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Large-Scale Assessment of Coastal Aquaculture Ponds with Sentinel-1 Time Series Data

Ottinger, Marco and Clauss, Kersten and Künzer, Claudia (2017) Large-Scale Assessment of Coastal Aquaculture Ponds with Sentinel-1 Time Series Data. Remote Sensing, 9 (440), pp. 1-23. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs9050440. ISSN 2072-4292.

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Official URL: http://www.mdpi.com/2072-4292/9/5/440


We present an earth observation based approach to detect aquaculture ponds in coastal areas with dense time series of high spatial resolution Sentinel-1 SAR data. Aquaculture is one of the fastest-growing animal food production sectors worldwide, contributes more than half of the total volume of aquatic foods in human consumption, and offers a great potential for global food security. The key advantages of SAR instruments for aquaculture mapping are their all-weather, day and night imaging capabilities which apply particularly to cloud-prone coastal regions. The different backscatter responses of the pond components (dikes and enclosed water surface) and aquaculture’s distinct rectangular structure allow for separation of aquaculture areas from other natural water bodies. We analyzed the large volume of free and open Sentinel-1 data to derive and map aquaculture pond objects for four study sites covering major river deltas in China and Vietnam. SAR image data were processed to obtain temporally smoothed time series. Terrain information derived from DEM data and accurate coastline data were utilized to identify and mask potential aquaculture areas. An open source segmentation algorithm supported the extraction of aquaculture ponds based on backscatter intensity, size and shape features. We were able to efficiently map aquaculture ponds in coastal areas with an overall accuracy of 0.83 for the four study sites. The approach presented is easily transferable in time and space, and thus holds the potential for continental and global mapping.

Item URL in elib:https://elib.dlr.de/112391/
Document Type:Article
Title:Large-Scale Assessment of Coastal Aquaculture Ponds with Sentinel-1 Time Series Data
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Ottinger, Marcomarco.ottinger (at) dlr.dehttps://orcid.org/0000-0002-7336-1283
Clauss, Kerstenkersten.clauss (at) dlr.deUNSPECIFIED
Künzer, Claudiaclaudia.kuenzer (at) dlr.deUNSPECIFIED
Date:4 May 2017
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Page Range:pp. 1-23
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Keywords:aquaculture, SAR, Sentinel-1, time series, image Segmentation, remote sensing, ponds coastal zone; river delta
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben Fernerkundung der Landoberfläche (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Ottinger, Marco
Deposited On:04 Jul 2017 11:21
Last Modified:14 Dec 2019 04:26

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