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Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

remote sensing Agriculture & Biology
drought Earth & Environmental Sciences
fluorescence Earth & Environmental Sciences
satellite data Earth & Environmental Sciences
Crops Engineering & Materials Science
Satellites Engineering & Materials Science
climate Earth & Environmental Sciences
crop yield Earth & Environmental Sciences

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Research Output 2007 2019

  • 58 Article
  • 2 Conference contribution
  • 1 Conference article
  • 1 Editorial

Are we approaching a water ceiling to maize yields in the United States?

Delucia, E. H., Chen, S., Guan, K., Peng, B., Li, Y., Gomez-casanovas, N., Kantola, I. B., Bernacchi, C. J., Huang, Y., Long, S. P. & Ort, D. R., Jun 18 2019, In : Ecosphere. 10, 6, e02773.

Research output: Contribution to journalArticle

Open Access
vapor pressure
water use efficiency

Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States

Li, Y., Guan, K., Schnitkey, G. D., Delucia, E. H. & Peng, B., Jul 1 2019, In : Global change biology. 25, 7, p. 2325-2337 13 p.

Research output: Contribution to journalArticle

Open Access

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

Cai, Y., Guan, K., Lobell, D., Potgieter, A. B., Wang, S., Peng, J., Xu, T., Asseng, S., Zhang, Y., You, L. & Peng, B., Aug 15 2019, In : Agricultural and Forest Meteorology. 274, p. 144-159 16 p.

Research output: Contribution to journalArticle

artificial intelligence
remote sensing

Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework

He, M., Kimball, J. S., Yi, Y., Running, S. W., Guan, K., Moreno, A., Wu, X. & Maneta, M., Sep 1 2019, In : Remote Sensing of Environment. 230, 111201.

Research output: Contribution to journalArticle

remote sensing
Data structures
satellite data

Toward building a transparent statistical model for improving crop yield prediction: Modeling rainfed corn in the U.S

Li, Y., Guan, K., Yu, A., Peng, B., Zhao, L., Li, B. & Peng, J., Mar 15 2019, In : Field Crops Research. 234, p. 55-65 11 p.

Research output: Contribution to journalArticle

statistical models
crop yield