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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 und Ottinger, Marco und Leinenkugel, Patrick und 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, 2018-04-08 - 2018-04-13, Vienna, Austria.

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

Kurzfassung

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.

elib-URL des Eintrags:https://elib.dlr.de/119830/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel: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.
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Clauss, KerstenKersten.Clauss (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Ottinger, MarcoMarco.Ottinger (at) dlr.dehttps://orcid.org/0000-0002-7336-1283NICHT SPEZIFIZIERT
Leinenkugel, Patrickpatrick.leinenkugel (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Künzer, ClaudiaClaudia.Kuenzer (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:10 April 2018
Referierte Publikation:Nein
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Seitenbereich:Seite 1
Verlag:European Geosciences Union
Name der Reihe:Geophysical Research Abstracts
Status:veröffentlicht
Stichwörter:rice, aquaculture, food security, time series, SAR, Sentinel
Veranstaltungstitel:EGU General Assembly 2018
Veranstaltungsort:Vienna, Austria
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:8 April 2018
Veranstaltungsende:13 April 2018
Veranstalter :European Geosciences Union
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Fernerkundung u. Geoforschung
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Landoberfläche
Hinterlegt von: Clauss, Kersten
Hinterlegt am:09 Mai 2018 11:22
Letzte Änderung:24 Apr 2024 20:24

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