MAPPING OF THE LAND COVER SPATIOTEMPORAL CHARACTERISTICS IN NORTHERN RUSSIA CAUSED BY CLIMATE CHANGE
- 1Department of Cartography and Geoinformatics, Saint-Petersburg State University, Russia
- 2Meteorological Department, Russian State Hydrometeorological University, Saint-Petersburg, Russia
- 3Institute of Biology, Komi Scientific Center, Ural Branch, Russian Academy of Sciences, Syktyvkar, Russia
- 4Department of Physical Geography and Landscape Design, Saint-Petersburg State University, Russia
Keywords: Climate Change, Dynamics of Vegetation, Growing Seasons, Vegetation Indexes, NDVI, NDWI
Abstract. The study is devoted to the investigation of regional climate change in Northern Russia. Due to sparseness of the meteorological observation network in northern regions, we investigate the application capabilities of remotely sensed vegetation cover as indicator of climate change at the regional scale. In previous studies, we identified statistically significant relationship between the increase of surface air temperature and increase of the shrub vegetation productivity. We verified this relationship using ground observation data collected at the meteorological stations and Normalised Difference Vegetation Index (NDVI) data produced from Terra/MODIS satellite imagery. Additionally, we designed the technique of growing seasons separation for detailed investigation of the land cover (shrub cover) dynamics. Growing seasons are the periods when the temperature exceeds +5°C and +10°C. These periods determine the vegetation productivity conditions (i.e., conditions that allow growth of the phytomass). We have discovered that the trend signs for the surface air temperature and NDVI coincide on planes and river floodplains.
On the current stage of the study, we are working on the automated mapping technique, which allows to estimate the direction and magnitude of the climate change in Northern Russia. This technique will make it possible to extrapolate identified relationship between land cover and climate onto territories with sparse network of meteorological stations. We have produced the gridded maps of NDVI and NDWI for the test area in European part of Northern Russia covered with the shrub vegetation. Basing on these maps, we may determine the frames of growing seasons for each grid cell. It will help us to obtain gridded maps of the NDVI linear trend for growing seasons on cell-by-cell basis. The trend maps can be used as indicative maps for estimation of the climate change on the studied areas.