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21.
Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features 总被引：1，自引：1，他引：0
One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors. 相似文献
22.
Mohammad Isazadeh Seyed Mostafa Biazar Afshin Ashrafzadeh 《Environmental Earth Sciences》2017,76(17):610
The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na+), and sulfate concentration (SO4 2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO4 2?, 1.05 mEq/l for Na+, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na+, K+, Ca2+, Mg2+, Cl?, SO4 2?, and HCO3 ?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs. 相似文献
23.
Alborz Mountains host Caspian Hyrcanian forest ecoregion along the northern slopes and forest steppe ecoregion in highlands. Hyrcanian forest covers the southeastern part of Caucasus biodiversity hotspot and is of great biogeographic importance. Altitudinal pattern and correlation between woody species biodiversity (DIV), forest structure ((stem density (DEN), mean basal area (MBA) and mean height class (MHC)) and disturbance (DIS) were explored along 2,400 m altitudinal gradient in Hyrcanian relict forest, Central Alborz Mountains. Vegetation changes from lowland forest (LoF) to mid- altitude forest (MiF) and montane forest (MoF) in this area. The altitudinal gradient was divided into twelve 200 m elevational belts. Point centered quarter method (PCQM) with 96 sampling points and 83 vegetation samples by plot method (PM) were used to record field data. Shannon-Wiener index and Pearson coefficient were used for diversity and correlation analysis. The results showed that DEN decreased linearly, MBA and MHC showed relatively hump shaped and DIS showed a reverse hump shaped pattern of change along altitudinal gradient. Woody species diversity decreased non-steadily from LoF to MoF. Transitional vegetations of Carpinus-Fagus and Fagus-Quercus represented higher diversity of woody taxa compared to adjacent homogenous communities. Significant correlation was observed between altitude and all parameters: DEN with MBA, DIS and DIV; MBA with DIS; MHC with DIS along with DIV; and DIS with DIV at the study area scale. Surprisingly,correlation between studied parameters differed within each vegetation type. Altitude probably acts as a proxy for human and environmental driving forces in this area. Stability of warm and wet condition, season length, soil depth along with forest accessibility probably influences the altitudinal pattern of the studied parameters. Disturbance affects forest structure and consequently diversity; especially in lowlands. The obtained results recommend using both forest biodiversity and mensuration data in management process of forest ecosystems. 相似文献
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The interaction effects of different applied ratios of a hydrophilic polymer (Superab A200) (0, 0.2, 0.6% w/w) under various soil salinity levels (initial salinity, 4 and 8 ms/cm) were evaluated on available water content (AWC), biomass, and water use efficiency for corn grown in loamy sand and sandy clay loam soils. The results showed that the highest AWC was measured at the lowest soil salinity. The application of 0.6% w/w of the polymer at the lowest salinity level increased the AWC by 2.2 and 1.2 times greater than those of control in the loamy sand and sandy clay loam soils, respectively. The analysis of variance of data showed that the effect of salinity was significant on biomass and water use efficiency of corn in the loamy sand and sandy clay loam soils. The highest amounts of these traits were measured in soils with the lowest salinity level. Application of polymer at the rate of 0.6% in the loamy sand soil and at the rate of 0.2% in the sandy clay loam soil resulted in the highest aerial and root biomass and water use efficiency for corn. At these polymer rates the amounts of water use efficiency for corn were 2.6 and 1.7 times greater than those of control in the loamy sand and sandy clay loam soils, respectively. Thus, the use of hydrophilic polymer in soils especially in the sandy soils increases soil water holding capacity, yield, and water use efficiency of plant. On the other hand, decreases the negative effect of soil salinity on plant and helps for irrigation projects to succeed in arid and semi‐arid areas. 相似文献
26.
Seyed Ahmad Meshkani Behzad Mehrabi Abdolmajid Yaghubpur Younes Fadakar Alghalandis 《Journal of Geochemical Exploration》2011
In regional exploration programs, the distribution of elements in known mineral deposits can be used as a guide for the classification of deposits, search for new prospects and modeling ore deposit patterns. The Sanandaj–Sirjan Zone (SSZ) is a major metallogenic zone in Iran, containing lead and zinc, iron, gold, copper deposits. In the central part of the SSZ, lead and zinc mineralization is widespread and hitherto exploration has been based on geological criteria. In this study, we used clustering techniques applied to element distribution for classification lead and zinc deposits in the central part of the SSZ. The hierarchical clustering technique was used to characterize the elemental pattern. Elements associated with lead and zinc deposits were separated into four clusters, encompassing both ore elements and their host rock-forming elements. It is shown that lead and zinc deposits in the central SSZ belong to two genetic groups: a MVT type hosted by limestone and dolomites and a SEDEX type hosted by shale, volcanic rocks and sandstone. The results of elemental clustering were used for pattern recognition by the K-means method and the respective deposits were classified into four distinct categories. K-means clustering also reveals that the elemental associations and spatial distribution of the lead and zinc deposits exhibit zoning in the central part of the SSZ. The ratios of ore-forming elements (Sb, Cd, and Zn) vs. (Pb and Ag) show zoning along an E–W trend, while host rock-forming elements (Mn, Ca, and Mg) vs. (Ba and Sr) show a zoning along a SE–NW trend. Large and medium deposits occur mainly in the center of the studied area, which justify further exploration around occurrences and abandoned mines in this area. The application of a pattern recognition method based on geochemical data from known mineralization in the central SSZ, and the classification derived from it, uncover elemental zoning, identify key elemental associations for further geochemical exploration and the potential to discover possible target areas for large to medium size ore deposits. This methodology can be applied in a similar way to search for new ore deposits in a wide range of known metallogenic zones. 相似文献
27.
Seyed Ali Mazhari Sadraldin Amini Jalil Ghalamghash Fernando Bea 《Arabian Journal of Geosciences》2011,4(7-8):1207-1214
The Naqadeh mafic plutonic rocks are located on a plutonic assemblage and include different granitoid rocks related to ～40 Ma. U-Pb SHRIMP data shows different ages of 96?±?2.3 Ma for mafic rocks. Naqadeh mafic plutonic rocks consist of diorite to diorite-gabbros with relatively high contents of incompatible elements, low Na2O, and $ {\hbox{Mg\# }} = \left[ {{\hbox{molar}}\;{100} \times {\hbox{MgO/}}\left( {{\hbox{MgO}} + {\hbox{FeO}}} \right)} \right] > 44.0 $ . These features suggest that the Naqadeh mafic rocks originate from enriched lithospheric mantle above subducted slab during Neotethys subduction under Iranian plate. 相似文献
28.
Sharifi Mortaza Tabatabaei Manesh Seyed Mohsen Safaei Homayon Karimi Somaye 《Geotectonics》2013,47(6):495-508
The metamorphic complex of the North Golpayegan is part of the Sanandaj-Sirjan Zone. There are at least three distinct stages of deformation in this complex. Throughout the first stage, Paleozoic and Mesozoic sedimentary rocks have experienced regional metamorphism during Late Jurassic tectonic events related to the subduction of the Neo-Tethys oceanic lithosphere under the Iranian microcontinent. During the second deformation stage in the Late Cretaceous-Paleocene, the rocks have been mylonitized. The third stage of deformation in the region has led to folding and faulting superimposed on previous structures, and to exhumation of the metamorphic complex. This stage has determined the current morphology and N70E strike of the complex. The mylonitic zones of the second stage of deformation have been formed along the dextral transpressional faults. During the third stage of deformation and exhumation of the metamorphic complex, the mylonitic zones have been uplifted to the surface. The granitoids in the metamorphic complex have been injected along the extensional shear fractures related to the dextral transpressional displacements. The granitoids have been transformed into mylonites within the synthetic or antithetic shear zones. These granitoids are recognized as syncollision type (CCG) and have been formed at the end of orogenic events synchronous to the collision between the Arabian and the Iranian plates at the Late Cretaceous-Paleocene. 相似文献
29.
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
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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