Studying the dynamics of mountain ecosystems in the context of climate change employing remotely sensed data

V. Muradyan; G. Tepanosyan; Sh. Asmaryan; A. Saghatelyan

doi:10.1117/12.2279423

6 September 2017 Studying the dynamics of mountain ecosystems in the context of climate change employing remotely sensed data

V. Muradyan, G. Tepanosyan, Sh. Asmaryan , A. Saghatelyan

Author Affiliations +

Proceedings Volume 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017); 104440A (2017) https://doi.org/10.1117/12.2279423
Event: Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 2017, Paphos, Cyprus

Abstract

This study was aimed to assess the spatio-temporal dynamic of ME using remote sensing methods. SPOT and AVHRR satellite data were used. Average annual, monthly and decade precipitation and temperature data obtained between 1982-2014 from 5 meteorological stations were used. NDVI, Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI) were calculated and compared with meteorological data. Analyzing the dynamics of average NDVI, VCI, TCI, VHI for the entire area of Syunik marz (Armenia) has indicated that it has a cyclic character with a growth trend. NDVI and VCI show a steady growth, whereas TCI decreases, so wholly the dynamic trend of VHI is stable. Collation between average decade meteorological data for 1998-2013 and NDVI has indicated that during vegetation growing season the vegetation dynamics is determined by the amount of precipitation and average temperature recorded not in the given, but in previous and particularly 2th and 3th decades. So, collation between RS and meteorological data for more than 30 years supports a conclusion that there is a clear rise in productivity of the studied region’s ecosystems in the context of climate change.

Citation Download Citation

V. Muradyan, G. Tepanosyan, Sh. Asmaryan , and A. Saghatelyan "Studying the dynamics of mountain ecosystems in the context of climate change employing remotely sensed data ", Proc. SPIE 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 104440A (6 September 2017); https://doi.org/10.1117/12.2279423

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