The U.S. Army manages thousands of sites that cover millions of acres of land for various military training purposes and activities and often faces a great challenge on how to optimize the use of resources. A typical example is that the training activities often lead to off-road vehicle trails and paths and how to use the trails and paths in terms of minimizing maintenance cost becomes a problem. Being able to accurately extract and map the trails and paths is critical in advancing the U.S. Army's sustainability practices. The primary objective of this study is to develop a method geared specifically toward the military's needs of identifying and updating the off-road vehicle trails and paths for both environmental and economic purposes. The approach was developed using a well-known template matching program, called Feature Analyst, to analyze and extract the relevant trails and paths from Fort Riley's designated training areas. A 0.5 meter resolution false color infrared orthophoto with various spectral transformations/enhancements were used to extract the trails and paths. The optimal feature parameters for the highest accuracy of detecting the trails and paths were also investigated. A modified Heidke skill score was used for accuracy assessment of the outputs in comparison to the observed. The results showed the method was very promising, compared to traditional visual interpretation and hand digitizing. Moreover, suggested methods for extracting the trails and paths using remotely sensed images, including image spatial and spectral resolution, image transformations and enhancements, and kernel size, was obtained. In addition, the complexity of the trails and paths and the discussion on how to improve their extraction in the future were given.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:theses-1828 |
| Date | 01 May 2012 |
| Creators | Oller, Adam |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses |
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