摘要：Normal 0 false false false MicrosoftInternetExplorer4 st1\:*{behavior:url(#ieooui) } /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} Management of seagrass ecosystem requires availability of information on the actual condition of seagrass coverage. Remote sensing technology for seagrass mapping has been used to detect the presence of seagrass coverage, but so far no information on the condition of seagrass could be obtained. Therefore, a research is required using remote sensing imagery to obtain information on the condition of seagrass coverage. The aim of this research is to formulate mathematical relationship between seagrass coverage and depth invariant indices on Quickbird imagery. Transformation was done on multispectral bands which could detect sea floor objects that are in the region of blue, green and red bands. The study areas covered are the seas around Barranglompo Island and Barrangcaddi Island, westward of Makassar city, Indonesia. Various seagrass coverages were detected within the region under study. Mathematical relationship between seagrass coverage and depth invariant indices was obtained by multiple linear regression method. Percentage of s eagrass coverage (C) was obtained by transformation of depth invariant indices (Xij) on Quickbird imagery, with transformation equation as follows: C = 19.934 – 63.347 X 12 + 23.239 X 23 . A good accuracy of 75% for the seagrass coverage was obtained by transformation of depth invariant indices (Xij) on Quickbird imagery. Keywords: seagrass coverage, depth invariant index
Loading...
