Lake Neor reveals how mountain vegetation responded to 7000 years of hydroclimate variability in northwestern Iran

Palynological and geochemical analyses provide valuable information about modern and past climatic regimes and vegetation. The impact of climate and humans on past vegetation in the semi-arid areas of northwestern Iran has received increased interest in the wake of warming temperatures in the Middle East. Palynological and down-core XRF elemental abundances from a peat core from Lake Neor enabled a reconstruction of vegetational changes of the past 7000 years over the highlands of northwestern Iran. Periods of increased arboreal pollen (AP) types and high (Artemisia + Poaceae)/Chenopodiaceae ratios along with low titanium abundances, high percentages of total organic carbon, more negative δD values, and higher carbon accumulation rates suggest a relatively wet climate. These conditions have persisted during the periods 6700–6200, 5200–4450 and 3200–2200 cal a bp. The overall low AP values, substantial rise of Chenopodiaceae, high Ti abundances and low values of palaeo-redox proxies, are all evidences of a drier climate, as has been reconstructed for the periods 6200–5200 and 4030–3150 cal a bp and the last 2200 years. An important feature of the last centuries is the increase of anthropogenic and pastoral indicator pollen types. Our results may provide basic data to predict future trends in vegetation dynamics under future climate change in western Asia.     

Monitoring of dust storm and estimation of aerosol concentration in the Middle East using remotely sensed images

Arabian Journal of Geosciences - Dust storms are one of the major environmental disasters in the arid regions of Middle East, occurring in very high frequency. As a result, monitoring dust storms...     

MATLAB programs for the synthetic models

The separation of residual gravity anomaly from regional gravity has considerably been studied for many years in gravity explorations. In addition, it is considered as a critical step in gravity data inversion. Some techniques have been developed for regional–residual anomaly separation both in space and frequency domains. One of these techniques for computing the regional anomaly is nonlinear filtering. In this paper, some techniques such as low-pass filtering, Butterworth, upward continuation, and nonlinear filtering are used to on synthetic gravity data in present of random noise and noise free for the purpose of residual–regional anomaly separation. The obtained results of techniques are compared with each other. The results have shown that separation methods are so efficient where synthetic models are located in shallow depth. Moreover, it is found that in comparison with other separation techniques, nonlinear filtering is more efficient in residual–regional anomaly separation and upward continuation technique is more efficient than Butterworth filter and low-pass filter. In addition, all of the obtained results have shown that Butterworth and low-pass filters are the same.     

Prospecting for Clinoptilolite-Type Zeolite in a Volcano-Sedimentary Terrain Using ASTER Data: A Case Study from Alborz Mountains,Northern Iran

Zeolites are hydrated alumino-silicates of alkali metals and alkaline earth cations which occur in sedimentary and volcano-sedimentary terrains. In this study, visible–near-infrared and shortwave infrared data of ASTER were evaluated in prospecting for zeolite in part of the green tuff belt of the Alborz Mountains, northern Iran. The study area is dominantly covered by sedimentary and volcano-sedimentary rocks, in which zeolite minerals occur only in the Late Eocene vitric tuff. Principal components (PC) analysis and spectral information divergence (SID) were used to discriminate and map the sedimentary and volcano-sedimentary units and the zeolite-rich areas, respectively. The X-ray diffraction and reflectance spectroscopy results indicated that clinoptilolite is the major type of zeolite mineral in this area. Comparing a color composite image, produced from PC images 1–3–5 as R–G–B, with the published geological map and the field investigations indicated that major sedimentary and volcano-sedimentary units as well as their alluvial deposits were discriminated efficiently. Results of the SID method, using an image-derived spectrum of clinoptilolite as a reference, showed good agreements with the field observations. The results of this study indicated that ASTER data are useful for discriminating various sedimentary and volcano-sedimentary units as well as clinoptilolite-type zeolite-rich areas in arid and semiarid terrains.