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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 1, pp. 133-143

Influence of observation conditions on the accuracy of NDVI vegetation index calculation from Earth remote sensing data

A.I. Alexanin 1, 2 , A.N. Timofeev 2 
1 Institute of Automation and Control Processes FEB RAS, Vladivostok, Russia
2 Far Eastern Federal University, Vladivostok, Russia
Accepted: 29.12.2022
DOI: 10.21046/2070-7401-2023-20-1-133-143
The problem of calculating the normalized vegetation index (NDVI) from satellite data is considered. The index values calculated from the MODIS/Aqua radiometer data by the SeaDAS software package algorithm are compared with the values obtained at the research site La Crau (France) for 7 years. The site is located near the Mediterranean coast and is a flat field where grass grows. The measurements are carried out by an automatic photometric station ROSAS. Calculations show the proximity of satellite and field measurements: bias — 0.005; standard deviation 0.03. The algorithm used does not take into account the effect of aerosol on the NDVI value. However, the errors due to the lack of accounting for aerosol lie within the limits of the total calculation error. There is a slight dependence of the error on the zenith angle of the sun, which varied in the range from 20 to 70. The bidirectional reflectance distribution function of the surface on the site is uniform, except for the directions close to the sunbeam. The measurements were far from the sunbeam zone. However, the accuracy of the calculation depends on the difference between the azimuth angle of the site survey and the azimuth to the sun. The NDVI mismatches due to differences in the central wave numbers of different satellites also turned out to be significant. The comparison was made for the following radiometers: MODIS/Aqua, Landsat-8/OLI-1, Landsat-9/OLI-2, Kanopus-V/MSS.
Keywords: vegetation index NDVI, atmospheric image correction, MODIS/Aqua
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