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Open AccessArticle

The Use of Satellite Information (MODIS/Aqua) for Phenological and Classification Analysis of Plant Communities

1
Institute of Biophysics SB RAS, Federal Research Center “Krasnoyarsk Science Center SB RAS”, Academgorodok 50-50, 660036 Krasnoyarsk, Russia
2
Federal Research Center “Krasnoyarsk Science Center SB RAS”, Academgorodok 50, 660036 Krasnoyarsk, Russia
3
Institute of Computational Modeling SB RAS, Federal Research Center “Krasnoyarsk Science Center SB RAS”, Academgorodok 50-44, 660036 Krasnoyarsk, Russia
4
Sukachev Institute of Forest SB RAS, Federal Research Center “Krasnoyarsk Science Center SB RAS”, Academgorodok 50-28, 660036 Krasnoyarsk, Russia
*
Author to whom correspondence should be addressed.
Forests 2019, 10(7), 561; https://doi.org/10.3390/f10070561
Received: 27 May 2019 / Revised: 1 July 2019 / Accepted: 2 July 2019 / Published: 4 July 2019
Vegetation indices derived from remote sensing measurements are commonly used to describe and monitor vegetation. However, the same plant community can have a different NDVI (normalized difference vegetation index) depending on weather conditions, and this complicates classification of plant communities. The present study develops methods of classifying the types of plant communities based on long-term NDVI data (MODIS/Aqua). The number of variables is reduced by introducing two integrated parameters of the NDVI seasonal series, facilitating classification of the meadow, steppe, and forest plant communities in Siberia using linear discriminant analysis. The quality of classification conducted by using the markers characterizing NDVI dynamics during 2003–2017 varies between 94% (forest and steppe) and 68% (meadow and forest). In addition to determining phenological markers, canonical correlations have been calculated between the time series of the proposed markers and the time series of monthly average air temperatures. Based on this, each pixel with a definite plant composition can be characterized by only four values of canonical correlation coefficients over the entire period analyzed. By using canonical correlations between NDVI and weather parameters and employing linear discriminant analysis, one can obtain a highly accurate classification of the study plant communities. View Full-Text
Keywords: boreal forests and ecosystems; NDVI (normalized difference vegetation index); classification of plant communities; linear discriminant analysis boreal forests and ecosystems; NDVI (normalized difference vegetation index); classification of plant communities; linear discriminant analysis
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MDPI and ACS Style

Ivanova, Y.; Kovalev, A.; Yakubailik, O.; Soukhovolsky, V. The Use of Satellite Information (MODIS/Aqua) for Phenological and Classification Analysis of Plant Communities. Forests 2019, 10, 561.

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