Estimation of Methane Emissions from Rice Paddies in the Mekong Delta Based on Land Surface Dynamics Characterization with Remote Sensing
Estimation of Methane Emissions from Rice Paddies in the Mekong Delta Based on Land Surface Dynamics Characterization with Remote Sensing
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DOI：
10.3390/rs10091438
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发表时间：
2018-09-01
期刊：
影响因子：
5
通讯作者：
Inubushi, Kazuyuki
中科院分区：
文献类型：
--
作者：
Arai, Hironori;Takeuchi, Wataru;Inubushi, Kazuyuki
在湄公河三角洲的水稻土中，土壤古菌释放出大量的甲烷。仅使用卫星可观测的解释变量再现地面通量数据是评估区域排放量的一种高度透明的方法。我们假设PALSAR-2（相控阵型L波段合成孔径雷达）可以区分淹没土壤和非淹没土壤，即使土壤被水稻植物覆盖。然后，我们验证了卫星观测变量（土壤淹没和种植日历）和分层贝叶斯模型的地面通量数据的再现性。此外，淹没/非淹没土壤进行了分类与PALSAR-2。模型参数成功地收敛使用哈密顿-蒙特卡罗方法。PALSAR-2地表水覆盖率与MODIS淹没指数的交叉验证（中分辨率成像光谱仪）和AMSR-2（Advanced Microwave Scanning Radiometer-2）数据表明，（1）即使在MODIS和AMSR-2淹没指数值（2）随着MODIS-NDWI和AMSR-2-NDFI的增加，PALSAR-2-LSWC低值的检出率降低。这些发现表明，即使MODIS和AMSR-2无法检测到水稻植物覆盖的淹没土壤，PALSAR-2也有潜力检测到水稻植物覆盖的淹没土壤，并显示了PALSAR-2-LSWC与其他两个非植被地区指数之间的相似性。
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.