Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 7/23/2008
Publication Date: 7/23/2008
Citation: Hatfield, J.L. 2008. Seasonal patterns of vegetative indices over cropping systems [CD-ROM]. In: International Conference on Precision Agriculture Abstracts & Proceedings, July 20-23, 2008, Denver, CO. Interpretive Summary:
Technical Abstract: Remote sensing offers potential to precision agriculture applications in terms of providing both temporal and spatial information. There have been applications of the vegetative indices based on reflectance in the visible and near-infrared of which the normalized difference vegetative index (NDVI) is the most popular because of its relationship to crop growth and development. The NDVI, however, is not sensitive to changes in leaf area or biomass above conditions of complete light interception or to subtle changes in leaf color induced by nutrients or pest damage. The purpose of this study is to evaluate the seasonal patterns of nineteen vegetative indices over different crop rotations in central Iowa. Observations were made with a ground-based eight-band radiometer over corn, soybean, wheat, and canola throughout the year since 2001. Wavebands on this unit covered the range from 0.46 through 0.81 µm. This six-year data set has been collected over different tillage and nitrogen management practices as part of these rotation studies at a minimum of weekly observations under clear sky conditions. The goal of the study was to compare the seasonal patterns of these indices and the variation induced by the management practices imposed on the crop rotation. An evaluation of the error in each vegetative index was assessed through the collection of five sites within each treatment and each treatment was replicated three times. Each vegetative index was computed for each observation time and then evaluated for the seasonal trajectory and stability over years to detect changes in observed plant parameters, e.g., leaf area, biomass, ground cover, leaf chlorophyll content, residue cover. Differences among vegetative indices were found throughout the season and application of different indices can improve the ability to detect field scale changes in crop parameters.