Examining the relationships between land cover and greenhouse gas concentrations using remote-sensing data in East Asia

Abstract

Measurements of land-cover changes suggest that such shifts may alter atmospheric concentrations of greenhouse gases (GHGs). However, owing to the lack of large-scale GHG data, a quantitative description of the relationships between land-cover changes and GHG concentrations does not exist on a regional scale. The Greenhouse Gases Observing Satellite (GOSAT) launched by Japan on 23 January 2009 can be of use in investigating this issue. In this study, we first calculated the monthly average GHG concentrations in East Asia from April 2009 to October 2011 and found that CO₂ concentration displays a seasonal cycle, but that the CH₄ seasonal trend is unclear. To understand the relationship between land cover and GHG concentrations, we used GHG data from GOSAT, normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and land-cover data from EAS-GlobCover (2009) to analyse the correlation coefficients between land cover and GHG concentrations. We observed that vegetation may generally be considered as a source of, but not a sink for, CO₂ and CH₄, either on a yearly scale or during the growing season. With respect to the relationships between land-cover types and GHG concentrations, we conclude that on a yearly scale, land-cover types are not closely correlated with GHG concentrations. During the growing season, croplands and scrublands are negatively correlated with XCO₂ (the ratio of the total number of CO₂ molecules to that of dry air molecules), and forest, grasslands and bare areas are positively correlated with XCO₂. Forest and croplands can be viewed as CH₄ sources, while scrublands and grasslands can be thought of as CH₄ sinks.

Acknowledgements

This study was supported by Scientific Research (B), 23405005 (PI: Associate Prof. Xiufeng Wang, Hokkaido University, Japan) and the National Natural Science Foundation of China (41201159, study on the effect mechanism of commercial centre pattern on traffic carbon emissions in Shenyang city. PI: Assistant Researcher Jing Li, Chinese Academy of Sciences, China). We also thank the GOSAT project of Japan, NASA and ESA for providing data that were used in this study.