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The impact of environmental factors on the measurement of the normalized difference vegetation index

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November 13, 2012
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Dobos, A., Víg, R., & Nagy, J. (2012). The impact of environmental factors on the measurement of the normalized difference vegetation index. Acta Agraria Debreceniensis, 49, 141-147. https://doi.org/10.34101/actaagrar/49/2512
Abstract

The level of nitrogen supply of a plant population can be quickly measured with non-destructive optical measurement devices and the differentiated determination of nitrogen shortage and the replenishment of nitrogen can also be carried out. The level of nitrogen supply is based on the fact that the chlorophyll content of crops is in close correlation with nitrogen content and that the amount of chlorophyll can be easily measured on the basis of the light absorption of chlorophyll molecules. The successfulness of optical measurements can be influenced by the change of weather  parameters; therefore, it is important to know the correlations between measurement results and weather parameters when it comes to practical use.
The GreenSeeker Model 505 measurement device determines the relative chlorophyll content in the form of the Normalized Difference
Vegetation Index (NDVI) calculated on the basis of the intensity of the reflected red and infrared rays of light from the crop population. The measurements were performed in alfalfa population with 10 replications at five measurement heights and four measurement times. The weather parameters were measured by a weather station located in the middle of the alfalfa population and the correlations between the meteorological data and the NDVI values were examined. During the statistical evaluation of the results, it was established that the NDVI measurement is primarily influenced by the relative humidity of the air, secondly by air temperature and thirdly by wind speed. Relative humidity was in strong correlation with the NDVI values which were also influenced by the measurement height and time. Regression was not significant in the case of 20 cm  measurement height, but the measurements above 40 cm height showed significant correlations. The correlation was shown to be strong at each measurement time, but the influence of humidity was the lowest at 11:00 and 14:00.