Assessment of Sentinel‐2A multispectral image for benthic habitat composition mapping. Issue 2 (1st February 2020)

• Record Type: Journal Article
• Authors: Wicaksono, Pramaditya; Fauzan, Muhammad Afif; Asta, Septian Galih Widhi
• Is Part Of: IET image processing. Volume 14:Issue 2(2020)
• Page Start: 279
• Page End: 288
• Publication Date: 2020-02-01
• Subjects: bathymetry -- image segmentation -- remote sensing -- image sensors -- geophysical image processing -- image classification -- oceanographic techniques -- geophysical signal processing; ALOS AVNIR‐2 -- aerial image -- custom‐made unmanned aerial vehicle -- individual benthic class -- benthic habitat class spatial distribution -- image segmentation -- classification tree analysis -- nonconstructed class covers carbonate sand -- Sentinel‐2A -- benthic habitat spatial distribution mapping -- multispectral image -- benthic habitat composition mapping; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2018.6044
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Sentinel‐2A accuracy for benthic habitat composition mapping was tested and compared to ALOS AVNIR‐2. Aerial image acquired using custom‐made unmanned aerial vehicle was used to train and validate the model. The mapping was conducted regardless of the benthic class and at individual benthic class. Benthic habitat class spatial distribution was obtained using the combination of image segmentation and classification tree analysis. The aerial image was interpreted based on the percentage of the constructed and non‐constructed classes. The constructed class includes coral reefs, dead coral, seagrass, and macroalgae, while non‐constructed class covers carbonate sand, rock, and rubble. Sentinel‐2A produced higher accuracy (92%) than ALOS AVNIR‐2 (78%) for benthic habitat spatial distribution mapping. However, in the empirical modelling of benthic habitat composition, ALOS AVNIR‐2 (SE 23–24%) produced slightly better accuracy than Sentinel‐2A (SE 23–27%). Several factors affected the low accuracy, which include the sub‐pixel mixing of benthic habitat and constructed class, the delay between dates of acquisition, and radiometric quality of the images. Since the fundamental relationship between reflectance value and the percentage of the constructed class has been justified and consistent, given more experiments it has the potential to predict benthic habitat composition with higher accuracy in the future.