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Effective environmental factors in the distribution of vegetation types in Poshtkouh rangelands of Yazd Province (Iran) 总被引：1，自引：0，他引：1
M. Jafari M. A. Zare Chahouki A. Tavili H. Azarnivand Gh. Zahedi Amiri 《Journal of Arid Environments》2004,56(4):627
The objective of this research was to study the relationships between environmental factors and vegetation in order to find the most effective factors in the separation of the vegetation types in Poshtkou rangelands of Yazd province. Sampling of soil and vegetation were performed with randomized-systematic method. Vegetation data including density and cover percentage were estimated quantitatively within each quadrat, and using the two-way indicator species analysis (TWINSPAN), and vegetation was classified into different groups. The topographic conditions were recorded in quadrat locations. Soil samples were taken in 0–30 and 30–60 cm depths in each quadrat. The measured soil variables included texture, lime, saturation moisture, gypsum, acidity (pH), electrical conductivity, sodium absorption ratio, and soluble ions (Na+, K+, Mg2+, Cl−, CO32−, HCO3− and SO42−). Multivariate techniques including principal component analysis (PCA) and canonical correspondence analysis (CCA) were used to analyse the collected data. The results showed that the vegetation distribution pattern was mainly related to soil characteristics such as salinity, texture, soluble potassium, gypsum, and lime. Totally, considering the habitat conditions, ecological needs and tolerance range each plant species has a significant relation with soil properties. 相似文献
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Ali Jafari Mohammad Mehdi Ebadzadeh Reza Safabakhsh 《Journal of the Indian Society of Remote Sensing》2017,45(3):417-429
The normal compositional model (NCM) is a well-known and powerful model in hyperspectral unmixing which represents endmembers as independent Gaussian vectors to capture endmember variability. However, the assumption of independent endmembers diminishes the model accuracy because the high degree of correlation between endmembers of a scene and identical sources of variability demonstrate that the endmembers are dependent. This paper proposes a new hyperspectral unmixing algorithm which represents endmembers using dependent Gaussian vectors to estimate abundance fractions. To overcome the higher complexity caused by dependence assumption, this algorithm introduces new independent Gaussian vectors named Base Vectors to represent different endmembers by a weighted linear combination. Also, the proposed unmixing algorithm uses maximum likelihood method to estimate weight coefficients of Base Vectors which are used to represent mixed pixel. Finally, abundance estimation can be done using the new representation for endmembers and mixed pixel. The proposed algorithm is evaluated and compared with other state-of-the-art unmixing algorithms using simulated and real hyperspectral images. Experimental results demonstrate that the proposed unmixing algorithm can unmix pixels composed of correlated endmembers in hyperspectral images in the presence of spectral variability more accurately than previous methods. 相似文献
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Spectral unmixing estimates the abundance of each endmember at every pixel of a hyperspectral image. Each material in traditional unmixing algorithms is represented through a constant spectral signature. However, endmember variability always exists due to environmental, atmospheric, and temporal conditions, which leads to poor accuracy of the estimated abundances. This paper proposes a new unmixing algorithm based on a new linear transformation called endmember orthonormal mapping (EOM) to overcome the aforementioned problem. The EOM transformation maps original spectral space to a new EOM space to reduce endmember variability. In the original spectral space, each material is represented by a set of spectra (endmember set) which is extracted using the automated endmember bundles (AEB) method. The EOM transforms each endmember set to a vector in the EOM space so that these vectors are orthonormal. On account of orthonormalized endmembers, the condition number of the mixing matrix in the EOM space reduces. Furthermore, we consider the noise term as an additional virtual endmember set mapped to a vector that is orthogonal to other endmembers. As a result, a promising unmixing accuracy is obtained through applying the least squares abundance estimation in the subspace orthogonal to noise. Experimental results of both synthetic and real hyperspectral images demonstrate that the proposed algorithms provide much enhanced performance compared with the state-of-the-art algorithms. 相似文献
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Biological soil crust (BSC) restoration could effectively contribute in reducing several adverse environmental impacts such as soil erodibility. The usefulness of the microorganism constituent of the arid land (e.g., desert land cyanobacteria Microcoleus) for the BSC restoration has already been introduced, not only by laboratory studies but also by many other field investigations. In order to isolate the soil cyanobacteria with a potential to support BSC succession, soil samples from the southwestern dry lands in Iran were taken, soils serial dilution was prepared and submerged, and streaking-plate methods were applied. The newly isolated native cyanobacterium was identified as the Microcoleus on the genus level following the standard references. The isolated cyanobacterium was cultured phototrophically using five different media consisting of BBM, BG-11, F/2, Jourdan, and artificial wastewater submerged batch. Microcoleus spp. was found in all sites soil samples. The maximum biomass was achieved in the Jourdan submerged culture medium with an amount of 0.88 g/L. The cell density in this culture medium was increased up to 20 times of the initial cell density during 7 days of the cultivation. The specific biomass growth rate was calculated to be in a range of 0.03–0.057 per day. The preliminary experiments and reported restoration activities of Microcoleus submerged cultures were shown to have the potential for providing the soil with the inoculant for the restoration of the degraded arid lands such as Middle East region. 相似文献
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Zahra Yazdi Alireza Jafari Rad Mehraj Aghazadeh Peyman Afzal 《Journal of the Indian Society of Remote Sensing》2018,46(10):1581-1593
The Sonajeel prospect is located in the Arasbaran belt which is one of the significant copper mineralization belts in NW Iran. There are mostly Eocene volcano-sedimentary rocks and Post Eocene intrusive units which are the source for mineralization in the area. ASTER multispectral images were used for delineation of alteration zones as a key feature of porphyry copper mineralization. Due to the need for geometric correction and ortho-rectification of the ASTER images, a high resolution QuickBird image with pixel width of about 60 cm (in PAN) was employed as a reference image in order to boost the rectification process. Ortho-rectification has been done by using digital elevation model which is created by topographic map in scale 1:1000. Potassic alteration as one of the essential alteration types in porphyry copper deposits, distributed mostly in the north of the Sonajeel prospect that determined by Thermal infrared bands processing. Phyllic and argillic alteration zones detected by creating relative absorption band-depth grids which are comparable to field observations. Moreover, silica rich areas which are remnants of hydrothermal circulation and form at the top of porphyry copper systems were detected for recognition of epithermal deposits (with 1 km distance from Sonajeel porphyry system). Finally, Remote Sensing results were compared by field evidences especially for determination of an epithermal system. Most parts of the alteration zones were observed of the surface confirmed with the remote sensing alteration (in average about 75% matched fittingly), displayed concentrations anomalous in the NE and NW parts of the studied area. 相似文献
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Mohammad Ashtari Jafari 《Pure and Applied Geophysics》2012,169(9):1655-1661
Two medium-sized earthquakes occurred on 20 December 2010 and 27 January 2011 in Rigan County, Kerman Province, southeastern Iran. According to the dislocation grid search method results, the first event was nearly strike-slip including reverse component (strike 115°, dip 50°, and rake ?5°) whereas the second event had some amount of reverse component (strike 125°, dip 75°, and rake ?5°). Based on synthetic Green’s function deconvolution and aftershock distribution, the down-dip-propagated rupture migrated toward southeast districts with low population distribution, confirming the reason for low casualties. Meanwhile, the aftershock distribution indicates the existence of a new earthquake fault for which we suggest the name “Rigan earthquake fault.” However, the same aftershock distribution indicates that the second mainshock was inevitably triggered by the first one, most probably along the continuation of the Bam earthquake fault. 相似文献
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