Monitoring Growing Season Length of Deciduous Broad Leaf Forest Derived From Satellite Data in Iran
Sasan Babaei Kafaki, Asadollah Mataji and Seyed Armin Hashemi
DOI : 10.3844/ajessp.2009.647.652
American Journal of Environmental Sciences
Volume 5, Issue 5
Problem statement: Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and biogeochemical cycles. This study aimed to quantify changes in plant phenology of deciduous broadleaf forests between the years 1982-1999 and investigate the relationships between the onset dates of phenology and climatic factors. Approach: We studied the climate changes effected on the growing season duration in vegetation of Iran, using the AVHRR/NDVI biweekly time-series data collected from 1982-1999 and concurrent mean temperature and precipitation data. The first estimated fastest changes of NDVI corresponded to the vegetation green-up and dormancy from the seasonal cycle of NDVI during 1982-1999. The onset dates of vegetation green-up and dormancy were determined based on the estimated rates and the NDVI seasonal cycles. Results: The results showed that over the study period, the growing season duration has lengthened by 0.94 days year-1 in study region. The green-up of vegetation has advanced in the spring by 0.63 days year-1 and the dormancy delayed in autumn by 0.32 days year-1. The onset date of green-up for all vegetation types negatively correlated with mean preseason temperature for almost all the preseason periods significant, suggesting that the warmer winters probably benefit an earlier green-up the following spring. Conclusion: Based on NOAA/AVHRR NDVI biweekly time-series data and concurrent climate information, it was estimated that the growing season duration of Iran’s vegetation was significantly lengthened, primarily through an earlier green-up and a later dormancy during the period of 1982-1999.
© 2009 Sasan Babaei Kafaki, Asadollah Mataji and Seyed Armin Hashemi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.