UNMANNED AERIAL SYSTEMS (UAS) IMAGE PREPROCESSING TO REDUCE ARTIFACTS AND IMPROVE GEOMETRIC REGISTRATION WHEN GENERATING ORTHOPHOTO MOSAICS AND 3D MODELS

Drones can now be used to quickly collect imagery data in a highly automated way; however, individual images must be combined to form an orthomosaic or 3-Dimentional (3D) model using photogrammetry software. Currently, the existing software may generate erroneous output in the form of artifacts or positional errors caused by homogeneous areas, light reflections, object movement between photos, or sub-optimal algorithms. The goal of this research was to develop preprocessing algorithms that would filter movement (or other time or position-based differences) and areas of homogeneity. The hypothesis is that filtering these parts of the image would reduce artifacts and improve the positional accuracy of the resulting orthomosaic images and 3D models. Software improvements to reduce these errors will be especially useful if delivered in an open-source product. Python code was developed to preprocess the images that were input to OpenDroneMap (ODM). The system was tested on a variety of different datasets that each contained a subset of the characteristics that often cause problems (movement, reflection, or undifferentiated areas). Various combinations of filters (treatments) were applied to the datasets and the 2D and 3D results were reviewed for a reduction in artifacts. The results were significantly better with respect to artifacts, but no significant improvement in positional accuracy was observed except in the cases where the drone stopped when capturing an image

Contrasting Orthophotos by Height, Overlap, and Drone

Drones have recently become a mainstay for surveying and modeling of small areas of land in a cost-efficient manner. Yet there are many variables that affect the time, quality, and cost of capturing and generating such products. We look at several of these parameters and discuss the alternatives to minimize cost over a series of projects. The parameters in question include height, overlap, sensor resolution, processing time, drone costs, computer costs, processing costs, time in the field, storage, drone endurance and the likelihood of costly delays. A series of flights using different drones and flight parameters were then used to validate the hypothesis. The results indicate that for a particular need and sensor resolution there exists a curve of height vs overlap that produces similar results. Thus, selecting the point on the curve that minimizes flight time will produce the lowest cost for a series of projects

Analysis of student beliefs in a tertiary preparatory mathematics course

Every year approximately 800 students enrol in the tertiary preparatory course TPP7181 at the University of Southern Queensland. Successful completion of this course will allow students to enrol in either further preparatory level mathematics courses or undergraduate study. For many of the students enrolled in this course, the study of mathematics was undertaken quite some time ago and usually in a school setting. Drop out rates for this course are quite high and it is hypothesized that motivation may be a key factor in determining student success or otherwise. In this study scales assessing self-efficacy were utilized in an attempt to gauge aspects of the motivation of students enrolled in the course. Initial results suggest that only specific measures of student confidence predict their performance and that both gender and age mediate the strength of this prediction