Using Time-series Airborne Multispectral Imagery to Characterize Grassland Cover and Land Management Practices Influencing Soil Carbon Stocks

Land use practices greatly influence soil carbon stocks, which in turn influences the potential for soils to store carbon. With a growing interest in the use of a carbon credit system to decrease atmospheric carbon dioxide, there is increasing interest in development of cost effective methods for identifying land cover types and land use practices that maximize carbon storage potential. This study focuses on the use of remotely sensed data for characterizing Central Great Plains grassland land types and their management practices. During this study, near-biweekly multispectral submeter resolution imagery was collected throughout two growing seasons over 30 grassland study sites. These measurements were related to field data collected within five grassland management types including cool-season (C3) hayed, C3 grazed, warm-season (C4) hayed, C4 grazed, and USDA Conservation Reserve Program (CRP) lands. Field variables measured included: green Leaf Area Index and Fraction of Intercepted PAR, live and senescent plant cover, and topsoil carbon. Our findings show significant differences in topsoil carbon and bulk density levels among management categories, with grazed fields exhibiting generally higher levels of both carbon and bulk density compared to hayed fields. The airborne multitemporal datasets showed optimal data collection periods, which varied considerably from conventional wisdom on this matter. Our findings show remotely sensed measurements useful for discriminating among management practices influencing grassland soil carbon stocks. We also examined the relationship between our high-resolution airborne imagery and Landsat Thematic Mapper data and found them to be highly correlated, suggesting that our finding can be scaled up to the regional scale.