During World War II, United States Army and Navy pilots trained on several hundred bombing ranges encompassing more than 12 million acres of land, leaving behind crater-scarred landscapes across the country. Post-war estimates suggest that 10-15% of aerial bombs used failed to detonate as intended, so these areas today are contaminated by a large number of dangerous unexploded bombs (UXB) which remain under the surface. Until recently, detecting UXB has been a tedious and expensive process done in three stages: (1) identifying and mapping general areas of concentrated bomb craters using historical air photos and records; (2) intensely searching these areas at a larger scale for much smaller UXB entry holes; and (3) confirming the presence of individual UXB using magnetometry or ground-penetrating radar. This research aims to streamline the workflow for stage 1 and 2 using semi-automated object-based image analysis (OBIA) methods with multi-source high spatial-resolution imagery. Using the Fort Myers Bombing and Gunnery Range in Florida as a study area, this thesis determines what OBIA software and Imagery is best at locating UXB in this environment. I assess the use of LiDAR-derived DEMs, historical air photos and high-resolution color digital orthophotos in Feature Analyst and Imagine Objective, and discuss optimal inputs and configurations for UXB searches in karst wetlands. This methodology might be applied by the detection and clearance industry in former war zones, and aid in restoring former training ranges to safe land uses in the U.S.


Cynthia Miller

Committee Member

Fei Yuan

Committee Member

Forrest Wilkerson

Date of Degree




Document Type



Master of Science (MS)


Social and Behavioral Sciences

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License



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