Seafloor mapping based on multibeam echosounder bathymetry and backscatter data using Object-Based Image Analysis: a case study from the Rewal site, the Southern Baltic

Janowski, Łukasz; Tęgowski, Jarosław; Nowak, Jarosław

Seafloor mapping based on multibeam echosounder bathymetry and backscatter data using Object-Based Image Analysis: a case study from the Rewal site, the Southern Baltic

Oceanological and Hydrobiological Studies

Volume 47 (2018): Issue 3 (September 2018)

By:

Łukasz Janowski, Jarosław Tęgowski and Jarosław Nowak

Open Access

|Sep 2018

Figures & Tables

Location of the Rewal study site within the Polish EEZ. Sources: our study, OpenStreetMap, European Environment Agency

Distribution of the mean backscatter intensity in four ground-truth classes. Sources: our study

A) result of bathymetric processing; B) result of backscatter processing and location of ground-truth samples, division into training and validation ground-truth samples; C) result of rugosity extracted as a secondary derivative of bathymetry; D) result of CART classification based on Object-Based Image Analysis. Sources: our study

Error matrix of the CART classification based on the OBIA technique_ MS – Muddy Sand, C – Clay, FS – Fine Sand, VFS – Very Fine Sand_ Sources: our study

	Refererce Class
User	MS	C	FS	VFS	Sum
MS	2	0	0	1	3
C	0	0	0	0	0
FS	0	0	2	0	2
VFS	0	0	0	3	3
Sum	2	0	2	4
Producer	1	undefined	1	0.75
User	0.666667	undefined	1	1
Overall Accuracy	0.875
KIA	0.809524

List of all ground-truth samples with their descriptions and locations_ Sources: our study

ID	Sediment type	Class	Type	Latitude	Longitude
VR 201	Very Fine Sand	VFS	training	54.105263	14.911653
VR 202	Fine Sand	FS	training	54.108030	14.911664
VR 203	Muddy Sand	MS	training	54.120947	14.911780
VR 204	Muddy Sand	MS	validation	54.127028	14.911643
VR 205	Very Fine Sand	VFS	training	54.111783	14.926790
VR 206	Very Fine Sand	VFS	training	54.114840	14.926752
VR 207	Fine Sand	FS	training	54.126588	14.926762
VR 208	Very Fine Sand	VFS	validation	54.120305	14.942225
VR 209	Fine Sand	FS	validation	54.110749	14.942321
VR 210	Very Fine Sand	VFS	validation	54.106412	14.972621
VR 211	Very Fine Sand	VFS	validation	54.122082	14.972553
VR 212	Muddy Sand	MS	validation	54.130222	14.972554
VR 214	Fine Sand	FS	validation	54.116665	14.987440
VR 215	Very Fine Sand	VFS	training	54.111829	14.987819
VR 216	Very Fine Sand	VFS	validation	54.109825	14.987764
VR 225	Muddy Sand	MS	training	54.125345	14.896156
VR 226	Very Fine Sand	VFS	training	54.118745	14.896162
VR 227	Clay	C	training	54.109162	14.896139
VR 228	Muddy Sand	MS	training	54.106042	14.896208

DOI: https://doi.org/10.1515/ohs-2018-0024 | Journal eISSN: 1897-3191 | Journal ISSN: 1730-413X

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Language: English

Page range: 248 - 259

Submitted on: Oct 4, 2017

Accepted on: Jan 16, 2018

Published on: Sep 21, 2018

Published by: University of Gdańsk

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

habitat mapping,

multibeam echosounder,

image processing,

Object-Based Image Analysis,

Classification and Regression Trees,

Related subjects:

© 2018 Łukasz Janowski, Jarosław Tęgowski, Jarosław Nowak, published by University of Gdańsk
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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Seafloor mapping based on multibeam echosounder bathymetry and backscatter data using Object-Based Image Analysis: a case study from the Rewal site, the Southern Baltic

Figures & Tables

Figure 1

Figure 2

Figure 3

Figure 4

Error matrix of the CART classification based on the OBIA technique_ MS – Muddy Sand, C – Clay, FS – Fine Sand, VFS – Very Fine Sand_ Sources: our study

List of all ground-truth samples with their descriptions and locations_ Sources: our study

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