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

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.

Monitoring and Mapping of Rice Cropping Pattern in Flooding Area in the Vietnamese Mekong Delta Using Sentinel-1A Data: A Case of An Giang Province

“…Some single-rice plots were misclassified as built-up or double-rice due to some of them not yet producing any cultivations or due to the vegetable-rice model application, respectively. Thus, the use of PALSAR-2 data can improve the accuracy as introduced by [56] to distinguish between the inundated rice fields and noninundated rice fields.…”

“…The author showed this approach has great potential for global production projections. Interestingly, Arai et al [56] predicted methane emissions based on remote sensing data and found that PALSAR-2 could distinguish inundated-rice field and noninundated rice field in Vietnam. It should be pointed out, moreover, that Bouvet et al [31], Nguyen et al [41], and Phan et al [45] used SAR sensors from COSMO-SkyMed X-band, Sentinel-1A, and ENVISAT/ASAR satellite images, respectively, for monitoring rice in the VMD.…”

A Data-Intensive Approach to Address Food Sustainability: Integrating Optic and Microwave Satellite Imagery for Developing Long-Term Global Cropping Intensity and Sowing Month from 2001 to 2015

“…Several potential applications of AMSR-E/2 LSWC that are effective for the monitoring of agricultural issues, especially the flooding sessions in rice paddy phenology, have been proposed [51]. AMSR-E/2 LSWC can also be applied to large-scale flooding detection [52].…”

Methane emissions in triple rice cropping: patterns and a method for reduction

“…The climate of tropical monsoon (Am) enables high productivity by triple rice cropping (cropping three times a year). Rice paddies are a methane emission source, and the Mekong Delta is a hotspot (Arai et al, 2018;Werner et al, 2016). However, this has not been well studied (Vo et al, 2018).…”