Environmental change and socioeconomic pressure are expected to have significant impacts on Northern Alborz vegetation, particularly along ecotone such as the treeline. Remote sensing may be well suited to monitoring recent changes across the treeline because it captures integrated changes of all vegetation life forms over large spatial extents. This research examines treeline vegetation composition and change along the Nojmeh treeline using a high resolution, ETM + 2000. In this paper we investigate the use of satellite data to produce a classification of a treeline ecotone in Northern Alborz Mountains which has supported the field investigation as ground truth data collected in the summers from 2008 to 2010. The maximum correlation is related to the Bands 3 and 4 of Landsat ETM + with shrubs canopy cover that indicated in r of 0.34 and 0.37 respectively. The maximum rate of correlation in respect to the indices were recognized for the vegetation cover of moisture stress index (MSI) for forbs cover (r= 0.62). The ratio vegetation index (RVI) for grasses cover was indicated (r= 0.53). In conclusion, the results are specified that the ETM + sensor is the significant data with the elevated competence to discrimination of ecotone using vegetation indices.

The Earth's climate system is significantly affected by global warming. This study examined the spatiotemporal variations in average and extreme values of relative humidity, temperature, and temperature-humidity index in the northern areas of Iran from 1986 to 2016. The temperature-humidity index was generated for each of the 30 meteorological stations based on relative humidity and temperature data. Previously, trend analysis was calculated in different seasons using ordinary linear and quantile regression methods. For the most part, the results indicate a declining trend in relative humidity and a rising trend in temperature. The highest percentage of decreasing trend slopes for maximum relative humidity (≤-50%) in all seasons, but for maximum temperature, the highest percentage of increasing trend slopes in summer and winter (≥ 30%) identified on the southern coast of the Caspian Sea. However, a decreasing trend (%≤-15) was detected for the maximum temperature in autumn at the northern regions. Average and high values of THI in the summer season (≥ 75) have increased in the western and northern parts with high intensity (≥ 40%). The low values of THI in winter (≤ 30) have increased with a slight slope (20%), which indicates a decline in some of days with cold stress in winter for most regions. The findings of this study are generally useful for identifying changes in weather extremes and their effects on human health.

Nowadays, with significant climate change, the trend of environmental hazards is increasing. In the meantime, floods have shown a growing trend than other hazards. Haraz watershed in northern Iran is prone to floods due to the heavy rainfall with irregular pattern. Therefore, combining different methods and examining new approaches is an essential step in the development of methods in this field. In the present study, Analytical Network Process, Analytic Hierarchy Process and Fuzzy Analytic Hierarchy Process models were combined with Ordered Weighted Average, Weighted Linear Combination, Local Weighted Linear Combination models to prepare a flood risk map. The performance of two new models, Weighted Multi-Criteria Analysis and Geo-Technique for Order of Preference by Similarity to Ideal Solution, was also evaluated in this field. The results of the models showed that in general the basin is in a moderate risk situation. Meanwhile, the south-eastern parts of the basin show a high flood risk situation. Also, by comparing the models, it was found that the combination of multi-criteria models and the use of Weighted Multi-Criteria Analysis and Geo-Technique for Order of Preference by Similarity to Ideal Solution models are very effective and efficient for preparing flood risk maps.

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