Date of Award


Document Type


Degree Name

Master of Science


Department of Systems Engineering and Management

First Advisor

Eric Mbonimpa, PhD


Mitigation of aircraft noise and encroachment by residential areas at various U.S. military installations remains a challenge and hampers effective military operations. The Air Force has established standard practices that utilize computational noise models to generate and display noise propagation from military installations. Despite great advances in models and mitigation action plans, the current USAF Noisemap modeling tool and methods do not consider the effects of variation in land cover. Moreover, such limitations could greatly affect the accuracy of predicting aircraft noise pollution. The standard modeling method assumes a ground cover impedance of 225 Kpa*s/m2, which generalizes the land cover characteristics as grass to reduce computational difficulties and man-hours. However, hard surfaces such as asphalt can have an impedance of 3000 Kpa*s/m2. We hypothesize that noise propagation from the source to the receiver can significantly vary with detailed land use and land cover changes. Therefore, a detailed comparison of land cover scenarios and their impacts on noise propagation at military installation was conducted in this study. Multiple scenarios were produced using four types of land cover maps (GIS-based, NLCD-based, Grass-Only, and Dominant -based) and flight operations. Moody AFB, GA, and its flight operations were selected as a case study. Statistical analyses showed that changing the land cover of aircraft runway and flightline to hard surfaces in the model led to significant increases in noise level at three out of ten sampled locations in comparison to the standard Grass-Only scenarios. However, this was observed only when the aircraft is on the ground (static operations). No significant difference was observed for other scenarios when compared to the grass-only, except when the NLCD-map size was reduced to only encompass the areas within the perimeter of Moody AFB, GA. Scenarios with more detailed land cover did not generate significant differences in noise when compared the Grass-Only. Further, randomizing the land cover types within a region v revealed noise propagation were most sensitive to changes in land impedance and location when compared to operations locations and impedance ranges. However, majority of the impedances were stratified between low or high values. Additionally, each scenarios modeling time was captured. Modeling time increase with land cover detail for each scenarios. The Dominant-based scenarios required the least amount of time to model. In conclusion, the current noise modeling practices using Grass-Only cover may not be affected by the land cover in many locations, but few scenarios that showed differences warrant further analysis using more installations, flight operations and 3D objects. This could inform USAF modelers whether extra computational effort is needed. This study used only A-10 aircraft at Moody AFB, GA and a future study that analyze various aircrafts is recommended to draw stronger conclusions on land cover change impact on noise propagation models.

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