Skip to main content
placeholder image

Discriminating seagrass density from satellite imagery using pixel and object based classification method on Small Island, Spermonde Archipelago-Indonesia

Conference Paper


Abstract


  • Remote sensing technology provides a reliable means of creating an inventory of coastal natural resources to assit with their management. The purpose of this study was to discriminate seagrass density using medium and high resolution satellite imagery. The field survey was conducted on Bahuluang island, Spermonde archipelago.Imageryof Sentinel-2a as medium resolution (10 m) and SPOT-6 as hight resolution (1.5 m) were used to discriminate the seagrass. Both pixel-based (k-Means). Object-based classification was used as an approach of Nearest Neighbor (KKN) methods using segmentation method before doing classification, and in this methode used parameters that must be determined in example based feature extraction workflow using Edge scale level dan full lamda scale level algorithm, namely parameters of spectral, texture, and spatial. Pixel-based classification methods provideds better over all accuracy than object-based classification and can be used for seagrass mapping in the Spermonde Archipelago. However, it is necessary to conduct a more detail assessments at different water depths.

Publication Date


  • 2018

Citation


  • Thalib, M. S., Nurdin, N., Hamylton, S., & Munawar, S. A. (2018). Discriminating seagrass density from satellite imagery using pixel and object based classification method on Small Island, Spermonde Archipelago-Indonesia. In Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018 Vol. 1 (pp. 377-389).

Scopus Eid


  • 2-s2.0-85071848767

Web Of Science Accession Number


Start Page


  • 377

End Page


  • 389

Volume


  • 1

Abstract


  • Remote sensing technology provides a reliable means of creating an inventory of coastal natural resources to assit with their management. The purpose of this study was to discriminate seagrass density using medium and high resolution satellite imagery. The field survey was conducted on Bahuluang island, Spermonde archipelago.Imageryof Sentinel-2a as medium resolution (10 m) and SPOT-6 as hight resolution (1.5 m) were used to discriminate the seagrass. Both pixel-based (k-Means). Object-based classification was used as an approach of Nearest Neighbor (KKN) methods using segmentation method before doing classification, and in this methode used parameters that must be determined in example based feature extraction workflow using Edge scale level dan full lamda scale level algorithm, namely parameters of spectral, texture, and spatial. Pixel-based classification methods provideds better over all accuracy than object-based classification and can be used for seagrass mapping in the Spermonde Archipelago. However, it is necessary to conduct a more detail assessments at different water depths.

Publication Date


  • 2018

Citation


  • Thalib, M. S., Nurdin, N., Hamylton, S., & Munawar, S. A. (2018). Discriminating seagrass density from satellite imagery using pixel and object based classification method on Small Island, Spermonde Archipelago-Indonesia. In Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018 Vol. 1 (pp. 377-389).

Scopus Eid


  • 2-s2.0-85071848767

Web Of Science Accession Number


Start Page


  • 377

End Page


  • 389

Volume


  • 1