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Spatio-Temporal Patterns of Coastal Aquaculture Derived from Sentinel-1 Time Series Data and the Full Landsat Archive

Stiller, Dorothee and Ottinger, Marco and Leinenkugel, Patrick (2019) Spatio-Temporal Patterns of Coastal Aquaculture Derived from Sentinel-1 Time Series Data and the Full Landsat Archive. Remote Sensing, 11, pp. 1-18. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs11141707 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/11/14/1707/pdf

Abstract

Asia is the major contributor to global aquaculture production in quantity, accounting for almost 90%. These practices lead to extensive land-use and land-cover changes in coastal areas, and thus harm valuable and sensitive coastal ecosystems. Remote sensing and GIS technologies contribute to the mapping and monitoring of changes in aquaculture, providing essential information for coastal management applications. This study aims to investigate aquaculture expansion and spatio-temporal dynamics in two Chinese river deltas over three decades: the Yellow River Delta (YRD) and the Pearl River Delta (PRD). Long-term patterns of aquaculture change are extracted based on combining a reference layer on existing aquaculture ponds for 2015 derived from Sentinel-1 data with annual information on water bodies extracted from the long-term Landsat archive. Furthermore, the suitability of the proposed approach to be applied on a global scale is tested based on exploiting the Global Surface Water (GSW) dataset. We found enormous increases in aquaculture area for the investigated target deltas: an 18.6-fold increase for the YRD (1984–2016), and a 4.1-fold increase for the PRD (1990–2016). Furthermore, we detect hotspots of aquaculture expansion based on linear regression analyses for the deltas, indicating that hotspots are located in coastal regions for the YRD and along the Pearl River in the PRD. A comparison with high-resolution Google Earth data demonstrates that the proposed approach can detect spatio-temporal changes of aquaculture at an overall accuracy of 89%. The presented approach has the potential to be applied to larger spatial scales covering a time period of more than three decades. This is crucial to define appropriate management strategies to reduce the environmental impacts of aquaculture expansion, which are expected to increase in the future.

Item URL in elib:https://elib.dlr.de/128487/
Document Type:Article
Title:Spatio-Temporal Patterns of Coastal Aquaculture Derived from Sentinel-1 Time Series Data and the Full Landsat Archive
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Stiller, DorotheeDorothee.Stiller (at) dlr.dehttps://orcid.org/0000-0002-8681-6144
Ottinger, MarcoMarco.Ottinger (at) dlr.dehttps://orcid.org/0000-0002-7336-1283
Leinenkugel, PatrickPatrick.Leinenkugel (at) dlr.dehttps://orcid.org/0000-0001-5571-800X
Date:18 July 2019
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:No
Volume:11
DOI :10.3390/rs11141707
Page Range:pp. 1-18
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:aquaculture; food security; Landsat; Sentinel-1; temporal analysis; river delta; coastal region; China; Asia
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Stiller, Dorothee
Deposited On:05 Aug 2019 10:24
Last Modified:21 Nov 2019 05:05

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