Mg VIII DIAGNOSTIC LINE RATIOS IN SKYLAB SOLAR OBSERVATIONS

Recent calculations of Mgviii electron and proton impact excitations rates are used to derive theoretical electron temperature (T _e)- and density (N _e)-sensitive emission line ratios involving transitions in the 315–782 Å wavelength range. Some of these ratios are presented in the form of ratio–ratio diagrams, which should in principle allow both N _e and T _e to be deduced. These results are compared with solar observational data from Skylab, but agreement between theory and observation is very poor, probably due to blending.     

Magnetized string cosmological model in cylindrically symmetric inhomogeneous universe-revisited

Cylindrically symmetric inhomogeneous magnetized string cosmological model is investigated. The source of the magnetic field is due to an electric current produced along x-axis. F ₂₃ is the only non-vanishing component of electromagnetic field tensor. To get the deterministic solution, it has been assumed that the expansion (θ) in the model is proportional to the eigen value σ ₁ ¹ of the shear tensor σ _j ⁱ . The physical and geometric properties of the model are also discussed in presence and absence of magnetic field.     

Landslide susceptibility mapping of a catchment area using frequency ratio,fuzzy logic and multivariate logistic regression approaches

Geospatial database creation for landslide susceptibility mapping is often an almost inhibitive activity. This has been the reason that for quite some time landslide susceptibility analysis was modelled on the basis of spatially related factors. This paper presents the use of frequency ratio, fuzzy logic and multivariate regression models for landslide susceptibility mapping on Cameron catchment area, Malaysia, using a Geographic Information System (GIS) and remote sensing data. Landslide locations were identified in the study area from the interpretation of aerial photographs, high resolution satellite images, inventory reports and field surveys. Topographical, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing tools. There were nine factors considered for landslide susceptibility mapping and the frequency ratio coefficient for each factor was computed. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land cover from TM satellite image; the vegetation index value from Landsat satellite images; and precipitation distribution from meteorological data. Using these factors the fuzzy membership values were calculated. Then fuzzy operators were applied to the fuzzy membership values for landslide susceptibility mapping. Further, multivariate logistic regression model was applied for the landslide susceptibility. Finally, the results of the analyses were verified using the landslide location data and compared with the frequency ratio, fuzzy logic and multivariate logistic regression models. The validation results showed that the frequency ratio model (accuracy is 89%) is better in prediction than fuzzy logic (accuracy is 84%) and logistic regression (accuracy is 85%) models. Results show that, among the fuzzy operators, in the case with “gamma” operator (λ = 0.9) showed the best accuracy (84%) while the case with “or” operator showed the worst accuracy (69%).     

A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf

Diffuse attenuation coefficient (k _d ) is a critical parameter for benthic habitat mapping using remotely sensed data. This research attempted to develop a new approach to estimate k _d in blue and green bands of QuickBird satellite image based on the integration of Lyzenga’s method and updated NASA-k _d ⁴⁹⁰ algorithm. To do this, the Lyzenga’s method was utilized to determine the ratio of k _d in different bands of QuickBird satellite image. Additionally, NASA-k _d ⁴⁹⁰ algorithm was applied to determine k _d ⁴⁹⁰ by using remotely sensed reflectance values of blue (R _rs ^Blue ) and green (R _rs ^Green ) bands in each pixel of QuickBird satellite image. Since the aforementioned algorithm has been developed for other types of sensors, an approach using weighted mean value of parameters for SeaWiFS, MERIS, VIIRS, and OCTS sensors were employed to estimate parameter values for QuickBird image. After determining the k _d ⁴⁹⁰ values as k _d for blue band, the k _d values for green and red bands were subsequently obtained by using Lyzenga’s method. Then, Mumby and Edwards’ method was employed as evidence to evaluate the accuracy of the results achieved from newly developed approach. Eventually, the maximum likelihood classifier was implemented during pre and post correction steps to examine the capability of the proposed approach. The final results proved to be consistent in the areas deeper than 2 m between estimated k _d values using the proposed approach and the results obtained from Mumby and Edwards’ method. On the other hand, the values estimated for extremely shallow areas seem to be overestimated. Furthermore, results demonstrated an increment of ~16 % in the overall accuracy of the classification.     

An Integrated GIS Based Statistical Model to Compute Groundwater Vulnerability Index for Decision Maker in Agricultural Area

The conservation areas in a plain are affected by the groundwater contamination from intense application of the fertilizers. The vulnerability of groundwater can be tested by using the DRASTIC model for the pollutants. The groundwater susceptibility to pollution in the various areas is mapped through DRASTIC model. However, the effects of pollution types and its characteristics are not considered, as this model is used without any modifications. This technique must be standardized for usage in the various aquifers and specific pollution types. The rates of DRASTIC parameters are corrected to obtain the potential for a more accurate analysis of the vulnerability pollution. The relationships between the parameters are identified with respect to the nitrate concentration in the groundwater by calculating the new rates. The methodology was applied to the selected area situated in the south eastern region of Iran at Kerman plain. Twenty-seven different locations were selected to test and analyse the nitrate concentration in the water from underground wells. The pollution in the aquifer was associated and correlated with the DRASTIC index by using the measured nitrate concentrations. The relationship between the index and the measured pollution in the Kerman plain was determined by applying the Wilcoxon rank-sum nonparametric statistical tests and the rates were calculated. It was found specifically in the agricultural areas that the modified DRASTIC model performed more efficiently than the traditional method for nonpoint source pollution, as indicated by the results. After modifications, the regression coefficients revealed that the relationship between the vulnerability index and the nitrate concentration was 77 %, while it was 37 % before the modifications were used. These statistics show that the modified DRASTIC performed far more efficiently than the original version.     

Land suitability analysis for cereal production in Himachal Pradesh (India) using Geographical Information System

Land suitability analysis is prerequisite for sustainable agriculture and it plays a pivotal role in the niche based agricultural planning in mountain regions. In this paper different parameters viz. climatic (precipitation and temperature), topographic (elevation), soil type and land cover/land use have been used in order to perform land suitability evaluation for cereals food-grain crops in Himachal Pradesh using Geographic Information System (GIS). The suitability analysis was performed by digital processing of geo-referenced data (elevation, climate, soil and landcover) and calculating potential production areas by combining different types of geographical data through decision rules framed for each crop in ArcView spatial analyst. Suitable areas have been delineated for cereal crops in the form of land suitability maps. In comparison to the actual area under cereal crops, the possibility of further expansion under each cereal crop was determined. These discriminated areas appear suitable for growing these crops and can be harnessed efficiently for achieving long term sustainability and food security.     

Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran

The main goal of this study was to investigate the application of the weights-of-evidence and certainty factor approaches for producing landslide susceptibility maps of a landslide-prone area (Haraz) in Iran. For this purpose, the input layers of the landslide conditioning factors were prepared in the first stage. The landslide conditioning factors considered for the study area were slope gradient, slope aspect, altitude, lithology, land use, distance from streams, distance from roads, distance from faults, topographic wetness index, stream power index, stream transport index and plan curvature. For validation of the produced landslide susceptibility maps, the results of the analyses were compared with the field-verified landslide locations. Additionally, the receiver operating characteristic curves for all the landslide susceptibility models were constructed and the areas under the curves were calculated. The landslide locations were used to validate results of the landslide susceptibility maps. The verification results showed that the weights-of-evidence model (79.87%) performed better than certainty factor (72.02%) model with a standard error of 0.0663 and 0.0756, respectively. According to the results of the area under curve evaluation, the map produced by weights-of-evidence exhibits satisfactory properties.     

An effective visualization and comparison of online terrain draped with multi-sensor satellite images

The objective of this paper is to discuss the effectiveness of visualizing online 3D terrain draped with different satellite imageries. The topographic data of the study area were obtained from the contour maps of Universiti Putra Malaysia, Selangor, Malaysia. The high resolution satellite imageries used in this project involving QUICKBIRD (0.6 m resolution), IKONOS (1 m resolution), and SPOT5 (5 m resolution). R2V software was used for editing the contour data, whereas Arc GIS was used for overlaying the imageries over the 3D terrain data. Then the data were exported into Virtual Reality Markup Language to compare the effectiveness of different satellite imageries based on the data file size, imageries size, number of images tile, loading time during office hours (from 8 a.m. to 5 p.m.) and out of office hours (after 5 p.m.), frame rate per second, and visualization quality. The results revealed that IKONOS satellite imageries are better for an effective online 3D terrain visualization utilizing GIS data even though it has lower resolution compared to QUICKBIRD.     

Relative effect method of landslide susceptibility zonation in weathered granite soil: a case study in Deokjeok-ri Creek,South Korea

The objective of this study was to produce and evaluate a landslide susceptibility map for weathered granite soils in Deokjeok-ri Creek, South Korea. The relative effect (RE) method was used to determine the relationship between landslide causative factors (CFs) and landslide occurrence. To determine the effect of CFs on landslides, data layers of aspect, elevation, slope, internal relief, curvature, distance to drainage, drainage density, stream power index, sediment transport index, topographic wetness index, soil drainage character, soil type, soil depth, forest type, timber age, and geology were analyzed in a geographical information system (GIS) environment. A GIS-based landslide inventory map of 748 landslide locations was prepared using data from previous reports, aerial photographic interpretation, and extensive field work. A RE model was generated from a training set consisting of 673 randomly selected landslides in the inventory map, with the remaining 75 landslides used for validation of the susceptibility map. The results of the analysis were verified using the landslide location data. According to the analysis, the RE model had a success rate of 86.3 % and a predictive accuracy of 88.6 %. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations. The results of this study can therefore be used to mitigate landslide-induced hazards and to plan land use.