Indian Journal of Geo-Marine Sciences

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Comparing Performance of Inter-Sensor NDVI for the Detection of Floating Macroalgal Blooms in the Yellow Sea


Affiliations
1 Department of Agricultural Extension and Rural Development, EXIM Bank Agricultural University Bangladesh, Chapainawabganj – 6300, Bangladesh
2 Department of Aquatic Resource Management, Sylhet Agricultural University, Sylhet – 3100, Bangladesh
3 Department of Convergence Study on the Ocean Science and Technology, Ocean Science and Technology School, Korea Maritime and Ocean University, Busan – 49111, Korea, Democratic People's Republic of

There are many complains against macroalgal bloom (MAB) from all over the world for its high negative economic impacts. Early and precise detection of MAB occurance can reduce huge economic loss in tourism and marine business. Thus, this study aims to detect the MAB in the Yellow Sea (YS) by comparing performance of Normalized Difference Vegetation Index (NDVI) between Geostationary Ocean Color Imager (GOCI) and Landsat-8 sensors from 2014 to 2019. The largest MAB during this period was identified from Landsat-8 sensors along the coast of Sheyang and Qingdao of China in 2018. The locations of MABs were almost nearby areas during the begining phase of MABs in consecutive years. In successive years huge and dense MABs reached the brink of shoreline of Qingdao. In Landsat-8 images in most cases larger total areas of MABs were detected including very small pathches which could not be detected from GOCI due to low spatial resolution. The findings of this study will be helpful for scientists to choose between GOCI and Landsat-8 based on the objectives of their study.
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  • Comparing Performance of Inter-Sensor NDVI for the Detection of Floating Macroalgal Blooms in the Yellow Sea

Abstract Views: 167  | 

Authors

M. H. Sakib
Department of Agricultural Extension and Rural Development, EXIM Bank Agricultural University Bangladesh, Chapainawabganj – 6300, Bangladesh
A. H. A. Rashid
Department of Aquatic Resource Management, Sylhet Agricultural University, Sylhet – 3100, Bangladesh
C-S. Yang
Department of Convergence Study on the Ocean Science and Technology, Ocean Science and Technology School, Korea Maritime and Ocean University, Busan – 49111, Korea, Democratic People's Republic of

Abstract


There are many complains against macroalgal bloom (MAB) from all over the world for its high negative economic impacts. Early and precise detection of MAB occurance can reduce huge economic loss in tourism and marine business. Thus, this study aims to detect the MAB in the Yellow Sea (YS) by comparing performance of Normalized Difference Vegetation Index (NDVI) between Geostationary Ocean Color Imager (GOCI) and Landsat-8 sensors from 2014 to 2019. The largest MAB during this period was identified from Landsat-8 sensors along the coast of Sheyang and Qingdao of China in 2018. The locations of MABs were almost nearby areas during the begining phase of MABs in consecutive years. In successive years huge and dense MABs reached the brink of shoreline of Qingdao. In Landsat-8 images in most cases larger total areas of MABs were detected including very small pathches which could not be detected from GOCI due to low spatial resolution. The findings of this study will be helpful for scientists to choose between GOCI and Landsat-8 based on the objectives of their study.