%0 Journal Article %1 dlr121618 %A Clauss, Kersten %A Ottinger, Marco %A Leinenkugel, Patrick %A Kuenzer, Claudia %D 2018 %I Elsevier %J International Journal of Applied Earth Observation and Geoinformation %K article kuenzer lsfe %N 73 %P 574-585 %R 10.1016/j.jag.2018.07.022 %T Estimating rice production in the Mekong Delta, Vietnam, utilizing time series of Sentinel-1 SAR data %U https://www.sciencedirect.com/science/article/pii/S0303243418303064 %V 2018 %X Rice is the most important food crop in Asia and rice exports can significantly contribute to a country's GDP. Vietnam is the third largest exporter and fifth largest producer of rice, the majority of which is grown in the Mekong Delta. The cultivation of rice plants is important, not only in the context of food security, but also contributes to greenhouse gas emissions, provides man-made wetlands as an ecosystem, sustains smallholders in Asia and influences water resource planning and run-off water management. Rice growth can be monitored with Synthetic Aperture Radar (SAR) time series due to the agronomic flooding followed by rapid biomass increase affecting the backscatter signal. With the advent of Sentinel-1 a wealth of free and open SAR data is available to monitor rice on regional or larger scales and limited data availability should not be an issue from 2015 onwards. We used Sentinel-1 SAR time series to estimate rice production in the Mekong Delta, Vietnam, for three rice seasons centered on the year 2015. Rice production for each growing season was estimated by first classifying paddy rice area using superpixel segmentation and a phenology based decision tree, followed by yield estimation using random forest regression models trained on in situ yield data collected by surveying 357 rice farms. The estimated rice production for the three rice growing seasons 2015 correlates well with data at the district level collected from the province statistics offices with R2s of 0.93 for the Winter--Spring, 0.86 for the Summer--Autumn and 0.87 for the Autumn--Winter season.

@article{dlr121618, abstract = {Rice is the most important food crop in Asia and rice exports can significantly contribute to a country's GDP. Vietnam is the third largest exporter and fifth largest producer of rice, the majority of which is grown in the Mekong Delta. The cultivation of rice plants is important, not only in the context of food security, but also contributes to greenhouse gas emissions, provides man-made wetlands as an ecosystem, sustains smallholders in Asia and influences water resource planning and run-off water management. Rice growth can be monitored with Synthetic Aperture Radar (SAR) time series due to the agronomic flooding followed by rapid biomass increase affecting the backscatter signal. With the advent of Sentinel-1 a wealth of free and open SAR data is available to monitor rice on regional or larger scales and limited data availability should not be an issue from 2015 onwards. We used Sentinel-1 SAR time series to estimate rice production in the Mekong Delta, Vietnam, for three rice seasons centered on the year 2015. Rice production for each growing season was estimated by first classifying paddy rice area using superpixel segmentation and a phenology based decision tree, followed by yield estimation using random forest regression models trained on in situ yield data collected by surveying 357 rice farms. The estimated rice production for the three rice growing seasons 2015 correlates well with data at the district level collected from the province statistics offices with R2s of 0.93 for the Winter{--}Spring, 0.86 for the Summer{--}Autumn and 0.87 for the Autumn{--}Winter season.}, added-at = {2023-03-22T12:13:18.000+0100}, author = {Clauss, Kersten and Ottinger, Marco and Leinenkugel, Patrick and Kuenzer, Claudia}, biburl = {https://www.bibsonomy.org/bibtex/28b909bbc64702ab1ec569c2246632984/earthobs_uniwue}, doi = {10.1016/j.jag.2018.07.022}, interhash = {0b915e855b4d926bf5c1750f29cad642}, intrahash = {8b909bbc64702ab1ec569c2246632984}, issn = {1569-8432}, journal = {International Journal of Applied Earth Observation and Geoinformation}, keywords = {article kuenzer lsfe}, language = {EN}, month = {Juli}, number = 73, pages = {574-585}, publisher = {Elsevier}, timestamp = {2023-03-22T12:13:18.000+0100}, title = {Estimating rice production in the Mekong Delta, Vietnam, utilizing time series of Sentinel-1 SAR data}, url = {https://www.sciencedirect.com/science/article/pii/S0303243418303064}, volume = 2018, year = 2018 }