Utilizing Geospatial Technologies (Gst) To Enhance Commuter Biking As A Viable Alternative Mode Of Public Transportation System In Baltimore City
MetadataShow full item record
Type of WorkText
ProgramDoctor of Engineering
RightsThis item is made available by Morgan State University for personal, educational, and research purposes in accordance with Title 17 of the U.S. Copyright Law. Other uses may require permission from the copyright owner.
SubjectsGeographic information systems
Geographic information systems
Over the past several decades, commuter biking has seen an upward resurgence in many US cities, due to several reasons including environmental, economical, and health. However, the U.S. still lags behind the rest of the world in commuter biking. Studies suggest that transportation spending does play an important role in determining whether commuter biking becomes a viable alternative mode of transportation. Baltimore City, like most other major urban cities, continues to suffer from traffic congestions, severe air pollution, diminishing natural open space, and traffic related diseases. Some studies put the amount of land-cover consumed by transportation and related infrastructure at between 30% and 61%. The current approach to resolving these challenges such as widening roadways and inserting pocket bike lanes will not be able to cope with projected population increase, motor vehicle increase, nor stringent environment regulations. It is, therefore, prudent to begin exploring other environmentally friendly modes of transportation such as commuter biking as a viable option. This study explores the use of geospatial technologies (GSTs) including remote sensing (RS), and geographic information systems (GIS) to enhance commuter bike infrastructure in Baltimore City, Maryland. GIS coverages include land-use/land-cover, roads, soils, elevation, and demographics; RS data include an IKONOS image; these dataset were processed using ArcGIS and ENVI software. Level I supervised and unsupervised classification of the IKONOS image was carried out. Results showed urban/Built-Up areas to be 31%, vegetation 56%, and water/marsh around 13%. Google Earth measurements of road attributes were relatively accurate, and GIS procedures generated fast and cost-effective products that could be useful in bikeway infrastructure enhancements.