Assessment of pasture biomass with the normalized difference vegetation index from active ground-based sensors

E. Scott Flynn, Charles T. Dougherty, Ole Wendroth

Research output: Contribution to journalArticlepeer-review

55 Scopus citations


Calculating forage availability is challenging for managers of grazing systems due to the spatial heterogeneity of swards. Remote sensing applications may help to overcome this problem through estimates of biomass made with reflectance data. The objectives of this study were to (i) estimate herbage mass using an active, on-the-go, ground-based, narrow band sensor to calculate the normalized difference vegetation index (NDVI), (ii) determine if NDVI may be used to assess spatial variability of herbage mass of grasslands, and (iii) determine if NDVI may be used to evaluate management of grazing systems. The NDVI was measured using an active ground-based sensor, the GreenSeeker (Ntech Industries, Ukiah, CA). In tall fescue [Schedonorus arundinaceus (Schreb.) Dumort], NDVI was correlated with biomass determined by destructive harvesting (r2 = 0.68) and also with a calibrated rising plate meter (RPM) (r2 = 0.54). Semivariograms revealed that NDVI sampling intervals of 0.76 m adequately described the spatial variability structure of grazed swards. The frequency distributions of sward biomass derived from NDVI may reflect the foraging strategies of cattle. Negative skewness and high kurtosis are consistent with selective grazing, while positive skewness and low kurtosis are consistent with less diet selectivity. Frequency distributions also improved definition of available forage within each field. We concluded that spatial properties of grassland biomass may be derived from high resolution NDVI and RPM data and could be used to evaluate conditions of grassland landscapes and to aid decision-making of managed grazing systems.

Original languageEnglish
Pages (from-to)114-121
Number of pages8
JournalAgronomy Journal
Issue number1
StatePublished - Jan 2008

ASJC Scopus subject areas

  • Agronomy and Crop Science


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