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Trends in phenological parameters and relationship between land surface phenology and climate data in the Hyrcanian forests of Iran


Kiapasha, Khadije; Darvishsefat, Ali Asghar; Julien, Yves; Sobrino, Jose A; Zargham, Nosratoallah; Attarod, Pedram; Schaepman, Michael E (2017). Trends in phenological parameters and relationship between land surface phenology and climate data in the Hyrcanian forests of Iran. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(11):4961-4970.

Abstract

Vegetation activity may be changed in response to climate variability by affecting seasonality and phenological events. Monitoring of land surface phenological changes play a key role in understanding feedback of ecosystem dynamics. This study focuses on the analysis of trends in land surface phenology derived parameters using normalized difference vegetation index time series based on Global Inventory Monitoring and Mapping Studies data in the Hyrcanian forests of Iran covering the period 1981–2012. First, we applied interpolation for data reconstruction in order to remove outliers and cloud contamination in time series. Phenological parameters were retrieved by using the midpoint approach, whereas trends were estimated using the Theil–Sen approach. Correlation coefficients were evaluated from multiple linear regression between phenological parameters against temperature and precipitation time series. Significant Mann–Kendall test analysis indicate average start of season (SOS) and end of season (EOS) increased by −0.16 and +0.14 days per year, respectively. Results of significant trend analysis showed that later EOS was associated with increasing temperature trends and we found strongest relationships between temperature and phenological parameters in the west of the Hyrcanian forests, where precipitation was abundant. Moreover, SOS correlated strongly with total precipitation and mean temperature. This study allows us to better estimate the drivers affecting the vegetation dynamics in the Hyrcanian forests of Iran.

Abstract

Vegetation activity may be changed in response to climate variability by affecting seasonality and phenological events. Monitoring of land surface phenological changes play a key role in understanding feedback of ecosystem dynamics. This study focuses on the analysis of trends in land surface phenology derived parameters using normalized difference vegetation index time series based on Global Inventory Monitoring and Mapping Studies data in the Hyrcanian forests of Iran covering the period 1981–2012. First, we applied interpolation for data reconstruction in order to remove outliers and cloud contamination in time series. Phenological parameters were retrieved by using the midpoint approach, whereas trends were estimated using the Theil–Sen approach. Correlation coefficients were evaluated from multiple linear regression between phenological parameters against temperature and precipitation time series. Significant Mann–Kendall test analysis indicate average start of season (SOS) and end of season (EOS) increased by −0.16 and +0.14 days per year, respectively. Results of significant trend analysis showed that later EOS was associated with increasing temperature trends and we found strongest relationships between temperature and phenological parameters in the west of the Hyrcanian forests, where precipitation was abundant. Moreover, SOS correlated strongly with total precipitation and mean temperature. This study allows us to better estimate the drivers affecting the vegetation dynamics in the Hyrcanian forests of Iran.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Uncontrolled Keywords:Computers in Earth Sciences, Atmospheric Science
Language:English
Date:2017
Deposited On:05 Dec 2017 16:32
Last Modified:19 Aug 2018 11:41
Publisher:Institute of Electrical and Electronics Engineers
ISSN:1939-1404
OA Status:Closed
Publisher DOI:https://doi.org/10.1109/JSTARS.2017.2736938

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