Estimation of Methaae Emission from Wetland with Sub-pixel Level Land Cover Characterization of Remotely Sensed Data

摘要

[ABSTRACT] Methane has high global warming potential and its increase may give a serious impact to our future climate and environment. Since wetland is one of the major emission sources of methane estimation of methane emission requires precise characterization of wetland conditions in global or continental scale. This study examined a remote sensing method to estimate methane emission from extensive wetland areas. A scaling method between high spatial resolution data (SPOT HRV) and coarse resolution but wide coverage data (NOAA AVHRR) was investigated to extrapolate local information on land cover mixture condition in wetland from HRV to more extensive area through AVHRR, and to estimate wetland coverage area more precisely. First, in SPOT data, land cover types of the area was classified into four categories including vegetation, water, and two types of bogs which are sources of methane, and next AVHRR image density was statistically regressed with category mixture ratio derived from HRV pixels in each AVHRR pixel. This scaling model from regression analysis provides wetland coverage ratio in sub-pixel level only from AVHRR data. The method was applied to western Siberian wetland, and total emission of methane was calculated by multiplying estimated bog areas with unit emission rate of methane in each bog types.