Canscan — An Algorithm for Automatic Extraction of Canyons
<p>A characteristic cross-section of a canyon defined by the slope inclination α, depth H and width W. The white line is centreline of the canyon along which its length (L) is measured.</p> "> Figure 2
<p>A cross-section of a canyon with its four characteristic points.</p> "> Figure 3
<p>Geometric relationships between four characteristic points (1, 2, 3 and 4) defined by the parameters of the maximal width W<sub>max</sub>, the minimal height h<sub>min</sub> and the minimal inclination angle α<sub>min</sub>.</p> "> Figure 4
<p>Constructed rays (1-4<sup>1</sup>, 1-4<sup>2</sup>, 1-4<sup>3</sup>) with the length corresponding to the parameter of the maximal width defined by the DTM point under consideration (point 1) and points classified as potential candidates for the second characteristic points (2<sup>1</sup>, 2<sup>2</sup>, 2<sup>3</sup>).</p> "> Figure 5
<p>The identification of the characteristic points on the opposite slope within circular sectors constructed along the section of the ray between the second characteristic point 2 and the point 3 that is horizontally separated from the ray endpoint 4 with the search radius r. Segments joining the endpoints (E<sup>1</sup>, E<sup>2</sup> and E<sup>3</sup>) with the centre (3<sup>E</sup>) of the circular sector within which they are identified represent the opposite slope.</p> "> Figure 6
<p>Smoothing of regions composed of identified cross-sections – white areas represent parts of the region excluded by smoothing, the yellow area is the result of smoothing and the red line is the skeleton line used for the length assessment.</p> "> Figure 7
<p>Several identified cross-sections (red) with their midpoints (M) and their projections on the terrain surface (T). Midpoints of the cross-sections longer than the parameter of the minimal width are merged into the region (grey) which skeleton line (white) is used for the length assessment.</p> "> Figure 8
<p>The first DTM with 16 m resolution and size of 148 × 204 pixels (left) and the extracted canyon (middle – white area) The border line of the extracted canyon (red) overlaid onto the contour map (right) with the equidistance of 25 m derived from the first DTM.</p> "> Figure 9
<p>The second DTM (16 m resolution) used for testing (up left) and with draped extraction results (down left – white area). The boundary of the extracted canyon superimposed on the contour map with the equidistance of 10 m (right).</p> "> Figure 10
<p>Results of canyon extractions performed on DTMs with the resolution of 8 (left) and 16 (right) meters.</p> "> Figure 11
<p>A constructed ray (1-4, full white line) traversing a slope is classified as a cross-section due to the large value of the central angle (red) of circular sectors used for detecting endpoints of cross-sections.</p> "> Figure 12
<p>Pixels with the lowest elevation (white) along identified cross-sections draped onto the wired mesh of DTM.</p> "> Figure 13
<p>Four characteristic points of a cross-section along a hill.</p> ">
Abstract
:1. Introduction
2. Materials
2.1. Study Area and Datasets
2.2. Implementation of the Algorithm
3. Methods
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- Identification of input parameters
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- Recognition of cross-sections of the canyon
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- Merging pixels in DEM representing these cross-sections into regions
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- Length assessment of the regions composed of recognized cross-sections.
3.1. Identification of Input Parameters
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- minimal inclination of slopes αmin
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- maximal width (the horizontal length of the longest cross-section along the canyon) Wmax
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- minimal width (the horizontal length of the shortest cross-section along the canyon) Wmin
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- minimal depth ( the height of the shallowest cross-section along the canyon) Hmin
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- minimal length Lmin
3.2. Recognition of the Cross-Sections
3.3. Merging of the DTM Pixels Representing Cross-Sections in to Regions
3.4. The Estimation of the Length of the Regions Composed of Identified Cross-Sections
4. Results
5. Discussion
6. Conclusions
Acknowledgements
References and Notes
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Balic, N.; Koch, B. Canscan — An Algorithm for Automatic Extraction of Canyons. Remote Sens. 2009, 1, 197-209. https://doi.org/10.3390/rs1030197
Balic N, Koch B. Canscan — An Algorithm for Automatic Extraction of Canyons. Remote Sensing. 2009; 1(3):197-209. https://doi.org/10.3390/rs1030197
Chicago/Turabian StyleBalic, Nebojsa, and Barbara Koch. 2009. "Canscan — An Algorithm for Automatic Extraction of Canyons" Remote Sensing 1, no. 3: 197-209. https://doi.org/10.3390/rs1030197