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Artículos de revistas

Literatura académica sobre el tema "Geospatial APIs"

Autor: Grafiati

Publicado: 10 de marzo de 2023

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Artículos de revistas sobre el tema "Geospatial APIs"

1

Eldawy, Ahmed, and Gobe Hobona. "The 2nd ACM SIGSPATIAL International Workshop on Geospatial Data Access and Processing APIs (SpatialAPI 2020)." SIGSPATIAL Special 12, no. 3 (2021): 20–22. http://dx.doi.org/10.1145/3447994.3448003.

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With the increasing amount of publicly available geospatial data, the demand on spatial data exploration and analysis kept growing. The SIGSPATIAL community is both a provider of new systems with cutting-edge technology on accessing and processing geospatial data, and a user for all these systems. The SpatialAPI workshop is designed to help the SIGSPATIAL community by growing the knowledge of the existing well-established systems that are available for accessing and processing geospatial data. This includes, but is not limited to, web APIs, programming libraries, database systems, and geospati

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2

Mooney, P., and M. Minghini. "GEOSPATIAL DATA EXCHANGE USING BINARY DATA SERIALIZATION APPROACHES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W1-2022 (August 6, 2022): 307–13. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-307-2022.

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Abstract. In this paper we investigate the benefits of binary data serialization as a means of storing and sharing large amounts of geospatial data in an interoperable way. De-facto text-based exchange encodings typically exposed by modern Application Programming Interfaces (APIs), including eXtensible Markup Language (XML) and JavaScript Object Notation (JSON), are generally inefficient for an increasingly higher number of applications due to their inflated volumes of data, low speed and the high computational cost for parsing and processing. In this work we consider comparisons of JSON/Geosp

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3

Tischler, Michael A. "Accelerating Geospatial Modeling in ArcGIS with Graphical Processor Units." International Journal of Applied Geospatial Research 7, no. 4 (2016): 41–52. http://dx.doi.org/10.4018/ijagr.2016100104.

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Geospatial data can be enormous in size and tedious to process efficiently on standard computational workstations. Distributing the processing tasks through highly parallelized processing reduces the burden on the primary processor and processing times can drastically shorten as a result. ERSI's ArcGIS, while widely used in the military, does not natively support multi-core processing or utilization of graphic processor units (GPUs). However, the ArcPy Python library included in ArcGIS 10 provides geospatial developers with the means to process geospatial data in a flexible environment that ca

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4

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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<p><strong>Abstract.</strong> 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 spatia

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5

Virtanen, Juho-Pekka, Arttu Julin, Kaisa Jaalama, and Hannu Hyyppä. "Creating Open Online Applications with Geospatial Interfaces - Case Study "Palvelututka"." Photogrammetric Journal of FInland 27, no. 2 (2021): 1–14. http://dx.doi.org/10.17690/021272.1.

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Three-dimensional city models are an increasingly common data set maintained by many cities globally. At the same time, the focus of research has shifted from their production to their utilization in application development. We present the implementation of a demonstrator application combining the online visualization of a 3D city information model with the data from an application programming interface. By this, we aim to demonstrate the combined use of city APIs and 3D geospatial assets, promote their use for application development and show the performance of existing, openly available tool

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6

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

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7

Simoes, J., and A. Cerciello. "SERVING GEOSPATIAL DATA USING MODERN AND LEGACY STANDARDS: A CASE STUDY FROM THE URBAN HEALTH DOMAIN." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W1-2022 (August 6, 2022): 419–25. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-419-2022.

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Abstract. The eMOTIONAL Cities project sets out to understand how the natural and built environment can shape the feelings and emotions of those who experience it. It does so with a cross-disciplinary approach which includes urban planners, doctors, psychologists, neuroscientists and engineers. At the core of this research project, lies a Spatial Data Infrastructure (SDI) which assembles datasets that characterise the emotional landscape and built environment, in different Cities across Europe and the US. The SDI is a key tool, not only to make the research data available within the project co

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8

Bhattacharya, D., and M. Painho. "DESIGN FOR CONNECTING SPATIAL DATA INFRASTRUCTURES WITH SENSOR WEB (SENSDI)." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-4 (June 3, 2016): 33–39. http://dx.doi.org/10.5194/isprsannals-iii-4-33-2016.

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Integrating Sensor Web With Spatial Data Infrastructures (SENSDI) aims to extend SDIs with sensor web enablement, converging geospatial and built infrastructure, and implement test cases with sensor data and SDI. It is about research to harness the sensed environment by utilizing domain specific sensor data to create a generalized sensor webframework. The challenges being semantic enablement for Spatial Data Infrastructures, and connecting the interfaces of SDI with interfaces of Sensor Web. The proposed research plan is to Identify sensor data sources, Setup an open source SDI, Match the APIs

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9

Bhattacharya, D., and M. Painho. "DESIGN FOR CONNECTING SPATIAL DATA INFRASTRUCTURES WITH SENSOR WEB (SENSDI)." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-4 (June 3, 2016): 33–39. http://dx.doi.org/10.5194/isprs-annals-iii-4-33-2016.

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Integrating Sensor Web With Spatial Data Infrastructures (SENSDI) aims to extend SDIs with sensor web enablement, converging geospatial and built infrastructure, and implement test cases with sensor data and SDI. It is about research to harness the sensed environment by utilizing domain specific sensor data to create a generalized sensor webframework. The challenges being semantic enablement for Spatial Data Infrastructures, and connecting the interfaces of SDI with interfaces of Sensor Web. The proposed research plan is to Identify sensor data sources, Setup an open source SDI, Match the APIs

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10

NOLAN, JAMES J., ARUN K. SOOD, and ROBERT SIMON. "DISCOVERING AND COMPOSING DISTRIBUTED ATOMIC AGENTS FOR IMAGERY AND GEOSPATIAL PROBLEM SOLVING." International Journal of Pattern Recognition and Artificial Intelligence 16, no. 08 (2002): 995–1019. http://dx.doi.org/10.1142/s021800140200212x.

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This paper describes our approach to building a scalable, flexible agent-based architecture for imagery and geospatial processing. Central to this approach is the agent discovery and composition mechanism which scales to support networks with thousands of agents. The agent architecture implements over 100 imagery and geospatial processing agents based on the Java Advanced Imaging and OpenMap(TM) APIs. The agents are distributed over a Jini enabled network, and communicate with one another via JavaSpaces. We discuss our "atomic" approach in this paper: developing low-level processing agents tha

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