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Disaster Advances

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Disaster Advances





Land-Use Land-Cover Changes in East Singbhum Mineralized Zone: A Case Study

Kashinath Pal, Deb D., Vardhan H., Aruna M. and Samanta B.

Remote sensing images and techniques are widely used for environmental monitoring, climate changes, forest management and for water resource management. In the present work, identification of land-use land-cover (LULC) changes was studied based on Landsat Satellite (MSS) and IRS Satellite (LISS-III) images by Maximum Likelihood Classification (MLC) method. The study finds that the areas of water bodies and dense forest have decreased by more than 11 % and 6 %, respectively, while area covered by vegetation and habitats have increased by 16 % and 5 %, respectively. It was also found that dense forest was increased by 30 % around Norwapahar mine site area.

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Modelling Natural Disaster Management Systems: the Case of the Indian Ocean Countries

Santos-Reyes Jaime

Recent earthquakes, such as those occurred in Haiti, Japan and elsewhere, have demonstrated the vulnerability of society to such events. It becomes vital to see disaster risk as a product of a 'system'; to have a 'systemic' approach. 'Systemic' means seeing pattern and inter-relationship within a complex whole; i.e. to see events as products of the working of a system; i.e. death/injury/property loss etc. as results of the working of systems. The paper presents an application of a Systemic Disaster Management System (SDMS) model that has been constructed by using a 'systemic' approach. The model has been applied to model a natural 'disaster management system' at an international level; i.e. those countries located in the Indian Ocean that was affected by the 2004 tsunami disaster. The results show that the proposed model has the potentiality to be used proactively in modelling natural 'disaster management systems'. Moreover, it can be applied reactively in the sense that a past natural disaster can be analyzed by employing the model. It is hoped that the proposed systemic approach may help to gain a better understanding of managing natural disasters.

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Coupling of hydrodynamic modeling and aerial photogrammetry-derived digital surface model for flood simulation scenarios using GIS: Kuala Lumpur flood, Malaysia

Fugura A'kif Al, Billa Lawal, Pradhan Biswajeet, Mohamed Thamer Ahmed and Rawashdeh Samih

Hydrological simulations are useful methods of assessing and testing different scenarios of the impact of a hydrological event on a hydrological environment. Their effect and efficiency are however limited without the support of spatial planning tools such as GIS. GIS provides the platform for simulations to be integrated with supporting basin and floodplain data to be projected spatially and visualized spatially in support of decision making. Kuala Lumpur, Malaysia is experiencing frequent floods due to the rapid expansion of the city and increasing intensity of monsoon rainfall. In this study hydrodynamic simulation is coupled with a well developed digital surface and terrain model (DEM) to map flood extent in Kuala Lumpur. Techniques and methods discuss the integration of hydrological processes, remote sensing and GIS processing in 3D hydrological GIS modeling to represent different flooding scenarios.

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AE Pattern of Rock Burst Disaster induced by Strata Activation in Coal Mine

Tan Yun-liang, Zhang Ze and Zhao Tong-bin

As the mining depth increases, the rock burst is getting more and more hazardous. How to make early warning for rock burst validly is an urgent work. In this article, rock burst and AE pattern induced by three types of strata-activation: brittle-thick-hard roof, flexible-thick-hard roof and fault activation, were investigated. (a) For the case of brittle-thick-hard roof, the interval from fracturing to weighting is short, the released energy monitored by AE is synchronous. It is difficult to make some early warning for severe rock burst induced by sudden roof weighting, by using AE monitoring technique. (b) For the case of flexiblethick- hard roof, the roof weighting appears periodically, which can be taken as an indicator of medium and long-term early warning for rock burst; the AE events of low energy within silent-time can be used to make short-term early warning for rock burst. (c) For the case of fault, when coal face advances to the vicinity of fault, the fault begins to act and the energy of AE event becomes larger and larger and the early warning for rock burst should be made immediately.

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Association between mean zonal winds in the lower stratosphere and cyclonic storms

Joshi Indira Sudhir

The cyclonic storm frequency exhibits variations of different time scales. A study has been undertaken to examine the relation between the cyclonic storms and the equatorial lower stratospheric zonal wind oscillation (QBO). There exists a weak but significant relation between the mean zonal westerly winds (westerly phases of the QBO) and the frequency of cyclonic storms (Correlation between frequency of storms and westerly phase of QBO = 0.38 significant at less than 5 per cent level).

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Application of Support Vector Machine with Posterior Probability Estimates in Debris Flow Hazard Assessment

Li Xiuzhen and Kong Jiming

Support Vector Machine (SVM), a new machine learning method based on Statistical Learning Theory, has been widely applied in various fields because of the excellent learning performance and unique advantages in solving small-sample, nonlinear and high-dimensional problems. In this paper, we built a multi-class SVM model with posterior probability estimates for hazard assessment of regional debris flow. It is shown by the instances that the SVM model has higher assessment accuracy rate (the accuracy rates for training and testing samples are 90% and 92.86% respectively and the accuracy rate for total samples is 91.18%) and can give a probability belonging to each class as well as a class for debris flow hazard.

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Integrated Assessment Method for the Flood Management Project in Taiwan

Lee H.C.

This paper presents a method of integrating an environmental impact assessment (EIA) and a social impact assessment (SIA), designed to assist in the management of Taiwan’s flood-prone areas. This method is disciplinarily integrative because it includes both an EIA and an SIA. It is methodologically integrative because it encourages both technocratic and participatory approaches and offers a precise way to carry out integrative calculations. The calculation method takes into consideration both how the criterion weights are evaluated and the project’s performance scores evaluated based on each criterion. This study also introduces several ways of presenting the final assessment results, allowing appraisers to visualize the stakeholders’ overall attitude and prioritize a list as to what aspects of the evaluated project should be improved first.

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Seismomagnetic Signal Comparison using the Morlet Wavelet Method

Chen Chieh-Hung, Wen Strong, Liu Jann-Yenq, Yeh Ta-Kang, Wang Chung-Ho, Yen Horng-Yuan, Hattori Katsumi and Lin Ching-Ren

The Morlet wavelet transform is commonly utilized to understand amplitude distributions in the frequency domain. To compare amplitude distributions at two different stations, the wavelet coherence as a normalized numerical index is employed. The wavelet coherence at two stations away from an epicenter often approaches 1 and their relative phase presents synchronous variations suggesting that geomagnetic fields are dominated by changes in the ionosphere and/or magnetosphere. When a station located near an epicenter is added to the analytical process, the small wavelet coherence at the period of approximately 0.5 day appears and disappears suddenly 40 days before and few days after earthquakes, respectively. Analytical results are in agreement with ratio changes of daily variation ranges at two stations during earthquakes reported in previous studies and shed light on location estimation of epicenters for forthcoming events using geomagnetic intensity fields.

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Natural Disaster Occurrence and Average Global Temperature

Pan Xubin, Shen Danna, Dong Xuejun and Patton Bob

In the context of climate change, there is potential for a higher frequency of natural disasters. Here a linear regression analysis is employed to link the relationship between the natural disaster occurrence and average global temperature from 1980 to 2010. The results indicate that epidemic, extreme temperature, flood and storm events are strongly affected by climate. If the average global temperature increases by 1 oC, the occurrence of epidemic, extreme temperature, flood and storm would increase by 101, 42, 268 and 95 occurrences per year respectively.

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