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Whalen, Kevin ChristopherA map system to disseminate national science on forests for the creation of regional tree planting prioritization plans
MS, Kent State University, 2017, College of Arts and Sciences / Department of Computer Science
In the United States, urban forestry efforts are sustained through efforts from individuals, businesses, philanthropic organizations, and government agencies across local, state, and national levels. The i-Tree Tools suite of software promotes the use of, peer-reviewed science to explain the benefits that trees provide in a method intended for the general public. This thesis shares the computer-specific knowledge collected during the design, implementation, and continued expansion of i-Tree Landscape. The i-Tree Landscape application is a web-browser based, online, geographic information system, referred to as a web-GIS app. The "pages" of the web-app are part of a system of software libraries and services, along with dedicated hardware, which were specifically researched, compared, selected, and optimally configured for their roles in supporting the system as a whole. This work will also briefly touch upon the open source libraries and services running in the Landscape system, as well as, some of the decisions they influenced with acquiring hardware to support its deployment. Delivering the data and formulas associated with the benefits of trees for the entire geographic area of the United States becomes difficult over the internet, especially when it must be achieved via a non-expert interface. To manage this, the flow of the application is separated into five, non-sequential steps, prefixed with a landing page, and postfixed with a publishable report. This partitioning helps with code responsibility separation, as well. In addition to producing a tailorable report for describing the benefits of trees, the primary purpose of the application is to help prioritize tree planting efforts. This is well needed by foresters to help allocate for popular practice of mass tree plantings. The planning is done via a customizable model utilizing nearly all of the possible attributes as weighting options. The regional aggregations for this are available to users through nine boundary layers, most notably including counties, block groups, and watersheds. The research supporting the data on trees is from working directly with the authors of peer-reviewed research from the United States Department of Agriculture Forest Service laboring at the Northern Research Station at the College of Environmental Science and Forestry in Syracuse, New York. i-Tree Landscape has succeeded in becoming a science dissemination facility, by the use of information visualization, with the purpose of making decisions that promote urban forestry stewardship through modern web-GIS, and data processing techniques.

Committee:

Cheng-Chang Lu, PhD (Advisor); Austin Melton, PhD (Committee Member); Gokarna Sharma, PhD (Committee Member)

Subjects:

Computer Science; Ecology; Environmental Science; Geography; Urban Forestry; Urban Planning

Keywords:

budget national map processing; geographic information system; GIS; national land cover; forestry; tree planting prioritization; GDAL; GEOS; GeoServer; PostGIS; JTS; Open Geospatial Consortium; OGC; Open Source Geospatial Foundation; OSGeo;

Rettig, Andrew J.Design and Implementation of Affordable, Self-Documenting, Near-Real-Time Geospatial Sensor Webs for Environmental Monitoring using International Standards
PhD, University of Cincinnati, 2014, Arts and Sciences: Geography
This dissertation documents the design and implementation of a near-real-time geospatial in situ sensor network for monitoring stormwater runoff at the Green Learning Station. The project solves the need by the Environmental Protection Agency and Cincinnati Metropolitan Sewer District for an affordable and standardized network. The project also makes contributions to geospatial standards and sensor web research. This dissertation uses open innovation, including open standards, to help reduce cost and complexities of environmental sensor networking architectures. Article 1 focuses on the technical implementation of the in situ sensor network helping to fill the research gap of applied end-to-end in situ sensing. This gap is further highlighted by the inadequacies within international geospatial standards. Article 2 discusses the greatest hardware challenge within sensor webs, embedded devices. The Green Learning Station project solved this challenge, bridged the gap between sensor protocols and standard communication protocols, with Common-off-the-Shelf (COTS) routers. The modified routers enable the development of the client/server architecture for environmental sensor networking outlined in Article 3. The client software is designed for embedded devices while the web services were designed with the Representational State Transfer (REST) approach. The Green Learning Station design and implementation is unique because of the open innovation approach to geospatial in situ sensor webs by a team of engineers with expertise at every layer of the architecture. This expertise enabled the inclusion of spatial standards and spatial data throughout the architecture. This approach creates a standardized and affordable geospatial sensor network as an example for others to study and expand upon for a variety of monitoring solutions.

Committee:

Richard Beck, Ph.D. (Committee Chair); Dharma Agrawal, D.Sc. (Committee Member); Ishi Buffam, Ph.D. (Committee Member); Hongxing Liu, Ph.D. (Committee Member); Michael Widener, Ph.D. (Committee Member)

Subjects:

Geographic Information Science

Keywords:

Environmental sensor networks;Internet of Things;Open Geospatial Consortium;Open innovation;GIScience;Urban runoff

Rettig, Andrew J.An Open Geospatial Consortium Standards-based Arctic Climatology Sensor Network Prototype
MA, University of Cincinnati, 2010, Arts and Sciences: Geography
We have constructed a prototype Open Geospatial Consortium (OGC) standards-based Arctic Climatology Sensor Network Prototype (ACSNP) in response to recent developments in sensor technology and Internet Protocol Suite (TCP/IP) wireless communications in Barrow, Alaska for the National Science Foundation (NSF). The OGC standards enable increased, interoperability, scalability, and extensibility for geospatial information at a reduced cost. Our approach for the prototype is to integrate established technologies to create near-real-time geographic information networks (GINs). We linked a variety of meteorological and image sensors to wide area wireless networks in Barrow, Alaska. The network is a TCP/IP-based 700 Mhz WipLL network consisting of a 16 kilometer diameter local cloud as well as Iridium Open Port Units, which allow for global connectivity, at other remote research stations and on ice breakers. The Department of Energy (DOE) building in Barrow is the location of two automatically populated mirrored File Transfer Protocol (FTP) servers running Microsoft Server 2003 within a virtualized environment. High availability for the GIN is met through the use of virtualization as well as redundant power supplies and hardware-based security. The data are automatically harvested from the remote site over redundant 2XT-1 satellite links to the central data center in Cincinnati, Ohio where it is formatted to comply with the OGC database initiatives to create an OGC-compliant geodatabase within Microsoft SQL Server 2008. This cyberinfrastructure is remotely monitored 24X7 tracking network components and mission critical applications providing notification of potential capacity, connection and performance problems. The final web publication is the result of a three part system; geodatabases, web services and web applications. A data harvester is used for automating data retrieval and distribution into a geodatabase. The harvester allows for centralized control and monitoring of transfers through a browser interface and provides a comprehensive built-in scheduler and produces complete reports. A function of the database is the conversion of raw noncompliant sensor data into the standardized OGC geodatabase. For web services we use ESRI’s ArcGIS Server technology for retrieval and publication utilizing ESRI’s compliance with OGC web services. These web services may then be embedded within clients, such as ESRI’s ArcGIS Desktop and Google Earth for analysis, and web applications. The Arctic Climatology Sensor Network Prototype is accessible at OpenSensorMap.com.

Committee:

Richard Beck, PhD (Committee Chair); Robert Browning South, PhD (Committee Member); Hongxing Liu, PhD (Committee Member)

Subjects:

Geotechnology

Keywords:

Spatial Data Infrastructure;Geographic Information Network;Sensor Network;Open Geospatial Consortium;Climatology;Arctic

Patni, Harshal KamleshReal Time Semantic Analysis of Streaming Sensor Data
Master of Science (MS), Wright State University, 2011, Computer Science
The emergence of dynamic information sources - like social, mobile and sensors, has led to ginormous streams of real time data on the web also called, the era of Big Data [1]. Research studies suggest, these dynamic networks have created more data in the last three years than in the entire history of civilization, and this trend will only increase in the coming years [1]. Gigaom article on Big data shows, how the total information generated by these dynamic information sources has completely surpassed the total storage capacity. Thus keeping in mind the problem of ever-increasing data, this thesis focuses on semantically integrating and analyzing multiple, multimodal, heterogeneous streams of weather data with the goal of creating meaningful thematic abstractions in real-time. This is accomplished by implementing an infrastructure for creating and mining thematic abstractions over massive amount of real-time sensor streams. Evaluation section shows 69% data reduction with this approach.

Committee:

Amit Sheth, PhD (Advisor); Ramakanth Kavaluru, PhD (Committee Member); Krishnaprasad Thirunarayan, PhD (Committee Member)

Subjects:

Computer Science; Geographic Information Science

Keywords:

Semantic Web;Semantic Sensor Web;Real-Time Sensor Web;RDF;SPARQL;SSN Ontology;Open Geospatial Consortium;Sensor Web Enablement;Observation and Meausrements