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Online image classification and analysis using OGC web processing service

EARTH SCIENCE INFORMATICS 2019年第3期12卷 307-317页

作者： Singh, Hariom Garg, R. D. Karnatak, Harish C. Indian Inst Technol Roorkee Dept Civil Engn Geomat Engn Grp Roorkee Uttar Pradesh India ISRO Indian Inst Remote Sensing Dehra Dun Uttar Pradesh India

The online geoprocessing and analysis using state-of-the-art technology are offering automated analytical tools to a large group of users. This paper describes an online geoprocessing and analysis framework, which allows an inexperienced user to perform unsupervised classification of remote sensing data. The parallel computing based geoprocessing and analysis framework adopted in this work has been implemented using Free and Open Source Software for Geospatial (FOSS4G). web processing service (WPS) based geoprocessing framework facilitates the deployment of unsupervised classification algorithm on the web in a standardized way. However, it is dynamic in nature to deploy other geoprocessing algorithms. The developed system describes how to process remote sensing data (Sentinel-2, Landsat-8, etc.) for classification and sharing the interoperable results in a distributed environment. To validate the classification results, a prototype architecture based on participatory GIS is developed for field data collection, accuracy assessment and online dissemination. The accuracy assessment (i.e., overall accuracy, Kappa coefficient) is performed to validate the derived classification results using collected field data.

关键词： Distributed GIS Parallel computing Unsupervised classification web processing service Participatory GIS

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An automated and optimized approach for online spatial biodiversity model: a case study of OGC web processing service

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GEOCARTO INTERNATIONAL 2019年第2期34卷 194-214页

作者： Singh, Hariom Karnatak, Harish C. Garg, R. D. Indian Inst Technol Roorkee Civil Engn Dept Geomat Engn Grp Roorkee Uttar Pradesh India ISRO Indian Inst Remote Sensing Dehra Dun India

An online spatial biodiversity model (SBM) for optimized and automated spatial modelling and analysis of geospatial data is proposed, which is based on web processing service (WPS) and web service orchestration (WSO) in parallel computing environment. The developed model integrates distributed geospatial data in geoscientific processing workflow to compute the algorithms of spatial landscape indices over the web using free and open source software. A case study for Uttarakhand state of India demonstrates the model outputs such as spatial biodiversity disturbance index (SBDI) and spatial biological richness index (SBRI). In order to optimize and automate, an interactive web interface is developed using participatory GIS approaches for implementing fuzzy AHP. In addition, sensitivity analysis and geosimulation experiments are also performed under distributed GIS environment. Results suggest that parallel algorithms in SBM execute faster than sequential algorithms and validation of SBRI with biological diversity shows significant correlation by indicating high R-2 values.

关键词： web processing service parallel computing spatial biodiversity model distributed GIS fuzzy AHP participatory GIS

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web processing service for climate impact and extreme weather event analyses. Flyingpigeon (Version 1.0)

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COMPUTERS & GEOSCIENCES 2018年 110卷 65-72页

作者： Hempelmann, Nils Ehbrecht, Carsten Alvarez-Castro, Carmen Brockmann, Patrick Falk, Wolfgang Hoffmann, Jorg Kindermann, Stephan Koziol, Ben Nangini, Cathy Radanovics, Sabine Vautard, Robert Yiou, Pascal Lab Sci Climat & Environm St Aubin Essonne France German Climate Comp Ctr Hamburg Germany Bayer Landesanstalt Wald & Forstwirtschaft Freising Weihenstephan Germany Julius Kuhn Inst Fed Res Ctr Cultivated Plants Quedlinburg Germany Univ Colorado NOAA Environm Software Infrastruct & Interoperabil Grp Boulder CO 80309 USA

Analyses of extreme weather events and their impacts often requires big data processing of ensembles of climate model simulations. Researchers generally proceed by downloading the data from the providers and processing the data files "at home" with their own analysis processes. However, the growing amount of available climate model and observation data makes this procedure quite awkward. In addition, data processing knowledge is kept local, instead of being consolidated into a common resource of reusable code. These drawbacks can be mitigated by using a web processing service (WPS). A WPS hosts services such as data analysis processes that are accessible over the web, and can be installed close to the data archives. We developed a WPS named 'flyingpigeon' that communicates over an HTTP network protocol based on standards defined by the Open Geospatial Consortium (OGC), to be used by climatologists and impact modelers as a tool for analyzing large datasets remotely. Here, we present the current processes we developed in flyingpigeon relating to commonly-used processes (preprocessing steps, spatial subsets at continent, country or region level, and climate indices) as well as methods for specific climate data analysis (weather regimes, analogues of circulation, segetal flora distribution, and species distribution models). We also developed a novel, browser-based interactive data visualization for circulation analogues, illustrating the flexibility of WPS in designing custom outputs. Bringing the software to the data instead of transferring the data to the code is becoming increasingly necessary, especially with the upcoming massive climate datasets.

关键词： web processing service Climate impact Extreme weather events Birdhouse OGC

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An end-user-friendly hydrological web service for hydrograph prediction in ungauged basins

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HYDROLOGICAL SCIENCES JOURNAL 2022年第16期67卷 2420-2428页

作者： Dallery, Donatien Squividant, Herve de Lavenne, Alban Launay, Josette Cudennec, Christophe INRAE Inst Agro UMR SAS Rennes France SMHI Norrkoping Sweden

A consolidated geomorphology-based approach for discharge prediction in ungauged basins (PUB) through deconvolution of discharge signals from gauged donor catchments, their transposition and their convolution towards target outlets, has been made available online to end users through a web processing service (WPS) for the synoptic peninsular region of Brittany, France. In the spirit of hydrological services, the SIMFEN WPS allows anyone to execute the hydrological modelling package transfR online through: (1) Open Geospatial Consortium (OGC (R)) interoperability standards;(2) collection and use of public hydrometric data;(3) connection to the pre-existing MNTSurf WPS for geomorphometric analysis;(4) visualization using a collaboratively developed Mviewer;and (5) innovative WPS workflows. The ability to model discharge series at any ungauged outlet of the synoptic region is offered to specialists of other disciplines, non-modeller water practitioners and interested citizens to support interdisciplinarity, water monitoring and management, and related science-society-policy debates and actions.

关键词： prediction in ungauged basins (PUB) unsolved problems in hydrology (UPH) UPH #21 discharge series online modelling hydrological service global framework for climate services (GFCS) open geospatial consortium (OGC® ) web processing service

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NLPHub: An e-Infrastructure-based text mining hub

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2021年第5期33卷 e5986-e5986页

作者： Coro, Gianpaolo Panichi, Giancarlo Pagano, Pasquale Perrone, Erico CNR Ist Sci & Tecnol Informaz A Faedo Via G Moruzzi 1 I-56124 Pisa Italy

Text mining involves a set of processes that analyze text to extract high-quality information. Among its large number of applications, there are experiments that tackle big data challenges using complex system architectures. However, text mining approaches are neither easy to discover and use nor easily combinable by end-users. Furthermore, they should be contextualized within new approaches to science (eg, Open Science) that ensure longevity and reuse of methods and results. This article presents NLPHub, a distributed system that orchestrates and combines several state-of-the-art text mining services that recognize spatiotemporal events, keywords, and a large set of named entities. NLPHub adopts an Open Science approach, which fosters the reproducibility, repeatability, and reusability of methods and results, by using an e-Infrastructure supporting data-intensive Science. NLPHub adds Open Science-compliance to the connected services through the use of representational standards for services and computations. It also manages heterogeneous service access policies and enables collaboration and sharing facilities. This article reports a performance assessment based on an annotated corpus of named entities, which demonstrates that NLPHub can improve the performance of the single-integrated processes by cleverly combining their output.

关键词： cloud computing natural language processing Open Science Software-as-a-service text processing text mining e-Infrastructures web processing service

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A web service based advanced traveller information system for itinerary planning in an uncertain multimodal network

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GEOCARTO INTERNATIONAL 2020年第14期35卷 1553-1569页

作者： Ghavami, Seyed Morsal Univ Zanjan Fac Engn Geomat Dept Zanjan Iran

This article intends to provide an advanced traveller information system based on open geospatial consortium (OGC) standards to perform a fuzzy bi-criteria shortest-path analysis for a multimodal transportation network. To do so, chaining of OGC web services is used to resolve interoperability problems among distributed and heterogeneous resource data. First, a web feature service is assigned to each mode of transportation to gather and convert the data to a standard format, such as geographic markup language. Then, the obtained data are combined to model and construct the multimodal transportation network. Subsequently, a web processing service is designed for performing a fuzzy bi-criteria shortest-path analysis in the multimodal transportation network. Finally, the best routes between the origin-destination pair are presented on a digital map by using a web map service. In the study, among various route-selection criteria, travel time and comfort are considered. To model these criteria, the fuzzy set theory is utilized. By using fuzzy decision tables and a Tsukamoto fuzzy inference system, the desirability of the routes is calculated. The results of comparison among the four travel routes between various origin-destination pairs indicate that the proposed system could be an applicable tool for providing pre-trip information and assisting multimodal travellers under uncertain conditions.

关键词： Open Geospatial Consortium advanced traveller information system multimodal transportation networks web processing service Tsukamoto fuzzy inference systems

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Cloud Computing Enabled web processing service for Earth Observation Data processing

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2012年第6期5卷 1637-1649页

作者： Chen, Zeqiang Chen, Nengcheng Yang, Chao Di, Liping Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430079 Peoples R China George Mason Univ CSISS Fairfax VA 22032 USA

The OpenGIS web processing service (WPS) can process both simple and complex geospatial tasks including Earth Observation tasks. As the requirements of Earth Observation data, algorithms, calculation models, and daily life become increasingly complicated;WPS needs to provide high-performance service-oriented computing capability. This paper proposes a cloud computing enabled WPS framework for Earth Observation data processing. It consists of a client layer and a WPS layer, which further consists of a WPS server layer and a cloud computing layer. The cloud computing environment is based on the open-source software Apache Hadoop. The three layers of the proposed cloud computing enabled WPS are outlined, followed by a workflow that processes a user's task using these three layers. Then technological implementation details are explained. An experiment processing Moderate Resolution Imaging Spectro-radiometer (MODIS) data shows that WPS can be enabled in a cloud computing environment.

关键词： Apache Hadoop cloud computing earth observation data processing service oriented architecture web processing service

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Enhancing the OGC WPS interface with GeoPipes support for real-time geoprocessing

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International Journal of Digital Earth 2018年第1期11卷 48-63页

作者： Stefan Herle Jörg Blankenbach Geodetic Institute and Chair for Computing in Civil Engineering and Geo Information Systems RWTH Aachen UniversityAachenGermany

Real-time geospatial information is used in various applications such as risk management or alerting ***,the rise of new sensing technologies also increases the demand for processing the data in real ***’s spatial data infrastructures,however,do not meet the requirements for real-time *** OpenGIS®web processing service(WPS)is not designed to process real-time *** has some major drawbacks in asynchronous processing and cannot handle(geo)data streams out of the *** previous papers,we introduced the GeoPipes approach to share spatiotemporal data in real *** implemented the concept extending the Message Queue and Telemetry Transport(MQTT)protocol by a spatial and temporal dimension,which we call *** this paper,we demonstrate the integration of the GeoPipes idea in the WPS interface to expose standardized real-time geoprocessing *** proof of the concept is illustrated in some exemplary real-time geo processes.

关键词： Real-time geoprocessing web processing service sensor web Internet-ofthings GeoPipes

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JupyTEP IDE as an Online Tool for Earth Observation Data processing

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REMOTE SENSING 2019年第17期11卷 1973-1973页

作者： Rapinski, Jacek Bednarczyk, Michal Zinkiewicz, Daniel Univ Warmia & Mazury Inst Geodesy Fac Geodesy Geospatial & Civil Engn Oczapowskiego 1 PL-10719 Olsztyn Poland WASAT Sp Zoo Trzy Lipy 3 PL-80172 Gdansk Poland

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.

关键词： Docker eEarth observation data processing IDE IPython Jupyter notebook web application web processing service

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Ontology for processing service orchestration 6

Ontology for processing service orchestration

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6th International Conference on Agro-Geoinformatics

作者： Zhang, Mingda Lieberman, Joshua Yue, Peng Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan Hubei Peoples R China Harvard Univ Ctr Geog Analy Cambridge MA 02138 USA Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Hubei Peoples R China

ISBN: (纸本)9781538638859

With the advancement of web service technologies, more and more spatial data and analysis functions are available on the web. Scientific workflows are widely used to orchestrate services to solve complex geospatial problems. The ontology for processing service orchestration (OPSO) is developed to empower domain experts to explore large datasets and complex processing workflows iteratively and collaboratively. OPSO represents three aspects of workflows: template, instance and provenance. The geoprocessing workflow tool named GeoJModelBuilder is extended to support OPSO, and an example will be used to demonstrate how the proposed ontology works.

关键词： geospatial ontology scientific workflow web processing service

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