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Distribution changes of seagrass beds area using sentinel-2A imagery in lancang island, seribu island, Indonesia
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Seagrass is a flowering plant (angiosperm) that inhabits shallow waters and plays a vital ecological role as a breeding ground, habitat, and food source for marine organisms. However, increasing human activities, including waste disposal, fishing, and coastal tourism, have contributed to the degradation of seagrass ecosystems. This study aims to map the spatial distribution and temporal changes of seagrass areas using Object-Based Image Analysis (OBIA) in the waters of Lancang Island, Seribu Islands, Indonesia. Image processing involved segmentation and multi-level classification (levels 1, 2, and 3) with optimal segmentation scales of 50, 10, and 1, respectively. The classification results identified three categories: non-seagrass, sparse seagrass, and dense seagrass. In 2016, seagrass covered 68.16 ha but declined to 42.37 ha by 2023, while non-seagrass areas expanded from 123.11 ha to 146.59 ha. Land-cover transitions revealed a conversion of 37.84 ha from seagrass to non-seagrass and 12.04 ha from non-seagrass to seagrass. Overall, seagrass experienced a net loss of 37.88 ha during the study period. The classification achieved an overall accuracy of 70%.
Title: Distribution changes of seagrass beds area using sentinel-2A imagery in lancang island, seribu island, Indonesia
Description:
Seagrass is a flowering plant (angiosperm) that inhabits shallow waters and plays a vital ecological role as a breeding ground, habitat, and food source for marine organisms.
However, increasing human activities, including waste disposal, fishing, and coastal tourism, have contributed to the degradation of seagrass ecosystems.
This study aims to map the spatial distribution and temporal changes of seagrass areas using Object-Based Image Analysis (OBIA) in the waters of Lancang Island, Seribu Islands, Indonesia.
Image processing involved segmentation and multi-level classification (levels 1, 2, and 3) with optimal segmentation scales of 50, 10, and 1, respectively.
The classification results identified three categories: non-seagrass, sparse seagrass, and dense seagrass.
In 2016, seagrass covered 68.
16 ha but declined to 42.
37 ha by 2023, while non-seagrass areas expanded from 123.
11 ha to 146.
59 ha.
Land-cover transitions revealed a conversion of 37.
84 ha from seagrass to non-seagrass and 12.
04 ha from non-seagrass to seagrass.
Overall, seagrass experienced a net loss of 37.
88 ha during the study period.
The classification achieved an overall accuracy of 70%.
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