Snake model for the extraction of loess shoulder-line from DEMs

Su, Yan; Tang, Guoan; Li, Fayuan; Zhang, Lei

doi:10.1007/s11629-013-2484-0

Cited by 19 publications

(19 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, the extraction accuracy of the Loess shoulder line is one of the important factors to influence the study. Many researchers [25,26,34] have performed an in-depth study on the extraction methods and the accuracy of the Loess shoulder line. This study is based on previous researchers' high-accuracy extraction of the Loess shoulder line in the study area and to ensure that Loess shoulder-line data can accurately reflect the topography change of the study site.…”

Section: Influence Factors Of Loess Shoulder-linementioning

confidence: 99%

“…Digital land surface analysis has been used to extract the basic terrain derivatives (e.g., slope and aspect) [15,16] and to study complicated applications (e.g., paleo-topographic reconstruction and landform classification) [17][18][19][20][21] of the Loess Plateau. The terrain points [22][23][24], lines [25][26][27], and surfaces [28][29][30] studies mainly focused on research with the view of developing and evaluating technologies and methods, and there is a lack of research and discussion on the role of terrain data in the study of the topography and geomorphology of the Loess Plateau. Tang et al [1] established the theory of the slope topo-sequence, which they successfully applied to study the Loess landform.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Topographic Spatial Variation Analysis of Loess Shoulder Lines in the Loess Plateau of China Based on MF-DFA

Cao

et al. 2017

IJGI

View full text Add to dashboard Cite

Abstract:The Loess Plateau in China is internationally known for its unique geographical features and has therefore been studied by many researchers. This research exploits the regional differences in the spatial morphological characteristics of Loess shoulder lines in different landform types as an important basis for geomorphological regionalization. In this study, we used ensemble empirical mode decomposition (EEMD), multi-fractal detrended fluctuation analysis (MF-DFA), and detrended cross-correlation analysis (DCCA) to analyze topographic data series extracted from shoulder lines. Loess shoulder-line land variations series data from the Suide, Ganquan, and Chunhua areas on the Loess Plateau were selected and a combination of the two above-mentioned methods was used to study land variations at these three sample sites. The results revealed differences in the topographic variations of the multi-fractal characteristics and the topographic spatial variation in the Loess shoulder line of the three sample sites. Furthermore, the extent to which the results were affected by noise and the analysis scale differed among the three areas.

show abstract

Section: Influence Factors Of Loess Shoulder-linementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Topographic Spatial Variation Analysis of Loess Shoulder Lines in the Loess Plateau of China Based on MF-DFA

Cao

et al. 2017

IJGI

View full text Add to dashboard Cite

show abstract

“…The shoulder line, also termed as gully-edge line (Hessel, 2002;Wu et al, 2008) or gully borderline (Daba, Rieger, & Strauss, 2003), is an apparent boundary of the U-shaped gully with a clear break in the slope angle (Hessel, 2002;Li, Zhang, Zhu, He, & Yao, 2015), which divides smooth interfluves and precipitous gully-slope lands (Song et al, 2013). As a terrain feature to characterize soil erosion and the morphological variation of landforms (Lu, Qian, & Chen, 1998;Tang, Xiao, Jia, & Yang, 2007;Yan, Tang, Li, & Zhang, 2014), the shoulder line is a natural boundary between land type and land use , as well as an adjacent boundary for positive and negative terrain, upland and gully land, slope erosion, and gully erosion (Song et al, 2013;Xiong, Tang, Yan, Zhu, & Sun, 2014;Zhou et al, 2010). The shoulder line is always located in the most active part of a gully, and its dynamics reflect the extension of gully length and the expansion of the gully area (Chen & Feng, 1992).…”

Section: Introductionmentioning

confidence: 99%

Influences of different surveying and mapping methods on fractal characteristics of gully-head shoulder lines

et al. 2016

View full text Add to dashboard Cite

2016): Influences of different surveying and mapping methods on fractal characteristics of gully-head shoulder lines, Physical Geography, ABSTRACT Accurate quantification of gully shoulder lines (gully borderlines) will help better understand gully formation and evolution. Surveying and mapping are the most important ways to obtain precise morphology. To evaluate the influences of different steps of surveying and of curvefitting methods of mapping on the morphology of the shoulder line characterized by fractal dimensions, 13 shoulder lines at gully heads were surveyed using a total station and then mapped with different methods of curve fitting, with the fractal dimensions calculated by maps compared with those measured in the field. Fractal dimensions by field measurement ranged from 1.185 to 1.456. Compared with field measurements, the average absolute errors of polygonal line, quadratic B-spline, and arc-fitting methods are 0.045, 0.040, and 0.046, respectively; the average relative errors are 3.48, 3.13, and 3.59%. Therefore, the quadratic B-spline method has a higher accuracy. The standard error of the fractal dimension tends to be larger as average step length increases. The error is ~5% when the step length is 0.7 m, which is advisable for field surveying. This study will help promote the efficiency of field surveying and mapping, and thus promote the accuracy and credibility of gully morphology.

show abstract

“…Due to the topographical variation in the loess landform, the surfaces generated by the vegetation removal point cloud data are incorrect, which is Figure.2 shows the detail of vegetation removal point cloud which is incorrect surface. (Yan, Tang et al 2014) Therefore, the shoulder line should be extracted to separate surface into positive terrain and negative terrain and removing "noise" points respectively. Many methods of shoulder line extraction have been proposed based on DEM, which can be referenced (Lu, Qian et al 1998, Xiao and Tang 2007, Zhou, Tang et al 2010, Zhang, Tang et al 2012, Yan, Tang et al 2014.…”

Section: Introductionmentioning

confidence: 99%

“…(Yan, Tang et al 2014) Therefore, the shoulder line should be extracted to separate surface into positive terrain and negative terrain and removing "noise" points respectively. Many methods of shoulder line extraction have been proposed based on DEM, which can be referenced (Lu, Qian et al 1998, Xiao and Tang 2007, Zhou, Tang et al 2010, Zhang, Tang et al 2012, Yan, Tang et al 2014. However, the method of high precise shoulder line extraction based on point cloud data is still unsolved because of the "noise" points.…”

Section: Introductionmentioning

confidence: 99%

Point Cloud Oriented Shoulder Line Extraction in Loess Hilly Area

Yang

Xiong

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:Shoulder line is the significant line in hilly area of Loess Plateau in China, dividing the surface into positive and negative terrain (P-N terrains). Due to the point cloud vegetation removal methods of P-N terrains are different, there is an imperative need for shoulder line extraction. In this paper, we proposed an automatic shoulder line extraction method based on point cloud. The workflow is as below: (i) ground points were selected by using a grid filter in order to remove most of noisy points. (ii) Based on DEM interpolated by those ground points, slope was mapped and classified into two classes (P-N terrains), using Natural Break Classified method. (iii) The common boundary between two slopes is extracted as shoulder line candidate. (iv) Adjust the filter gird size and repeat step i-iii until the shoulder line candidate matches its real location. (v) Generate shoulder line of the whole area. Test area locates in Madigou, Jingbian County of Shaanxi Province, China. A total of 600 million points are acquired in the test area of 0.23km 2 , using Riegl VZ400 3D Laser Scanner in August 2014. Due to the limit Granted computing performance, the test area is divided into 60 blocks and 13 of them around the shoulder line were selected for filter grid size optimizing. The experiment result shows that the optimal filter grid size varies in diverse sample area, and a power function relation exists between filter grid size and point density. The optimal grid size was determined by above relation and shoulder lines of 60 blocks were then extracted. Comparing with the manual interpretation results, the accuracy of the whole result reaches 85%. This method can be applied to shoulder line extraction in hilly area, which is crucial for point cloud denoising and high accuracy DEM generation.

show abstract

Snake model for the extraction of loess shoulder-line from DEMs

Cited by 19 publications

References 7 publications

Topographic Spatial Variation Analysis of Loess Shoulder Lines in the Loess Plateau of China Based on MF-DFA

Topographic Spatial Variation Analysis of Loess Shoulder Lines in the Loess Plateau of China Based on MF-DFA

Influences of different surveying and mapping methods on fractal characteristics of gully-head shoulder lines

Point Cloud Oriented Shoulder Line Extraction in Loess Hilly Area

Contact Info

Product

Resources

About