4.5 Article

Continuous Monitoring of Crop Reflectance, Vegetation Fraction, and Identification of Developmental Stages Using a Four Band Radiometer

Journal

AGRONOMY JOURNAL
Volume 105, Issue 6, Pages 1769-1779

Publisher

WILEY
DOI: 10.2134/agronj2013.0242

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Funding

  1. Carbon Sequestration Program, University of Nebraska-Lincoln through the Office of Science (BER) U.S. Department of Energy [DE-FG02-03ER63639]

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Real-time monitoring of crop vegetation fraction and identification of development stages provides useful information for crop management. Using sensors at close range makes it possible to collect data with very high temporal resolution. This study used four-band radiometers with green, red, red edge, and near infrared spectral bands for daily monitoring of maize (Zea mays L.) and soybean [Glycine max (L.) Merr.] reflectance during the growing season in three fields over 3 yr. Two fields were continuous irrigated maize and the third was managed under a maize/soybean rotation. The objectives were (i) determine diurnal and seasonal temporal behavior of reflectance in two contrasting crops, maize and soybean, (ii) remotely estimate the crop developmental stage using spectral spaces and vegetation indices, and (iii) estimate vegetation fraction using spectral spaces. Diurnal reflectance behavior indicated that the median reflectance measured within 2.5 h of solar noon was reliable for examining the daily behavior of reflectance and vegetation indices. Since the information content of reflectance in different spectral bands varies over the course of a season, spectral spaces (reflectance in one band vs. reflectance in another band) were constructed and shown to be a useful tool for identifying crop developmental stages. Five distinct stages of vegetation status (soil/residue, green-up, vegetative, senescence, and soil/stover/residue) were accurately identified using the red vs. green reflectance spectral space. Vegetation fraction was estimated using spectral spaces in maize with estimation error below 0.071 and in soybean below 0.064. Thus, high temporal resolution sensors can be a reliable tool for monitoring vegetation for a variety of applications.

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