Mapping of river terraces with low-cost UAS based structure-from-motion photogrammetry in a complex terrain setting

Authors: Hui Li*, China University of Geosciences, Louisiana State University Agricultural Center, Lin Chen, China University of Geosciences, Zhaoyang Wang, China University of Geosciences, Zhongdi Yu, Beijing North-Star Digital Remote Sensing Technology Co., Ltd
Topics: Remote Sensing
Keywords: River terrace; UAS; structure from motion; DSM; complex terrain setting
Session Type: Paper
Day: 4/5/2019
Start / End Time: 1:10 PM / 2:50 PM
Room: Harding, Marriott, Mezzanine Level
Presentation File: No File Uploaded


River terraces are the principal geomorphic features for unravelling tectonics, sea level, and climate conditions during the evolution history of a river. Increasing availability of high-resolution topography data generated by low cost Unmanned Aerial Systems (UAS) and modern photogrammetry offer an opportunity to identify and characterize these features. This work assessed the capabilities of UAS-based Structure-from-Motion (SfM) photogrammetry, coupled with a river terrace detection algorithm for mapping of river terraces over a 1.9 km2 valley of complex terrain setting, with a focus on the performance of this latest technology over such complex terrains. With the proposed image acquisition approach and SfM photogrammetry, we constructed a 3.8-cm resolution OrthoMosaic and digital surface model (DSM). The vertical accuracy of DSM was assessed against 196 independent check points measured with a real-time kinematic (RTK) GPS. The results indicated that the root mean squared error (RMSE) and mean absolute error (MAE) were 3.1 cm and 2.9 cm, respectively. A simple algorithm was then employed to detect river terraces from the generated DSM. The results showed that three levels of river terraces and a high-level floodplain were identified. Most of the detected river terraces were confirmed by field observations. Overall, our results demonstrated that the low-cost UAS-based SfM technique can yield highly accurate ultrahigh-resolution topography data over complex terrain settings, making it particularly suitable for quick and cost-effective mapping of micro to medium-sized geomorphic features under such terrains in remote or poorly accessible areas.

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