Алгоритм определения фенологических характеристик лесного покрова на основе временных рядов спутниковых данных
Authors: ВОРОБЬЕВ О.Н. , КУРБАНОВ Э.А. , ДЕМИШЕВА Е.Н. , Меньшиков С.А. , Смирнова Л.Н. 
Published: February 2025

Фенологические показатели лесного покрова являются ключевыми индикаторами для лучшего понимания текущего состояния лесов и их отклик на изменение климата. В работе предложен алгоритм обработки временных рядов вегетационного индекса NDVI за 2000–2018 гг., полученных по 16-дневным композитам спектрорадиометра MODIS на территорию Куярского лесничества Марийского лесного Заволжья, в программе TIMESAT. Серия данных NDVI MODIS была выравнена в этой программе с использованием метода (фильтра) Савицкого-Голея. Алгоритм позволил количественно оценить шесть фенологических показателей лесного покрова для участка (группы пикселей) исследуемого лесничества: начало сезона (SOS), конец сезона (EOS), продолжительность вегетационного периода (LOS), максимальное значение NDVI (MV), день года MV и амплитуда вегетационного сезона (SA). Результаты исследования показали, что за 18-летний период колебания в фенологических показателях не оказали существенного влияния на продуктивность и рост лесов на исследуемой площади.
Phenological parameters of forest cover are key indicators for understanding the current state of forests and their response to climate change. The aim of the work was the development and testing of an algorithm for reviling phenological characteristics and indicators of forest bio-productivity based on the analysis of time series of satellite data in the TIMESAT dynamic window at the level of a single forest district. In the study, we used the MODIS data obtained for the forest cover of the Mari Zavolzhje region. The paper proposes an algorithm for processing the NDVI time series for 2000–2018, obtained by MODIS 16-day composites of on the territory of the Kuyar forestry of the Mari forest Zavolzhje region, in the TIMESAT program. The NDVI MODIS data series were aligned in this program using the Savitsky-Golay filter. The time series differs from simple data sampling by taking into account the correlation of measurements with time, and not just the statistical characteristics of the estimated data. Seasonal data were obtained from the smoothed curves in the TIMESAT program, on the basis of which a file in the "tpa" format was formed. The seasonal period of each of the 18 years of observations was considered from mid-April to mid-November of the respective year, which averaged 210 days in total. The algorithm made it possible to quantify 6 out of 1 phenological indicators of forest cover for a plot (group of pixels) of the studied forest areas: the start of the season (SOS), the end of the season (EOS), the length of the season (LOS), the maximum NDVI (MV), the day of the year of MV and vegetation season amplitude (SA). SOS and EOS averages obtained show relatively stable dynamics over the study period. Some shift in the days of the start of the season was observed in 2001, 2005, 2009, 2015 and 2016, when SOS reached more than 140 days from the beginning of the calendar year. For the same years, the maximum days of the end of the season (EOS) are accounted for exceeding 250 days from the beginning of the calendar year. The length of the season on the investigated forest district (LOS) varies on average from 96 to 154 days. The maximum LOS periods were for 2001 (138 days), 2010 (151 days), 2013 (121 days), and 2016 (154 days) respectively. The results of the study showed that over the 18-years period variations in phenological indicators did not have a significant impact on the productivity and growth of forests in the study area. Although the use of NDVI to monitor phenological characteristics in mixed coniferous and deciduous forests has some limitations, our research has shown that it can be a very useful tool in assessing the effects of environmental change on the growth of forest ecosystems.