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Land Cover / Land Use Mapping in the Mekong Delta, Vietnam, with focus on pond aquaculture and paddy rice utilizing time series of Copernicus Sentinel data.

Clauss, Kersten and Ottinger, Marco and Leinenkugel, Patrick and Künzer, Claudia (2018) Land Cover / Land Use Mapping in the Mekong Delta, Vietnam, with focus on pond aquaculture and paddy rice utilizing time series of Copernicus Sentinel data. European Geosciences Union. EGU General Assembly 2018, 8-13 Apr 2018, Vienna, Austria.

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Official URL: https://meetingorganizer.copernicus.org/EGU2018/EGU2018-7929-1.pdf

Abstract

Paddy rice and pond aquaculture are important for Vietnam’s food security and contribute significantly to the GDP through exports. Knowledge about the production of rice and aquatic goods is significant in the contexts of food security, water management, trade policy, greenhouse gas emissions and hydrological modelling. Aquaculture ponds and paddy fields in Asia are often located in vulnerable regions, such as costal lowlands and river deltas, which are susceptible to sea level rise, floods and droughts, salt water intrusion and other hazards while at the same time battling issues of urban encroachment, stagnating yields and increased demand due to population growth. The Sentinel-1 satellites are the first constellation that offers a free and open data archive of high spatial and temporal resolution SAR data with a global coverage. This vast amount of data is particularly suited for time series analysis and holds great potential for future land use/land cover (LU/LC) change assessments. We present two studies showing the potential of Sentinel-1 for pond aquaculture and rice mapping. The study area for all studies was the complete Mekong Delta, Vietnam. Pond aquaculture was mapped by using Sentinel-1 time series, water thresholding, open-source segmentation algorithms and the derivation of shape parameters to differentiate aquaculture ponds from other water bodies. For the paddy rice mapping study we used a superpixel segmentation algorithm to create Sentinel-1 time series at the object level, instead of the pixel level, and derived rice area as well as seasonality by means of a straight forward decision tree algorithm. To manage the large data volume we devised workflows that incorporated cloud computing via Google Earth Engine for data processing. All products have been calculated at 10m spatial resolution.

Item URL in elib:https://elib.dlr.de/119830/
Document Type:Conference or Workshop Item (Speech)
Title:Land Cover / Land Use Mapping in the Mekong Delta, Vietnam, with focus on pond aquaculture and paddy rice utilizing time series of Copernicus Sentinel data.
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Clauss, KerstenKersten.Clauss (at) dlr.deUNSPECIFIED
Ottinger, MarcoMarco.Ottinger (at) dlr.deUNSPECIFIED
Leinenkugel, Patrickpatrick.leinenkugel (at) dlr.deUNSPECIFIED
Künzer, ClaudiaClaudia.Kuenzer (at) dlr.deUNSPECIFIED
Date:10 April 2018
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:p. 1
Publisher:European Geosciences Union
Series Name:Geophysical Research Abstracts
Status:Published
Keywords:rice, aquaculture, food security, time series, SAR, Sentinel
Event Title:EGU General Assembly 2018
Event Location:Vienna, Austria
Event Type:international Conference
Event Dates:8-13 Apr 2018
Organizer:European Geosciences Union
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 > Land Surface
Deposited By: Clauss, Kersten
Deposited On:09 May 2018 11:22
Last Modified:31 Jul 2019 20:17

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