Pseudostatic approach for seismic analysis of pile group

This paper evaluates a simple approximate pseudostatic method for estimating the maximum internal forces and horizontal displacements of pile group subjected to lateral seismic excitation. The method involves two main steps: (1) computation of the free-field soil movements caused by the earthquake, and (2) the analysis of the response of the pile group based on the maximum free-field soil movements (considered as static movements) as well as a static loading at the pile head, which depends on the computed spectral acceleration of the structure being supported. The methodology takes into account the effects of group interaction and soil yielding at pile–soil interface. The applicability of this approach has been validated by a similar approach for single piles and then verified by both experimental centrifuge models of pile-supported structures and field measurements of Ohba-Ohashi Bridge in Japan. It is demonstrated that the proposed method yields reasonable estimates of the pile maximum moment, shear, and horizontal displacement for many practical cases despite of its simplicity. Limitations and reliability of the methodology are discussed and some practical conclusions on the performance of the proposed approach are presented.     

Integrating cellular automata,artificial neural network,and fuzzy set theory to simulate threatened orchards: application to Maragheh,Iran

Urbanization processes challenge the growth of orchards in many cities in Iran. In Maragheh, orchards are crucial ecological, economical, and tourist sources. To explore orchards threatened by urban expansion, this study first aims to develop a new model by coupling cellular automata (CA) and artificial neural network with fuzzy set theory (CA–ANN–Fuzzy). While fuzzy set theory captures the uncertainty associated with transition rules, the ANN considers spatial and temporal nonlinearities of the driving forces underlying the urban growth processes. Second, the CA–ANN–Fuzzy model is compared with two existing approaches, namely a basic CA and a CA coupled with an ANN (CA–ANN). Third, we quantify the amount of orchard loss during the last three decades as well as for the upcoming years up to 2025. Results show that CA–ANN–Fuzzy with 83% kappa coefficient performs significantly better than conventional CA (with 51% kappa coefficient) and CA–ANN (with 79% kappa coefficient) models in simulating orchard loss. The historical data shows a considerable loss of 26% during the last three decades, while the CA–ANN–Fuzzy simulation reveals a considerable future loss of 7% of Maragheh’s orchards in 2025 due to urbanization. These areas require special attention and must be protected by the local government and decision-makers.     

Validating gap-filling of Landsat ETM+ satellite images in the Golestan Province,Iran

The Landsat series of satellites provides a valuable data source for land surface mapping and monitoring. Unfortunately, the scan line corrector (SLC) of the Landsat7 Enhanced Thematic Mapper plus (ETM+) sensor failed on May 13, 2003. This problem resulted in about 22 % of the pixels per scene not being scanned and has seriously limited the scientific applications of ETM+ data. A number of methods have been developed to fill the gaps in the incorrect images. Most of these methods have problems in heterogeneous landscapes. We applied and validated a simple and effective gap-fill algorithm developed by the US Geological Survey to a study area in the Golestan Province in the north of Iran. This algorithm operates under the assumption that the same-class neighboring pixels around the unscanned pixels have similar spectral characteristics, and that these neighboring and unscanned pixels share patterns of spectral differences between dates. For validation, unsupervised land use classification was performed on both gap-filled SLC-off data and the original “sound” data set. Classification results and accuracies were very comparable.     

GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran,Iran)

The aim of this study is to produce landslide susceptibility mapping by probabilistic likelihood ratio (PLR) and spatial multi-criteria evaluation (SMCE) models based on geographic information system (GIS) in the north of Tehran metropolitan, Iran. The landslide locations in the study area were identified by interpretation of aerial photographs, satellite images, and field surveys. In order to generate the necessary factors for the SMCE approach, remote sensing and GIS integrated techniques were applied in the study area. Conditioning factors such as slope degree, slope aspect, altitude, plan curvature, profile curvature, surface area ratio, topographic position index, topographic wetness index, stream power index, slope length, lithology, land use, normalized difference vegetation index, distance from faults, distance from rivers, distance from roads, and drainage density are used for landslide susceptibility mapping. Of 528 landslide locations, 70 % were used in landslide susceptibility mapping, and the remaining 30 % were used for validation of the maps. Using the above conditioning factors, landslide susceptibility was calculated using SMCE and PLR models, and the results were plotted in ILWIS-GIS. Finally, the two landslide susceptibility maps were validated using receiver operating characteristic curves and seed cell area index methods. The validation results showed that area under the curve for SMCE and PLR models is 76.16 and 80.98 %, respectively. The results obtained in this study also showed that the probabilistic likelihood ratio model performed slightly better than the spatial multi-criteria evaluation. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.     

Evaluation of Air Pollution Trend Using GIS and RS Applications in South West of Iran

In this paper, remote sensing and GIS have been used to assess the status of NO₂ at the south west of Iran. 221 data about concentration of NO₂ was extracted from Ozone Monitoring Instrument. Ordinary kriging and inverse distance weighting interpolation methods was used to interpolate data. Results showed that ordinary kriging method using cross-validation have had less error. North east of the study area has the highest concentration of NO₂ (329 molecule/cm²) and the concentration of NO₂ decreases from north east to South west of the study area. On the other hand, data trend results showed that the data seems to exhibit a fairly strong trend in the east west direction and a weaker one in the north–south direction.     

Evaluation of Almond (Amygdalus Scopartia) Habitat Using Multi-criteria Decision Making Method

Bolhasan Forest region with an area of 5,725?ha is located on east north of Dezful County, Iran. The region belongs to natural forests of Dezful. Considering the area is mainly covered by valuable species of Amygdalus Scopartia, its sustainable exploitation and development as well as restoration enjoys great importance. Study ahead aims at selection of suitable habitats for under studied species using Analytical Hierarchy Process (AHP). Therewith, the required thematic maps were imported in to GIS Software and final suitability map was prepared. The results indicated that around 2,119?ha (37%) out of all study area has high suitability for habitat of Amygdalus Scopartia. In the meanwhile, 1,603?ha [equal to 28%] is categorized as good suitability class and 2,003?ha [35%] has poor suitability.     

A depth average SPH model including μ(I) rheology and crushing for rock avalanches

Classical depth-integrated smoothed particle hydrodynamics (SPH) models for avalanches are extended in the present work to include a μ(I)− rheological model enriched with a fragmentation law. With this improvement, the basal friction becomes grain distribution dependent. Rock avalanches, where grain distribution tends to change with time while propagating, are the appropriate type of landslide to apply the new numerical proposal. The μ(I)− rheological models considered in the present work are those of Hatano and Gray, combined with two different fragmentation laws, a hyperbolic and a fractal-based law. As an application, Frank avalanche, which took place in Canada in 1903, is analyzed under the scope of the present approach, focusing in the influence of the rheological and fragmentation laws in the evolution of the avalanche.     

Modeling and assessing the effects of land use changes on runoff generation with the CLUE-s and WetSpa models

Theoretical and Applied Climatology - Land use change is an important determinant of hydrological processes and is known to affect hydrological parameters such as runoff volume, flood frequency,...