Web GIS from off–site of the disaster site in Japan. To facilitate sharing disaster geospatial information, we introduced a framework of Geography Network as GIS portal. The GIS portal was based on loosely–coupled system architecture. Therefore, it was able to change the system structure by system requirement of the project. The GIS portal was used continuously and commonly for the 2005 Fukuoka Earthquake and 2005–2006 Heavy Snow Disaster and the 2007 Chuetsu-Oki Earthquake. In this paper, we define the system requirement to share disaster geospatial information by knowledge from case studies, and describe a practical method to build the framework, demonstrate the benefit from the framework.

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Kelly, Maggi, Kelly Easterday, Michelle Koo, James H. Thorne, Shruti Mukythar, and Brian Galey. "Geospatial Informatics Key to Recovering and Sharing Historical Ecological Data for Modern Use." Photogrammetric Engineering & Remote Sensing 83, no. 11 (November 1, 2017): 779–86. http://dx.doi.org/10.14358/pers.83.10.779.

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Bocher, Erwan, and Olivier Ertz. "A redesign of OGC Symbology Encoding standard for sharing cartography." PeerJ Computer Science 4 (January 8, 2018): e143. http://dx.doi.org/10.7717/peerj-cs.143.

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Despite most Spatial Data Infrastructures offering service-based visualization of geospatial data, requirements are often at a very basic level leading to poor quality of maps. This is a general observation for any geospatial architecture as soon as open standards as those of the Open Geospatial Consortium (OGC) are applied. To improve the situation, this paper does focus on improvements at the portrayal interoperability side by considering standardization aspects. We propose two major redesign recommendations. First to consolidate the cartographic theory at the core of the OGC Symbology Encoding standard. Secondly to build the standard in a modular way so as to be ready to be extended with upcoming future cartographic requirements. Thus, we start by defining portrayal interoperability by means of typical-use cases that frame the concept of sharing cartography. Then we bring to light the strengths and limits of the relevant open standards to consider in this context. Finally we propose a set of recommendations to overcome the limits so as to make these use cases a true reality. Even if the definition of a cartographic-oriented standard is not able to act as a complete cartographic design framework by itself, we argue that pushing forward the standardization work dedicated to cartography is a way to share and disseminate good practices and finally to improve the quality of the visualizations.

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Intagorn, Suradej, and Kristina Lerman. "Mining Geospatial Knowledge on the Social Web." International Journal of Information Systems for Crisis Response and Management 3, no. 2 (April 2011): 33–47. http://dx.doi.org/10.4018/jiscrm.2011040103.

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Up-to-date geospatial information can help crisis management community to coordinate its response. In addition to data that is created and curated by experts, there is an abundance of user-generated, user-curated data on Social Web sites such as Flickr, Twitter, and Google Earth. User-generated data and metadata can be used to harvest knowledge, including geospatial knowledge that will help solve real-world problems including information discovery, geospatial information integration and data management. This paper proposes a method for acquiring geospatial knowledge in the form of places and relations between them from the user-generated data and metadata on the Social Web. The key to acquiring geospatial knowledge from social metadata is the ability to accurately represent places. The authors describe a simple, efficient algorithm for finding a non-convex boundary of a region from a sample of points from that region. Used within a procedure that learns part-of relations between places from real-world data extracted from the social photo-sharing site Flickr, the proposed algorithm leads to more precise relations than the earlier method and helps uncover knowledge not contained in expert-curated geospatial knowledge bases.

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Chang, Lu Qun, Jian Hua Li, Li Zhong Tian, Peng Lin, Ying Wu, and Wei Zheng Zhong. "DCGF in Ji’Nan: Construction and Issues." Advanced Materials Research 950 (June 2014): 333–38. http://dx.doi.org/10.4028/www.scientific.net/amr.950.333.

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The aim of this paper is to give a review of Digital China Geospatial Framework (DCGF) construction in Ji’nan which is named Digital Ji’nan Geospatial Framework (DJGF). As a national promotting project of DCGF, DJGF has seven components: Municipal Geospatial Information Resource Catalog (MGIRC), Geospatial Framework Datasets (GFD), Geographical Information Database Management System (GIDMS), Public Service Platform (PSP), Security system , Runtime Environment and Pilot Projects. The key methods used in DJGF mainly include Extraction-Transformation-Loading (ETL) technology and service extension. Along with the construction of DJGF, the integrated surveying business system has been built, automatial processing technologies also have been applied to improve the data production efficiency. Moreover, " sub-building, co-sharing, one data-one resource" mechanism has been Put forward and promote the benign circulation of datas. Now, as a fundamental platform for geospatial data exchanging and service supplying, DJGF have been widely used in urban planning, land resources, environment, climate, etc.

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Peng, Z. ‐R. "A proposed framework for feature‐level geospatial data sharing: a case study for transportation network data." International Journal of Geographical Information Science 19, no. 4 (April 2005): 459–81. http://dx.doi.org/10.1080/13658810512331319127.

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Hong, J. H., and Y. T. Su. "VISA: AN AUTOMATIC AWARE AND VISUAL AIDS MECHANISM FOR IMPROVING THE CORRECT USE OF GEOSPATIAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 399–406. http://dx.doi.org/10.5194/isprsarchives-xli-b2-399-2016.

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With the fast growth of internet-based sharing mechanism and OpenGIS technology, users nowadays enjoy the luxury to quickly locate and access a variety of geospatial data for the tasks at hands. While this sharing innovation tremendously expand the possibility of application and reduce the development cost, users nevertheless have to deal with all kinds of “differences” implicitly hidden behind the acquired georesources. We argue the next generation of GIS-based environment, regardless internet-based or not, must have built-in knowledge to automatically and correctly assess the fitness of data use and present the analyzed results to users in an intuitive and meaningful way. The VISA approach proposed in this paper refer to four different types of visual aids that can be respectively used for addressing analyzed results, namely, virtual layer, informative window, symbol transformation and augmented TOC. The VISA-enabled interface works in an automatic-aware fashion, where the standardized metadata serve as the known facts about the selected geospatial resources, algorithms for analyzing the differences of temporality and quality of the geospatial resources were designed and the transformation of analyzed results into visual aids were automatically executed. It successfully presents a new way for bridging the communication gaps between systems and users. GIS has been long seen as a powerful integration tool, but its achievements would be highly restricted if it fails to provide a friendly and correct working platform.

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Hong, J. H., and Y. T. Su. "VISA: AN AUTOMATIC AWARE AND VISUAL AIDS MECHANISM FOR IMPROVING THE CORRECT USE OF GEOSPATIAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 399–406. http://dx.doi.org/10.5194/isprs-archives-xli-b2-399-2016.

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With the fast growth of internet-based sharing mechanism and OpenGIS technology, users nowadays enjoy the luxury to quickly locate and access a variety of geospatial data for the tasks at hands. While this sharing innovation tremendously expand the possibility of application and reduce the development cost, users nevertheless have to deal with all kinds of “differences” implicitly hidden behind the acquired georesources. We argue the next generation of GIS-based environment, regardless internet-based or not, must have built-in knowledge to automatically and correctly assess the fitness of data use and present the analyzed results to users in an intuitive and meaningful way. The VISA approach proposed in this paper refer to four different types of visual aids that can be respectively used for addressing analyzed results, namely, virtual layer, informative window, symbol transformation and augmented TOC. The VISA-enabled interface works in an automatic-aware fashion, where the standardized metadata serve as the known facts about the selected geospatial resources, algorithms for analyzing the differences of temporality and quality of the geospatial resources were designed and the transformation of analyzed results into visual aids were automatically executed. It successfully presents a new way for bridging the communication gaps between systems and users. GIS has been long seen as a powerful integration tool, but its achievements would be highly restricted if it fails to provide a friendly and correct working platform.

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Folmer, E., W. Beek, and L. Rietveld. "LINKED DATA VIEWING AS PART OF THE SPATIAL DATA PLATFORM OF THE FUTURE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W8 (July 11, 2018): 49–52. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w8-49-2018.

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Abstract. The Land Registry and Mapping Agency of the Netherlands (‘Kadaster’ in Dutch) is developing an online publication platform for sharing its geospatial data assets called KDP (`Kadaster Data Platform’ in Dutch). One of the main goals of this platform is to better share geospatial data with the wider, web-oriented world, including its developers, approaches, and standards. Linked Open Data (W3C), GeoSPARQL (OGC), and Open APIs (OpenAPI Specification) are the predominant standardized approaches for this purpose. As a result, the most important spatial datasets of the Netherlands – including several key registries – are now being published as Linked Open Data that can be accessed through a SPARQL endpoint and a collection of REST APIs. In addition to providing raw access to the data, Kadaster Data Platform also offers developers functionalities that allow them to gain a better understanding about the contents of its datasets. These functionalities include various ways for viewing Linked Data . This paper focuses on two of the main components the Kadaster Data Platform is using for this purpose: FacetCheck and Data Stories.

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Cowan, DSc, MA, BA, Nuala M. "Building a geospatial data model for humanitarian response." Journal of Emergency Management 12, no. 5 (September 1, 2014): 383. http://dx.doi.org/10.5055/jem.2014.0203.

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Objective: An effectual emergency response effort is contingent upon the quality and timeliness of information provided to both the decision making and coordinating functions; conditions that are hard to guarantee in the urgent climate of the response effort. The purpose of this paper is to present a validated Humanitarian Data Model (HDM) that can assist in the rapid assessment of disaster needs and subsequent decision making. Substandard, inconsistent information can lead to poorly informed decisions, and subsequently, inappropriate response activities. Here we present a novel, organized, and fluid information management workflow to be applied during the rapid assessment phase of an emergency response. A comprehensive, peer-reviewed geospatial data model not only directs the design of data collection tools but also allows for more systematic data collection and management, leading to improved analysis and response outcomes.Design: This research involved the development of a comprehensive geospatial data model to guide the collection, management and analysis of geographically referenced assessment information, for implementation at the rapid response phase of a disaster using a mobile data collection app based on key outcome parameters. A systematic review of literature and best practices was used to identify and prioritize the minimum essential data variables.Subjects: The data model was critiqued for variable content, structure, and usability by a group of subject matter experts in the fields of humanitarian information management and geographical information systems.Conclusions: Consensus found that the adoption of a standardized system of data collection, management, and processing, such as the data model presented here, could facilitate the collection and sharing of information between agencies with similar goals, facilitate the better coordination of efforts by unleashing the power of geographic information for humanitarian decision support.

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Cheng, X., Z. Gui, K. Hu, S. Gao, P. Shen, and H. Wu. "A CLOUD-BASED PLATFORM SUPPORTING GEOSPATIAL COLLABORATION FOR GIS EDUCATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-6/W1 (May 27, 2015): 1–4. http://dx.doi.org/10.5194/isprsarchives-xl-6-w1-1-2015.

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GIS-related education needs support of geo-data and geospatial software. Although there are large amount of geographic information resources distributed on the web, the discovery, process and integration of these resources are still unsolved. Researchers and teachers always searched geo-data by common search engines but results were not satisfied. They also spent much money and energy on purchase and maintenance of various kinds of geospatial software. Aimed at these problems, a cloud-based geospatial collaboration platform called GeoSquare was designed and implemented. The platform serves as a geoportal encouraging geospatial data, information, and knowledge sharing through highly interactive and expressive graphic interfaces. Researchers and teachers can solve their problems effectively in this one-stop solution. Functions, specific design and implementation details are presented in this paper. Site of GeoSquare is: <a href="http://geosquare.tianditu.com/" target="_blank">http://geosquare.tianditu.com/</a>

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Santoro, E. "THE ACQUISITION, PRODUCTION AND DISSEMINATION OF GEOSPATIAL DATA FOR EMERGENCY MANAGEMENT AND PRESERVATION OF CULTURAL HERITAGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5/W1 (May 12, 2017): 15–24. http://dx.doi.org/10.5194/isprs-archives-xlii-5-w1-15-2017.

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The crisis management of a disaster, whether caused naturally or by human action, requires a thorough knowledge of the territory involved, with regard to both its terrain and its developed areas. Therefore, it is essential that the National Mapping and Cadastral Agencies (NMCAs) and all other public and scientific institutions responsible for the production of geospatial information closely co-operate in making their data in that field available. This crucial sharing of geographic information is a top-level priority, not only in a disaster emergency situation, but also for effective urban and environmental planning and Cultural Heritage protection and preservation. Geospatial data-sharing, responding to the needs of all institutions involved in disaster surveying operations, is fundamental, as a priority, to the task of avoiding loss of human lives. However, no less important is the acquisition, dissemination and use of this data, in addition to direct, “in-the-field” operations of specialists in geomatics, in order to preserve the Cultural Heritage located in the crisis area. It is in this context that an NMCA such as the Italian Military Geographic Institute (IGMI) plays a key role.

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Richardson, Douglas B., Mei-Po Kwan, George Alter, and Jean E. McKendry. "Replication of scientific research: addressing geoprivacy, confidentiality, and data sharing challenges in geospatial research." Annals of GIS 21, no. 2 (April 3, 2015): 101–10. http://dx.doi.org/10.1080/19475683.2015.1027792.

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Jun, Sanghwan, and Sungho Lee. "Prototype system for geospatial data building-sharing developed by utilizing open source web technology." Spatial Information Research 25, no. 5 (October 2017): 725–33. http://dx.doi.org/10.1007/s41324-017-0138-y.

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Zhang, H., W. Huang, J. Jiang, M. Du, and J. Yang. "A HIGH-CURRENCY GEO-SPATIAL SERVICE GATEWAY FOR NATIONAL GEO-INFORMATION SERVICE PLATFORM." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2021 (June 30, 2021): 383–88. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2021-383-2021.

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Abstract. Today, more and more geospatial services are provided by the governments and enterprises to share various geographic information data and functions, and services-based application integration has become a trend. However, many problems existed in the geo-platform for Geographic information sharing while providing services in the form of API, such as the coexistence of different versions of the same service, similar service routes of different APIs, cluttered service protocols, and complex authority management, that makes the integration among different geographic information services difficult and reduces the development efficiency. There are already some API gateway technologies to solve the problem, but the characteristics of geospatial services are not considered in the existing product. To address these problems, this paper proposed a high-currency geospatial service gateway system for National Geo-Information Service Platform based on the opensource framework of Kong for realizing the unified management and authorized open. The system provides the whole lifecycle management and fine-grained control for the service, and the functions such as unified geospatial service access, protocol conversion, service management, authorization verification, rate limiting, and security protection are also equipped. The system has been released and integrated in the National Geo-Information Service Platform, supporting hundreds of millions of service invocation every day. The result proves it simplifies geospatial services management, deployment, and application, and benefits the exchanging and sharing of geographic information.

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Ventura, Bartolomeo, Andrea Vianello, Daniel Frisinghelli, Mattia Rossi, Roberto Monsorno, and Armin Costa. "A Methodology for Heterogeneous Sensor Data Organization and Near Real-Time Data Sharing by Adopting OGC SWE Standards." ISPRS International Journal of Geo-Information 8, no. 4 (April 2, 2019): 167. http://dx.doi.org/10.3390/ijgi8040167.

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Finding a solution to collect, analyze, and share, in near real-time, data acquired by heterogeneous sensors, such as traffic, air pollution, soil moisture, or weather data, represents a great challenge. This paper describes the solution developed at Eurac Research to automatically upload data, in near real-time, by adopting Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) standards to guarantee interoperability. We set up a methodology capable of ingesting heterogeneous datasets to automatize observation uploading and sensor registration, with minimum interaction required of the user. This solution has been successfully tested and applied in the Long Term (Socio-)Ecological Research (LT(S)ER) Matsch-Mazia initiative, and the code is accessible under the CC BY 4.0 license.

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Widyaningrum, E., and B. G. H. Gorte. "CHALLENGES AND OPPORTUNITIES: ONE STOP PROCESSING OF AUTOMATIC LARGE-SCALE BASE MAP PRODUCTION USING AIRBORNE LIDAR DATA WITHIN GIS ENVIRONMENT. CASE STUDY: MAKASSAR CITY, INDONESIA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 365–69. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-365-2017.

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LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information Agency in Indonesia. As a progressive advanced technology, Geographic Information System (GIS) open possibilities to deal with geospatial data automatic processing and analyses. Considering further needs of spatial data sharing and integration, the one stop processing of LiDAR data in a GIS environment is considered a powerful and efficient approach for the base map provision. The quality of the automated topographic base map is assessed and analysed based on its completeness, correctness, quality, and the confusion matrix.

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Tateishi, R., J. T. Sri Sumantyo, A. Miyazaki, and H. Sumitani. "DEVELOPMENT OF A NEW GEOSPATIAL DATA SHARING/OVERLAY SYSTEM FOR LAND ENVIRONMENTAL STUDIES – CERES GAIA –." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B4 (July 31, 2012): 201–2. http://dx.doi.org/10.5194/isprsarchives-xxxix-b4-201-2012.

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Giuliani, G., and P. Peduzzi. "The PREVIEW Global Risk Data Platform: a geoportal to serve and share global data on risk to natural hazards." Natural Hazards and Earth System Sciences 11, no. 1 (January 5, 2011): 53–66. http://dx.doi.org/10.5194/nhess-11-53-2011.

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Abstract. With growing world population and concentration in urban and coastal areas, the exposure to natural hazards is increasing and results in higher risk of human and economic losses. Improving the identification of areas, population and assets potentially exposed to natural hazards is essential to reduce the consequences of such events. Disaster risk is a function of hazard, exposure and vulnerability. Modelling risk at the global level requires accessing and processing a large number of data, from numerous collaborating centres. These data need to be easily updated, and there is a need for centralizing access to this information as well as simplifying its use for non GIS specialists. The Hyogo Framework for Action provides the mandate for data sharing, so that governments and international development agencies can take appropriate decision for disaster risk reduction. Timely access and easy integration of geospatial data are essential to support efforts in Disaster Risk Reduction. However various issues in data availability, accessibility and integration limit the use of such data. In consequence, a framework that facilitate sharing and exchange of geospatial data on natural hazards should improve decision-making process. The PREVIEW Global Risk Data Platform is a highly interactive web-based GIS portal supported by a Spatial Data Infrastructure that offers free and interoperable access to more than 60 global data sets on nine types of natural hazards (tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions) and related exposure and risk. This application portrays an easy-to-use online interactive mapping interface so that users can easily work with it and seamlessly integrate data in their own data flow using fully compliant OGC Web Services (OWS).

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Percivall, George, and Ingo Simonis. "ADVANCEMENTS IN OPEN GEOSPATIAL STANDARDS FOR PHOTOGRAMMETRY AND REMOTE SENSING FROM OGC." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 705–9. http://dx.doi.org/10.5194/isprsarchives-xli-b4-705-2016.

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The necessity of open standards for effective sharing and use of remote sensing continues to receive increasing emphasis in policies of agencies and projects around the world. Coordination on the development of open standards for geospatial information is a vital step to insure that the technical standards are ready to support the policy objectives. The mission of the Open Geospatial Consortium (OGC) is to advance development and use of international standards and supporting services that promote geospatial interoperability. To accomplish this mission, OGC serves as the global forum for the collaboration of geospatial data / solution providers and users. Photogrammetry and remote sensing are sources of the largest and most complex geospatial information. Some of the most mature OGC standards for remote sensing include the Sensor Web Enablement (SWE) standards, the Web Coverage Service (WCS) suite of standards, encodings such as NetCDF, GMLJP2 and GeoPackage, and the soon to be approved Discrete Global Grid Systems (DGGS) standard. In collaboration with ISPRS, OGC working with government, research and industrial organizations continue to advance the state of geospatial standards for full use of photogrammetry and remote sensing.

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Journal articles on the topic 'Geospatial data sharing'

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