Monitoring Crop Tillage Practices and Carbon Sequestration with NASA EOS for Enhanced Agricultural Management Decision Support

EarthzineDEVELOP Virtual Poster Session, Original

Image showing Relative difference Normalized Burn Ratios (RdNBR) showing four levels of burn severity in the Possum Kingdom Lake (left) and Bastrop Complex (right) fires.

Methodology of our project: Digital numbers of Hyperion imagery are converted to reflectance values, which are then ingested into the Cellulose Absorption Index (CAI) Model. After map algebra is performed on intermediary Hyperion raster data sets, the model yields crop residue fraction.

Methodology of our project: Digital numbers of Hyperion imagery are converted to reflectance values, which are then ingested into the Cellulose Absorption Index (CAI) Model. After map algebra is performed on intermediary Hyperion raster data sets, the model yields crop residue fraction.

Team Location: NASA Langley Research Center

Authors: Joseph Regan, Robert Bradley, Anastazia Neely, Andrew Tidwell.

Advisors/Mentors: Dr. Kenton Ross, Jamie Favors.

Other Acknowledgements: Dr. Ronald Follett, Baojuan Zheng.

Abstract: Concerns about climate change have driven efforts to reduce or offset greenhouse gas emissions. Agricultural activity has drawn considerable attention because it accounts for nearly 12 percent of total anthropogenic carbon emissions. Depending on the type of tillage method used, farm land can be a source or a sink for carbon. Conventional tillage disturbs the soil, releases greenhouse gases into the atmosphere, and can increase soil erosion. Conservation and no-till tillage practices, which disrupt the soil only slightly (or not at all), have been advocated for their ability to sequester carbon, decrease airborne particulate matter, reduce soil erosion, maintain soil moisture, and increase long-term crop productivity. This project aims to distinguish areas of conservation tillage from conventional tillage using remote sensing data, employing the Landsat and Hyperion satellites. We hypothesize that there should be a standard method which is able to convert index values into residue classifications without ground data analysis. This method, while slightly less accurate, is more practical for end-users by allowing them to quickly assess residue cover in a given region regardless of physical distance.

Video transcript available here.