Performance evaluation of OCO-2 XCO2 signatures in exploring casual relationship between CO2 emission and land cover

Continental scale monitoring is the primary satellite remote sensing method in previous studies for carbon emission patterns in relation to land cover. OCO-2 satellite is the most advanced CO2 monitoring satellite with high spatial resolution. This paper investigated performance of OCO-2 XCO2 signature in exploring causal relationship between land cover and carbon emissions. The land cover types (croplands, permanent wetlands, urban and built-up) influenced by development activities generally show higher XCO2 mean concentrations than non-anthropogenic land cover types. Evergreen broadleaf forest shows lowest local R2 while highest local R2 is generated from croplands. The adjusted R2s (the explanation power of geographically weighted regression, GWR model) were statistically significant on every land cover type. This research output could be used as a valuable reference that improved spatial resolution of OCO-2 could explain co-relationship between local CO2 flux and land cover for specific region within a country.

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