Estimation of seagrass coverage by depth invariant indices on Quickbird imagery

12Citations
Citations of this article
58Readers
Mendeley users who have this article in their library.

Abstract

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 seagrass coverage (C) was obtained by transformation of depth invariant indices (Xij) on Quickbird imagery, with transformation equation as follows: C = 19.934 - 63.347 X12 + 23.239 X23. A good accuracy of 75% for the seagrass coverage was obtained by transformation of depth invariant indices (Xij) on Quickbird imagery.

Cite

CITATION STYLE

APA

Amran, M. A. (2010). Estimation of seagrass coverage by depth invariant indices on Quickbird imagery. Biotropia, 17(1), 42–50. https://doi.org/10.11598/btb.2010.17.1.43

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free