The use of sentinel 2A imageries to improve mangrove inventarization at coremap CTI monitoring areas
In 2014, the project preparation for Coral Reef Management (Coremap) CTI claim that mangrove at Selayar was approximately 676.7 hectares distributed at 15 villages. Tambolongan at Bontosikuyu district was the largest area of about 132 hectares. These values extracted using Landsat imageries based on...
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Published in | IOP conference series. Earth and environmental science Vol. 564; no. 1; pp. 12065 - 12074 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Bristol
IOP Publishing
01.09.2020
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Subjects | |
Online Access | Get full text |
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Summary: | In 2014, the project preparation for Coral Reef Management (Coremap) CTI claim that mangrove at Selayar was approximately 676.7 hectares distributed at 15 villages. Tambolongan at Bontosikuyu district was the largest area of about 132 hectares. These values extracted using Landsat imageries based on visual and composite image classification. Since Sentinel 2A launched in 2015, the use of this satellite imagery has spread widely in ecosystem monitoring due to its higher spatial, spectral and temporal resolution and mostly because it is free to access. Nevertheless, field sampling is still needed to crosscheck the final result. Since 2015 three mangrove locations at Selayar island monitored annually. By 2018, two new locations at Pasi island added. In 2019 three sites added at two different islands, so now a total nine mangrove station covering the whole Selayar islands. Nine species of mangroves were found by the end of 2019 monitoring, which are Avicennia alba, A. officinalis, A. marina, Bruguiera gymnorrhiza, Rhizophora apiculata, R. mucronata, R. stylosa, Cerios tagal, and Sonneratia alba. Spectral image characterization by using 12 bands of Sentinel 2A shows that most of these mangroves had peak reflectances at 783 and 865 nanometer, and the highest reflectance are lower than 0.45. These findings may contribute to better spatial identifications for mangrove monitoring and also the consequences to the revision of previous information extracted from Landsat imageries. |
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ISSN: | 1755-1307 1755-1315 |
DOI: | 10.1088/1755-1315/564/1/012065 |