Jiang Sheng, Tang Guoan, Liu Kai
Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, 1 Wenyuan Road, Nanjing, Jiangsu 210023, China; State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), 1 Wenyuan Road, Nanjing, Jiangsu, 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, 1 Wenyuan Road, Nanjing, Jiangsu 210023, China.
PLoS One. 2015 Apr 24;10(4):e0123804. doi: 10.1371/journal.pone.0123804. eCollection 2015.
Loess shoulder-lines are significant structural lines which divide the complicated loess landform into loess interfluves and gully-slope lands. Existing extraction algorithms for shoulder-lines mainly are based on local maximum of terrain features. These algorithms are sensitive to noise for complicated loess surface and the extraction parameters are difficult to be determined, making the extraction results usually inaccurate. This paper presents a new extraction approach for loess shoulder-lines, in which Marr-Hildreth edge operator is employed to construct initial shoulder-lines. Then the terrain mask for confining the boundary of shoulder-lines is proposed based on slope degree classification and morphology methods, avoiding interference from non-valley area and modify the initial loess shoulder-lines. A case study is conducted in Yijun located in the northern Shanxi Loess Plateau of China. The Digital Elevation Models with a grid size of 5 m is applied as original data. To obtain optimal scale parameters, the Euclidean Distance Offset Percentages between shoulder-lines is calculated by the Marr-Hildreth operator and the manual delineations. The experimental results show that the new method could achieve the highest extraction accuracy when σ = 5 in Gaussian smoothing. According to the accuracy assessment, the average extraction accuracy is about 88.5%, which indicates that the proposed method is applicable for the extraction of loess shoulder-lines in the loess hilly and gully areas.
黄土谷缘线是将复杂的黄土地貌划分为黄土塬和沟坡地的重要构造线。现有的谷缘线提取算法主要基于地形特征的局部最大值。这些算法对于复杂的黄土表面对噪声敏感,且提取参数难以确定,导致提取结果通常不准确。本文提出了一种新的黄土谷缘线提取方法,该方法采用Marr-Hildreth边缘算子构建初始谷缘线。然后基于坡度分类和形态学方法提出了用于限定谷缘线边界的地形掩码,避免了非沟谷区域的干扰并对初始黄土谷缘线进行修正。在中国陕北黄土高原的宜君县进行了案例研究。以网格大小为5米的数字高程模型作为原始数据。为了获得最优尺度参数,通过Marr-Hildreth算子和人工勾绘计算谷缘线之间的欧氏距离偏移百分比。实验结果表明,在高斯平滑中当σ = 5时新方法能够实现最高的提取精度。根据精度评估,平均提取精度约为88.5%,这表明所提出的方法适用于黄土丘陵沟壑区黄土谷缘线的提取。