https://orcid.org/0000-0001-7424-644X
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ABSTRACT
Agricultural terraces are important for agricultural production and soil-and-water conservation. They comprise treads and risers that require manual construction and maintenance. If managed improperly, risers will collapse, causing soil loss, gully erosion, and cultivation threats. However, mapping terrace risers remains a challenge. This study presents a novel approach to automatically map terrace risers by combining remote sensing images and digital elevation models (DEMs). First, a terraced hillslope was extracted via a hill-shading method and edges in the image were detected using a Canny edge detector. Next, the DEM was used to generate the contour direction, and edges along this direction were searched and coded as candidate terrace risers via directional detection. Finally, the results of directional detection and the edge image obtained from the Canny detector were overlaid to backtrack complete terrace risers. The approach was validated using four study areas with different topographic characteristics in the Loess Plateau, China. The results verify that the approach achieves outstanding performance and robustness in mapping terrace risers. The precision, recall, and F-measure were 90.81%–97.57%, 88.53%–94.10%, and 90.13%–95.80%, respectively. This approach is flexible and applicable with freely available images and DEM sources.
Acknowledgments
The authors express their gratitude to the journal editor and reviewers, whose thoughtful suggestions played an important role in improving the quality of this paper. Many thanks are also given to Liu Hailong for his assistance in Programming Codes on C#, Dai Ziyang for his comments on language.
Disclosure statement
No potential conflict of interest was reported by the authors.
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Notes on contributors
Wen Dai
Wen Dai received the B.S. degrees from the Guizhou University, Guiyang, China. He is currently pursuing the Ph.D. degree at Nanjing Normal University, Nanjing, China. His current research interests include remote sensing image analysis and digital terrain analysis.
Jiaming Na
Jiaming Na received the B.S. degrees from the Nanjing Agricultural University, Nanjing, China. He is currently pursuing the Ph.D. degree at Nanjing Normal University, Nanjing, China. His current research interest is point cloud analysis.
Nan Huang
Nan Huang received the B.S. degrees from the Anhui Normal University, Wuhu, China. She is currently pursuing the Master degree at Nanjing Normal University, Nanjing, China. She mainly works on the research in digital terrain analysis.
Guanghui Hu
Guanghui Hu received the B.S. degree from the Shandong University of Science and Technology, Qingdao, China. He is currently pursuing the Master degree at Nanjing Normal University, Nanjing, China. His current research interest is digital terrain analysis.
Xin Yang
Xin Yang received the Ph.D. degree from Nanjing Normal University. She is a professor in Nanjing Normal University now. Her main research interest includes digital terrain analysis.
Guoan Tang
Guoan Tang born in 1961. He received the Ph.D. degree from University of Salzburg. He is a professor and a Ph.D. supervisor now. His main research interest includes digital terrain analysis.
Liyang Xiong
Liyang Xiong received the Ph.D. degree from Nanjing Normal University. He is a professor in Nanjing Normal University now. His main research interest is landform evolution.
Fayuan Li
Fayuan Li received the Ph.D. degree from Chinese Academy of Sciences. He is a professor in Nanjing Normal University now. His main research interest is gully erosion.