Spatial–temporal analysis of the shoreline change rate using automatic computation and geospatial tools along the Tetouan coast in Morocco

Natural Hazards - Analyzing and understanding coastline variability and dynamics are important for scientists and policy-makers. This study investigates the long-term process of shoreline change...     

Community and psychological barriers to tsunami preparation

Tsunami risk was investigated as a platform for helping to understand the impact of community and psychological factors in natural disaster preparedness. Residents who lived within four meters of sea level in high and moderate tsunami risk areas of Vancouver Island were queried about possible influences on their preparation. Both community-level and psychological factors played significant roles. More community participation and fewer justifications for not preparing (the dragons of inaction) directly predicted reported preparation. The relation between sense of community and preparation was mediated by the level of community participation, and the relation between positive outcome expectancy and preparation was mediated by the dragons of inaction. Together, the resulting model accounted for 21% of the variance in reported tsunami preparation. Policy implications are discussed.

     

Correlation of lineaments and groundwater quality in Dasht-e-Arjan Fars,SW of Iran

The NE-oriented Dasht-e-Arjan graben is located 65 km west of Shiraz and has resulted from the active Kare-e-Bas fault segmentations. This extensional graben bounded by two fault system east-Arjan and west-Arjan to the Shahneshin and Salamati anticline. In these study using Landsat 7 ETM images with resolution 2.5 m and directional filtering in the four azimuths and semi-automatic technique for linear structure in the study area. Using the obtained data from extracted lineaments, the rose diagrams of the main strike lineaments are well confirm with field measurements of faults with N56° ± 4°E direction. The structural lineaments of the study area show that the Dasht-e-Arjan area is underlain by the limestone, sandstone, and marl. LANDSAT imagery of the area has been analyzed and interpreted in order to determine the lineament and groundwater quality across the area. The fracture is structurally controlled and mostly influences both the groundwater and surface water pollution and flow directions in the Dasht-e-Arjan. Using visual interpretation, determining the lineaments on the satellite image is very difficult and subjective, and it requires an experienced interpreter. In this study, the lineament analysis is undertaken to examine the orientation of the lineament, the relationship between lineaments and tectonic features and groundwater quality. Lineament density maps show that the lineament density is high around areas. Areas having high lineament density represent areas with relatively high groundwater pollution. Field observations agreed with the results from the analysis of the imagery.     

Bedload transport of small rivers in Malaysia

Numerous time-consuming equations, based on the relationship between the reliability and representativeness of the data utilized in defining variables and constants, require complex parameters to estimate bedload transport. In this study the easily accessible data including flow discharge, water depth, water surface slope, and surface grain diameter （ds0） from small rivers in Malaysia were used to estimate bedload transport. Genetic programming （GP） and artificial neural network （ANN） models are applied as complementary tools to estimate bed load transport based on a balance between simplicity and accuracy in small rivers. The developed models demonstrate higher performance with an overall accuracy of 97% and 93% for ANN and GP, respectively compared with other traditional methods and empirical equations.     

Analyzing spatiotemporal land use/cover dynamic using remote sensing imagery and GIS techniques case: Kan basin of Iran

Land use/land cover (LU/LC) that are significant elements for the interconnection of human activities and environment monitoring can be useful to find out the deviations of saving a maintainable environment. Remote sensing is a very useful tool for the affair of land use or land cover monitoring, which can be helpful to decide the allocation of land use and land cover. Supervised classification-maximum likelihood algorithm in GIS was applied in this study to detect land use/land cover changes observed in Kan basin using multispectral satellite data obtained from Landsat 5 (TM) and 8 (OLI) for the years 2000 and 2016, respectively. The main aim of this study was to gain a quantitative understanding of land use and land cover changes in Kan basin of Tehran over the period 2000–2016. For this purpose, firstly supervised classification technique was applied to Landsat images acquired in 2000 and 2016. The Kan basin was classified into five major LU/LC classes including: Built up areas, garden, pasture, water and bare-land. Change detection analysis was performed to compare the quantities of land cover class conversions between time intervals. The results revealed both increase and decrease of the different LU/LC classes from 2000 to 2016. The results indicate that during the study period, built-up land, and pastures have increased by 0.2% (76.4 km²) and 0.3% (86.03 km²) while water, garden and bare land have decreased by 0, 0.01% (3.62 km²) and 0.4% (117.168 km²), respectively. Information obtained from change detection of LU/LC can aid in providing optimal solutions for the selection, planning, implementation and monitoring of development schemes to meet the increasing demands of human needs in land management.     

Moho depth determination beneath the Zagros Mountains from 3D inversion of gravity data

Due to its geological and economic importance, the Zagros Mountains have been investigated by many researchers during the last decades. Nevertheless, in spite of all the studies conducted on the region, there are still some controversial problems concerning the structure of the Zagros Mountains, including crustal depths, demanding more insights into understanding the crustal constraints of the region. Accordingly, we have conducted a gravity study to determine Moho depth map of the Zagros Mountains region, including its major structural domains from the coastal plain of the Persian Gulf to central Iran. The employed data are the densest and most accurate terrestrial gravity data set observed until now with the precision of 5 μGal and resolution of 5 arc-minute by 5 arc-minute. To image Moho depth variations, gravity inversion software GROWTH2.0 is used, proposing the possibility to model stratified structures by means of a semi-objective exploratory 3D inversion approach. The obtained results reveal the crustal thickness of ~?30–35 km underneath the southwestern most Zagros Fold-Thrust Belt increasing northeastward to 48 km. The maximum Moho depth is estimated ~?62 km below the Zagros Mountains belt along the Main Zagros Thrust. Northeast of the study area, an average crustal thickness of 46 km is computed beneath Urumieh–Dokhtar magmatic arc and central Iran.