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Keywords = web processing service (WPS)

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21 pages, 993 KiB  
Article
PQ-Mist: Priority Queueing-Assisted Mist–Cloud–Fog System for Geospatial Web Services
by Sunil K. Panigrahi, Veena Goswami, Hemant K. Apat, Ganga B. Mund, Himansu Das and Rabindra K. Barik
Mathematics 2023, 11(16), 3562; https://doi.org/10.3390/math11163562 - 17 Aug 2023
Cited by 3 | Viewed by 2087
Abstract
The IoT and cloud environment renders enormous quantities of geospatial information. Fog and mist computing is the scaling technology that handles geospatial data and sends it to the cloud storage system through fog/mist nodes. Installing a mist–cloud–fog system reduces latency and throughput. This [...] Read more.
The IoT and cloud environment renders enormous quantities of geospatial information. Fog and mist computing is the scaling technology that handles geospatial data and sends it to the cloud storage system through fog/mist nodes. Installing a mist–cloud–fog system reduces latency and throughput. This mist–cloud–fog system has processed different types of geospatial web services, i.e., web coverage service (WCS), web processing services (WPS), web feature services (WFS), and web map services (WMS). There is an urgent requirement to increase the number of computer devices tailored to deliver high-priority jobs for processing these geospatial web services. This paper proposes a priority-queueing assisted mist–cloud–fog system for efficient resource allocation for high- and low-priority tasks. In this study, WFS is treated as high-priority service, whereas WMS is treated as low-priority service. This system dynamically allocates mist nodes and is determined by the load on the system. In addition to that, the assignment of tasks is determined by priority. Not only does this classify high-priority tasks and low-priority tasks, which helps reduce the amount of delay experienced by high-priority jobs, but it also dynamically allocates mist devices within the network depending on the computation load, which helps reduce the amount of power that is consumed by the network. The findings indicate that the proposed system can achieve a significantly lower delay for higher-priority jobs for more significant rates of task arrival when compared with other related schemes. In addition to this, it offers a technique that is both mathematical and analytical for investigating and assessing the performance of the proposed system. The QoS requirements for each device demand are factored into calculating the number of mist nodes deployed to satisfy those requirements. Full article
(This article belongs to the Special Issue Fuzzy Logic and Computational Intelligence)
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22 pages, 1915 KiB  
Article
Geospatial Web Services Discovery through Semantic Annotation of WPS
by Meriem Sabrine Halilali, Eric Gouardères, Mauro Gaio and Florent Devin
ISPRS Int. J. Geo-Inf. 2022, 11(4), 254; https://doi.org/10.3390/ijgi11040254 - 12 Apr 2022
Cited by 6 | Viewed by 3343
Abstract
This paper presents an approach to GWS (GeospatialWeb Service) discovery through the semantic annotation of WPS (Web Processing Service) service descriptions. The rationale behind this work is that search engines that use appropriate semantic-based similarity measures in the matching process are more accurate [...] Read more.
This paper presents an approach to GWS (GeospatialWeb Service) discovery through the semantic annotation of WPS (Web Processing Service) service descriptions. The rationale behind this work is that search engines that use appropriate semantic-based similarity measures in the matching process are more accurate in terms of precision and recall than those based on syntactic matching alone. The lack of semantics in the description of services using a standard such as WPS prevents the use of such a matching process and is considered a limitation of GWS discovery. The GWS discovery approach presented is based on the consideration of semantics in the service description method and in the matching process. The description of services is based on a semantic lightweight meta-model instantiated in the WPS 2.0 standard, extending the description of the service through metadata tags. The matching process is performed in three steps (functionality matching step, I/O (Input/Output) matching step and non-functional matching step). Its core is a semantic similarity measure that combines logical and non-logical matching methods. Finally, the paper presents the results of an experiment applying the proposed discovery approach on a GWS corpus, showing promising results and the added value of the three-step matching process. Full article
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19 pages, 11052 KiB  
Technical Note
JupyTEP IDE as an Online Tool for Earth Observation Data Processing
by Jacek Rapiński, Michał Bednarczyk and Daniel Zinkiewicz
Remote Sens. 2019, 11(17), 1973; https://doi.org/10.3390/rs11171973 - 21 Aug 2019
Cited by 8 | Viewed by 4826
Abstract
The paper describes a new tool called JupyTEP integrated development environment (IDE), which is an online integrated development environment for earth observation data processing available in the cloud. This work is a result of the project entitled “JupyTEP IDE—Jupyter-based IDE as an interactive [...] Read more.
The paper describes a new tool called JupyTEP integrated development environment (IDE), which is an online integrated development environment for earth observation data processing available in the cloud. This work is a result of the project entitled “JupyTEP IDE—Jupyter-based IDE as an interactive and collaborative environment for the development of notebook style EO algorithms on network of exploitation platforms infrastructure” carried out in cooperation with European Space Agency. The main goal of this project was to provide a universal earth observation data processing tool to the community. JupyTEP IDE is an extension of Jupyter software ecosystem with customization of existing components for the needs of earth observation scientists and other professional and non-professional users. The approach is based on configuration, customization, adaptation, and extension of Jupyter, Jupyter Hub, and Docker components on earth observation data cloud infrastructure in the most flexible way; integration with accessible libraries and earth observation data tools (sentinel application platform (SNAP), geospatial data abstraction library (GDAL), etc.); adaptation of existing web processing service (WPS)-oriented earth observation services. The user-oriented product is based on a web-related user interface in the form of extended and modified Jupyter user interface (frontend) with customized layout, earth observation data processing extension, and a set of predefined notebooks, widgets, and tools. The final IDE is addressed to the remote sensing experts and other users who intend to develop Jupyter notebooks with the reuse of embedded tools, common WPS interfaces, and existing notebooks. The paper describes the background of the system, its architecture, and possible use cases. Full article
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16 pages, 3939 KiB  
Article
A Performance Evaluation of a Geo-Spatial Image Processing Service Based on Open Source PaaS Cloud Computing Using Cloud Foundry on OpenStack
by Kiwon Lee and Kwangseob Kim
Remote Sens. 2018, 10(8), 1274; https://doi.org/10.3390/rs10081274 - 13 Aug 2018
Cited by 9 | Viewed by 5306
Abstract
Recently, web application services based on cloud computing technologies are being offered. In the web-based application field of geo-spatial data management or processing, data processing services are produced or operated using various information communication technologies. Platform-as-a-Service (PaaS) is a type of cloud computing [...] Read more.
Recently, web application services based on cloud computing technologies are being offered. In the web-based application field of geo-spatial data management or processing, data processing services are produced or operated using various information communication technologies. Platform-as-a-Service (PaaS) is a type of cloud computing service model that provides a platform that allows service providers to implement, execute, and manage applications without the complexity of establishing and maintaining the lower-level infrastructure components, typically related to application development and launching. There are advantages, in terms of cost-effectiveness and service development expansion, of applying non-proprietary PaaS cloud computing. Nevertheless, there have not been many studies on the use of PaaS technologies to build geo-spatial application services. This study was based on open source PaaS technologies used in a geo-spatial image processing service, and it aimed to evaluate the performance of that service in relation to the Web Processing Service (WPS) 2.0 specification, based on the Open Geospatial Consortium (OGC) after a test application deployment using the configured service supported by a cloud environment. Using these components, the performance of an edge extraction algorithm on the test system in three cases, of 300, 500, and 700 threads, was assessed through a comparison test with another test system, in the same three cases, using Infrastructure-as-a-Service (IaaS) without Load Balancer-as-a-Service (LBaaS). According to the experiment results, in all the test cases of WPS execution considered in this study, the PaaS-based geo-spatial service had a greater performance and lower error rates than the IaaS-based cloud without LBaaS. Full article
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15 pages, 3035 KiB  
Article
A Javascript GIS Platform Based on Invocable Geospatial Web Services
by Konstantinos Evangelidis and Theofilos Papadopoulos
Geosciences 2018, 8(4), 139; https://doi.org/10.3390/geosciences8040139 - 20 Apr 2018
Cited by 1 | Viewed by 8312
Abstract
Semantic Web technologies are being increasingly adopted by the geospatial community during last decade through the utilization of open standards for expressing and serving geospatial data. This was also dramatically assisted by the ever-increasing access and usage of geographic mapping and location-based services [...] Read more.
Semantic Web technologies are being increasingly adopted by the geospatial community during last decade through the utilization of open standards for expressing and serving geospatial data. This was also dramatically assisted by the ever-increasing access and usage of geographic mapping and location-based services via smart devices in people’s daily activities. In this paper, we explore the developmental framework of a pure JavaScript client-side GIS platform exclusively based on invocable geospatial Web services. We also extend JavaScript utilization on the server side by deploying a node server acting as a bridge between open source WPS libraries and popular geoprocessing engines. The vehicle for such an exploration is a cross platform Web browser capable of interpreting JavaScript commands to achieve interaction with geospatial providers. The tool is a generic Web interface providing capabilities of acquiring spatial datasets, composing layouts and applying geospatial processes. In an ideal form the end-user will have to identify those services, which satisfy a geo-related need and put them in the appropriate row. The final output may act as a potential collector of freely available geospatial web services. Its server-side components may exploit geospatial processing suppliers composing that way a light-weight fully transparent open Web GIS platform. Full article
(This article belongs to the Special Issue Geodata Management)
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14 pages, 10074 KiB  
Article
Linkage of OGC WPS 2.0 to the e-Government Standard Framework in Korea: An Implementation Case for Geo-Spatial Image Processing
by Gooseon Yoon, Kwangseob Kim and Kiwon Lee
ISPRS Int. J. Geo-Inf. 2017, 6(1), 25; https://doi.org/10.3390/ijgi6010025 - 20 Jan 2017
Cited by 5 | Viewed by 6366
Abstract
There are many cases wherein services offered in geospatial sectors are integrated with other fields. In addition, services utilizing satellite data play important roles in daily life and in sectors such as environment and science. Therefore, a management structure appropriate to the scale [...] Read more.
There are many cases wherein services offered in geospatial sectors are integrated with other fields. In addition, services utilizing satellite data play important roles in daily life and in sectors such as environment and science. Therefore, a management structure appropriate to the scale of the system should be clearly defined. The motivation of this study is to resolve issues, apply standards related to a target system, and provide practical strategies with a technical basis. South Korea uses the e-Government Standard Framework, using the Java-based Spring framework, to provide guidelines and environments with common configurations and functions for developing web-based information systems for public services. This web framework offers common sources and resources for data processing and interface connection to help developers focus on business logic in designing a web system. In this study, a geospatial image processing system—linked with the Open Geospatial Consortium (OGC) Web Processing Service (WPS) 2.0 standard for real geospatial information processing, and based on this standard framework—was designed and built utilizing fully open sources. This is the first case of implementation based on WPS 2.0 running on the e-Government Standard Framework. Establishing a standard for its use will be important, and the system built in this study can serve as a reference for the foundational architecture in building geospatial web service systems with geodata-processing functionalities in government agencies. Full article
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14 pages, 1517 KiB  
Article
Building an Elastic Parallel OGC Web Processing Service on a Cloud-Based Cluster: A Case Study of Remote Sensing Data Processing Service
by Xicheng Tan, Liping Di, Meixia Deng, Jing Fu, Guiwei Shao, Meng Gao, Ziheng Sun, Xinyue Ye, Zongyao Sha and Baoxuan Jin
Sustainability 2015, 7(10), 14245-14258; https://doi.org/10.3390/su71014245 - 21 Oct 2015
Cited by 16 | Viewed by 5938
Abstract
Since the Open Geospatial Consortium (OGC) proposed the geospatial Web Processing Service (WPS), standard OGC Web Service (OWS)-based geospatial processing has become the major type of distributed geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the [...] Read more.
Since the Open Geospatial Consortium (OGC) proposed the geospatial Web Processing Service (WPS), standard OGC Web Service (OWS)-based geospatial processing has become the major type of distributed geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the dominant challenge for OWSs. This paper presents the construction of an elastic parallel OGC WPS service on a cloud-based cluster and the designs of a high-performance, cloud-based WPS service architecture, the scalability scheme of the cloud, and the algorithm of the elastic parallel geoprocessing. Experiments of the remote sensing data processing service demonstrate that our proposed method can provide a higher-performance WPS service that uses less computing resources. Our proposed method can also help institutions reduce hardware costs, raise the rate of hardware usage, and conserve energy, which is important in building green and sustainable geospatial services or applications. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management & Sustainable Ecosystem)
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18 pages, 1238 KiB  
Article
The RichWPS Environment for Orchestration
by Felix Bensmann, Dorian Alcacer-Labrador, Dennis Ziegenhagen and Rainer Roosmann
ISPRS Int. J. Geo-Inf. 2014, 3(4), 1334-1351; https://doi.org/10.3390/ijgi3041334 - 5 Dec 2014
Cited by 7 | Viewed by 7288
Abstract
Web service (WS) orchestration can be considered as a fundamental concept in service-oriented architectures (SOA), as well as in spatial data infrastructures (SDI). In recent years in SOA, advanced solutions were developed, such as realizing orchestrated web services on the basis of already [...] Read more.
Web service (WS) orchestration can be considered as a fundamental concept in service-oriented architectures (SOA), as well as in spatial data infrastructures (SDI). In recent years in SOA, advanced solutions were developed, such as realizing orchestrated web services on the basis of already existing more fine-granular web services by using standardized notations and existing orchestration engines. Even if the concepts can be mapped to the field of SDI, on a conceptual level the implementations target different goals. As a specialized form of a common web service, an Open Geospatial Consortium (OGC) web service (OWS) is optimized for a specific purpose. On the technological level, web services depend on standards like the Web Service Description Language (WSDL) or the Simple Object Access Protocol (SOAP). However OWS are different. Consequently, a new concept for OWS orchestration is needed that works on the interface provided by OWS. Such a concept is presented in this work. The major component is an orchestration engine integrated in a Web Processing Service (WPS) server that uses a domain specific language (DSL) for workflow description. The developed concept is the base for the realization of new functionality, such as workflow testing, and workflow optimization. Full article
(This article belongs to the Special Issue 20 Years of OGC: Open Geo-Data, Software, and Standards)
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19 pages, 1269 KiB  
Article
Pygrass: An Object Oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS)
by Pietro Zambelli, Sören Gebbert and Marco Ciolli
ISPRS Int. J. Geo-Inf. 2013, 2(1), 201-219; https://doi.org/10.3390/ijgi2010201 - 11 Mar 2013
Cited by 40 | Viewed by 14446
Abstract
PyGRASS is an object-oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS), a powerful open source GIS widely used in academia, commercial settings and governmental agencies. We present the architecture of the PyGRASS library, covering [...] Read more.
PyGRASS is an object-oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS), a powerful open source GIS widely used in academia, commercial settings and governmental agencies. We present the architecture of the PyGRASS library, covering interfaces to GRASS modules, vector and raster data, with a focus on the new capabilities that it provides to GRASS users and developers. Our design concept of the module interface allows the direct linking of inputs and outputs of GRASS modules to create process chains, including compatibility checks, process control and error handling. The module interface was designed to be easily extended to work with remote processing services (Web Processing Service (WPS), Web Service Definition Language (WSDL)/Simple Object Access Protocol (SOAP)). The new object-oriented Python programming API introduces an abstract layer that opens the possibility to use and access transparently the efficient raster and vector functions of GRASS that are implemented in C. The design goal was to provide an easy to use, but powerful, Python interface for users and developers who are not familiar with the programming language C and with the GRASS C-API. We demonstrate the capabilities, scalability and performance of PyGRASS with several dedicated tests and benchmarks. We compare and discuss the results of the benchmarks with dedicated C implementations. Full article
(This article belongs to the Special Issue Geospatial Monitoring and Modelling of Environmental Change)
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24 pages, 2653 KiB  
Article
Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification
by Juliane Huth, Claudia Kuenzer, Thilo Wehrmann, Steffen Gebhardt, Vo Quoc Tuan and Stefan Dech
Remote Sens. 2012, 4(9), 2530-2553; https://doi.org/10.3390/rs4092530 - 7 Sep 2012
Cited by 60 | Viewed by 15601
Abstract
We present a novel and innovative automated processing environment for the derivation of land cover (LC) and land use (LU) information. This processing framework named TWOPAC (TWinned Object and Pixel based Automated classification Chain) enables the standardized, independent, user-friendly, and comparable derivation of [...] Read more.
We present a novel and innovative automated processing environment for the derivation of land cover (LC) and land use (LU) information. This processing framework named TWOPAC (TWinned Object and Pixel based Automated classification Chain) enables the standardized, independent, user-friendly, and comparable derivation of LC and LU information, with minimized manual classification labor. TWOPAC allows classification of multi-spectral and multi-temporal remote sensing imagery from different sensor types. TWOPAC enables not only pixel-based classification, but also allows classification based on object-based characteristics. Classification is based on a Decision Tree approach (DT) for which the well-known C5.0 code has been implemented, which builds decision trees based on the concept of information entropy. TWOPAC enables automatic generation of the decision tree classifier based on a C5.0-retrieved ascii-file, as well as fully automatic validation of the classification output via sample based accuracy assessment.Envisaging the automated generation of standardized land cover products, as well as area-wide classification of large amounts of data in preferably a short processing time, standardized interfaces for process control, Web Processing Services (WPS), as introduced by the Open Geospatial Consortium (OGC), are utilized. TWOPAC’s functionality to process geospatial raster or vector data via web resources (server, network) enables TWOPAC’s usability independent of any commercial client or desktop software and allows for large scale data processing on servers. Furthermore, the components of TWOPAC were built-up using open source code components and are implemented as a plug-in for Quantum GIS software for easy handling of the classification process from the user’s perspective. Full article
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