Relevant bibliographies by topics / Geospatial APIs

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Geospatial APIs'

Author: Grafiati
Published: 10 March 2023

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Journal articles on the topic "Geospatial APIs"

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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 (January 25, 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 geospatial extensions to existing systems.
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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/Geospatial JSON (GeoJSON) and two popular binary data encodings (Protocol Buffers and Apache Avro) for storing and sharing geospatial data. Using a number of experiments, we illustrate the advantages and disadvantages of both approaches for common workflows that make use of geospatial data encodings such as GeoPackage and GeoJSON. The paper contributes a number of practical recommendations around the potential for binary data serialization for interoperable (geospatial) data storage and sharing in the future.
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Tischler, Michael A. "Accelerating Geospatial Modeling in ArcGIS with Graphical Processor Units." International Journal of Applied Geospatial Research 7, no. 4 (October 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 can be linked with GPU application programming interfaces (APIs). This research extends a custom desktop geospatial model of spatial similarity for remote soil classification which takes advantage of both standard ArcPy/ArcGIS geoprocessing functions and custom GPU kernels, operating on an NVIDIA Tesla S2050 equipped with potential access to 1792 cores. The author will present their results which describe hardware and software configurations, processing efficiency gains, and lessons learned.
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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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<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 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.</p>
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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 tools for 3D city model application development
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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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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 consortium, but also to allow cross-fertilisation with other ongoing projects and later on, to reach a wider public audience. For more than twenty years SDIs have adopted the OGC W*s service interfaces, which are based on SOAP, the Simple Object Access Protocol. In recent years a new “family” of APIs has emerged within OGC, which is more aligned with modern web practices. In this project, we set out to leverage the advantages of this new approach, and compiled a stack to implement an SDI based on OGC APIs. However, we realised that we still need to support the legacy standards, either because an OGC API replacement is not mature enough, or there are no implementations available. This has led us to compile another stack based on the legacy standards. In this paper we describe our architecture, along with the challenges that we had to address. Both stacks are based on OSGeo Software, and they are available on GitHub.
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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 and functions between Sensor Web and SDI, and Case studies like hazard applications, urban applications etc. We take up co-operative development of SDI best practices to enable a new realm of a location enabled and semantically enriched World Wide Web - the "Geospatial Web" or "Geosemantic Web" by setting up one to one correspondence between WMS, WFS, WCS, Metadata and 'Sensor Observation Service' (SOS); 'Sensor Planning Service' (SPS); 'Sensor Alert Service' (SAS); a service that facilitates asynchronous message interchange between users and services, and between two OGC-SWE services, called the 'Web Notification Service' (WNS). Hence in conclusion, it is of importance to geospatial studies to integrate SDI with Sensor Web. The integration can be done through merging the common OGC interfaces of SDI and Sensor Web. Multi-usability studies to validate integration has to be undertaken as future research.
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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 and functions between Sensor Web and SDI, and Case studies like hazard applications, urban applications etc. We take up co-operative development of SDI best practices to enable a new realm of a location enabled and semantically enriched World Wide Web - the "Geospatial Web" or "Geosemantic Web" by setting up one to one correspondence between WMS, WFS, WCS, Metadata and 'Sensor Observation Service' (SOS); 'Sensor Planning Service' (SPS); 'Sensor Alert Service' (SAS); a service that facilitates asynchronous message interchange between users and services, and between two OGC-SWE services, called the 'Web Notification Service' (WNS). Hence in conclusion, it is of importance to geospatial studies to integrate SDI with Sensor Web. The integration can be done through merging the common OGC interfaces of SDI and Sensor Web. Multi-usability studies to validate integration has to be undertaken as future research.
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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 (December 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 that are used by application of specific agents. We discuss several concepts in this approach: agent lookup and discovery through traditional information retrieval techniques, the ability to rapidly prototype agents based on commercial software products, and a knowledge management approach that reuses prior processing approaches and results. We present results demonstrating the scalability of our agent discovery and composition mechanism to compare them with other traditional discovery mechanisms, and demonstrate how the discovery mechanism scales to support thousands of agents.
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Dissertations / Theses on the topic "Geospatial APIs"

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Francis, Alexandra Michelle. "REST API to Access and Manage Geospatial Pipeline Integrity Data." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1496.

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Today’s economy and infrastructure is dependent on raw natural resources, like crude oil and natural gases, that are optimally transported through a net- work of hundreds of thousands of miles of pipelines throughout America[28]. A damaged pipe can negatively a↵ect thousands of homes and businesses so it is vital that they are monitored and quickly repaired[1]. Ideally, pipeline operators are able to detect damages before they occur, but ensuring the in- tegrity of the vast amount of pipes is unrealistic and would take an impractical amount of time and manpower[1]. Natural disasters, like earthquakes, as well as construction are just two of the events that could potentially threaten the integrity of pipelines. Due to the diverse collection of data sources, the necessary geospatial data is scat- tered across di↵erent physical locations, stored in di↵erent formats, and owned by di↵erent organizations. Pipeline companies do not have the resources to manually gather all input factors to make a meaningful analysis of the land surrounding a pipe. Our solution to this problem involves creating a single, centralized system that can be queried to get all necessary geospatial data and related informa- tion in a standardized and desirable format. The service simplifies client-side computation time by allowing our system to find, ingest, parse, and store the data from potentially hundreds of repositories in varying formats. An online web service fulfills all of the requirements and allows for easy remote access to do critical analysis of the data through computer based decision support systems (DSS). Our system, REST API for Pipeline Integrity Data (RAPID), is a multi- tenant REST API that utilizes HTTP protocol to provide a online and intuitive set of functions for DSS. RAPID’s API allows DSS to access and manage data stored in a geospatial database with a supported Django web framework. Full documentation of the design and implementation of RAPID’s API are detailed in this thesis document, supplemented with some background and validation of the completed system.
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Ogden, Mitchell. "Communications and Methodologies in Crime Geography: Contemporary Approaches to Disseminating Criminal Incidence and Research." Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/etd/3652.

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Many tools exist to assist law enforcement agencies in mitigating criminal activity. For centuries, academics used statistics in the study of crime and criminals, and more recently, police departments make use of spatial statistics and geographic information systems in that pursuit. Clustering and hot spot methods of analysis are popular in this application for their relative simplicity of interpretation and ease of process. With recent advancements in geospatial technology, it is easier than ever to publicly share data through visual communication tools like web applications and dashboards. Sharing data and results of analyses boosts transparency and the public image of police agencies, an image important to maintaining public trust in law enforcement and active participation in community safety.
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Soderi, Mirco. "Semantic models for the modeling and management of big data in a smart city environment." Doctoral thesis, 2021. http://hdl.handle.net/2158/1232245.

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The overall purpose of this research has been the building or the improve- ment of semantic models for the representation of data related to smart cities and smart industries, in such a way that it could also be possible to build context-rich, user-oriented, ecient and eective applications based on such data. In some more detail, one of the key purposes has been the modelling of structural and the functioning aspects of the urban mobility and the produc- tion of instances exploiting the Open Street Map, that once integrated with trac sensors data, it has lead to the building and displaying of real-time trac reconstructions at a city level. One second key purpose has been the modelling of the Internet of Things, that allows today to seamlessy and e- ciently identify sensing devices that are deployed in a given area or along a given path and that are of a given type, and also inspect real-time data that they produce, through a user-oriented Web application, namely the Service Map. A pragmatic approach to the modelling has been followed, always tak- ing into consideration the best practices of semantic modelling on one side for that a clean, comprehensive and understandable model could result, and the reality of the data at our hands and of the applicative requirements on the other side. As said, the identication of architectures and methods that could grant eciency and scalability in data access has also been a primary purpose of this research that has led to the denition and implementation of a federation of Service Maps, namely the Super Service Map. The archi- tecture is fully distributed: each Super Service Map has a local list of the actual Service Maps with relevant metadata, it exposes the same interface as actual Service Maps, it forwards requests and builds merged responses, also implementing security and caching mechanisms. As said, the identica- tion of technologies, tools, methods, for presenting the data in a user-friendly manner is also has been a relevant part of this research, and it has led among the other to the denition and implementation of a client-server architecture and a Web interface in the Snap4City platform for the building, manage- ment, and displaying of synoptic templates and instances thanks to which users can securely display and iteract with dierent types of data. In end, some eort has been made for the automatic classication of RDF datasets as for their structures and purposes, based on the computation of metrics through SPARQL queries and on the application of dimensionality reduc- tion and clustering techniques. A Web portal is available where directories, datasets, metrics, and computations can be inspected even at real-time.
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Book chapters on the topic "Geospatial APIs"

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Charvát, Karel, and Michal Kepka. "Crowdsourced Data." In Big Data in Bioeconomy, 63–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_5.

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AbstractCrowdsourcing together with Volunteered Geographic Information (VGI) are currently part of a broader concept – Citizens Science. The methods provide information on existing geospatial data or is a part of data collection from geolocated devices. They enable opening parts of scientific work to the general public. DataBio Crowdsourcing Solution is a combination of the SensLog server platform and HSLayers web and mobile applications. SensLog is a server system for managing sensor data, volunteered geographic information and other geospatial data. Web and mobile applications are used to collect and visualize SensLog data. SensLog data model builds on the Observations & Measurements conceptual model from ISO 19156 and includes additional sections, e.g., for user authentication or volunteered geographic information (VGI) collection. It uses PostgreSQL database with PostGIS for data storage and several API endpoints.
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Ju, Bola Michelle, Lesley Arnold, and Kathrine Kelm. "Rapid Development of Location-based Apps: Saving Lives during a Pandemic – the South Korean Experience." In COVID-19 Pandemic, Geospatial Information, and Community Resilience, 305–20. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003181590-27.

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Tischler, Michael A. "Accelerating Geospatial Modeling in ArcGIS With Graphical Processor Units." In Geospatial Intelligence, 411–22. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8054-6.ch019.

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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 can be linked with GPU application programming interfaces (APIs). This research extends a custom desktop geospatial model of spatial similarity for remote soil classification which takes advantage of both standard ArcPy/ArcGIS geoprocessing functions and custom GPU kernels, operating on an NVIDIA Tesla S2050 equipped with potential access to 1792 cores. The author will present their results which describe hardware and software configurations, processing efficiency gains, and lessons learned.
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Furner, Christopher P., Pradeep Racherla, and Jeffrey S. Babb. "What We Know and Do Not Know About Mobile App Usage and Stickiness." In Geospatial Research, 117–41. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9845-1.ch005.

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Mobile applications (apps) have transformed the way firms and consumers communicate with each other, and have now become integral to firms' marketing strategies. However, in a marketplace characterized by myriad choices, one of the biggest challenges that Marketers face is to foster continued and frequent use, or stickiness. This brings forth two important questions: what factors affect consumers' decision to use and “stick” to apps? What are the key outcomes of stickiness for both consumers and firms? This study maps the conceptual and research issues underlying consumers' decision journey and outcomes with respect to mobile app use. We build a framework based on the central tenets of interactivity combined with the insights gleaned from a survey of interdisciplinary literature. We discuss the implications for research and practice in this emerging area of interest.
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Singh, Harpinder, Dheeraj Gambhir, Sagar Taneja, and Amardeep Singh. "Use of Cloud, Multimedia, and QR Codes to Enhance Print Maps." In Geospatial Intelligence, 1094–99. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8054-6.ch046.

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Quick response (QR) codes are two-dimensional codes. They are machine-readable optical labels which contain information of the object on which they are attached. Due to their large storage capacity and faster readability, they are becoming more popular than one-dimensional bar codes. They are widely used in creation of inventories, product tracking, document management, etc. With the widespread use of smart phones, QR codes are becoming more popular. QR code interpreting apps are freely available and all modern smartphones are equipped with a camera and internet to process and interpret these codes. The value of printed maps can also be enhanced by using QR codes. This chapter reviews how the value of printed or hard copy maps can be enhanced by adding QR codes that have multimedia content placed on the Cloud.
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Osello, Anna, Andrea Acquaviva, Daniele Dalmasso, David Erba, Matteo Del Giudice, Enrico Macii, and Edoardo Patti. "BIM and Interoperability for Cultural Heritage through ICT." In Advances in Geospatial Technologies, 274–91. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8379-2.ch008.

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This chapter presents a methodology based on Building Information Modelling (BIM) and interoperability to convert existing buildings, even historical, into smart buildings. The chapter starts describing the main concepts of BIM and interoperability in the Architecture, Engineer and Construction (AEC) industry with special attention on integrating information from heterogeneous devices deployed in the building. Then, it details the SEEMPubS (Smart Energy Efficient Middleware for Public Buildings) middleware, which consists on three layers: (i) Integration Layer, (ii) Middleware Layer, and (iii) Application Layer. The validation of the most significant results is presented using both gamification and technical approaches involving different end-users. Finally, Apps for data management are introduced with a Community Portal and an Android Application for real-time data visualization. Future works introduce the integration of smart building into smart district context.
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Singh, Harpinder, Dheeraj Gambhir, Sagar Taneja, and Amardeep Singh. "Use of Cloud, Multimedia, and QR Codes to Enhance Print Maps." In Advances in Geospatial Technologies, 218–23. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5039-6.ch009.

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Quick response (QR) codes are two-dimensional codes. They are machine-readable optical labels which contain information of the object on which they are attached. Due to their large storage capacity and faster readability, they are becoming more popular than one-dimensional bar codes. They are widely used in creation of inventories, product tracking, document management, etc. With the widespread use of smart phones, QR codes are becoming more popular. QR code interpreting apps are freely available and all modern smartphones are equipped with a camera and internet to process and interpret these codes. The value of printed maps can also be enhanced by using QR codes. This chapter reviews how the value of printed or hard copy maps can be enhanced by adding QR codes that have multimedia content placed on the Cloud.
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Conference papers on the topic "Geospatial APIs"

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Gerontini, Maria, and Simon Moritz. "Large Scale Geospatial Analysis on Mobile Application Usage." In 2014 Eighth International Conference on Next Generation Mobile Apps, Services and Technologies (NGMAST). IEEE, 2014. http://dx.doi.org/10.1109/ngmast.2014.38.

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Staso, Umberto Di, Marco Soave, and Raffaele De Amicis. "Engaging Outdoor User Experience Based on High Fidelity 3D Terrain Representation on Mobile Apps." In 2013 4th International Conference on Computing for Geospatial Research & Application (COM.Geo). IEEE, 2013. http://dx.doi.org/10.1109/comgeo.2013.9.

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Johnson, Clayton, Stephen Schmidt, Justin Taylor, and John deLaChapelle. "Geospatial Database Development: Supporting Geohazard Risk Assessments Through Real-Time Data and Geospatial Analytics." In 2022 14th International Pipeline Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/ipc2022-87139.

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Abstract TC Energy owns and operates over 32,000 miles of natural gas pipelines within 38 states in the United States, a sizable portion of which crosses through terrain highly susceptible to geologic hazards. To better support geohazard risk management, TC Energy has implemented a customized web-based geohazard platform (GeoForce) to identify, inventory, and track geohazards across their U.S. pipeline system. The platform was built within the Environmental Systems Research Institute (ESRI) ArcGIS Enterprise environment and leverages a diverse amount of ESRI product offerings. The platform is hosted on ArcGIS Portal and includes multiple custom apps and dashboards which allow users to efficiently view, summarize, add, and update geohazard data. Another key component of the system is a connection to ArcGIS GeoEvent Server. GeoEvent Server allows for the delivery of near real-time geohazard threat notifications through emails and dashboards (i.e., seismic events, flooding, precipitation). The notifications also provide detailed information for the sections of the system affected by the event, and in the case of a seismic event, a suggested course of action in alignment with TC Energy procedures. ArcGIS Image Server was leveraged to host over 4 terabytes of LiDAR imagery which can be used in concert with the other geohazard datasets present in the database. Custom geospatial scripts were also developed to create a near real-time link between the GeoForce master database and TC Energy’s master data mart, asset information, regulatory, and other organizational data. These scripts flag and report where spatial and/or attribute data have changed or may no longer be valid and therefore require follow-up action to support risk management (e.g., when pipelines are abandoned, HCAs are updated, or pipe properties are updated). The scripts also store the centerline attribute changes in a table for further review to identify potential trends. The GeoForce database is also built as a launching platform for proactive analytics, and eventually predictive analytics for critical precipitation thresholds for landslide risk management, landslide susceptibility mapping, system-wide risk scoring, seismic events and ILI bending strain coincident with geohazards. Details related to the threat alerts that are issued by the geospatial system are stored and visualized in a PowerBI integration. With the incorporation of ArcGIS Notebook Server, algorithms will be developed that will review the historical threat repository that is being generated and issue threat alerts based on probability of a hazardous event occurring in proximity of the pipeline system.
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Zhengqing Yun, Soo Yong Lim, and M. F. Iskander. "Propagation prediction in urban areas using geospatial data available on the Internet." In 2008 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting. IEEE, 2008. http://dx.doi.org/10.1109/aps.2008.4619035.

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Zhengqing Yun, Soo Yong Lim, and M. F. Iskander. "Modeling three-dimensional terrain in urban propagation environment using geospatial data in cyberspace." In 2010 IEEE International Symposium Antennas and Propagation and CNC-USNC/URSI Radio Science Meeting. IEEE, 2010. http://dx.doi.org/10.1109/aps.2010.5561712.

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Yun, Z., M. F. Iskander, and S. Y. Lim. "The effect of 3D building reconstruction errors on propagation prediction using geospatial data in cyberspace." In 2009 IEEE Antennas and Propagation Society International Symposium (APSURSI). IEEE, 2009. http://dx.doi.org/10.1109/aps.2009.5171829.

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Jesus, Lara Fabian Rodrigues de, Daniel Oliveira Reis, and Juliano Ricardo Fabricante. "ATUALIZAÇÃO DA CATEGORIZAÇÃO DO RISCO DE EXTINÇÃO DA ESPÉCIE ANEMIA GARDNERI HOOK." In I Congresso Brasileiro On-line de Estudos Ecológicos. Revista Multidisciplinar de Educação e Meio Ambiente, 2021. http://dx.doi.org/10.51189/rema/2689.

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Introdução: Endêmica da Mata Atlântica dos Estados do Espírito Santo, Minas Gerais e Rio de Janeiro, a espécie Anemia gardneri Hook. é uma erva rupícola ou terrícola da família Anemiaceae que está categorizada atualmente como “Vulnerável” pelo CNCflora. Devido à pressão antrópica que sofrem as suas localidades de ocorrência, torna-se necessário a revisão periódica do seu status de conservação. Objetivo: Assim, o objetivo do presente estudo foi realizar a atualização da categorização do risco de extinção de A. gardneri para o Brasil. Material e Métodos: Para isso, foram coletados pontos de ocorrência georreferenciados da espécie nas bases de dados online GBIF e Specieslink. Após limpos e organizados, esses pontos foram exportados para o software Geospatial Cooonservation Assessment Tool (GeoCAT) e, seguindo o critério de Área de Ocupação (AOO) estabelecido pela IUCN, foi traçado um polígono, respeitando o princípio do mínimo polígono convexo. Este polígono ainda foi gradeado com células de 4 Km². Posteriormente cada célula com a presença da espécie foi contabilizada para obtenção de sua AOO. Resultados: Com uma AOO de 44 Km² e devido as condições de conservação das suas localidades de ocorrência (incêndios recorrentes, extração irregular de solo, supressão ilegal da vegetação e presença de espécies exóticas invasoras), a espécie Anemia gardneri teve sua categorização atualizada de “Vulnerável” para “Em Perigo” pelos critérios B2biiicii. Conclusão: Diante dos resultados obtidos, é possível concluir que Anemia gardneri apresenta risco acentuado de extinção caso as condições de conservação das suas localidades de ocorrência não sofram profundas mudanças. Adicionalmente, sugere-se a criação de projetos de conservação ex situ para a espécie.
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Lim, Nigel, Lucas Lim, and Haribabu Komatineni. "Pseudocode and Demonstration of a Multi-Use Artificial Intelligence Algorithm to Perform Challenging and Highly Optimised Pipeline/Cable Routing Cases." In Offshore Technology Conference Asia. OTC, 2022. http://dx.doi.org/10.4043/31360-ms.

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Abstract The process of routing energy conduits (pipelines, cables and umbilicals) in offshore locations represents a critical phase in the concept planning, engineering and construction of these assets. The downstream impact of poorly designed routes is epitomized by a) increased offshore construction durations b) requirements for additional engineered mitigations from geophysical / geotechnical constraints and c) unforeseen requirements for intervention during operations. The cause of these unoptimized routes can be due to low-level engineering tasks which confines to repetitive, inefficient, and unnecessarily iterative processes between draughters, engineers and asset owners. The increasing accessibility and advancement of digital technologies enables highly optimised solutions even through difficult offshore regions. To address the above, this paper presents the scoping, development and application of a multi-functional algorithm created using modern software code frameworks. The algorithm serves as building blocks into an artificial intelligence platform. This routing algorithm simulates, expands and adapts to engineering and consulting expertise from a worldwide network of energy experts. This recreation of expertise firstly identifies commonly encountered routing constraints such as geophysical features, seabed gradients, existing offshore facilities etc. Ideal geometric parameters are then determined to minimise route costs. These processes are then increased, thus enhancing expertise through scale. The algorithm structure will be presented in summarised minimal pseudocode. The pseudocode will present the application programming interface (API) between the constraints based and end parameter calculation approach. The API includes digital innovations such as a) processing of offshore geotechnical survey data, b) recreating offshore locales and routes in a data environment, c) implementation of geospatial intersection detection, d) 3-dimensional route length optimisation and e) automated route selection criteria. This will demonstrate the order of magnitude replication of subject matter expertise into a digital realm, thus eliminating time-consuming, repetition and human error. Finally, the application of the algorithm will be demonstrated by various case studies of offshore locales with challenging conditions such as highly disturbed seabeds and large quantities of existing man-made assets. The front-end cloud platform of the algorithm will be exhibited, showing a streamlined approach and improved routing engineering. Through this, engineers in the future offshore energy developments can answer the question "What is the best route?".
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