Environmental Information Systems: Projects
- Defense Coastal/Estuarine Research Program Data and Information Management Systems
- Web-Based Reach Indexing Tool
- Data for Environmental Models
- Development of Air Quality Management Decision Support System for Beijing, China
- Quantitative Predictive Risk Assessment Model
Defense Coastal/Estuarine Research Program Data and Information Management Systems
Client
U.S. Department of Defense, Strategic Environmental Research and Development Program
Description
RTI has assembled a diverse team of academic experts (the RTI DCERP Team) in coastal/estuarine ecosystem issues to conduct the Defense Coastal/Estuarine Research Program (DCERP) research and monitoring effort. The Strategic Environmental Research and Development Program supports the sustainability of military training and testing in the ecologically and economically important ecosystems in and surrounding North Carolina's Marine Corps Base at Camp Lejeune (MCBCL).
To facilitate the collection and storage of environmental data and to create a permanent repository for this data collected during the project's implementation, RTI is designing and developing information management systems to support geospatial data management, statistical analysis, model integration, document sharing, and collaboration. We evaluated and selected the hardware and software environment for the system based on the needs of the project and MCBCL.
RTI developed the requirements and design for the information systems, which include the following:
- The Monitoring and Research Data Information System (MARDIS) to archive and access data. MARDIS uses MS SQL Server and ASP.NET for securely entering, analyzing, integrating, displaying, exporting, and sharing data. It contains a web-mapping application that allows researchers to visualize the spatial data.
- A Document Database to store unstructured files, such as maps and reports. Built on MS SQL Server and ASP.NET, the database contains spreadsheets, SAS files, word-processing documents, such as reports and publications, Web sites, and maps that are not in a structured format. It enables users to search these documents via explicit metadata that describe the content of each file.
- A collaborative Web site that enable the RTI DCERP Team to communicate and manage and share administrative planning documents, reports of activities, and other information. The site includes a calendar for scheduling field monitoring and research activities. This secure site was developed in Plone, an open-source content management system built on an open-source application server, Python, which is an open-source, object-oriented programming language. It uses cascading style sheets for standardized styling of web pages.
Web-Based Reach Indexing Tool
Client
US EPA
Description
The Web-based Reach Indexing Tool (WebRIT) is an interactive mapping tool that allows users to view surface waters and related water quality information in the National Hydrography Dataset (NHD) and to georeference, submit, review, verify, update, and correct data in program-specific databases. It is particularly useful for users who need to store locational data for their water quality programs because WebRIT allows them to select surface water areas of interest and to assign a unique identifier to link those areas to attribute information in an associated program database. The locational data for water quality information is stored through the use of reach addresses from the NHD. A reach address identifies a specific location on a particular stream or lake the same way a residence address identifies a specific location on a particular street.
The WebRIT includes a user management component, a Web-based mapping application, a back-end relational and spatial databases, and with the move towards service-oriented architecture (SOA), we have integrated several new Web services. It employs a variety of spatial analysis techniques, including polygon overlay and proximity analysis. WebRIT integrates .NET, JSP, ASP, XML, stored PL/SQL procedures, ArcIMS, ArcSDE, Oracle, Oracle spatial, and Web services into a powerful, yet easy to use, Web-based locational data tool. RTI has developed and upgraded this application over several years by working extensively with the client to define user requirements, writing detailed physical and logical design documents, developing and testing new versions of the application in the RTI development environment, and deploying the application at the client site.
Data for Environmental Models
Client
US EPA Office of Research and Development
Description
To support EPA's efforts to develop a flexible system for multimedia environmental modeling, RTI conducted a multiphase effort to design and develop a client application for generating and storing datasets needed to run comprehensive multimedia environmental models. The software is designed to be flexible, easily updated, take advantage of open-source technologies to make the system nonproprietary, and use data that is freely available on the Internet. RTI documented 32 use cases to be used initially with the Data for Environmental Models (D4EM) system, each designed to produce a portion of a complete environmental dataset. These environmental datasets include a wide range of relational and spatial data.
During this work RTI developed extensive design documentation, created a sophisticated and highly flexible database schema for storing the environmental data, developed tools to integrate downloaded data into modeling systems, developed a control strategy to maintain consistency of data, and documented each step taken while collecting data. The system integrates tools such as Java, XML, C#, FRAMES Modeling Environment, MapWindow GIS software, and SQLite relational database software. During the development effort, RTI coordinated with a broader development team of researchers using a collaborative development environment hosted by the U.S. Department of Agriculture's Co-Lab site.
Development of Air Quality Management Decision Support System for Beijing, China
Client
World Bank, Beijing Municipal Government, PA Consulting Group
Description
To assist the Beijing Municipal Government in its efforts to meet international standards in time for the 2008 Summer Olympic Games, RTI developed a GIS-based decision support system for managing urban air quality for use in Beijing. We designed the databases, compiled an emissions inventory, and established a state-of-the-art Air Quality Management Decision Support System (AQMDSS), which will improve Beijing's ability to make decisions about air quality management. The system will enable Beijing officials to model and forecast air quality, assess the environmental effects of pollution-control measures, and analyze cost benefit, as well as other information.
RTI used open-source development tools to produce a first-of-its-kind, comprehensive tool that integrates several widely accepted, public domain models into one system. The system was built for the Linux operating system using Java programming, and PostgreSQL database software.
RTI designed the system based on interviews with the client to determine its requirements. The overall system provides easy and interactive data input and output for all component modules, fast and efficient data processing, and generation of results in text, graphic, GIS-based visual, and other formats.
Quantitative Predictive Risk Assessment Model (QPRAM)
Client
The U.S. Food and Drug Administration (FDA)
Description
The FDA is responsible for ensuring the safety of all domestic and imported fresh produce consumed in the United States. In response to this need, RTI developed a quantitative predictive risk assessment model (QPRAM) to characterize the risk of foodborne disease associated with a pathogen-commodity pair identified by the risk ranking tool (E. coli O157:H7 and romaine lettuce) that will serve as a "virtual laboratory" for FDA to investigate alternative contamination scenarios using available data. The model includes five stages—production, harvest, processing, distribution, and consumption—and specifies risk factors associated with each stage.
RTI's model simulates the spatial and/or temporal distributions of contamination in each stage to capture the heterogeneity of contamination in time and space. RTI's model is the first to adopt an agent-based modeling approach in the food safety arena to represent potential interactions among the modeled agents as a function of stage-specific risk factors influencing the spread/magnitude of contamination. The model is supported by a comprehensive relational database which provides scientifically based information on the specific pathogens and produce items. Its flexible design allows for an unlimited number of refinements by incorporating subroutines and/or additional data.
RTI's assessment characterized fresh produce production and handling practices; estimation of contamination prevalence and level considering key contributing factors such as growth, natural die-off, and spread of pathogens; multipathway modeling of food chain contamination transmission; Monte Carlo modeling of source and exposure variability; and risk characterization. RTI's model will be instrumental in evaluating the efficacy of food safety policies and quantifying the relative reductions in risk associated with proposed interventions. The agent-based approach will serve as the basis for next generation site-specific analyses.
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