Assessing the effects of the climate change on land cover changes in different time periods
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ORIGINAL PAPER
Assessing the effects of the climate change on land cover changes in different time periods Hassan Khosravi 1 & Ali Azareh 1 & Hadi Eskandari Dameneh 2 & Elham Rafiei Sardoii 1 & Hamed Eskandari Dameneh 1
Received: 5 May 2016 / Accepted: 9 January 2017 # Saudi Society for Geosciences 2017
Abstract The present research evaluated the relation between the normalized difference vegetation index (NDVI) changes and the climate change during 2000–2014 in Qazvin Plain, Iran. Daily precipitation and mean temperature values during 2015–2040 and 2040–2065 were predicted using the statistical downscaling model (SDSM), and these values were compared with the values of the base period (2000–2014). The MODIS images (MOD13A2) were used for NDVI monitoring. In order to investigate the effects of climate changes on vegetation, the relationship between the NDVI and climatic parameters was assessed in monthly, seasonal, and annual time periods. According to the obtained results under the B2 scenario, the mean annual precipitation at Qazvin Station during 2015–2040 and 2040–2065 was 6.7 mm (9.3%) and 8.2 mm (11.36%) lower than the values in the base period, respectively. Moreover, the mean annual temperature in the mentioned periods was 0.7 and 0.92 °C higher than that in the base period, respectively. Analysis of the correlations between the NDVI and climatic parameters in different periods showed that there is a significant correlation between the seasonal temperature and NDVI (P < 0.01). Moreover, the NDVI will increase 0.009 and 0.011 during 2015–2040 and 2040–2065, respectively.
Keywords NDVI . Temperature . Precipitation . Qazvin Plain . Remote sensing
* Hassan Khosravi [email protected]
1
University of Tehran, Tehran, Islamic Republic of Iran
2
University of Hormozgan, Bandar Abbas, Islamic Republic of Iran
Introduction Climate is a major ecological factor that its changes are the most important threat to sustainable development. Climate change which is mainly caused by human activities has led to changes in various parts of the ecosystem in recent decades (IPCC 2007). Therefore, studying the trend of atmospheric variables such as temperature and precipitation is very important, in order to determine the effects of climate changes on different resources in the future periods. For this purpose, at first, the climate parameters are predicted by the statistical downscaling model (SDSM) for the future period. Then, the relation between climate parameters and the normalized difference vegetation index (NDVI) is studied. If the relation is significant, the vegetation index trend can be predicted for the future period based on changed climate parameters. Valid methods, such as general circulation model (GCM), should be adopted to simulate greenhouse gas-induced climate changes (Christensen et al. 2007). Despite the growing number of GCMs, the existing models are not suitable for regional environmental studies as they cannot predict climate changes at small scales (e.g., weather stations). Downscaling models w
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