Use of spectral vegetation indices derived from airborne hyperspectral imagery for detection of european corn borer infestation in iowa corn plots

Matthew W. Carroll, John A. Glaser, Richard L. Hellmich, Thomas E. Hunt, Thomas W. Sappington, Dennis Calvin, Ken Copenhaver, John Fridgen

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Eleven spectral vegetation indices that emphasize foliar plant pigments were calculated using airborne hyperspectral imagery and evaluated in 2004 and 2005 for their ability to detect experimental plots of corn manually inoculated with Ostrinia nubilalis (Hübner) neonate larvae. Manual inoculations were timed to simulate infestation of corn, Zea mays L., by first and second flights of adult O. nubilalis. The ability of spectral vegetation indices to detect O. nubilalis-inoculated plots improved as the growing season progressed, with multiple spectral vegetation indices able to identify infested plots in late August and early September. Our findings also indicate that for detecting O. nubilalis-related plant stress in corn, spectral vegetation indices targeting carotenoid and anthocyanin pigments are not as effective as those targeting chlorophyll. Analysis of image data suggests that feeding and stem boring by O. nubilalis larvae may increase the rate of plant senescence causing detectable differences in plant biomass and vigor when compared with control plots. Further, we identified an approximate time frame of 5-6 wk postinoculation, when spectral differences of manually inoculated "second" generation O. nubilalis plots seem to peak.

Original languageEnglish (US)
Pages (from-to)1614-1623
Number of pages10
JournalJournal of economic entomology
Volume101
Issue number5
DOIs
StatePublished - Oct 2008

All Science Journal Classification (ASJC) codes

  • Ecology
  • Insect Science

Fingerprint

Dive into the research topics of 'Use of spectral vegetation indices derived from airborne hyperspectral imagery for detection of european corn borer infestation in iowa corn plots'. Together they form a unique fingerprint.

Cite this