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GIS TECHNICIAN POSITION
The Fairfax County Park Authority seeks an individual to fill the role of GIS Technician to assist with GIS dataset creation, verification, documentation and management. The Fairfax County Park Authority is the primary parks and recreation provider in Fairfax County, VA which is located just outside of Washington, DC. The Park Authority is the county’s largest landowner and owns over 23,000 acres of property and manages over 420 parks. The GIS Technician will join the Planning & Development Division of the Park Authority and will report to the agency’s Senior GIS Analyst. This is a limited-term exempt position that will be scheduled to work 900 hours per calendar year. Compensation will be $22 to $23 per hour depending on qualifications.
The Fairfax County Park Authority is currently undertaking a comprehensive update of its existing geospatial data for the agency as well as its data for other local parks and recreation providers. This includes the need to create, update and document detailed geospatial data on physical assets (e.g. ballfields, playgrounds, trails), cultural and natural resources (e.g. wildlife, vegetation, archaeology), land records (e.g. easements, agreements) and programming (e.g. classes, marketing). Applicants should be mature, self-motivated, highly organized, and comfortable working under limited supervision.
Responsibilities of the GIS Technician include:
Creation of new GIS database layers and data;
Verification of and updates to existing GIS database layers and data;
Development and design of datasets including database schema;
Quality control checks on GIS data layers to ensure they meet specifications;
Creation of metadata and data dictionary entries for new and existing datasets;
Communication with internal & external staff to verify completeness and accuracy of GIS data;
Collection of GIS data in the field using tablets and GNSS devices;
Creation of simple web mapping applications to aid in dataset verification and quality control; Other tasks as assigned
This is an exempt part-time position and does not offer health benefits or paid leave. Schedule is flexible during typical business hours Monday through Friday. Work will occur in an office setting but periodic visits to parks in the area to collect data in the field are anticipated.
Any combination of education, experience, and training equivalent to the following: Graduation from an accredited college or university with a Bachelor’s degree in geography, GIS, geospatial science or a related field
Knowledge and experience with Desktop GIS (ArcGIS Pro, ArcMap, ArcCatalog)
Knowledge and experience with Web GIS (ArcGIS Online)
Experience creating, editing and managing GIS data
Experience creating metadata and data dictionaries
Knowledge and experience with the Microsoft Office suite of programs
Ability to work well independently and with little supervision
Able to handle multiple tasks concurrently
Excellent verbal and written communication skills
Experience using hand-held GPS units Ability to lift at least 25 lbs.
Ability to walk or hike up to one mile to verify park features using GPS device Valid US driver’s license
Knowledge and experience with designing, creating and managing geodatabase schema including designing geodatabase fields, domains and subtypes
Knowledge and experience with designing, creating and managing geodatabase items including feature classes, tables, feature datasets, relationship
classes and topologies
Experience with advanced GIS editing tools (such as vertex modification, feature construction and attribute assistant)
Experience using topology rules to verify dataset integrity and quality
Experience creating web mapping applications in ArcGIS Online through tools such as Web App
Experience collecting GIS data using Collector for ArcGIS
Experience working with high accuracy GNSS receivers
Applicants should email their resume and a cover letter to Justin.Roberson@fairfaxcounty.gov
Please email your application no later than August 31st, 2017. Applications after this date will not be accepted.
Fairfax County is an EOE/AA employer
The U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T) announced today the selection of George Mason University in Fairfax, Va. to lead a consortium of U.S. academic institutions and other partners for a new Center of Excellence (COE) in Criminal Investigations and Network Analysis (CINA). S&T will provide CINA with a $3.85 million grant for its first operating year in a 10-year grant period.
The leadership team will consist of GGS professor Anthony Stefanidis, who serves as director of the new Center of Excellence; University Professor Louise Shelley, director of Mason’s Terrorism, Transnational Crime and Corruption Center; Paulo Costa, associate professor of systems engineering and operations research; professor David Weisburd, executive director of Mason’s Center for Evidence-Based Crime Policy; Allison Redlich, professor in the Department of Criminology, Law and Society; Jim Jones, associate professor of electrical and computer engineering; and professor Mary Ellen O’Toole, director of Mason’s Forensic Science Program.
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Below you will find the details for the position including any supplementary documentation and questions you should review before applying for the opening. To apply for the position, please click the Apply for this Job link/button.
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For full consideration, applicants must apply for position number F9812z at http://jobs.gmu.edu/; complete and submit the online application; and upload (1) a cover letter (detailing teaching specialization and interests), (2) an up-to-date curriculum vitae, (3) teaching portfolio (to be uploaded in field labeled ‘other doc’), and (4) the names of three to five professional references with their contact information, including e-mail addresses.
For more information about GGS, visit us on the web at http://ggs.gmu.edu/.
US Army Geospatial Center, Program Manager – Modeling & Simulation lead for terrain/geospatial database design
In this position you will be responsible for the following duties:
- Directing and overseeing M&S terrain/geospatial database design.
- Establishing requirements to collect and maintain core M&S information.
- Directing the formulation of a M&S program and annual program budget.
- Evaluating and interpreting directives and policy instructions regarding M&S terrain.
- Overseeing the alignment of M&S data with geospatial/GIS data types, structures, formats and services leading to a convergence of M&S terrain/geospatial.
- Developing requirements for standard capabilities to utilize and standardize M&S terrain/geospatial data.
- Occasional Travel
- 20% for technical meetings, site visits and conferences.
About the Organization: Now is a great time to join Redhorse Corporation. Redhorse specializes in developing and implementing creative strategies and solutions with private, state, and federal customers in the areas of cultural and environmental resources services, climate and energy change, information technology, and intelligence services. We are hiring creative, motivated, and talented people with a passion for doing what’s right, what’s smart, and what works. Please see the available positions below and follow the provided links to view the position descriptions and apply on the company website (https://www.redhorsecorp.com/). We are looking for two candidates to fill each described role below which will be onsite in the Northern Virginia / DC Metro area.
Candidate: Scott Heneghan
Master of Science in Geoinformatics and Geospatial Intelligence
Department of Geography and Geoinformation Science
Date: Tuesday, January 17, 2017
Time: 10:00 AM
Place: Exploratory Hall 2304
GRASSROOTS TO VOTING BOOTHS: A STUDY OF THE SPATIOTEMPORAL DYNAMICS OF TRADITIONAL MEDIA COVERAGE AND SOCIAL MEDIA IMPACT IN 2016 UNITED STATES PRESIDENTIAL CANDIDATES
Director: Dr. Anthony Stefanidis
Committee Members: Dr. Arie Croitoru, Dr. Andrew Crooks
The subject of social media effect on elections has been studied by multiple peer reviewed journals, however none take a space time statistical approach to social media’s effect on traditional media in the context of a presidential election. This article attempts to review the space time patterns of social media and how they can potentially drive news coverage from local papers across different parts of the United States. Specifically, the number of tweets around the newspaper locations as compared against the number of news reports about either Bernie Sanders or Donald Trump were reviewed in order to determine if social media is in fact a driver of change. The trends of the results over time were analyzed using the Pearson product moment correlation.
Candidate: Jason Shapiro
Doctor of Philosophy in Earth Systems and Geoinformation Sciences
Department of Geography and Geoinformation Science
Date: Friday, December 2, 2016
Time: 1:00 PM
Place: Exploratory Hall 2304
MODELING THE IMPACTS OF AIRPORTS ON URBAN DENSITY: CASE STUDY OF WASHINGTON DULLES INTERNATIONAL AIRPORT
Director: Dr. Donglian Sun
Committee Members: Dr. Matthew Rice, Dr. Terry Slonecker, Dr. Stephen Fuller
Airports are often seen as powerful anchors for urban development causing domino effects of induced impacts. Business activity caused by airports creates employment and population growth, resulting in increased urban development.
A case study of Washington Dulles International Airport is investigated to better understand the relationship between airports and urban development. The research is divided into four parts:
1. Models of urban development clustering;
2. Analysis of variables influencing urban density;
3. Temporal analysis of airport urban development dynamics; and
4. Tests of the causality relationship between airports and urban development.
The models of urban development clustering developed use a diverse set of economic and environmental urban density proxy measures including the intensity of night time lights, surface temperature, the existence of impervious surfaces, as well as property values and rents. The proxy measures are applied in an Anselin Local Moran I Cluster Analysis and in a Geographic Weighted Regression (GWR) to investigate and model the airport-urban development relationship. The Anselin Local Moran I Analysis detects, delineates, and investigates urban development clustering near an airport. A GWR investigates the impact of explanatory variables including distance to the airport, primary roads, and the central business district on urban development.
The analysis also considers the statistical significance and spatial diffusion of explanatory variables in anchoring urban development.
The results can be summarized in four key findings suggesting that there is an independent urban cluster near Dulles Airport and the airport has had a significant influence in the area’s urban dynamics:
1. Dulles Airport has anchored urban development;
2. Airport operations have affected the magnitude of development;
3. An independent urban cluster exists near Dulles Airport; and
4. Several factors in addition to the existence of the airport explain the urban development.
This research advances the science relating to the airport–urbanization relationship in several ways.
1. An empirical model for induced airport impacts on urbanization is developed. Previous efforts have focused on direct and indirect impacts such as the relationship between airports and employment and property values without addressing the induced impacts on urbanization. Other studies have conceptually identified this relationship without testing it empirically.
2. It models urban development at the local level rather than at the regional or state/nationwide level. It examines the influence of the airport and the local spatial distribution of urban development using 1200 meter cells. Previous studies examined urban development impacts from airports at a regional scale covering a metropolitan area or a larger geographic extent.
3. Remote sensing and GIS are used to model the relationship between the airport and urbanization. Previous studies have used an economic and conceptual analysis of airport-anchored development, but did not apply remote sensing data and GIS to examine the impacts.
4. It develops a case study for Washington Dulles International Airport that models airport-induced urbanization. Previous studies have conceptually identified Dulles Airport as anchoring urbanization, but have not empirically modelled the airport’s impacts on urbanization.
5. Urban clusters of development proximate to Dulles Airport are detected and delineated. The development of the Dulles Airport-anchored urban clusters is examined using the relationship of airport proximity with other explanatory variables, including distance to primary roads and the central business district. In addition, the spatial diffusion and land use of the urban clusters are analyzed. Previous studies have focused on conceptual and direct and indirect models, but have not empirically analyzed airport-anchored clusters.