Location: Hydrology and Remote Sensing Laboratory
Title: Agricultural greenhouse gas flux determination via remote sensing and modeling Authors
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: August 31, 2011
Publication Date: August 25, 2011
Citation: Serbin, G., Hunt Jr, E.R., Brown, D.J., Izaurralde, R.C., Paustain, K.H., West, T.O., Shumaker, B.L., Rice, C.W., Green, R.O. 2011. Agricultural greenhouse gas flux determination via remote sensing and modeling [abstract]. ASA Annual Meetings. http://hypspiri.jpl.nasa.gov/downloads/2011_workshop/day3/. Technical Abstract: Serious concerns have been raised about increasing levels of atmospheric greenhouse gases (GHGs) and associated climate change. For every degree in global temperature increase, grain production yields are expected to decrease 10%, while the global human population continues to increase by roughly 80 million per year. These increasing temperatures and GHGs, coupled with increasing food demand, present significant environmental, economic, and political challenges in the years to come. Of these GHGs, carbon (C) is of the most concern as it is released through the combustion of fossil fuels and released from agricultural soils by conventional agricultural management practices. Soils represent the largest C stock globally and also hold the potential to sequester large quantities of atmospheric C through use of modern tillage techniques that preserve large quantities of crop residue cover on top of the soil. As these unharvested former living tissues of crops decompose, they add organic C to the soil, minimize the need for fuel in farming operations, and protect the soil from erosion. In North America, increased adoption of these methods could help recover large quantities of soil C that have been lost since conversion to agriculture about 150 years ago (30 – 50% have been lost from former prairie soils). Ground-based methods for monitoring tillage are impractical for regional-sized areas, but remote sensing is an attractive efficient alternative. While numerous studies have been performed using multispectral remote sensors such as Landsat, they have not been as accurate as those that utilize narrow hyperspectral bands capable of acquiring a spectral feature associated with cellulose (from crop residue) at 2100 nm. The acquisition of tillage data after harvest and just after planting, in conjunction with remotely-sensed crop condition information such as vegetation cover, leaf area index, chlorophyll content, water stress, and evapotranspiration can be used as inputs into soil C models, such as the Environmental Policy Integrated Climate (EPIC) and Century models, that estimate agricultural soil C fluxes. The proposed HyspIRI mission will contain all of the necessary spectral bands to measure all of these parameters, and as such, is an excellent platform to test methodologies for worldwide agricultural GHG monitoring and facilitate the development of future advanced multispectral sensors for orbital spacecraft missions.