The red imported fire ant (Solenopsis invicta)(RIFA) is a major pest in the United States, causing serious economic and human costs. This study explored the feasibility of using digital aerial remote sensing in multispectral/multitemporal detection and mapping of RIFA mounds. Comparison of photointerpretive mound counts versus ground control counts was performed within two grass types, common Bermuda and tall fescue. Flights collecting digital image data occurred at three intervals in 2009, with ground truth data collected collaterally. Poisson regression count modeling was first utilized for analysis of both datasets. Moran's Index geospatial analysis was applied following the Poisson model. Outcomes in this study from these models demonstrate their ability to robustly support studies for tracking and control of RIFA or other pest populations. Additionally, in one location, type of grass cover appeared to affect detectability of mounds between the two methods.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-4250 |
| Date | 30 April 2011 |
| Creators | Carruth, Mark Ellis |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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