Automated multi-scale classification of the terrain units of the Jiaxie Guyots and their mineral resource characteristics
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Abstract: Given the advances in satellite altimetry and multibeam bathymetry, benthic terrain classification based on digital bathymetric models (DBMs) has been widely used for the mapping of benthic topographies. For instance, cobalt-rich crusts (CRCs) are important mineral resources found on seamounts and guyots in the western Pacific Ocean. Thick, plate-like CRCs are known to form on the summit and slopes of seamounts at the 1 000–3 000 m depth, while the relationship between seamount topography and spatial distribution of CRCs remains unclear. The benthic terrain classification of seamounts can solve this problem, thereby, facilitating the rapid exploration of seamount CRCs. Our study used an EM122 multibeam echosounder to retrieve high-resolution bathymetry data in the CRCs contract license area of China, i.e., the Jiaxie Guyots in 2015 and 2016. Based on the DBM construted by bathymetirc data, broad- and fine-scale bathymetric position indices were utilized for quantitative classification of the terrain units of the Jiaxie Guyots on multiple scales. The classification revealed four first-order terrain units (e.g., flat, crest, slope, and depression) and eleven second-order terrain units (e.g., local crests, depressions on crests, gentle slopes, crests on slopes, and local depressions, etc.). Furthermore, the classification of the terrain and geological analysis indicated that the Weijia Guyot has a large flat summit, with local crests at the southern summit, whereas most of the guyot flanks were covered by gentle slopes. “Radial” mountain ridges have developed on the eastern side, while large-scale gravitational landslides have developed on the western and southern flanks. Additionally, landslide masses can be observed at the bottom of these slopes. The coverage of local crests on the seamount is ~1 000 km2, and the local crests on the peak and flanks of the guyots may be the areas where thick and continuous plate-like CRCs are likely to occur.
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Figure 1. Seafloor terrain map of Jiaxie Guyots. The red and blue dashed boxes are ranges of Fig. 4 and Fig. 6, respectively.
Figure 2. Terrain factors. a. Slope; b. aspect; c. vector ruggedness measure (VRM); d. curvature; e. broad-scale bathymetric position index (B_BPI); f. fine-scale bathymetric position index (F_BPI). The contour line is elevation.
Figure 3. Result of seamount terrain units. a. First-order units; b. second-order units.
Figure 4. Multi-scale terrain analysis. a. First-order units (10 km); b. first-order units (6 km); c. second-order units (3 km).
Figure 5. Synthesis profile of guyots terrain. VRM: vector ruggedness measure; B_BPI: broad-scale bathymetric position index; F_BPI: fine-scale bathymetric position index.
Figure 6. Geological analysis of different terrain units on the guyots. a. Second-order units; b. drilling samples; c. snapshots of vedio obtained by ROV; d. synthesis profile of terrain factors. VRM: vector ruggedness measure; B_BPI: broad-scale bathymetric position index; F_BPI: fine-scale bathymetric position index.
Table 1. Terrain factors
Terrain factors Formulation Description Reference Slope $S = \arctan \sqrt { { {\left(\dfrac{ { {{\rm{d}} }z} }{ { { {{\rm{d}}} }x} }\right)}^2} + { {\left(\dfrac{ { { {{\rm{d}}} }z} }{ { { {{\rm{d}}} }y} }\right)}^2} }$ − Horn (1981) Aspect $A = 57.295\;78 \times \arctan 2\left(\dfrac{ { { {{\rm{d}}} }z} }{ { { {{\rm{d}}} }y} } + \dfrac{ { { {{\rm{d}}} }z} }{ { { {{\rm{d}}} }x} }\right)$
${A_{\rm{N}}} = \cos A,{A_{\rm{E}}} = \sin A$AN-North, AE-East. Zevenbergen and Thorne (1987) SAPA ${ {{\rm{SAPA}}} } = \dfrac{ { { {{\rm{Are}}{{\rm{a}}_{{\rm{surface}}} } } } } }{ { { {{\rm{Are}}{{\rm{a}}_{{\rm{planer}}} } } } } }$ Areasurface: terrain surface area; Areaplaner: terrain project-planer area Jenness (2004) VRM ${ {{\rm{VRM}}} } = 1 - \dfrac{ { { {{\rm{Abs}}} }({{r}})} }{{{n}}}$, ${ {{\rm{Abs}}} }(r) = \sqrt { { {\left( {\displaystyle\sum x } \right)}^2} + { {\left( {\displaystyle\sum y } \right)}^2} + { {\left( {\displaystyle\sum z } \right)}^2} }$
$xy = 1 \times \sin \alpha $, $ z = 1 \times \cos \alpha $, $ x = xy \times \sin \beta $, $ y = xy \times \cos \beta $
Sappington et al. (2007) BPI ${ { {\rm{BPI} }({\rm{Scale factor} })} } = { { { {\rm{int} } } } } { {({\rm{Depth} } - {\rm{Dept} }{ {\rm{h} }_{ {\rm{Focal\,mean} } } }({\rm{Circle} },{\rm{Rad} }) + 0.5) } }$
${\rm{BPI} }({\rm{Scale factor} }) = { {\rm{int} } } ({\rm{Depth} } - {\rm{Dept} }{ {\rm{h} }_{ {\rm{Focal\,mean} } } }({\rm{Annulus} },{\rm{IRad} },{\rm{ORad} }) + 0.5)$− Lundblad et al. (2006) Note: − represents no description; r represents the resultant vector; Annulus, Circle: the elevation differences between a focal point and the mean elevation of the surrounding cells within a user defined annulus, or circle; Rad: Radius; IRad: inner radius of annulus in cells; ORad: outer radius of annulus in cells. 
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Table 2. Parameters of seamount terrain classification
First-order terrain units ID First-order units B_BPI_bottom B_BPI_top F_BPI_bottom F_BPI_top Slope_bottom Slope_top Depth_bottom Depth_top 1 crest 100 − − − − − − − 2 depression − −100 − − − − − − 3 flat on summit −100 100 − − − 5 −2 000 − 4 flat on slope −100 100 − − − 5 − −2 000 5 slope −100 100 − − 5 − − − Second-order terrain units ID Second-order units B_BPI_bottom B_BPI_top F_BPI_bottom F_BPI_top Slope_bottom Slope_top Depth_bottom Depth_top 11 local depressions on crests 100 −100 12 local crests 100 − 100 − − − − − 13 broad crests 100 − −100 100 − − − − 21 local depressions − −100 − −100 − − − − 22 local protrusions
on depressions− −100 100 − − − − − 23 broad depressions − −100 −100 100 − − − − 31 flats on summit −100 100 − − − 5 −2 000 − 41 flats on bottom −100 100 − − − 5 − −2 000 51 local depressions on slope −100 100 − −100 5 − − − 52 gentle slopes −100 100 −100 100 5 − − − 53 local protrusions on slopes −100 100 100 − 5 − − − Note: − represents no data.
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