KARAKTERISASI SPEKTRAL KONDISI PADANG LAMUN MENGGUNAKAN CITRA LANDSAT 8 OLI

Abstract

The high level of human activity in coastal areas has had an impact on seagrass beds. The advancement of satellite imaging technology makes monitoring seaweed conditions even easier. The purpose of this study was to identify the spectral reflectance patterns of different seagrass cover levels and make it the basis for mapping the seagrass condition on Barranglompo Island. Based on google earth has been determined 4 sampling stations that represent the spread of seagrass on Barranglompo Island. Each station is divided into 4 sub-stations from land to sea. Sampling of seagrass cover was carried out by the McKenzie (2003) method modified by close sampling, to 30 x 30 square meters following the spatial resolution of Landsat image 8. Each observation point was estimated the percentage of seagrass cover and the dominant species. Digital seagrass pixel extraction is performed from band 1 to 7 landsat 8 according to point position in the field and then grouped by cover class and condition. Seagrasses found in Barranglampo Island are 8 species: Enhalus acoroides, Thalassia hemprichii, Halophila ovalis, Cymodocea rotundata, Cymodocea serulata, Halodule uninervis, Halodule pinifolia and Syringodium isoetifolium. In general, Enhalus acoroides and Thalassia hemprichii have higher closure than other seagrass species. The spectral reflection of seagrass landscape imagery 8 OLI channel 1 - 7 is good enough to show the seagrass condition in bad category, good enough, and good. Spectral reflection of the seagrass has a peak on the green channel. The worse the seagrass condition the higher the spectral reflection. Seagrass with bad conditions has a low cover so that other substrates such as sand will contribute to the spectral value recorded by satellite sensors. This result will facilitate mapping of seagrass condition on small islands by using Landsat 8 OLI image.

Keywords: seagrass condition, spectral reflection, landsat 8, South Sulawesi