982 resultados para Flood vulnerability index


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The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.

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Natural hazards such as landslides are triggered by numerous factors such as ground movements, rock falls, slope failure, debris flows, slope instability, etc. Changes in slope stability happen due to human intervention, anthropogenic activities, change in soil structure, loss or absence of vegetation (changes in land cover), etc. Loss of vegetation happens when the forest is fragmented due to anthropogenic activities. Hence land cover mapping with forest fragmentation can provide vital information for visualising the regions that require immediate attention from slope stability aspects. The main objective of this paper is to understand the rate of change in forest landscape from 1973 to 2004 through multi-sensor remote sensing data analysis. The forest fragmentation index presented here is based on temporal land use information and forest fragmentation model, in which the forest pixels are classified as patch, transitional, edge, perforated, and interior, that give a measure of forest continuity. The analysis carried out for five prominent watersheds of Uttara Kannada district– Aganashini, Bedthi, Kali, Sharavathi and Venkatpura revealed that interior forest is continuously decreasing while patch, transitional, edge and perforated forest show increasing trend. The effect of forest fragmentation on landslide occurrence was visualised by overlaying the landslide occurrence points on classified image and forest fragmentation map. The increasing patch and transitional forest on hill slopes are the areas prone to landslides, evident from the field verification, indicating that deforestation is a major triggering factor for landslides. This emphasises the need for immediate conservation measures for sustainable management of the landscape. Quantifying and describing land use - land cover change and fragmentation is crucial for assessing the effect of land management policies and environmental protection decisions.

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This study borrows the measures developed for the operation of water resources systems as a means of characterizing droughts in a given region. It is argued that the common approach of assessing drought using a univariate measure (severity or reliability) is inadequate as decision makers need assessment of the other facets considered here. It is proposed that the joint distribution of reliability, resilience, and vulnerability (referred to as RRV in a reservoir operation context), assessed using soil moisture data over the study region, be used to characterize droughts. Use is made of copulas to quantify the joint distribution between these variables. As reliability and resilience vary in a nonlinear but almost deterministic way, the joint probability distribution of only resilience and vulnerability is modeled. Recognizing the negative association between the two variables, a Plackett copula is used to formulate the joint distribution. The developed drought index, referred to as the drought management index (DMI), is able to differentiate the drought proneness of a given area when compared to other areas. An assessment of the sensitivity of the DMI to the length of the data segments used in evaluation indicates relative stability is achieved if the data segments are 5years or longer. The proposed approach is illustrated with reference to the Malaprabha River basin in India, using four adjoining Climate Prediction Center grid cells of soil moisture data that cover an area of approximately 12,000 km(2). (C) 2013 American Society of Civil Engineers.

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This paper presents a new voltage stability index based on the tangent vector of the power flow jacobian. This index is capable of providing the relative vulnerability information of the system buses from the point of view of voltage collapse. In an effort to compare this index with a similar index, the popular voltage stability index L is studied and it is shown through system studies that the L index is not a very consistent indicator of the voltage collapse point of the system but is only a reasonable indicator of the vulnerability of the system buses to voltage collapse. We also show that the new index can be used in the voltage stability analysis of radial systems which is not possible with the L index. This is a significant result of this investigation since there is a lot of contemporary interest in distributed generation and microgrids which are by and large radial in nature. Simulation results considering several test systems are provided to validate the results and the computational needs of the proposed scheme is assessed in comparison with other schemes

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Scaling approaches are widely used by hydrologists for Regional Frequency Analysis (RFA) of floods at ungauged/sparsely gauged site(s) in river basins. This paper proposes a Recursive Multi-scaling (RMS) approach to RFA that overcomes limitations of conventional simple- and multi-scaling approaches. The approach involves identification of a separate set of attributes corresponding to each of the sites (being considered in the study area/region) in a recursive manner according to their importance, and utilizing those attributes to construct effective regional regression relationships to estimate statistical raw moments (SMs) of peak flows. The SMs are then utilized to arrive at parameters of flood frequency distribution and quantile estimate(s) corresponding to target return period(s). Effectiveness of the RMS approach in arriving at flood quantile estimates for ungauged sites is demonstrated through leave-one-out cross-validation experiment on watersheds in Indiana State, USA. Results indicate that the approach outperforms index-flood based Region-of-Influence approach, simple- and multi-scaling approaches and a multiple linear regression method. (C) 2015 Elsevier B.V. All rights reserved.

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4 p.

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In this paper, some observations are made following a flash-flood that occurred in Stake Clough, a small tributary of the River Goyt, during the evening of 6 August 1996. The site was visited eight times between 8 August - 30 October 1996 to take samples and make observations on the stream. The flood scoured the bed of Stake Clough but more significantly, caused it to change course along the middle part of the floodplain. Initially after the flood, the numbers of insects in all stretches of the stream channel were low (100-200 m super(2)), but then gradually rose to population densities approaching ten times this figure. The benthos was dominated by the Chironomidae and also leuctrid stoneflies (Leuctra nigra, L. hippopus and L. inermis). On 8th August 1996, 12 mesh bags, each containing oak leaves, were placed in the stream and collected after 24 hours. These were also dominated by chironomids, and contained relatively high numbers of the caddis, Potamophylax cingulatus.

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Assessing the vulnerability of stocks to fishing practices in U.S. federal waters was recently highlighted by the National Marine Fisheries Service (NMFS), National Oceanic and Atmospheric Administration, as an important factor to consider when 1) identifying stocks that should be managed and protected under a fishery management plan; 2) grouping data-poor stocks into relevant management complexes; and 3) developing precautionary harvest control rules. To assist the regional fishery management councils in determining vulnerability, NMFS elected to use a modified version of a productivity and susceptibility analysis (PSA) because it can be based on qualitative data, has a history of use in other fisheries, and is recommended by several organizations as a reasonable approach for evaluating risk. A number of productivity and susceptibility attributes for a stock are used in a PSA and from these attributes, index scores and measures of uncertainty are computed and graphically displayed. To demonstrate the utility of the resulting vulnerability evaluation, we evaluated six U.S. fisheries targeting 162 stocks that exhibited varying degrees of productivity and susceptibility, and for which data quality varied. Overall, the PSA was capable of differentiating the vulnerability of stocks along the gradient of susceptibility and productivity indices, although fixed thresholds separating low-, moderate-, and highly vulnerable species were not observed. The PSA can be used as a flexible tool that can incorporate regional-specific information on fishery and management activity.

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Background: Habitat fragmentation may result in the reduction of diversity of parasite communities by affecting population size and dispersal pattern of species. In the flood plain of the Yangtze River in China, many lakes, which were once connected with the river, have become isolated since the 1950s from the river by the construction of dams and sluices, with many larger lakes subdivided into smaller ones by road embankments. These artificial barriers have inevitably obstructed the migration of fish between the river and lakes and also among lakes. In this study, the gastrointestinal helminth communities were investigated in a carnivorous fish, the yellowhead catfish Pelteobagrus fulvidraco, from two connected and five isolated lakes in the flood plain in order to detect the effect of lake fragmentation on the parasite communities. Results: A total of 11 species of helminths were recorded in the stomach and intestine of P. fulvidraco from seven lakes, including two lakes connected with the Yangtze River, i.e. Poyang and Dongting lakes, and five isolated lakes, i.e. Honghu, Liangzi, Tangxun, Niushan and Baoan lakes. Mean helminth individuals and diversity of helminth communities in Honghu and Dongting lakes was lower than in the other five lakes. The nematode Procamallanus fulvidraconis was the dominant species of communities in all the seven lakes. No significant difference in the Shannon-Wiener index was detected between connected lakes (0.48) and isolated lakes (0.50). The similarity of helminth communities between Niushan and Baoan lakes was the highest (0.6708), and the lowest was between Tangxun and Dongting lakes (0.1807). The similarity was low between Dongting and the other lakes, and the similarity decreased with the geographic distance among these lakes. The helminth community in one connected lake, Poyang Lake was clustered with isolated lakes, but the community in Dongting Lake was separated in the tree. Conclusion: The similarity in the helminth communities of this fish in the flood-plain lakes may be attributed to the historical connection of these habitats and to the completion of the life-cycles of this fish as well as the helminth species within the investigated habitats. The diversity and the digenean majority in the helminth communities can be related to the diet of this fish, and to the lacustrine and macrophytic characters of the habitats. The lake isolation from the river had little detectable effect on the helminth communities of the catfish in flood-plain lakes of the Yangtze River. The low similarities in helminth communities between the Dongting Lake and others may just be a reflection of its unique water environment and anthropogenic alterations or fragmentation in this lake.

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During the summer of 2007 the United Kingdom experienced some of the worst flooding in its history, with the city of Hull amongst the worst affected. Meanwhile, the city of New Orleans, USA was subject to severe flooding in August 2005 as a result of Hurricane Katrina. The study has found that both the UK and US government disaster management programmes were ill prepared for these flood events. Many parallel issues have been discovered and discussed. The conditions of vulnerability that are evident in developing countries are not widely present in the UK or US but this must not be allowed to lead to complacency and lack of preparation and awareness. The cost in terms of mortality is relatively low compared to similar events in developing countries; however, the economic implications are considerable and must be addressed.

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Recent studies predict elevated and accelerating rates of species extinctions over the 21st century, due to climate change and habitat loss. Considering that such primary species loss may initiate cascades of secondary extinctions and push systems towards critical tipping points, we urgently need to increase our understanding of if certain sequences of species extinctions can be expected to be more devastating than others Most theoretical studies addressing this question have used a topological (non-dynamical) approach to analyse the probability that food webs will collapse, below a fixed threshold value in species richness, when subjected to different sequences of species loss. Typically, these studies have neither considered the possibility of dynamical responses of species, nor that conclusions may depend on the value of the collapse threshold. Here we analyse how sensitive conclusions on the importance of different species are to the threshold value of food web collapse. Using dynamical simulations, where we expose model food webs to a range of extinction sequences, we evaluate the reliability of the most frequently used index, R<inf>50</inf>, as a measure of food web robustness. In general, we find that R<inf>50</inf> is a reliable measure and that identification of destructive deletion sequences is fairly robust, within a moderate range of collapse thresholds. At the same time, however, focusing on R<inf>50</inf> only hides a lot of interesting information on the disassembly process and can, in some cases, lead to incorrect conclusions on the relative importance of species in food webs.

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This study deals with investigating the groundwater quality for irrigation purpose, the vulnerability of the aquifer system to pollution and also the aquifer potential for sustainable water resources development in Kobo Valley development project. The groundwater quality is evaluated up on predicting the best possible distribution of hydrogeochemicals using geostatistical method and comparing them with the water quality guidelines given for the purpose of irrigation. The hydro geochemical parameters considered are SAR, EC, TDS, Cl-, Na+, Ca++, SO4 2- and HCO3 -. The spatial variability map reveals that these parameters falls under safe, moderate and severe or increasing problems. In order to present it clearly, the aggregated Water Quality Index (WQI) map is constructed using Weighted Arithmetic Mean method. It is found that Kobo-Gerbi sub basin is suffered from bad water quality for the irrigation purpose. Waja Golesha sub-basin has moderate and Hormat Golena is the better sub basin in terms of water quality. The groundwater vulnerability assessment of the study area is made using the GOD rating system. It is found that the whole area is experiencing moderate to high risk of vulnerability and it is a good warning for proper management of the resource. The high risks of vulnerability are noticed in Hormat Golena and Waja Golesha sub basins. The aquifer potential of the study area is obtained using weighted overlay analysis and 73.3% of the total area is a good site for future water well development. The rest 26.7% of the area is not considered as a good site for spotting groundwater wells. Most of this area fall under Kobo-Gerbi sub basin.

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Natural disasters are events that cause general and widespread destruction of the built environment and are becoming increasingly recurrent. They are a product of vulnerability and community exposure to natural hazards, generating a multitude of social, economic and cultural issues of which the loss of housing and the subsequent need for shelter is one of its major consequences. Nowadays, numerous factors contribute to increased vulnerability and exposure to natural disasters such as climate change with its impacts felt across the globe and which is currently seen as a worldwide threat to the built environment. The abandonment of disaster-affected areas can also push populations to regions where natural hazards are felt more severely. Although several actors in the post-disaster scenario provide for shelter needs and recovery programs, housing is often inadequate and unable to resist the effects of future natural hazards. Resilient housing is commonly not addressed due to the urgency in sheltering affected populations. However, by neglecting risks of exposure in construction, houses become vulnerable and are likely to be damaged or destroyed in future natural hazard events. That being said it becomes fundamental to include resilience criteria, when it comes to housing, which in turn will allow new houses to better withstand the passage of time and natural disasters, in the safest way possible. This master thesis is intended to provide guiding principles to take towards housing recovery after natural disasters, particularly in the form of flood resilient construction, considering floods are responsible for the largest number of natural disasters. To this purpose, the main structures that house affected populations were identified and analyzed in depth. After assessing the risks and damages that flood events can cause in housing, a methodology was proposed for flood resilient housing models, in which there were identified key criteria that housing should meet. The same methodology is based in the US Federal Emergency Management Agency requirements and recommendations in accordance to specific flood zones. Finally, a case study in Maldives – one of the most vulnerable countries to sea level rise resulting from climate change – has been analyzed in light of housing recovery in a post-disaster induced scenario. This analysis was carried out by using the proposed methodology with the intent of assessing the resilience of the newly built housing to floods in the aftermath of the 2004 Indian Ocean Tsunami.

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The objectives of this study are: (a) to analyze if the relationship between parenting dimensions and children adjustment regarding coping strategies are similar in Argentinian and Spanish samples within poverty contexts; (b) to compare parental dimensions in the two groups studied, and (c) to determine the efficiency of parenting through the study of their influence in children coping strategies. The Graffar-Méndez Castellano Scale (Méndez-Castellano & Méndez, 1994), that brings a socioeconomic description of the population; an Argentinian Scale of Children Perception of Parental Relationships for 8 to 12 years of age (Richaud, 2007a), and the Argentine Questionnaire of Coping for children (Richaud, 2006) were administered to a sample of 458 Spanish and Argentinian children from 8 to 12 years old. Correlations were carried out to analyze the relationships between parenting dimensions and children coping strategies in both groups, and MANOVA, to study if there were different parental dimensions in the two groups —Argentina and Spain—, and to analyze if there were differences in children coping strategies. The results indicate that correlational pattern is similar in both groups, but parental dimensions are different for each culture, being the Argentinian parents more neglectful than Spanish parents. At the same time, Argentinian children adopt coping strategies less efficient that the Spanish children ones, involving in that way a greater emotional conflict.

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As the calibration and evaluation of flood inundation models are a prerequisite for their successful application, there is a clear need to ensure that the performance measures that quantify how well models match the available observations are fit for purpose. This paper evaluates the binary pattern performance measures that are frequently used to compare flood inundation models with observations of flood extent. This evaluation considers whether these measures are able to calibrate and evaluate model predictions in a credible and consistent way, i.e. identifying the underlying model behaviour for a number of different purposes such as comparing models of floods of different magnitudes or on different catchments. Through theoretical examples, it is shown that the binary pattern measures are not consistent for floods of different sizes, such that for the same vertical error in water level, a model of a flood of large magnitude appears to perform better than a model of a smaller magnitude flood. Further, the commonly used Critical Success Index (usually referred to as F<2 >) is biased in favour of overprediction of the flood extent, and is also biased towards correctly predicting areas of the domain with smaller topographic gradients. Consequently, it is recommended that future studies consider carefully the implications of reporting conclusions using these performance measures. Additionally, future research should consider whether a more robust and consistent analysis could be achieved by using elevation comparison methods instead.