Browsing by Subject "Geodesy"
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Item Developing an Intelligent Decision Support System Framework for School Transport Management(2019-03-29) Almurshidi, Ahmed Hassan; Jeihani, Mansoureh; Chavis, Celeste; Shin, Hyeon-Shic; Sen, Siddhartha; Transportation; Doctor of PhilosophyThe current school bus stops along school bus routes in the UAE are based on requests from the parents, and most of them are in front of the main gate of each studentās house. As a result, bus stops are generally placed so close to each other that in some cases the distance between two stops is just 40 meters. Moreover, a lack of school transportation planning often leads to having unnecessary bus stops, which increases the travel time of the school bus. In this research, GIS-based models were created to assist the Emirates Transport Authority and Ministry of Education in optimizing their bus stops. The main constraints were determined by the Emirates Transport Authority such as proposed location for stops, and average dwelling time for each student. The ArcGIS network analyst extension was used to create optimum route models and assign each student to a new bus stop. These two models, new route model and location-allocation model, were used to identify redundant bus stops throughout the study area (Dibba al Fujairah- U.A.E). The result suggested 73% of the current bus stops could be eliminated, saving approximately 26% of the travel time. Eleven students live within 350 meters of the main gate of the school, so they are not eligible for free school transportation. The models developed in this study can easily be transferred to other UAE school districts and re-run based on user-defined parameters. For sure, it will inspire the school transport and Ministry of Education officials to examine and apply the proposed systematic optimal route design approach to their current system. Finally, this study opens the door to further investigation for various aspects for improving the school transportation system in the UAE, such as reducing the number of bus fleets and carbon dioxide.Item Examining The Impact Of Environmental Variables On The Insurgent Behavior With The Aid Of Gis: Case Study Of Afghanistan(2014) Carwell, Marcus Jermaine; Jha, Manoj K.; Civil Engineering; Doctor of EngineeringThe guerilla warfare style tactics of the Afghanistan insurgents is a problem the US-UN troops face in Afghanistan. The insurgents are able to utilize the surrounding environment to gain a tactical advantage. Examples consist of suicide bombers, sniper attacks, Improvised Explosive Device (IED), and car bombs. These types of attacks utilize the surrounding environment in order to gain success. For example, the suicide bomb is more likely to have success if there is an environment full of people (e.g., busy city streets). An environment full of people makes it hard to target a threat. Sniper attacks have a greater chance of success if executed at high elevations or slopes with thick forest or high vegetation as a cover. The objective of this research is to develop a model utilizing Geographic Information System (GIS) as a framework to determine the significance of environmental variables on Afghanistan insurgency and resulting vulnerability to US-UN troops. A review of the relevant literature is conducted which helps to become familiar with the different mathematical models used to combat guerilla warfare. Frederick Lanchester developed attrition equations for military conflict in 1916. The Deitchman (1962) attrition equation for military conflict model takes into account the area or geographical location of an insurgent when implementing ambush attacks. McCormick and Giordano's 2002 equation expands upon guerrilla warfare by adding the effects of recruitment and the population support for the insurgency and the government. These mathematical models take into account geography, terrain, population density and infrastructure when combating guerilla warfare tactics. This research investigates the tracking and visualization of insurgent attacks based on their use of the geography, terrain, population density, and infrastructure, also referred to as Environmental Variables (EVs). The data used focuses on the EV parameters at an insurgent attack location. A GIS tracks the spatial and temporal movement of insurgents and creates a visual representation of Afghanistan. The EVs are visually represented at the insurgents' attack locations with a GIS. Logistic regression is the proposed model used to determine which EV parameters are significant to the vulnerability of US-UN troop's location. The familiarity with the EV parameters during the time of attack allows one to see which EV parameters would put US-UN troops in positions vulnerable to attacks. Logistic regression models the data from the GIS framework. The EV parameters that are significant are identified at insurgent's attack locations. A Network Analyst based GIS algorithm helps to locate the vulnerable areas that meet the specified EV criteria. The proposed model is applied to real case studies of Afghanistan insurgent attacks against US-UN troops. The results show Afghanistan insurgents' use the EVs to increase the probability of US-UN fatalities. The years 2008, 2009 and 2010 for Afghanistan are significant with a Multiple R of 0.83966 and R Square 0.705028 with the F-test of 71%. The ANOVA for the Afghanistan database tested significant with F at 0. The regression coefficient table p-value for the EVs tested 5.7E-182 for Population Density, 1.33E-74 for Elevation, 0.006331 for Slope, and 7.55E-32 for the nearest River from the insurgent's attack location. The environmental variables' p-value tested less than 0.05. Therefore, it can be concluded that EVs are significant in creating a higher probability of a US-UN fatality. A GIS algorithm is employed, which creates a route based on the distance to maneuver around the insurgent's attack locations that contain EVs that increase US-UN fatalities. The Afghanistan GIS Database allows US-UN troops to monitor entire areas with a visual image. Then optimal routes can be identified within an Afghanistan province that would minimize the possibility of a US-UN fatality. Future works may include further refinement to the model by performing a multi-objective optimization to come up with the safest routes by simultaneously examining the impact of various EVs in a multi-objective context. Key Words: GIS, spatial analysis, insurgents, environmental variables, Afghanistan insurgencyItem Improved Refraction Corrections for Satellite Laser Ranging (SLR) by Ray Tracing through Meteorological Data(2007-07-12) Hulley, Glynn Collis; Hoff, Raymond M.; Pavlis, Erricos C.; Physics; Physics, AtmosphericThe most important accuracy-limiting factor for modern space-based geodetic techniques such as Satellite Laser Ranging (SLR), Very Long Baseline Interferometry (VLBI), the Global Positioning System (GPS), and satellite altimetry is the modeling of atmospheric refraction corrections. SLR uses lasers to measure very precise ranges from ground tracking stations to orbiting geodetic satellites with current single-shot accuracies at the sub-centimeter level.Item Utilizing Geospatial Technologies (Gst) To Enhance Commuter Biking As A Viable Alternative Mode Of Public Transportation System In Baltimore City(2015) Jackson-Pringle, Judy; Wilson, Frederick K.; Civil Engineering; Doctor of EngineeringOver 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.