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Title:Building a Sustainable GIS Framework for Supporting a Tribal Transportation Problem
Authors:EunSu Lee
University:North Dakota State University
Publication Date:Mar 2017
Report #:MPC-15-287
Project #:MPC-425
TRID #:01633275
Keywords:data analysis, data quality, geographic information systems, Indian reservations, network analysis (planning), quality assurance, quality control, roads, spatial analysis, transportation planning
Type:Research Report – MPC Publications

Abstract

Due to the recent oil boom, the Fort Berthold Reservation has experienced a dramatic increase in highway and local traffic. To support energy transportation and provide safe roads, the reservation needs cost-efficient and effective transportation planning for present and future needs. A quality road network for the reservation is crucial for transportation operations and management. This study will demonstrate how to integrate multiple road networks to provide comprehensive digital roads using public sources and provide guides to perform a quality control (QC) assessment before delivering data and using these data for geospatial analysis. This paper will also provide the fundamental concepts for quality assurance (QA) and QC. Thus, tribal geographic information system (GIS) professionals working with other reservations will gain second-hand experience configuring quality checks and processes for automation and running the automated data checks. With the integrated road networks, the tribal transportation agency can develop bike line management, conduct ambulance service coverage analysis, develop a program of asset management, and plan road maintenance and rehabilitation. The authors recommend that the agency develop a linear referencing system (LRS) on the proposed road network to adopt efficient asset management and version control.

How to Cite

Lee, EunSu. Building a Sustainable GIS Framework for Supporting a Tribal Transportation Problem, MPC-15-287. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2017.

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