Nitrogen (N) fertilizer management is one of the main concerns for precision agriculture under corn production, which aims to not only maximize the profits, but also ensure environmental sustainability. Effective N fertilizer management can either avoid N stress or provide timely and accurate detection of in-season N stress for remedies. Traditional N trial experiments to evaluate different N management practices have to wait until harvest, and do not allow tracking of when and how N stress develops. Meanwhile, rapidly developed remote sensing technology offers new opportunities for in-season evaluation of N status and detection of N stress for crops, including both the unmanned aircraft vehicle (UAV)-based and satellite-based multispectral sensing. In this study, we collected weekly multispectral images of UAV and Planet Lab's CubeSat, as well as various other ground measurements for an experimental cornfield that included 28 N management treatments in Central Illinois, 2017. We found that both the UAV-and CubeSat-based multispectral sensors were able to detect N stress at vegetative stages before tasseling, and could detect changes in the level of N stress through derived chlorophyll index green (CIg) for different N management practices. The CubeSat-based CIg showed high consistency with the UAV-based CIg (correlation above 0.9), which indicated the potential of CubeSat-based CIg to be applied for N stress detection at a larger spatial scale. This study demonstrates that the UAV-and CubeSat-based multispectral sensing has the promising potential to monitor N stress of corn throughout the growing season, which may assist decision making of N management.
|Original language||English (US)|
|Number of pages||14|
|Journal||IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing|
|State||Published - Dec 2019|
Bibliographical noteFunding Information:
Manuscript received June 15, 2019; revised September 26, 2019; accepted October 30, 2019. Date of publication January 5, 2020; date of current version February 4, 2020. The work of K. Guan was supported by Illinois Nutrient Research & Education Council. The work of K. Guan and B. Peng was supported by NASA New Investigator Award through the NASA Terrestrial Ecology Program and NASA Harvest Program managed by University of Maryland. (Corresponding authors: Yaping Cai; Kaiyu Guan.) Y. Cai and S. Wang are with the CyberGIS Center for Advanced Digital and Spatial Studies, Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA (e-mail: firstname.lastname@example.org; email@example.com).
- Corn nitrogen stress
- Planet Lab
- in-season detection
- unmanned aerial vehicles (UAV)