Journal of Siberian Federal University. Engineering & Technologies / Technology to Detect Anomalies of Net Primary Production of Vegetation Dynamics on the Basis of Non-Linear Trends (MODIS NPP)

Full text (.pdf)
Issue
Journal of Siberian Federal University. Engineering & Technologies. 2017 10 (1)
Authors
Larko, Aleksander A.; Ivanova, Julia D.; Shevyrnogov, Anatoly P.
Contact information
Larko, Aleksander A.: Institute of Biophysics SB RAS, Federal Research Center “Krasnoyarsk Science Center SB RAS” 50/50 Akademgorodok, Krasnoyarsk, 660036, Russia; Ivanova, Julia D.: Institute of Biophysics SB RAS, Federal Research Center “Krasnoyarsk Science Center SB RAS” 50/50 Akademgorodok, Krasnoyarsk, 660036, Russia; lulja@yandex.ru; Shevyrnogov, Anatoly P.: Institute of Biophysics SB RAS, Federal Research Center “Krasnoyarsk Science Center SB RAS” 50/50 Akademgorodok, Krasnoyarsk, 660036, Russia; lantar@inbox.ru
Keywords
NPP; nonlinear trends; vegetation dynamics; satellite data
Abstract

The paper proposes a technology to detect anomalies of net primary production of vegetation dynamics and the authors have done an analysis of the data. The authors are based on ecological theory for conceptual technology that allows you to monitor an extended territory, using estimates NPP (MODIS NPP) as an indicator of the conditions of vegetation. For the detection of areas with anomalies NPP dynamics was used STL method (Seasonal-Trend Decomposition Procedure Based on Loess). The study was conducted in the south of the Krasnoyarsk region, which has a great variety of natural landscapes from the steppes to the high alpine meadows of the Sayan Mountains. For analysis of the dynamics of anomalies of NPP used satellite data in temperature and humidity

Pages
113-125
Paper at repository of SibFU
https://elib.sfu-kras.ru/handle/2311/31512

Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

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