Ground-based remote sensing of water and nitrogen stress

Michael Kostrzewski, Peter Waller, Philip Guertin, Julio Haberland, Paul Colaizzi, Edward Barnes, Thomas Thompson, Tom Clarke, Emily Riley, Christopher Choi

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


A ground-based remote sensing system (Agricultural Irrigation Imaging System, or AgIIS) was attached to a linear-move irrigation system. The system was used to develop images of a 1-ha field at 1 X 1 m resolution to address issues of spatial scale and to test the ability of a ground-based remote sensing system to separate water and nitrogen stress using the coefficient of variation (CV) for water and nitrogen stress indices. A 2 X 2 Latin square water and nitrogen experiment with four replicates was conducted on cotton for this purpose. Treatments included optimal and low nitrogen with optimal and low water. ANOVA was not an adequate method to assess the statistical variation between treatments due to the large number of data points. In general, the coefficient of variation of water and nitrogen stress indices increased with water and nitrogen stress. In fact, the coefficient of variation of stress indices was a more reliable measurement of water and nitrogen status than the mean value of the indices. Differences in coefficient of variation of stress indices between treatments were detectable at 3 m grid resolution and finer for water stress and at 7 m grid resolution and finer for nitrogen stress.

Original languageEnglish (US)
Pages (from-to)29-38
Number of pages10
JournalTransactions of the American Society of Agricultural Engineers
Issue number1
StatePublished - Jan 2003


  • Coefficient of variation
  • Cotton
  • Irrigation
  • Nitrogen
  • Remote sensing
  • Stress
  • Water

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)


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