An Assessment of a Low-Cost Approach to Automatic Spatial Referencing Of sUAS-SfM Image Orthomosaics for Use in Denied Environments

Abstract

Low-cost unmanned aerial systems have be underutilized in post-disaster scenarios. The need for fast and accurate information is very important when making sense of situations where immanent risk to response personnel as well as disaster survivors is present. The establishment of a geospatial relationship to determine the condition of a space or place becomes ever so important in the aftermath of a catastrophic event such as a terrorist attack, or a natural disaster. In a cluttered environment, it is often difficult if not impossible to establish a geospatial relationship using image data acquired by a small unmanned aerial system without spatial referencing. To test a potential methodology to solve this issue of spatial relevance in a denied environments where no ground control can be established, an experiment was conducted using a custom built sUAS to carry an off-the-shelf camera for image acquisition. With the use of open-source software the imagery collected was given spatial reference and processed through a contemporary image processing workflow. The image output was analyzed for its error with respect to the requirements of the Federal Emergency Management Agency.