ACCURACY OF UNSUPERVISED CLASSIFICATION TO DETERMINE CORAL HEALTH USING SPOT-6 AND SENTINEL-2A
Autor: | Teruhisa Komatsu, Supriadi, Mahatma Lanuru, I. Kartika, Nurjannah Nurdin, M. Akbar As |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
0106 biological sciences
lcsh:Applied optics. Photonics Ground truth lcsh:T 010604 marine biology & hydrobiology Coral k-means clustering Rubble lcsh:TA1501-1820 Image processing 010501 environmental sciences engineering.material 01 natural sciences lcsh:Technology Multispectral pattern recognition Waves and shallow water lcsh:TA1-2040 engineering Environmental science Satellite imagery lcsh:Engineering (General). Civil engineering (General) 0105 earth and related environmental sciences Remote sensing |
Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W16, Pp 503-509 (2019) |
ISSN: | 2194-9034 1682-1750 |
Popis: | Characteristics of corals spectral from different species are expected to have optically different characters. The aims of this research are to compare unsupervised classification between IsoData and K-Means methods with Lyzenga application, and to analyze the precision of SPOT-6 and Sentinel-2A satellite imagery in classsifying shallow water habitat. The image processing are atmosferic correction, cropping, masking, Depth Invariant Index, Unsupervised classification, ground truthing, reclassify, accuracy assessment, and shallow water habitat spectral reflectance analysis. Rubble and dead coral with algae were indicating as coral death due to either damaging human activity or natural death such as bleaching. The accuracy of unsupervised classification IsoData and K-Means method have the same accuracy 62.50%. The IsoData method is better detected live coral and algae. Rubble were dominant detected in K-Means method. |
Databáze: | OpenAIRE |
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