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31.
The main objective of the science of phenology is to identify the time of the occurrence of conspicuous periodic phenomena in plants under the impact of climatic factors. The study of phonologic phenomena through visual observations and terrestrial studies and temperature registration using a thermo hydrometer in different altitudinal levels and using the satellite data of IRS1C/1D LISSIII in twelve 1-ha plots in pure beech stands in the altitudinal range of 500 to 1,200 m above the sea level from April to December was carried out in such a way that for each month, one image of sensor was allocated. The produced vegetation indices were matched with terrestrial observations of the phenology periods in each month in the beech plots. The results show that the increase of the altitude above the sea level functions like latitude and its most remarkable impact is the decreasing of the temperature and the shortening of growing season. The terrestrial observations carried out in the plots show that a sudden increase in the temperature leads to the faster growth and emergence of the leaves. The produced correlation coefficient between the temperature and the emergence of the leaves was (p?=?0.01) r?=?0.87. Moreover, the end of fall in the studied region has a direct and significant relation with temperature. The amount of correlation coefficient between the temperature and end of fall in the studied region is equal to (p?=?0.01) r?=?0.91. Normalized difference vegetation index (NDVI) is more related to the growth and nurturing of the leaves. The amount of NDVI during the growth of the leaves, completion of the leaves, and fall of the leaves is equal to 0.35, 0.6, and 0.25, respectively. 相似文献
32.
Seyed Armin Hashemi Mir Mozaffar Fallah Chai Shohreh Bayat 《Arabian Journal of Geosciences》2013,6(9):3363-3369
Vegetation indices have been introduced for analyzing and assessing the status of quantitative and qualitative characteristics of vegetation using satellite images. However, choosing the best indices to be used in forest biodiversity and vegetation is one of the important problems faced by the users. The purpose of this research is to evaluate six vegetation indices in the analysis of tree species diversity in the northern forests of Iran. The present research uses LISS III sensor data from IRS-P6 satellite. Geometric rectification of images was performed using ground control points, and Chavez model was used for atmospheric correction of the data. The six spectral vegetation indices included NDVI, IPVI, Ashburn Vegetation Index (AVI), TVI, TTVI, and RVI. Shannon–Wiener species diversity index was used to analyze diversity, and the value of the index was calculated in each sample plot. Then, the spectral values of each sample plot were extracted from different bands. The best subset regression was used to analyze the relationship between species diversity and the related bands. The results obtained from the regression showed that polynomial equations under scrutiny as independent variables can assess tree and shrub species diversity better than other bands and compounds used (R 2?=?0.47). The obtained results also indicated a higher capacity in the case of the AVI index for estimating tree species diversity in the under study area. 相似文献
33.
Calibration of the specific barrier model to Iranian plateau earthquakes and development of physically based attenuation relationships for Iran 总被引：1，自引：0，他引：1
H. Zafarani M. Mousavi As. Noorzad A. Ansari 《Soil Dynamics and Earthquake Engineering》2008,28(7):550-576
Earthquake ground-motion relationships for soil and rock sites in Iran have been developed based on the specific barrier model (SBM) used within the context of the stochastic modeling and calibrated against up-to-date Iranian strong-motion data. A total of 171 strong-motion accelerograms recorded at distances of up to 200 km from 24 earthquakes with moment magnitudes ranging from Mw 5.2 to 7.4 are used to determine the region-specific source parameters of this model. Regression analysis was conducted using the “random effects” methodology that considers both earthquake-to-earthquake (inter-event) variability and within-earthquake (intra-event) variability to effectively handle the problem of weighting observations from different earthquakes. The minimization of the error function in each iteration of the “random effects” procedure was performed using the genetic algorithm method. The residuals are examined against available Iranian strong-motion data to confirm that the model predictions are unbiased and that there are no significant residual trends with distance and magnitude. No evidence of self-similarity breakdown is observed between the source radius and its seismic moment. To verify the robustness of the results, tests were performed to confirm that the results are unchanged if the number of observations is changed by removing different randomly selected datasets from the original database. Stochastic simulations, using the derived SBM, are then performed to predict peak ground-motion and response spectra parameters for a wide range of magnitudes and distances. The stochastic SBM predictions agree well with the new empirical regression equations proposed for Iran, Europe and Middle East in the magnitude–distance ranges well represented by the data. It has been shown that the SBM of this study provides unbiased ground-motion estimates over the entire frequency range of most engineering interests (1–10 Hz) for the Iranian earthquakes. Our results are also important for the assessment of hazards in other seismically active environments in the Middle East and Mediterranean regions. 相似文献
34.
Najmeh?Khalili Saeed?Reza?KhodashenasEmail author Kamran?Davary Mohammad?Mousavi?Baygi Fatemeh?Karimaldini 《Arabian Journal of Geosciences》2016,9(13):624
In this paper, we have utilized ANN (artificial neural network) modeling for the prediction of monthly rainfall in Mashhad synoptic station which is located in Iran. To achieve this black-box model, we have used monthly rainfall data from 1953 to 2003 for this synoptic station. First, the Hurst rescaled range statistical (R/S) analysis is used to evaluate the predictability of the collected data. Then, to extract the rainfall dynamic of this station using ANN modeling, a three-layer feed-forward perceptron network with back propagation algorithm is utilized. Using this ANN structure as a black-box model, we have realized the complex dynamics of rainfall through the past information of the system. The approach employs the gradient decent algorithm to train the network. Trying different parameters, two structures, M531 and M741, have been selected which give the best estimation performance. The performance statistical analysis of the obtained models shows with the best tuning of the developed monthly prediction model the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are 0.93, 0.99, and 6.02 mm, respectively, which confirms the effectiveness of the developed models. 相似文献
35.
Ashraf Samaneh AghaKouchak Amir Nazemi Ali Mirchi Ali Sadegh Mojtaba Moftakhari Hamed R. Hassanzadeh Elmira Miao Chi-Yuan Madani Kaveh Mousavi Baygi Mohammad Anjileli Hassan Arab Davood Reza Norouzi Hamid Mazdiyasni Omid Azarderakhsh Marzi Alborzi Aneseh Tourian Mohammad J. Mehran Ali Farahmand Alireza Mallakpour Iman 《Climatic change》2019,152(3-4):379-391
Climatic Change - By combining long-term ground-based data on water withdrawal with climate model projections, this study quantifies the compounding effects of human activities and climate change... 相似文献
36.
Saeid Pourmorad Harami Reza Mousavi Solgi Ali Aleali Mohsen 《Lithology and Mineral Resources》2021,56(1):89-112
Lithology and Mineral Resources - The alluvial-fan sediments play a very important role in mineral reserves and underground water resources, though a comprehensive study on such sediments,... 相似文献
37.
This study focuses on the evaluation of 3-hourly 0.25° × 0.25° satellite-based rainfall estimates produced by the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA). The evaluation is performed during six heavy rainfall events that were generated by tropical storms passing over Louisiana, United States. Two surface-based rainfall datasets from gauge and radar observations are used as a ground reference for evaluating the real-time (RT) version of the TMPA product and the post-real-time bias adjusted research version. The evaluation analysis is performed at the native temporal and spatial scales of the TMPA products, 3-hourly and 0.25° × 0.25°. Several graphical and statistical techniques are applied to characterize the deviation of the TMPA estimates from the reference datasets. Both versions of the TMPA products track reasonably well the temporal evolution and fluctuations of surface rainfall during the analyzed storms with moderate to high correlation values of 0.5–0.8. The TMPA estimates reported reasonable levels of rainfall detection especially when light rainfall rates are excluded. On a storm scale, the TMPA products are characterized by varying degrees of bias which was mostly within ± 25% and ± 50% for the research and RT products, respectively. Analysis of the error distribution indicated that, on average, the TMPA products tend to overestimate small rain rates and underestimate large rain rates. Compared to the real-time estimates, the research product shows significant improvement in the overall and conditional bias, and in the correlation coefficients, with slight deterioration in the probability of detecting rainfall occurrences. A fair agreement in terms of reproducing the tail of the distribution of rain rates (i.e., probability of surface rainfall exceeding certain thresholds) was observed especially for the RT estimates. Despite the apparent differences with surface rainfall estimates, the results reported in this study highlight the TMPA potential as a valuable resource of high-resolution rainfall information over many areas in the world that lack capabilities for monitoring landfalling tropical storms. 相似文献
38.
Zinc extraction from Iranian low-grade complex zinc–lead ore by two native microorganisms: Acidithiobacillus ferrooxidans and Sulfobacillus 总被引：2，自引：0，他引：2
S.M. Mousavi S. Yaghmaei M. Vossoughi A. Jafari R. Roostaazad 《International Journal of Mineral Processing》2006,80(2-4):238-243
A mesophilic iron oxidizing bacterium, Acidithiobacillus ferrooxidans, has been isolated (33 °C) from a typical, chalcopyrite concentrate of the Sarcheshmeh copper mine in the region of Kerman located in the south of Iran. In addition, a thermophilic iron oxidizing bacterium, Sulfobacillus, has been isolated (60 °C) from the sphalerite concentrate of Kooshk lead and zinc mine near the city of Yazd in the center point of Iran. Variation of pH, ferrous and ferric concentration on time and effects of some factors such as temperature, cell growth, initial ferrous concentration and pH on bioleaching of low-grade complex zinc–lead ore were investigated. The results obtained from bioleaching experiments indicate that the efficiency of zinc extraction is dependent on all of the mentioned variables; especially the temperature and initial Fe(II) concentration have more effect than other factors for these microorganisms. In addition, results show that the maximum zinc recovery was achieved using a thermophilic culture. Zinc dissolution reached 58% with Sulfobacillus while it was 51% with A. ferrooxidans at pH = 1.5, initial Fe(II) concentration = 7 and 9 g/L for A. ferrooxidans and Sulfobacillus, respectively, after 30 days. 相似文献
39.
It is known that construction of large sewers based on consideration of flow with non-deposition without a bed deposit is not economical. Sewer design based on consideration of flow with non-deposition with a bed deposit reduces channel bed slope and construction cost in which the presence of a small depth of sediment deposition on the bed increases the sediment transport capacity of the flow. This paper suggests a new Pareto-optimal model developed by the multigene genetic programming (MGGP) technique to estimate particle Froude number (Frp) in large sewers with conditions of sediment deposition on the bed. To this end, four data sets including wide ranges of sediment size and concentration, deposit thickness, and pipe size are used. On the basis of different statistical performance indices, the efficiency of the proposed Pareto-optimal MGGP model is compared to those of the best MGGP model developed in the current study as well as the conventional regression models available in the literature. The results indicate the higher efficiency of the MGGP-based models for Frp estimation in the case of no additional deposition onto a bed with a sediment deposit. Inasmuch as the Pareto-optimal MGGP model utilizes a lower number of input parameters to yield comparatively higher performance than the conventional regression models, it can be used as a parsimonious model for self-cleansing design of large sewers in practice. 相似文献
40.
Imtiyaz A. Parvez Andrea Magrin Franco Vaccari Ashish Ramees R. Mir Antonella Peresan Giuliano Francesco Panza 《Journal of Seismology》2017,21(6):1559-1575
Current computational resources and physical knowledge of the seismic wave generation and propagation processes allow for reliable numerical and analytical models of waveform generation and propagation. From the simulation of ground motion, it is easy to extract the desired earthquake hazard parameters. Accordingly, a scenario-based approach to seismic hazard assessment has been developed, namely the neo-deterministic seismic hazard assessment (NDSHA), which allows for a wide range of possible seismic sources to be used in the definition of reliable scenarios by means of realistic waveforms modelling. Such reliable and comprehensive characterization of expected earthquake ground motion is essential to improve building codes, particularly for the protection of critical infrastructures and for land use planning. Parvez et al. (Geophys J Int 155:489–508, 2003) published the first ever neo-deterministic seismic hazard map of India by computing synthetic seismograms with input data set consisting of structural models, seismogenic zones, focal mechanisms and earthquake catalogues. As described in Panza et al. (Adv Geophys 53:93–165, 2012), the NDSHA methodology evolved with respect to the original formulation used by Parvez et al. (Geophys J Int 155:489–508, 2003): the computer codes were improved to better fit the need of producing realistic ground shaking maps and ground shaking scenarios, at different scale levels, exploiting the most significant pertinent progresses in data acquisition and modelling. Accordingly, the present study supplies a revised NDSHA map for India. The seismic hazard, expressed in terms of maximum displacement (Dmax), maximum velocity (Vmax) and design ground acceleration (DGA), has been extracted from the synthetic signals and mapped on a regular grid over the studied territory. 相似文献