Skip to main content
ARS Home » Plains Area » Lincoln, Nebraska » Agroecosystem Management Research » Research » Publications at this Location » Publication #320028
Title: Quantification and mapping of surface residue cover and tillage practices for maize and soybean fields in south central Nebraska-USA using Landsat imagery

Author
item SHARMA, VIVEK - University Of Nebraska
item IRMAK, SUAT - University Of Nebraska
item KILIC, AYSE - University Of Nebraska
item SHARMA, VASUDHA - University Of Nebraska
item Gilley, John
item MEYER, GEORGE - University Of Nebraska
item MARX, DAVID - University Of Nebraska

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/21/2016
Publication Date: N/A
Citation: N/A

Interpretive Summary: There are no methods currently available to quantify the percent crop residue cover and area under conservation tillage practices at large scales on a continual basis. This research used satellite data to evaluate six tillage indices to map crop residue cover in eight counties in south central Nebraska. A numerical model using a tillage index accurately estimated crop residue cover for different tillage practices at large scales. The numerical model was then used to spatially map crop residue cover on a regional scale by considering the timing of planting and tillage. Model results indicated that approximately 30, 30, 28, 14, 31, 41, 30 and 16% of maize area and 14, 13, 5, 19, 28, 14 and 7% of soybean area had more than 70% crop residue cover in Adams, Clay, Fillmore, Hamilton, Kearney, Saline, Seward and York Counties, respectively. This research illustrates that satellite data are capable of estimating and mapping crop residue cover on a regional scale and continual basis using locally developed information on tillage practices and crop residue cover. Further research is needed to incorporate soil and residue moisture content into the numerical model to enhance model accuracy.

Technical Abstract: The area cultivated under conservation tillage practices such as no-till and minimal tillage has recently increased in south central Nebraska (NE). Consequently, changes in some of the impacts of cropping systems on soil such as enhancing soil and water quality, improving soil structures and infiltration, increasing water use efficiency and promoting carbon sequestration may result. However, there are no methods currently available to quantify the percent crop residue cover (CRC) and area under conservation tillage practices at large scales on a continual basis. This research used Landsat-7 (ETM+) and Landsat-8 (OLI/TRIS) satellite data to evaluate six tillage indices [i.e., normalized vegetative difference index (NDTI); normalized difference index 7 (NDI7); normalized difference index 5 (NDI5); normalized difference senescent vegetative index (NDSVI); modified CRC; and simple tillage index (STI)] to map CRC in eight counties in south central Nebraska, USA. A linear regression CRC model showed that NDTI performed well to differentiate the CRC for different tillage practices at large scales with a coefficient of determination (R2) of 0.62, 0.68, 0.78, and 0.07 for March 25, April 18, May 28 and June 06, 2013 respectively. The minimum NDTI method was then used to spatially map the CRC on a regional scale by considering the timing of planting and tillage implementation. Measured CRC was divided into training (calibration) and test (validation) datasets. A modified CRC model was developed using a training dataset with an R2 of 0.89 (RMSD = 10.63%). A 3 x 3 matrix showed an overall accuracy of 0.90 with Kappa statistic coefficient of 0.89. Our results indicate that about 30, 30, 28, 14, 31, 41, 30 and 16% of maize area and 14, 13, 5, 19, 28, 14 and 7% of soybean area had more than 70% of CRC in Adams, Clay, Fillmore, Hamilton, Kearney, Saline, Seward and York Counties, respectively. This research and the procedures presented illustrate that multi spectral Landsat images are capable of estimating and mapping CRC (with a reasonable accuracy of within 10.6%) on a regional scale and continual basis using locally developed tillage practice vs. crop residue algorithms. Further research is needed to incorporate soil and residue moisture content into the CRC vs. tillage index relationships to enhance the accuracy of the models in estimating CRC.