Investigation of Eastern Siberia vegetation index variations on long-term satellite data

Eugenia V. Varlamova; Vladimir S. Solovyev

doi:10.1117/12.2504575

13 December 2018 Investigation of Eastern Siberia vegetation index variations on long-term satellite data

Eugenia V. Varlamova, Vladimir S. Solovyev

Proceedings Volume 10833, 24th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 108338C (2018) https://doi.org/10.1117/12.2504575
Event: XXIV International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, 2018, Tomsk, Russian Federation

Abstract

The study of NDVI variations and phenology dates of Eastern Siberia vegetation on NOAA satellite data (1982-2017) is carried out. Trend maps of seasonal NDVI (May-September) and maps of correlations NDVI with air temperature and precipitation were constructed. Area with the highest NDVI linear trend (10 – 15%) is located in the northern part of Yakutia. The increasing of NDVI seasonal trend is mainly due to significant increase of NDVI in May. Correlation between NDVI (in May) in the test site and air temperature is R=0.8. While the relationship between NDVI and precipitation is negligible. For 1982-2004 NDVI trend had near-zero values, but during 2004-2015 NDVI trend showed a significant increase about ~27%. The significant increase of air temperature (~30°C) during 2004-2015 is also observed in test site. Method “NDVI 0.3”1 based on NDVI threshold 0.3 was used to calculated the start and end of vegetation season in test site. In addition, BISE² algorithm was used to reducing noise in daily NDVI time-series. Analysis of phenology variations during 1982-2017 showed: the SOS shifted by ~12 days earlier and EOS by ~4 days later. Thus, the growing season has increased. The average trend of growing season length is ~16 days. For same time, the mean values NDVI of growing season increased by ~10% and mean values NDVI of July by ~17%.

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Eugenia V. Varlamova and Vladimir S. Solovyev "Investigation of Eastern Siberia vegetation index variations on long-term satellite data", Proc. SPIE 10833, 24th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 108338C (13 December 2018); https://doi.org/10.1117/12.2504575

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KEYWORDS

Vegetation

Satellites

Climate change

Climatology

Environmental sensing

Meteorology

Temperature metrology

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