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Remote Sens. 2018, 10(9), 1438; https://doi.org/10.3390/rs10091438

Estimation of Methane Emissions from Rice Paddies in the Mekong Delta Based on Land Surface Dynamics Characterization with Remote Sensing

1
Institute of Industrial Science, The University of Tokyo, Meguro, Tokyo 153-8505, Japan
2
Japan Society for the Promotion of Science, Chiyoda, Tokyo 102-0083, Japan
3
Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, Ibaraki 305-8505, Japan
4
Ho Chi Minh City Space Technology Application Center, Vietnam National Space Center, Vietnam Academy of Science and Technology, 268A Nam Ky Khoi Nghia Street, District 3, Ho Chi Minh City 700000, Vietnam
5
Graduate School of Horticulture, Chiba University, Matsudo, Chiba 271-8510, Japan
*
Author to whom correspondence should be addressed.
Received: 19 August 2018 / Revised: 1 September 2018 / Accepted: 4 September 2018 / Published: 9 September 2018
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Abstract

In paddy soils in the Mekong Delta, soil archaea emit substantial amounts of methane. Reproducing ground flux data using only satellite-observable explanatory variables is a highly transparent method for evaluating regional emissions. We hypothesized that PALSAR-2 (Phased Array type L-band Synthetic Aperture RADAR) can distinguish inundated soil from noninundated soil even if the soil is covered by rice plants. Then, we verified the reproducibility of the ground flux data with satellite-observable variables (soil inundation and cropping calendar) and with hierarchical Bayesian models. Furthermore, inundated/noninundated soils were classified with PALSAR-2. The model parameters were successfully converged using the Hamiltonian–Monte Carlo method. The cross-validation of PALSAR-2 land surface water coverage (LSWC) with several inundation indices of MODIS (Moderate Resolution Imaging Spectroradiometer) and AMSR-2 (Advanced Microwave Scanning Radiometer-2) data showed that (1) high PALSAR-2-LSWC values were detected even when MODIS and AMSR-2 inundation index values (MODIS-NDWI and AMSR-2-NDFI) were low and (2) low values of PALSAR-2-LSWC tended to be less frequently detected as the MODIS-NDWI and AMSR-2-NDFI increased. These findings indicate the potential of PALSAR-2 to detect inundated soils covered by rice plants even when MODIS and AMSR-2 cannot, and show the similarity between PALSAR-2-LSWC and the other two indices for nonvegetated areas. View Full-Text
Keywords: methane; rice paddies; greenhouse gas; ALOS-2/PALSAR-2; L-band synthetic aperture RADAR; inundation; phenology; Mekong Delta methane; rice paddies; greenhouse gas; ALOS-2/PALSAR-2; L-band synthetic aperture RADAR; inundation; phenology; Mekong Delta
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Arai, H.; Takeuchi, W.; Oyoshi, K.; Nguyen, L.D.; Inubushi, K. Estimation of Methane Emissions from Rice Paddies in the Mekong Delta Based on Land Surface Dynamics Characterization with Remote Sensing. Remote Sens. 2018, 10, 1438.

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