A comparative study of asset configurations to acquire low-altitude imagery for landscape modeling applications

Authors: Chris W Baynard*, University of North Florida, Dept of Economics and Geography, Ayan Dutta, University of North Florida, School of Computing, O Patrick Kreidl, University of North Florida, School of Engineering
Topics: Remote Sensing, UAS / UAV, Drones
Keywords: UAVs, drones, aerial photography, Earth observation, kites, balloons, pole aerial photography, landscape change, 3D printing, 3D modeling
Session Type: Virtual Paper
Day: 4/9/2021
Start / End Time: 4:40 PM / 5:55 PM
Room: Virtual 24
Presentation File: No File Uploaded


The adoption of UAVs, or drones, provides the ability to gather timely and localized high-resolution low-altitude imagery that has a variety of uses and applications. For example, UAVs have greatly enhanced landscape-level studies by providing updated imagery that can be turned into actionable information in the form of orthomosaics, vegetation health, elevation and 3D models. Nevertheless, UAVs cannot be flown everywhere. FAA regulations, sensitive areas, conservation zones, national parks and international rules for example, restrict the use of drones, which can limit research approaches. Additionally, the cost, training and certification also constrain the adoption of these dynamic sensors. While the imagery acquired is often high-quality, these sensors are not the only option. Lower-cost and easier to implement technologies such as kite, balloon and pole aerial photography open up many possibilities to acquire Earth observation and infrastructure/urban change imagery that can complement and sometimes rival drone data for better understanding landscape changes and development patterns. Furthermore, the modification and design of 3D printed models in platform design (to carry cameras) leads to innovative creations that can be scaled up. In this study we utilize four different sensor/platform combinations (UAVs, kites, balloons and poles) to acquire imagery at various locations on the University of North Florida campus (open field, garden, newly built roads) in order to highlight the pros and cons of these approaches. Furthermore, it provides examples of processed imagery products which yield data that can inform planning and decision making.

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