сверхбольшие архивы спутниковых данных и возможности их распределенного анализа

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Analysis of LANDSAT NDVI time series for detecting land degradation in dry climatic zones of Russia and Mongolia

Tsydypov B., Garmaev E., Tulokhonov A., Alymbaeva Zh., Ayurzhanaev A., Sodnomov B., Batotsyrenov E., Chimeddorj Ts., Gombosurengiin U.

// В сборнике: ARCTIC DIALOGUE IN THE GLOBAL WORLD The Proceedings of Joint Science and Education Conference, 2015. С.314-318.

ISBN: 978-5-9793-0754-1

Our study examines whether Landsat NDVI satellite data time series can be used to detect land degradation areas in dry climatic zones of Russia and Mongolia. Time series analysis was applied to an 25-year Landsat NDVI satellite data record, based on the hypothesis that the resulting NDVI residual trend vectors would enable successful detection of changes in photosynthetically active vegetation. The aim of our work is to reveal and analyze changes in the vegetation cover of Russian and Mongolian dry climatic zones using a variety of field and remote sensing methods. Model key polygons located in semiarid climatic zone of Russia and Mongolia were considered for the investigation of vegetation dynamics. For these polygons plots of the NDVI temporal variation and NDVI maps of its spatio-temporal dynamics on the basis of TM and OLI spectroradiometer imagery (Landsat-5 and Landsat-8 satellites respectively) were constructed. The temporal dynamics of the vegetation was estimated using archive geoportal data of the Russian Space Research Institute of RAS for the period of 2001-2014. NDVI areas were mapped on the base of multitemporal satellite imagery for the first half of September from 1989 to 2014. The full-scale landscape indication of the selected NDVI areas was conducted. This indication is supported by the analysis of vegetation by environmental groups for drought resistance. The vegetation digression during last 25 years is traced across almost the entire territory of the selected polygons.

 

Ссылка на текст: files/publications/elibrary_24477953_96240975.pdf
  • СО РАН
  • Монгольский государственный сельскохозяйственный университет, Улан-Батор, Монголия
  • Research Institute of Animal Husbandry, Београд-Земун, Сербия
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