Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services

One of the most widely-implemented service standards provided by the Open Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS). WMS is widely employed globally, but there is limited knowledge of the global distribution, adoption status or the service quality of these online WMS resources. To fill this void, we investigated global WMSs resources and performed distributed performance monitoring of these services. This paper explicates a distributed monitoring framework that was used to monitor 46,296 WMSs continuously for over one year and a crawling method to discover these WMSs. We analyzed server locations, provider types, themes, the spatiotemporal coverage of map layers and the service versions for 41,703 valid WMSs. Furthermore, we appraised the stability and performance of basic operations for 1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major reasons for request errors and performance issues, as well as the relationship between service response times and the spatiotemporal distribution of client monitoring sites. This paper will help service providers, end users and developers of standards to grasp the status of global WMS resources, as well as to understand the adoption status of OGC standards. The conclusions drawn in this paper can benefit geospatial resource discovery, service performance evaluation and guide service performance improvements.Comment: 24 pages; 15 figure

Facilitate Visualization and Distribution of NASA\u27s Environmental Science Data through Open Standards and Open Source Software for Geospatial

This paper introduces the utilization of open standards and open source software for visualization and distribution of geospatial environmental science data at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). The ORNL DAAC is one of the NASA Earth Observing System Data and Information System (EOSDIS) data centers. A big challenge for the ORNL DAAC (https://daac.ornl.gov) is to efficiently manage over a thousand heterogeneous environmental data, collected through field campaigns, aircraft/satellite observations, and model simulations. ORNL DAAC also has to provide tools to easily find, visualize, and access the heterogeneous data. To address this challenge, the ORNL DAAC has leveraged Open Geospatial Consortium (OGC) standards and open source software to develop the Spatial Data Access Tool (SDAT, https://webmap.ornl.gov/ogc). SDAT is a suite of open standards-based web mapping, subsetting, and transformation services and applications that allow users to visualize and download geospatial data in customized spatial/temporal extents, formats, and projections. The open source MapServer/Geospatial Data Abstraction Library (GDAL) powers the backend OGC Web services of SDAT. Open source Javascript libraries, including OpenLayers, GeoExt, and proj4js, were used to create the SDAT Web User Interface and MapWidget, a light-weight Javascript library that allows SDAT visualization to be easily embedded on any webpage. SDAT also provides KML files to enable interactive data visualization in the popular Google Earth application or any KML-compatible client. SDAT provides a common framework and standard service interfaces for ORNL DAAC data holdings. SDAT user interface hides their heterogeneity from end users, and promotes their usage. SDAT facilitates integration of ORNL DAAC data resources with other related data systems. In 2016, SDAT served more than 2 million mapping requests and 72 thousand customized data downloads from over 2500 distinct data users

Viability assessment of WPS 2.0 services as communication standard for expensive web-based machine learning analysis. A case of study : Indoor Location

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesCommunication between client and server is a key factor in the modern age. Nowadays, telecommunications are at the base of every system and Software that is available. The way Software communicates can determine the efficacy of it. In the GIS world, a server is often used for offloading expensive tasks such as geospatial operations or statistical analysis. This technique improves the performance of the Software systems and makes them able to scale based on the demand on real time. For making the communication between client and server more efficient, interoperable and standard, the OGC released the standard WPS. WPS defines abstract operations that are able to describe a client server communication for remote process executions. This thesis focuses on the asynchronous execution feature introduced in the version 2.0 of WPS. The main goal is to study how asynchronous process execution can benefit a client both in performance and availability. The result are promising and it is demonstrated that WPS is a solid standard for describing web services operations. Based on the obtained results, future studies can extend the standard in order to make it more general and suitable for more situations

Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains

Evaluation of standards and techniques for retrieval of geospatial raster data : a study for the ICOS Carbon Portal

Evaluation of Standards and Techniques for Retrieval of Geospatial Raster Data - A study for ICOS Carbon Portal Geospatial raster data represent the world as a surface with its geographic information which varies continuously. These data can be grid-based data like Digital Terrain Elevation Data (DTED) and geographic image data like multispectral images. The Integrated Carbon Observation System (ICOS) European project is launched to measure greenhouse gases emission. The outputs of these measurements are the data in both geospatial vector (raw data) and raster formats (elaborated data). By using these measurements, scientists create flux maps over Europe. The flux maps are important for many groups such as researchers, stakeholders and public users. In this regard, ICOS Carbon Portal (ICOS CP) looks for a sufficient way to make the ICOS elaborated data available for all of these groups in an online environment. Among others, ICOS CP desires to design a geoportal to let users download the modelled geospatial raster data in different formats and geographic extents. Open GeoSpatial Consortium (OGC) Web Coverage Service (WCS) defines a geospatial web service to render geospatial raster data such as flux maps in any desired subset in space and time. This study presents two techniques to design a geoportal compatible with WCS. This geoportal should be able to retrieve the ICOS data in both NetCDF and GeoTIFF formats as well as allow retrieval of subsets in time and space. In the first technique, a geospatial raster database (Rasdaman) is used to store the data. Rasdaman OGC component (Petascope) as the server tool connects the database to the client side through WCS protocol. In the Second technique, an advanced file-based system (NetCDF) is applied to maintain the data. THREDDS as the WCS server ships the data to the client side through WCS protocol. These two techniques returned good result to download the data in desired formats and subsets.Evaluation of Standards and Techniques for Retrieval of Geospatial Raster Data Geospatial data refer to an object or phenomena located on the specific scene in space, in relation with the other objects. They are linked to geometry and topology. Geospatial raster data are a subset of geospatial data. Geospatial raster data represent the world as a surface with its geographic information which varies continuously. These data can be grid-based data like Digital Terrain Elevation Data (DTED) and geographic image data like multispectral images. The challenges present in working with geospatial raster data are related to three important components: I) storage and management systems, II) standardized services and III) software interface of geospatial raster data. Each component has its own importance in the aim of improving the interaction with geospatial raster data. A proper geospatial raster data storage and management system makes it easy to classify, search and retrieve the data. A standardized service is needed to unify, download, process and share these data among other users. The last challenge is choosing suitable software interface to support the standardized services on the web. The aim is to provide ability for users to download geospatial raster data in different formats in any desired space and time subsets. In this regard, two different techniques are evaluated to connect the main three components to provide such aim. In the first technique, a geospatial raster database is used to store the data. Then this database is connected to the software interface through standardized service. In the Second technique, an advanced file-based system is applied to maintain the data. The server ships the data to software interface through standardized service. Although these two techniques have their own difficulties, they returned good result. Users can download the data in desired formats on the web. In addition, they can download the data for any specific area and specific time

Proceedings of the 3rd Open Source Geospatial Research & Education Symposium OGRS 2014

The third Open Source Geospatial Research & Education Symposium (OGRS) was held in Helsinki, Finland, on 10 to 13 June 2014. The symposium was hosted and organized by the Department of Civil and Environmental Engineering, Aalto University School of Engineering, in partnership with the OGRS Community, on the Espoo campus of Aalto University. These proceedings contain the 20 papers presented at the symposium. OGRS is a meeting dedicated to exchanging ideas in and results from the development and use of open source geospatial software in both research and education.  The symposium offers several opportunities for discussing, learning, and presenting results, principles, methods and practices while supporting a primary theme: how to carry out research and educate academic students using, contributing to, and launching open source geospatial initiatives. Participating in open source initiatives can potentially boost innovation as a value creating process requiring joint collaborations between academia, foundations, associations, developer communities and industry. Additionally, open source software can improve the efficiency and impact of university education by introducing open and freely usable tools and research results to students, and encouraging them to get involved in projects. This may eventually lead to new community projects and businesses. The symposium contributes to the validation of the open source model in research and education in geoinformatics

A Web Map Service implementation for the visualization of multidimensional gridded environmental data

We describe ncWMS, an implementation of the Open Geospatial Consortium’s Web Map Service (WMS) specification for multidimensional gridded environmental data. ncWMS can read data in a large number of common scientific data formats – notably the NetCDF format with the Climate and Forecast conventions – then efficiently generate map imagery in thousands of different coordinate reference systems. It is designed to require minimal configuration from the system administrator and, when used in conjunction with a suitable client tool, provides end users with an interactive means for visualizing data without the need to download large files or interpret complex metadata. It is also used as a “bridging” tool providing interoperability between the environmental science community and users of geographic information systems. ncWMS implements a number of extensions to the WMS standard in order to fulfil some common scientific requirements, including the ability to generate plots representing timeseries and vertical sections. We discuss these extensions and their impact upon present and future interoperability. We discuss the conceptual mapping between the WMS data model and the data models used by gridded data formats, highlighting areas in which the mapping is incomplete or ambiguous. We discuss the architecture of the system and particular technical innovations of note, including the algorithms used for fast data reading and image generation. ncWMS has been widely adopted within the environmental data community and we discuss some of the ways in which the software is integrated within data infrastructures and portals

Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

A Data-driven, High-performance and Intelligent CyberInfrastructure to Advance Spatial Sciences

abstract: In the field of Geographic Information Science (GIScience), we have witnessed the unprecedented data deluge brought about by the rapid advancement of high-resolution data observing technologies. For example, with the advancement of Earth Observation (EO) technologies, a massive amount of EO data including remote sensing data and other sensor observation data about earthquake, climate, ocean, hydrology, volcano, glacier, etc., are being collected on a daily basis by a wide range of organizations. In addition to the observation data, human-generated data including microblogs, photos, consumption records, evaluations, unstructured webpages and other Volunteered Geographical Information (VGI) are incessantly generated and shared on the Internet. Meanwhile, the emerging cyberinfrastructure rapidly increases our capacity for handling such massive data with regard to data collection and management, data integration and interoperability, data transmission and visualization, high-performance computing, etc. Cyberinfrastructure (CI) consists of computing systems, data storage systems, advanced instruments and data repositories, visualization environments, and people, all linked together by software and high-performance networks to improve research productivity and enable breakthroughs that are not otherwise possible. The Geospatial CI (GCI, or CyberGIS), as the synthesis of CI and GIScience has inherent advantages in enabling computationally intensive spatial analysis and modeling (SAM) and collaborative geospatial problem solving and decision making. This dissertation is dedicated to addressing several critical issues and improving the performance of existing methodologies and systems in the field of CyberGIS. My dissertation will include three parts: The first part is focused on developing methodologies to help public researchers find appropriate open geo-spatial datasets from millions of records provided by thousands of organizations scattered around the world efficiently and effectively. Machine learning and semantic search methods will be utilized in this research. The second part develops an interoperable and replicable geoprocessing service by synthesizing the high-performance computing (HPC) environment, the core spatial statistic/analysis algorithms from the widely adopted open source python package – Python Spatial Analysis Library (PySAL), and rich datasets acquired from the first research. The third part is dedicated to studying optimization strategies for feature data transmission and visualization. This study is intended for solving the performance issue in large feature data transmission through the Internet and visualization on the client (browser) side. Taken together, the three parts constitute an endeavor towards the methodological improvement and implementation practice of the data-driven, high-performance and intelligent CI to advance spatial sciences.Dissertation/ThesisDoctoral Dissertation Geography 201