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Is It Reliable to Extract Gully Morphology Parameters Based on High-Resolution Stereo Images? A Case of Gully in a “Soil-Rock Dual Structure Area”
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Is It Reliable to Extract Gully Morphology Parameters Based on High-Resolution Stereo Images? A Case of Gully in a “Soil-Rock Dual Structure Area”
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Is It Reliable to Extract Gully Morphology Parameters Based on High-Resolution Stereo Images? A Case of Gully in a “Soil-Rock Dual Structure Area”
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Journal Article
Is It Reliable to Extract Gully Morphology Parameters Based on High-Resolution Stereo Images? A Case of Gully in a “Soil-Rock Dual Structure Area”
2024
Overview
The gully morphology parameter is an important quantitative index for monitoring gully erosion development. Its extraction method and accuracy evaluation in the “soil-rock dual structure area” are of great significance to the evaluation of gully erosion in this type of area. In this study, unmanned aerial vehicle (UAV) tilt photography data were used to evaluate the accuracy of extracting gully morphology parameters from high-resolution remote sensing stereoscopic images. The images data (0.03 m) were taken as the reference in Zhangmazhuang and Jinzhongyu small river valleys in Yishui County, Shandong Province, China. The accuracy of gully morphology parameters were extracted from simultaneous high-resolution remote sensing stereo images data (0.5 m) was evaluated, and the parameter correction model was constructed. The results showed that (1) the average relative errors of circumference (P), area (A), linear length of bottom (L1), and curve length of bottom (L2) are mainly concentrated within 10%, and the average relative errors of top width (TW) are mainly within 20%. (2) The average relative error of three-dimensional (3D) parameters such as gully volume (V) and gully depth (D) is mainly less than 50%. (3) The larger the size of the gully, the smaller the 3D parameters extracted by visual interpreters, especially the absolute value of the mean relative error (Rmean) of V and D. (4) A relationship model was built between the V and D values obtained by the two methods. When V and D were extracted from high-resolution remote sensing stereo images, the relationship model was used to correct the measured parameter values. These findings showed that high-resolution remote sensing stereo images represents an efficient and convenient data source for monitoring gully erosion in a small watershed in a “soil-rock dual structure area”.
