Information Content of Spectral Vegetation Indices for Assessing the Weed Infestation of Crops Using Ground-Based and Satellite Data

• Published in: Izvestiya. Atmospheric and oceanic physics Vol. 57; no. 9; pp. 1188 - 1197
• Main Authors: Pisman, T. I., Erunova, M. G., Botvich, I. Yu, Emelyanov, D. V., Kononova, N. A., Bobrovsky, A. V., Kryuchkov, A. A., Shpedt, A. A., Shevyrnogov, A. P.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01-12-2021; Springer Nature B.V
• Subjects: Agricultural land; Cereal crops; Chlorophyll; Chlorophylls; Climatology; Correlation; Crop infestation; Crops; Dynamics; Earth and Environmental Science; Earth Sciences; Fields; Geophysics/Geodesy; Growing season; Infestation; Methods and Processing Tools and Interpretation of Space Information; Normalized difference vegetative index; Satellite data; Satellites; Spatial discrimination; Spatial distribution; Spatial resolution; Spectrometry; Vegetation; Vegetation index; Weeds; Wheat; ground-based spectrometry; geobotanical studies; vegetation indices; PlanetScope; wheat crops; Krasnoyarsk krai
• ISSN: 0001-4338; 1555-628X
• DOI: 10.1134/S0001433821090577

This paper presents the results of a study assessing the degree of weed infestation of wheat crops. They are obtained using optical ground-based and satellite spectral data with a 3-m spatial resolution from PlanetScope Dove satellites for 2019. The vegetation indices, including the normalized difference vegetation index (NDVI), the relative chlorophyll index (Chlorophyll Index Green—ClGreen or GCI), the modified soil-adjusted vegetation index (MSAVI2), and the visible atmospherically resistant index (VARI) are used in the interpretation of ground-based spectrometric and space images. This paper indicates the possibility of assessing the degree of weed infestation of agricultural fields. The higher the weed infestation, the lower the index values. The dynamics of VARI is found to be different from the dynamics of NDVI, ClGreen, and MSAVI2 during the growing season. The strong correlation between NDVI, ClGreen, and MSAVI2 and the weak correlation between VARI and other indices are observed. The possibility of identifying weedy sites in the agricultural fields is shown using the spatial distribution map of ClGreen dated August 2, 2019.