Open AccessForest cover trend analysis using MODIS time series and its climatic responses in the Mari El Republic of Russia
Author(s) -
Eldar Kurbanov,
Oleg Vorobev,
Sergey Lezhnin,
Denis Dergunov,
Y Wang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/932/1/012003
Subject(s) - phenology , normalized difference vegetation index , deciduous , land cover , environmental science , climate change , climatology , vegetation (pathology) , time series , geography , physical geography , remote sensing , land use , ecology , medicine , pathology , machine learning , computer science , biology , geology
This study assesses whether MODIS NDVI satellite data time series can be used to detect changes in forest phenology over the different forest types of the Mari El Republic of Russia. Due to the severe climatic conditions, coniferous and deciduous forests of this region are especially vulnerable to climate change, which can lead to stresses from droughts and increase the frequency of wild fires in the long term. Time series analysis was applied to 16-day composite MODIS (MOD13Q1) (250 m) satellite data records (2000-2020) for the investigated territory, based on understanding that the NDVI trend vectors would enable detection of phenological changes in forest cover. There was also the determination of land cover/land use change for the area and examination of meteorological data for the investigated period. For the study, we utilized four phenological metrics: start of season (SOS), end of season (EOS), length of season (LOS), and Maximum vegetation index (MVI). The NDVI MODIS data series were smoothed in the TimeSAT software using the Savitsky-Golay filter. The results of the study show that over the 20-years period variations in phenological metrics do not have a significant impact on the productivity and growth of forest ecosystems in the Mari El Republic.