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The Profiles Based on Ridge and Valley Lines to Extract Shoulder Lines on the Loess Plateau.
- Source :
- Remote Sensing; Jan2023, Vol. 15 Issue 2, p380, 18p
- Publication Year :
- 2023
-
Abstract
- The shoulder line is fundamental to geomorphic evolution and erosion monitoring research on the Loess Plateau, which represents the boundary between positive terrain (intergully) and negative terrain (inner gully). The existing extraction methods mainly suffer the problems of unclear geological significance, poor landform application, and low efficiency of algorithms. This paper proposes a new loess shoulder line automatic extraction method, in which topographic feature points (ridge and valley points) were used as endpoints to generate continuous profiles, and two parameters, analysis operator size (L) and filter threshold (σ), were created for shoulder point extraction from each profile. This method can be applied to complex landforms such as the continuous shoulder lines of terraces and extracts. Herein, three typical areas on the Dongzhi Plateau were selected to assess the performance of the method, and a digital elevation model (DEM) with a resolution of 5 m was used as source data. The accuracy assessment index was the Euclidean distance offset percentage (EDOP), and the original evaluation method was improved based on Structure from Motion–Multiview Stereo (SfM-MVS) technology. The experimental results showed that the average accuracy of the proposed method in the three test areas reached 89.3%, which is higher than that of the multidirectional hill-shading and P-N methods. Via testing in different areas, it could be concluded that the extraction efficiency was less affected by the area of the test region, and the approach exhibited a suitable robustness. Simultaneously, the optimal values of parameters L and σ were examined. This study increases the possibility of accurate shoulder line extraction in the large area of the Loess Plateau. [ABSTRACT FROM AUTHOR]
- Subjects :
- LOESS
SHOULDER
DIGITAL elevation models
EUCLIDEAN distance
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 15
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 161479394
- Full Text :
- https://doi.org/10.3390/rs15020380