Relationship Between Manganese Nodule Abundance and Geologici/Topographic Factors of the Southern KODOS Area in the Northeastern Equatorial Pacific Using GIS and Probability Method

The aims of this study are to construct database using geostatistics and Geographic Information System (GIS), and to derive the spatial relationships between manganese nodule abundance and each factor affecting nodule abundance, such as metal grade, slope, aspect, water depth, topography, and acoust...

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Veröffentlicht in:Ocean and polar research 2004, Vol.26 (2), p.219-230
Hauptverfasser: Ko, Young-Tak, Min, Kyung-Duck, Park, Cheong-Kee, Kang, Jung-Keuk, Kim, Ki-Hyune, Lee, Tae-Gook, Kim, Hyun-Sub
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container_end_page 230
container_issue 2
container_start_page 219
container_title Ocean and polar research
container_volume 26
creator Ko, Young-Tak
Min, Kyung-Duck
Park, Cheong-Kee
Kang, Jung-Keuk
Kim, Ki-Hyune
Lee, Tae-Gook
Kim, Hyun-Sub
description The aims of this study are to construct database using geostatistics and Geographic Information System (GIS), and to derive the spatial relationships between manganese nodule abundance and each factor affecting nodule abundance, such as metal grade, slope, aspect, water depth, topography, and acoustic characteristics of the subbottom using the GIS and probability methods. The greater is the copper and nickel grade, the higher is the rating. The distribution pattern of nickel grade is similar to that of copper grade. The slopes are generally less than $3^{\circ}$, excluding seamounts and cliff areas. There is no increment in the rating with increasing slope. The rating is highest for slopes between 2.5 and $3.5^{\circ}$ in block B2 and between 3 and $6^{\circ}$ in block C1. The topography is classified into five groups: seamount, hill crest, hill slant, hill base or plain, and seafloor basin or valley. The ratings prove lowest for seamount and hill crest. The results of the study show a decrease in the rating with an increase in water depth in the study area. There was a poor relationship between manganese nodule abundance and the thickness of the upper transparent layer in block C1. Using GIS, it is possible to analyze a large amount of data efficiently, and to maximize the practical application, to increase specialization, and to enhance the accuracy of the analyses.
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The greater is the copper and nickel grade, the higher is the rating. The distribution pattern of nickel grade is similar to that of copper grade. The slopes are generally less than $3^{\circ}$, excluding seamounts and cliff areas. There is no increment in the rating with increasing slope. The rating is highest for slopes between 2.5 and $3.5^{\circ}$ in block B2 and between 3 and $6^{\circ}$ in block C1. The topography is classified into five groups: seamount, hill crest, hill slant, hill base or plain, and seafloor basin or valley. The ratings prove lowest for seamount and hill crest. The results of the study show a decrease in the rating with an increase in water depth in the study area. There was a poor relationship between manganese nodule abundance and the thickness of the upper transparent layer in block C1. 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The greater is the copper and nickel grade, the higher is the rating. The distribution pattern of nickel grade is similar to that of copper grade. The slopes are generally less than $3^{\circ}$, excluding seamounts and cliff areas. There is no increment in the rating with increasing slope. The rating is highest for slopes between 2.5 and $3.5^{\circ}$ in block B2 and between 3 and $6^{\circ}$ in block C1. The topography is classified into five groups: seamount, hill crest, hill slant, hill base or plain, and seafloor basin or valley. The ratings prove lowest for seamount and hill crest. The results of the study show a decrease in the rating with an increase in water depth in the study area. There was a poor relationship between manganese nodule abundance and the thickness of the upper transparent layer in block C1. 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title Relationship Between Manganese Nodule Abundance and Geologici/Topographic Factors of the Southern KODOS Area in the Northeastern Equatorial Pacific Using GIS and Probability Method
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