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During the last 30 years, UAE witnessed earthquakes that ranged from minor to moderate, with maximum magnitude of 5.1 that occurred in the Masafi area (eastern UAE, on March 11, 2002). Recent earthquakes that hit Iran such as on May 11, 2013, caused tremors and mild shaking of buildings in some UAE cities. Although the tremors are small in magnitude, their sequences apparently become an important research topic and deserve more assessment from different perspectives such as geographical, geological, engineering, and social. This is because low risk does not equal no risk. This study is concerned with public perceptions of earthquake preparedness (reduction of disaster impact) that can be measured by various variables such as developing an emergency plan, preparation of disaster supply kits, and training. The methodology consists of a survey of 470 people who live around the Masafi area, near Fujairah city, UAE. GIS and GPS were used for site selection in conducting the survey, and remote sensing was used as an aid in identification of buildings’ ages. Results show that around 90% of the people surveyed have water tanks that can support them up to 3 days, and 60% of them normally buy food that can support them up to 2 days. Thirty percent of the respondents were familiar with storing first-aid kits and tools such as flashlights. The findings point to a need for more research regarding public awareness about earthquakes. The findings of this study may be useful for people who are involved in the four cornerstones of disaster risk reduction: community participation, public policy actions, safer construction and urban development, and development of a culture of prevention.  相似文献   
2.
The UAE has witnessed rapid urban development and economic growth in recent years. With its ambitious vision to become one of the advanced nations by 2021, planners and policy-makers need to know the most likely direction of future urban development. In this study, remotely sensed imagery coupled with cellular automata models were used to predict land cover in Al Ain, the second largest city in the Emirate of Abu Dhabi. Markov and cellular automata models were used for 1992 and 2006 to predict land cover in 2012. Land Use and Land Cover maps for the study area were derived from 1992, 2006, and 2012 Landsat satellite images (TM, ETM+). The models achieved an overall accuracy of approximately 80 %. A Markov model was applied for 2006 and 2012 to predict land cover in 2030. The results conformed to the general trend of the Al Ain Master Plan 2030. This study demonstrates that remote sensing, with the availability of free Landsat data, is a viable technology that could be used to help in the prediction process especially in developing countries, where data availability is a problem.  相似文献   
3.
This paper is the first ever attempt to study population distribution in Al Ain city in Eastern United Arab Emirates (UAE) through integration of remote sensing and Geographic Information System (GIS). The remote sensing data used in this study included high spatial resolution (1 m) IKONOS imagery of February 17, 2001. For the population related studies IKONOS data offers number of advantages over other satellite images, e.g. it has high spatial resolution, it covers a larger area per image, it cost less per km2, and available on a more regular basis. Such characteristics provide a mechanism by which population estimates can be updated with high accuracy and better rate of frequency. The average difference between the population recorded in the 2001 and that estimated from IKONOS images for Al Ain city is found to be equal to 5%. GIS is used for modelling the relationship among population variables and shows result obtained. Empirical model analyses results of this study show that the overall density of the city is consistent with location theories, i.e., declining population density from the Central Business District (CBD). The trend of higher-income people living in peripheries of cities is evident worldwide as it is in Al Ain.  相似文献   
4.

Prediction and control of blast-induced ground vibration is a matter of concern in mining industry since long. Several approaches ranging from scaled distance regression, different numerical methods to wave superimposition theories have been tried by many researchers for better prediction and control of blast-induced ground vibration. Signature hole analysis is one of the popular simulation methods to predict the ground vibration generated due to production blast. It superimposes the recorded signature hole waveform using a computer program to predict the production blast-induced vibration. The technique inputs the designated time of detonation of each hole and superimposes the waves generated by each hole to predict the nearest value of peak particle velocity and frequency of blast-induced ground vibration. Although a very useful approach, it requires a computer program to simulate the linear superimposition of waveforms. The simulation is not possible for every blast as it takes time and also is difficult for field engineers to simulate every time, whereas it is always easy for blasting engineers to adapt and use an empirical equation/approach for prediction and control of blast-induced ground vibration than simulation. In this paper, an attempt has been made to develop an innovative and simplified analytical approach of signature hole analysis. The simplified sinusoidal wave equation is obtained from recorded signature hole ground vibration waveform properties and is superimposed mathematically according to the multi-hole blast design to predict the production blast-induced ground vibrations. The validation of the developed approach was done in three different sites, and up to 15% more accuracy in prediction of the blast, vibrations are achieved in comparison with signature hole analysis prediction.

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5.
Coastal zones are most vulnerable for landuse changes in this rapid industrialization and urbanization epoch. It is necessary to evaluate land use — land cover (LULC) changes to develop efficient management strategies. The main objective of this paper is to evaluate and quantity Abu Dhabi coastal zone LULC changes from 1972 to 2000 using multi-temporal LANDSAT satellite data and digital change detection techniques. Supervised classification coupled with expert visual interpretation techniques were used to produce LULC classified images with an accuracy of 88%. Change detection process was achieved by applying post-classification comparison techniques in ENVI software. From this study it has been observed that the important coastal landuse types of Abu Dhabi coast .i.e. wetlands and woody Vegetation (Mangrove, represented by a single species,Avicennia marina) have been reduced drastically in their extent due to reclamation, dredging, tipping and other anthropogenic activities along the coastal zone. However, it has been observed that there is rapid increase in the man-made plantation and managed vegetation from 1990 to 2000 due to the Abu Dhabi government initiation. This study has given good insight into Abu Dhabi coastal zone changes during last 3 decades.  相似文献   
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