Remote Sensing (Sep 2018)

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

  • Hironori Arai,
  • Wataru Takeuchi,
  • Kei Oyoshi,
  • Lam Dao Nguyen,
  • Kazuyuki Inubushi

DOI
https://doi.org/10.3390/rs10091438
Journal volume & issue
Vol. 10, no. 9
p. 1438

Abstract

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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.

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