Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 136 landside locations were constructed from various sources. Then the landslide inventory map was randomly split into a training dataset 70 % (95 landslide locations) for training the ANN model and the remaining 30 % (41 landslides locations) was used for validation purpose. Nine landslide conditioning factors such as slope, slope aspect, altitude, land use, lithology, distance from rivers, distance from roads, distance from faults, and rainfall were constructed in geographical information system. In this study, both MLP and RBF algorithms were used in artificial neural network model. The results showed that MLP with Broyden–Fletcher–Goldfarb–Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. The success rate curve showed that the area under the curve for RBF and MLP was 0.9085 (90.85 %) and 0.9193 (91.93 %) accuracy, respectively. Similarly, the validation result showed that the area under the curve for MLP and RBF models were 0.881 (88.1 %) and 0.8724 (87.24 %), respectively. The results of this study showed that landslide susceptibility mapping in the Vaz Watershed of Iran using the ANN approach is viable and can be used for land use planning.     

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.     

Bianchi type-I cosmological models with time dependent q and Λ-term in general relativity

On getting motivation from increasing evidence for the need of a geometry that resembles Bianchi morphology to explain the observed anisotropy in the WMAP data, Einstein’s field equations with variable cosmological “constant” are considered in presence of perfect fluid for a homogeneous and anisotropic Bianchi type-I space-time. Einstein’s field equations are solved by considering a time dependent deceleration parameter which affords a late time acceleration in the universe. The cosmological constant Λ is found to be a decreasing function of time and it approaches a small positive value at the present epoch which is corroborated by consequences from recent supernovae Ia observations. From recently developed Statefinder pair, the behavior of different stages of the evolution of the universe has been studied. The physical significance of the cosmological models have also been discussed.     

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.     

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.     

On the importance of satellite lines to the helium-like Kα complex and the G ratio for calcium, iron and nickel

New, more detailed calculations of the emission spectra of the He-like Kα complex of calcium, iron and nickel have been carried out using data from both distorted-wave and R-matrix calculations. The value of the GD ratio (an extended definition of the G ratio that accounts for the effect of resolved and unresolved satellite lines) is significantly enhanced at temperatures below the temperature of He-like maximum abundance. Furthermore, it is shown that satellite lines are important contributors to the GD ratio such that   GD / G > 1  at temperatures well above the temperature of maximum abundance. These new calculations demonstrate, with an improved treatment of the KLn     satellite lines, that Kα satellite lines need to be included in models of He-like spectra even at relatively high temperatures. The excellent agreement between spectra and line ratios calculated from R-matrix and distorted-wave data also confirms the validity of models based on distorted-wave data for highly charged systems, provided the effect of resonances is taken into account as independent processes.     

Trend analysis of evapotranspiration over India: Observed from long-term satellite measurements

Owing to the lack of consistent spatial time series data on actual evapotranspiration (ET), very few studies have been conducted on the long-term trend and variability in ET at a national scale over the Indian subcontinent. The present study uses biome specific ET data derived from NOAA satellite’s advanced very high resolution radiometer to investigate the trends and variability in ET over India from 1983 to 2006. Trend analysis using the non-parametric Mann–Kendall test showed that the domain average ET decreased during the period at a rate of \(0.22\,\hbox {mm year}^{-1}\). A strong decreasing trend (\(m = -1.75\, \hbox {mm year}^{-1}\), \(F = 17.41\), \(P\) 0.01) was observed in forest regions. Seasonal analyses indicated a decreasing trend during southwest summer monsoon (\(m= -0.320\, \hbox {mm season}^{-1}\,\hbox {year}^{-1})\) and post-monsoon period (\(m= -0.188\, \hbox {mm season}^{-1 }\,\hbox {year}^{-1})\). In contrast, an increasing trend was observed during northeast winter monsoon (\(m = 0.156 \,\hbox {mm season}^{-1 }\,\hbox {year}^{-1})\) and pre-monsoon (\(m = 0.068\, \hbox {mm season}^{-1 }\,\hbox {year}^{-1})\) periods. Despite an overall net decline in the country, a considerable increase ( \(4 \,\hbox {mm year}^{-1}\)) was observed over arid and semi-arid regions. Grid level correlation with various climatic parameters exhibited a strong positive correlation (\(r \!>\!0.5\)) of ET with soil moisture and precipitation over semi-arid and arid regions, whereas a negative correlation (\(r\) \(-0.5\)) occurred with temperature and insolation in dry regions of western India. The results of this analysis are useful for understanding regional ET dynamics and its relationship with various climatic parameters over India. Future studies on the effects of ET changes on the hydrological cycle, carbon cycle, and energy partitioning are needed to account for the feedbacks to the climate.     

Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR)

Landslide hazard, vulnerability, and risk-zoning maps are considered in the decision-making process that involves land use/land cover (LULC) planning in disaster-prone areas. The accuracy of these analyses is directly related to the quality of spatial data needed and methods employed to obtain such data. In this study, we produced a landslide inventory map that depicts 164 landslide locations using high-resolution airborne laser scanning data. The landslide inventory data were randomly divided into a training dataset: 70 % for training the models and 30 % for validation. In the initial step, a susceptibility map was developed using logistic regression approach in which weights were assigned to every conditioning factor. A high-resolution airborne laser scanning data (LiDAR) was used to derive the landslide conditioning factors for the spatial prediction of landslide hazard areas. The resultant susceptibility was validated using the area under the curve method. The validation result showed 86.22 and 84.87 % success and prediction rates, respectively. In the second stage, a landslide hazard map was produced using precipitation data for 15 years. The precipitation maps were subsequently prepared and show two main categories (two temporal probabilities) for the study area (the average for any day in a year and abnormal intensity recorded in any day for 15 years) and three return periods (15-, 10-, and 5-year periods). Hazard assessment was performed for the entire study area. In the third step, an element at risk map was prepared using LULC, which was considered in the vulnerability assessment. A vulnerability map was derived according to the following criteria: cost, time required for reconstruction, relative risk of landslide, risk to population, and general effect to certain damage. These criteria were applied only on the LULC of the study area because of lack of data on the population and building footprint and types. Finally, risk maps were produced using the derived vulnerability and hazard information. Thereafter, a risk analysis was conducted. The LULC map was cross-matched with the results of the hazard maps for the return period, and the losses were aggregated for the LULC. Then, the losses were calculated for the three return periods. The map of the risk areas may assist planners in overall landslide hazard management.     

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.     

Simultaneous inversion of the aftershock data of the 1993 Killari earthquake in Peninsular India and its seismotectonic implications

The aftershock sequence of the September 30th, 1993 Killari earthquake in the Latur district of Maharashtra state, India, recorded by 41 temporary seismograph stations are used for estimating 3-D velocity structure in the epicentral area. The local earthquake tomography (LET) method of Thurber (1983) is used. About 1500P and 1200S wave travel-times are inverted. TheP andS wave velocities as well asV _P/V_Sratio vary more rapidly in the vertical as well as in the horizontal directions in the source region compared to the adjacent areas. The main shock hypocentre is located at the junction of a high velocity and a low velocity zone, representing a fault zone at 6–7 km depth. The estimated average errors ofP velocity andV _P/V_Sratio are ±0.07 km/s and ±0.016, respectively. The best resolution ofP and S-wave velocities is obtained in the aftershock zone. The 3-D velocity structure and precise locations of the aftershocks suggest a ‘stationary concept’ of the Killari earthquake sequence.