Mapping malaria risk and vulnerability in the United Republic of Tanzania: a spatial explicit model.

PubMed

Hagenlocher, Michael; Castro, Marcia C

2015-01-01

Outbreaks of vector-borne diseases (VBDs) impose a heavy burden on vulnerable populations. Despite recent progress in eradication and control, malaria remains the most prevalent VBD. Integrative approaches that take into account environmental, socioeconomic, demographic, biological, cultural, and political factors contributing to malaria risk and vulnerability are needed to effectively reduce malaria burden. Although the focus on malaria risk has increasingly gained ground, little emphasis has been given to develop quantitative methods for assessing malaria risk including malaria vulnerability in a spatial explicit manner. Building on a conceptual risk and vulnerability framework, we propose a spatial explicit approach for modeling relative levels of malaria risk - as a function of hazard, exposure, and vulnerability - in the United Republic of Tanzania. A logistic regression model was employed to identify a final set of risk factors and their contribution to malaria endemicity based on multidisciplinary geospatial information. We utilized a Geographic Information System for the construction and visualization of a malaria vulnerability index and its integration into a spatially explicit malaria risk map. The spatial pattern of malaria risk was very heterogeneous across the country. Malaria risk was higher in Mainland areas than in Zanzibar, which is a result of differences in both malaria entomological inoculation rate and prevailing vulnerabilities. Areas of high malaria risk were identified in the southeastern part of the country, as well as in two distinct "hotspots" in the northwestern part of the country bordering Lake Victoria, while concentrations of high malaria vulnerability seem to occur in the northwestern, western, and southeastern parts of the mainland. Results were visualized using both 10×10 km(2) grids and subnational administrative units. The presented approach makes an important contribution toward a decision support tool. By decomposing malaria risk into its components, the approach offers evidence on which factors could be targeted for reducing malaria risk and vulnerability to the disease. Ultimately, results offer relevant information for place-based intervention planning and more effective spatial allocation of resources.

Comparison of environmental and socio-economic domains of vulnerability to flood hazards

NASA Astrophysics Data System (ADS)

Leidel, M.; Kienberger, S.; Lang, S.; Zeil, P.

2009-04-01

Socio-economic and environmental based vulnerability models have been developed within the research context of the FP6 project BRAHMATWINN. The conceptualisation of vulnerability has been defined in the project and is characterised as a function of sensitivity and adaptive capacity, where sensitivity is used to refer to systems that are susceptible to the impacts of environmental stress. Adaptive capacity is used to refer to systems or resources available to communities that could help them adapt or cope with the adverse consequences of environmental stresses in the recovery phase. In a wider context the approach reflects the wider objective and conceptualizations of the IPCC (Intergovernmental Panel on Climate Change) framework, where vulnerability is characterized as a component of overall risk. A methodology has been developed which delineates spatial units of vulnerability (VULNUS). These units share a specific common characteristic and allow the independent spatial modelling of a complex phenomena independent from administrative units and raster based approaches. An increasing detail of spatial data and complex decision problems require flexible means for scaled spatial representations, for mapping the dynamics and constant changes, and delivering the crucial information. Automated techniques of object-based image analysis (OBIA, Lang & Blaschke, 2006), capable of integrating a virtually unlimited set of spatial data sets, try to match the information extraction with our world view. To account for that, a flexible concept of manageable units is required. The term geon was proposed by Lang (2008) to describe generic spatial objects that are homogenous in terms of a varying spatial phenomena under the influence of, and partly controlled by, policy actions. The geon concept acts as a framework for the regionalization of continuous spatial information according to defined parameters of homogeneity. It is flexible in terms of a certain perception of a problem (specific policy realm, specific hazard domain, etc.). In this study, vulnerability units have been derived as a specific instance of a geon set within an area exposed to flood risk. Using geons, we are capable of transforming singular domains of information on specific systemic components to policy-relevant, conditioned information (Kienberger et al., 2008; Tiede & Lang, 2007). According to the work programme socio-economic vulnerabilities have been modelled for the Salzach catchment. A specific set of indicators has been developed with a strong stakeholder orientation. Next to that, and to allow an easier integration within the aimed development of Water Resource Response Units (WRRUs) the environmental domain of vulnerability has additionally been modelled. We present the results of the socio-economic and environmental based approach to model vulnerability. The research methodology utilises census as well as land use/land cover data to derive and assess vulnerability. As a result, spatial units have been identified which represent common characteristics of socio-economic environmental vulnerability. The results show the spatially explicit vulnerability and its underlying components sensitivity and adaptive capacity for socio-economic and environmental domains and discuss differences. Within the test area, the Salzach River catchment in Austria, primarily urban areas adjacent to water courses are highly vulnerable. It can be stated that the delineation of vulnerability units that integrates all dimensions of sustainability are a prerequisite for a holistic and thus adaptive integrated water management approach. Indeed, such units constitute the basis for future dynamic vulnerability assessments, and thus for the assessment of uncertainties due to climate change. Kienberger, S., S. Lang & D. Tiede (2008): Socio-economic vulnerability units - modelling meaningful spatial units. In: Proceedings of the GIS Research UK 16th Annual conference GISRUK 2008, Manchester. Lang, S. (2008): Object-based image analysis for remote sensing applications: modeling reality - dealing with complexity. In: Blaschke, T., S. Lang & G. Hay (eds.): Object-Based Image Analysis - Spatial concepts for knowledge-driven remote sensing applications. New York: Springer, 3-28. Lang, S. & T. Blaschke (2006) Bridging remote sensing and GIS - what are the most supportive pillars? In: S: Lang & T. Blaschke (eds.): International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences vol. XXXVI-4/C42. CD-ROM and online at www.isprs.org. Tiede D. & S .Lang (2007): Analytical 3D views and virtual globes - putting analytical results into spatial context. ISPRS, ICA, DGfK - Joint Workshop: Visualization and Exploration of Geospatial Data, Stuttgart

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile.

PubMed

Inostroza, Luis; Palme, Massimo; de la Barrera, Francisco

2016-01-01

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making.

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile

PubMed Central

Palme, Massimo; de la Barrera, Francisco

2016-01-01

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making. PMID:27606592

Mapping the Drivers of Climate Change Vulnerability for Australia’s Threatened Species

PubMed Central

Lee, Jasmine R.; Maggini, Ramona; Taylor, Martin F. J.; Fuller, Richard A.

2015-01-01

Effective conservation management for climate adaptation rests on understanding the factors driving species’ vulnerability in a spatially explicit manner so as to direct on-ground action. However, there have been only few attempts to map the spatial distribution of the factors driving vulnerability to climate change. Here we conduct a species-level assessment of climate change vulnerability for a sample of Australia’s threatened species and map the distribution of species affected by each factor driving climate change vulnerability across the continent. Almost half of the threatened species assessed were considered vulnerable to the impacts of climate change: amphibians being the most vulnerable group, followed by plants, reptiles, mammals and birds. Species with more restricted distributions were more likely to show high climate change vulnerability than widespread species. The main factors driving climate change vulnerability were low genetic variation, dependence on a particular disturbance regime and reliance on a particular moisture regime or habitat. The geographic distribution of the species impacted by each driver varies markedly across the continent, for example species impacted by low genetic variation are prevalent across the human-dominated south-east of the country, while reliance on particular moisture regimes is prevalent across northern Australia. Our results show that actions to address climate adaptation will need to be spatially appropriate, and that in some regions a complex suite of factors driving climate change vulnerability will need to be addressed. Taxonomic and geographic variation in the factors driving climate change vulnerability highlights an urgent need for a spatial prioritisation of climate adaptation actions for threatened species. PMID:26017785

Maxillofacial Injuries as Markers of Interpersonal Violence in Belo Horizonte-Brazil: Analysis of the Socio-Spatial Vulnerability of the Location of Victim’s Residences

PubMed Central

Silva, Carlos José de Paula; Moura, Ana Clara Mourão; Paiva, Paula Cristina Pelli; Ferreira, Raquel Conceição; Silvestrini, Rafaella Almeida; Vargas, Andréa Maria Duarte; de Paula, Liliam Pacheco Pinto; Naves, Marcelo Drummond; Ferreira, Efigênia Ferreira e

2015-01-01

The aim of the present study was to analyze the spatial pattern of cases of maxillofacial injuries caused by interpersonal violence, based on the location of the victim’s residence, and to investigate the existence of conditions of socio-spatial vulnerability in these areas. This is a cross-sectional study, using the data of victims attended in three emergency hospitals in Belo Horizonte-Brazil between January 2008 and December 2010. Based on the process of spatial signature, the socio-spatial condition of the victims was identified according to data from census tracts. The spatial distribution trends of the addresses of victims were analyzed using Kernel maps and Ripley’s K function. Multicriteria analysis was used to analyze the territorial insertion of victims, using a combination of variables to obtain the degree of socio-spatial vulnerability. The residences of the victims were distributed in an aggregated manner in urban areas, with a confidence level of 99%. The highest densities were found in areas of unfavorable socioeconomic conditions and, to a lesser extent, areas with worse residential and neighborhood infrastructure. Spatial clusters of households formed in slums with a significant level of socio-spatial vulnerability. Explanations of the living conditions in segregated urban areas and analysis of the concentration of more vulnerable populations should be a priority in the development of public health and safety policies. PMID:26274320

Social vulnerability to heat in Greater Atlanta, USA: spatial pattern of heat, NDVI, socioeconomics and household composition

NASA Astrophysics Data System (ADS)

Sim, Sunhui

2017-10-01

The purpose of the article is evaluating spatial patterns of social vulnerability to heat in Greater Atlanta in 2015. The social vulnerability to heat is an index of socioeconomic status, household composition, land surface temperature and normalized differential vegetation index (NDVI). Land surface temperature and NDVI were derived from the red, NIR and thermal infrared (TIR) of a Landsat OLI/TIRS images collected on September 14, 2015. The research focus is on the variation of heat vulnerability in Greater Atlanta. The study found that heat vulnerability is highly clustered spatially, resulting in "hot spots" and "cool spots". The results show significant health disparities. The hotspots of social vulnerability to heat occurred in neighborhoods with lower socioeconomic status as measured by low education, low income and more poverty, greater proportion of elderly people and young children. The findings of this study are important for identifying clusters of heat vulnerability and the relationships with social factors. These significant results provide a basis for heat intervention services.

Quantification of Road Network Vulnerability and Traffic Impacts to Regional Landslide Hazards.

NASA Astrophysics Data System (ADS)

Postance, Benjamin; Hillier, John; Dixon, Neil; Dijkstra, Tom

2015-04-01

Slope instability represents a prevalent hazard to transport networks. In the UK regional road networks are frequently disrupted by multiple slope failures triggered during intense precipitation events; primarily due to a degree of regional homogeneity of slope materials, geomorphology and weather conditions. It is of interest to examine how different locations and combinations of slope failure impact road networks, particularly in the context of projected climate change and a 40% increase in UK road demand by 2040. In this study an extensive number (>50 000) of multiple failure event scenarios are simulated within a dynamic micro simulation to assess traffic impacts during peak flow (7 - 10 AM). Possible failure locations are selected within the county of Gloucestershire (3150 km2) using historic failure sites and British Geological Survey GeoSure data. Initial investigations employ a multiple linear regression analyses to consider the severity of traffic impacts, as measured by time, in respect of spatial and topographical network characteristics including connectivity, density and capacity in proximity to failure sites; the network distance between disruptions in multiple failure scenarios is used to consider the effects of spatial clustering. The UK Department of Transport road travel demand and UKCP09 weather projection data to 2080 provide a suitable basis for traffic simulations and probabilistic slope stability assessments. Future work will thus focus on the development of a catastrophe risk model to simulate traffic impacts under various narratives of future travel demand and slope instability under climatic change. The results of this investigation shall contribute to the understanding of road network vulnerabilities and traffic impacts from climate driven slope hazards.

Environmental Health Related Socio-Spatial Inequalities: Identifying “Hotspots” of Environmental Burdens and Social Vulnerability

PubMed Central

Shrestha, Rehana; Flacke, Johannes; Martinez, Javier; van Maarseveen, Martin

2016-01-01

Differential exposure to multiple environmental burdens and benefits and their distribution across a population with varying vulnerability can contribute heavily to health inequalities. Particularly relevant are areas with high cumulative burdens and high social vulnerability termed as “hotspots”. This paper develops an index-based approach to assess these multiple burdens and benefits in combination with vulnerability factors at detailed intra-urban level. The method is applied to the city of Dortmund, Germany. Using non-spatial and spatial methods we assessed inequalities and identified “hotspot” areas in the city. We found modest inequalities burdening higher vulnerable groups in Dortmund (CI = −0.020 at p < 0.05). At the detailed intra-urban level, however, inequalities showed strong geographical patterns. Large numbers of “hotspots” exist in the northern part of the city compared to the southern part. A holistic assessment, particularly at a detailed local level, considering both environmental burdens and benefits and their distribution across the population with the different vulnerability, is essential to inform environmental justice debates and to mobilize local stakeholders. Locating “hotspot” areas at this detailed spatial level can serve as a basis to develop interventions that target vulnerable groups to ensure a health conducive equal environment. PMID:27409625

Quantification and spatial characterization of moisture and NaCl content of Iberian dry-cured ham slices using NIR hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Hyperspectral imaging technology is increasingly regarded as a powerful tool for the classification and spatial quantification of a wide range of agrofood product properties. Taking into account the difficulties involved in validating hyperspectral calibrations, the models constructed here proved mo...

15 CFR 990.52 - Injury assessment-quantification.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., the time for natural recovery without restoration, but including any response actions. The analysis of... injury; (2) The sensitivity and vulnerability of the injured natural resource and/or service; (3) The...

SYNTHESIS OF SPATIAL DATA FOR DECISION-MAKING

EPA Science Inventory

EPA'S Regional Vulnerability Assessment Program (ReVA) has developed a web-based statistical tool that synthesizes available spatial data into indices of condition, vulnerability (risk, considering cumulative effects), and feasibility of management options. The Environmental Deci...

Spatial vulnerability of fine particulate matter relative to the prevalence of diabetes in the United States.

PubMed

Chien, Lung-Chang; Alamgir, Hasanat; Yu, Hwa-Lung

2015-03-01

Recent research supports a link between diabetes and fine particulate matter (≤ 2.5μg in diameter; PM2.5) in both laboratory and epidemiology studies. However, research investigating the potential relationship of the spatial vulnerability of diabetes to concomitant PM2.5 levels is still sparse, and the level of diabetes geographic disparities attributed to PM2.5 levels has yet to be evaluated. We conducted a Bayesian structured additive regression modeling approach to determine whether long-term exposure to PM2.5 is spatially associated with diabetes prevalence after adjusting for the socioeconomic status of county residents. This study utilizes the following data sources from 2004 to 2010: the Behavioral Risk Factor Surveillance System, the American Community Survey, and the Environmental Protection Agency. We also conducted spatial comparisons with low, median-low, median-high, and high levels of PM2.5 concentrations. When PM2.5 concentrations increased 1 μg/m(3), the increase in the relative risk percentage for diabetes ranged from -5.47% (95% credible interval = -6.14, -4.77) to 2.34% (95% CI = 2.01, 2.70), where 1323 of 3109 counties (42.55%) displayed diabetes vulnerability with significantly positive relative risk percentages. These vulnerable counties are more likely located in the Southeast, Central, and South Regions of the U.S. A similar spatial vulnerability pattern for concentrations of low PM2.5 levels was also present in these same three regions. A clear cluster of vulnerable counties at median-high PM2.5 level was found in Michigan. This study identifies the spatial vulnerability of diabetes prevalence associated with PM2.5, and thereby provides the evidence needed to prompt and establish enhanced surveillance that can monitor diabetes vulnerability in areas with low PM2.5 pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatial vulnerability of fine particulate matter relative to the geographic disparities of adult's diabetes prevalence in the United States

NASA Astrophysics Data System (ADS)

Chien, Lung-Chang; Alamgir, Hassanat; Yu, Hwa-Lung

2015-04-01

Potentially larger regional effects of climate change have been revealed on the elevation of fine particulate matter (≤ 2.5 µg in diameter; PM2.5) in the U.S. In addition, recent research supports a link between diabetes and PM2.5 in both laboratory and epidemiology studies. However, research investigating the potential relationship of the spatial vulnerability of diabetes to concomitant PM2.5 levels is still sparse, and the level of diabetes geographic disparities attributed to PM2.5 levels has yet to be evaluated. We conducted a Bayesian structured additive regression modeling approach to determine whether long-term exposure to PM2.5 is spatially associated with diabetes prevalence after adjusting for the socioeconomic status of county residents. This study utilizes the following data sources from 2004-2010: the Behavioral Risk Factor Surveillance System, the American Community Survey, and the Environmental Protection Agency. We also conducted spatial comparisons with low, median-low, median-high, and high levels of PM2.5 concentrations. When PM2.5 concentrations increased 1 µg/m3, the increase in the relative risk percentage for diabetes ranged from -5.47% (95% credible interval = -6.14, -4.77) to 2.34% (95% CI = 2.01, 2.70), where 1,323 of 3,109 counties (42.55%) displayed diabetes vulnerability with significantly positive relative risk percentages. These vulnerable counties are more likely located in the Southeast, Central, and South Regions of the U.S. A similar spatial vulnerability pattern for concentrations of low PM2.5 levels was also present in these same three regions. A clear cluster of vulnerable counties at median-high PM2.5 level was found in Michigan. This study identifies the spatial vulnerability of diabetes prevalence associated with PM2.5, and thereby provides the evidence needed to prompt and establish enhanced surveillance that can monitor diabetes vulnerability in areas with low PM2.5 pollution.

Temporal and spatial changes in social vulnerability to natural hazards

PubMed Central

Cutter, Susan L.; Finch, Christina

2008-01-01

During the past four decades (1960–2000), the United States experienced major transformations in population size, development patterns, economic conditions, and social characteristics. These social, economic, and built-environment changes altered the American hazardscape in profound ways, with more people living in high-hazard areas than ever before. To improve emergency management, it is important to recognize the variability in the vulnerable populations exposed to hazards and to develop place-based emergency plans accordingly. The concept of social vulnerability identifies sensitive populations that may be less likely to respond to, cope with, and recover from a natural disaster. Social vulnerability is complex and dynamic, changing over space and through time. This paper presents empirical evidence on the spatial and temporal patterns in social vulnerability in the United States from 1960 to the present. Using counties as our study unit, we found that those components that consistently increased social vulnerability for all time periods were density (urban), race/ethnicity, and socioeconomic status. The spatial patterning of social vulnerability, although initially concentrated in certain geographic regions, has become more dispersed over time. The national trend shows a steady reduction in social vulnerability, but there is considerable regional variability, with many counties increasing in social vulnerability during the past five decades. PMID:18268336

On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?

PubMed

Wolf, Tanja; Chuang, Wen-Ching; McGregor, Glenn

2015-10-23

Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action.

Social, Environmental, and Health Vulnerability to Climate Change: The Case of the Municipalities of Minas Gerais, Brazil.

PubMed

Quintão, Ana Flávia; Brito, Isabela; Oliveira, Frederico; Madureira, Ana Paula; Confalonieri, Ulisses

2017-01-01

Vulnerability to climate change is a complex and dynamic phenomenon involving both social and physical/environmental aspects. It is presented as a method for the quantification of the vulnerability of all municipalities of Minas Gerais, a state in southeastern Brazil. It is based on the aggregation of different kinds of environmental, climatic, social, institutional, and epidemiological variables, to form a composite index. This was named "Index of Human Vulnerability" and was calculated using a software (SisVuClima®) specifically developed for this purpose. Social, environmental, and health data were combined with the climatic scenarios RCP 4.5 and 8.5, downscaled from ETA-HadGEM2-ES for each municipality. The Index of Human Vulnerability associated with the RCP 8.5 has shown a higher vulnerability for municipalities in the southern and eastern parts of the state of Minas Gerais.

Signs of critical transition in the Everglades wetlands in response to climate and anthropogenic changes.

PubMed

Foti, Romano; del Jesus, Manuel; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2013-04-16

The increasing pressure of climatic change and anthropogenic activities is predicted to have major effects on ecosystems around the world. With their fragility and sensitivity to hydrologic shifts and land-use changes, wetlands are among the most vulnerable of such ecosystems. Focusing on the Everglades National Park, we here assess the impact of changes in the hydrologic regime, as well as habitat loss, on the spatial configuration of vegetation species. Because the current structuring of vegetation clusters in the Everglades exhibits power-law behavior and such behavior is often associated with self-organization and dynamics occurring near critical transition points, the quantification and prediction of the impact of those changes on the ecosystem is deemed of paramount importance. We implement a robust model able to identify the main hydrologic and local drivers of the vegetation species spatial structuring and apply it for quantitative assessment. We find that shifts in the hydropatterns will mostly affect the relative abundance of species that currently colonize specific hydroperiod niches. Habitat loss or disruption, however, would have a massive impact on all plant communities, which are found to exhibit clear threshold behaviors when a given percentage of habitable habitat is lost.

Signs of critical transition in the Everglades wetlands in response to climate and anthropogenic changes

PubMed Central

Foti, Romano; del Jesus, Manuel; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2013-01-01

The increasing pressure of climatic change and anthropogenic activities is predicted to have major effects on ecosystems around the world. With their fragility and sensitivity to hydrologic shifts and land-use changes, wetlands are among the most vulnerable of such ecosystems. Focusing on the Everglades National Park, we here assess the impact of changes in the hydrologic regime, as well as habitat loss, on the spatial configuration of vegetation species. Because the current structuring of vegetation clusters in the Everglades exhibits power-law behavior and such behavior is often associated with self-organization and dynamics occurring near critical transition points, the quantification and prediction of the impact of those changes on the ecosystem is deemed of paramount importance. We implement a robust model able to identify the main hydrologic and local drivers of the vegetation species spatial structuring and apply it for quantitative assessment. We find that shifts in the hydropatterns will mostly affect the relative abundance of species that currently colonize specific hydroperiod niches. Habitat loss or disruption, however, would have a massive impact on all plant communities, which are found to exhibit clear threshold behaviors when a given percentage of habitable habitat is lost. PMID:23576751

Wildland fire risk and social vulnerability in the Southeastern United States: An exploratory spatial data analysis approach

Treesearch

Cassandra Johnson Gaither; N.C. Poudyal; S. Goodrick; J.M. Bowker; S. Malone; J. Gan

2011-01-01

The southeastern U.S. is one of the more wildland fire prone areas of the country and also contains some of the poorest or most socially vulnerable rural communities. Our project addresses wildland fire risk in this part of the U.S and its intersection with social vulnerability. We examine spatial association between high wildland fire prone areas which also rank high...

A GIS Approach to Identifying Socially and Medically Vulnerable Older Adult Populations in South Florida.

PubMed

Hames, Elizabeth; Stoler, Justin; Emrich, Christopher T; Tewary, Sweta; Pandya, Naushira

2017-11-10

We define, map, and analyze geodemographic patterns of socially and medically vulnerable older adults within the tri-county region of South Florida. We apply principal components analysis (PCA) to a set of previously identified indicators of social and medical vulnerability at the census tract level. We create and map age-stratified vulnerability scores using a geographic information system (GIS), and use spatial analysis techniques to identify patterns and interactions between social and medical vulnerability. Key factors contributing to social vulnerability in areas with higher numbers of older adults include age, large household size, and Hispanic ethnicity. Medical vulnerability in these same areas is driven by disease burden, access to emergency cardiac services, availability of nursing home and hospice beds, access to home health care, and available mental health services. Age-dependent areas of social vulnerability emerge in Broward County, whereas age-dependent areas of medical vulnerability emerge in Palm Beach County. Older-adult social and medical vulnerability interact differently throughout the study area. Spatial analysis of older adult social and medical vulnerability using PCA and GIS can help identify age-dependent pockets of vulnerability that are not easily identifiable in a populationwide analysis; improve our understanding of the dynamic spatial organization of health care, health care needs, access to care, and outcomes; and ultimately serve as a tool for health care planning. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Assessing socioeconomic vulnerability to dengue fever in Cali, Colombia: statistical vs expert-based modeling

PubMed Central

2013-01-01

Background As a result of changes in climatic conditions and greater resistance to insecticides, many regions across the globe, including Colombia, have been facing a resurgence of vector-borne diseases, and dengue fever in particular. Timely information on both (1) the spatial distribution of the disease, and (2) prevailing vulnerabilities of the population are needed to adequately plan targeted preventive intervention. We propose a methodology for the spatial assessment of current socioeconomic vulnerabilities to dengue fever in Cali, a tropical urban environment of Colombia. Methods Based on a set of socioeconomic and demographic indicators derived from census data and ancillary geospatial datasets, we develop a spatial approach for both expert-based and purely statistical-based modeling of current vulnerability levels across 340 neighborhoods of the city using a Geographic Information System (GIS). The results of both approaches are comparatively evaluated by means of spatial statistics. A web-based approach is proposed to facilitate the visualization and the dissemination of the output vulnerability index to the community. Results The statistical and the expert-based modeling approach exhibit a high concordance, globally, and spatially. The expert-based approach indicates a slightly higher vulnerability mean (0.53) and vulnerability median (0.56) across all neighborhoods, compared to the purely statistical approach (mean = 0.48; median = 0.49). Both approaches reveal that high values of vulnerability tend to cluster in the eastern, north-eastern, and western part of the city. These are poor neighborhoods with high percentages of young (i.e., < 15 years) and illiterate residents, as well as a high proportion of individuals being either unemployed or doing housework. Conclusions Both modeling approaches reveal similar outputs, indicating that in the absence of local expertise, statistical approaches could be used, with caution. By decomposing identified vulnerability “hotspots” into their underlying factors, our approach provides valuable information on both (1) the location of neighborhoods, and (2) vulnerability factors that should be given priority in the context of targeted intervention strategies. The results support decision makers to allocate resources in a manner that may reduce existing susceptibilities and strengthen resilience, and thus help to reduce the burden of vector-borne diseases. PMID:23945265

Water supply, demand, and quality indicators for assessing the spatial distribution of water resource vulnerability in the Columbia River Basin

USGS Publications Warehouse

Chang, Heejun; Jung, Il-Won; Strecker, Angela L.; Wise, Daniel; Lafrenz, Martin; Shandas, Vivek; ,; Yeakley, Alan; Pan, Yangdong; Johnson, Gunnar; Psaris, Mike

2013-01-01

We investigated water resource vulnerability in the US portion of the Columbia River basin (CRB) using multiple indicators representing water supply, water demand, and water quality. Based on the US county scale, spatial analysis was conducted using various biophysical and socio-economic indicators that control water vulnerability. Water supply vulnerability and water demand vulnerability exhibited a similar spatial clustering of hotspots in areas where agricultural lands and variability of precipitation were high but dam storage capacity was low. The hotspots of water quality vulnerability were clustered around the main stem of the Columbia River where major population and agricultural centres are located. This multiple equal weight indicator approach confirmed that different drivers were associated with different vulnerability maps in the sub-basins of the CRB. Water quality variables are more important than water supply and water demand variables in the Willamette River basin, whereas water supply and demand variables are more important than water quality variables in the Upper Snake and Upper Columbia River basins. This result suggests that current water resources management and practices drive much of the vulnerability within the study area. The analysis suggests the need for increased coordination of water management across multiple levels of water governance to reduce water resource vulnerability in the CRB and a potentially different weighting scheme that explicitly takes into account the input of various water stakeholders.

Vulnerability of marginal seas to sea level rise

NASA Astrophysics Data System (ADS)

Gomis, Damia; Jordà, Gabriel

2017-04-01

Sea level rise (SLR) is a serious thread for coastal areas and has a potential negative impact on society and economy. SLR can lead for instance to land loss, beach reduction, increase of the damage of marine storms on coastal infrastructures and to the salinization of underground water streams. It is well acknowledged that future SLR will be inhomogeneous across the globe, with regional differences of up to 100% with respect to global mean sea level (GMSL). Several studies have addressed the projections of SLR at regional scale, but most of them are based on global climate models (GCMs) that have a relatively coarse spatial resolution (>1°). In marginal seas this has proven to be a strong limitation, as their particular configurations require spatial resolutions that are not reachable by present GCMs. A paradigmatic case is the Mediterranean Sea, connected to the global ocean through the Strait of Gibraltar, a narrow passage of 14 km width. The functioning of the Mediterranean Sea involves a variety of processes including an overturning circulation, small-scale convection and a rich mesoscale field. Moreover, the long-term evolution of Mediterranean sea level has been significantly different from the global mean during the last decades. The observations of present climate and the projections for the next decades have lead some authors to hypothesize that the particular characteristics of the basin could allow Mediterranean mean sea level to evolve differently from the global mean. Assessing this point is essential to undertake proper adaptation strategies for the largely populated Mediterranean coastal areas. In this work we apply a new approach that combines regional and global projections to analyse future SLR. In a first step we focus on the quantification of the expected departures of future Mediterranean sea level from GMSL evolution and on the contribution of different processes to these departures. As a result we find that, in spite of its particularities, Mediterranean Sea level would follow global changes with departures lower than + 5 cm. In a second step we use the same methodology to obtain SLR projections at global scale in order to assess the vulnerability of other coastal areas. Namely, we define a vulnerability index based on relating the characteristics of present day variability with SLR projections under different scenarios. Results show that the averaged vulnerability index is 0.5 for scenario RCP8.5 (projected SLR is about a half of the maximum sea level recorded in the last decades). However, in the Mediterranean, the Caribbean and the Sea of Japan the vulnerability index is much higher (2.6, 2.4 and 2.1, respectively). From this point of view, therefore, these regions could be considered the most vulnerable regions in the world.

[Spatial patterns of eco-environmental vulnerability in Daqing City].

PubMed

Li, Jing; Zhang, Ping-Yu; Li, He; Su, Fei

2011-12-01

This paper established an index system for the assessment of eco-environmental vulnerability in Daqing City, from the aspects of sensitivity and response capability, and aiming at the major disturbances from crude oil exploitation and production activities. The improved entropy method was adopted to evaluate the weights of the indices, and the spatial patterns of eco-environment vulnerability in the City were analyzed, according to the model functions. In 2009, the more sensitive areas of the eco-environment in the City were mainly concentrated in the intensive regions of crude oil exploitation, processing, and petrochemical industry, and the ecological problems such as land salinization were the secondary causes for this higher sensitivity. The overall response capability of the eco-environment to unfavorable disturbances was relatively high, which reduced the eco-environment vulnerability to some extent. There was a great spatial difference in the eco-environment vulnerability in the City. The vulnerability was comparatively higher in the districts of Honggang, Sartu and Longfeng, with the degree being 0.80, 0.71 and 0.68, but lower in Ranghulu and Datong, with the degree of 0.20 and 0.04, respectively.

On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?

PubMed Central

Wolf, Tanja; Chuang, Wen-Ching; McGregor, Glenn

2015-01-01

Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action. PMID:26512681

Attenuation of Storm Surge Flooding By Wetlands in the Chesapeake Bay: An Integrated Geospatial Framework Evaluating Impacts to Critical Infrastructure

NASA Astrophysics Data System (ADS)

Khalid, A.; Haddad, J.; Lawler, S.; Ferreira, C.

2014-12-01

Areas along the Chesapeake Bay and its tributaries are extremely vulnerable to hurricane flooding, as evidenced by the costly effects and severe impacts of recent storms along the Virginia coast, such as Hurricane Isabel in 2003 and Hurricane Sandy in 2012. Coastal wetlands, in addition to their ecological importance, are expected to mitigate the impact of storm surge by acting as a natural protection against hurricane flooding. Quantifying such interactions helps to provide a sound scientific basis to support planning and decision making. Using storm surge flooding from various historical hurricanes, simulated using a coupled hydrodynamic wave model (ADCIRC-SWAN), we propose an integrated framework yielding a geospatial identification of the capacity of Chesapeake Bay wetlands to protect critical infrastructure. Spatial identification of Chesapeake Bay wetlands is derived from the National Wetlands Inventory (NWI), National Land Cover Database (NLCD), and the Coastal Change Analysis Program (C-CAP). Inventories of population and critical infrastructure are extracted from US Census block data and FEMA's HAZUS-Multi Hazard geodatabase. Geospatial and statistical analyses are carried out to develop a relationship between wetland land cover, hurricane flooding, population and infrastructure vulnerability. These analyses result in the identification and quantification of populations and infrastructure in flooded areas that lie within a reasonable buffer surrounding the identified wetlands. Our analysis thus produces a spatial perspective on the potential for wetlands to attenuate hurricane flood impacts in critical areas. Statistical analysis will support hypothesis testing to evaluate the benefits of wetlands from a flooding and storm-surge attenuation perspective. Results from geospatial analysis are used to identify where interactions with critical infrastructure are relevant in the Chesapeake Bay.

Forecasting Urban Forest Ecosystem Structure, Function, and Vulnerability

NASA Astrophysics Data System (ADS)

Steenberg, James W. N.; Millward, Andrew A.; Nowak, David J.; Robinson, Pamela J.; Ellis, Alexis

2017-03-01

The benefits derived from urban forest ecosystems are garnering increasing attention in ecological research and municipal planning. However, because of their location in heterogeneous and highly-altered urban landscapes, urban forests are vulnerable and commonly suffer disproportionate and varying levels of stress and disturbance. The objective of this study is to assess and analyze the spatial and temporal changes, and potential vulnerability, of the urban forest resource in Toronto, Canada. This research was conducted using a spatially-explicit, indicator-based assessment of vulnerability and i-Tree Forecast modeling of temporal changes in forest structure and function. Nine scenarios were simulated for 45 years and model output was analyzed at the ecosystem and municipal scale. Substantial mismatches in ecological processes between spatial scales were found, which can translate into unanticipated loss of function and social inequities if not accounted for in planning and management. At the municipal scale, the effects of Asian longhorned beetle and ice storm disturbance were far less influential on structure and function than changes in management actions. The strategic goals of removing invasive species and increasing tree planting resulted in a decline in carbon storage and leaf biomass. Introducing vulnerability parameters in the modeling increased the spatial heterogeneity in structure and function while expanding the disparities of resident access to ecosystem services. There was often a variable and uncertain relationship between vulnerability and ecosystem structure and function. Vulnerability assessment and analysis can provide strategic planning initiatives with valuable insight into the processes of structural and functional change resulting from management intervention.

Forecasting Urban Forest Ecosystem Structure, Function, and Vulnerability.

PubMed

Steenberg, James W N; Millward, Andrew A; Nowak, David J; Robinson, Pamela J; Ellis, Alexis

2017-03-01

The benefits derived from urban forest ecosystems are garnering increasing attention in ecological research and municipal planning. However, because of their location in heterogeneous and highly-altered urban landscapes, urban forests are vulnerable and commonly suffer disproportionate and varying levels of stress and disturbance. The objective of this study is to assess and analyze the spatial and temporal changes, and potential vulnerability, of the urban forest resource in Toronto, Canada. This research was conducted using a spatially-explicit, indicator-based assessment of vulnerability and i-Tree Forecast modeling of temporal changes in forest structure and function. Nine scenarios were simulated for 45 years and model output was analyzed at the ecosystem and municipal scale. Substantial mismatches in ecological processes between spatial scales were found, which can translate into unanticipated loss of function and social inequities if not accounted for in planning and management. At the municipal scale, the effects of Asian longhorned beetle and ice storm disturbance were far less influential on structure and function than changes in management actions. The strategic goals of removing invasive species and increasing tree planting resulted in a decline in carbon storage and leaf biomass. Introducing vulnerability parameters in the modeling increased the spatial heterogeneity in structure and function while expanding the disparities of resident access to ecosystem services. There was often a variable and uncertain relationship between vulnerability and ecosystem structure and function. Vulnerability assessment and analysis can provide strategic planning initiatives with valuable insight into the processes of structural and functional change resulting from management intervention.

Climate Risk and Vulnerability in the Caribbean and Gulf of Mexico Region: Interactions with Spatial Population and Land Cover Change

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M.; Baptista, S.; Adamo, S.

2010-12-01

Vulnerability to climate variability and change will depend on dynamic interactions between different aspects of climate, land-use change, and socioeconomic trends. Measurements and projections of these changes are difficult at the local scale but necessary for effective planning. New data sources and methods make it possible to assess land-use and socioeconomic changes that may affect future patterns of climate vulnerability. In this paper we report on new time series data sets that reveal trends in the spatial patterns of climate vulnerability in the Caribbean/Gulf of Mexico Region. Specifically, we examine spatial time series data for human population over the period 1990-2000, time series data on land use and land cover over 2000-2009, and infant mortality rates as a proxy for poverty for 2000-2008. We compare the spatial trends for these measures to the distribution of climate-related natural disaster risk hotspots (cyclones, floods, landslides, and droughts) in terms of frequency, mortality, and economic losses. We use these data to identify areas where climate vulnerability appears to be increasing and where it may be decreasing. Regions where trends and patterns are especially worrisome include coastal areas of Guatemala and Honduras.

Potential of 3D City Models to assess flood vulnerability

NASA Astrophysics Data System (ADS)

Schröter, Kai; Bochow, Mathias; Schüttig, Martin; Nagel, Claus; Ross, Lutz; Kreibich, Heidi

2016-04-01

Vulnerability, as the product of exposure and susceptibility, is a key factor of the flood risk equation. Furthermore, the estimation of flood loss is very sensitive to the choice of the vulnerability model. Still, in contrast to elaborate hazard simulations, vulnerability is often considered in a simplified manner concerning the spatial resolution and geo-location of exposed objects as well as the susceptibility of these objects at risk. Usually, area specific potential flood loss is quantified on the level of aggregated land-use classes, and both hazard intensity and resistance characteristics of affected objects are represented in highly simplified terms. We investigate the potential of 3D City Models and spatial features derived from remote sensing data to improve the differentiation of vulnerability in flood risk assessment. 3D City Models are based on CityGML, an application scheme of the Geography Markup Language (GML), which represents the 3D geometry, 3D topology, semantics and appearance of objects on different levels of detail. As such, 3D City Models offer detailed spatial information which is useful to describe the exposure and to characterize the susceptibility of residential buildings at risk. This information is further consolidated with spatial features of the building stock derived from remote sensing data. Using this database a spatially detailed flood vulnerability model is developed by means of data-mining. Empirical flood damage data are used to derive and to validate flood susceptibility models for individual objects. We present first results from a prototype application in the city of Dresden, Germany. The vulnerability modeling based on 3D City Models and remote sensing data is compared i) to the generally accepted good engineering practice based on area specific loss potential and ii) to a highly detailed representation of flood vulnerability based on a building typology using urban structure types. Comparisons are drawn in terms of affected building area and estimated loss for a selection of inundation scenarios.

Quantification of the memory imprint effect for a charged particle environment

NASA Technical Reports Server (NTRS)

Bhuva, B. L.; Johnson, R. L., Jr.; Gyurcsik, R. S.; Kerns, S. E.; Fernald, K. W.

1987-01-01

The effects of total accumulated dose on the single-event vulnerability of NMOS resistive-load SRAMs are investigated. The bias-dependent shifts in device parameters can imprint the memory state present during exposure or erase the imprinted state. Analysis of these effects is presented along with an analytic model developed for the quantification of these effects. The results indicate that the imprint effect is dominated by the difference in the threshold voltage of the n-channel devices.

Risk assessment by dynamic representation of vulnerability, exploitation, and impact

NASA Astrophysics Data System (ADS)

Cam, Hasan

2015-05-01

Assessing and quantifying cyber risk accurately in real-time is essential to providing security and mission assurance in any system and network. This paper presents a modeling and dynamic analysis approach to assessing cyber risk of a network in real-time by representing dynamically its vulnerabilities, exploitations, and impact using integrated Bayesian network and Markov models. Given the set of vulnerabilities detected by a vulnerability scanner in a network, this paper addresses how its risk can be assessed by estimating in real-time the exploit likelihood and impact of vulnerability exploitation on the network, based on real-time observations and measurements over the network. The dynamic representation of the network in terms of its vulnerabilities, sensor measurements, and observations is constructed dynamically using the integrated Bayesian network and Markov models. The transition rates of outgoing and incoming links of states in hidden Markov models are used in determining exploit likelihood and impact of attacks, whereas emission rates help quantify the attack states of vulnerabilities. Simulation results show the quantification and evolving risk scores over time for individual and aggregated vulnerabilities of a network.

Vulnerability to the transmission of human visceral leishmaniasis in a Brazilian urban area

PubMed Central

de Toledo, Celina Roma Sánchez; de Almeida, Andréa Sobral; Chaves, Sergio Augusto de Miranda; Sabroza, Paulo Chagastelles; Toledo, Luciano Medeiros; Caldas, Jefferson Pereira

2017-01-01

ABSTRACT OBJECTIVE To analyze the determinants for the occurrence of human visceral leishmaniasis linked to the conditions of vulnerability. METHODS This is an ecological study, whose spatial analysis unit was the Territorial Analysis Unit in Araguaína, State of Tocantins, Brazil, from 2007 to 2012. We have carried out an analysis of the sociodemographic and urban infrastructure situation of the municipality. Normalized primary indicators were calculated and used to construct the indicators of vulnerability of the social structure, household structure, and urban infrastructure. From them, we have composed a vulnerability index. Kernel density estimation was used to evaluate the density of cases of human visceral leishmaniasis, based on the coordinates of the cases. Bivariate global Moran’s I was used to verify the existence of spatial autocorrelation between the incidence of human visceral leishmaniasis and the indicators and index of vulnerability. Bivariate local Moran’s I was used to identify spatial clusters. RESULTS We have observed a pattern of centrifugal spread of human visceral leishmaniasis in the municipality, where outbreaks of the disease have progressively reached central and peri-urban areas. There has been no correlation between higher incidences of human visceral leishmaniasis and worse living conditions. Statistically significant clusters have been observed between the incidences of human visceral leishmaniasis in both periods analyzed (2007 to 2009 and 2010 to 2012) and the indicators and index of vulnerability. CONCLUSIONS The environment in circumscribed areas helps as protection factor or increases the local vulnerability to the occurrence of human visceral leishmaniasis. The use of methodology that analyzes the conditions of life of the population and the spatial distribution of human visceral leishmaniasis is essential to identify the most vulnerable areas to the spread/maintenance of the disease. PMID:28513764

Social, Environmental, and Health Vulnerability to Climate Change: The Case of the Municipalities of Minas Gerais, Brazil

PubMed Central

Brito, Isabela; Oliveira, Frederico; Madureira, Ana Paula

2017-01-01

Vulnerability to climate change is a complex and dynamic phenomenon involving both social and physical/environmental aspects. It is presented as a method for the quantification of the vulnerability of all municipalities of Minas Gerais, a state in southeastern Brazil. It is based on the aggregation of different kinds of environmental, climatic, social, institutional, and epidemiological variables, to form a composite index. This was named “Index of Human Vulnerability” and was calculated using a software (SisVuClima®) specifically developed for this purpose. Social, environmental, and health data were combined with the climatic scenarios RCP 4.5 and 8.5, downscaled from ETA-HadGEM2-ES for each municipality. The Index of Human Vulnerability associated with the RCP 8.5 has shown a higher vulnerability for municipalities in the southern and eastern parts of the state of Minas Gerais. PMID:28465693

Evaluation of socio-spatial vulnerability of citydwellers and analysis of risk perception: industrial and seismic risks in Mulhouse

NASA Astrophysics Data System (ADS)

Glatron, S.; Beck, E.

2008-10-01

Social vulnerability has been studied for years with sociological, psychological and economical approaches. Our proposition focuses on perception and cognitive representations of risks by city dwellers living in a medium size urban area, namely Mulhouse (France). Perception, being part of the social vulnerability and resilience of the society to disasters, influences the potential damage; for example it leads to adequate or inadequate behaviour in the case of an emergency. As geographers, we assume that the spatial relationship to danger or hazard can be an important factor of vulnerability and we feel that the spatial dimension is a challenging question either for better knowledge or for operational reasons (e.g. management of preventive information). We interviewed 491 people, inhabitants and workers, regularly distributed within the urban area to get to know their opinion on hazards and security measures better. We designed and mapped a vulnerability index on the basis of their answers. The results show that the social vulnerability depends on the type of hazard, and that the distance to the source of danger influences the vulnerability, especially for hazards with a precise location (industrial for example). Moreover, the effectiveness of the information campaigns is doubtful, as the people living close to hazardous industries (target of specific preventive information) are surprisingly more vulnerable and less aware of industrial risk.

[Spatial and temporal changes of the ecological vulnerability in a serious soil erosion area, Southern China.

PubMed

Yao, Xiong; Yu, Kun Yong; Liu, Jian; Yang, Su Ping; He, Ping; Deng, Yang Bo; Yu, Xin Yan; Chen, Zhang Hao

2016-03-01

Research on eco-environment vulnerability assessment contributes to the ecological environmental conservation and restoration. With Changting County as the study area, this paper selec-ted 7 indicators including slope, soil type, multi-year average precipitation, elevation deviate degree, normalized difference vegetation index, population density and land use type to build ecological vulnerability assessment system by using multicollinearity diagnostics analysis approach. The quantitative assessment of ecological vulnerability in 1999, 2006 and 2014 was calculated by using entropy weight method and comprehensive index method. The changes of the temporal-spatial distribution of ecological vulnerability were also analyzed. The results showed that the ecological vulnerability level index (EVLI) decreased overall but increased locally from 1999 to 2014. The average EVLI values in 1999, 2006 and 2014 were 0.4533±0.1216, 0.4160±0.1111 and 0.3916±0.1139, respectively, indicating that the ecological vulnerability in Changting County was at the moderate grade. The EVLI decreased from 2.92 in 1999 to 2.38 in 2006 and 2.13 in 2014. The spatial distribution of the ecological vulnerability was high inside but low outside. The high vulnerability areas were distributed mainly in Hetian Town and Tingzhou Town, where the slope was less than 15° and the altitude was lower than 500 m. During the study period, Sanzhou Town had the largest decreasing range of EVLI while Tingzhou Town had the lowest.

Climate change vulnerability to agrarian ecosystem of small Island: evidence from Sagar Island, India

NASA Astrophysics Data System (ADS)

Mandal, S.; Satpati, L. N.; Choudhury, B. U.; Sadhu, S.

2018-04-01

The present study assessed climate change vulnerability in agricultural sector of low-lying Sagar Island of Bay of Bengal. Vulnerability indices were estimated using spatially aggregated biophysical and socio-economic parameters by applying principal component analysis and equal weight method. The similarities and differences of outputs of these two methods were analysed across the island. From the integration of outputs and based on the severity of vulnerability, explicit vulnerable zones were demarcated spatially. Results revealed that life subsistence agriculture in 11.8% geographical area (2829 ha) of the island along the western coast falls under very high vulnerable zone (VHVZ VI of 84-99%) to climate change. Comparatively higher values of exposure (0.53 ± 0.26) and sensitivity (0.78 ± 0.14) subindices affirmed that the VHV zone is highly exposed to climate stressor with very low adaptive capacity (ADI= 0.24 ± 0.16) to combat vulnerability to climate change. Hence, food security for a population of >22 thousands comprising >3.7 thousand agrarian households are highly exposed to climate change. Another 17% area comprising 17.5% population covering 20% villages in north-western and eastern parts of the island also falls under high vulnerable (VI= 61%-77%) zone. Findings revealed large spatial heterogeneity in the degree of vulnerability across the island and thus, demands devising area specific planning (adaptation and mitigation strategies) to address the climate change impact implications both at macro and micro levels.

Social vulnerability assessment using spatial multi-criteria analysis (SEVI model) and the Social Vulnerability Index (SoVI model) - a case study for Bucharest, Romania

NASA Astrophysics Data System (ADS)

Armaş, I.; Gavriş, A.

2013-06-01

In recent decades, the development of vulnerability frameworks has enlarged the research in the natural hazards field. Despite progress in developing the vulnerability studies, there is more to investigate regarding the quantitative approach and clarification of the conceptual explanation of the social component. At the same time, some disaster-prone areas register limited attention. Among these, Romania's capital city, Bucharest, is the most earthquake-prone capital in Europe and the tenth in the world. The location is used to assess two multi-criteria methods for aggregating complex indicators: the social vulnerability index (SoVI model) and the spatial multi-criteria social vulnerability index (SEVI model). Using the data of the 2002 census we reduce the indicators through a factor analytical approach to create the indices and examine if they bear any resemblance to the known vulnerability of Bucharest city through an exploratory spatial data analysis (ESDA). This is a critical issue that may provide better understanding of the social vulnerability in the city and appropriate information for authorities and stakeholders to consider in their decision making. The study emphasizes that social vulnerability is an urban process that increased in a post-communist Bucharest, raising the concern that the population at risk lacks the capacity to cope with disasters. The assessment of the indices indicates a significant and similar clustering pattern of the census administrative units, with an overlap between the clustering areas affected by high social vulnerability. Our proposed SEVI model suggests adjustment sensitivity, useful in the expert-opinion accuracy.

[Ecological vulnerability of coal mining area: a case study of Shengli Coalfield in Xilinguole of Inner Mongolia, China].

PubMed

Quan, Zhan-Jun; Li, Yuan; Li, Jun-Sheng; Han, Yu; Xiao, Neng-Wen; Fu, Meng-Di

2013-06-01

In this paper, an ecological vulnerability evaluation index system for the Shengli Coalfield in Xilinguole of Inner Mongolia was established, which included 16 factors in ecological sensitivity, natural and social pressure, and ecological recovery capacity, respectively. Based on the expert scoring method and analytic hierarchy process (AHP), an ecological vulnerability model was built for the calculation of the regional ecological vulnerability by means of RS and GIS spatial analysis. An analysis of the relationships between land use and ecological vulnerability was also made, and the results were tested by spatial auto-correlation analysis. Overall, the ecological vulnerability of the study area was at medium-high level. The exploitation of four opencast areas in the Coalfield caused a significant increase of ecological vulnerability. Moreover, due to the effects of mine drained water and human activities, the 300 -2000 m around the opencast areas was turning into higher ecologically fragile area. With further exploitation, the whole Coalfield was evolved into moderate and heavy ecological vulnerability area, and the coal resources mining was a key factor in this process. The cluster analysis showed that the spatial distribution of the ecological vulnerability in the study area had reasonable clustering characteristics. To decrease the population density, control the grazing capacity of grassland, and regulate the ratios of construction land and cultivated land could be the optimal ways for resolving the natural and social pressure, and to increase the investment and improve the vegetation recovery coefficient could be the fundamental measures for decreasing the ecological vulnerability of the study area.

Methods for the quantification of coarse woody debris and an examination of its spatial patterning: A study from the Tenderfoot Creek Experimental Forest, MT

Treesearch

Paul B. Alaback; Duncan C. Lutes

1997-01-01

Methods for the quantification of coarse woody debris volume and the description of spatial patterning were studied in the Tenderfoot Creek Experimental Forest, Montana. The line transect method was found to be an accurate, unbiased estimator of down debris volume (> 10cm diameter) on 1/4 hectare fixed-area plots, when perpendicular lines were used. The Fischer...

Capturing subregional variability in regional-scale climate change vulnerability assessments of natural resources

Treesearch

Polly C. Buotte; David L. Peterson; Kevin S. McKelvey; Jeffrey A. Hicke

2016-01-01

Natural resource vulnerability to climate change can depend on the climatology and ecological conditions at a particular site. Here we present a conceptual framework for incorporating spatial variability in natural resource vulnerability to climate change in a regional-scale assessment. The framework was implemented in the first regional-scale vulnerability...

Assessing and managing freshwater ecosystems vulnerable to global change

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Birge, Hannah E.; Drakare, Stina; McKie, Brendan G.; Johnson, Richard K.

2014-01-01

Freshwater ecosystems are important for global biodiversity and provide essential ecosystem services. There is consensus in the scientific literature that freshwater ecosystems are vulnerable to the impacts of environmental change, which may trigger irreversible regime shifts upon which biodiversity and ecosystem services may be lost. There are profound uncertainties regarding the management and assessment of the vulnerability of freshwater ecosystems to environmental change. Quantitative approaches are needed to reduce this uncertainty. We describe available statistical and modeling approaches along with case studies that demonstrate how resilience theory can be applied to aid decision-making in natural resources management. We highlight especially how long-term monitoring efforts combined with ecological theory can provide a novel nexus between ecological impact assessment and management, and the quantification of systemic vulnerability and thus the resilience of ecosystems to environmental change.

Forest climate change Vulnerability and Adaptation Assessment in Himalayas

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Shrestha, H. L.; Agarwal, N. K.; Choudhurya, D.; Gilani, H.; Dhonju, H. K.; Murthy, M. S. R.

2014-11-01

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

Genetic k-Means Clustering Approach for Mapping Human Vulnerability to Chemical Hazards in the Industrialized City: A Case Study of Shanghai, China

PubMed Central

Shi, Weifang; Zeng, Weihua

2013-01-01

Reducing human vulnerability to chemical hazards in the industrialized city is a matter of great urgency. Vulnerability mapping is an alternative approach for providing vulnerability-reducing interventions in a region. This study presents a method for mapping human vulnerability to chemical hazards by using clustering analysis for effective vulnerability reduction. Taking the city of Shanghai as the study area, we measure human exposure to chemical hazards by using the proximity model with additionally considering the toxicity of hazardous substances, and capture the sensitivity and coping capacity with corresponding indicators. We perform an improved k-means clustering approach on the basis of genetic algorithm by using a 500 m × 500 m geographical grid as basic spatial unit. The sum of squared errors and silhouette coefficient are combined to measure the quality of clustering and to determine the optimal clustering number. Clustering result reveals a set of six typical human vulnerability patterns that show distinct vulnerability dimension combinations. The vulnerability mapping of the study area reflects cluster-specific vulnerability characteristics and their spatial distribution. Finally, we suggest specific points that can provide new insights in rationally allocating the limited funds for the vulnerability reduction of each cluster. PMID:23787337

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao, Huaiyong, E-mail: huaiyongshao@163.com; Center for Global Change and Earth Observations, Michigan State University, East Lansing 48823, MI; Sun, Xiaofei

The Chinese government has conducted the Returning Grazing Land to Grassland Project (RGLGP) across large portions of grasslands from western China since 2003. In order to explore and understand the impact in the grassland's eco-environment during the RGLGP, we utilized Projection Pursuit Model (PPM) and Geographic Information System (GIS) to develop a spatial assessment model to examine the ecological vulnerability of the grassland. Our results include five indications: (1) it is practical to apply the spatial PPM on ecological vulnerability assessment for the grassland. This methodology avoids creating an artificial hypothesis, thereby providing objective results that successfully execute a multi-indexmore » assessment process and analysis under non-linear systems in eco-environments; (2) the spatial PPM is not only capable of evaluating regional eco-environmental vulnerability in a quantitative way, but also can quantitatively demonstrate the degree of effect in each evaluation index for regional eco-environmental vulnerability; (3) the eco-environment of the Xianshui River Basin falls into the medium range level. The normalized difference vegetation index (NDVI) and land use cover and change (LUCC) crucially influence the Xianshui River Basin's eco-environmental vulnerability. Generally, in the Xianshui River Basin, regional eco-environmental conditions improved during 2000 and 2010. The RGLGP positively affected NDVI and LUCC structure, thereby promoting the enhancement of the regional eco-environment; (4) the Xianshui River Basin divides its ecological vulnerability across different levels; therefore our study investigates three ecological regions and proposes specific suggestions for each in order to assist in eco-environmental protection and rehabilitation; and lastly that (5) the spatial PPM established by this study has the potential to be applied on all types of grassland eco-environmental vulnerability assessments under the RGLGP and under the similar conditions in the Returning Agriculture Land to Forest Project (RALFP). However, when establishing an eco-environmental vulnerability assessment model, it is necessary to choose suitable evaluation indexes in accordance with regional eco-environmental characteristics. - Highlights: • We present a method for regional eco-environmental vulnerability assessment. • The method combines Projection Pursuit Model with Geographic Information System. • The Returning Grazing Land to Grassland Project is crucial to environment recovery. • The method is more objective to assess regional eco-environmental vulnerability.« less

Development of a heat vulnerability index for New York State.

PubMed

Nayak, S G; Shrestha, S; Kinney, P L; Ross, Z; Sheridan, S C; Pantea, C I; Hsu, W H; Muscatiello, N; Hwang, S A

2017-12-01

The frequency and intensity of extreme heat events are increasing in New York State (NYS) and have been linked with increased heat-related morbidity and mortality. But these effects are not uniform across the state and can vary across large regions due to regional sociodemographic and environmental factors which impact an individual's response or adaptive capacity to heat and in turn contribute to vulnerability among certain populations. We developed a heat vulnerability index (HVI) to identify heat-vulnerable populations and regions in NYS. Census tract level environmental and sociodemographic heat-vulnerability variables were used to develop the HVI to identify heat-vulnerable populations and areas. Variables were identified from a comprehensive literature review and climate-health research in NYS. We obtained data from 2010 US Census Bureau and 2011 National Land Cover Database. We used principal component analysis to reduce correlated variables to fewer uncorrelated components, and then calculated the cumulative HVI for each census tract by summing up the scores across the components. The HVI was then mapped across NYS (excluding New York City) to display spatial vulnerability. The prevalence rates of heat stress were compared across HVI score categories. Thirteen variables were reduced to four meaningful components representing 1) social/language vulnerability; 2) socioeconomic vulnerability; 3) environmental/urban vulnerability; and 4) elderly/ social isolation. Vulnerability to heat varied spatially in NYS with the HVI showing that metropolitan areas were most vulnerable, with language barriers and socioeconomic disadvantage contributing to the most vulnerability. Reliability of the HVI was supported by preliminary results where higher rates of heat stress were collocated in the regions with the highest HVI. The NYS HVI showed spatial variability in heat vulnerability across the state. Mapping the HVI allows quick identification of regions in NYS that could benefit from targeted interventions. The HVI will be used as a planning tool to help allocate appropriate adaptation measures like cooling centers and issue heat alerts to mitigate effects of heat in vulnerable areas. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evaluation on island ecological vulnerability and its spatial heterogeneity.

PubMed

Chi, Yuan; Shi, Honghua; Wang, Yuanyuan; Guo, Zhen; Wang, Enkang

2017-12-15

The evaluation on island ecological vulnerability (IEV) can help reveal the comprehensive characteristics of the island ecosystem and provide reference for controlling human activities on islands. An IEV evaluation model which reflects the land-sea dual features, natural and anthropogenic attributes, and spatial heterogeneity of the island ecosystem was established, and the southern islands of Miaodao Archipelago in North China were taken as the study area. The IEV, its spatial heterogeneity, and its sensitivities to the evaluation elements were analyzed. Results indicated that the IEV was in status of mild vulnerability in the archipelago scale, and population pressure, ecosystem productivity, environmental quality, landscape pattern, and economic development were the sensitive elements. The IEV showed significant spatial heterogeneities both in land and surrounding waters sub-ecosystems. Construction scale control, optimization of development allocation, improvement of exploitation methods, and reasonable ecological construction are important measures to control the IEV. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Methodology for Dynamic Security Risk Quantification and Optimal Resource Allocation of Security Assets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brigantic, Robert T.; Betzsold, Nick J.; Bakker, Craig KR

In this presentation we overview a methodology for dynamic security risk quantification and optimal resource allocation of security assets for high profile venues. This methodology is especially applicable to venues that require security screening operations such as mass transit (e.g., train or airport terminals), critical infrastructure protection (e.g., government buildings), and largescale public events (e.g., concerts or professional sports). The method starts by decomposing the three core components of risk -- threat, vulnerability, and consequence -- into their various subcomponents. For instance, vulnerability can be decomposed into availability, accessibility, organic security, and target hardness and each of these can bemore » evaluated against the potential threats of interest for the given venue. Once evaluated, these subcomponents are rolled back up to compute the specific value for the vulnerability core risk component. Likewise, the same is done for consequence and threat, and then risk is computed as the product of these three components. A key aspect of our methodology is dynamically quantifying risk. That is, we incorporate the ability to uniquely allow the subcomponents and core components, and in turn, risk, to be quantified as a continuous function of time throughout the day, week, month, or year as appropriate.« less

An exploratory spatial analysis of social vulnerability and smoke plum dispersion in the U.S

Treesearch

Cassandra Johnson Gaither; Scott Goodrick; Bryn Elise Murphy; Neelam Poudyal

2015-01-01

This study explores the spatial association between social vulnerability and smoke plume dispersion at the census block group level for the 13 southern states in the USDA Forest Service’s Region 8. Using environmental justice as a conceptual basis, we use Exploratory Spatial Data Analysis to identify clusters or “hot spots” for the incidence of both higher than average...

Performance of the CORDEX regional climate models in simulating offshore wind and wind potential

NASA Astrophysics Data System (ADS)

Kulkarni, Sumeet; Deo, M. C.; Ghosh, Subimal

2018-03-01

This study is oriented towards quantification of the skill addition by regional climate models (RCMs) in the parent general circulation models (GCMs) while simulating wind speed and wind potential with particular reference to the Indian offshore region. To arrive at a suitable reference dataset, the performance of wind outputs from three different reanalysis datasets is evaluated. The comparison across the RCMs and their corresponding parent GCMs is done on the basis of annual/seasonal wind statistics, intermodel bias, wind climatology, and classes of wind potential. It was observed that while the RCMs could simulate spatial variability of winds, well for certain subregions, they generally failed to replicate the overall spatial pattern, especially in monsoon and winter. Various causes of biases in RCMs were determined by assessing corresponding maps of wind vectors, surface temperature, and sea-level pressure. The results highlight the necessity to carefully assess the RCM-yielded winds before using them for sensitive applications such as coastal vulnerability and hazard assessment. A supplementary outcome of this study is in form of wind potential atlas, based on spatial distribution of wind classes. This could be beneficial in suitably identifying viable subregions for developing offshore wind farms by intercomparing both the RCM and GCM outcomes. It is encouraging that most of the RCMs and GCMs indicate that around 70% of the Indian offshore locations in monsoon would experience mean wind potential greater than 200 W/m2.

Spatial quantification of groundwater abstraction in the irrigated Indus basin.

PubMed

Cheema, M J M; Immerzeel, W W; Bastiaanssen, W G M

2014-01-01

Groundwater abstraction and depletion were assessed at a 1-km resolution in the irrigated areas of the Indus Basin using remotely sensed evapotranspiration (ET) and precipitation; a process-based hydrological model and spatial information on canal water supplies. A calibrated Soil and Water Assessment Tool (SWAT) model was used to derive total annual irrigation applied in the irrigated areas of the basin during the year 2007. The SWAT model was parameterized by station corrected precipitation data (R) from the Tropical Rainfall Monitoring Mission, land use, soil type, and outlet locations. The model was calibrated using a new approach based on spatially distributed ET fields derived from different satellite sensors. The calibration results were satisfactory and strong improvements were obtained in the Nash-Sutcliffe criterion (0.52 to 0.93), bias (-17.3% to -0.4%), and the Pearson correlation coefficient (0.78 to 0.93). Satellite information on R and ET was then combined with model results of surface runoff, drainage, and percolation to derive groundwater abstraction and depletion at a nominal resolution of 1 km. It was estimated that in 2007, 68 km³ (262 mm) of groundwater was abstracted in the Indus Basin while 31 km³ (121 mm) was depleted. The mean error was 41 mm/year and 62 mm/year at 50% and 70% probability of exceedance, respectively. Pakistani and Indian Punjab and Haryana were the most vulnerable areas to groundwater depletion and strong measures are required to maintain aquifer sustainability. © 2013, National Ground Water Association.

Meteorological risks as drivers of innovation for agroecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van de Vyver, Hans; Zamani, Sepideh; Curnel, Yannick; Planchon, Viviane; Verspecht, Ann; Van Huylenbroeck, Guido

2015-04-01

Devastating weather-related events recorded in recent years have captured the interest of the general public in Belgium. The MERINOVA project research hypothesis is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management which is being tested using a "chain of risk" approach. The major objectives are to (1) assess the probability of extreme meteorological events by means of probability density functions; (2) analyse the extreme events impact of on agro-ecosystems using process-based bio-physical modelling methods; (3) identify the most vulnerable agro-ecosystems using fuzzy multi-criteria and spatial analysis; (4) uncover innovative risk management and adaptation options using actor-network theory and economic modelling; and, (5) communicate to research, policy and practitioner communities using web-based techniques. Generalized Extreme Value (GEV) theory was used to model annual rainfall maxima based on location-, scale- and shape-parameters that determine the centre of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Likewise the distributions of consecutive rainy days, rainfall deficits and extreme 24-hour rainfall were modelled. Spatial interpolation of GEV-derived return levels resulted in maps of extreme precipitation, precipitation deficits and wet periods. The degree of temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was determined using a bio-physically based modelling framework that couples phenological models, a soil water balance, crop growth and environmental models. 20-year return values were derived for frost, heat stress, drought, waterlogging and field access during different sensitive stages for different arable crops. Extreme yield values were detected from detrended long term arable yields and relationships were found with soil moisture conditions, heat stress or other meteorological variables during the season. A methodology for identifying agro-ecosystem vulnerability was developed using spatially explicit information and was tested for arable crop production in Belgium. The different components of vulnerability for a region include spatial information on meteorology, soil available water content, soil erosion, the degree of waterlogging, crop share and the diversity of potato varieties. The level of vulnerability and resilience of an agro-ecosystem is also determined by risk management. The types of agricultural risk and their relative importance differ across sectors and farm types. Risk types are further distinguished according to production, market, institutional, financial and liability risks. Strategies are often combined in the risk management strategy of a farmer and include reduction and prevention, mitigation, coping and impact reduction. Based on an extensive literature review, a portfolio of potential strategies was identified at farm, market and policy level. Research hypotheses were tested using an on-line questionnaire on knowledge of agricultural risk, measuring the general risk aversion of the farmer and risk management strategies. The "chain of risk" approach adopted as a research methodology allows for investigating the hypothesis that meteorological risks act as drivers for agricultural innovation. Risks related to extreme weather events in Belgium are mainly caused by heat, frost, excess rainfall, drought and storms, and their impact is predominantly felt by arable, horticultural and extensive dairy farmers. Quantification of the risk is evaluated in terms of probability of occurrence, magnitude, frequency and extent of impact on several agro-ecosystems services. The spatial extent of vulnerability is developed by integrating different layers of geo-information, while risk management is analysed using questionnaires and economic modelling methods. Future work will concentrate on the further development and testing of the currently developed modelling methodologies. https://merinova.vito.be The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

Fuzzy-based assessment of groundwater intrinsic vulnerability of a volcanic aquifer in the Chilean Andean Valley.

PubMed

Duhalde, Denisse J; Arumí, José L; Oyarzún, Ricardo A; Rivera, Diego A

2018-06-11

A fuzzy logic approach has been proposed to face the uncertainty caused by sparse data in the assessment of the intrinsic vulnerability of a groundwater system with parametric methods in Las Trancas Valley, Andean Mountain, south-central Chile, a popular touristic place in Chile, but lacking of a centralized drinking and sewage water public systems; this situation is a potentially source of groundwater pollution. Based on DRASTIC, GOD, and EKv and the expert knowledge of the study area, the Mamdani fuzzy approach was generated and the spatial data were processed by ArcGIS. The groundwater system exhibited areas with high, medium, and low intrinsic vulnerability indices. The fuzzy approach results were compared with traditional methods results, which, in general, have shown a good spatial agreement even though significant changes were also identified in the spatial distribution of the indices. The Mamdani logic approach has shown to be a useful and practical tool to assess the intrinsic vulnerability of an aquifer under sparse data conditions.

The influence of urban heat islands and socioeconomic factors on the spatial distribution of Aedes aegypti larval habitats.

PubMed

De Azevedo, Thiago S; Bourke, Brian Patrick; Piovezan, Rafael; Sallum, Maria Anice M

2018-05-08

We addressed the potential associations among the temporal and spatial distribution of larval habitats of Aedes (Stegomyia) aegypti, the presence of urban heat islands and socioeconomic factors. Data on larval habitats were collected in Santa Bárbara d'Oeste, São Paulo, Brazil, from 2004 to 2006, and spatial and temporal variations were analysed using a wavelet-based approach. We quantified urban heat islands by calculating surface temperatures using the results of wavelet analyses and grey level transformation from Thematic Mapper images (Landsat 5). Ae. aegypti larval habitats were geo-referenced corresponding to the wavelet analyses to test the potential association between geographical distribution of habitats and surface temperature. In an inhomogeneous spatial point process, we estimated the frequency of occurrence of larval habitats in relation to temperature. The São Paulo State Social Vulnerability Index in the municipality of Santa Barbára d'Oeste was used to test the potential association between presence of larval habitats and social vulnerability. We found abundant Ae. aegypti larval habitats in areas of higher surface temperature and social vulnerability and fewer larval habitats in areas with lower surface temperature and social vulnerability.

Land cover as an important factor for landslide risk assessment

NASA Astrophysics Data System (ADS)

Promper, C.; Glade, T.; Puissant, A.; Malet, J.-P.

2012-04-01

Landcover change is a crucial component of hazard and vulnerability in terms of quantification of possible future landslide risk, and the importance for spatial planners but also individuals is obvious. Damage of property, losses of agricultural land, loss of production but also damaged infrastructures and fatalities may be the result of landslide hazards. To avoid these economic damages as well as possible fatalities in the future, a method of assessing spatial but also temporal patterns of landslides is necessary. This study represents results of landcover modeling as a first step to the proposition of scenario of landslide risk for the future. The method used for future land cover analysis is the CLUE modeling framework combining past and actual observed landcover conditions. The model is based on a statistical relationship between the actual land cover and driving forces. The allocation of landcover pixel is modified by possible autonomous developments and competition between land use types. (Verburg et al. 1999) The study area is located in a district in the alpine foreland of Lower Austria: Waidhofen/Ybbs, of about 130km2. The topography is characterized by narrow valleys, flat plateau and steep slopes. The landcover is characterized by region of densely populated areas in the valley bottom along the Ybbs River, and a series of separated farm houses on the top of the plateau. Population density is about 90 persons / km2 which represent the observed population density of Austria. The initial landcover includes forest, grassland, culture, built-up areas and individual farms. Most of the observed developments are controlled by the topography (along the valleys) and the actual road network. The results of the landcover model show different scenarios of changes in the landslide prone landcover types. These maps will be implemented into hazard analysis but also into vulnerability assessment regarding elements at risk. Verburg, P.H., de Koning, G.H.J., Kok, K., Veldkamp, A. & Bouma, J. 1999. A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use. Ecological Modelling 116 (1): 45-61.

A Spatial Framework to Map Heat Health Risks at Multiple Scales.

PubMed

Ho, Hung Chak; Knudby, Anders; Huang, Wei

2015-12-18

In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G(i) index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G(i) index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.

Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India.

PubMed

Krishnan, Pandian; Ananthan, Pachampalayam Shanmugam; Purvaja, Ramachandran; Joyson Joe Jeevamani, Jeyapaul; Amali Infantina, John; Srinivasa Rao, Cherukumalli; Anand, Arur; Mahendra, Ranganalli Somashekharappa; Sekar, Iyyapa; Kareemulla, Kalakada; Biswas, Amit; Kalpana Sastry, Regulagedda; Ramesh, Ramachandran

2018-05-31

The impacts of climate change are of particular concern to the coastal region of tropical countries like India, which are exposed to cyclones, floods, tsunami, seawater intrusion, etc. Climate-change adaptation presupposes comprehensive assessment of vulnerability status. Studies so far relied either on remote sensing-based spatial mapping of physical vulnerability or on certain socio-economic aspects with limited scope for upscaling or replication. The current study is an attempt to develop a holistic and robust framework to assess the vulnerability of coastal India at different levels. We propose and estimate cumulative vulnerability index (CVI) as a function of exposure, sensitivity and adaptive capacity, at the village level, using nationally comparable and credible datasets. The exposure index (EI) was determined at the village level by decomposing the spatial multi-hazard maps, while sensitivity (SI) and adaptive capacity indices (ACI) were estimated using 23 indicators, covering social and economic aspects. The indicators were identified through the literature review, expert consultations, opinion survey, and were further validated through statistical tests. The socio-economic vulnerability index (SEVI) was constructed as a function of sensitivity and adaptive capacity for planning grassroot-level interventions and adaptation strategies. The framework was piloted in Sindhudurg, a coastal district in Maharashtra, India. It comprises 317 villages, spread across three taluks viz., Devgad, Malvan and Vengurla. The villages in Sindhudurg were ranked based on this multi-criteria approach. Based on CVI values, 92 villages (30%) in Sindhudurg were identified as highly vulnerable. We propose a decision tool for identifying villages vulnerable to changing climate, based on their level of sensitivity and adaptive capacity in a two-dimensional matrix, thus aiding in planning location-specific interventions. Here, vulnerability indicators are classified and designated as 'drivers' (indicators with significantly high values and intervention priority) and 'buffers' (indicators with low-to-moderate values) at the village level. The framework provides for aggregation or decomposition of CVI and other sub-indices, in order to plan spatial contingency plans and enable swift action for climate adaptation.

Modelling the elements of country vulnerability to earthquake disasters.

PubMed

Asef, M R

2008-09-01

Earthquakes have probably been the most deadly form of natural disaster in the past century. Diversity of earthquake specifications in terms of magnitude, intensity and frequency at the semicontinental scale has initiated various kinds of disasters at a regional scale. Additionally, diverse characteristics of countries in terms of population size, disaster preparedness, economic strength and building construction development often causes an earthquake of a certain characteristic to have different impacts on the affected region. This research focuses on the appropriate criteria for identifying the severity of major earthquake disasters based on some key observed symptoms. Accordingly, the article presents a methodology for identification and relative quantification of severity of earthquake disasters. This has led to an earthquake disaster vulnerability model at the country scale. Data analysis based on this model suggested a quantitative, comparative and meaningful interpretation of the vulnerability of concerned countries, and successfully explained which countries are more vulnerable to major disasters.

Construction of an integrated social vulnerability index in urban areas prone to flash flooding

NASA Astrophysics Data System (ADS)

Aroca-Jimenez, Estefania; Bodoque, Jose Maria; Garcia, Juan Antonio; Diez-Herrero, Andres

2017-09-01

Among the natural hazards, flash flooding is the leading cause of weather-related deaths. Flood risk management (FRM) in this context requires a comprehensive assessment of the social risk component. In this regard, integrated social vulnerability (ISV) can incorporate spatial distribution and contribution and the combined effect of exposure, sensitivity and resilience to total vulnerability, although these components are often disregarded. ISV is defined by the demographic and socio-economic characteristics that condition a population's capacity to cope with, resist and recover from risk and can be expressed as the integrated social vulnerability index (ISVI). This study describes a methodological approach towards constructing the ISVI in urban areas prone to flash flooding in Castilla y León (Castile and León, northern central Spain, 94 223 km2, 2 478 376 inhabitants). A hierarchical segmentation analysis (HSA) was performed prior to the principal components analysis (PCA), which helped to overcome the sample size limitation inherent in PCA. ISVI was obtained from weighting vulnerability factors based on the tolerance statistic. In addition, latent class cluster analysis (LCCA) was carried out to identify spatial patterns of vulnerability within the study area. Our results show that the ISVI has high spatial variability. Moreover, the source of vulnerability in each urban area cluster can be identified from LCCA. These findings make it possible to design tailor-made strategies for FRM, thereby increasing the efficiency of plans and policies and helping to reduce the cost of mitigation measures.

The geography of post-disaster mental health: spatial patterning of psychological vulnerability and resilience factors in New York City after Hurricane Sandy.

PubMed

Gruebner, Oliver; Lowe, Sarah R; Sampson, Laura; Galea, Sandro

2015-06-10

Only very few studies have investigated the geographic distribution of psychological resilience and associated mental health outcomes after natural or man made disasters. Such information is crucial for location-based interventions that aim to promote recovery in the aftermath of disasters. The purpose of this study therefore was to investigate geographic variability of (1) posttraumatic stress (PTS) and depression in a Hurricane Sandy affected population in NYC and (2) psychological vulnerability and resilience factors among affected areas in NYC boroughs. Cross-sectional telephone survey data were collected 13 to 16 months post-disaster from household residents (N = 418 adults) in NYC communities that were most heavily affected by the hurricane. The Posttraumatic Stress Checklist for DSM-5 (PCL-5) was applied for measuring posttraumatic stress and the nine-item Patient Health Questionnaire (PHQ-9) was used for measuring depression. We applied spatial autocorrelation and spatial regimes regression analyses, to test for spatial clusters of mental health outcomes and to explore whether associations between vulnerability and resilience factors and mental health differed among New York City's five boroughs. Mental health problems clustered predominantly in neighborhoods that are geographically more exposed towards the ocean indicating a spatial variation of risk within and across the boroughs. We further found significant variation in associations between vulnerability and resilience factors and mental health. Race/ethnicity (being Asian or non-Hispanic black) and disaster-related stressors were vulnerability factors for mental health symptoms in Queens, and being employed and married were resilience factors for these symptoms in Manhattan and Staten Island. In addition, parental status was a vulnerability factor in Brooklyn and a resilience factor in the Bronx. We conclude that explanatory characteristics may manifest as psychological vulnerability and resilience factors differently across different regional contexts. Our spatial epidemiological approach is transferable to other regions around the globe and, in the light of a changing climate, could be used to strengthen the psychosocial resources of demographic groups at greatest risk of adverse outcomes pre-disaster. In the aftermath of a disaster, the approach can be used to identify survivors at greatest risk and to plan for targeted interventions to reach them.

An Analysis of HIV and AIDS Spatial Awareness and Vulnerability Level with Specific Reference to Staff at One Polytechnic in Zimbabwe

ERIC Educational Resources Information Center

Gatsi, Caroline; Chikuvadze, Pinias; Mugijima, Samuel

2016-01-01

With the gravity of the HIV and AIDS situation in most African nations and its implications for the education sector, a study was undertaken to analyze the spatial awareness and vulnerability level to pandemic in tertiary institutions with specific reference to academic and support staff at one polytechnic in Zimbabwe. A sample comprised of…

[Mapping environmental vulnerability from ETM + data in the Yellow River Mouth Area].

PubMed

Wang, Rui-Yan; Yu, Zhen-Wen; Xia, Yan-Ling; Wang, Xiang-Feng; Zhao, Geng-Xing; Jiang, Shu-Qian

2013-10-01

The environmental vulnerability retrieval is important to support continuing data. The spatial distribution of regional environmental vulnerability was got through remote sensing retrieval. In view of soil and vegetation, the environmental vulnerability evaluation index system was built, and the environmental vulnerability of sampling points was calculated by the AHP-fuzzy method, then the correlation between the sampling points environmental vulnerability and ETM + spectral reflectance ratio including some kinds of conversion data was analyzed to determine the sensitive spectral parameters. Based on that, models of correlation analysis, traditional regression, BP neural network and support vector regression were taken to explain the quantitative relationship between the spectral reflectance and the environmental vulnerability. With this model, the environmental vulnerability distribution was retrieved in the Yellow River Mouth Area. The results showed that the correlation between the environmental vulnerability and the spring NDVI, the September NDVI and the spring brightness was better than others, so they were selected as the sensitive spectral parameters. The model precision result showed that in addition to the support vector model, the other model reached the significant level. While all the multi-variable regression was better than all one-variable regression, and the model accuracy of BP neural network was the best. This study will serve as a reliable theoretical reference for the large spatial scale environmental vulnerability estimation based on remote sensing data.

Delineation of Spatial Variability in the Temperature-Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada.

PubMed

Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B

2017-01-01

Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998-2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Our methods provide a data-driven framework for spatial delineation of the temperature--mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature-mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66-75; http://dx.doi.org/10.1289/EHP224.

Multiple Natural Hazards Assessment and Comparison to Planned Land Use in an Andean Touristic Site within the Riskscape Central Chile

NASA Astrophysics Data System (ADS)

Braun, Andreas; Jaque Castillo, Edilia

2017-04-01

The Andes of central Chile are a natural environment characterized by multiple natural hazards (mass movements, volcanic hazards, seismic hazards, snow avalanches to name a few). The totality of these hazards, according to the notion of Müller-Mahn et al. an in relation to vulnerable entities, spans a riskscape. Spatial planning should take this riskscape into account in order to ensure a save an resilient regional development. However, as frequently observed in developing or newly developed countries, such precaution measures are only hardly realized. Spatial planing tends to be reactive to private inversion, opportunistic and frequently clientelistic. This results in spatial structures whose future development is vulnerable to natural disasters. The contribution analyses these circumstances within a riskscape in central Chile. Within the VIII. Region, close to the volcanic complex Nevados de Chillan, a touristic development around a Hotel for winter sports is established. However, the place is affected by a multitude of natural hazards. The contribution, on the basis of primary and secondary data, first provides hazard maps for several natural hazards. Secondly, the individual hazard maps are merged to an overall hazard map. This overall hazard map is related to the vulnerable entities to span a riskscape. The vulnerable entities are settlements, but also tourist infrastructures. Then, the contribution compares how a precautions spatial planning could have avoided putting vulnerable entities at risk, which spatial structure - especially regarding tourism - is actually found and which challenges for spatial development do exist. It reveals that the most important tourist infrastructures are found particularly at places, characterized by a high overall hazard. Furthermore, it will show that alternatives at economically equally attractive sites, but with a much smaller overall hazard, would have existed. It concludes by discussing possible reasons for this by considering the Chilean planning system.

Delineation of Spatial Variability in the Temperature–Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada

PubMed Central

Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B.

2016-01-01

Background: Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. Objectives: We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Methods: Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998–2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. Results: The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Conclusions: Our methods provide a data-driven framework for spatial delineation of the temperature-–mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature–mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66–75; http://dx.doi.org/10.1289/EHP224 PMID:27346526

Improving poverty and inequality modelling in climate research

NASA Astrophysics Data System (ADS)

Rao, Narasimha D.; van Ruijven, Bas J.; Riahi, Keywan; Bosetti, Valentina

2017-12-01

As climate change progresses, the risk of adverse impacts on vulnerable populations is growing. As governments seek increased and drastic action, policymakers are likely to seek quantification of climate-change impacts and the consequences of mitigation policies on these populations. Current models used in climate research have a limited ability to represent the poor and vulnerable, or the different dimensions along which they face these risks. Best practices need to be adopted more widely, and new model features that incorporate social heterogeneity and different policy mechanisms need to be developed. Increased collaboration between modellers, economists, and other social scientists could aid these developments.

Drought vulnerability assessment of maize in Sub-Saharan Africa: Insights from physical and social perspectives

NASA Astrophysics Data System (ADS)

Kamali, Bahareh; Abbaspour, Karim C.; Wehrli, Bernhard; Yang, Hong

2018-03-01

Drought as a slow-onset phenomenon inflicts important losses to agriculture where the degree of vulnerability depends not only on physical variables such as precipitation and temperature, but also on societal preparedness. While the scopes of physical and social vulnerability are very different in nature, studies distinguishing these two aspects have been lacking. In this study we address the physical and social aspects of drought vulnerability of maize (CDVIphy and CDVIsoc) in Sub-Saharan Africa (SSA). To quantify vulnerability, we applied a probabilistic framework combining a Drought Exposure Index (DEI) with a physical or social Crop Failure Index, CFIphy or CFIsoc, respectively. DEI was derived from the exceedance probability of precipitation. Maize yields, simulated using the Environmental Policy Integrated Climate (EPIC) model, were used to build CFIphy, whereas the residual of simulated and FAO recorded yields were used to construct CFIsoc. The results showed that southern and partially central Africa are more vulnerable to physical drought as compared to other regions. Central and western Africa, however, are socially highly vulnerable. Comparison of CDVIphy and CDVIsoc revealed that societal factors cause more vulnerability than physical variables in almost all SSA countries except Nigeria and South Africa. We conclude that quantification of both drought vulnerabilities help a better characterization of droughts and identify regions where more investments in drought preparedness are required.

Exploring spatial patterns of vulnerability for diverse biodiversity descriptors in regional conservation planning.

PubMed

Vimal, Ruppert; Pluvinet, Pascal; Sacca, Céline; Mazagol, Pierre-Olivier; Etlicher, Bernard; Thompson, John D

2012-03-01

In this study, we developed a multi-criteria assessment of spatial variability of the vulnerability of three different biodiversity descriptors: sites of high conservation interest by virtue of the presence of rare or remarkable species, extensive areas of high ecological integrity, and landscape diversity in grid cells across an entire region. We assessed vulnerability in relation to (a) direct threats in and around sites to a distance of 2 km associated with intensive agriculture, building and road infrastructure and (b) indirect effects of human population density on a wider scale (50 km). The different combinations of biodiversity and threat indicators allowed us to set differential priorities for biodiversity conservation and assess their spatial variation. For example, with this method we identified sites and grid cells which combined high biodiversity with either high threat values or low threat values for the three different biodiversity indicators. In these two classes the priorities for conservation planning will be different, reduce threat values in the former and restrain any increase in the latter. We also identified low priority sites (low biodiversity with either high or low threats). This procedure thus allows for the integration of a spatial ranking of vulnerability into priority setting for regional conservation planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Outdoor characterization of radio frequency electromagnetic fields in a Spanish birth cohort

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calvente, I.; Department of Radiology and Physical Medicine, School of Medicine, University of Granada, Av. Madreid s/n, Granada 18071; Fernández, M.F.

There is considerable public concern in many countries about the possible adverse effects of exposure to non-ionizing radiation electromagnetic fields, especially in vulnerable populations such as children. The aim of this study was to characterize environmental exposure profiles within the frequency range 100 kHz–6 GHz in the immediate surrounds of the dwellings of 123 families from the INMA-Granada birth cohort in Southern Spain, using spot measurements. The arithmetic mean root mean-square electric field (E{sub RMS}) and power density (S{sub RMS}) values were, respectively, 195.79 mV/m (42.3% of data were above this mean) and 799.01 µW/m{sup 2} (30% of values weremore » above this mean); median values were 148.80 mV/m and 285.94 µW/m{sup 2}, respectively. Exposure levels below the quantification limit were assigned a value of 0.01 V/m. Incident field strength levels varied widely among different areas or towns/villages, demonstrating spatial variability in the distribution of exposure values related to the surface area population size and also among seasons. Although recorded values were well below International Commission for Non-Ionizing Radiation Protection reference levels, there is a particular need to characterize incident field strength levels in vulnerable populations (e.g., children) because of their chronic and ever-increasing exposure. The effects of incident field strength have not been fully elucidated; however, it may be appropriate to apply the precautionary principle in order to reduce exposure in susceptible groups. - Highlights: • Spot measurements were performed in the immediate surrounds of children's dwellings. • Mean root mean-square electric field and power density values were calculated. • Most recorded values were far below international standard guideline limits. • Data demonstrate spatial variability in the distribution of exposure levels. • While adverse effects are proven, application of the precautionary principle may be appropriate.« less

Ethical implications of location and accelerometer measurement in health research studies with mobile sensing devices.

PubMed

Fuller, Daniel; Shareck, Martine; Stanley, Kevin

2017-10-01

Quantification of individual behaviours using mobile sensing devices, including physical activity and spatial location, is a rapidly growing field in both academic research and the corporate world. In this case study, we summarize the literature examining the ethical aspects of mobile sensing and argue that a robust discussion about the ethical implications of mobile sensing for research purposes has not occurred sufficiently in the literature. Based on our literature summary and guided by basic ethical principles set out in Canadian, US, and International Ethics documents we propose four areas where further discussion should occur: consent, privacy and confidentiality, mitigating risk, and consideration of vulnerable populations. We argue that ongoing consent is crucial for participants to be aware of the precision and volume of data that is collected with mobile sensing devices. Related to privacy we discuss that participants may not agree that anonymized data is sufficient for privacy and confidentiality when mobile sensing data are collected. There has been some discussion about mitigating risk in the literature. We highlight that the researchers' obligations toward mitigating risks that are not directly related to the study purpose are unclear and require considerable discussion. Finally, using mobile sensing devices to study vulnerable populations requires careful consideration, particularly with respect to balancing research needs with participant burden. Based on our discussion, we identify a broad set of unanswered questions about the ethics of mobile sensing that should be addressed by the research community. Copyright © 2017 Elsevier Ltd. All rights reserved.

Urban sprawl and fragmentation in Latin America: a dynamic quantification and characterization of spatial patterns.

PubMed

Inostroza, Luis; Baur, Rolf; Csaplovics, Elmar

2013-01-30

South America is one of the most urbanized continents in the world, where almost 84% of the total population lives in cities, more urbanized than North America (82%) and Europe (73%). Spatial dynamics, their structure, main features, land consumption rates, spatial arrangement, fragmentation degrees and comparability, remain mostly unknown for most Latin American cities. Using satellite imagery the main parameters of sprawl are quantified for 10 Latin American cities over a period of 20 years by monitoring growth patterns and identifying spatial metrics to characterize urban development and sprawling features measured with GIS tools. This quantification contributes to a better understanding of urban form in Latin America. A pervasive spatial expansion has been observed, where most of the studied cities are expanding at fast rates with falling densities trend. Although important differences in the rates of land consumption and densities exist, there is an underlying fragmentation trend towards increasing sprawl. These trends of spatial discontinuity may eventually be intensified by further economic development. Urban Sprawl/Latin America/GIS metrics/spatial development. Copyright © 2012 Elsevier Ltd. All rights reserved.

Building vulnerability to hydro-geomorphic hazards: Estimating damage probability from qualitative vulnerability assessment using logistic regression

NASA Astrophysics Data System (ADS)

Ettinger, Susanne; Mounaud, Loïc; Magill, Christina; Yao-Lafourcade, Anne-Françoise; Thouret, Jean-Claude; Manville, Vern; Negulescu, Caterina; Zuccaro, Giulio; De Gregorio, Daniela; Nardone, Stefano; Uchuchoque, Juan Alexis Luque; Arguedas, Anita; Macedo, Luisa; Manrique Llerena, Nélida

2016-10-01

The focus of this study is an analysis of building vulnerability through investigating impacts from the 8 February 2013 flash flood event along the Avenida Venezuela channel in the city of Arequipa, Peru. On this day, 124.5 mm of rain fell within 3 h (monthly mean: 29.3 mm) triggering a flash flood that inundated at least 0.4 km2 of urban settlements along the channel, affecting more than 280 buildings, 23 of a total of 53 bridges (pedestrian, vehicle and railway), and leading to the partial collapse of sections of the main road, paralyzing central parts of the city for more than one week. This study assesses the aspects of building design and site specific environmental characteristics that render a building vulnerable by considering the example of a flash flood event in February 2013. A statistical methodology is developed that enables estimation of damage probability for buildings. The applied method uses observed inundation height as a hazard proxy in areas where more detailed hydrodynamic modeling data is not available. Building design and site-specific environmental conditions determine the physical vulnerability. The mathematical approach considers both physical vulnerability and hazard related parameters and helps to reduce uncertainty in the determination of descriptive parameters, parameter interdependency and respective contributions to damage. This study aims to (1) enable the estimation of damage probability for a certain hazard intensity, and (2) obtain data to visualize variations in damage susceptibility for buildings in flood prone areas. Data collection is based on a post-flood event field survey and the analysis of high (sub-metric) spatial resolution images (Pléiades 2012, 2013). An inventory of 30 city blocks was collated in a GIS database in order to estimate the physical vulnerability of buildings. As many as 1103 buildings were surveyed along the affected drainage and 898 buildings were included in the statistical analysis. Univariate and bivariate analyses were applied to better characterize each vulnerability parameter. Multiple corresponding analyses revealed strong relationships between the "Distance to channel or bridges", "Structural building type", "Building footprint" and the observed damage. Logistic regression enabled quantification of the contribution of each explanatory parameter to potential damage, and determination of the significant parameters that express the damage susceptibility of a building. The model was applied 200 times on different calibration and validation data sets in order to examine performance. Results show that 90% of these tests have a success rate of more than 67%. Probabilities (at building scale) of experiencing different damage levels during a future event similar to the 8 February 2013 flash flood are the major outcomes of this study.

Intrinsic and specific vulnerability of groundwater in central Spain: the risk of nitrate pollution

NASA Astrophysics Data System (ADS)

Martínez-Bastida, Juan J.; Arauzo, Mercedes; Valladolid, Maria

2010-05-01

The intrinsic vulnerability of groundwater in the Comunidad de Madrid (central Spain) was evaluated using the DRASTIC and GOD indexes. Groundwater vulnerability to nitrate pollution was also assessed using the composite DRASTIC (CD) and nitrate vulnerability (NV) indexes. The utility of these methods was tested by analyzing the spatial distribution of nitrate concentrations in the different aquifers located in the study area: the Tertiary Detrital Aquifer, the Moor Limestone Aquifer, the Cretaceous Limestone Aquifer and the Quaternary Aquifer. Vulnerability maps based on these four indexes showed very similar results, identifying the Quaternary Aquifer and the lower sub-unit of the Moor Limestone Aquifer as deposits subjected to a high risk of nitrate pollution due to intensive agriculture. As far as the spatial distribution of groundwater nitrate concentrations is concerned, the NV index showed the greatest statistical significance ( p < 0.01). This new type of multiplicative model offers greater accuracy in estimations of specific vulnerability with respect to the real impact of each type of land use. The results of this study provide a basis on which to guide the designation of nitrate vulnerable zones in the Comunidad de Madrid, in line with European Union Directive 91/676/EEC.

Economic vulnerability of timber resources to forest fires

Treesearch

Francisco Rodriguez y Silva; Juan Ramon Molina; Armando Gonzalez-Caban; Miguel Angel Herrera Machuca

2012-01-01

The temporal-spatial planning of activities for a territorial fire management program requires knowing the value of forest ecosystems. In this paper we extend to and apply the economic valuation principle to the concept of economic vulnerability and present a methodology for the economic valuation of the forest production ecosystems. The forest vulnerability is...

Vulnerability of the global terrestrial ecosystems to climate change.

PubMed

Li, Delong; Wu, Shuyao; Liu, Laibao; Zhang, Yatong; Li, Shuangcheng

2018-05-27

Climate change has far-reaching impacts on ecosystems. Recent attempts to quantify such impacts focus on measuring exposure to climate change but largely ignore ecosystem resistance and resilience, which may also affect the vulnerability outcomes. In this study, the relative vulnerability of global terrestrial ecosystems to short-term climate variability was assessed by simultaneously integrating exposure, sensitivity, and resilience at a high spatial resolution (0.05°). The results show that vulnerable areas are currently distributed primarily in plains. Responses to climate change vary among ecosystems and deserts and xeric shrublands are the most vulnerable biomes. Global vulnerability patterns are determined largely by exposure, while ecosystem sensitivity and resilience may exacerbate or alleviate external climate pressures at local scales; there is a highly significant negative correlation between exposure and sensitivity. Globally, 61.31% of the terrestrial vegetated area is capable of mitigating climate change impacts and those areas are concentrated in polar regions, boreal forests, tropical rainforests, and intact forests. Under current sensitivity and resilience conditions, vulnerable areas are projected to develop in high Northern Hemisphere latitudes in the future. The results suggest that integrating all three aspects of vulnerability (exposure, sensitivity, and resilience) may offer more comprehensive and spatially explicit adaptation strategies to reduce the impacts of climate change on terrestrial ecosystems. © 2018 John Wiley & Sons Ltd.

Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California.

PubMed

Liévanos, Raoul S

2018-04-16

The California Community Environmental Health Screening Tool (CalEnviroScreen) advances research and policy pertaining to environmental health vulnerability. However, CalEnviroScreen departs from its historical foundations and comparable screening tools by no longer considering racial status as an indicator of environmental health vulnerability and predictor of cumulative pollution burden. This study used conceptual frameworks and analytical techniques from environmental health and inequality literature to address the limitations of CalEnviroScreen, especially its inattention to race-based environmental health vulnerabilities. It developed an adjusted measure of cumulative pollution burden from the CalEnviroScreen 2.0 data that facilitates multivariate analyses of the effect of neighborhood racial composition on cumulative pollution burden, net of other indicators of population vulnerability, traffic density, industrial zoning, and local and regional clustering of pollution burden. Principal component analyses produced three new measures of population vulnerability, including Latina/o cumulative disadvantage that represents the spatial concentration of Latinas/os, economic disadvantage, limited English-speaking ability, and health vulnerability. Spatial error regression analyses demonstrated that concentrations of Latinas/os, followed by Latina/o cumulative disadvantage, are the strongest demographic determinants of adjusted cumulative pollution burden. Findings have implications for research and policy pertaining to cumulative impacts and race-based environmental health vulnerabilities within and beyond California.

Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California

PubMed Central

2018-01-01

The California Community Environmental Health Screening Tool (CalEnviroScreen) advances research and policy pertaining to environmental health vulnerability. However, CalEnviroScreen departs from its historical foundations and comparable screening tools by no longer considering racial status as an indicator of environmental health vulnerability and predictor of cumulative pollution burden. This study used conceptual frameworks and analytical techniques from environmental health and inequality literature to address the limitations of CalEnviroScreen, especially its inattention to race-based environmental health vulnerabilities. It developed an adjusted measure of cumulative pollution burden from the CalEnviroScreen 2.0 data that facilitates multivariate analyses of the effect of neighborhood racial composition on cumulative pollution burden, net of other indicators of population vulnerability, traffic density, industrial zoning, and local and regional clustering of pollution burden. Principal component analyses produced three new measures of population vulnerability, including Latina/o cumulative disadvantage that represents the spatial concentration of Latinas/os, economic disadvantage, limited English-speaking ability, and health vulnerability. Spatial error regression analyses demonstrated that concentrations of Latinas/os, followed by Latina/o cumulative disadvantage, are the strongest demographic determinants of adjusted cumulative pollution burden. Findings have implications for research and policy pertaining to cumulative impacts and race-based environmental health vulnerabilities within and beyond California. PMID:29659481

Vulnerability assessment including tangible and intangible components in the index composition: An Amazon case study of flooding and flash flooding.

PubMed

Andrade, Milena Marília Nogueira de; Szlafsztein, Claudio Fabian

2018-07-15

The vulnerability of cities and communities in the Amazon to flooding and flash flooding is increasing. The effects of extreme events on populations vary across landscapes, causing vulnerability to differ spatially. Traditional vulnerability studies in Brazil and across the world have used the vulnerability index for the country and, more recently, municipality scales. The vulnerability dimensions are exposure, sensitivity, and adaptive capacity. For each of these dimensions, there is a group of indicators that constitutes a vulnerability index using quantitative data. Several vulnerability assessments have used sensitivity and exposure analyses and, recently, adaptive capacity has been considered. The Geographical Information Systems (GIS) analysis allows spatial regional modeling using quantitative vulnerability indicators. This paper presents a local-scale vulnerability assessment in an urban Amazonian area, Santarém City, using interdisciplinary methods. Data for exposure and sensitivity were gathered by remote sensing and census data, respectively. However, adaptive capacity refers to local capacities, whether infrastructural or not, and the latter were gathered by qualitative participatory methods. For the mixed data used to study adaptive capacity, we consider tangible components for countable infrastructure that can cope with hazards, and intangible components that reflect social activities based on risk perceptions and collective action. The results indicate that over 80% of the area is highly or moderately vulnerable to flooding and flash flooding. Exposure and adaptive capacity were determinants of the results. Lower values of adaptive capacity play a significant role in vulnerability enhancement. Copyright © 2018 Elsevier B.V. All rights reserved.

Thalamic Proteome Changes and Behavioral Impairments in Thiamine-deficient Rats.

PubMed

Nunes, Polliana Toledo; Gómez-Mendoza, Diana Paola; Rezende, Cristiana Perdigão; Figueiredo, Henrique César Pereira; Ribeiro, Angela Maria

2018-06-09

Thiamine deficiency (TD) has been used as an experimental model in rodents to study the molecular mechanisms of neurodegeneration and its association with behavioral changes. The aims of the present study were to investigate the spatial cognitive performance of pyrithiamine-induced thiamine deficiency (PTD) in adult male rats and disclose the thalamic proteome alterations caused by a severe TD episode. After the onset of the neurological signs, such as seizure and/or loss of righting reflex, the TD treatment was interrupted. Following 15 days of recovery, all rats were submitted to the spatial cognitive tasks in the Morris Water Maze (MWM). The results show that the PTD rats exhibited deficits during the learning process, which was reverted by repeated training. However, despite the spatial cognitive recovery, some protein changes were not reversible. The proteomic analysis, using label-free quantification, revealed deregulation of 183 thalamic proteins. Using bioinformatic tools, these proteins were categorized according to Gene Ontology functional annotation and metabolic pathways. We show that a severe TD affects proteins involved in different biological processes, such as, oxidative stress, neurotransmitter synthesis and synaptic vesicle cycle. These could explain the outcome in neurotransmitter release changes caused by TD, previously observed by our group and by other authors. These findings disclose the role of key proteins and metabolic pathways probably involved in the neurodegeneration process induced by TD. These proteins represent relevant molecular targets for future studies focusing also on the molecular basis of selective vulnerability of some brain areas to TD insult. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

A comparison of data-driven groundwater vulnerability assessment methods

USGS Publications Warehouse

Sorichetta, Alessandro; Ballabio, Cristiano; Masetti, Marco; Robinson, Gilpin R.; Sterlacchini, Simone

2013-01-01

Increasing availability of geo-environmental data has promoted the use of statistical methods to assess groundwater vulnerability. Nitrate is a widespread anthropogenic contaminant in groundwater and its occurrence can be used to identify aquifer settings vulnerable to contamination. In this study, multivariate Weights of Evidence (WofE) and Logistic Regression (LR) methods, where the response variable is binary, were used to evaluate the role and importance of a number of explanatory variables associated with nitrate sources and occurrence in groundwater in the Milan District (central part of the Po Plain, Italy). The results of these models have been used to map the spatial variation of groundwater vulnerability to nitrate in the region, and we compare the similarities and differences of their spatial patterns and associated explanatory variables. We modify the standard WofE method used in previous groundwater vulnerability studies to a form analogous to that used in LR; this provides a framework to compare the results of both models and reduces the effect of sampling bias on the results of the standard WofE model. In addition, a nonlinear Generalized Additive Model has been used to extend the LR analysis. Both approaches improved discrimination of the standard WofE and LR models, as measured by the c-statistic. Groundwater vulnerability probability outputs, based on rank-order classification of the respective model results, were similar in spatial patterns and identified similar strong explanatory variables associated with nitrate source (population density as a proxy for sewage systems and septic sources) and nitrate occurrence (groundwater depth).

Ozone distribution in remote ecologically vulnerable terrain of the southern Sierra Nevada, CA.

PubMed

Panek, Jeanne; Saah, David; Esperanza, Annie; Bytnerowicz, Andrzej; Fraczek, Witold; Cisneros, Ricardo

2013-11-01

Ozone concentration spatial patterns remain largely uncharacterized across the extensive wilderness areas of the Sierra Nevada, CA, despite being downwind of major pollution sources. These natural areas, including four national parks and four national forests, contain forest species that are susceptible to ozone injury. Forests stressed by ozone are also more vulnerable to other agents of mortality, including insects, pathogens, climate change, and ultimately fire. Here we analyze three years of passive ozone monitor data from the southern Sierra Nevada and interpolate landscape-scale spatial and temporal patterns during the summer-through-fall high ozone concentration period. Segmentation analysis revealed three types of ozone exposure sub-regions: high, low, and variable. Consistently high ozone exposure regions are expected to be most vulnerable to forest mortality. One high exposure sub-region has been documented elsewhere as being further vulnerable to increased drought and fire potential. Identifying such hot-spots of forest vulnerability has utility for prioritizing management. Copyright © 2013 Elsevier Ltd. All rights reserved.

Drought disaster vulnerability mapping of agricultural sector in Bringin District, Semarang Regency

NASA Astrophysics Data System (ADS)

Lestari, D. R.; Pigawati, B.

2018-02-01

Agriculture sector is a sector that is directly affected by drought. The phenomenon of drought disaster on agriculture sector has occurred in Semarang regency. One of districts in Semarang which is affected by drought is Bringin district. Bringin district is a productive agricultural area. However, the district experienced the most severe drought in 2015. The question research of this study is, “How is the spatial distribution of drought vulnerability on agriculture sector in Bringin district, Semarang regency?” The purpose of this study is to determine the spatial distribution of drought vulnerability on agriculture sector to village units in Bringin district. This study investigated drought vulnerability based on Intergovernmental Panel on Climate Change (IPCC) by analyzing exposure, sensitivity, and adaptive capacity through mapping process. This study used quantitative approach. There were formulation analysis, scoring analysis, and overlay analysis. Drought vulnerability on agriculture sector in Bringin district was divided into three categories: low, medium, and high.

A deterministic model of electron transport for electron probe microanalysis

NASA Astrophysics Data System (ADS)

Bünger, J.; Richter, S.; Torrilhon, M.

2018-01-01

Within the last decades significant improvements in the spatial resolution of electron probe microanalysis (EPMA) were obtained by instrumental enhancements. In contrast, the quantification procedures essentially remained unchanged. As the classical procedures assume either homogeneity or a multi-layered structure of the material, they limit the spatial resolution of EPMA. The possibilities of improving the spatial resolution through more sophisticated quantification procedures are therefore almost untouched. We investigate a new analytical model (M 1-model) for the quantification procedure based on fast and accurate modelling of electron-X-ray-matter interactions in complex materials using a deterministic approach to solve the electron transport equations. We outline the derivation of the model from the Boltzmann equation for electron transport using the method of moments with a minimum entropy closure and present first numerical results for three different test cases (homogeneous, thin film and interface). Taking Monte Carlo as a reference, the results for the three test cases show that the M 1-model is able to reproduce the electron dynamics in EPMA applications very well. Compared to classical analytical models like XPP and PAP, the M 1-model is more accurate and far more flexible, which indicates the potential of deterministic models of electron transport to further increase the spatial resolution of EPMA.

Resolution and quantification accuracy enhancement of functional delay and sum beamforming for three-dimensional acoustic source identification with solid spherical arrays

NASA Astrophysics Data System (ADS)

Chu, Zhigang; Yang, Yang; Shen, Linbang

2017-05-01

Functional delay and sum (FDAS) is a novel beamforming algorithm introduced for the three-dimensional (3D) acoustic source identification with solid spherical microphone arrays. Being capable of offering significantly attenuated sidelobes with a fast speed, the algorithm promises to play an important role in interior acoustic source identification. However, it presents some intrinsic imperfections, specifically poor spatial resolution and low quantification accuracy. This paper focuses on conquering these imperfections by ridge detection (RD) and deconvolution approach for the mapping of acoustic sources (DAMAS). The suggested methods are referred to as FDAS+RD and FDAS+RD+DAMAS. Both computer simulations and experiments are utilized to validate their effects. Several interesting conclusions have emerged: (1) FDAS+RD and FDAS+RD+DAMAS both can dramatically ameliorate FDAS's spatial resolution and at the same time inherit its advantages. (2) Compared to the conventional DAMAS, FDAS+RD+DAMAS enjoys the same super spatial resolution, stronger sidelobe attenuation capability and more than two hundred times faster speed. (3) FDAS+RD+DAMAS can effectively conquer FDAS's low quantification accuracy. Whether the focus distance is equal to the distance from the source to the array center or not, it can quantify the source average pressure contribution accurately. This study will be of great significance to the accurate and quick localization and quantification of acoustic sources in cabin environments.

Ecosystem services in Mediterranean river basin: climate change impact on water provisioning and erosion control.

PubMed

Bangash, Rubab F; Passuello, Ana; Sanchez-Canales, María; Terrado, Marta; López, Alfredo; Elorza, F Javier; Ziv, Guy; Acuña, Vicenç; Schuhmacher, Marta

2013-08-01

The Mediterranean basin is considered one of the most vulnerable regions of the world to climate change and such changes impact the capacity of ecosystems to provide goods and services to human society. The predicted future scenarios for this region present an increased frequency of floods and extended droughts, especially at the Iberian Peninsula. This paper evaluates the impacts of climate change on the water provisioning and erosion control services in the densely populated Mediterranean Llobregat river basin of. The assessment of ecosystem services and their mapping at the basin scale identify the current pressures on the river basin including the source area in the Pyrenees Mountains. Drinking water provisioning is expected to decrease between 3 and 49%, while total hydropower production will decrease between 5 and 43%. Erosion control will be reduced by up to 23%, indicating that costs for dredging the reservoirs as well as for treating drinking water will also increase. Based on these data, the concept for an appropriate quantification and related spatial visualization of ecosystem service is elaborated and discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Research Analysis of temporal and spatial characteristics of eco-environmental vulnerability in the Xianshui River basin based on GIS

NASA Astrophysics Data System (ADS)

Yao, Kun; Bai, Lin; Li, Xiao Ju; Wang, Xiao

2018-05-01

The Xianshui River basin is an important ecological barrier and water conservation area of Qinghai-Tibet plateau. To master the spatial and temporal differentiation of ecological environment is beneficial to the realization of the protection of regional ecological environment and the development of restoration measures. In this paper, the evaluation index system of ecological environment vulnerability was constructed from topography, climate, soil, land use and social economy. In this study, GIS and information entropy theory are combined to complete the analysis of spatial and temporal variation of vulnerability of ecological environment vulnerability in 2000-2015 years, and the main results are as follows: The ecological vulnerability of the watershed is characterized by the obvious vertical distribution, which is characterized by the gradual increase of the vulnerability of the south to the north. The evaluation results were classified as potential, micro, mild, moderate and severe, with the proportion of each grade being Micro > mild > potential > moderate > severity. The proportion of light and below accounts for more than 80% of the whole area, and the whole basin is at a medium vulnerable level. The change of overall trend indicates that the overall ecological environment of the basin has improved obviously in 15 years. The driving force factor analysis shows that the national environmental protection and restoration project is playing a significant role and plays a major driving role in the obvious improvement of the ecological environment in the basin area. However, there are still a few parts of the region that are deteriorating. This is mainly due to the special natural environment and over exploitation of hydropower resources.

Watershed Dynamics, with focus on connectivity index and management of water related impacts on road infrastructure

NASA Astrophysics Data System (ADS)

Kalantari, Z.

2015-12-01

In Sweden, spatially explicit approaches have been applied in various disciplines such as landslide modelling based on soil type data and flood risk modelling for large rivers. Regarding flood mapping, most previous studies have focused on complex hydrological modelling on a small scale whereas just a few studies have used a robust GIS-based approach integrating most physical catchment descriptor (PCD) aspects on a larger scale. This study was built on a conceptual framework for looking at SedInConnect model, topography, land use, soil data and other PCDs and climate change in an integrated way to pave the way for more integrated policy making. The aim of the present study was to develop methodology for predicting the spatial probability of flooding on a general large scale. This framework can provide a region with an effective tool to inform a broad range of watershed planning activities within a region. Regional planners, decision-makers, etc. can utilize this tool to identify the most vulnerable points in a watershed and along roads to plan for interventions and actions to alter impacts of high flows and other extreme weather events on roads construction. The application of the model over a large scale can give a realistic spatial characterization of sediment connectivity for the optimal management of debris flow to road structures. The ability of the model to capture flooding probability was determined for different watersheds in central Sweden. Using data from this initial investigation, a method to subtract spatial data for multiple catchments and to produce soft data for statistical analysis was developed. It allowed flood probability to be predicted from spatially sparse data without compromising the significant hydrological features on the landscape. This in turn allowed objective quantification of the probability of floods at the field scale for future model development and watershed management.

Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynami...

Social Vulnerability and Ebola Virus Disease in Rural Liberia.

PubMed

Stanturf, John A; Goodrick, Scott L; Warren, Melvin L; Charnley, Susan; Stegall, Christie M

2015-01-01

The Ebola virus disease (EVD) epidemic that has stricken thousands of people in the three West African countries of Liberia, Sierra Leone, and Guinea highlights the lack of adaptive capacity in post-conflict countries. The scarcity of health services in particular renders these populations vulnerable to multiple interacting stressors including food insecurity, climate change, and the cascading effects of disease epidemics such as EVD. However, the spatial distribution of vulnerable rural populations and the individual stressors contributing to their vulnerability are unknown. We developed a Social Vulnerability Classification using census indicators and mapped it at the district scale for Liberia. According to the Classification, we estimate that districts having the highest social vulnerability lie in the north and west of Liberia in Lofa, Bong, Grand Cape Mount, and Bomi Counties. Three of these counties together with the capital Monrovia and surrounding Montserrado and Margibi counties experienced the highest levels of EVD infections in Liberia. Vulnerability has multiple dimensions and a classification developed from multiple variables provides a more holistic view of vulnerability than single indicators such as food insecurity or scarcity of health care facilities. Few rural Liberians are food secure and many cannot reach a medical clinic in <80 minutes. Our results illustrate how census and household survey data, when displayed spatially at a sub-county level, may help highlight the location of the most vulnerable households and populations. Our results can be used to identify vulnerability hotspots where development strategies and allocation of resources to address the underlying causes of vulnerability in Liberia may be warranted. We demonstrate how social vulnerability index approaches can be applied in the context of disease outbreaks, and our methods are relevant elsewhere.

Spatially integrative metrics reveal hidden vulnerability of microtidal salt marshes

USGS Publications Warehouse

Ganju, Neil K.; Defne, Zafer; Kirwan, Matthew L.; Fagherazzi, Sergio; D'Alpaos, Andrea; Carniello, Luca

2017-01-01

Salt marshes are valued for their ecosystem services, and their vulnerability is typically assessed through biotic and abiotic measurements at individual points on the landscape. However, lateral erosion can lead to rapid marsh loss as marshes build vertically. Marsh sediment budgets represent a spatially integrated measure of competing constructive and destructive forces: a sediment surplus may result in vertical growth and/or lateral expansion, while a sediment deficit may result in drowning and/or lateral contraction. Here we show that sediment budgets of eight microtidal marsh complexes consistently scale with areal unvegetated/vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. All sites are exhibiting a sediment deficit, with half the sites having projected lifespans of less than 350 years at current rates of sea-level rise and sediment availability. These results demonstrate that open-water conversion and sediment deficits are holistic and sensitive indicators of salt marsh vulnerability.

A spatial analysis of population dynamics and climate change in Africa: potential vulnerability hot spots emerge where precipitation declines and demographic pressures coincide

USGS Publications Warehouse

López-Carr, David; Pricope, Narcisa G.; Aukema, Juliann E.; Jankowska, Marta M.; Funk, Christopher C.; Husak, Gregory J.; Michaelsen, Joel C.

2014-01-01

We present an integrative measure of exposure and sensitivity components of vulnerability to climatic and demographic change for the African continent in order to identify “hot spots” of high potential population vulnerability. Getis-Ord Gi* spatial clustering analyses reveal statistically significant locations of spatio-temporal precipitation decline coinciding with high population density and increase. Statistically significant areas are evident, particularly across central, southern, and eastern Africa. The highly populated Lake Victoria basin emerges as a particularly salient hot spot. People located in the regions highlighted in this analysis suffer exceptionally high exposure to negative climate change impacts (as populations increase on lands with decreasing rainfall). Results may help inform further hot spot mapping and related research on demographic vulnerabilities to climate change. Results may also inform more suitable geographical targeting of policy interventions across the continent.

Spatially integrative metrics reveal hidden vulnerability of microtidal salt marshes

PubMed Central

Ganju, Neil K.; Defne, Zafer; Kirwan, Matthew L.; Fagherazzi, Sergio; D'Alpaos, Andrea; Carniello, Luca

2017-01-01

Salt marshes are valued for their ecosystem services, and their vulnerability is typically assessed through biotic and abiotic measurements at individual points on the landscape. However, lateral erosion can lead to rapid marsh loss as marshes build vertically. Marsh sediment budgets represent a spatially integrated measure of competing constructive and destructive forces: a sediment surplus may result in vertical growth and/or lateral expansion, while a sediment deficit may result in drowning and/or lateral contraction. Here we show that sediment budgets of eight microtidal marsh complexes consistently scale with areal unvegetated/vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. All sites are exhibiting a sediment deficit, with half the sites having projected lifespans of less than 350 years at current rates of sea-level rise and sediment availability. These results demonstrate that open-water conversion and sediment deficits are holistic and sensitive indicators of salt marsh vulnerability. PMID:28112167

Spatially integrative metrics reveal hidden vulnerability of microtidal salt marshes.

PubMed

Ganju, Neil K; Defne, Zafer; Kirwan, Matthew L; Fagherazzi, Sergio; D'Alpaos, Andrea; Carniello, Luca

2017-01-23

Salt marshes are valued for their ecosystem services, and their vulnerability is typically assessed through biotic and abiotic measurements at individual points on the landscape. However, lateral erosion can lead to rapid marsh loss as marshes build vertically. Marsh sediment budgets represent a spatially integrated measure of competing constructive and destructive forces: a sediment surplus may result in vertical growth and/or lateral expansion, while a sediment deficit may result in drowning and/or lateral contraction. Here we show that sediment budgets of eight microtidal marsh complexes consistently scale with areal unvegetated/vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. All sites are exhibiting a sediment deficit, with half the sites having projected lifespans of less than 350 years at current rates of sea-level rise and sediment availability. These results demonstrate that open-water conversion and sediment deficits are holistic and sensitive indicators of salt marsh vulnerability.

Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

NASA Astrophysics Data System (ADS)

Lee, G.; Jun, K. S.; Chung, E.-S.

2015-04-01

This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

Exploring climate change vulnerability across sectors and scenarios using indicators of impacts and coping capacity.

PubMed

Dunford, R; Harrison, P A; Jäger, J; Rounsevell, M D A; Tinch, R

Addressing climate change vulnerability requires an understanding of both the level of climate impacts and the capacity of the exposed population to cope. This study developed a methodology for allowing users to explore vulnerability to changes in ecosystem services as a result of climatic and socio-economic changes. It focuses on the vulnerability of Europe across multiple sectors by combining the outputs of a regional integrated assessment (IA) model, the CLIMSAVE IA Platform, with maps of coping capacity based on the five capitals approach. The presented methodology enables stakeholder-derived socio-economic futures to be represented within a quantitative integrated modelling framework in a way that changes spatially and temporally with the socio-economic storyline. Vulnerability was mapped for six key ecosystem services in 40 combined climate and socio-economic scenarios. The analysis shows that, whilst the north and west of Europe are generally better placed to cope with climate impacts than the south and east, coping could be improved in all areas. Furthermore, whilst the lack of coping capacity in dystopian scenarios often leads to greater vulnerability, there are complex interactions between sectors that lead to patterns of vulnerability that vary spatially, with scenario and by sector even within the more utopian futures.

A place-based model for assessing the coherence of the flash floods and socio-economic vulnerability across the Contiguous United States (CONUS)

NASA Astrophysics Data System (ADS)

Khajehei, S.; Moradkhani, H.

2017-12-01

Understanding socio-economic characteristics involving natural hazards potential, vulnerability, and resilience is necessary to address the damages to economy and loss of life from extreme natural hazards. The vulnerability to flash floods is dependent on both biophysical and socio-economic factors. Although the biophysical characteristics (e.g. climate, vegetation, and land use) are informative and useful for predicting spatial and temporal extent of flash floods, they have minimal bearing on predicting when and where flash floods are likely to influence people or damage valuable assets and resources. The socio-economic factors determine spatial and temporal scales of the regions affected by flash floods. In this study, we quantify the socio-economic vulnerability to flash floods across the Contiguous United States (CONUS). A socio-economic vulnerability index was developed, employing Bayesian principal components for each state in the CONUS. For this purpose, extensive sets of social and economic variables from US Census and the Bureau of Economic Analysis were used. We developed maps presenting the coincidence of socio-economic vulnerability and the flash floods records. This product can help inform flash flood prevention, mitigation and recovery planning, as well as reducing the flash flood hazards affecting vulnerable places and population.

Latin hypercube approach to estimate uncertainty in ground water vulnerability

USGS Publications Warehouse

Gurdak, J.J.; McCray, J.E.; Thyne, G.; Qi, S.L.

2007-01-01

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Integrated assessment on the vulnerability of animal husbandry to snow disasters under climate change in the Qinghai-Tibetan Plateau

NASA Astrophysics Data System (ADS)

Wei, Yanqiang; Wang, Shijin; Fang, Yiping; Nawaz, Zain

2017-10-01

Animal husbandry is a dominant and traditional source of livelihood and income in the Qinghai-Tibetan Plateau. The Qinghai-Tibetan Plateau is the third largest snow covered area in China and is one of the main snow disaster regions in the world. It is thus imperative to urgently address the issue of vulnerability of the animal husbandry sector to snow disasters for disaster mitigation and adaptation under growing risk of these disasters as a result of future climate change. However, there is very few literature reported on the vulnerability of animal husbandry in the Qinghai-Tibetan Plateau. This assessment aims at identifying vulnerability of animal husbandry at spatial scale and to identify the reasons for vulnerability for adaptive planning and disaster mitigation. First, historical snow disaster characteristics have been analyzed and used for the spatial weight for vulnerability assessment. Second, indicator-based vulnerability assessment model and indicator system have been established. We combined risk of snow hazard, sensitivity of livestock to disaster, physical exposure to disaster, and community capacity to adapt to snow disaster in an integrated vulnerability index. Lastly, vulnerability of animal husbandry to snow disaster on the Qinghai-Tibetan Plateau has been evaluated. Results indicate that high vulnerabilities are mainly concentrated in the eastern and central plateau and that vulnerability decreases gradually from the east to the west. Due to global warming, the vulnerability trend has eased to some extent during the last few decades. High livestock density exposure to blizzard-prone regions and shortages of livestock barn and forage are the main reasons of high vulnerability. The conclusion emphasizes the important role of the local government and community to help local pastoralists for reducing vulnerability to snow disaster and frozen hazard. The approaches presented in this paper can be used for snow disaster mitigation, resilience enhancement and effectively reducing vulnerability to natural hazards in other regions.

Nonrigid motion compensation in B-mode and contrast enhanced ultrasound image sequences of the carotid artery

NASA Astrophysics Data System (ADS)

Carvalho, Diego D. B.; Akkus, Zeynettin; Bosch, Johan G.; van den Oord, Stijn C. H.; Niessen, Wiro J.; Klein, Stefan

2014-03-01

In this work, we investigate nonrigid motion compensation in simultaneously acquired (side-by-side) B-mode ultrasound (BMUS) and contrast enhanced ultrasound (CEUS) image sequences of the carotid artery. These images are acquired to study the presence of intraplaque neovascularization (IPN), which is a marker of plaque vulnerability. IPN quantification is visualized by performing the maximum intensity projection (MIP) on the CEUS image sequence over time. As carotid images contain considerable motion, accurate global nonrigid motion compensation (GNMC) is required prior to the MIP. Moreover, we demonstrate that an improved lumen and plaque differentiation can be obtained by averaging the motion compensated BMUS images over time. We propose to use a previously published 2D+t nonrigid registration method, which is based on minimization of pixel intensity variance over time, using a spatially and temporally smooth B-spline deformation model. The validation compares displacements of plaque points with manual trackings by 3 experts in 11 carotids. The average (+/- standard deviation) root mean square error (RMSE) was 99+/-74μm for longitudinal and 47+/-18μm for radial displacements. These results were comparable with the interobserver variability, and with results of a local rigid registration technique based on speckle tracking, which estimates motion in a single point, whereas our approach applies motion compensation to the entire image. In conclusion, we evaluated that the GNMC technique produces reliable results. Since this technique tracks global deformations, it can aid in the quantification of IPN and the delineation of lumen and plaque contours.

Accounting for Landscape Heterogeneity Improves Spatial Predictions of Tree Vulnerability to Drought

NASA Astrophysics Data System (ADS)

Schwantes, A. M.; Parolari, A.; Swenson, J. J.; Johnson, D. M.; Domec, J. C.; Jackson, R. B.; Pelak, N. F., III; Porporato, A. M.

2017-12-01

Globally, as climate change continues, forest vulnerability to droughts and heatwaves is increasing, but vulnerability differs regionally and locally depending on landscape position. However, most models used in forecasting forest responses to heatwaves and droughts do not incorporate relevant spatial processes. To improve predictions of spatial tree vulnerability, we employed a non-linear stochastic model of soil moisture dynamics across a landscape, accounting for spatial differences in aspect, topography, and soils. Our unique approach integrated plant hydraulics and landscape processes, incorporating effects from lateral redistribution of water using a topographic index and radiation and temperature differences attributable to aspect. Across a watershed in central Texas we modeled dynamic water stress for a dominant tree species, Juniperus ashei. We compared our results to a detailed spatial dataset of drought-impacted areas (>25% canopy loss) derived from remote sensing during the severe 2011 drought. We then projected future dynamic water stress through the 21st century using climate projections from 10 global climate models under two scenarios, and compared models with and without landscape heterogeneity. Within this watershed, 42% of J. ashei dominated systems were impacted by the 2011 drought. Modeled dynamic water stress tracked these spatial patterns of observed drought-impacted areas. Total accuracy increased from 59%, when accounting only for soil variability, to 73% when including lateral redistribution of water and radiation and temperature effects. Dynamic water stress was projected to increase through the 21st century, with only minimal buffering from the landscape. During the hotter and more severe droughts projected in the 21st century, up to 90% of the watershed crossed a dynamic water stress threshold associated with canopy loss in 2011. Favorable microsites may exist across a landscape where trees can persist; however, if future droughts are too severe, the buffering capacity of a heterogenous landscape could be overwhelmed. Incorporating spatial data will improve projections of future tree water stress and identification of potential resilient refugia.

Threats from urban expansion, agricultural transformation and forest loss on global conservation priority areas.

PubMed

Veach, Victoria; Moilanen, Atte; Di Minin, Enrico

2017-01-01

Including threats in spatial conservation prioritization helps identify areas for conservation actions where biodiversity is at imminent risk of extinction. At the global level, an important limitation when identifying spatial priorities for conservation actions is the lack of information on the spatial distribution of threats. Here, we identify spatial conservation priorities under three prominent threats to biodiversity (residential and commercial development, agricultural expansion, and forest loss), which are primary drivers of habitat loss and threaten the persistence of the highest number of species in the International Union for the Conservation of Nature (IUCN) Red List, and for which spatial data is available. We first explore how global priority areas for the conservation of vertebrate (mammals, birds, and amphibians) species coded in the Red List as vulnerable to each threat differ spatially. We then identify spatial conservation priorities for all species vulnerable to all threats. Finally, we identify the potentially most threatened areas by overlapping the identified priority areas for conservation with maps for each threat. We repeat the same with four other well-known global conservation priority area schemes, namely Key Biodiversity Areas, Biodiversity Hotspots, the global Protected Area Network, and Wilderness Areas. We find that residential and commercial development directly threatens only about 4% of the global top 17% priority areas for species vulnerable under this threat. However, 50% of the high priority areas for species vulnerable to forest loss overlap with areas that have already experienced some forest loss. Agricultural expansion overlapped with ~20% of high priority areas. Biodiversity Hotspots had the greatest proportion of their total area under direct threat from all threats, while expansion of low intensity agriculture was found to pose an imminent threat to Wilderness Areas under future agricultural expansion. Our results identify areas where limited resources should be allocated to mitigate risks to vertebrate species from habitat loss.

Threats from urban expansion, agricultural transformation and forest loss on global conservation priority areas

PubMed Central

Moilanen, Atte; Di Minin, Enrico

2017-01-01

Including threats in spatial conservation prioritization helps identify areas for conservation actions where biodiversity is at imminent risk of extinction. At the global level, an important limitation when identifying spatial priorities for conservation actions is the lack of information on the spatial distribution of threats. Here, we identify spatial conservation priorities under three prominent threats to biodiversity (residential and commercial development, agricultural expansion, and forest loss), which are primary drivers of habitat loss and threaten the persistence of the highest number of species in the International Union for the Conservation of Nature (IUCN) Red List, and for which spatial data is available. We first explore how global priority areas for the conservation of vertebrate (mammals, birds, and amphibians) species coded in the Red List as vulnerable to each threat differ spatially. We then identify spatial conservation priorities for all species vulnerable to all threats. Finally, we identify the potentially most threatened areas by overlapping the identified priority areas for conservation with maps for each threat. We repeat the same with four other well-known global conservation priority area schemes, namely Key Biodiversity Areas, Biodiversity Hotspots, the global Protected Area Network, and Wilderness Areas. We find that residential and commercial development directly threatens only about 4% of the global top 17% priority areas for species vulnerable under this threat. However, 50% of the high priority areas for species vulnerable to forest loss overlap with areas that have already experienced some forest loss. Agricultural expansion overlapped with ~20% of high priority areas. Biodiversity Hotspots had the greatest proportion of their total area under direct threat from all threats, while expansion of low intensity agriculture was found to pose an imminent threat to Wilderness Areas under future agricultural expansion. Our results identify areas where limited resources should be allocated to mitigate risks to vertebrate species from habitat loss. PMID:29182662

Assessment of prey vulnerability through analysis of wolf movements and kill sites.

PubMed

Bergman, Eric J; Garrott, Robert A; Creel, Scott; Borkowski, John J; Jaffe, Rosemary; Watson, E G R

2006-02-01

Within predator-prey systems behavior can heavily influence spatial dynamics, and accordingly, the theoretical study of how spatial dynamics relate to stability within these systems has a rich history. However, our understanding of these behaviors in large mammalian systems is poorly developed. To address the relationship between predator selection patterns, prey density, and prey vulnerability, we quantified selection patterns for two fine-scale behaviors of a recovering wolf (Canis lupus) population in Yellowstone National Park, Wyoming, USA. Wolf spatial data were collected between November and May from 1998-1999 until 2001-2002. Over four winters, 244 aerial locations, 522 ground-based telemetry locations, 1287 km of movement data from snow tracking, and the locations of 279 wolf kill sites were recorded. There was evidence that elk (Cervus elaphus) and bison (Bison bison) densities had a weak effect on the sites where wolves traveled and made kills. Wolf movements showed a strong selection for geothermal areas, meadows, and areas near various types of habitat edges. Proximity to edge and habitat class also had a strong influence on the locations where elk were most vulnerable to predation. There was little evidence that wolf kill sites differed from the places where wolves traveled, indicating that elk vulnerability influenced where wolves selected to travel. Our results indicate that elk are more vulnerable to wolves under certain conditions and that wolves are capable of selecting for these conditions. As such, vulnerability plays a central role in predator-prey behavioral games and can potentially impact the systems to which they relate.

Mapping social-ecological vulnerability to inform local decision making.

PubMed

Thiault, Lauric; Marshall, Paul; Gelcich, Stefan; Collin, Antoine; Chlous, Frédérique; Claudet, Joachim

2018-04-01

An overarching challenge of natural resource management and biodiversity conservation is that relationships between people and nature are difficult to integrate into tools that can effectively guide decision making. Social-ecological vulnerability offers a valuable framework for identifying and understanding important social-ecological linkages, and the implications of dependencies and other feedback loops in the system. Unfortunately, its implementation at local scales has hitherto been limited due at least in part to the lack of operational tools for spatial representation of social-ecological vulnerability. We developed a method to map social-ecological vulnerability based on information on human-nature dependencies and ecosystem services at local scales. We applied our method to the small-scale fishery of Moorea, French Polynesia, by combining spatially explicit indicators of exposure, sensitivity, and adaptive capacity of both the resource (i.e., vulnerability of reef fish assemblages to fishing) and resource users (i.e., vulnerability of fishing households to the loss of fishing opportunity). Our results revealed that both social and ecological vulnerabilities varied considerably through space and highlighted areas where sources of vulnerability were high for both social and ecological subsystems (i.e., social-ecological vulnerability hotspots) and thus of high priority for management intervention. Our approach can be used to inform decisions about where biodiversity conservation strategies are likely to be more effective and how social impacts from policy decisions can be minimized. It provides a new perspective on human-nature linkages that can help guide sustainability management at local scales; delivers insights distinct from those provided by emphasis on a single vulnerability component (e.g., exposure); and demonstrates the feasibility and value of operationalizing the social-ecological vulnerability framework for policy, planning, and participatory management decisions. © 2017 Society for Conservation Biology.

Spatially Representing Vulnerability to Extreme Rain Events Using Midwestern Farmers' Objective and Perceived Attributes of Adaptive Capacity.

PubMed

Gardezi, Maaz; Arbuckle, J Gordon

2017-11-29

Potential climate-change-related impacts to agriculture in the upper Midwest pose serious economic and ecological risks to the U.S. and the global economy. On a local level, farmers are at the forefront of responding to the impacts of climate change. Hence, it is important to understand how farmers and their farm operations may be more or less vulnerable to changes in the climate. A vulnerability index is a tool commonly used by researchers and practitioners to represent the geographical distribution of vulnerability in response to global change. Most vulnerability assessments measure objective adaptive capacity using secondary data collected by governmental agencies. However, other scholarship on human behavior has noted that sociocultural and cognitive factors, such as risk perceptions and perceived capacity, are consequential for modulating people's actual vulnerability. Thus, traditional assessments can potentially overlook people's subjective perceptions of changes in climate and extreme weather events and the extent to which people feel prepared to take necessary steps to cope with and respond to the negative effects of climate change. This article addresses this knowledge gap by: (1) incorporating perceived adaptive capacity into a vulnerability assessment; (2) using spatial smoothing to aggregate individual-level vulnerabilities to the county level; and (3) evaluating the relationships among different dimensions of adaptive capacity to examine whether perceived capacity should be integrated into vulnerability assessments. The result suggests that vulnerability assessments that rely only on objective measures might miss important sociocognitive dimensions of capacity. Vulnerability indices and maps presented in this article can inform engagement strategies for improving environmental sustainability in the region. © 2017 Society for Risk Analysis.

Focusing Conservation Efforts on Ecosystem Service Supply May Increase Vulnerability of Socio-Ecological Systems

PubMed Central

Barral, Paula; Carmona, Alejandra; Nahuelhual, Laura

2016-01-01

Growing concern about the loss of ecosystem services (ES) promotes their spatial representation as a key tool for the internalization of the ES framework into land use policies. Paradoxically, mapping approaches meant to inform policy decisions focus on the magnitude and spatial distribution of the biophysical supply of ES, largely ignoring the social mechanisms by which these services influence human wellbeing. If social mechanisms affecting ES demand, enhancing it or reducing it, are taken more into account, then policies are more effective. By developing and applying a new mapping routine to two distinct socio-ecological systems, we show a strong spatial uncoupling between ES supply and socio-ecological vulnerability to the loss of ES, under scenarios of land use and cover change. Public policies based on ES supply might not only fail at detecting priority conservation areas for the wellbeing of human societies, but may also increase their vulnerability by neglecting areas of currently low, but highly valued ES supply. PMID:27167737

Focusing Conservation Efforts on Ecosystem Service Supply May Increase Vulnerability of Socio-Ecological Systems.

PubMed

Laterra, Pedro; Barral, Paula; Carmona, Alejandra; Nahuelhual, Laura

2016-01-01

Growing concern about the loss of ecosystem services (ES) promotes their spatial representation as a key tool for the internalization of the ES framework into land use policies. Paradoxically, mapping approaches meant to inform policy decisions focus on the magnitude and spatial distribution of the biophysical supply of ES, largely ignoring the social mechanisms by which these services influence human wellbeing. If social mechanisms affecting ES demand, enhancing it or reducing it, are taken more into account, then policies are more effective. By developing and applying a new mapping routine to two distinct socio-ecological systems, we show a strong spatial uncoupling between ES supply and socio-ecological vulnerability to the loss of ES, under scenarios of land use and cover change. Public policies based on ES supply might not only fail at detecting priority conservation areas for the wellbeing of human societies, but may also increase their vulnerability by neglecting areas of currently low, but highly valued ES supply.

Quantification of optical absorption coefficient from acoustic spectra in the optical diffusive regime using photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Guo, Zijian; Favazza, Christopher; Wang, Lihong V.

2012-02-01

Photoacoustic (PA) tomography (PAT) can image optical absorption contrast with ultrasonic spatial resolution in the optical diffusive regime. Multi-wavelength PAT can noninvasively monitor hemoglobin oxygen saturation (sO2) with high sensitivity and fine spatial resolution. However, accurate quantification in PAT requires knowledge of the optical fluence distribution, acoustic wave attenuation, and detection system bandwidth. We propose a method to circumvent this requirement using acoustic spectra of PA signals acquired at two optical wavelengths. With the acoustic spectral method, the absorption coefficients of an oxygenated bovine blood phantom at 560 and 575 nm were quantified with errors of ><5%.

Outdoor characterization of radio frequency electromagnetic fields in a Spanish birth cohort.

PubMed

Calvente, I; Fernández, M F; Pérez-Lobato, R; Dávila-Arias, C; Ocón, O; Ramos, R; Ríos-Arrabal, S; Villalba-Moreno, J; Olea, N; Núñez, M I

2015-04-01

There is considerable public concern in many countries about the possible adverse effects of exposure to non-ionizing radiation electromagnetic fields, especially in vulnerable populations such as children. The aim of this study was to characterize environmental exposure profiles within the frequency range 100kHz-6GHz in the immediate surrounds of the dwellings of 123 families from the INMA-Granada birth cohort in Southern Spain, using spot measurements. The arithmetic mean root mean-square electric field (ERMS) and power density (SRMS) values were, respectively, 195.79mV/m (42.3% of data were above this mean) and 799.01µW/m(2) (30% of values were above this mean); median values were 148.80mV/m and 285.94µW/m(2), respectively. Exposure levels below the quantification limit were assigned a value of 0.01V/m. Incident field strength levels varied widely among different areas or towns/villages, demonstrating spatial variability in the distribution of exposure values related to the surface area population size and also among seasons. Although recorded values were well below International Commission for Non-Ionizing Radiation Protection reference levels, there is a particular need to characterize incident field strength levels in vulnerable populations (e.g., children) because of their chronic and ever-increasing exposure. The effects of incident field strength have not been fully elucidated; however, it may be appropriate to apply the precautionary principle in order to reduce exposure in susceptible groups. Copyright © 2014 Elsevier Inc. All rights reserved.

Monitoring Coastal Embankment Subsidence and Relative Sea Level Rise in Coastal Bangladesh Using Satellite Geodetic Data

NASA Astrophysics Data System (ADS)

Guo, Q.; Shum, C. K.; Jia, Y.; Yi, Y.; Zhu, K.; Kuo, C. Y.; Liibusk, A.

2015-12-01

The Bangladesh Delta is located at the confluence of the mega Ganges, Brahmaputra and Meghan Rivers in the Bay of Bengal. It is home to over 160 million people and is one of the most densely populated countries in the world. It is prone to seasonal transboundary monsoonal flooding, potentially aggravated by more frequent and intensified cyclones resulting from anthropogenic climate change. Sea level rise, along with tectonic, sediment compaction/load and groundwater extraction induced land uplift/subsidence, have significantly exacerbated these risks and Bangladesh's coastal vulnerability. Bangladesh has built 123 coastal embankments or polders since the 1960's, to protect the coastal regions from cyclone/tidal flooding and to reduce salinity incursions. Since then, many coastal polders have suffered severe erosion and anthropogenic damage, and require repairs or rebuilding. However, the physical and anthropogenic processes governing the historic relative sea level rise and its future projection towards its quantification remain poorly understood or known, and at present not accurate enough or with an adequately fine local spatial scale for practical mitigation of coastal vulnerability or coastal resilience studies. This study reports on our work in progress to use satellite geodetic and remote sensing observations, including satellite radar altimetry/backscatter measurements over land and in coastal oceans, optical/infrared imageries, and SAR backscatter/InSAR data, to study the feasibility of coastal embankment/polder erosion monitoring, quantify seasonal polder water intrusions, observing polder subsidence, and finally, towards the goal of improving the relative sea level rise hazards assessment at the local scale in coastal Bangladesh.

Comparing carbon storage of Siberian tundra and taiga permafrost ecosystems at very high spatial resolution

NASA Astrophysics Data System (ADS)

Siewert, Matthias B.; Hanisch, Jessica; Weiss, Niels; Kuhry, Peter; Maximov, Trofim C.; Hugelius, Gustaf

2015-10-01

Permafrost-affected ecosystems are important components in the global carbon (C) cycle that, despite being vulnerable to disturbances under climate change, remain poorly understood. This study investigates ecosystem carbon storage in two contrasting continuous permafrost areas of NE and East Siberia. Detailed partitioning of soil organic carbon (SOC) and phytomass carbon (PC) is analyzed for one tundra (Kytalyk) and one taiga (Spasskaya Pad/Neleger) study area. In total, 57 individual field sites (24 and 33 in the respective areas) have been sampled for PC and SOC, including the upper permafrost. Landscape partitioning of ecosystem C storage was derived from thematic upscaling of field observations using a land cover classification from very high resolution (2 × 2 m) satellite imagery. Nonmetric multidimensional scaling was used to explore patterns in C distribution. In both environments the ecosystem C is mostly stored in the soil (≥86%). At the landscape scale C stocks are primarily controlled by the presence of thermokarst depressions (alases). In the tundra landscape, site-scale variability of C is controlled by periglacial geomorphological features, while in the taiga, local differences in catenary position, soil texture, and forest successions are more important. Very high resolution remote sensing is highly beneficial to the quantification of C storage. Detailed knowledge of ecosystem C storage and ground ice distribution is needed to predict permafrost landscape vulnerability to projected climatic changes. We argue that vegetation dynamics are unlikely to offset mineralization of thawed permafrost C and that landscape-scale reworking of SOC represents the largest potential changes to C cycling.

Geomorphological hazard and tourist vulnerability along Portofino Park trails (Italy)

NASA Astrophysics Data System (ADS)

Brandolini, P.; Faccini, F.; Piccazzo, M.

2006-06-01

The many trails existing in the coastal area of Portofino Promontory are used by tourists for trekking or as pathways to small villages and beaches. The aim of this paper is to define geomorphological hazard and tourist vulnerability in this area, within the framework of the management and planning of hiking activities in Portofino Natural Park. In particular, processes triggered by gravity, running waters and wave motion, affecting the slopes and the cliff, are considered. The typology of the trails and trail maintenance are also taken into account in relation to weather conditions that can make the excursion routes dangerous for tourists. In conclusion, an operative model is applied for the definition of possible risk scenarios. This model is founded on an inventory and the quantification of geomorphological hazards and tourist vulnerability, in comparison with trail rescue data. The model can be applied to other environments and tourist areas.

How urban system vulnerabilities to flooding could be assessed to improve resilience and adaptation in spatial planning

NASA Astrophysics Data System (ADS)

Pasi, Riccardo; Viavattene, Christophe; La Loggia, Goffredo

2016-04-01

Natural hazards damage assets and infrastructure inducing disruptions to urban functions and key daily services. These disruptions may be short or long with a variable spatial scale of impact. From an urban planning perspective, measuring these disruptions and their consequences at an urban scale is fundamental in order to develop more resilient cities. Whereas the assessment of physical vulnerabilities and direct damages is commonly addressed, new methodologies for assessing the systemic vulnerability at the urban scale are required to reveal these disruptions and their consequences. Physical and systemic vulnerability should be measured in order to reflect the multifaceted fragility of cities in the face of external stress, both in terms of the natural/built environment and socio-economic sphere. Additionally, a systemic approach allows the consideration of vulnerability across different spatial scales, as impacts may vary and be transmitted across local, regional or national levels. Urban systems are spatially distributed and the nature of this can have significant effects on flood impacts. The proposed approach identifies the vulnerabilities of flooding within urban contexts, including both in terms of single elementary units (buildings, infrastructures, people, etc.) and systemic functioning (urban functions and daily life networks). Direct losses are appraised initially using conventional methodologies (e.g. depth-damage functions). This aims to both understand the spatial distribution of physical vulnerability and associated losses and, secondly, to identify the most vulnerable building types and ways to improve the physical adaptation of our cities, proposing changes to building codes, design principles and other municipal regulation tools. The subsequent systemic approach recognises the city as a collection of sub-systems or functional units (such as neighbourhoods and suburbs) providing key daily services for inhabitants (e.g. healthcare facilities, schools, administration offices, food shops, leisure and cultural services etc.) and which are interconnected through transport networks. Moreover, each city is part of broader systems - which may or may not follow administrative boundaries - and, as such, need to be connected to its wider surroundings, in a multi-scalar perspective. The systemic analysis, herein limited to residential households, evaluates the presence, the distribution among functional units and the redundancy of key daily services. As such, systemic interdependences between neighbourhoods/suburbs and municipalities emerge, highlighting how systemic vulnerability spreads beyond the flooded areas. This aims to understand which planning patterns and existing mixed-use developments are more flood resilient (thereby informing future urban development/regeneration) and which infrastructure and assets have a key role within the urban system (and have therefore to be prioritised for protection). The methodology is currently developed through an extensive use of Geographic Information Systems (GIS) and applied to an Italian case study (Noale municipality, Venice). Current developments and on-going issues in its application and in the data collection (including the use of aerial survey data) will be discussed in the presentation.

Detection and quantification of adulterants in milk powder using high-throughput Raman chemical imaging technique

USDA-ARS?s Scientific Manuscript database

Milk is a vulnerable target for economically motivated adulteration. In this study, a line-scan high-throughput Raman imaging system was used to authenticate milk powder. A 5 W 785 nm line laser (240 mm long and 1 mm wide) was used as a Raman excitation source. The system was used to acquire hypersp...

Tsunami vulnerability assessment mapping for the west coast of Peninsular Malaysia using a geographical information system (GIS)

NASA Astrophysics Data System (ADS)

Najihah, R.; Effendi, D. M.; Hairunnisa, M. A.; Masiri, K.

2014-02-01

The catastrophic Indian Ocean tsunami of 26 December 2004 raised a number of questions for scientist and politicians on how to deal with the tsunami risk and assessment in coastal regions. This paper discusses the challenges in tsunami vulnerability assessment and presents the result of tsunami disaster mapping and vulnerability assessment study for West Coast of Peninsular Malaysia. The spatial analysis was carried out using Geographical Information System (GIS) technology to demarcate spatially the tsunami affected village's boundary and suitable disaster management program can be quickly and easily developed. In combination with other thematic maps such as road maps, rail maps, school maps, and topographic map sheets it was possible to plan the accessibility and shelter to the affected people. The tsunami vulnerability map was used to identify the vulnerability of villages/village population to tsunami. In the tsunami vulnerability map, the intensity of the tsunami was classified as hazard zones based on the inundation level in meter (contour). The approach produced a tsunami vulnerability assessment map consists of considering scenarios of plausible extreme, tsunami-generating events, computing the tsunami inundation levels caused by different events and scenarios and estimating the possible range of casualties for computing inundation levels. The study provides an interactive means to identify the tsunami affected areas after the disaster and mapping the tsunami vulnerable village before for planning purpose were the essential exercises for managing future disasters.

Vulnerability assessment of chemical industry facilities in South Korea based on the chemical accident history

NASA Astrophysics Data System (ADS)

Heo, S.; Lee, W. K.; Jong-Ryeul, S.; Kim, M. I.

2016-12-01

The use of chemical compounds are keep increasing because of their use in manufacturing industry. Chemical accident is growing as the consequence of the chemical use increment. Devastating damages from chemical accidents are far enough to aware people's cautious about the risk of the chemical accident. In South Korea, Gumi Hydrofluoric acid leaking accident triggered the importance of risk management and emphasized the preventing the accident over the damage reducing process after the accident occurs. Gumi accident encouraged the government data base construction relate to the chemical accident. As the result of this effort Chemical Safety-Clearing-house (CSC) have started to record the chemical accident information and damages according to the Harmful Chemical Substance Control Act (HCSC). CSC provide details information about the chemical accidents from 2002 to present. The detail informations are including title of company, address, business type, accident dates, accident types, accident chemical compounds, human damages inside of the chemical industry facilities, human damage outside of the chemical industry facilities, financial damages inside of the chemical industry facilities, and financial damages outside of the chemical industry facilities, environmental damages and response to the chemical accident. Collected the chemical accident history of South Korea from 2002 to 2015 and provide the spatial information to the each accident records based on their address. With the spatial information, compute the data on ArcGIS for the spatial-temporal analysis. The spatial-temporal information of chemical accident is organized by the chemical accident types, damages, and damages on environment and conduct the spatial proximity with local community and environmental receptors. Find the chemical accident vulnerable area of South Korea from 2002 to 2015 and add the vulnerable area of total period to examine the historically vulnerable area from the chemical accident in South Korea.

Vulnerabilities of ecosystems across U.S. National Parks to biome shifts, wildfire changes, and invasive species due to climate change

NASA Astrophysics Data System (ADS)

Gonzalez, P.; Eigenbrod, F.; Early, R.; Wang, F.; Notaro, M.; Williams, J. W.

2016-12-01

U.S. national parks conserve globally unique biodiversity. Yet, historical impacts of climate change and future vulnerabilities threaten species and ecosystems across this system of protected areas. Spatial analyses of historical climate and downscaled future climate projections show climate trends across the system. Spatial analyses of vegetation and wildfire (using a dynamic global vegetation model), habitat fragmentation (using remote sensing-derived land cover), and invasive species introduction and establishment show patterns of future vulnerability across the 50 U.S. states and 412 U.S. national parks. Results reveal high historical and projected temperature increases and precipitation changes, projected increases of wildfire across western U.S. national parks, high vulnerability to biome shifts and habitat fragmentation of up to one-third of National Park System area, and high vulnerability to invasive species of one-ninth of National Park System area. Ecosystems in the Sierra Nevada, Cascade Range, desert Southwest, and Laurentian Great Lakes are highly vulnerable to upslope and poleward shifts of the North America sequence of biomes: temperate shrubland - temperate broadleaf forest - temperate mixed forest - temperate conifer forest - subalpine and boreal forest - alpine and tundra. These areas include Grand Canyon, Mount Rainier, and Yosemite National Parks. The southwestern U.S., including Grand Canyon and Sequoia National Parks, is vulnerable to increases in wildfire. The eastern and midwestern U.S., including Great Smokey Mountains and Voyageurs National Parks, are highly vulnerable to invasive species. These results identify vulnerable areas and potential refugia to help prioritize areas for future natural resource management actions and biodiversity conservation in U.S. national parks.

Exploration of health risks related to air pollution and temperature in three Latin American cities

NASA Astrophysics Data System (ADS)

Romero-Lankao, P.; Borbor Cordova, M.; Qin, H.

2013-12-01

We explore whether the health risks related to air pollution and temperature extremes are spatially and socioeconomically differentiated within three Latin American cities: Bogota, Colombia, Mexico City, Mexico, and Santiago, Chile. Based on a theoretical review of three relevant approaches to risk analysis (risk society, environmental justice, and urban vulnerability as impact), we hypothesize that health risks from exposure to air pollution and temperature in these cities do not necessarily depend on socio-economic inequalities. To test this hypothesis, we gathered, validated, and analyzed temperature, air pollution, mortality and socioeconomic vulnerability data from the three study cities. Our results show the association between air pollution levels and socioeconomic vulnerabilities did not always correlate within the study cities. Furthermore, the spatial differences in socioeconomic vulnerabilities within cities do not necessarily correspond with the spatial distribution of health impacts. The present study improves our understanding of the multifaceted nature of health risks and vulnerabilities associated with global environmental change. The findings suggest that health risks from atmospheric conditions and pollutants exist without boundaries or social distinctions, even exhibiting characteristics of a boomerang effect (i.e., affecting rich and poor alike) on a smaller scale such as areas within urban regions. We used human mortality, a severe impact, to measure health risks from air pollution and extreme temperatures. Public health data of better quality (e.g., morbidity, hospital visits) are needed for future research to advance our understanding of the nature of health risks related to climate hazards.

Spatial vulnerability of Australian urban populations to extreme heat events

NASA Astrophysics Data System (ADS)

Loughnan, Margaret; Tapper, Nigel; Phan, Thu; Lynch, Kellie; McInnes, Judith

2013-04-01

Extreme heat events pose a risk to the health of all individuals, especially the elderly and the chronically ill, and are associated with an increased demand for healthcare services. In order to address this problem, policy makers' need information about temperatures above which mortality and morbidity of the exposed population is likely to increase, where the vulnerable groups in the community are located, and how the risks from extreme heat events are likely to change in the future. This study identified threshold temperatures for all Australian capital cities, developed a spatial index of population vulnerability, and used climate model output to predict changes in the number of days exceeding temperature thresholds in the future, as well as changes in risk related to changes in urban density and an ageing population. The study has shown that daily maximum and minimum temperatures from the Bureau of Meteorology forecasts can be used to calculate temperature thresholds for heat alert days. The key risk factors related to adverse health outcomes were found to be areas with intense urban heat islands, areas with higher proportions of older people, and areas with ethnic communities. Maps of spatial vulnerability have been developed to provide information to assist emergency managers, healthcare professionals, and ancillary services develop heatwave preparedness plans at a local scale that target vulnerable groups and address heat-related health risks. The numbers of days exceeding current heat thresholds are predicted to increase over the next 20 to 40 years in all Australian capital cities.

Spatially resolved quantification of agrochemicals on plant surfaces using energy dispersive X-ray microanalysis.

PubMed

Hunsche, Mauricio; Noga, Georg

2009-12-01

In the present study the principle of energy dispersive X-ray microanalysis (EDX), i.e. the detection of elements based on their characteristic X-rays, was used to localise and quantify organic and inorganic pesticides on enzymatically isolated fruit cuticles. Pesticides could be discriminated from the plant surface because of their distinctive elemental composition. Findings confirm the close relation between net intensity (NI) and area covered by the active ingredient (AI area). Using wide and narrow concentration ranges of glyphosate and glufosinate, respectively, results showed that quantification of AI requires the selection of appropriate regression equations while considering NI, peak-to-background (P/B) ratio, and AI area. The use of selected internal standards (ISs) such as Ca(NO(3))(2) improved the accuracy of the quantification slightly but led to the formation of particular, non-typical microstructured deposits. The suitability of SEM-EDX as a general technique to quantify pesticides was evaluated additionally on 14 agrochemicals applied at diluted or regular concentration. Among the pesticides tested, spatial localisation and quantification of AI amount could be done for inorganic copper and sulfur as well for the organic agrochemicals glyphosate, glufosinate, bromoxynil and mancozeb. (c) 2009 Society of Chemical Industry.

Spatial Supermarket Redlining and Neighborhood Vulnerability: A Case Study of Hartford, Connecticut

PubMed Central

Zhang, Mengyao

2015-01-01

The disinclination of chain supermarkets to locate or pull out existing stores from impoverished neighborhoods is termed as “supermarket redlining”. This paper attempts to map and understand the spatial effects of potential supermarket redlining on food vulnerability in urban disadvantaged neighborhoods of Hartford, Connecticut. Using a combination of statistical and spatial analysis functions, we first, built a Supermarket Redlining Index (SuRI) from five indicators such as sales volume, employee count, accepts food coupons from federally assisted programs, and size and population density of the service area to rank supermarkets in the order of their importance. Second, to understand the effect of redlining, a Supermarket Redlining Impact Model (SuRIM) was built with eleven indicators describing both the socioeconomic and food access vulnerabilities. The interaction of these vulnerabilities would identify the final outcome: neighborhoods where the impact of supermarket redlining would be critical. Results mapped critical areas in the inner-city of Hartford where if a nearby supermarket closes or relocates to a suburb with limited mitigation efforts to gill the grocery gap, a large number of minority, poor, and disadvantaged residents will experience difficulties to access healthy food leading to food insecurity or perhaps a food desert. We also suggest mitigation efforts to reduce the impact of large supermarket closures. PMID:27034615

Spatial Supermarket Redlining and Neighborhood Vulnerability: A Case Study of Hartford, Connecticut.

PubMed

Zhang, Mengyao; Debarchana, Ghosh

2016-02-01

The disinclination of chain supermarkets to locate or pull out existing stores from impoverished neighborhoods is termed as "supermarket redlining". This paper attempts to map and understand the spatial effects of potential supermarket redlining on food vulnerability in urban disadvantaged neighborhoods of Hartford, Connecticut. Using a combination of statistical and spatial analysis functions, we first, built a Supermarket Redlining Index (SuRI) from five indicators such as sales volume, employee count, accepts food coupons from federally assisted programs, and size and population density of the service area to rank supermarkets in the order of their importance. Second, to understand the effect of redlining, a Supermarket Redlining Impact Model (SuRIM) was built with eleven indicators describing both the socioeconomic and food access vulnerabilities. The interaction of these vulnerabilities would identify the final outcome: neighborhoods where the impact of supermarket redlining would be critical. Results mapped critical areas in the inner-city of Hartford where if a nearby supermarket closes or relocates to a suburb with limited mitigation efforts to gill the grocery gap, a large number of minority, poor, and disadvantaged residents will experience difficulties to access healthy food leading to food insecurity or perhaps a food desert. We also suggest mitigation efforts to reduce the impact of large supermarket closures.

Rainfall-induced landslide vulnerability Assessment in urban area reflecting Urban structure and building characteristics

NASA Astrophysics Data System (ADS)

Park, C.; Cho, M.; Lee, D.

2017-12-01

Landslide vulnerability assessment methodology of urban area is proposed with urban structure and building charateristics which can consider total damage cost of climate impacts. We used probabilistic analysis method for modeling rainfall-induced shallow landslide susceptibility by slope stability analysis and Monte Carlo simulations. And We combined debris flows with considering spatial movements under topographical condition and built environmental condition. Urban vulnerability of landslide is assessed by two categories: physical demages and urban structure aspect. Physical vulnerability is related to buildings, road, other ubran infra. Urban structure vulnerability is considered a function of the socio-economic factors, trigger factor of secondary damage, and preparedness level of the local government. An index-based model is developed to evaluate the life and indirect damage under landslide as well as the resilience ability against disasters. The analysis was performed in a geographic information system (GIS) environment because GIS can deal efficiently with a large volume of spatial data. The results of the landslide susceptibility assessment were compared with the landslide inventory, and the proposed approach demonstrated good predictive performance. The general trend found in this study indicates that the higher population density areas under a weaker fiscal condition that are located at the downstream of mountainous areas are more vulnerable than the areas in opposite conditions.

Impact Induced Delamination Detection and Quantification With Guided Wavefield Analysis

NASA Technical Reports Server (NTRS)

Tian, Zhenhua; Leckey, Cara A. C.; Yu, Lingyu; Seebo, Jeffrey P.

2015-01-01

This paper studies impact induced delamination detection and quantification by using guided wavefield data and spatial wavenumber imaging. The complex geometry impact-like delamination is created through a quasi-static indentation on a CFRP plate. To detect and quantify the impact delamination in the CFRP plate, PZT-SLDV sensing and spatial wavenumber imaging are performed. In the PZT-SLDV sensing, the guided waves are generated from the PZT, and the high spatial resolution guided wavefields are measured by the SLDV. The guided wavefield data acquired from the PZT-SLDV sensing represent guided wave propagation in the composite laminate and include guided wave interaction with the delamination damage. The measured guided wavefields are analyzed through the spatial wavenumber imaging method, which generates an image containing the dominant local wavenumber at each spatial location. The spatial wavenumber imaging result for the simple single layer Teflon insert delamination provided quantitative information on delamination damage size and location. The location of delamination damage is indicated by the area with larger wavenumbers in the spatial wavenumber image. The impact-like delamination results only partially agreed with the damage size and shape. The results also demonstrated the dependence on excitation frequency. Future work will further investigate the accuracy of the wavenumber imaging method for real composite damage and the dependence on frequency of excitation.

INTEGRATION OF SPATIAL DATA: METHODS EVALUATION WITH REGARD TO DATA ISSUES AND ASSESSMENT QUESTIONS

EPA Science Inventory

EPA's Regional Vulnerability Assessment (REVA) Program is developing and demonstrating approaches to assess current and future environmental vulnerabilities at a regional scale. An initial effort within this research program has been to develop and evaluate methods to synthesize ...

Vulnerability inducing technologies: An initial appreciation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reinhardt, G.C.

The arms control community continues to act as though vulnerability were directly proportional to numbers of nuclear weapons, however rapidly they would voice their rejection of such a proposition if it were placed before them in an intellectual forum. Such neglect in matching action to knowledge is a well-known human phenomenon, but in this case it is particularly troublesome. START manages to reduce the numbers of weapons to just the right extent to encourage damage limiting. The present number of nuclear weapons on either side probably provides a robust deterrent; six thousand probably does not. To make matters worse, wemore » live in a period of burgeoning technical expansion, so that even with the best intent on both sides, new technology threatens to cause new vulnerabilities in strategic systems. To pin a shorthand label on the problem, we will refer to vulnerability inducing technology as ''VIT.'' In order to appreciate VIT, we will make a rough quantification of its consequences. This will at least provide some incentive for further study because the consequences are grave indeed. 2 tabs.« less

Modeling Coastal Vulnerability through Space and Time.

PubMed

Hopper, Thomas; Meixler, Marcia S

2016-01-01

Coastal ecosystems experience a wide range of stressors including wave forces, storm surge, sea-level rise, and anthropogenic modification and are thus vulnerable to erosion. Urban coastal ecosystems are especially important due to the large populations these limited ecosystems serve. However, few studies have addressed the issue of urban coastal vulnerability at the landscape scale with spatial data that are finely resolved. The purpose of this study was to model and map coastal vulnerability and the role of natural habitats in reducing vulnerability in Jamaica Bay, New York, in terms of nine coastal vulnerability metrics (relief, wave exposure, geomorphology, natural habitats, exposure, exposure with no habitat, habitat role, erodible shoreline, and surge) under past (1609), current (2015), and future (2080) scenarios using InVEST 3.2.0. We analyzed vulnerability results both spatially and across all time periods, by stakeholder (ownership) and by distance to damage from Hurricane Sandy. We found significant differences in vulnerability metrics between past, current and future scenarios for all nine metrics except relief and wave exposure. The marsh islands in the center of the bay are currently vulnerable. In the future, these islands will likely be inundated, placing additional areas of the shoreline increasingly at risk. Significant differences in vulnerability exist between stakeholders; the Breezy Point Cooperative and Gateway National Recreation Area had the largest erodible shoreline segments. Significant correlations exist for all vulnerability (exposure/surge) and storm damage combinations except for exposure and distance to artificial debris. Coastal protective features, ranging from storm surge barriers and levees to natural features (e.g. wetlands), have been promoted to decrease future flood risk to communities in coastal areas around the world. Our methods of combining coastal vulnerability results with additional data and across multiple time periods have considerable potential to provide valuable predictions that resource managers can effectively use to identify areas for restoration and protection.

Modeling Coastal Vulnerability through Space and Time

PubMed Central

2016-01-01

Coastal ecosystems experience a wide range of stressors including wave forces, storm surge, sea-level rise, and anthropogenic modification and are thus vulnerable to erosion. Urban coastal ecosystems are especially important due to the large populations these limited ecosystems serve. However, few studies have addressed the issue of urban coastal vulnerability at the landscape scale with spatial data that are finely resolved. The purpose of this study was to model and map coastal vulnerability and the role of natural habitats in reducing vulnerability in Jamaica Bay, New York, in terms of nine coastal vulnerability metrics (relief, wave exposure, geomorphology, natural habitats, exposure, exposure with no habitat, habitat role, erodible shoreline, and surge) under past (1609), current (2015), and future (2080) scenarios using InVEST 3.2.0. We analyzed vulnerability results both spatially and across all time periods, by stakeholder (ownership) and by distance to damage from Hurricane Sandy. We found significant differences in vulnerability metrics between past, current and future scenarios for all nine metrics except relief and wave exposure. The marsh islands in the center of the bay are currently vulnerable. In the future, these islands will likely be inundated, placing additional areas of the shoreline increasingly at risk. Significant differences in vulnerability exist between stakeholders; the Breezy Point Cooperative and Gateway National Recreation Area had the largest erodible shoreline segments. Significant correlations exist for all vulnerability (exposure/surge) and storm damage combinations except for exposure and distance to artificial debris. Coastal protective features, ranging from storm surge barriers and levees to natural features (e.g. wetlands), have been promoted to decrease future flood risk to communities in coastal areas around the world. Our methods of combining coastal vulnerability results with additional data and across multiple time periods have considerable potential to provide valuable predictions that resource managers can effectively use to identify areas for restoration and protection. PMID:27732674

Study on the Groundwater Vulnerability Assessment in Sanjiang Plain in Northeast China

NASA Astrophysics Data System (ADS)

Tang, Y.; Tang, W. K.; Liu, C.

2012-12-01

The Sanjiang Plain is located in eastern part of China's Heilongjiang Province.It's total area is 109 000 km2, with cultivated land area being 3.6677 million hm2. It is a major national commodity grain base. Rice planting area in Sanjiang Plain has been increasing year by year. Groundwater exploitation is increasing rapidly as a result of rapid increase of paddy field area. It is necessary to research and analyze spatial diversity of groundwater pollution vulnerability for Sanjiang Plain, so as to fulfill the goal of integrated planning, rational utilization of land and water resource, avoiding or minimizing groundwater contamination, and protecting grain security of China. Based on the commonly used DRASTIC method internationally, and according to hydrogeology, land use and other characteristics of Sanjiang Plain, this paper establishes groundwater vulnerability assessment index system. Since the Sanjiang Plain is an area that gives priority to agriculture, and impact of agricultural land and agricultural activity on groundwater vulnerability can not be ignored. Two indicators of agricultural land use rate (L) and population density (P) are increased in the DRASTC index system, the remaining 5 indicators are groundwater depth (D), aquifer net recharge(R), aquifer media type (A), soil type(S), aquifer hydraulic conductivity (C). Taking ArcGis as a calculation analysis platform to assess groundwater vulnerability of the Sanjiang Plain, by using hierarchical analysis method of the fuzzy mathematics method to calculate each index weigh of evaluation vulnerability. This paper applies 6 levels of assessment standard as follows: vulnerability index DI <2 stands for not vulnerable; 2 8 stands for extremely vulnerable. Groundwater vulnerably contaminated area is delineated based on the groundwater vulnerability spatial distribution of Sanjiang Plain. Reasonable land use plan should be made, and strictly groundwater protection measures should be taken to reduce the risk of groundwater contamination.

The sinking Mekong delta; modeling 25 years of groundwater extraction and subsidence

NASA Astrophysics Data System (ADS)

Minderhoud, P. S. J.; Erkens, G.; Pham, H. V.; Bui, V. T.; Erban, L. E.; Kooi, H.; Stouthamer, E.

2017-12-01

The Vietnamese Mekong delta, the third's largest delta in the world, is experiencing annual subsidence rates up to several centimeters. As a result, vulnerability to flooding and storm surges, salinization and, ultimately, permanent inundation increases. Extraction of groundwater from the soft deltaic subsurface can be a major driving mechanism of subsidence, however a quantification of temporal and spatial impact to subsidence in the Mekong delta was not done yet. We developed a delta-wide, 3D hydrogeological model coupled to a 1D geotechnical module to quantify the contribution of excessive groundwater exploitation to subsidence. The modelling period of 25 years captures the period in which the hydrogeological state of the delta transforming from almost undisturbed to a situation with increasing aquifer depletion. Our model provides a quantitative spatially-explicit assessment of groundwater extraction-induced subsidence for the entire Mekong delta since the start of widespread depletion of the groundwater reserves. Over the past decades subsidence related to groundwater extraction has accelerated towards the highest sinking rates at present. During the past 25 years, the delta sank on average 18 cm, with areas over 30 cm. Currently the delta experiences an average subsidence rate of 1.1 cm yr-1, some areas subside over 2.5 cm yr-1, due to groundwater exploitation. These rates outpace global sea level rise almost by an order of magnitude. Given the increasing trends in groundwater demand in the delta, the current rates are likely to increase in the near future.

Multi-scale geospatial agroecosystem modeling: A case study on the influence of soil data resolution on carbon budget estimates

EPA Science Inventory

The development of effective measures to stabilize atmospheric 22 CO2 concentration and mitigate negative impacts of climate change requires accurate quantification of the spatial variation and magnitude of the terrestrial carbon (C) flux. However, the spatial pattern and strengt...

Risk identification of agricultural drought for sustainable agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.; Tarquis, A. M.

2014-04-01

Drought is considered as one of the major natural hazards with significant impact to agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20 year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than those of mild to moderate drought throughout the warm season. Finally, the areas with diachronic drought persistence can be located. Drought early warning is developed using empirical functional relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought classes, respectively. The two fitted curves offer a forecasting tool on a monthly basis from May to October. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential. The adopted remote sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

Biophysical, infrastructural and social heterogeneities explain spatial distribution of waterborne gastrointestinal disease burden in Mexico City

NASA Astrophysics Data System (ADS)

Baeza, Andrés; Estrada-Barón, Alejandra; Serrano-Candela, Fidel; Bojórquez, Luis A.; Eakin, Hallie; Escalante, Ana E.

2018-06-01

Due to unplanned growth, large extension and limited resources, most megacities in the developing world are vulnerable to hydrological hazards and infectious diseases caused by waterborne pathogens. Here we aim to elucidate the extent of the relation between the spatial heterogeneity of physical and socio-economic factors associated with hydrological hazards (flooding and scarcity) and the spatial distribution of gastrointestinal disease in Mexico City, a megacity with more than 8 million people. We applied spatial statistics and multivariate regression analyses to high resolution records of gastrointestinal diseases during two time frames (2007–2009 and 2010–2014). Results show a pattern of significant association between water flooding events and disease incidence in the city center (lowlands). We also found that in the periphery (highlands), higher incidence is generally associated with household infrastructure deficiency. Our findings suggest the need for integrated and spatially tailored interventions by public works and public health agencies, aimed to manage socio-hydrological vulnerability in Mexico City.

Assessment of a Bayesian Belief Network-GIS framework as a practical tool to support marine planning.

PubMed

Stelzenmüller, V; Lee, J; Garnacho, E; Rogers, S I

2010-10-01

For the UK continental shelf we developed a Bayesian Belief Network-GIS framework to visualise relationships between cumulative human pressures, sensitive marine landscapes and landscape vulnerability, to assess the consequences of potential marine planning objectives, and to map uncertainty-related changes in management measures. Results revealed that the spatial assessment of footprints and intensities of human activities had more influence on landscape vulnerabilities than the type of landscape sensitivity measure used. We addressed questions regarding consequences of potential planning targets, and necessary management measures with spatially-explicit assessment of their consequences. We conclude that the BN-GIS framework is a practical tool allowing for the visualisation of relationships, the spatial assessment of uncertainty related to spatial management scenarios, the engagement of different stakeholder views, and enables a quick update of new spatial data and relationships. Ultimately, such BN-GIS based tools can support the decision-making process used in adaptive marine management. Copyright © 2010 Elsevier Ltd. All rights reserved.

Vulnerability assessment to frost disaster in dieng volcanic highland using spatial multi-criteria evaluation

NASA Astrophysics Data System (ADS)

Pradana, A.; Rahmanu, Y. A.; Prabaningrum, I.; Nurafifa, I.; Hizbaron, D. R.

2018-04-01

Dieng Volcanic Highland is one of frost disaster prone area which is very unique phenomenon in tropical region. Frost indicated by appearance of frozen dew or ice layer on the ground or vegetation surface due air inversion and cold temperatures during midnight in dry season. Appearance of frost significantly causes plant damage and losses on agricultural land, while the impacts were strongly influenced by level of vulnerability within agricultural communities. This study aims to analyze the impact of frost on agricultural land in Dieng, to identify characteristics of physical, social, economic vulnerability and coping capacity of agricultural communities to frost disaster in Dieng, and to estimate total vulnerability of frost disasters in Dieng through SMCE scenario. Research was conducted in Dieng Village, Wonosobo and Dieng Kulon Village, Banjarnegara. Method to assess vulnerability level is performed by Spatial Multi Criteria Evaluation (SMCE) method using ILWIS software through a combination of physical, social, and economic vulnerability regarding frost hazard, as well as coping capacity of farmers. Data collected by interview within different agricultural plots using questionnaire and in-depth interview method on frost affected agricultural land. Impact of frost mostly causes damage on potato agricultural land than any other types of commodities, such as carrot, leek or cabbage. Losses varies in range of 0 million to 55 million rupiah, at most events in range of 10 million to 15 million rupiah during frost season on July-August-September. Main factors determining vulnerability comes from crop losses, preparedness effort, and type of commodity. Agricultural land dominated by high level physical vulnerability (95.37 percent), high level social vulnerability (70.79 percent), moderate level economic vulnerability (79.23 percent) and moderate level coping capacity (73.18 percent). All five scenarios indicated that level of total vulnerability vary only from moderate level up to high level.

Vulnerability and risk of deltaic social-ecological systems exposed to multiple hazards.

PubMed

Hagenlocher, Michael; Renaud, Fabrice G; Haas, Susanne; Sebesvari, Zita

2018-08-01

Coastal river deltas are hotspots of global change impacts. Sustainable delta futures are increasingly threatened due to rising hazard exposure combined with high vulnerabilities of deltaic social-ecological systems. While the need for integrated multi-hazard approaches has been clearly articulated, studies on vulnerability and risk in deltas either focus on local case studies or single hazards and do not apply a social-ecological systems perspective. As a result, vulnerabilities and risks in areas with strong social and ecological coupling, such as coastal deltas, are not fully understood and the identification of risk reduction and adaptation strategies are often based on incomplete assumptions. To overcome these limitations, we propose an innovative modular indicator library-based approach for the assessment of multi-hazard risk of social-ecological systems across and within coastal deltas globally, and apply it to the Amazon, Ganges-Brahmaputra-Meghna (GBM), and Mekong deltas. Results show that multi-hazard risk is highest in the GBM delta and lowest in the Amazon delta. The analysis reveals major differences between social and environmental vulnerability across the three deltas, notably in the Mekong and the GBM deltas where environmental vulnerability is significantly higher than social vulnerability. Hotspots and drivers of risk vary spatially, thus calling for spatially targeted risk reduction and adaptation strategies within the deltas. Ecosystems have been identified as both an important element at risk as well as an entry point for risk reduction and adaptation strategies. Copyright © 2018. Published by Elsevier B.V.

On the Scaling Behavior of Reliability-Resilience-Vulnerability Indices in Agricultural Watersheds

EPA Science Inventory

Risk indices such as reliability-resilience-vulnerability (R-R-V) have been proposed to assess watershed health. In this study, the spatial scaling behavior of R-R-V indices has been explored for five agricultural watersheds in the midwestern United States. The study was conduc...

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

Exploration of health risks related to air pollution and temperature in three Latin American cities.

PubMed

Romero-Lankao, Patricia; Qin, Hua; Borbor-Cordova, Mercy

2013-04-01

This paper explores whether the health risks related to air pollution and temperature extremes are spatially and socioeconomically differentiated within three Latin American cities: Bogota, Colombia, Mexico City, Mexico, and Santiago, Chile. Based on a theoretical review of three relevant approaches to risk analysis (risk society, environmental justice, and urban vulnerability as impact), we hypothesize that health risks from exposure to air pollution and temperature in these cities do not necessarily depend on socio-economic inequalities. To test this hypothesis, we gathered, validated, and analyzed temperature, air pollution, mortality and socioeconomic vulnerability data from the three study cities. Our results show the association between air pollution levels and socioeconomic vulnerabilities did not always correlate within the study cities. Furthermore, the spatial differences in socioeconomic vulnerabilities within cities do not necessarily correspond with the spatial distribution of health impacts. The present study improves our understanding of the multifaceted nature of health risks and vulnerabilities associated with global environmental change. The findings suggest that health risks from atmospheric conditions and pollutants exist without boundaries or social distinctions, even exhibiting characteristics of a boomerang effect (i.e., affecting rich and poor alike) on a smaller scale such as areas within urban regions. We used human mortality, a severe impact, to measure health risks from air pollution and extreme temperatures. Public health data of better quality (e.g., morbidity, hospital visits) are needed for future research to advance our understanding of the nature of health risks related to climate hazards. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi.

PubMed

Montenegro, Diego; Cunha, Ana Paula da; Ladeia-Andrade, Simone; Vera, Mauricio; Pedroso, Marcel; Junqueira, Angela

2017-10-01

Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per year on average. To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area undergoing domiciliary vector interruption of T. cruzi in Colombia. Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive assistance (GAIA) methods] and spatial statistics were performed on data from a socio-environmental questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and indicators of five determinants of the CD vector pathway were summarily defined, including: (1) house indicator (HI); (2) triatominae indicator (TI); (3) host/reservoir indicator (Ho/RoI); (4) ecotope indicator (EI); and (5) socio-cultural indicator (S-CI). Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T. cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors' setting (border areas) on local values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector. The study model proposed here is flexible and can be adapted to various eco-epidemiological profiles and is suitable for focusing anti-T. cruzi serological surveillance programs in vulnerable human populations.

Spatial Distribution and Trends of Waterborne Diseases in Tashkent Province

PubMed Central

Subramanian, Veluswami Saravanan; Cho, Min Jung; Tan, Siwei Zoe; Fayzieva, Dilorom; Sebaly, Christian

2017-01-01

Introduction: The cumulative effect of limited investment in public water systems, inadequate public health infrastructure, and gaps in infectious disease prevention increased the incidence of waterborne diseases in Uzbekistan. The objectives of this study were: (1) to spatially analyze the distribution of the diseases in Tashkent Province, (2) to identify the intensity of spatial trends in the province, (3) to identify urban-rural characteristics of the disease distribution, and (4) to identify the differences in disease incidence between pediatric and adult populations of the province. Methods: Data on four major waterborne diseases and socio-demographics factors were collected in Tashkent Province from 2011 to 2014. Descriptive epidemiological methods and spatial-temporal methods were used to investigate the distribution and trends, and to identify waterborne diseases hotspots and vulnerable population groups in the province. Results: Hepatitis A and enterobiasis had a high incidence in most of Tashkent Province, with higher incidences in the eastern and western districts. Residents of rural areas, including children, were found to be more vulnerable to the waterborne diseases compared to other populations living in the province. Conclusions: This pilot study calls for more scientific investigations of waterborne diseases and their effect on public health in the region, which could facilitate targeted public health interventions in vulnerable regions of Uzbekistan. PMID:29138738

Spatial Distribution and Trends of Waterborne Diseases in Tashkent Province.

PubMed

Subramanian, Veluswami Saravanan; Cho, Min Jung; Tan, Siwei Zoe; Fayzieva, Dilorom; Sebaly, Christian

2017-01-01

The cumulative effect of limited investment in public water systems, inadequate public health infrastructure, and gaps in infectious disease prevention increased the incidence of waterborne diseases in Uzbekistan. The objectives of this study were: (1) to spatially analyze the distribution of the diseases in Tashkent Province, (2) to identify the intensity of spatial trends in the province, (3) to identify urban-rural characteristics of the disease distribution, and (4) to identify the differences in disease incidence between pediatric and adult populations of the province. Data on four major waterborne diseases and socio-demographics factors were collected in Tashkent Province from 2011 to 2014. Descriptive epidemiological methods and spatial-temporal methods were used to investigate the distribution and trends, and to identify waterborne diseases hotspots and vulnerable population groups in the province. Hepatitis A and enterobiasis had a high incidence in most of Tashkent Province, with higher incidences in the eastern and western districts. Residents of rural areas, including children, were found to be more vulnerable to the waterborne diseases compared to other populations living in the province. This pilot study calls for more scientific investigations of waterborne diseases and their effect on public health in the region, which could facilitate targeted public health interventions in vulnerable regions of Uzbekistan.

Development of structural vulnerability curve associated with high magnitude torrent occurrences in Switzerland

NASA Astrophysics Data System (ADS)

Wing-Yuen Chow, Candace; Bründl, Michael; Keiler, Margreth

2017-04-01

In mountain regions, high economic losses have increased significantly in the past decades due to severe hazard processes, in spite of notable investments in hazard management. Assessing the vulnerability of built structures to high magnitude torrent events is a part of consequence analysis, where hazard intensity is related to the degree of loss sustained. While vulnerability curves have been developed for different countries, the presented work contributes new data from Swiss-based case studies that address a known gap associated with the consequences of high magnitude events. Data for this stage of the investigation communicates the degree of loss associated with affected structures and has been provided by local authorities dealing with natural hazards (e.g. Amt für Wald des Kantons Bern (KAWA) and cantonal insurance providers). Information used for the empirical quantification of vulnerability to torrent processes is derived from detailed post-event documentation and the loss database and verified with field visits. Building the initial database supports data sharing and the systematic inclusion of additional case studies as they become available. The collection of this new data is fundamental to the development of a local vulnerability curve based on observed sediment deposition heights, a proxy for describing hazard intensity. The result will then be compared to curves derived from Austrian and Italian datasets.

Atherosclerotic plaque characterization by spatial and temporal speckle pattern analysis

NASA Astrophysics Data System (ADS)

Tearney, Guillermo J.; Bouma, Brett E.

2002-04-01

Improved methods are needed to identify the vulnerable coronary plaques responsible for acute myocardial infraction or sudden cardiac death. We describe a method for characterizing the structure and biomechanical properties of atherosclerotic plaques based on speckle pattern fluctuations. Near-field speckle images were acquired from five human aortic specimens ex vivo. The speckle decorrelation time constant varied significantly for vulnerable aortic plaques (τ = 40 ms) versus stable plaques (τ = 400 ms) and normal aorta (τ = 500 ms). These initial results indicate that different atherosclerotic plaque types may be distinguished by analysis of temporal and spatial speckle pattern fluctuations.

The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather.

PubMed

Krstic, Nikolas; Yuchi, Weiran; Ho, Hung Chak; Walker, Blake B; Knudby, Anders J; Henderson, Sarah B

2017-12-01

Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998-2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68-0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Towards high-resolution 4D flow MRI in the human aorta using kt-GRAPPA and B1+ shimming at 7T.

PubMed

Schmitter, Sebastian; Schnell, Susanne; Uğurbil, Kâmil; Markl, Michael; Van de Moortele, Pierre-François

2016-08-01

To evaluate the feasibility of aortic 4D flow magnetic resonance imaging (MRI) at 7T with improved spatial resolution using kt-GRAPPA acceleration while restricting acquisition time and to address radiofrequency (RF) excitation heterogeneities with B1+ shimming. 4D flow MRI data were obtained in the aorta of eight subjects using a 16-channel transmit/receive coil array at 7T. Flow quantification and acquisition time were compared for a kt-GRAPPA accelerated (R = 5) and a standard GRAPPA (R = 2) accelerated protocol. The impact of different dynamic B1+ shimming strategies on flow quantification was investigated. Two kt-GRAPPA accelerated protocols with 1.2 × 1.2 × 1.2 mm(3) and 1.8 × 1.8 × 2.4 mm(3) spatial resolution were compared. Using kt-GRAPPA, we achieved a 4.3-fold reduction in net acquisition time resulting in scan times of about 10 minutes. No significant effect on flow quantification was observed compared to standard GRAPPA with R = 2. Optimizing the B1+ fields for the aorta impacted significantly (P <  0.05) the flow quantification while specific B1+ settings were required for respiration navigators. The high-resolution protocol yielded similar flow quantification, but allowed the depiction of branching vessels. 7T in combination with B1+ shimming allows for high-resolution 4D flow MRI acquisitions in the human aorta, while kt-GRAPPA limits total scan times without affecting flow quantification. J. Magn. Reson. Imaging 2016;44:486-499. © 2016 Wiley Periodicals, Inc.

Scale as the common language for soil variations revealed with geophysics, biophysics, and remote sensing

USDA-ARS?s Scientific Manuscript database

Quantification and estimation of crop response to management are important for efficient use of resources. Because the spatial distribution of crop response is related to the distribution of soil properties, crop response to management practices will also have a strong spatial component. Most plot r...

Crack Imaging and Quantification in Aluminum Plates with Guided Wave Wavenumber Analysis Methods

NASA Technical Reports Server (NTRS)

Yu, Lingyu; Tian, Zhenhua; Leckey, Cara A. C.

2015-01-01

Guided wavefield analysis methods for detection and quantification of crack damage in an aluminum plate are presented in this paper. New wavenumber components created by abrupt wave changes at the structural discontinuity are identified in the frequency-wavenumber spectra. It is shown that the new wavenumbers can be used to detect and characterize the crack dimensions. Two imaging based approaches, filter reconstructed imaging and spatial wavenumber imaging, are used to demonstrate how the cracks can be evaluated with wavenumber analysis. The filter reconstructed imaging is shown to be a rapid method to map the plate and any existing damage, but with less precision in estimating crack dimensions; while the spatial wavenumber imaging provides an intensity image of spatial wavenumber values with enhanced resolution of crack dimensions. These techniques are applied to simulated wavefield data, and the simulation based studies show that spatial wavenumber imaging method is able to distinguish cracks of different severities. Laboratory experimental validation is performed for a single crack case to confirm the methods' capabilities for imaging cracks in plates.

Indicator-based model to assess vulnerability to landslides in urban areas. Case study of Husi city (Eastern Romania)

NASA Astrophysics Data System (ADS)

Grozavu, Adrian; Ciprian Margarint, Mihai; Catalin Stanga, Iulian

2013-04-01

In the last three or four decades, vulnerability evolved from physical fragility meanings to a more complex concept, being a key element of risk assessment. In landslide risk assessment, there are a large series of studies regarding landslide hazard, but far fewer researches focusing on vulnerability measurement. Furthermore, there is still no unitary understanding on the methodological framework, neither any internationally agreed standard for landslide vulnerability measurements. The omnipresent common element is the existence of elements at risk, but while some approaches are limited to exposure, other focus on the degree of losses (human injuries, material damages and monetary losses, structural dysfunctions etc.). These losses are differently assessed using both absolute and relative values on qualitative or quantitative scales and they are differently integrated to provide a final vulnerability value. This study aims to assess vulnerability to landslides at local level using an indicator-based model applied to urban areas and tested for Husi town (Eastern Romania). The study region is characterized by permeable and impermeable alternating sedimentary rocks, monoclinal geological structure and hilly relief with impressive cuestas, continental temperate climate, and precipitation of about 500 mm/year, rising to 700 m and even more in some rainy years. The town is a middle size one (25000 inhabitants) and it had an ascending evolution in the last centuries, followed by an increasing human pressure on lands. Methodologically, the first step was to assess the landslide susceptibility and to identify in this way those regions within which any asset would be exposed to landslide hazards. Landslide susceptibility was assessed using the logistic regression approach, taking into account several quantitative and qualitative factors (elements of geology, morphometry, rainfall, land use etc.). The spatial background consisted in the Digital Elevation Model and all derived maps (slope, aspect, shading), realized based on the topographical plans and maps (1:1000, 1:5000). The second step was to realize the spatial inventory of elements at risk (vector format), based on the General Urban Plan (1:5000), the orthorectified aerial images (2009, resolution: 0.5 meters) and field investigations. All elements have been classified using attribute databases: residential buildings (single or multiple dwellings), other buildings according to their functionality, main and secondary roads, special transport network etc. Data about population have been added in order to assess the intrinsic value of each element and the number of potentially affected peoples. The study also took into account issues as preparedness and preventive measures (risk prevention plans, reinforcing structures, draining wells etc.), coping ability (network geometry and connectivity, emergency services accessibility) and recovering capacity (e.g. the existence of insurance policies). According to their importance and functionality, a distinct rank (ri … rn) was assigned to each element at risk (i1…in) showing the level of vulnerability. The rank values were assigned mainly on the expert knowledge and they range from 1 (limited damages, no affected people) to 5 (several households and people affected, dysfunctions in the urban system). The vulnerability index (Vi) was obtained combining the rank with the role of vulnerability factors (Fi), according to their degree of influence: the number of people that would be affected, the potential material and economic damages, the relationship with the neighboring exposed elements, the existence of the preventing, coping and recovering measures etc. Thus, the general equation of vulnerability has the form of weighted geometric mean: Vi=ri•Fi = ri•(w1F1 • w2F2 • … • wmFm). It must be noted that the weighting coefficients (wi) have subunitary or supraunitary value according to their role in diminishing or increasing the vulnerability level. The general vulnerability index (GVI) was obtained through a final transformation that was done to limit the spread of variation between zero (minimum vulnerability) and one (maximum vulnerability): GVIi = Vi/Vmax. In this form, the elements at risk are individually inventoried and spatialized in vector format as points, lines, polygons, each one having its own vulnerability value, but the results can be used only at the precise local level (both by practitioners and decision makers). To allow a more profound interpretation, the general vulnerability index was spatialized in two distinct ways: (1) creating a raster with a standard pixel size (e.g. 20 x 20 m, 50 x 50 m) and calculating the average vulnerability of the exposed elements in each pixel; (2) choosing a interpolation method (e.g. krigging) that would allow to integrate the spatial autocorrelation of the elements at risk and to obtain an output raster at the same resolution with the susceptibility map and a further risk assessment.

Hazard-Specific Vulnerability Mapping for Water Security in a Shale Gas Context

NASA Astrophysics Data System (ADS)

Allen, D. M.; Holding, S.; McKoen, Z.

2015-12-01

Northeast British Columbia (NEBC) is estimated to hold large reserves of unconventional natural gas and has experienced rapid growth in shale gas development activities over recent decades. Shale gas development has the potential to impact the quality and quantity of surface and ground water. Robust policies and sound water management are required to protect water security in relation to the water-energy nexus surrounding shale gas development. In this study, hazard-specific vulnerability mapping was conducted across NEBC to identify areas most vulnerable to water quality and quantity deterioration due to shale gas development. Vulnerability represents the combination of a specific hazard threat and the susceptibility of the water system to that threat. Hazard threats (i.e. potential contamination sources and water abstraction) were mapped spatially across the region. The shallow aquifer susceptibility to contamination was characterised using the DRASTIC aquifer vulnerability approach, while the aquifer susceptibility to abstraction was mapped according to aquifer productivity. Surface water susceptibility to contamination was characterised on a watershed basis to describe the propensity for overland flow (i.e. contaminant transport), while watershed discharge estimates were used to assess surface water susceptibility to water abstractions. The spatial distribution of hazard threats and susceptibility were combined to form hazard-specific vulnerability maps for groundwater quality, groundwater quantity, surface water quality and surface water quantity. The vulnerability maps identify priority areas for further research, monitoring and policy development. Priority areas regarding water quality occur where hazard threat (contamination potential) coincide with high aquifer susceptibility or high overland flow potential. Priority areas regarding water quantity occur where demand is estimated to represent a significant proportion of estimated supply. The identification of priority areas allows for characterization of the vulnerability of water security in the region. This vulnerability mapping approach, using the hazard threat and susceptibility indicators, can be applied to other shale gas areas to assess vulnerability to shale gas activities and support water security.

Spatial econometric model of natural disaster impacts on human migration in vulnerable regions of Mexico.

PubMed

Saldaña-Zorrilla, Sergio O; Sandberg, Krister

2009-10-01

Mexico's vast human and environmental diversity offers an initial framework for comprehending some of the prevailing great disparities between rich and poor. Its socio-economic constructed vulnerability to climatic events serves to expand this understanding. Based on a spatial econometric model, this paper tests the contribution of natural disasters to stimulating the emigration process in vulnerable regions of Mexico. Besides coping and adaptive capacity, it assesses the effects of economic losses due to disasters as well as the adverse production and trade conditions of the 1990s on emigration rates in 2000 at the municipality level. Weather-related disasters were responsible for approximately 80 per cent of economic losses in Mexico between 1980 and 2005, mostly in the agricultural sector, which continues to dominate many parts of the country. It is dramatic that this sector generates around only four per cent of gross domestic product but provides a livelihood to about one-quarter of the national population. It is no wonder, therefore, that most emigration from this country arises in vulnerable rural areas.

Spatial Sequences, but Not Verbal Sequences, Are Vulnerable to General Interference during Retention in Working Memory

ERIC Educational Resources Information Center

Morey, Candice C.; Miron, Monica D.

2016-01-01

Among models of working memory, there is not yet a consensus about how to describe functions specific to storing verbal or visual-spatial memories. We presented aural-verbal and visual-spatial lists simultaneously and sometimes cued one type of information after presentation, comparing accuracy in conditions with and without informative…

The effect of spatial resolution on water scarcity estimates in Australia

NASA Astrophysics Data System (ADS)

Gevaert, Anouk; Veldkamp, Ted; van Dijk, Albert; Ward, Philip

2017-04-01

Water scarcity is an important global issue with severe socio-economic consequences, and its occurrence is likely to increase in many regions due to population growth, economic development and climate change. This has prompted a number of global and regional studies to identify areas that are vulnerable to water scarcity and to determine how this vulnerability will change in the future. A drawback of these studies, however, is that they typically have coarse spatial resolutions. Here, we studied the effect of increasing the spatial resolution of water scarcity estimates in Australia, and the Murray-Darling Basin in particular. This was achieved by calculating the water stress index (WSI), an indicator showing the ratio of water use to water availability, at 0.5 and 0.05 degree resolution for the period 1990-2010. Monthly water availability data were based on outputs of the Australian Water Resources Assessment Landscape model (AWRA-L), which was run at both spatial resolutions and at a daily time scale. Water use information was obtained from a monthly 0.5 degree global dataset that distinguishes between water consumption for irrigation, livestock, industrial and domestic uses. The data were downscaled to 0.05 degree by dividing the sectoral water uses over the areas covered by relevant land use types using a high resolution ( 0.5km) land use dataset. The monthly WSIs at high and low resolution were then used to evaluate differences in the patterns of water scarcity frequency and intensity. In this way, we assess to what extent increasing the spatial resolution can improve the identification of vulnerable areas and thereby assist in the development of strategies to lower this vulnerability. The results of this study provide insight into the scalability of water scarcity estimates and the added value of high resolution water scarcity information in water resources management.

Meteorological risks are drivers of environmental innovation in agro-ecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van de Vijver, Hans; Vanwindekens, Frédéric; de Frutos Cachorro, Julia; Verspecht, Ann; Planchon, Viviane; Buyse, Jeroen

2017-04-01

Agricultural crop production is to a great extent determined by weather conditions. The research hypothesis is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management. The methodology comprised five major parts: the hazard, its impact on different agro-ecosystems, vulnerability, risk management and risk communication. Generalized Extreme Value (GEV) theory was used to model annual maxima of meteorological variables based on a location-, scale- and shape-parameter that determine the center of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Spatial interpolation of GEV-derived return levels resulted in spatial temperature extremes, precipitation deficits and wet periods. The temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was realised using a bio-physically based modelling framework that couples phenology, a soil water balance and crop growth. 20-year return values for drought and waterlogging during different crop stages were related to arable yields. The method helped quantify agricultural production risks and rate both weather and crop-based agricultural insurance. The spatial extent of vulnerability is developed on different layers of geo-information to include meteorology, soil-landscapes, crop cover and management. Vulnerability of agroecosystems was mapped based on rules set by experts' knowledge and implemented by Fuzzy Inference System modelling and Geographical Information System tools. The approach was applied for cropland vulnerability to heavy rain and grassland vulnerability to drought. The level of vulnerability and resilience of an agro-ecosystem was also determined by risk management which differed across sectors and farm types. A calibrated agro-economic model demonstrated a marked influence of climate adapted land allocation and crop management on individual utility. The "chain of risk" approach allowed for investigating the hypothesis that meteorological risks act as drivers for agricultural innovation. Risk types were quantified in terms of probability and distribution, and further distinguished according to production type. Examples of strategies and options were provided at field, farm and policy level using different modelling methods.

The spatial distribution of vulnerability to the health impacts of flooding in the Mekong Delta, Vietnam.

PubMed

Phung, Dung; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Do, Cuong Manh; Nguyen, Thuy; Duong, Nam Chi

2016-06-01

Flooding causes significant public health issues. The Mekong Delta has been considered the region to be the most vulnerable to flooding in Vietnam. This study assessed the spatial vulnerability of the health impacts of flooding in the Mekong Delta region, Vietnam. This study applied a vulnerability assessment framework which was computed as the function of three dimensions: exposure, sensitivity, and adaptive capacity. The indicators for each dimension were derived from the relevant literature, consultations with experts, and data availability. An analytic hierarchy process (AHP) and a principal component analysis (PCA) were used to determine the weight of indicators. Vulnerability indexes (VIs) were then computed for each province. A total of 29 indicators (sensitivity index, 14; adaptive capacity index, 13; and exposure index, 2) were employed to evaluate the vulnerability to the health impacts of flooding at a provincial level. The results of AHP revealed that the highest VIs were found in the Dong Thap and An Giang provinces (VI, 1.948 and 1.574, respectively). VIs were distributed with higher indexes in upstream provinces close to a river than in coastal provinces. PCA generated three components from the 29 indicators, and the VIs computed from the PCA method are in substantial agreement with the AHP method (ICC = 0.71, p < 0.05). The vulnerability to the health impacts of flooding varies from province to province in the Mekong Delta region in Vietnam. Individual plans for health preparedness and adaption to flooding should be developed for each province in the Mekong Delta region.

A metric-based assessment of flood risk and vulnerability of rural communities in the Lower Shire Valley, Malawi

NASA Astrophysics Data System (ADS)

Adeloye, A. J.; Mwale, F. D.; Dulanya, Z.

2015-06-01

In response to the increasing frequency and economic damages of natural disasters globally, disaster risk management has evolved to incorporate risk assessments that are multi-dimensional, integrated and metric-based. This is to support knowledge-based decision making and hence sustainable risk reduction. In Malawi and most of Sub-Saharan Africa (SSA), however, flood risk studies remain focussed on understanding causation, impacts, perceptions and coping and adaptation measures. Using the IPCC Framework, this study has quantified and profiled risk to flooding of rural, subsistent communities in the Lower Shire Valley, Malawi. Flood risk was obtained by integrating hazard and vulnerability. Flood hazard was characterised in terms of flood depth and inundation area obtained through hydraulic modelling in the valley with Lisflood-FP, while the vulnerability was indexed through analysis of exposure, susceptibility and capacity that were linked to social, economic, environmental and physical perspectives. Data on these were collected through structured interviews of the communities. The implementation of the entire analysis within GIS enabled the visualisation of spatial variability in flood risk in the valley. The results show predominantly medium levels in hazardousness, vulnerability and risk. The vulnerability is dominated by a high to very high susceptibility. Economic and physical capacities tend to be predominantly low but social capacity is significantly high, resulting in overall medium levels of capacity-induced vulnerability. Exposure manifests as medium. The vulnerability and risk showed marginal spatial variability. The paper concludes with recommendations on how these outcomes could inform policy interventions in the Valley.

Mapping the Decadal Spatio-temporal Variation of Social Vulnerability to Hydro-climatic Extremes over India

NASA Astrophysics Data System (ADS)

H, V.; Karmakar, S.; Ghosh, S.

2015-12-01

Human induced global warming is unequivocal and observational studies shows that, this has led to increase in the intensity and frequency of hydro-climatic extremes, most importantly precipitation extreme, heat waves and drought; and also is expected to be increased in the future. The occurrence of these extremes have a devastating effects on nation's economy and on societal well-being. Previous studies on India provided the evidences of significant changes in the precipitation extreme from pre- to post-1950, with huge spatial heterogeneity; and projections of heat waves indicated that significant part of India will experience heat stress conditions in the future. Under these circumstance, it is necessary to develop a nation-wide social vulnerability map to scrutinize the adequacy of existing emergency management. Yet there has been no systematic past efforts on mapping social vulnerability to hydro-climatic extremes at nation-wide for India. Therefore, immediate efforts are required to quantify the social vulnerability, particularly developing country like India, where major transformations in demographic characteristics and development patterns are evident during past decades. In the present study, we perform a comprehensive spatio-temporal social vulnerability analysis by considering multiple sensitive indicators for three decades (1990-2010) which identifies the hot-spots, with higher vulnerability to hydro-climatic extremes. The population datasets are procured from Census of India and the meteorological datasets are obtained from India Meteorological Department (IMD). The study derives interesting results on decadal changes of spatial distribution of risk, considering social vulnerability and hazard to extremes.

Mapping cropping patterns in irrigated rice fields in West Java: Towards mapping vulnerability to flooding using time-series MODIS imageries

NASA Astrophysics Data System (ADS)

Sianturi, Riswan; Jetten, V. G.; Sartohadi, Junun

2018-04-01

Information on the vulnerability to flooding is vital to understand the potential damages from flood events. A method to determine the vulnerability to flooding in irrigated rice fields using the Enhanced Vegetation Index (EVI) was proposed in this study. In doing so, the time-series EVI derived from time-series 8 day 500 m spatial resolution MODIS imageries (MOD09A1) was used to generate cropping patterns in irrigated rice fields in West Java. Cropping patterns were derived from the spatial distribution and phenology metrics so that it is possible to show the variation of vulnerability in space and time. Vulnerability curves and cropping patterns were used to determine the vulnerability to flooding in irrigated rice fields. Cropping patterns capture the shift in the vulnerability, which may lead to either an increase or decrease of the degree of damage in rice fields of origin and other rice fields. The comparison of rice field areas between MOD09A1 and ALOS PALSAR and MOD09A1 and Agricultural Statistics showed consistent results with R2 = 0.81 and R2 = 0.93, respectively. The estimated and observed DOYs showed RMSEs = 9.21, 9.29, and 9.69 days for the Start of Season (SOS), heading stage, and End of Season (EOS), respectively. Using the method, one can estimate the relative damage provided available information on the flood depth and velocity. The results of the study may support the efforts to reduce the potential damages from flooding in irrigated rice fields.

Climate extremes and predicted warming threaten Mediterranean Holocene firs forests refugia

PubMed Central

Camarero, J. Julio; Carrer, Marco; Gutiérrez, Emilia; Alla, Arben Q.; Andreu-Hayles, Laia; Hevia, Andrea; Koutavas, Athanasios; Martínez-Sancho, Elisabet; Nola, Paola; Papadopoulos, Andreas; Pasho, Edmond; Toromani, Ervin

2017-01-01

Warmer and drier climatic conditions are projected for the 21st century; however, the role played by extreme climatic events on forest vulnerability is still little understood. For example, more severe droughts and heat waves could threaten quaternary relict tree refugia such as Circum-Mediterranean fir forests (CMFF). Using tree-ring data and a process-based model, we characterized the major climate constraints of recent (1950–2010) CMFF growth to project their vulnerability to 21st-century climate. Simulations predict a 30% growth reduction in some fir species with the 2050s business-as-usual emission scenario, whereas growth would increase in moist refugia due to a longer and warmer growing season. Fir populations currently subjected to warm and dry conditions will be the most vulnerable in the late 21st century when climatic conditions will be analogous to the most severe dry/heat spells causing dieback in the late 20th century. Quantification of growth trends based on climate scenarios could allow defining vulnerability thresholds in tree populations. The presented predictions call for conservation strategies to safeguard relict tree populations and anticipate how many refugia could be threatened by 21st-century dry spells. PMID:29109266

Geoenvironments from the vicinity of Arctowski Station, Admiralty Bay, King George Island, Antarctica: vulnerability and valuation assessment

USGS Publications Warehouse

Schaefer, Carlos Ernesto G.R.; Santana, Rogério Mercandelle; Simas, Felipe Nogueira Bello; Francelino, Márcio R.; Filho, Elpídio Inácio Fernandes; Albuquerque, Miriam Abreu; Calijuri, Maria Lúcia

2007-01-01

The use of a geographic information system (GIS) allows the mapping and quantification of biotic and physical features of importance to the environmental planning of Antarctic areas. In this paper we examined the main aspects of the geoenvironments of Arctowski Station vicinity (Admiralty bay, Maritime Antartica), by means of a photointerpretation of an orthomosaic at 1:6000 scale, produced by non-conventional aerial photographs obtained by the Brazilian Cryosols project. We carried out a preliminary environmental valuation and vulnerability assessment of the area. Hence, geoenvironments were classified and ranked according with their biological valuation and vulnerability (fragility), mapping 20 units covering approximately 150 ha. The most fragile geoenvironmental units were former and present penguin rookeries with different vegetation covers, all very prone to degradation by over-trampling and human perturbations. The relationships between each geoenvironment were also explored, emphasizing the ecological aspects and their valuation. In quantitative terms, the most vulnerable and fragile units (classes 4 and 5) occupy nearly 22 % of the total area, being highly concentrated near the coastal areas. There, ornithogenic input is an important factor favoring the vegetation development.

Climate extremes and predicted warming threaten Mediterranean Holocene firs forests refugia.

PubMed

Sánchez-Salguero, Raúl; Camarero, J Julio; Carrer, Marco; Gutiérrez, Emilia; Alla, Arben Q; Andreu-Hayles, Laia; Hevia, Andrea; Koutavas, Athanasios; Martínez-Sancho, Elisabet; Nola, Paola; Papadopoulos, Andreas; Pasho, Edmond; Toromani, Ervin; Carreira, José A; Linares, Juan C

2017-11-21

Warmer and drier climatic conditions are projected for the 21st century; however, the role played by extreme climatic events on forest vulnerability is still little understood. For example, more severe droughts and heat waves could threaten quaternary relict tree refugia such as Circum-Mediterranean fir forests (CMFF). Using tree-ring data and a process-based model, we characterized the major climate constraints of recent (1950-2010) CMFF growth to project their vulnerability to 21st-century climate. Simulations predict a 30% growth reduction in some fir species with the 2050s business-as-usual emission scenario, whereas growth would increase in moist refugia due to a longer and warmer growing season. Fir populations currently subjected to warm and dry conditions will be the most vulnerable in the late 21st century when climatic conditions will be analogous to the most severe dry/heat spells causing dieback in the late 20th century. Quantification of growth trends based on climate scenarios could allow defining vulnerability thresholds in tree populations. The presented predictions call for conservation strategies to safeguard relict tree populations and anticipate how many refugia could be threatened by 21st-century dry spells.

Mapping Extreme Heat Vulnerability and Health Outcomes to inform the District of Columbia's Climate Adaptation Plan

NASA Astrophysics Data System (ADS)

Declet-Barreto, J.; Wilhelmi, O.; Goggans, A.

2016-12-01

In this collaborative engagement, scientists are partnering with the District of Columbia (DC) to develop an extreme heat vulnerability assessment. To do so, we map socio-demographic and built environment indicators of extreme heat vulnerability in Census Tracts in DC neighborhoods. In order to provide information useful for DC public health and urban planning practitioners, we aggregate the indicators into an index of extreme heat vulnerability. We compare the index against heat-related call data from DC's 911 system to better understand the socio-spatial distribution of extreme heat-related health outcomes. Our assessment can help inform the District's Climate Adaptation Plan as well as increase public engagement in reducing vulnerability to extreme heat.

A relative vulnerability estimation of flood disaster using data envelopment analysis in the Dongting Lake region of Hunan

NASA Astrophysics Data System (ADS)

Li, C.-H.; Li, N.; Wu, L.-C.; Hu, A.-J.

2013-07-01

The vulnerability to flood disaster is addressed by a number of studies. It is of great importance to analyze the vulnerability of different regions and various periods to enable the government to make policies for distributing relief funds and help the regions to improve their capabilities against disasters, yet a recognized paradigm for such studies seems missing. Vulnerability is defined and evaluated through either physical or economic-ecological perspectives depending on the field of the researcher concerned. The vulnerability, however, is the core of both systems as it entails systematic descriptions of flood severities or disaster management units. The research mentioned often has a development perspective, and in this article we decompose the overall flood system into several factors: disaster driver, disaster environment, disaster bearer, and disaster intensity, and take the interaction mechanism among all factors as an indispensable function. The conditions of flood disaster components are demonstrated with disaster driver risk level, disaster environment stability level and disaster bearer sensitivity, respectively. The flood system vulnerability is expressed as vulnerability = f(risk, stability, sensitivity). Based on the theory, data envelopment analysis method (DEA) is used to detail the relative vulnerability's spatiotemporal variation of a flood disaster system and its components in the Dongting Lake region. The study finds that although a flood disaster system's relative vulnerability is closely associated with its components' conditions, the flood system and its components have a different vulnerability level. The overall vulnerability is not the aggregation of its components' vulnerability. On a spatial scale, zones central and adjacent to Dongting Lake and/or river zones are characterized with very high vulnerability. Zones with low and very low vulnerability are mainly distributed in the periphery of the Dongting Lake region. On a temporal scale, the occurrence of a vibrating flood vulnerability trend is observed. A different picture is displayed with the disaster driver risk level, disaster environment stability level and disaster bearer sensitivity level. The flood relative vulnerability estimation method based on DEA is characteristic of good comparability, which takes the relative efficiency of disaster system input-output into account, and portrays a very diverse but consistent picture with varying time steps. Therefore, among different spatial and time domains, we could compare the disaster situations with what was reflected by the same disaster. Additionally, the method overcomes the subjectivity of a comprehensive flood index caused by using an a priori weighting system, which exists in disaster vulnerability estimation of current disasters.

Spatial patterns of ergot and quantification of sclerotia in perennial ryegrass seed fields

USDA-ARS?s Scientific Manuscript database

Ergot, caused by Claviceps purpurea, is a major disease of perennial ryegrass grass grown for seed in eastern Oregon. The objective of this research was to quantify and describe the spatial patterns of ergot severity in each of three 50 ha commercial fields of perennial ryegrass grown for seed in 20...

Identifying Population Vulnerable to Extreme Heat Events in San Jose, California.

NASA Astrophysics Data System (ADS)

Rivera, A. L.

2016-12-01

The extreme heat days not only make cities less comfortable for living but also they are associated with increased morbidity and mortality. Mapping studies have demonstrated spatial variability in heat vulnerability. A study conducted between 2000 and 2011 in New York City shows that deaths during heat waves was more likely to occur in black individuals, at home in census tracts which received greater public assistance. This map project intends to portray areas in San Jose California that are vulnerable to extreme heat events. The variables considered to build a vulnerability index are: land surface temperature, vegetated areas (NDVI), and people exposed to these area (population density).

On the Scaling Behavior of Reliability-Resilience-Vulnerability ...

EPA Pesticide Factsheets

Risk indices such as reliability-resilience-vulnerability (R-R-V) have been proposed to assess watershed health. In this study, the spatial scaling behavior of R-R-V indices has been explored for five agricultural watersheds in the midwestern United States. The study was conducted using two different measures of spatial scale: (i) the ratio of contributing upland area to area required for channel initiation (FA), and (ii) Strahler stream order. It was found that R-R-V indices do change with spatial scale, but a representative watershed-specific threshold FA value exists for these indices to achieve stable values. Scaling with Strahler stream order is feasible if the watershed possesses a tree-like stream network. As an example of anthropogenic influences, this study also examined the role of BMPs placed within an agricultural watershed via a cost-effective optimization scheme on the evolution of R-R-V values with scale. While the placement of BMPs acheived reductions in concentrations and/or loads of constituents, they may not significantly change watershed risk measures, but are likely to cause significant reduction in vulnerability. If primarily upland BMPs are placed in a diffuse manner throughout the watershed, there might not be a significant change in the scaling behavior of R-R-V values. The primary objective of this study is to investigate the effect of spatial scale on risk-based watershed health assessment. A related objective is to examine wh

Computational analysis of PET by AIBL (CapAIBL): a cloud-based processing pipeline for the quantification of PET images

NASA Astrophysics Data System (ADS)

Bourgeat, Pierrick; Dore, Vincent; Fripp, Jurgen; Villemagne, Victor L.; Rowe, Chris C.; Salvado, Olivier

2015-03-01

With the advances of PET tracers for β-Amyloid (Aβ) detection in neurodegenerative diseases, automated quantification methods are desirable. For clinical use, there is a great need for PET-only quantification method, as MR images are not always available. In this paper, we validate a previously developed PET-only quantification method against MR-based quantification using 6 tracers: 18F-Florbetaben (N=148), 18F-Florbetapir (N=171), 18F-NAV4694 (N=47), 18F-Flutemetamol (N=180), 11C-PiB (N=381) and 18F-FDG (N=34). The results show an overall mean absolute percentage error of less than 5% for each tracer. The method has been implemented as a remote service called CapAIBL (http://milxcloud.csiro.au/capaibl). PET images are uploaded to a cloud platform where they are spatially normalised to a standard template and quantified. A report containing global as well as local quantification, along with surface projection of the β-Amyloid deposition is automatically generated at the end of the pipeline and emailed to the user.

Integrated Earthquake Risk Assessment in the Kathmandu Valley - A Case Study

NASA Astrophysics Data System (ADS)

Schaper, Julia; Anhorn, Johannes; Khazai, Bijan; Nüsser, Marcus

2013-04-01

Rapid urban growth is a process which can be observed in cities worldwide. Managing these growing urban areas has become a major challenge for both governing bodies and citizens. Situated not only in a highly earthquake and landslide-prone area, but comprising also the cultural and political capital of Nepal, the fast expanding Kathmandu Valley in the Himalayan region is of particular interest. Vulnerability assessment has been an important tool for spatial planning in this already densely populated area. The magnitude 8.4 earthquake of Bihar in 1934 cost 8600 Nepalis their lives, destroyed 20% of the Kathmandu building stock and heavily damaged another 40%. Since then, Kathmandu has grown into a hub with over a million inhabitants. Rapid infrastructure and population growth aggravate the vulnerability conditions, particularly in the core area of Metropolitan Kathmandu. We propose an integrative framework for vulnerability and risk in Kathmandu Valley. In order to move towards a more systemic and integrated approach, we focus on interactions between natural hazards, physically engineered systems and society. High resolution satellite images are used to identify structural vulnerability of the building stock within the study area. Using object-based image analysis, the spatial dynamics of urban growth are assessed and validated using field data. Complementing this is the analysis of socio-economic attributes gained from databases and field surveys. An indicator-based vulnerability and resilience index will be operationalized using multi-attribute value theory and statistical methods such as principal component analysis. The results allow for a socio-economic comparison of places and their relative potential for harm and loss. The objective in this task is to better understand the interactions between nature and society, engineered systems and built environments through the development of an interdisciplinary framework on systemic seismic risk and vulnerability. Data from incidences of large-scale Himalayan earthquake disasters will form the basis for a multi-temporal analysis. By analyzing different time slots we identify development paths and building integrity shifts in the light of dynamic urbanization processes. Hereby, future trends and spatial scenarios can be developed. We suggest a goal oriented indicator evaluation process to compare different development scenarios. This serves as an orientation for spatial planning strategies for local and international stakeholders.

Potential climate change impacts on four biophysical indicators of cattle production from western US rangelands

Treesearch

Matthew Clark Reeves; Karen E. Bagne; John Tanaka

2017-01-01

We examined multiple environmental factors related to climate change that affect cattle production on rangelands to identify sources of vulnerability among seven regions of the western United States. Climate change effects were projected to 2100 using published spatially explicit model output for four indicators of vulnerability: forage quantity, vegetation type...

Global patterns in the vulnerability of ecosystems to vegetation shifts due to climate change

Treesearch

Patrick Gonzalez; Ronald P. Neilson; James M. Lenihan; Raymond J. Drapek

2010-01-01

Climate change threatens to shift vegetation, disrupting ecosystems and damaging human well-being. Field observations in boreal, temperate and tropical ecosystems have detected biome changes in the 20th century, yet a lack of spatial data on vulnerability hinders organizations that manage natural resources from identifying priority areas for adaptation measures. We...

Climate-smart management of biodiversity

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.; Rosenblatt, Daniel L.

2015-01-01

Determining where biodiversity is likely to be most vulnerable to climate change and methods to reduce that vulnerability are necessary first steps to incorporate climate change into biodiversity management plans. Here, we use a spatial climate change vulnerability assessment to (1) map the potential vulnerability of terrestrial biodiversity to climate change in the northeastern United States and (2) provide guidance on how and where management actions for biodiversity could provide long-term benefits under climate change (i.e., climate-smart management considerations). Our model suggests that biodiversity will be most vulnerable in Delaware, Maryland, and the District of Columbia due to the combination of high climate change velocity, high landscape resistance, and high topoclimate homogeneity. Biodiversity is predicted to be least vulnerable in Vermont, Maine, and New Hampshire because large portions of these states have low landscape resistance, low climate change velocity, and low topoclimate homogeneity. Our spatial climate-smart management considerations suggest that: (1) high topoclimate diversity could moderate the effects of climate change across 50% of the region; (2) decreasing local landscape resistance in conjunction with other management actions could increase the benefit of those actions across 17% of the region; and (3) management actions across 24% of the region could provide long-term benefits by promoting short-term population persistence that provides a source population capable of moving in the future. The guidance and framework we provide here should allow conservation organizations to incorporate our climate-smart management considerations into management plans without drastically changing their approach to biodiversity conservation.

[Teenage pregnancy rates and socioeconomic characteristics of municipalities in São Paulo State, Southeast Brazil: a spatial analysis].

PubMed

Martinez, Edson Zangiacomi; Roza, Daiane Leite da; Caccia-Bava, Maria do Carmo Gullaci Guimarães; Achcar, Jorge Alberto; Dal-Fabbro, Amaury Lelis

2011-05-01

Teenage pregnancy is a common public health problem worldwide. The objective of this ecological study was to investigate the spatial association between teenage pregnancy rates and socioeconomic characteristics of municipalities in São Paulo State, Southeast Brazil. We used a Bayesian model with a spatial distribution following a conditional autoregressive (CAR) form based on Markov Chain Monte Carlo algorithm. We used data from the Live Birth Information System (SINASC) and the Brazilian Institute of Geography and Statistics (IBGE). Early pregnancy was more frequent in municipalities with lower per capital gross domestic product (GDP), higher poverty rate, smaller population, lower human development index (HDI), and a higher percentage of individuals with State social vulnerability index of 5 or 6 (more vulnerable). The study demonstrates a significant association between teenage pregnancy and socioeconomic indicators.

Multi-level significance of vulnerability indicators. Case study: Eastern Romania

NASA Astrophysics Data System (ADS)

Stanga, I. C.; Grozavu, A.

2012-04-01

Vulnerability assessment aims, most frequently, to emphasize internal fragility of a system comparing to a reference standard, to similar systems or in relation to a given hazard. Internal fragility, either biophysical or structural, may affect the capacity to predict, to prepare for, to cope with or to recover from a disaster. Thus, vulnerability is linked to resilience and adaptive capacity. From local level to global one, vulnerability factors and corresponding indicators are different and their significance must be tested and validated in a well-structured conceptual and methodological framework. In this paper, the authors aim to show the real vulnerability of rural settlements in Eastern Romania in a multi-level approach. The research area, Tutova Hills, counts about 3421 sq.km and more than 200.000 inhabitants in 421 villages characterized by deficient accessibility, lack of endowments, subsistential agriculture, high pressure on natural environment (especially on forest and soil resources), poverty and aging process of population. Factors that could influence the vulnerability of these rural settlements have been inventoried and assigned into groups through a cluster analysis: habitat and technical urban facilities, infrastructure, economical, social and demographical indicators, environment quality, management of emergency situations etc. Firstly, the main difficulty was to convert qualitative variable in quantitative indicators and to standardize all values to make possible mathematical and statistical processing of data. Secondly, the great variability of vulnerability factors, their different measuring units and their high amplitude of variation require different method of standardization in order to obtain values between zero (minimum vulnerability) and one (maximum vulnerability). Final vulnerability indicators were selected and integrated in a general scheme, according to their significance resulted from an appropriate factor analysis: linear and logistic regression, varimax rotation, multiple-criteria decision analysis, weight of evidence, multi-criteria evaluation method etc. The approach started from the local level which allows a functional and structural analysis and was progressively translated to an upper level and to a spatial analysis. The model shows that changing the level of analysis diminishes the functional significance of some indicators and increases the capacity of discretization in the case of others, highlighting the spatial and functional complexity of vulnerability.

Segmentation and quantification of subcellular structures in fluorescence microscopy images using Squassh.

PubMed

Rizk, Aurélien; Paul, Grégory; Incardona, Pietro; Bugarski, Milica; Mansouri, Maysam; Niemann, Axel; Ziegler, Urs; Berger, Philipp; Sbalzarini, Ivo F

2014-03-01

Detection and quantification of fluorescently labeled molecules in subcellular compartments is a key step in the analysis of many cell biological processes. Pixel-wise colocalization analyses, however, are not always suitable, because they do not provide object-specific information, and they are vulnerable to noise and background fluorescence. Here we present a versatile protocol for a method named 'Squassh' (segmentation and quantification of subcellular shapes), which is used for detecting, delineating and quantifying subcellular structures in fluorescence microscopy images. The workflow is implemented in freely available, user-friendly software. It works on both 2D and 3D images, accounts for the microscope optics and for uneven image background, computes cell masks and provides subpixel accuracy. The Squassh software enables both colocalization and shape analyses. The protocol can be applied in batch, on desktop computers or computer clusters, and it usually requires <1 min and <5 min for 2D and 3D images, respectively. Basic computer-user skills and some experience with fluorescence microscopy are recommended to successfully use the protocol.

Biomechanics of Atherosclerotic Coronary Plaque: Site, Stability and In Vivo Elasticity Modeling

PubMed Central

Ohayon, Jacques; Finet, Gérard; Le Floc’h, Simon; Cloutier, Guy; Gharib, Ahmed M.; Heroux, Julie; Pettigrew, Roderic I.

2016-01-01

Coronary atheroma develop in local sites that are widely variable among patients and are considerably variable in their vulnerability for rupture. This article summarizes studies conducted by our collaborative laboratories on predictive biomechanical modeling of coronary plaques. It aims to give insights into the role of biomechanics in the development and localization of atherosclerosis, the morphologic features that determine vulnerable plaque stability, and emerging in vivo imaging techniques that may detect and characterize vulnerable plaque. Composite biomechanical and hemodynamic factors that influence the actual site of development of plaques have been studied. Plaque vulnerability, in vivo, is more challenging to assess. Important steps have been made in defining the biomechanical factors that are predictive of plaque rupture and the likelihood of this occurring if characteristic features are known. A critical key in defining plaque vulnerability is the accurate quantification of both the morphology and the mechanical properties of the diseased arteries. Recently, an early IVUS based palpography technique developed to assess local strain, elasticity and mechanical instabilities has been successfully revisited and improved to account for complex plaque geometries. This is based on an initial best estimation of the plaque components’ contours, allowing subsequent iteration for elastic modulus assessment as a basis for plaque stability determination. The improved method has also been preliminarily evaluated in patients with successful histologic correlation. Further clinical evaluation and refinement are on the horizon. PMID:24043605

A conceptual framework towards more holistic freshwater conservation planning through incorporation of stream connectivity and thermal vulnerability

NASA Astrophysics Data System (ADS)

Ramulifho, P. A.; Rivers-Moore, N. A.; Dallas, H. F.; Foord, S. H.

2018-01-01

The thermal regime of rivers plays an important role in the overall health and composition of aquatic ecosystems, and together with flow, is recognised as one of the most influential abiotic drivers of aquatic ecosystem processes affecting species distribution. Changes in thermal conditions in aquatic systems are driven by on-going human-induced climate change, hydrological, regional and structural factors. Here, we quantified the impact of instream impoundments on the natural longitudinal connectivity and estimated thermal vulnerability of catchments based on the functional relationship between changing temperature and the profile gradient of rivers in the eastern portion of South Africa. We identified catchments that are most vulnerable to thermal stress based on cold-water adapted species' tolerance to thermal changes. More than half of all studied catchments include rivers that are relatively intact longitudinally, with notable exceptions being rivers in the central portion of the study area. Thermal condition of high elevation sites is more heavily impacted by impoundments and consequently thermal vulnerability of these sites are higher. Blephariceridae and Notonemouridae, the most thermophobic families, are likely to become locally threatened or extinct, in the absence of connectivity. The quantification of stream connectivity and vulnerability of organisms to thermal changes in river systems are important decision making tools for effective adaptive and holistic conservation planning strategies.

MRI-based methods for quantification of the cerebral metabolic rate of oxygen

PubMed Central

Rodgers, Zachary B; Detre, John A

2016-01-01

The brain depends almost entirely on oxidative metabolism to meet its significant energy requirements. As such, the cerebral metabolic rate of oxygen (CMRO2) represents a key measure of brain function. Quantification of CMRO2 has helped elucidate brain functional physiology and holds potential as a clinical tool for evaluating neurological disorders including stroke, brain tumors, Alzheimer’s disease, and obstructive sleep apnea. In recent years, a variety of magnetic resonance imaging (MRI)-based CMRO2 quantification methods have emerged. Unlike positron emission tomography – the current “gold standard” for measurement and mapping of CMRO2 – MRI is non-invasive, relatively inexpensive, and ubiquitously available in modern medical centers. All MRI-based CMRO2 methods are based on modeling the effect of paramagnetic deoxyhemoglobin on the magnetic resonance signal. The various methods can be classified in terms of the MRI contrast mechanism used to quantify CMRO2: T2*, T2′, T2, or magnetic susceptibility. This review article provides an overview of MRI-based CMRO2 quantification techniques. After a brief historical discussion motivating the need for improved CMRO2 methodology, current state-of-the-art MRI-based methods are critically appraised in terms of their respective tradeoffs between spatial resolution, temporal resolution, and robustness, all of critical importance given the spatially heterogeneous and temporally dynamic nature of brain energy requirements. PMID:27089912

Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi

PubMed Central

Montenegro, Diego; da Cunha, Ana Paula; Ladeia-Andrade, Simone; Vera, Mauricio; Pedroso, Marcel; Junqueira, Angela

2017-01-01

BACKGROUND Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per year on average. OBJECTIVES To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area undergoing domiciliary vector interruption of T. cruzi in Colombia. METHODS Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive assistance (GAIA) methods] and spatial statistics were performed on data from a socio-environmental questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and indicators of five determinants of the CD vector pathway were summarily defined, including: (1) house indicator (HI); (2) triatominae indicator (TI); (3) host/reservoir indicator (Ho/RoI); (4) ecotope indicator (EI); and (5) socio-cultural indicator (S-CI). FINDINGS Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T. cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors’ setting (border areas) on local values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector. CONCLUSIONS The study model proposed here is flexible and can be adapted to various eco-epidemiological profiles and is suitable for focusing anti-T. cruzi serological surveillance programs in vulnerable human populations. PMID:28953999

Dynamic Flood Vulnerability Mapping with Google Earth Engine

NASA Astrophysics Data System (ADS)

Tellman, B.; Kuhn, C.; Max, S. A.; Sullivan, J.

2015-12-01

Satellites capture the rate and character of environmental change from local to global levels, yet integrating these changes into flood exposure models can be cost or time prohibitive. We explore an approach to global flood modeling by leveraging satellite data with computing power in Google Earth Engine to dynamically map flood hazards. Our research harnesses satellite imagery in two main ways: first to generate a globally consistent flood inundation layer and second to dynamically model flood vulnerability. Accurate and relevant hazard maps rely on high quality observation data. Advances in publicly available spatial, spectral, and radar data together with cloud computing allow us to improve existing efforts to develop a comprehensive flood extent database to support model training and calibration. This talk will demonstrate the classification results of algorithms developed in Earth Engine designed to detect flood events by combining observations from MODIS, Landsat 8, and Sentinel-1. Our method to derive flood footprints increases the number, resolution, and precision of spatial observations for flood events both in the US, recorded in the NCDC (National Climatic Data Center) storm events database, and globally, as recorded events from the Colorado Flood Observatory database. This improved dataset can then be used to train machine learning models that relate spatial temporal flood observations to satellite derived spatial temporal predictor variables such as precipitation, antecedent soil moisture, and impervious surface. This modeling approach allows us to rapidly update models with each new flood observation, providing near real time vulnerability maps. We will share the water detection algorithms used with each satellite and discuss flood detection results with examples from Bihar, India and the state of New York. We will also demonstrate how these flood observations are used to train machine learning models and estimate flood exposure. The final stage of our comprehensive approach to flood vulnerability couples inundation extent with social data to determine which flood exposed communities have the greatest propensity for loss. Specifically, by linking model outputs to census derived social vulnerability estimates (Indian and US, respectively) to predict how many people are at risk.

Synchrotron-based X-ray fluorescence microscopy enables multiscale spatial visualization of ions involved in fungal lignocellulose deconstruction

Treesearch

Grant T. Kirker; Samuel Zelinka; Sophie-Charlotte Gleber; David Vine; Lydia Finney; Si Chen; Young Pyo Hong; Omar Uyarte; Stefan Vogt; Jody Jellison; Barry Goodell; Joseph E. Jakes

2017-01-01

The role of ions in the fungal decay process of lignocellulose biomaterials, and more broadly fungal metabolism, has implications for diverse research disciplines ranging from plant pathology and forest ecology, to carbon sequestration. Despite the importance of ions in fungal decay mechanisms, the spatial distribution and quantification of ions in lignocellulosic cell...

Extended generalized recurrence plot quantification of complex circular patterns

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2017-03-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing patterns, turbulent spatial plankton patterns, and fractals. Determinism is a central measure in this framework quantifying the level of regularity of spatial structures. We show by basic examples of fully regular patterns of different symmetries that this measure underestimates the orderliness of circular patterns resulting from rotational symmetries. We overcome this crucial problem by checking additional structural elements of the generalized recurrence plot which is demonstrated with the examples. Furthermore, we show the potential of the extended quantity of determinism applying it to more irregular circular patterns which are generated by the complex Ginzburg-Landau-equation and which can be often observed in real spatially extended dynamical systems. So, we are able to reconstruct the main separations of the system's parameter space analyzing single snapshots of the real part only, in contrast to the use of the original quantity. This ability of the proposed method promises also an improved description of other systems with complicated spatio-temporal dynamics typically occurring in fluid dynamics, climatology, biology, ecology, social sciences, etc.

Neighborhood Effects on Heat Deaths: Social and Environmental Predictors of Vulnerability in Maricopa County, Arizona

PubMed Central

Declet-Barreto, Juan H.; Stefanov, William L.; Petitti, Diana B.

2012-01-01

Background: Most heat-related deaths occur in cities, and future trends in global climate change and urbanization may amplify this trend. Understanding how neighborhoods affect heat mortality fills an important gap between studies of individual susceptibility to heat and broadly comparative studies of temperature–mortality relationships in cities. Objectives: We estimated neighborhood effects of population characteristics and built and natural environments on deaths due to heat exposure in Maricopa County, Arizona (2000–2008). Methods: We used 2000 U.S. Census data and remotely sensed vegetation and land surface temperature to construct indicators of neighborhood vulnerability and a geographic information system to map vulnerability and residential addresses of persons who died from heat exposure in 2,081 census block groups. Binary logistic regression and spatial analysis were used to associate deaths with neighborhoods. Results: Neighborhood scores on three factors—socioeconomic vulnerability, elderly/isolation, and unvegetated area—varied widely throughout the study area. The preferred model (based on fit and parsimony) for predicting the odds of one or more deaths from heat exposure within a census block group included the first two factors and surface temperature in residential neighborhoods, holding population size constant. Spatial analysis identified clusters of neighborhoods with the highest heat vulnerability scores. A large proportion of deaths occurred among people, including homeless persons, who lived in the inner cores of the largest cities and along an industrial corridor. Conclusions: Place-based indicators of vulnerability complement analyses of person-level heat risk factors. Surface temperature might be used in Maricopa County to identify the most heat-vulnerable neighborhoods, but more attention to the socioecological complexities of climate adaptation is needed. PMID:23164621

Review Article: A comparison of flood and earthquake vulnerability assessment indicators

NASA Astrophysics Data System (ADS)

de Ruiter, Marleen C.; Ward, Philip J.; Daniell, James E.; Aerts, Jeroen C. J. H.

2017-07-01

In a cross-disciplinary study, we carried out an extensive literature review to increase understanding of vulnerability indicators used in the disciplines of earthquake- and flood vulnerability assessments. We provide insights into potential improvements in both fields by identifying and comparing quantitative vulnerability indicators grouped into physical and social categories. Next, a selection of index- and curve-based vulnerability models that use these indicators are described, comparing several characteristics such as temporal and spatial aspects. Earthquake vulnerability methods traditionally have a strong focus on object-based physical attributes used in vulnerability curve-based models, while flood vulnerability studies focus more on indicators applied to aggregated land-use classes in curve-based models. In assessing the differences and similarities between indicators used in earthquake and flood vulnerability models, we only include models that separately assess either of the two hazard types. Flood vulnerability studies could be improved using approaches from earthquake studies, such as developing object-based physical vulnerability curve assessments and incorporating time-of-the-day-based building occupation patterns. Likewise, earthquake assessments could learn from flood studies by refining their selection of social vulnerability indicators. Based on the lessons obtained in this study, we recommend future studies for exploring risk assessment methodologies across different hazard types.

Assessment of floodplain vulnerability during extreme Mississippi River flood 2011

USGS Publications Warehouse

Goodwell, Allison E.; Zhu, Zhenduo; Dutta, Debsunder; Greenberg, Jonathan A.; Kumar, Praveen; Garcia, Marcelo H.; Rhoads, Bruce L.; Holmes, Robert R.; Parker, Gary; Berretta, David P.; Jacobson, Robert B.

2014-01-01

Regional change in the variability and magnitude of flooding could be a major consequence of future global climate change. Extreme floods have the capacity to rapidly transform landscapes and expose landscape vulnerabilities through highly variable spatial patterns of inundation, erosion, and deposition. We use the historic activation of the Birds Point-New Madrid Floodway during the Mississippi and Ohio River Flooding of 2011 as a scientifically unique stress experiment to analyze indicators of floodplain vulnerability. We use pre- and postflood airborne Light Detection and Ranging data sets to locate erosional and depositional hotspots over the 540 km2 agricultural Floodway. While riparian vegetation between the river and the main levee breach likely prevented widespread deposition, localized scour and deposition occurred near the levee breaches. Eroded gullies nearly 1 km in length were observed at a low ridge of a relict meander scar of the Mississippi River. Our flow modeling and spatial mapping analysis attributes this vulnerability to a combination of erodible soils, flow acceleration associated with legacy fluvial landforms, and a lack of woody vegetation to anchor soil and enhance flow resistance. Results from this study could guide future mitigation and adaptation measures in cases of extreme flooding.

Assessment of floodplain vulnerability during extreme Mississippi River flood 2011.

PubMed

Goodwell, Allison E; Zhu, Zhenduo; Dutta, Debsunder; Greenberg, Jonathan A; Kumar, Praveen; Garcia, Marcelo H; Rhoads, Bruce L; Holmes, Robert R; Parker, Gary; Berretta, David P; Jacobson, Robert B

2014-01-01

Regional change in the variability and magnitude of flooding could be a major consequence of future global climate change. Extreme floods have the capacity to rapidly transform landscapes and expose landscape vulnerabilities through highly variable spatial patterns of inundation, erosion, and deposition. We use the historic activation of the Birds Point-New Madrid Floodway during the Mississippi and Ohio River Flooding of 2011 as a scientifically unique stress experiment to analyze indicators of floodplain vulnerability. We use pre- and postflood airborne Light Detection and Ranging data sets to locate erosional and depositional hotspots over the 540 km(2) agricultural Floodway. While riparian vegetation between the river and the main levee breach likely prevented widespread deposition, localized scour and deposition occurred near the levee breaches. Eroded gullies nearly 1 km in length were observed at a low ridge of a relict meander scar of the Mississippi River. Our flow modeling and spatial mapping analysis attributes this vulnerability to a combination of erodible soils, flow acceleration associated with legacy fluvial landforms, and a lack of woody vegetation to anchor soil and enhance flow resistance. Results from this study could guide future mitigation and adaptation measures in cases of extreme flooding.

Economic vulnerability of timber resources to forest fires.

PubMed

y Silva, Francisco Rodríguez; Molina, Juan Ramón; González-Cabán, Armando; Machuca, Miguel Ángel Herrera

2012-06-15

The temporal-spatial planning of activities for a territorial fire management program requires knowing the value of forest ecosystems. In this paper we extend to and apply the economic valuation principle to the concept of economic vulnerability and present a methodology for the economic valuation of the forest production ecosystems. The forest vulnerability is analyzed from criteria intrinsically associated to the forest characterization, and to the potential behavior of surface fires. Integrating a mapping process of fire potential and analytical valuation algorithms facilitates the implementation of fire prevention planning. The availability of cartography of economic vulnerability of the forest ecosystems is fundamental for budget optimization, and to help in the decision making process. Published by Elsevier Ltd.

The classification and assessment of vulnerability of man-land system of oasis city in arid area

NASA Astrophysics Data System (ADS)

Gao, Chao; Lei, Jun; Jin, Fengjun

2013-12-01

Oasis city system is the center of the man-land relationship in arid area and it is the most influential spatial and temporal multiple dynamic system. Oasis city system is not only the largest area where artificial disturbances occur at a regional scale but also the most concentrated area of human activity in arid area. In this study, we developed an applicable and convenient method to assess vulnerability of man-land system of oasis cities with vulnerability indicator system, respectively evaluating the sensitivity, adaptability and vulnerability of the eco-environment system, the economic system and the social system. The results showed that the sensitivity and vulnerability of oasis cities in Xinjiang, China have significant differences while their adaptability does little. In order to find the inherent differences in the vulnerability of oasis cities, triangle methodology has been adopted to divide Xinjiang oasis cities into five types. Some adaptive developing policies specific for individual cities are also proposed based on their vulnerability type and constraining factors.

USE OF REVA'S WEB-BASED ENVIRONMENTAL DECISION TOOLKIT (EDT) TO ASSESS VULNERABILITY TO MERCURY ACROSS THE UNITED STATES

EPA Science Inventory

The problem of assessing risk from mercury across the nation is extremely complex involving integration of 1) our understanding of the methylation process in ecosystems, 2) the identification and spatial distribution of sensitive populations, and 3) the spatial pattern of mercury...

INTEGRATION OF SPATIAL DATA: EVALUATION OF METHODS BASED ON DATA ISSUES AND ASSESSMENT QUESTIONS

EPA Science Inventory

EPA's Regional Vulnerability Assessment (ReVA) Program has focused initially on the synthesis of existing data. We have used the same set of spatial data and synthesized these data using a total of 11 existing and newly developed integration methods. These methods were evaluated ...

SPATIAL PATTERN OF FUTURE VULNERABILITY OF STREAM EUTROPHICATION IN THE MID-ATLANTIC REGION OF THE UNITED STATES

EPA Science Inventory

Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the d...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toro, Javier, E-mail: jjtoroca@unal.edu.co; Requena, Ignacio, E-mail: requena@decsai.ugr.es; Duarte, Oscar, E-mail: ogduartev@unal.edu.co

In environmental impact assessment, qualitative methods are used because they are versatile and easy to apply. This methodology is based on the evaluation of the strength of the impact by grading a series of qualitative attributes that can be manipulated by the evaluator. The results thus obtained are not objective, and all too often impacts are eliminated that should be mitigated with corrective measures. However, qualitative methodology can be improved if the calculation of Impact Importance is based on the characteristics of environmental factors and project activities instead on indicators assessed by evaluators. In this sense, this paper proposes themore » inclusion of the vulnerability of environmental factors and the potential environmental impact of project activities. For this purpose, the study described in this paper defined Total Impact Importance and specified a quantification procedure. The results obtained in the case study of oil drilling in Colombia reflect greater objectivity in the evaluation of impacts as well as a positive correlation between impact values, the environmental characteristics at and near the project location, and the technical characteristics of project activities. -- Highlights: • Concept of vulnerability has been used to calculate the importance impact assessment. • This paper defined Total Impact Importance and specified a quantification procedure. • The method includes the characteristics of environmental and project activities. • The application has shown greater objectivity in the evaluation of impacts. • Better correlation between impact values, environment and the project has been shown.« less

A new multi-disciplinary model for the assessment and reduction of volcanic risk: the example of the island of Vulcano, Italy

NASA Astrophysics Data System (ADS)

Simicevic, Aleksandra; Bonadonna, Costanza; di Traglia, Federico; Rosi, Mauro

2010-05-01

Volcanic eruptions are accompanied by numerous hazards which pose short- and long-term threats to people and property. Recent experiences have shown that successful responses to hazard events correlate strongly with the degree to which proactive policies of risk reduction are already in place before an eruption occurs. Effective proactive risk-reduction strategies require contributions from numerous disciplines. A volcanic eruption is not a hazard, per se, but rather an event capable of producing a variety of hazards (e.g. earthquakes, pyroclastic density currents, lava flows, tephra fall, lahars, landslides, gas release, and tsunamis) that can affect the built environment in a variety of ways, over different time scales and with different degrees of intensity. Our proposed model for the assessment and mitigation of exposure-based volcanic risk is mainly based on the compilation of three types of maps: hazard maps, hazard-specific vulnerability maps and exposure-based risk maps. Hazard maps identify the spatial distribution of individual volcanic hazard and it includes both event analysis and impact analysis. Hazard-specific vulnerability maps represent the systematic evaluation of physical vulnerability of the built environment to a range of volcanic phenomena, i.e. spatial distribution of buildings vulnerable to a given hazard based on the analysis of selected building elements. Buildings are classified on the basis of their major components that are relevant for different volcanic hazards, their strength, their construction materials and are defined taking into account the potential damage that each group of building elements (e.g. walls, roof, load-bearing structure) will suffer under a volcanic hazard. All those factors are enumerated in a checklist and are used for the building survey. Hazard-specific vulnerability maps are then overlapped with hazard maps in order to compile exposure-based risk maps and so quantify the potential damage. Such quantification is the starting point of the identification of suitable mitigation measures which will be analyzed through a cost-benefit analysis to assess their financial feasibility. Information about public networks is also recorded in order to give an overall idea of the built environment condition of the island. The vulnerability assessment of the technical systems describes the potential damages that could stress systems like electricity supply, water distribution, communication networks or transport systems. These damages can also be described as function disruption of the system. The important aspect is not only the physical capacity of a system to resist, but also its capacity to continue functioning. The model will be tested on the island of Vulcano in southern Italy. Vulcano is characterized by clear signs of volcanic unrest and is the type locality for a deadly style of eruption. The main active system of Vulcano Island (La Fossa cone) is known to produce a variety of eruption styles and intensities, each posing their own hazards and threats. Six different hazard scenarios have been identified based on a detailed stratigraphic work. The urbanization on Vulcano took place in the 1980s with no real planning and its population mostly subsists on tourism. Our preliminary results show that Vulcano is not characterized by a great variability of architectural typologies and construction materials. Three main types of buildings are present (masonry with concrete frame, masonry with manufactured stone units, masonry with hollow clay bricks) and no statistically significant trends were found between physical and morphological characteristics. The recent signs of volcanic unrest combined with a complex vulnerability of the island due to an uncontrolled urban development and a significant seasonal variation of the exposed population in summer months result in a high volcanic risk. As a result, Vulcano represents the ideal environment to test a multi-hazard based risk model and to study the transition between micro (building) and macro (urban environment) scale of analysis, which is still an unexplored field in the study of volcanic risk. Different levels of vulnerability need to be analyzed in order to increase the level of preparedness, plan a potential evacuation, manage a potential volcanic crisis and assess the best mitigation measures to put in place and reduce the volcanic risk.

Eco-environmental vulnerability assessment for large drinking water resource: a case study of Qiandao Lake Area, China

NASA Astrophysics Data System (ADS)

Gu, Qing; Li, Jun; Deng, Jinsong; Lin, Yi; Ma, Ligang; Wu, Chaofan; Wang, Ke; Hong, Yang

2015-09-01

The Qiandao Lake Area (QLA) is of great significance in terms of drinking water supply in East Coast China as well as a nationally renowned tourist attraction. A series of laws and regulations regarding the QLA environment have been enacted and implemented throughout the past decade with the aim of negating the harmful effects associated with expanding urbanization and industrialization. In this research, an assessment framework was developed to analyze the eco-environmental vulnerability of the QLA from 1990-2010 by integrating fuzzy analytic hierarchy process (FAHP) and geographical information systems (GIS) in an attempt to gain insights into the status quo of the QLA so as to review and evaluate the effectiveness of the related policies. After processing and analyzing the temporal and spatial variation of eco-environmental vulnerability and major environmental issues in the QLA, we found that the state of eco-environmental vulnerability of the QLA was acceptable, though a moderate deterioration was detected during the study period. Furthermore, analysis of the combination of vulnerability and water quality indicated that the water quality showed signs of declination, though the overall status remained satisfactory. It was hence concluded that the collective protection and treatment actions were effective over the study period, whereas immediately stricter measures would be required for protecting the drinking water quality from domestic sewage and industrial wastewater. Finally, the spatial variation of the eco-environmental vulnerability assessment also implied that specifically more targeted measures should be adopted in respective regions for long-term sustainable development of the QLA.

Assessing Risks from Cyclones for Human Lives and Livelihoods in the Coastal Region of Bangladesh

PubMed Central

Khan, Amanat Ullah; Kervyn, Matthieu

2017-01-01

As a disaster prone country, Bangladesh is regularly hit by natural hazards, including devastating cyclones, such as in 1970, 1991 and 2007. Although the number of cyclones’ fatalities reduced from 0.3 million in 1970 to a few thousand or fewer in recent events, loss of lives and impact on livelihoods remains a concern. It depends on the meteorological characteristics of cyclone and the general vulnerability and capacity of the exposed population. In that perspective, a spatially explicit risk assessment is an essential step towards targeted disaster risk reduction. This study aims at analyzing the spatial variation of the different factors contributing to the risk for coastal communities at regional scale, including the distribution of the hazards, exposure, vulnerability and capacity. An exploratory factor analysis method is used to map vulnerability contrasts between local administrative units. Indexing and ranking using geospatial techniques are used to produce maps of exposure, hazard, vulnerability, capacities and risk. Results show that vulnerable populations and exposed areas are distributed along the land sea boundary, islands and major inland rivers. The hazard, assessed from the density of historical cyclone paths, is highest in the southwestern part of the coast. Whereas cyclones shelters are shown to properly serve the most vulnerable populations as priority evacuation centers, the overall pattern of capacity accounting for building quality and road network shows a more complex pattern. Resultant risk maps also provide a reasonable basis from which to take further structural measures to minimize loss of lives in the upcoming cyclones. PMID:28757550

On the Utilization of Ice Flow Models and Uncertainty Quantification to Interpret the Impact of Surface Radiation Budget Errors on Estimates of Greenland Ice Sheet Surface Mass Balance and Regional Estimates of Mass Balance

NASA Astrophysics Data System (ADS)

Schlegel, N.; Larour, E. Y.; Gardner, A. S.; Lang, C.; Miller, C. E.; van den Broeke, M. R.

2016-12-01

How Greenland ice flow may respond to future increases in surface runoff and to increases in the frequency of extreme melt events is unclear, as it requires detailed comprehension of Greenland surface climate and the ice sheet's sensitivity to associated uncertainties. With established uncertainty quantification tools run within the framework of Ice Sheet System Model (ISSM), we conduct decadal-scale forward modeling experiments to 1) quantify the spatial resolution needed to effectively force distinct components of the surface radiation budget, and subsequently surface mass balance (SMB), in various regions of the ice sheet and 2) determine the dynamic response of Greenland ice flow to variations in components of the net radiation budget. The Glacier Energy and Mass Balance (GEMB) software is a column surface model (1-D) that has recently been embedded as a module within ISSM. Using the ISSM-GEMB framework, we perform sensitivity analyses to determine how perturbations in various components of the surface radiation budget affect model output; these model experiments allow us predict where and on what spatial scale the ice sheet is likely to dynamically respond to changes in these parameters. Preliminary results suggest that SMB should be forced at at least a resolution of 23 km to properly capture dynamic ice response. In addition, Monte-Carlo style sampling analyses reveals that the areas with the largest uncertainty in mass flux are located near the equilibrium line altitude (ELA), upstream of major outlet glaciers in the North and West of the ice sheet. Sensitivity analysis indicates that these areas are also the most vulnerable on the ice sheet to persistent, far-field shifts in SMB, suggesting that continued warming, and upstream shift in the ELA, are likely to result in increased velocities, and consequentially SMB-induced thinning upstream of major outlet glaciers. Here, we extend our investigation to consider various components of the surface radiation budget separately, in order to determine how and where errors in these fields may independently impact ice flow. This work was performed at the California Institute of Technology's Jet Propulsion Laboratory under a contract with the National Aeronautics and Space Administration's Cryosphere and Interdisciplinary Research in Earth Science Programs.

Enhancing the relevance of new scenarios for climate change impacts, adaptation and vulnerability research

NASA Astrophysics Data System (ADS)

van Ruijven, B. J.

2013-12-01

Over the past three decades, scenario analyses have occupied a central role in assessments of the potential impacts of climate change on natural and human systems at different scales during the 21st century. Here, we discuss the role and relevance of new scenarios using shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs) for climate change impacts, adaptation, and vulnerability (IAV) research. It first provides an overview of uses of social-environmental scenarios in IAV studies and identifies the main shortcomings of earlier such scenarios. Second, the paper elaborates on two aspects of new scenarios needing to be improved in order to enhance their usefulness for IAV studies: the ability to work coherently across spatial scales and adding indicators of importance to projections of vulnerability and adaptive capacity in addition to standard indicators of population and gross domestic product. This paper presents a research agenda to add income distribution, spatial population, human health projections, and governance indicators to the new scenarios.

A socioeconomic profile of vulnerable land to desertification in Italy.

PubMed

Salvati, Luca

2014-01-01

Climate changes, soil vulnerability, loss in biodiversity, and growing human pressure are threatening Mediterranean-type ecosystems which are increasingly considered as a desertification hotspot. In this region, land vulnerability to desertification strongly depends on the interplay between natural and anthropogenic factors. The present study proposes a multivariate exploratory analysis of the relationship between the spatial distribution of land vulnerability to desertification and the socioeconomic contexts found in three geographical divisions of Italy (north, center and south) based on statistical indicators. A total of 111 indicators describing different themes (demography, human settlements, labor market and human capital, rural development, income and wealth) were used to discriminate vulnerable from non-vulnerable areas. The resulting socioeconomic profile of vulnerable areas in northern and southern Italy diverged significantly, the importance of demographic and economic indicators being higher in southern Italy than in northern Italy. On the contrary, human settlement indicators were found more important to discriminate vulnerable and non-vulnerable areas in northern Italy, suggesting a role for peri-urbanization in shaping the future vulnerable areas. An in-depth knowledge of the socioeconomic characteristics of vulnerable land may contribute to scenarios' modeling and the development of more effective policies to combat desertification. © 2013 Elsevier B.V. All rights reserved.

Mapping permafrost change hot-spots with Landsat time-series

NASA Astrophysics Data System (ADS)

Grosse, G.; Nitze, I.

2016-12-01

Recent and projected future climate warming strongly affects permafrost stability over large parts of the terrestrial Arctic with local, regional and global scale consequences. The monitoring and quantification of permafrost and associated land surface changes in these areas is crucial for the analysis of hydrological and biogeochemical cycles as well as vegetation and ecosystem dynamics. However, detailed knowledge of the spatial distribution and the temporal dynamics of these processes is scarce and likely key locations of permafrost landscape dynamics may remain unnoticed. As part of the ERC funded PETA-CARB and ESA GlobPermafrost projects, we developed an automated processing chain based on data from the entire Landsat archive (excluding MSS) for the detection of permafrost change related processes and hotspots. The automated method enables us to analyze thousands of Landsat scenes, which allows for a multi-scaled spatio-temporal analysis at 30 meter spatial resolution. All necessary processing steps are carried out automatically with minimal user interaction, including data extraction, masking, reprojection, subsetting, data stacking, and calculation of multi-spectral indices. These indices, e.g. Landsat Tasseled Cap and NDVI among others, are used as proxies for land surface conditions, such as vegetation status, moisture or albedo. Finally, a robust trend analysis is applied to each multi-spectral index and each pixel over the entire observation period of up to 30 years from 1985 to 2015, depending on data availability. Large transects of around 2 million km² across different permafrost types in Siberia and North America have been processed. Permafrost related or influencing landscape dynamics were detected within the trend analysis, including thermokarst lake dynamics, fires, thaw slumps, and coastal dynamics. The produced datasets will be distributed to the community as part of the ERC PETA-CARB and ESA GlobPermafrost projects. Users are encouraged to provide feedback and ground truth data for a continuous improvement of our methodology and datasets, which will lead to a better understanding of the spatial and temporal distribution of changes within the vulnerable permafrost zone.

Landscape-level movement patterns by lions in western Serengeti: comparing the influence of inter-specific competitors, habitat attributes and prey availability.

PubMed

Kittle, Andrew M; Bukombe, John K; Sinclair, Anthony R E; Mduma, Simon A R; Fryxell, John M

2016-01-01

Where apex predators move on the landscape influences ecosystem structure and function and is therefore key to effective landscape-level management and species-specific conservation. However the factors underlying predator distribution patterns within functional ecosystems are poorly understood. Predator movement should be sensitive to the spatial patterns of inter-specific competitors, spatial variation in prey density, and landscape attributes that increase individual prey vulnerability. We investigated the relative role of these fundamental factors on seasonal resource utilization by a globally endangered apex carnivore, the African lion (Panthera leo) in Tanzania's Serengeti National Park. Lion space use was represented by novel landscape-level, modified utilization distributions (termed "localized density distributions") created from telemetry relocations of individual lions from multiple neighbouring prides. Spatial patterns of inter-specific competitors were similarly determined from telemetry re-locations of spotted hyenas (Crocuta crocuta), this system's primary competitor for lions; prey distribution was derived from 18 months of detailed census data; and remote sensing data was used to represent relevant habitat attributes. Lion space use was consistently influenced by landscape attributes that increase individual prey vulnerability to predation. Wet season activity, when available prey were scarce, was concentrated near embankments, which provide ambush opportunities, and dry season activity, when available prey were abundant, near remaining water sources where prey occurrence is predictable. Lion space use patterns were positively associated with areas of high prey biomass, but only in the prey abundant dry season. Finally, at the broad scale of this analysis, lion and hyena space use was positively correlated in the comparatively prey-rich dry season and unrelated in the wet season, suggesting lion movement was unconstrained by the spatial patterns of their main inter-specific competitors. The availability of potential prey and vulnerability of that prey to predation both motivate lion movement decisions, with their relative importance apparently mediated by overall prey abundance. With practical and theoretical implications, these results suggest that while top carnivores are consistently cognizant of how landscape features influence individual prey vulnerability, they also adopt a flexible approach to range use by adjusting spatial behaviour according to fluctuations in local prey abundance.

Climate change and waterborne diarrhoea in northern India: impacts and adaptation strategies.

PubMed

Moors, Eddy; Singh, Tanya; Siderius, Christian; Balakrishnan, Sneha; Mishra, Arabinda

2013-12-01

Although several studies show the vulnerability of human health to climate change, a clear comprehensive quantification of the increased health risks attributable to climate change is lacking. Even more complicated are assessments of adaptation measures for this sector. We discuss the impact of climate change on diarrhoea as a representative of a waterborne infectious disease affecting human health in the Ganges basin of northern India. A conceptual framework is presented for climate exposure response relationships based on studies from different countries, as empirical studies and appropriate epidemiological data sets for India are lacking. Four climate variables are included: temperature, increased/extreme precipitation, decreased precipitation/droughts and relative humidity. Applying the conceptual framework to the latest regional climate projections for northern India shows increases between present and future (2040s), varying spatially from no change to an increase of 21% in diarrhoea incidences, with 13.1% increase on average for the Ganges basin. We discuss three types of measures against diarrhoeal disease: reactive actions, preventive actions and national policy options. Preventive actions have the potential to counterbalance this expected increase. However, given the limited progress in reducing incidences over the past decade consorted actions and effective implementation and integration of existing policies are needed. © 2013.

Quantitative imaging reveals heterogeneous growth dynamics and treatment-dependent residual tumor distributions in a three-dimensional ovarian cancer model

NASA Astrophysics Data System (ADS)

Celli, Jonathan P.; Rizvi, Imran; Evans, Conor L.; Abu-Yousif, Adnan O.; Hasan, Tayyaba

2010-09-01

Three-dimensional tumor models have emerged as valuable in vitro research tools, though the power of such systems as quantitative reporters of tumor growth and treatment response has not been adequately explored. We introduce an approach combining a 3-D model of disseminated ovarian cancer with high-throughput processing of image data for quantification of growth characteristics and cytotoxic response. We developed custom MATLAB routines to analyze longitudinally acquired dark-field microscopy images containing thousands of 3-D nodules. These data reveal a reproducible bimodal log-normal size distribution. Growth behavior is driven by migration and assembly, causing an exponential decay in spatial density concomitant with increasing mean size. At day 10, cultures are treated with either carboplatin or photodynamic therapy (PDT). We quantify size-dependent cytotoxic response for each treatment on a nodule by nodule basis using automated segmentation combined with ratiometric batch-processing of calcein and ethidium bromide fluorescence intensity data (indicating live and dead cells, respectively). Both treatments reduce viability, though carboplatin leaves micronodules largely structurally intact with a size distribution similar to untreated cultures. In contrast, PDT treatment disrupts micronodular structure, causing punctate regions of toxicity, shifting the distribution toward smaller sizes, and potentially increasing vulnerability to subsequent chemotherapeutic treatment.

Projected tree species redistribution under climate change: Implications for ecosystem vulnerability across protected areas in the eastern United States

Treesearch

Scott G. Zolkos; Patrick Jantz; Tina Cormier; Louis R. Iverson; Daniel W. McKenney; Scott J. Goetz

2015-01-01

The degree to which tree species will shift in response to climate change is uncertain yet critical to understand for assessing ecosystem vulnerability. We analyze results from recent studies that model potential tree species habitat across the eastern United States during the coming century. Our goals were to quantify and spatially analyze habitat projections and...

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2017-12-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2018-06-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

An atmospheric vulnerability assessment framework for environment management and protection based on CAMx.

PubMed

Zhang, Yang; Shen, Jing; Li, Yu

2018-02-01

This paper presents an atmospheric vulnerability assessment framework based on CAMx that should be helpful to assess potential impacts of changes in human, atmospheric environment, and social economic elements of atmospheric vulnerability. It is also a useful and effective tool that can provide policy-guidance for environmental protection and management to reduce the atmospheric vulnerability. The developed framework was applied to evaluate the atmospheric environment vulnerability of 13 cities in the Beijing-Tianjin-Hebei (BTH) region for verification. The results indicated that regional disparity of the atmospheric vulnerability existed in the study site. More specifically, the central and southern regions show more atmospheric environment vulnerability than the northern regions. The impact factors of atmospheric environment vulnerability in the BTH region mainly derived from increasing population press, frequently unfavorable meteorological conditions, extensive economic growth of secondary industry, increased environmental pollution, and accelerating population aging. The framework shown in this paper is an interpretative and heuristic tool for a better understanding of atmospheric vulnerability. This framework can also be replicated at different spatial and temporal scales using context-specific datasets to straightly support environmental managers with decision-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk identification of agricultural drought for sustainable Agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.; Tarquis, A. M.

2014-09-01

Drought is considered as one of the major natural hazards with a significant impact on agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the vegetation health index (VHI). The computation of VHI is based on satellite data of temperature and the normalized difference vegetation index (NDVI). The spatiotemporal features of drought, which are extracted from VHI, are areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of the National Oceanic and Atmospheric Administration/advanced very high resolution radiometer (NOAA/AVHRR) satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season, with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than those of mild to moderate drought throughout the warm season. Finally, the areas with diachronic drought persistence can be located. Drought early warning is developed using empirical functional relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought classes, respectively. The two fitted curves offer a forecasting tool on a monthly basis from May to October. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential. The adopted remote-sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

Co-Creating theories and research design for an interdisciplinary project dealing with capacity building for people with migration background in Austria

NASA Astrophysics Data System (ADS)

Weber, Karin; Tscharner, Susanna; Stickler, Therese; Fuchs, Britta; Damyanovic, Doris; Hübl, Johannes

2017-04-01

Understanding spatial and social aspects of vulnerability is of growing importance in the context of climate change and natural hazards. The interplay of structural factors, socio-demographic aspects, current risk communication strategies, spatial planning instruments and related processes and the current spatial and environmental situation, including hazards and hazard zones, geographical locations, building and settlement types, contributing to people`s vulnerabilities needs to be analysed and understood to reduce vulnerability and to foster resilience. The project "CCCapMig" (Climate change and capacity building for people with migration background in Austria) aims at linking spatial and technical, as well as organisational and social aspects of climate change and natural hazards. This paper focuses on the co-creation of the theoretical framework and concepts and outlines the research design for this interdisciplinary cross-analysis of several case studies in rural Austria. The project is designed as an inter- and transdisciplinary survey and brings together engineering sciences, spatial sciences and social sciences. Reflecting the interdisciplinary approach, a theoretical framework was developed that refers to a combination of both theories and frameworks from vulnerability research, theories of risk perception and spatial theories and methods like the Sustainable Livelihoods Framework, the Protection-Motivation Theory and Landscape-Planning Theories: The "Sustainable Livelihoods Framework" adapted (by FA0) for disaster risk management offers an analytical framework to understand the emergence of vulnerabilities from the perspective of people`s livelihoods on individual and community level. It includes human, social, natural, physical and financial aspects and the role of institutions, policies and legal rights in reducing or increasing exposure to disaster risk and coping capacities. Additionally, theories on risk perception, especially Protection-Motivation Theory, developed by social sciences, will be used as assessment frame to understand people`s flood damage mitigation behaviour. Furthermore, spatial theories and landscape planning approaches (like an everyday, evidence-based approach) are combined with theories from social sciences reflecting the interdisciplinary approach of this project that has become standard in studies on disaster and climate change. This theoretical approach was developed through a collaborative research at the beginning of the research design in order to a) develop further and test existing concepts, b) to fine-tune the proposed method setting, c) to foster common understanding of theories and methods within the interdisciplinary research team. In general, the research process is characterised by critical theory and brings in reflective elements, allowing feedback circles between methods and theories. End-users and decision-makers will be integral partners, ensuring that feasibility of the recommendations and guidelines will be guaranteed. Consequently, the methods of data collection in this project reflect the results of the critical discussion of the theoretical frameworks and combine methods of social sciences: interviews with inhabitants living in hazard zones, detailed surveys of families, focus group discussions, and expert interviews with local and regional stakeholders involved in disaster risk management. In addition to that, structural factors, demographic data, current risk communication strategies, legal instruments and related processes and the current spatial and environmental situation (including hazards and hazard zones, geographical locations, building and settlement types) are analysed.

Vulnerability of Forests in India: A National Scale Assessment.

PubMed

Sharma, Jagmohan; Upgupta, Sujata; Jayaraman, Mathangi; Chaturvedi, Rajiv Kumar; Bala, Govindswamy; Ravindranath, N H

2017-09-01

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience.

Vulnerability of Forests in India: A National Scale Assessment

NASA Astrophysics Data System (ADS)

Sharma, Jagmohan; Upgupta, Sujata; Jayaraman, Mathangi; Chaturvedi, Rajiv Kumar; Bala, Govindswamy; Ravindranath, N. H.

2017-09-01

Forests are subjected to stress from climatic and non-climatic sources. In this study, we have reported the results of inherent, as well as climate change driven vulnerability assessments for Indian forests. To assess inherent vulnerability of forests under current climate, we have used four indicators, namely biological richness, disturbance index, canopy cover, and slope. The assessment is presented as spatial profile of inherent vulnerability in low, medium, high and very high vulnerability classes. Fourty percent forest grid points in India show high or very high inherent vulnerability. Plantation forests show higher inherent vulnerability than natural forests. We assess the climate change driven vulnerability by combining the results of inherent vulnerability assessment with the climate change impact projections simulated by the Integrated Biosphere Simulator dynamic global vegetation model. While 46% forest grid points show high, very high, or extremely high vulnerability under future climate in the short term (2030s) under both representative concentration pathways 4.5 and 8.5, such grid points are 49 and 54%, respectively, in the long term (2080s). Generally, forests in the higher rainfall zones show lower vulnerability as compared to drier forests under future climate. Minimizing anthropogenic disturbance and conserving biodiversity can potentially reduce forest vulnerability under climate change. For disturbed forests and plantations, adaptive management aimed at forest restoration is necessary to build long-term resilience.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia.

PubMed

Dorji, Passang; Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit.

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

PubMed Central

Fearns, Peter

2017-01-01

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor’s radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit. PMID:28380059

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dobson, Ian; Hiskens, Ian; Linderoth, Jeffrey

Building on models of electrical power systems, and on powerful mathematical techniques including optimization, model predictive control, and simluation, this project investigated important issues related to the stable operation of power grids. A topic of particular focus was cascading failures of the power grid: simulation, quantification, mitigation, and control. We also analyzed the vulnerability of networks to component failures, and the design of networks that are responsive to and robust to such failures. Numerous other related topics were investigated, including energy hubs and cascading stall of induction machines

Small-area spatiotemporal analysis of heatwave impacts on elderly mortality in Paris: A cluster analysis approach.

PubMed

Benmarhnia, Tarik; Kihal-Talantikite, Wahida; Ragettli, Martina S; Deguen, Séverine

2017-08-15

Heat-waves have a substantial public health burden. Understanding spatial heterogeneity at a fine spatial scale in relation to heat and related mortality is central to target interventions towards vulnerable communities. To determine the spatial variability of heat-wave-related mortality risk among elderly in Paris, France at the census block level. We also aimed to assess area-level social and environmental determinants of high mortality risk within Paris. We used daily mortality data from 2004 to 2009 among people aged >65 at the French census block level within Paris. We used two heat wave days' definitions that were compared to non-heat wave days. A Bernoulli cluster analysis method was applied to identify high risk clusters of mortality during heat waves. We performed random effects meta-regression analyses to investigate factors associated with the magnitude of the mortality risk. The spatial approach revealed a spatial aggregation of death cases during heat wave days. We found that small scale chronic PM 10 exposure was associated with a 0.02 (95% CI: 0.001; 0.045) increase of the risk of dying during a heat wave episode. We also found a positive association with the percentage of foreigners and the percentage of labor force, while the proportion of elderly people living in the neighborhood was negatively associated. We also found that green space density had a protective effect and inversely that the density of constructed feature increased the risk of dying during a heat wave episode. We showed that a spatial variation in terms of heat-related vulnerability exists within Paris and that it can be explained by some contextual factors. This study can be useful for designing interventions targeting more vulnerable areas and reduce the burden of heat waves. Copyright © 2017 Elsevier B.V. All rights reserved.

Vulnerability mapping as a tool to manage the environmental impacts of oil and gas extraction.

PubMed

Esterhuyse, Surina; Sokolic, Frank; Redelinghuys, Nola; Avenant, Marinda; Kijko, Andrzej; Glazewski, Jan; Plit, Lisa; Kemp, Marthie; Smit, Ansie; Vos, A Tascha; von Maltitz, Michael J

2017-11-01

Various biophysical and socio-economic impacts may be associated with unconventional oil and gas (UOG) extraction. A vulnerability map may assist governments during environmental assessments, spatial planning and the regulation of UOG extraction, as well as decision-making around UOG extraction in fragile areas. A regional interactive vulnerability map was developed for UOG extraction in South Africa. This map covers groundwater, surface water, vegetation, socio-economics and seismicity as mapping themes, based on impacts that may emanate from UOG extraction. The mapping themes were developed using a normative approach, where expert input during the identification and classification of vulnerability indicators may increase the acceptability of the resultant map. This article describes the development of the interactive vulnerability map for South Africa, where UOG extraction is not yet allowed and where regulations are still being developed to manage this activity. The importance and policy implications of using vulnerability maps for managing UOG extraction impacts in countries where UOG extraction is planned are highlighted in this article.

Spatial modeling of environmental vulnerability of marine finfish aquaculture using GIS-based neuro-fuzzy techniques.

PubMed

Navas, Juan Moreno; Telfer, Trevor C; Ross, Lindsay G

2011-08-01

Combining GIS with neuro-fuzzy modeling has the advantage that expert scientific knowledge in coastal aquaculture activities can be incorporated into a geospatial model to classify areas particularly vulnerable to pollutants. Data on the physical environment and its suitability for aquaculture in an Irish fjard, which is host to a number of different aquaculture activities, were derived from a three-dimensional hydrodynamic and GIS models. Subsequent incorporation into environmental vulnerability models, based on neuro-fuzzy techniques, highlighted localities particularly vulnerable to aquaculture development. The models produced an overall classification accuracy of 85.71%, with a Kappa coefficient of agreement of 81%, and were sensitive to different input parameters. A statistical comparison between vulnerability scores and nitrogen concentrations in sediment associated with salmon cages showed good correlation. Neuro-fuzzy techniques within GIS modeling classify vulnerability of coastal regions appropriately and have a role in policy decisions for aquaculture site selection. Copyright © 2011 Elsevier Ltd. All rights reserved.

Vulnerability mapping as a tool to manage the environmental impacts of oil and gas extraction

PubMed Central

Sokolic, Frank; Redelinghuys, Nola; Avenant, Marinda; Kijko, Andrzej; Glazewski, Jan; Plit, Lisa; Kemp, Marthie; Smit, Ansie; Vos, A. Tascha; von Maltitz, Michael J.

2017-01-01

Various biophysical and socio-economic impacts may be associated with unconventional oil and gas (UOG) extraction. A vulnerability map may assist governments during environmental assessments, spatial planning and the regulation of UOG extraction, as well as decision-making around UOG extraction in fragile areas. A regional interactive vulnerability map was developed for UOG extraction in South Africa. This map covers groundwater, surface water, vegetation, socio-economics and seismicity as mapping themes, based on impacts that may emanate from UOG extraction. The mapping themes were developed using a normative approach, where expert input during the identification and classification of vulnerability indicators may increase the acceptability of the resultant map. This article describes the development of the interactive vulnerability map for South Africa, where UOG extraction is not yet allowed and where regulations are still being developed to manage this activity. The importance and policy implications of using vulnerability maps for managing UOG extraction impacts in countries where UOG extraction is planned are highlighted in this article. PMID:29291094

Mapping fires and American Red Cross aid using demographic indicators of vulnerability.

PubMed

Lue, Evan; Wilson, John P

2017-04-01

Social vulnerability indicators can assist with informing disaster relief preparation. Certain demographic segments of a population may suffer disproportionately during disaster events, and a geographical understanding of them can help to determine where to place strategically logistical assets and to target disaster-awareness outreach endeavours. Records of house fire events and American Red Cross aid provision over a five-year period were mapped for the County of Los Angeles, California, United States, to examine the congruence between actual events and expectations of risk based on vulnerability theory. The geographical context provided by the data was compared with spatially-explicit indicators of vulnerability, such as age, race, and wealth. Fire events were found to occur more frequently in more vulnerable areas, and Red Cross aid was found to have an even stronger relationship to those places. The findings suggest that these indicators speak beyond vulnerability and relate to patterns of fire risk. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.

Single photon counting fluorescence lifetime detection of pericellular oxygen concentrations

NASA Astrophysics Data System (ADS)

Hosny, Neveen A.; Lee, David A.; Knight, Martin M.

2012-01-01

Fluorescence lifetime imaging microscopy offers a non-invasive method for quantifying local oxygen concentrations. However, existing methods are either invasive, require custom-made systems, or show limited spatial resolution. Therefore, these methods are unsuitable for investigation of pericellular oxygen concentrations. This study describes an adaptation of commercially available equipment which has been optimized for quantitative extracellular oxygen detection with high lifetime accuracy and spatial resolution while avoiding systematic photon pile-up. The oxygen sensitive fluorescent dye, tris(2,2'-bipyridyl)ruthenium(II) chloride hexahydrate [Ru(bipy)3]2+, was excited using a two-photon excitation laser. Lifetime was measured using a Becker & Hickl time-correlated single photon counting, which will be referred to as a TCSPC card. [Ru(bipy)3]2+ characterization studies quantified the influences of temperature, pH, cellular culture media and oxygen on the fluorescence lifetime measurements. This provided a precisely calibrated and accurate system for quantification of pericellular oxygen concentration based on measured lifetimes. Using this technique, quantification of oxygen concentrations around isolated viable chondrocytes, seeded in three-dimensional agarose gel, revealed a subpopulation of cells that exhibited significant spatial oxygen gradients such that oxygen concentration reduced with increasing proximity to the cell. This technique provides a powerful tool for quantifying spatial oxygen gradients within three-dimensional cellular models.

Single photon counting fluorescence lifetime detection of pericellular oxygen concentrations.

PubMed

Hosny, Neveen A; Lee, David A; Knight, Martin M

2012-01-01

Fluorescence lifetime imaging microscopy offers a non-invasive method for quantifying local oxygen concentrations. However, existing methods are either invasive, require custom-made systems, or show limited spatial resolution. Therefore, these methods are unsuitable for investigation of pericellular oxygen concentrations. This study describes an adaptation of commercially available equipment which has been optimized for quantitative extracellular oxygen detection with high lifetime accuracy and spatial resolution while avoiding systematic photon pile-up. The oxygen sensitive fluorescent dye, tris(2,2'-bipyridyl)ruthenium(II) chloride hexahydrate [Ru(bipy)(3)](2+), was excited using a two-photon excitation laser. Lifetime was measured using a Becker & Hickl time-correlated single photon counting, which will be referred to as a TCSPC card. [Ru(bipy)(3)](2+) characterization studies quantified the influences of temperature, pH, cellular culture media and oxygen on the fluorescence lifetime measurements. This provided a precisely calibrated and accurate system for quantification of pericellular oxygen concentration based on measured lifetimes. Using this technique, quantification of oxygen concentrations around isolated viable chondrocytes, seeded in three-dimensional agarose gel, revealed a subpopulation of cells that exhibited significant spatial oxygen gradients such that oxygen concentration reduced with increasing proximity to the cell. This technique provides a powerful tool for quantifying spatial oxygen gradients within three-dimensional cellular models.

The vulnerability and resilience of a city's water footprint: The case of Flagstaff, Arizona, USA

NASA Astrophysics Data System (ADS)

Rushforth, Richard R.; Ruddell, Benjamin L.

2016-04-01

Research has yet to operationalize water footprint information for urban water policy and planning to reduce vulnerability and increase resilience to water scarcity. Using a county-level database of the U.S. hydro-economy, NWED, we spatially mapped and analyzed the Water Footprint of Flagstaff, Arizona, a small city. Virtual water inflow and outflow networks were developed using the flow of commodities into and out of the city. The power law distribution of virtual water trade volume between Flagstaff and its county trading partners broke at a spatial distance of roughly 2000 km. Most large trading partners are within this geographical distance, and this distance is an objective definition for Flagstaff's zone of indirect hydro-economic influence—that is, its water resource hinterland. Metrics were developed to measure Flagstaff's reliance on virtual water resources, versus direct use of local physical water resources. Flagstaff's reliance on external water supplies via virtual water trade increases both its hydro-economic resilience and vulnerability to water scarcity. These methods empower city managers to operationalize the city's Water Footprint information to reduce vulnerability, increase resilience, and optimally balance the allocation of local physical water supplies with the outsourcing of some water uses via the virtual water supply chain.

An Integrated Approach for Urban Earthquake Vulnerability Analyses

NASA Astrophysics Data System (ADS)

Düzgün, H. S.; Yücemen, M. S.; Kalaycioglu, H. S.

2009-04-01

The earthquake risk for an urban area has increased over the years due to the increasing complexities in urban environments. The main reasons are the location of major cities in hazard prone areas, growth in urbanization and population and rising wealth measures. In recent years physical examples of these factors are observed through the growing costs of major disasters in urban areas which have stimulated a demand for in-depth evaluation of possible strategies to manage the large scale damaging effects of earthquakes. Understanding and formulation of urban earthquake risk requires consideration of a wide range of risk aspects, which can be handled by developing an integrated approach. In such an integrated approach, an interdisciplinary view should be incorporated into the risk assessment. Risk assessment for an urban area requires prediction of vulnerabilities related to elements at risk in the urban area and integration of individual vulnerability assessments. However, due to complex nature of an urban environment, estimating vulnerabilities and integrating them necessities development of integrated approaches in which vulnerabilities of social, economical, structural (building stock and infrastructure), cultural and historical heritage are estimated for a given urban area over a given time period. In this study an integrated urban earthquake vulnerability assessment framework, which considers vulnerability of urban environment in a holistic manner and performs the vulnerability assessment for the smallest administrative unit, namely at neighborhood scale, is proposed. The main motivation behind this approach is the inability to implement existing vulnerability assessment methodologies for countries like Turkey, where the required data are usually missing or inadequate and decision makers seek for prioritization of their limited resources in risk reduction in the administrative districts from which they are responsible. The methodology integrates socio-economical, structural, coastal, ground condition, organizational vulnerabilities, as well as accessibility to critical services within the framework. The proposed framework has the following eight components: Seismic hazard analysis, soil response analysis, tsunami inundation analysis, structural vulnerability analysis, socio-economic vulnerability analysis, accessibility to critical services, GIS-based integrated vulnerability assessment, and visualization of vulnerabilities in 3D virtual city model The integrated model for various vulnerabilities obtained for the urban area is developed in GIS environment by using individual vulnerability assessments for considered elements at risk and serve for establishing the backbone of the spatial decision support system. The stages followed in the model are: Determination of a common mapping unit for each aspect of urban earthquake vulnerability, formation of a geo-database for the vulnerabilities, evaluation of urban vulnerability based on multi attribute utility theory with various weighting algorithms, mapping of the evaluated integrated earthquake risk in geographic information systems (GIS) in the neighborhood scale. The framework is also applicable to larger geographical mapping scales, for example, the building scale. When illustrating the results in building scale, 3-D visualizations with remote sensing data is used so that decision-makers can easily interpret the outputs. The proposed vulnerability assessment framework is flexible and can easily be applied to urban environments at various geographical scales with different mapping units. The obtained total vulnerability maps for the urban area provide a baseline for the development of risk reduction strategies for the decision makers. Moreover, as several aspects of elements at risk for an urban area is considered through vulnerability analyses, effect on changes in vulnerability conditions on the total can easily be determined. The developed approach also enables decision makers to monitor temporal and spatial changes in the urban environment due to implementation of risk reduction strategies.

Applying a statewide geospatial leaching tool for assessing soil vulnerability ratings for agrochemicals across the contiguous United States.

PubMed

Ki, Seo Jin; Ray, Chittaranjan; Hantush, Mohamed M

2015-06-15

A large-scale leaching assessment tool not only illustrates soil (or groundwater) vulnerability in unmonitored areas, but also can identify areas of potential concern for agrochemical contamination. This study describes the methodology of how the statewide leaching tool in Hawaii modified recently for use with pesticides and volatile organic compounds can be extended to the national assessment of soil vulnerability ratings. For this study, the tool was updated by extending the soil and recharge maps to cover the lower 48 states in the United States (US). In addition, digital maps of annual pesticide use (at a national scale) as well as detailed soil properties and monthly recharge rates (at high spatial and temporal resolutions) were used to examine variations in the leaching (loads) of pesticides for the upper soil horizons. Results showed that the extended tool successfully delineated areas of high to low vulnerability to selected pesticides. The leaching potential was high for picloram, medium for simazine, and low to negligible for 2,4-D and glyphosate. The mass loadings of picloram moving below 0.5 m depth increased greatly in northwestern and central US that recorded its extensive use in agricultural crops. However, in addition to the amount of pesticide used, annual leaching load of atrazine was also affected by other factors that determined the intrinsic aquifer vulnerability such as soil and recharge properties. Spatial and temporal resolutions of digital maps had a great effect on the leaching potential of pesticides, requiring a trade-off between data availability and accuracy. Potential applications of this tool include the rapid, large-scale vulnerability assessments for emerging contaminants which are hard to quantify directly through vadose zone models due to lack of full environmental data. Copyright © 2015 Elsevier Ltd. All rights reserved.

An automated system using spatial oversampling for optical mapping in murine atria. Development and validation with monophasic and transmembrane action potentials.

PubMed

Yu, Ting Yue; Syeda, Fahima; Holmes, Andrew P; Osborne, Benjamin; Dehghani, Hamid; Brain, Keith L; Kirchhof, Paulus; Fabritz, Larissa

2014-08-01

We developed and validated a new optical mapping system for quantification of electrical activation and repolarisation in murine atria. The system makes use of a novel 2nd generation complementary metal-oxide-semiconductor (CMOS) camera with deliberate oversampling to allow both assessment of electrical activation with high spatial and temporal resolution (128 × 2048 pixels) and reliable assessment of atrial murine repolarisation using post-processing of signals. Optical recordings were taken from isolated, superfused and electrically stimulated murine left atria. The system reliably describes activation sequences, identifies areas of functional block, and allows quantification of conduction velocities and vectors. Furthermore, the system records murine atrial action potentials with comparable duration to both monophasic and transmembrane action potentials in murine atria. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Remotely Sensed Hydrometeorological and Agrometeorological Drought Risk Identification for Sustainable Agriculture.

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas R.; Blanta, Anna; Spyropoulos, Nicos

2013-04-01

Drought is considered as one of the major environmental hazards with significant impacts to agriculture, environment, economy and society. This paper addresses drought as a hazard within the risk management framework. Indeed, hazards may be defined as a potential threat to humans and their welfare and risk (or consequence) as the probability of a hazard occurring and creating loss. Besides, risk management consists of risk assessment and feedback of the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. In order to ensure sustainability in agricultural production a better understanding of the natural disasters, in particular droughts, that impact agriculture is essential. Droughts may result in environmental degradation of an area, which is one of the factors contributing to the vulnerability of agriculture, because it directly magnifies the risk of natural disasters. This paper deals with drought risk identification, which involves hazard quantification, event monitoring including early warning systems and statistical inference. For drought quantification the Reconnaissance Drought Index (RDI) combined with Vegetation Health Index (VHI) is employed. RDI is a new index based on hydrometeorological parameters, and in particular precipitation and potential evapotranspiration, which has been recently modified to incorporate monthly satellite (NOAA/AVHAA) data for a period of 20 years (1981-2001). VHI is based on NDVI. The study area is Thessaly in central Greece, which is one of the major agricultural areas of the country occasionally facing droughts. Drought monitoring is conducted by monthly remotely sensed RID and VHI images and several drought features are extracted such as severity, duration, areal extent, onset and end time. Drought early warning is developed using empirical relationships of the above mentioned features. In particular, two second-order polynomials are fitted relating severity and areal extend (number of pixels), one for low and other for high severity drought. The two fitted curves offer a forecasting tool on a monthly basis from the beginning of each hydrological year with high severity droughts occurring from October, whereas low severity droughts start in April. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential of drought. The adopted remote sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Yueqi; Lava, Pascal; Reu, Phillip

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

DOE PAGES

Wang, Yueqi; Lava, Pascal; Reu, Phillip; ...

2015-12-23

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

Coastal Vulnerability and risk assessment of infrastructures, natural and cultural heritage sites in Greece.

NASA Astrophysics Data System (ADS)

Alexandrakis, George; Kampanis, Nikolaos

2016-04-01

The majority of human activities are concentrated around coastal areas, making coastline retreat, a significant threat to coastal infrastructure, thus increasing protection cost and investment revenue losses. In this study the management of coastal areas in terms of protecting coastal infrastructures, cultural and environmental heritage sites, through risk assessment analysis is been made. The scope is to provide data for spatial planning for future developments in the coastal zone and the protection of existing ones. Also to determine the impact of coastal changes related to the loss of natural resources, agricultural land and beaches. The analysis is based on a multidisciplinary approach, combining environmental, spatial and economic data. This can be implemented by integrating the assessment of vulnerability of coasts, the spatial distribution and structural elements of coastal infrastructure (transport, tourism, and energy) and financial data by region, in a spatial database. The approach is based on coastal vulnerability estimations, considering sea level rise, land loss, extreme events, safety, adaptability and resilience of infrastructure and natural sites. It is based on coupling of environmental indicators and econometric models to determine the socio-economic impact in coastal infrastructure, cultural and environmental heritage sites. The indicators include variables like the coastal geomorphology; coastal slope; relative sea-level rise rate; shoreline erosion/accretion rate; mean tidal range and mean wave height. The anthropogenic factors include variables like settlements, sites of cultural heritage, transport networks, land uses, significance of infrastructure (e.g. military, power plans) and economic activities. The analysis in performed by a GIS application. The forcing variables are determined with the use of sub-indices related to coastal geomorphology, climate and wave variables and the socioeconomics of the coastal zone. The Greek coastline in considered as a case study, where the majority of the coastline appears to be undergoing erosion, with approximately 25% of the Aegean coastline, consisting mainly of beach zones and low-lying coastal (including deltaic) plains. In terms of economic activates coastal tourism is most effected, as beach zones are very high vulnerable to erosion. Also, small ports in remote islands are also found to be highly vulnerable. Acknowledgments This work was implemented within the framework of "Post-Doctoral Excellence Scholarship. State Scholarships Foundation, Greece IKY- Siemens Action"

Climate change and human health: Spatial modeling of water availability, malnutrition, and livelihoods in Mali, Africa

USGS Publications Warehouse

Jankowska, Marta M.; Lopez-Carr, David; Funk, Chris; Husak, Gregory J.; Chafe, Z.A.

2012-01-01

This study develops a novel approach for projecting climate trends in the Sahel in relation to shifting livelihood zones and health outcomes. Focusing on Mali, we explore baseline relationships between temperature, precipitation, livelihood, and malnutrition in 407 Demographic and Health Survey (DHS) clusters with a total of 14,238 children, resulting in a thorough spatial analysis of coupled climate-health dynamics. Results suggest links between livelihoods and each measure of malnutrition, as well as a link between climate and stunting. A ‘front-line’ of vulnerability, related to the transition between agricultural and pastoral livelihoods, is identified as an area where mitigation efforts might be usefully targeted. Additionally, climate is projected to 2025 for the Sahel, and demographic trends are introduced to explore how the intersection of climate and demographics may shift the vulnerability ‘front-line’, potentially exposing an additional 6 million people in Mali, up to a million of them children, to heightened risk of malnutrition from climate and livelihood changes. Results indicate that, holding constant morbidity levels, approximately one quarter of a million children will suffer stunting, nearly two hundred thousand will be malnourished, and over one hundred thousand will become anemic in this expanding arid zone by 2025. Climate and health research conducted at finer spatial scales and within shorter projected time lines can identify vulnerability hot spots that are of the highest priority for adaptation interventions; such an analysis can also identify areas with similar characteristics that may be at heightened risk. Such meso-scale coupled human-environment research may facilitate appropriate policy interventions strategically located beyond today’s vulnerability front-line.

Approach for assessing coastal vulnerability to oil spills for prevention and readiness using GIS and the Blowout and Spill Occurrence Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, J. R.; Grubesic, T. H.; Sim, L.

Increasing interest in offshore hydrocarbon exploration has pushed the operational fronts associated with exploration efforts further offshore into deeper waters and more uncertain subsurface settings. This has become particularly common in the U.S. Gulf of Mexico. In this study we develop a spatial vulnerability approach and example assessment to support future spill prevention and improve future response readiness. This effort, which is part of a larger integrated assessment modeling spill prevention effort, incorporated economic and environmental data, and utilized a novel new oil spill simulation model from the U.S. Department of Energy’s National Energy Technology Laboratory, the Blowout and Spillmore » Occurrence Model (BLOSOM). Specifically, this study demonstrated a novel approach to evaluate potential impacts of hypothetical spill simulations at varying depths and locations in the northern Gulf of Mexico. The simulations are analyzed to assess spatial and temporal trends associated with the oil spill. The approach itself demonstrates how these data, tools and techniques can be used to evaluate potential spatial vulnerability of Gulf communities for various spill scenarios. Results of the hypothetical scenarios evaluated in this study suggest that under conditions like those simulated, a strong westward push by ocean currents and tides may increase the impacts of deep water spills along the Texas coastline, amplifying the vulnerability of communities on the local barrier islands. Ultimately, this approach can be used further to assess a range of conditions and scenarios to better understand potential risks and improve informed decision making for operators, responders, and stakeholders to support spill prevention as well as response readiness.« less

Approach for assessing coastal vulnerability to oil spills for prevention and readiness using GIS and the Blowout and Spill Occurrence Model

DOE PAGES

Nelson, J. R.; Grubesic, T. H.; Sim, L.; ...

2015-08-01

Increasing interest in offshore hydrocarbon exploration has pushed the operational fronts associated with exploration efforts further offshore into deeper waters and more uncertain subsurface settings. This has become particularly common in the U.S. Gulf of Mexico. In this study we develop a spatial vulnerability approach and example assessment to support future spill prevention and improve future response readiness. This effort, which is part of a larger integrated assessment modeling spill prevention effort, incorporated economic and environmental data, and utilized a novel new oil spill simulation model from the U.S. Department of Energy’s National Energy Technology Laboratory, the Blowout and Spillmore » Occurrence Model (BLOSOM). Specifically, this study demonstrated a novel approach to evaluate potential impacts of hypothetical spill simulations at varying depths and locations in the northern Gulf of Mexico. The simulations are analyzed to assess spatial and temporal trends associated with the oil spill. The approach itself demonstrates how these data, tools and techniques can be used to evaluate potential spatial vulnerability of Gulf communities for various spill scenarios. Results of the hypothetical scenarios evaluated in this study suggest that under conditions like those simulated, a strong westward push by ocean currents and tides may increase the impacts of deep water spills along the Texas coastline, amplifying the vulnerability of communities on the local barrier islands. Ultimately, this approach can be used further to assess a range of conditions and scenarios to better understand potential risks and improve informed decision making for operators, responders, and stakeholders to support spill prevention as well as response readiness.« less

What actually confers adaptive capacity? Insights from agro-climatic vulnerability of Australian wheat.

PubMed

Bryan, Brett A; Huai, Jianjun; Connor, Jeff; Gao, Lei; King, Darran; Kandulu, John; Zhao, Gang

2015-01-01

Vulnerability assessments have often invoked sustainable livelihoods theory to support the quantification of adaptive capacity based on the availability of capital--social, human, physical, natural, and financial. However, the assumption that increased availability of these capitals confers greater adaptive capacity remains largely untested. We quantified the relationship between commonly used capital indicators and an empirical index of adaptive capacity (ACI) in the context of vulnerability of Australian wheat production to climate variability and change. We calculated ACI by comparing actual yields from farm survey data to climate-driven expected yields estimated by a crop model for 12 regions in Australia's wheat-sheep zone from 1991-2010. We then compiled data for 24 typical indicators used in vulnerability analyses, spanning the five capitals. We analyzed the ACI and used regression techniques to identify related capital indicators. Between regions, mean ACI was not significantly different but variance over time was. ACI was higher in dry years and lower in wet years suggesting that farm adaptive strategies are geared towards mitigating losses rather than capitalizing on opportunity. Only six of the 24 capital indicators were significantly related to adaptive capacity in a way predicted by theory. Another four indicators were significantly related to adaptive capacity but of the opposite sign, countering our theory-driven expectation. We conclude that the deductive, theory-based use of capitals to define adaptive capacity and vulnerability should be more circumspect. Assessments need to be more evidence-based, first testing the relevance and influence of capital metrics on adaptive capacity for the specific system of interest. This will more effectively direct policy and targeting of investment to mitigate agro-climatic vulnerability.

What Actually Confers Adaptive Capacity? Insights from Agro-Climatic Vulnerability of Australian Wheat

PubMed Central

Bryan, Brett A.; Huai, Jianjun; Connor, Jeff; Gao, Lei; King, Darran; Kandulu, John; Zhao, Gang

2015-01-01

Vulnerability assessments have often invoked sustainable livelihoods theory to support the quantification of adaptive capacity based on the availability of capital—social, human, physical, natural, and financial. However, the assumption that increased availability of these capitals confers greater adaptive capacity remains largely untested. We quantified the relationship between commonly used capital indicators and an empirical index of adaptive capacity (ACI) in the context of vulnerability of Australian wheat production to climate variability and change. We calculated ACI by comparing actual yields from farm survey data to climate-driven expected yields estimated by a crop model for 12 regions in Australia’s wheat-sheep zone from 1991–2010. We then compiled data for 24 typical indicators used in vulnerability analyses, spanning the five capitals. We analyzed the ACI and used regression techniques to identify related capital indicators. Between regions, mean ACI was not significantly different but variance over time was. ACI was higher in dry years and lower in wet years suggesting that farm adaptive strategies are geared towards mitigating losses rather than capitalizing on opportunity. Only six of the 24 capital indicators were significantly related to adaptive capacity in a way predicted by theory. Another four indicators were significantly related to adaptive capacity but of the opposite sign, countering our theory-driven expectation. We conclude that the deductive, theory-based use of capitals to define adaptive capacity and vulnerability should be more circumspect. Assessments need to be more evidence-based, first testing the relevance and influence of capital metrics on adaptive capacity for the specific system of interest. This will more effectively direct policy and targeting of investment to mitigate agro-climatic vulnerability. PMID:25668192

Groundwater vulnerability assessment for the Banyas Catchment of the Syrian coastal area using GIS and the RISKE method.

PubMed

Kattaa, Bassam; Al-Fares, Walid; Al Charideh, Abdul Rahman

2010-05-01

Vulnerability assessment to delineate areas that are more susceptible to contamination from anthropogenic sources has become an important element for sensible resource management and landuse planning. This contribution aims at estimating aquifer vulnerability by applying the RISKE model in Banyas Catchment Area (BCA), Tartous Prefecture, west Syria. An additional objective is to demonstrate the combined use of the RISKE model and a geographical information system (GIS) as an effective method for groundwater pollution risk assessment. The RISKE model uses five environmental parameters (Rock of aquifer media, Infiltration, Soil media, Karst, and Epikarst) to characterize the hydro-geological setting and evaluate aquifer vulnerability. The elevated eastern and low western part of the study area was dominated by high vulnerability classes, while the middle part was characterized by moderate vulnerability classes. Based on the vulnerability analysis, it was found that 2% and 39% of BCA is under low and high vulnerability to groundwater contamination, respectively, while more than 52% and 5% of the area of BCA can be designated as an area of moderate and very high vulnerability to groundwater contamination, respectively. The GIS technique has provided an efficient environment for analyses and high capabilities of handling a large amount of spatial data. Copyright 2009 Elsevier Ltd. All rights reserved.

Projecting Drivers of Human Vulnerability under the Shared Socioeconomic Pathways.

PubMed

Rohat, Guillaume

2018-03-19

The Shared Socioeconomic Pathways (SSPs) are the new set of alternative futures of societal development that inform global and regional climate change research. They have the potential to foster the integration of socioeconomic scenarios within assessments of future climate-related health impacts. To date, such assessments have primarily superimposed climate scenarios on current socioeconomic conditions only. Until now, the few assessments of future health risks that employed the SSPs have focused on future human exposure-i.e., mainly future population patterns-, neglecting future human vulnerability. This paper first explores the research gaps-mainly linked to the paucity of available projections-that explain such a lack of consideration of human vulnerability under the SSPs. It then highlights the need for projections of socioeconomic variables covering the wide range of determinants of human vulnerability, available at relevant spatial and temporal scales, and accounting for local specificities through sectoral and regional extended versions of the global SSPs. Finally, this paper presents two innovative methods of obtaining and computing such socioeconomic projections under the SSPs-namely the scenario matching approach and an approach based on experts' elicitation and correlation analyses-and applies them to the case of Europe. They offer a variety of possibilities for practical application, producing projections at sub-national level of various drivers of human vulnerability such as demographic and social characteristics, urbanization, state of the environment, infrastructure, health status, and living arrangements. Both the innovative approaches presented in this paper and existing methods-such as the spatial disaggregation of existing projections and the use of sectoral models-show great potential to enhance the availability of relevant projections of determinants of human vulnerability. Assessments of future climate-related health impacts should thus rely on these methods to account for future human vulnerability-under varying levels of socioeconomic development-and to explore its influence on future health risks under different degrees of climate change.

Climates Past, Present, and Yet-to-Come Shape Climate Change Vulnerabilities.

PubMed

Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R

2017-10-01

Climate change is altering life at multiple scales, from genes to ecosystems. Predicting the vulnerability of populations to climate change is crucial to mitigate negative impacts. We suggest that regional patterns of spatial and temporal climatic variation scaled to the traits of an organism can predict where and why populations are most vulnerable to climate change. Specifically, historical climatic variation affects the sensitivity and response capacity of populations to climate change by shaping traits and the genetic variation in those traits. Present and future climatic variation can affect both climate change exposure and population responses. We provide seven predictions for how climatic variation might affect the vulnerability of populations to climate change and suggest key directions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial analysis of land use and shallow groundwater vulnerability in the watershed adjacent to Assateague Island National Seashore, Maryland and Virginia, USA

USGS Publications Warehouse

LaMotte, A.E.; Greene, E.A.

2007-01-01

Spatial relations between land use and groundwater quality in the watershed adjacent to Assateague Island National Seashore, Maryland and Virginia, USA were analyzed by the use of two spatial models. One model used a logit analysis and the other was based on geostatistics. The models were developed and compared on the basis of existing concentrations of nitrate as nitrogen in samples from 529 domestic wells. The models were applied to produce spatial probability maps that show areas in the watershed where concentrations of nitrate in groundwater are likely to exceed a predetermined management threshold value. Maps of the watershed generated by logistic regression and probability kriging analysis showing where the probability of nitrate concentrations would exceed 3 mg/L (>0.50) compared favorably. Logistic regression was less dependent on the spatial distribution of sampled wells, and identified an additional high probability area within the watershed that was missed by probability kriging. The spatial probability maps could be used to determine the natural or anthropogenic factors that best explain the occurrence and distribution of elevated concentrations of nitrate (or other constituents) in shallow groundwater. This information can be used by local land-use planners, ecologists, and managers to protect water supplies and identify land-use planning solutions and monitoring programs in vulnerable areas. ?? 2006 Springer-Verlag.

Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

PubMed

Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao

2018-05-01

Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.

An overview of data integration methods for regional assessment.

PubMed

Locantore, Nicholas W; Tran, Liem T; O'Neill, Robert V; McKinnis, Peter W; Smith, Elizabeth R; O'Connell, Michael

2004-06-01

The U.S. Environmental Protections Agency's (U.S. EPA) Regional Vulnerability Assessment(ReVA) program has focused much of its research over the last five years on developing and evaluating integration methods for spatial data. An initial strategic priority was to use existing data from monitoring programs, model results, and other spatial data. Because most of these data were not collected with an intention of integrating into a regional assessment of conditions and vulnerabilities, issues exist that may preclude the use of some methods or require some sort of data preparation. Additionally, to support multi-criteria decision-making, methods need to be able to address a series of assessment questions that provide insights into where environmental risks are a priority. This paper provides an overview of twelve spatial integration methods that can be applied towards regional assessment, along with preliminary results as to how sensitive each method is to data issues that will likely be encountered with the use of existing data.

Analysis of bathymetric surveys to identify coastal vulnerabilities at Cape Canaveral, Florida

USGS Publications Warehouse

Thompson, David M.; Plant, Nathaniel G.; Hansen, Mark E.

2015-10-07

The purpose of this work is to describe an updated bathymetric dataset collected in 2014 and compare it to previous datasets. The updated data focus on the bathymetric features and sediment transport pathways that connect the offshore regions to the shoreline and, therefore, are related to the protection of other portions of the coastal environment, such as dunes, that support infrastructure and ecosystems. Previous survey data include National Oceanic and Atmospheric Administration’s (NOAA) National Ocean Service (NOS) hydrographic survey from 1956 and a USGS survey from 2010 that is augmented with NOS surveys from 2006 and 2007. The primary result of this analysis is documentation and quantification of the nature and rates of bathymetric changes that are near (within about 2.5 km) the current Cape Canaveral shoreline and interpretation of the impact of these changes on future erosion vulnerability.

Modelling the changing cumulative vulnerability to climate-related hazards for river basin management using a GIS-based multicriteria decision approach

NASA Astrophysics Data System (ADS)

Hung, Hung-Chih; Wu, Ju-Yu; Hung, Chih-Hsuan

2017-04-01

1. Background Asia-Pacific region is one of the most vulnerable areas of the world to climate-related hazards and extremes due to rapid urbanization and over-development in hazard-prone areas. It is thus increasingly recognized that the management of land use and reduction of hazard risk are inextricably linked. This is especially critical from the perspective of integrated river basin management. A range of studies has targeted existing vulnerability assessments. However, limited attention has been paid to the cumulative effects of multiple vulnerable factors and their dynamics faced by local communities. This study proposes a novel methodology to access the changing cumulative vulnerability to climate-related hazards, and to examine the relationship between the attraction factors relevant to the general process of urbanization and vulnerability variability with a focus on a river basin management unit. 2. Methods and data The methods applied in this study include three steps. First, using Intergovernmental Panel on Climate Change's (IPCC) approach, a Cumulative Vulnerability Assessment Framework (CVAF) is built with a goal to characterize and compare the vulnerability to climate-related hazards within river basin regions based on a composition of multiple indicators. We organize these indicator metrics into three categories: (1) hazard exposure; (2) socioeconomic sensitivity, and (3) adaptive capacity. Second, the CVAF is applied by combining a geographical information system (GIS)-based spatial statistics technique with a multicriteria decision analysis (MCDA) to assess and map the changing cumulative vulnerability, comparing conditions in 1996 and 2006 in Danshui River Basin, Taiwan. Third, to examine the affecting factors of vulnerability changing, we develop a Vulnerability Changing Model (VCM) using four attraction factors to reflect how the process of urban developments leads to vulnerability changing. The factors are transport networks, land uses, production values of industries, and infrastructures. We then conduct a regression analysis to test the VCM. To illustrate the proposed methodology, the data are collected from the National Science and Technology Center for Disaster Reduction, Taiwan as well as the National Land Use Investigation and official census statistics. 3. Results and policy implications Results of CVAF analysis demonstrate heterogeneous patterns of vulnerability in the region, and highlight trends of long-term changes. The vulnerable areas unfold as clustered patterns and spatial analogues across regions, rather than randomly distributed. Highest cumulative vulnerability is concentrated in densely populated and downstream reaches (such as Taipei City) of the Danshui River in both time periods. When examining the VCM, it indicates that upper stream and more remote areas generally show low vulnerability, increases are observed in some areas between 1996 and 2006 due to land use intensification, industrial and infrastructure expansion. These findings suggest that land use planning should consider the socioeconomic progression and infrastructure investment factors that contribute to urban sprawl and address current as well as future urban developments vulnerable to hazard risk transmission. The cumulative vulnerability assessment, mapping methods and modelling presented here can be applied to other climate change and hazard risks to highlight priority areas for further investigation and contribute towards improving river basin management.

Modelling homogeneous regions of social vulnerability to malaria in Rwanda.

PubMed

Bizimana, Jean Pierre; Kienberger, Stefan; Hagenlocher, Michael; Twarabamenye, Emmanuel

2016-03-31

Despite the decline in malaria incidence due to intense interventions, potentials for malaria transmission persist in Rwanda. To eradicate malaria in Rwanda, strategies need to expand beyond approaches that focus solely on malaria epidemiology and also consider the socioeconomic, demographic and biological/disease-related factors that determine the vulnerability of potentially exposed populations. This paper analyses current levels of social vulnerability to malaria in Rwanda by integrating a set of weighted vulnerability indicators. The paper uses regionalisation techniques as a spatially explicit approach for delineating homogeneous regions of social vulnerability to malaria. This overcomes the limitations of administrative boundaries for modelling the trans-boundary social vulnerability to malaria. The utilised approach revealed high levels of social vulnerability to malaria in the highland areas of Rwanda, as well as in remote areas where populations are more susceptible. Susceptibility may be due to the populations' lacking the capacity to anticipate mosquito bites, or lacking resilience to cope with or recover from malaria infection. By highlighting the most influential indicators of social vulnerability to malaria, the applied approach indicates which vulnerability domains need to be addressed, and where appropriate interventions are most required. Interventions to improve the socioeconomic development in highly vulnerable areas could prove highly effective, and provide sustainable outcomes against malaria in Rwanda. This would ultimately increase the resilience of the population and their capacity to better anticipate, cope with, and recover from possible infection.

Extended quantification of the generalized recurrence plot

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2016-04-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing structures, turbulent spatial plankton patterns, and fractals. But, it is also successfully applied to the description of spatio-temporal dynamics and the detection of regime shifts, such as in the complex Ginzburg-Landau- equation. The recurrence plot based determinism is a central measure in this framework quantifying the level of regularities in temporal and spatial structures. We extend this measure for the generalized recurrence plot considering additional operations of symmetry than the simple translation. It is tested not only on two-dimensional regular patterns and noise but also on complex spatial patterns reconstructing the parameter space of the complex Ginzburg-Landau-equation. The extended version of the determinism resulted in values which are consistent to the original recurrence plot approach. Furthermore, the proposed method allows a split of the determinism into parts which based on laminar and non-laminar regions of the two-dimensional pattern of the complex Ginzburg-Landau-equation. A comparison of these parts with a standard method of image classification, the co-occurrence matrix approach, shows differences especially in the description of patterns associated with turbulence. In that case, it seems that the extended version of the determinism allows a distinction of phase turbulence and defect turbulence by means of their spatial patterns. This ability of the proposed method promise new insights in other systems with turbulent dynamics coming from climatology, biology, ecology, and social sciences, for example.

Reproducibility study of whole-brain 1H spectroscopic imaging with automated quantification.

PubMed

Gu, Meng; Kim, Dong-Hyun; Mayer, Dirk; Sullivan, Edith V; Pfefferbaum, Adolf; Spielman, Daniel M

2008-09-01

A reproducibility study of proton MR spectroscopic imaging ((1)H-MRSI) of the human brain was conducted to evaluate the reliability of an automated 3D in vivo spectroscopic imaging acquisition and associated quantification algorithm. A PRESS-based pulse sequence was implemented using dualband spectral-spatial RF pulses designed to fully excite the singlet resonances of choline (Cho), creatine (Cre), and N-acetyl aspartate (NAA) while simultaneously suppressing water and lipids; 1% of the water signal was left to be used as a reference signal for robust data processing, and additional lipid suppression was obtained using adiabatic inversion recovery. Spiral k-space trajectories were used for fast spectral and spatial encoding yielding high-quality spectra from 1 cc voxels throughout the brain with a 13-min acquisition time. Data were acquired with an 8-channel phased-array coil and optimal signal-to-noise ratio (SNR) for the combined signals was achieved using a weighting based on the residual water signal. Automated quantification of the spectrum of each voxel was performed using LCModel. The complete study consisted of eight healthy adult subjects to assess intersubject variations and two subjects scanned six times each to assess intrasubject variations. The results demonstrate that reproducible whole-brain (1)H-MRSI data can be robustly obtained with the proposed methods.

Full-field transient vibrometry of the human tympanic membrane by local phase correlation and high-speed holography

NASA Astrophysics Data System (ADS)

Dobrev, Ivo; Furlong, Cosme; Cheng, Jeffrey T.; Rosowski, John J.

2014-09-01

Understanding the human hearing process would be helped by quantification of the transient mechanical response of the human ear, including the human tympanic membrane (TM or eardrum). We propose a new hybrid high-speed holographic system (HHS) for acquisition and quantification of the full-field nanometer transient (i.e., >10 kHz) displacement of the human TM. We have optimized and implemented a 2+1 frame local correlation (LC) based phase sampling method in combination with a high-speed (i.e., >40 K fps) camera acquisition system. To our knowledge, there is currently no existing system that provides such capabilities for the study of the human TM. The LC sampling method has a displacement difference of <11 nm relative to measurements obtained by a four-phase step algorithm. Comparisons between our high-speed acquisition system and a laser Doppler vibrometer indicate differences of <10 μs. The high temporal (i.e., >40 kHz) and spatial (i.e., >100 k data points) resolution of our HHS enables parallel measurements of all points on the surface of the TM, which allows quantification of spatially dependent motion parameters, such as modal frequencies and acoustic delays. Such capabilities could allow inferring local material properties across the surface of the TM.

Extending Vulnerability Assessment to Include Life Stages Considerations

PubMed Central

Hodgson, Emma E.; Essington, Timothy E.; Kaplan, Isaac C.

2016-01-01

Species are experiencing a suite of novel stressors from anthropogenic activities that have impacts at multiple scales. Vulnerability assessment is one tool to evaluate the likely impacts that these stressors pose to species so that high-vulnerability cases can be identified and prioritized for monitoring, protection, or mitigation. Commonly used semi-quantitative methods lack a framework to explicitly account for differences in exposure to stressors and organism responses across life stages. Here we propose a modification to commonly used spatial vulnerability assessment methods that includes such an approach, using ocean acidification in the California Current as an illustrative case study. Life stage considerations were included by assessing vulnerability of each life stage to ocean acidification and were used to estimate population vulnerability in two ways. We set population vulnerability equal to: (1) the maximum stage vulnerability and (2) a weighted mean across all stages, with weights calculated using Lefkovitch matrix models. Vulnerability was found to vary across life stages for the six species explored in this case study: two krill–Euphausia pacifica and Thysanoessa spinifera, pteropod–Limacina helicina, pink shrimp–Pandalus jordani, Dungeness crab–Metacarcinus magister and Pacific hake–Merluccius productus. The maximum vulnerability estimates ranged from larval to subadult and adult stages with no consistent stage having maximum vulnerability across species. Similarly, integrated vulnerability metrics varied greatly across species. A comparison showed that some species had vulnerabilities that were similar between the two metrics, while other species’ vulnerabilities varied substantially between the two metrics. These differences primarily resulted from cases where the most vulnerable stage had a low relative weight. We compare these methods and explore circumstances where each method may be appropriate. PMID:27416031

Extending Vulnerability Assessment to Include Life Stages Considerations.

PubMed

Hodgson, Emma E; Essington, Timothy E; Kaplan, Isaac C

2016-01-01

Species are experiencing a suite of novel stressors from anthropogenic activities that have impacts at multiple scales. Vulnerability assessment is one tool to evaluate the likely impacts that these stressors pose to species so that high-vulnerability cases can be identified and prioritized for monitoring, protection, or mitigation. Commonly used semi-quantitative methods lack a framework to explicitly account for differences in exposure to stressors and organism responses across life stages. Here we propose a modification to commonly used spatial vulnerability assessment methods that includes such an approach, using ocean acidification in the California Current as an illustrative case study. Life stage considerations were included by assessing vulnerability of each life stage to ocean acidification and were used to estimate population vulnerability in two ways. We set population vulnerability equal to: (1) the maximum stage vulnerability and (2) a weighted mean across all stages, with weights calculated using Lefkovitch matrix models. Vulnerability was found to vary across life stages for the six species explored in this case study: two krill-Euphausia pacifica and Thysanoessa spinifera, pteropod-Limacina helicina, pink shrimp-Pandalus jordani, Dungeness crab-Metacarcinus magister and Pacific hake-Merluccius productus. The maximum vulnerability estimates ranged from larval to subadult and adult stages with no consistent stage having maximum vulnerability across species. Similarly, integrated vulnerability metrics varied greatly across species. A comparison showed that some species had vulnerabilities that were similar between the two metrics, while other species' vulnerabilities varied substantially between the two metrics. These differences primarily resulted from cases where the most vulnerable stage had a low relative weight. We compare these methods and explore circumstances where each method may be appropriate.

Improving vulnerability models: lessons learned from a comparison between flood and earthquake assessments

NASA Astrophysics Data System (ADS)

de Ruiter, Marleen; Ward, Philip; Daniell, James; Aerts, Jeroen

2017-04-01

In a cross-discipline study, an extensive literature review has been conducted to increase the understanding of vulnerability indicators used in both earthquake- and flood vulnerability assessments, and to provide insights into potential improvements of earthquake and flood vulnerability assessments. It identifies and compares indicators used to quantitatively assess earthquake and flood vulnerability, and discusses their respective differences and similarities. Indicators have been categorized into Physical- and Social categories, and further subdivided into (when possible) measurable and comparable indicators. Physical vulnerability indicators have been differentiated to exposed assets such as buildings and infrastructure. Social indicators are grouped in subcategories such as demographics, economics and awareness. Next, two different vulnerability model types have been described that use these indicators: index- and curve-based vulnerability models. A selection of these models (e.g. HAZUS) have been described, and compared on several characteristics such as temporal- and spatial aspects. It appears that earthquake vulnerability methods are traditionally strongly developed towards physical attributes at an object scale and used in vulnerability curve models, whereas flood vulnerability studies focus more on indicators applied to aggregated land-use scales. Flood risk studies could be improved using approaches from earthquake studies, such as incorporating more detailed lifeline and building indicators, and developing object-based vulnerability curve assessments of physical vulnerability, for example by defining building material based flood vulnerability curves. Related to this, is the incorporation of time of the day based building occupation patterns (at 2am most people will be at home while at 2pm most people will be in the office). Earthquake assessments could learn from flood studies when it comes to the refined selection of social vulnerability indicators. Based on the lessons obtained in this study, we recommend future studies to further explore cross-hazard studies.

Factor weighting in DRASTIC modelling for assessing the groundwater vulnerability in Salatiga groundwater basin, Central Java Province, Indonesia

NASA Astrophysics Data System (ADS)

Kesuma, D. A.; Purwanto, P.; Putranto, T. T.; Rahmani, T. P. D.

2017-06-01

The increase in human population as well as area development in Salatiga Groundwater Basin, Central Java Province, will increase the potency of groundwater contamination in that area. Groundwater quality, especially the shallow groundwater, is very vulnerable to the contamination from industrial waste, fertilizer/agricultural waste, and domestic waste. The first step in the conservation of groundwater quality is by conducting the mapping of the groundwater vulnerability zonation against the contamination. The result of this research was groundwater vulnerability map which showed the areas vulnerable to the groundwater contamination. In this study, groundwater vulnerability map was assessed based on the DRASTIC Method and was processed spatially using Geographic Information System. The DRASTIC method is used to assess the level of groundwater vulnerability based on weighting on seven parameters, which are: depth to the water table (D), recharge (R), aquifer material (A), soil media (S), topography (T), impact of vadose zone (I), and hydraulic conductivity (C). The higher the DRASTIC Index will result in the higher vulnerability level of groundwater contamination in that area. The DRASTIC Indexes in the researched area were 85 - 100 (low vulnerability level), 101 -120 (low to moderate vulnerability level), 121 - 140 (moderate vulnerability level), 141 - 150, (moderate to high vulnerability level), and 151 - 159 (high vulnerability level). The output of this study can be used by local authority as a tool for consideration to arrange the policy for sustainable area development, especially the development in an area affecting the quality of Salatiga Groundwater Basin.

Index based regional vulnerability assessment to cyclones hazards of coastal area of Bangladesh

NASA Astrophysics Data System (ADS)

Mohammad, Q. A.; Kervyn, M.; Khan, A. U.

2016-12-01

Cyclone, storm surge, coastal flooding, salinity intrusion, tornado, nor'wester, and thunderstorms are the listed natural hazards in the coastal areas of Bangladesh. Bangladesh was hit by devastating cyclones in 1970, 1991, 2007, 2009, and 2016. Intensity and frequency of natural hazards in the coastal area are likely to increase in future due to climate change. Risk assessment is one of the most important steps of disaster risk reduction. As a climate change victim nation, Bangladesh claims compensation from green climate fund. It also created its own climate funds. It is therefore very important to assess vulnerability of the coast of Bangladesh to natural hazards for efficient allocation of financial investment to support the national risk reduction. This study aims at identifying the spatial variations in factors contributing to vulnerability of the coastal inhabitants of Bangladesh to natural hazards. An exploratory factor analysis method has been used to assess the vulnerability at each local administrative unit. The 141 initially selected 141 socio-economic indicators were reduced to 41 by converting some of them to meaningful widely accepted indicators and removing highly correlated indicators. Principle component analysis further reduced 41 indicators to 13 dimensions which explained 79% of total variation. PCA dimensions show three types of characteristics of the people that may lead people towards vulnerability. They are (a) demographic, education and job opportunities, (b) access to basic needs and facilities, and (c) special needs people. Vulnerability maps of the study area has been prepared by weighted overlay of the dimensions. Study revealed that 29 and 8 percent of total coastal area are very high and high vulnerable to natural hazards respectively. These are distributed along sea boundary and major rivers. Comparison of this spatial distribution with the capacities to face disaster show that highly vulnerable areas are well covered by cyclone shelters but are not the zone with the most resistant building and the most dense road networks. The findings will be helpful for policy makers to initiate, plan and implement short, medium and long term DRR strategies.

Continental patterns of submarine groundwater discharge reveal coastal vulnerabilities.

PubMed

Sawyer, Audrey H; David, Cédric H; Famiglietti, James S

2016-08-12

Submarine groundwater discharge (SGD) delivers water and dissolved chemicals from continents to oceans, and its spatial distribution affects coastal water quality. Unlike rivers, SGD is broadly distributed and relatively difficult to measure, especially at continental scales. We present spatially resolved estimates of fresh (land-derived) SGD for the contiguous United States based on historical climate records and high-resolution hydrographic data. Climate controls regional patterns in fresh SGD, while coastal drainage geometry imparts strong local variability. Because the recharge zones that contribute fresh SGD are densely populated, the quality and quantity of fresh SGD are both vulnerable to anthropogenic disturbance. Our analysis unveils hot spots for contaminant discharge to marine waters and saltwater intrusion into coastal aquifers. Copyright © 2016, American Association for the Advancement of Science.

Application of the new scenario framework for climate change research: Future social vulnerability in large urban areas

NASA Astrophysics Data System (ADS)

Rohat, Guillaume; Flacke, Johannes; Dao, Hy

2016-04-01

It is by now widely acknowledged that future social vulnerability to climate change depends on both future climate state and future socio-economic conditions. Nevertheless, while most of the vulnerability assessments are using climate projections, the integration of socio-economic projections into the assessment of vulnerabilities has been very limited. Up to now, the vast majority of vulnerability assessments has been using current socio-economic conditions, hence has failed to consider the influence of socio-economic developments in the construction of vulnerability. To enhance the use of socio-economic projections into climate change impacts, adaptation and vulnerability assessments, the climate change research community has been recently involved in the development of a new model for creating scenarios that integrate future changes in climate as well as in society, known under the name of the new scenario framework for climate change research. This theoretical framework is made of a set of alternative futures of socio-economic developments (known as shared socio-economic pathways - SSPs), a set of hypothesis about future climate policies (known as shared policy assumptions - SPAs) and a set of greenhouse gas concentration trajectories (known as representative concentration pathways - RCPs), which are all combined into a scenario matrix architecture (SMA) whose aim is to facilitate the use of this framework. Despite calls by the climate change research community for the use of this conceptual framework in impacts, adaptation and vulnerability research, its use and its assessment has been very limited. Focusing on case-studies (i.e. specific cities as well as specific climate impacts and their associated human exposures and vulnerabilities), the study presented here will attempt to operationalize this theoretical framework for the assessment of future social vulnerability in large urban areas. A particular attention will be paid to less advanced and more vulnerable countries in the global south. We will discuss how this framework can be implemented for large urban agglomerations. To do so, we will examine: (i) by what means globally-developed SSPs can be extended into sector-specific and location-specific socio-economic development scenarios, (ii) in what manner the quantification of key socio-economic indicators (in accordance with the different SSPs), coupled with regional climate projections under different RCPs, can lead to a quantitative and reliable assessment of the evolution of future social vulnerability, and (iii) to which extent the SMA, i.e. the combination of extended SSPs, regional climate projections (under different RCPs) and various locally-developed SPAs, can answer some of the key questions regarding climate change adaptation policies, from a vulnerability perspective.

Surface Enhanced Raman Spectroscopy (SERS) methods for endpoint and real-time quantification of miRNA assays

NASA Astrophysics Data System (ADS)

Restaino, Stephen M.; White, Ian M.

2017-03-01

Surface Enhanced Raman spectroscopy (SERS) provides significant improvements over conventional methods for single and multianalyte quantification. Specifically, the spectroscopic fingerprint provided by Raman scattering allows for a direct multiplexing potential far beyond that of fluorescence and colorimetry. Additionally, SERS generates a comparatively low financial and spatial footprint compared with common fluorescence based systems. Despite the advantages of SERS, it has remained largely an academic pursuit. In the field of biosensing, techniques to apply SERS to molecular diagnostics are constantly under development but, most often, assay protocols are redesigned around the use of SERS as a quantification method and ultimately complicate existing protocols. Our group has sought to rethink common SERS methodologies in order to produce translational technologies capable of allowing SERS to compete in the evolving, yet often inflexible biosensing field. This work will discuss the development of two techniques for quantification of microRNA, a promising biomarker for homeostatic and disease conditions ranging from cancer to HIV. First, an inkjet-printed paper SERS sensor has been developed to allow on-demand production of a customizable and multiplexable single-step lateral flow assay for miRNA quantification. Second, as miRNA concentrations commonly exist in relatively low concentrations, amplification methods (e.g. PCR) are therefore required to facilitate quantification. This work presents a novel miRNA assay alongside a novel technique for quantification of nuclease driven nucleic acid amplification strategies that will allow SERS to be used directly with common amplification strategies for quantification of miRNA and other nucleic acid biomarkers.

The precipitationshed as a tool for tracing hydrological tele-connections among social-ecological systems

NASA Astrophysics Data System (ADS)

Keys, Patrick; Wang-Erlandsson, Lan; Gordon, Line

2016-04-01

In hydrology, there are many spatial units of analysis that allow for the quantification of relevant processes, including the river basin (surface water) and the capture zone (groundwater). Our research provides a new unit that can be applied to atmospheric water, called the precipitationshed. We define the precipitationshed as the upwind land and ocean area that contributes evaporation to a given location's precipitation. Building off of much existing scholarly work, we have advanced the field of moisture recycling by defining the method for calculating precipitationshed boundaries, and through our analysis have found that there are persistent inter-annual sources of moisture for many places on the planet. The precipitationshed represents a new way of thinking about hydrological tele-connections across a landscape, region, or continent. We describe three ways in which the precipitationshed has been applied to important societal issues: the vulnerability of rainfall dependent societies, the analysis of moisture recycling as an ecosystem service, and the relationship between dry and wet year rainfall in megacity precipitationsheds. Our analysis reveals some important insights. First, the pressures of demographic and land-use change within the precipitationsheds of many agricultural regions globally potentially increases their vulnerability to future reductions in rainfall. Second, by classifying moisture recycling as an ecosystem service, we are able to better understand how hitherto unconnected places in a region are in fact geophysically connected. Third, we find that many megacities receive more dry season rainfall from land than in wet years, suggesting that these urban areas are particularly reliant, and exposed, to the land-use decisions that take place in their precipitationsheds. In this presentation, we aim to discuss the strengths and weaknesses of the precipitationshed concept, the challenges ahead for understanding how society can use the concept, and what important scientific questions remain to be understood.

Remotely Sensed Quantitative Drought Risk Assessment in Vulnerable Agroecosystems

NASA Astrophysics Data System (ADS)

Dalezios, N. R.; Blanta, A.; Spyropoulos, N. V.

2012-04-01

Hazard may be defined as a potential threat to humans and their welfare and risk (or consequence) as the probability of a hazard occurring and creating loss. Drought is considered as one of the major natural hazards with significant impact to agriculture, environment, economy and society. This paper deals with drought risk assessment, which the first step designed to find out what the problems are and comprises three distinct steps, namely risk identification, risk management which is not covered in this paper, there should be a fourth step to address the need for feedback and to take post-audits of all risk assessment exercises. In particular, quantitative drought risk assessment is attempted by using statistical methods. For the qualification of drought, the Reconnaissance Drought Index (RDI) is employed, which is a new index based on hydrometeorological parameters, such as precipitation and potential evapotranspiration. The remotely sensed estimation of RDI is based on NOA-AVHRR satellite data for a period of 20 years (1981-2001). The study area is Thessaly, central Greece, which is a drought-prone agricultural region characterized by vulnerable agriculture. Specifically, the undertaken drought risk assessment processes are specified as follows: 1. Risk identification: This step involves drought quantification and monitoring based on remotely sensed RDI and extraction of several features such as severity, duration, areal extent, onset and end time. Moreover, it involves a drought early warning system based on the above parameters. 2. Risk estimation: This step includes an analysis of drought severity, frequency and their relationships. 3. Risk evaluation: This step covers drought evaluation based on analysis of RDI images before and after each drought episode, which usually lasts one hydrological year (12month). The results of these three-step drought assessment processes are considered quite satisfactory in a drought-prone region such as Thessaly in central Greece. Moreover, remote sensing has proven very effective in delineating spatial variability and features in drought monitoring and assessment.

Quantification of Cannabinoid Content in Cannabis

NASA Astrophysics Data System (ADS)

Tian, Y.; Zhang, F.; Jia, K.; Wen, M.; Yuan, Ch.

2015-09-01

Cannabis is an economically important plant that is used in many fields, in addition to being the most commonly consumed illicit drug worldwide. Monitoring the spatial distribution of cannabis cultivation and judging whether it is drug- or fiber-type cannabis is critical for governments and international communities to understand the scale of the illegal drug trade. The aim of this study was to investigate whether the cannabinoids content in cannabis could be spectrally quantified using a spectrometer and to identify the optimal wavebands for quantifying the cannabinoid content. Spectral reflectance data of dried cannabis leaf samples and the cannabis canopy were measured in the laboratory and in the field, respectively. Correlation analysis and the stepwise multivariate regression method were used to select the optimal wavebands for cannabinoid content quantification based on the laboratory-measured spectral data. The results indicated that the delta-9-tetrahydrocannabinol (THC) content in cannabis leaves could be quantified using laboratory-measured spectral reflectance data and that the 695 nm band is the optimal band for THC content quantification. This study provides prerequisite information for designing spectral equipment to enable immediate quantification of THC content in cannabis and to discriminate drug- from fiber-type cannabis based on THC content quantification in the field.

Hydrologic vulnerability of tribal reservation lands across the U.S.

NASA Astrophysics Data System (ADS)

Jones, C., Jr.; Leibowitz, S. G.; Sawicz, K. A.; Comeleo, R. L.; Stratton, L. E.

2017-12-01

We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability to climate of the United States (U.S.) with special emphasis on tribal lands. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating a retrospective analysis of historical climate and hydrology into the HL approach, comparing this baseline of variability with future projections of temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of the water surplus. Projections that are not within two standard deviations of the historical decadal average contribute to the vulnerability index for each metric. This allows stakeholders and/or water resource managers to understand the potential impacts of future conditions. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices across the U.S. including all tribal reservations. Precipitation vulnerability is not as spatially-uniform as temperature. Most areas with snow are projected to experience significant changes in future snow accumulation. The seasonality vulnerability map shows that mountainous areas in the West are most prone to changes in seasonality. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability for disadvantaged groups across the U.S. By combining the HL concept and climate vulnerability analyses, we provide an approach that can assist tribal resource managers to perform vulnerability assessments and adaptation plans, which is a major priority for the tribes nationwide.

Examining the impact of lahars on buildings using numerical modelling

NASA Astrophysics Data System (ADS)

Mead, Stuart R.; Magill, Christina; Lemiale, Vincent; Thouret, Jean-Claude; Prakash, Mahesh

2017-05-01

Lahars are volcanic flows containing a mixture of fluid and sediment which have the potential to cause significant damage to buildings, critical infrastructure and human life. The extent of this damage is controlled by properties of the lahar, location of elements at risk and susceptibility of these elements to the lahar. Here we focus on understanding lahar-induced building damage. Quantification of building damage can be difficult due to the complexity of lahar behaviour (hazard), varying number and type of buildings exposed to the lahar (exposure) and the uncertain susceptibility of buildings to lahar impacts (vulnerability). In this paper, we quantify and examine the importance of lahar hazard, exposure and vulnerability in determining building damage with reference to a case study in the city of Arequipa, Peru. Numerical modelling is used to investigate lahar properties that are important in determining the inundation area and forces applied to buildings. Building vulnerability is quantified through the development of critical depth-pressure curves based on the ultimate bending moment of masonry structures. In the case study area, results suggest that building strength plays a minor role in determining overall building losses in comparison to the effects of building exposure and hydraulic characteristics of the lahar.

Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations

PubMed Central

2018-01-01

The quantification of changes in geomechanical properties due to chemical reactions is of paramount importance for geological subsurface utilisation, since mineral dissolution generally reduces rock stiffness. In the present study, the effective elastic moduli of two digital rock samples, the Fontainebleau and Bentheim sandstones, are numerically determined based on micro-CT images. Reduction in rock stiffness due to the dissolution of 10% calcite cement by volume out of the pore network is quantified for three synthetic spatial calcite distributions (coating, partial filling and random) using representative sub-cubes derived from the digital rock samples. Due to the reduced calcite content, bulk and shear moduli decrease by 34% and 38% in maximum, respectively. Total porosity is clearly the dominant parameter, while spatial calcite distribution has a minor impact, except for a randomly chosen cement distribution within the pore network. Moreover, applying an initial stiffness reduced by 47% for the calcite cement results only in a slightly weaker mechanical behaviour. Using the quantitative approach introduced here substantially improves the accuracy of predictions in elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in porosity and mineral distribution. PMID:29614776

Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations.

PubMed

Wetzel, Maria; Kempka, Thomas; Kühn, Michael

2018-04-01

The quantification of changes in geomechanical properties due to chemical reactions is of paramount importance for geological subsurface utilisation, since mineral dissolution generally reduces rock stiffness. In the present study, the effective elastic moduli of two digital rock samples, the Fontainebleau and Bentheim sandstones, are numerically determined based on micro-CT images. Reduction in rock stiffness due to the dissolution of 10% calcite cement by volume out of the pore network is quantified for three synthetic spatial calcite distributions (coating, partial filling and random) using representative sub-cubes derived from the digital rock samples. Due to the reduced calcite content, bulk and shear moduli decrease by 34% and 38% in maximum, respectively. Total porosity is clearly the dominant parameter, while spatial calcite distribution has a minor impact, except for a randomly chosen cement distribution within the pore network. Moreover, applying an initial stiffness reduced by 47% for the calcite cement results only in a slightly weaker mechanical behaviour. Using the quantitative approach introduced here substantially improves the accuracy of predictions in elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in porosity and mineral distribution.

Vulnerability of ground water to atrazine leaching in Kent County, Michigan

USGS Publications Warehouse

Holtschlag, D.J.; Luukkonen, C.L.

1997-01-01

A steady-state model of pesticide leaching through the unsaturated zone was used with readily available hydrologic, lithologic, and pesticide characteristics to estimate the vulnerability of the near-surface aquifer to atrazine contamination from non-point sources in Kent County, Michigan. The modelcomputed fraction of atrazine remaining at the water table, RM, was used as the vulnerability criterion; time of travel to the water table also was computed. Model results indicate that the average fraction of atrazine remaining at the water table was 0.039 percent; the fraction ranged from 0 to 3.6 percent. Time of travel of atrazine from the soil surface to the water table averaged 17.7 years and ranged from 2.2 to 118 years.Three maps were generated to present three views of the same atrazine vulnerability characteristics using different metrics (nonlinear transformations of the computed fractions remaining). The metrics were chosen because of the highly (right) skewed distribution of computed fractions. The first metric, rm = RMλ (where λ was 0.0625), depicts a relatively uniform distribution of vulnerability across the county with localized areas of high and low vulnerability visible. The second metric, rmλ-0.5, depicts about one-half the county at low vulnerability with discontinuous patterns of high vulnerability evident. In the third metric, rmλ-1.0 (RM), more than 95 percent of the county appears to have low vulnerability; small, distinct areas of high vulnerability are present.Aquifer vulnerability estimates in the RM metric were used with a steady-state, uniform atrazine application rate to compute a potential concentration of atrazine in leachate reaching the water table. The average estimated potential atrazine concentration in leachate at the water table was 0.16 μg/L (micrograms per liter) in the model area; estimated potential concentrations ranged from 0 to 26 μg/L. About 2 percent of the model area had estimated potential atrazine concentrations in leachate at the water table that exceeded the USEPA (U.S. Environmental Protection Agency) maximum contaminant level of 3 μg/L.Uncertainty analyses were used to assess effects of parameter uncertainty and spatial interpolation error on the variability of the estimated fractions of atrazine remaining at the water table. Results of Monte Carlo simulations indicate that parameter uncertainty is associated with a standard error of 0.0875 in the computed fractions (in the rm metric). Results of kriging analysis indicate that errors in spatial interpolation are associated with a standard error of 0.146 (in the rm metric). Thus, uncertainty in fractions remaining is primarily associated with spatial interpolation error, which can be reduced by increasing the density of points where the leaching model is applied.A sensitivity analysis indicated which of 13 hydrologic, lithologic, and pesticide characteristics were influential in determining fractions of atrazine remaining at the water table. Results indicate that fractions remaining are most sensitive to the unit changes in pesticide half life and in organic-carbon content in soils and unweathered rocks, and least sensitive to infiltration rates.The leaching model applied in this report provides an estimate of the vulnerability of the near-surface aquifer in Kent County to contamination by atrazine. The vulnerability estimate is related to water-quality criteria developed by the USEPA to help assess potential risks from atrazine to the near-surface aquifer. However, atrazine accounts for only 28 percent of the herbicide use in the county; additional potential for contamination exists from other pesticides and pesticide metabolites. Therefore, additional work is needed to develop a comprehensive understanding of the relative risks associated with specific pesticides. The modeling approach described in this report provides a technique for estimating relative vulnerabilities to specific pesticides and for helping to assess potential risks.

Conception of a method for the creation of volcanic risk index maps

NASA Astrophysics Data System (ADS)

Bion, P.; Van Wyk de Vries, B.; Valentine, G.

2012-04-01

Risk index maps are a variant of risk maps, having the advantage of containing unique kinds of information - levels of risk spatially represented - and can therefore be a more effective communication tool than traditional risk maps. Nevertheless, despite their apparent simplicity, their achievement is the result of a complex risk analysis, requiring the consideration of multidisciplinary indicators, expressing different parameters of the physical and human dimensions of the environment and their interactions. The risk index is obtained in three main stages: the definition of hazard and vulnerability indicators, the transformation of the indicators into subindices through mathematical processes (formulation, standardization, weighting), and the combination of the subindices into a final index. As of now, only few attempts of risk quantification have been done, related to landslide, flood or seismic hazards, and those linked to volcanic hazards are very incomplete because of the specificities and complexities of these kinds of events and their effects. Volcanic hazards have the particularity of being of different types, moreover all events can combine together or be combined with other external events (e.g. meteorological), and they can reach and therefore affect extensive areas by different phenomena. The methodology developed here assesses risk levels in regions potentially impacted by volcanic hazards. It incorporates volcanic hazard specificities and nuances of "vulnerability" by integrating the diversity of the environmental components. It analyses the natural and human strengths, weaknesses, opportunities and threats, which are located within the areas potentially "at risk". Consequently, it considers negative but also positive indicators (respectively aggravating and improving the potential consequences), which can be internal but also external to the volcanic hazards. The approach also considers a temporal variability of the events and their direct or indirect associated effects. The developed approach tends to be especially aimed at urban planners, who would possess a new fundamental tool for organizing the territories located "nearby" volcanoes, in which population density is continually increasing. The volcanic risk index maps would give indications on the areas with the highest risk level, and the urban planners would also be able to determine the elements causing such level. This would lead them to the possibility of proposing recommendations and adequate measures to participate to the reduction of vulnerability, in particular in limiting the exposure and the impacts associated with the volcanic hazards, which would consequently reduce the volcanic risks.

Accounting for adaptive capacity and uncertainty in assessments of species’ climate-change vulnerability

USGS Publications Warehouse

Wade, Alisa A.; Hand, Brian K.; Kovach, Ryan; Luikart, Gordon; Whited, Diane; Muhlfeld, Clint C.

2016-01-01

Climate change vulnerability assessments (CCVAs) are valuable tools for assessing species’ vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. Here, we provide a more comprehensive CCVA approach that incorporates all three elements used for assessing species’ climate change vulnerability: exposure, sensitivity, and adaptive capacity. We illustrate our approach using case studies of two threatened salmonids with different life histories – anadromous steelhead trout (Oncorhynchus mykiss) and non-anadromous bull trout (Salvelinus confluentus) – within the Columbia River Basin, USA. We identified general patterns of high vulnerability in low-elevation and southernmost habitats for both species. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the two species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multi-species conservation. Our results highlight how CCVAs should be considered within a broader conceptual and computational framework for refining hypotheses, guiding research, and comparing plausible scenarios of species’ vulnerability for ongoing and projected climate change.

Global-scale river flood vulnerability in the last 50 years.

PubMed

Tanoue, Masahiro; Hirabayashi, Yukiko; Ikeuchi, Hiroaki

2016-10-26

The impacts of flooding are expected to rise due to population increases, economic growth and climate change. Hence, understanding the physical and spatiotemporal characteristics of risk drivers (hazard, exposure and vulnerability) is required to develop effective flood mitigation measures. Here, the long-term trend in flood vulnerability was analysed globally, calculated from the ratio of the reported flood loss or damage to the modelled flood exposure using a global river and inundation model. A previous study showed decreasing global flood vulnerability over a shorter period using different disaster data. The long-term analysis demonstrated for the first time that flood vulnerability to economic losses in upper-middle, lower-middle and low-income countries shows an inverted U-shape, as a result of the balance between economic growth and various historical socioeconomic efforts to reduce damage, leading to non-significant upward or downward trends. We also show that the flood-exposed population is affected by historical changes in population distribution, with changes in flood vulnerability of up to 48.9%. Both increasing and decreasing trends in flood vulnerability were observed in different countries, implying that population growth scenarios considering spatial distribution changes could affect flood risk projections.

Global-scale river flood vulnerability in the last 50 years

PubMed Central

Tanoue, Masahiro; Hirabayashi, Yukiko; Ikeuchi, Hiroaki

2016-01-01

The impacts of flooding are expected to rise due to population increases, economic growth and climate change. Hence, understanding the physical and spatiotemporal characteristics of risk drivers (hazard, exposure and vulnerability) is required to develop effective flood mitigation measures. Here, the long-term trend in flood vulnerability was analysed globally, calculated from the ratio of the reported flood loss or damage to the modelled flood exposure using a global river and inundation model. A previous study showed decreasing global flood vulnerability over a shorter period using different disaster data. The long-term analysis demonstrated for the first time that flood vulnerability to economic losses in upper-middle, lower-middle and low-income countries shows an inverted U-shape, as a result of the balance between economic growth and various historical socioeconomic efforts to reduce damage, leading to non-significant upward or downward trends. We also show that the flood-exposed population is affected by historical changes in population distribution, with changes in flood vulnerability of up to 48.9%. Both increasing and decreasing trends in flood vulnerability were observed in different countries, implying that population growth scenarios considering spatial distribution changes could affect flood risk projections. PMID:27782160

GIS Analysis of Changes in Ecological Vulnerability Using a SPCA Model in the Loess Plateau of Northern Shaanxi, China

PubMed Central

Kang, Hou; Xuxiang, Li; Jing, Zhang

2015-01-01

Changes in ecological vulnerability were analyzed for Northern Shaanxi, China using a geographic information system (GIS). An evaluation model was developed using a spatial principal component analysis (SPCA) model containing land use, soil erosion, topography, climate, vegetation and social economy variables. Using this model, an ecological vulnerability index was computed for the research region. Using natural breaks classification (NBC), the evaluation results were divided into five types: potential, slight, light, medium and heavy. The results indicate that there is greater than average optimism about the conditions of the study region, and the ecological vulnerability index (EVI) of the southern eight counties is lower than that of the northern twelve counties. From 1997 to 2011, the ecological vulnerability index gradually decreased, which means that environmental security was gradually enhanced, although there are still some places that have gradually deteriorated over the past 15 years. In the study area, government and economic factors and precipitation are the main reasons for the changes in ecological vulnerability. PMID:25898407

Mapping Vulnerability to Disasters in Latin America and the Caribbean, 1900-2007

USGS Publications Warehouse

Maynard-Ford, Miriam C.; Phillips, Emily C.; Chirico, Peter G.

2008-01-01

The vulnerability of a population and its infrastructure to disastrous events is a factor of both the probability of a hazardous event occurring and the community's ability to cope with the resulting impacts. Therefore, the ability to accurately identify vulnerable populations and places in order to prepare for future hazards is of critical importance for disaster mitigation programs. This project created maps of higher spatial resolution of vulnerability to disaster in Latin America and the Caribbean from 1900 to 2007 by mapping disaster data by first-level administrative boundaries with the objective of identifying geographic trends in regional occurrences of disasters and vulnerable populations. The method of mapping by administrative level is an improvement on displaying and analyzing disasters at the country level and shows the relative intensity of vulnerability within and between countries in the region. Disaster mapping at the country level produces only a basic view of which countries experience various types of natural disasters. Through disaggregation, the data show which geographic areas of these countries, including populated areas, are historically most susceptible to different hazard types.

Identification and ranking of environmental threats with ecosystem vulnerability distributions.

PubMed

Zijp, Michiel C; Huijbregts, Mark A J; Schipper, Aafke M; Mulder, Christian; Posthuma, Leo

2017-08-24

Responses of ecosystems to human-induced stress vary in space and time, because both stressors and ecosystem vulnerabilities vary in space and time. Presently, ecosystem impact assessments mainly take into account variation in stressors, without considering variation in ecosystem vulnerability. We developed a method to address ecosystem vulnerability variation by quantifying ecosystem vulnerability distributions (EVDs) based on monitoring data of local species compositions and environmental conditions. The method incorporates spatial variation of both abiotic and biotic variables to quantify variation in responses among species and ecosystems. We show that EVDs can be derived based on a selection of locations, existing monitoring data and a selected impact boundary, and can be used in stressor identification and ranking for a region. A case study on Ohio's freshwater ecosystems, with freshwater fish as target species group, showed that physical habitat impairment and nutrient loads ranked highest as current stressors, with species losses higher than 5% for at least 6% of the locations. EVDs complement existing approaches of stressor assessment and management, which typically account only for variability in stressors, by accounting for variation in the vulnerability of the responding ecosystems.

Assessment of well vulnerability for groundwater source protection based on a solute transport model: a case study from Jilin City, northeast China

NASA Astrophysics Data System (ADS)

Huan, Huan; Wang, Jinsheng; Lai, Desheng; Teng, Yanguo; Zhai, Yuanzheng

2015-05-01

Well vulnerability assessment is essential for groundwater source protection. A quantitative approach to assess well vulnerability in a well capture zone is presented, based on forward solute transport modeling. This method was applied to three groundwater source areas (Jiuzhan, Hadawan and Songyuanhada) in Jilin City, northeast China. The ratio of the maximum contaminant concentration at the well to the released concentration at the contamination source ( c max/ c 0) was determined as the well vulnerability indicator. The results indicated that well vulnerability was higher close to the pumping well. The well vulnerability in each groundwater source area was low. Compared with the other two source areas, the cone of depression at Jiuzhan resulted in higher spatial variability of c max/ c 0 and lower minimum c max/ c 0 by three orders of magnitude. Furthermore, a sensitivity analysis indicated that the denitrification rate in the aquifer was the most sensitive with respect to well vulnerability. A process to derive a NO3-N concentration at the pumping well is presented, based on determining the maximum nitrate loading limit to satisfy China's drinking-water quality standards. Finally, the advantages, disadvantages and prospects for improving the precision of this well vulnerability assessment approach are discussed.

Assessing intrinsic and specific vulnerability models ability to indicate groundwater vulnerability to groups of similar pesticides: A comparative study

USGS Publications Warehouse

Douglas, Steven; Dixon, Barnali; Griffin, Dale W.

2018-01-01

With continued population growth and increasing use of fresh groundwater resources, protection of this valuable resource is critical. A cost effective means to assess risk of groundwater contamination potential will provide a useful tool to protect these resources. Integrating geospatial methods offers a means to quantify the risk of contaminant potential in cost effective and spatially explicit ways. This research was designed to compare the ability of intrinsic (DRASTIC) and specific (Attenuation Factor; AF) vulnerability models to indicate groundwater vulnerability areas by comparing model results to the presence of pesticides from groundwater sample datasets. A logistic regression was used to assess the relationship between the environmental variables and the presence or absence of pesticides within regions of varying vulnerability. According to the DRASTIC model, more than 20% of the study area is very highly vulnerable. Approximately 30% is very highly vulnerable according to the AF model. When groundwater concentrations of individual pesticides were compared to model predictions, the results were mixed. Model predictability improved when concentrations of the group of similar pesticides were compared to model results. Compared to the DRASTIC model, the AF model more accurately predicts the distribution of the number of contaminated wells within each vulnerability class.

Assessing Method to Identifying Water Resilience Against Natural and Climate Change Hazards.

NASA Astrophysics Data System (ADS)

Amril, Rofi; Maryono

2018-02-01

A geographic region may become vulnerable toward water resources in a variety of ways. Common issues arise when man-made infrastructure such as housing, industrial, agriculture and other spatial land use policy implementation exceeds more than desired level. Vulnerability of a region due to water resources could be interpreted as the inability of the region to sustaining economic and social activity associated to socio-economic water availability. This study assess four aspects of water resilience: water quantity, water distribution, water quality, and water requirements. Literature review then followed by interview with academic expert used as method of study. This study found that four aspect of water vulnerability mostly have been applied to asses water resource vulnerability. Each aspect have a specific characteristic and could be define more specific and detail indicator according to the local content.

Assessing community vulnerabilities to natural hazards on the Island of Hawaii

NASA Astrophysics Data System (ADS)

Nishioka, Chris; Delparte, Donna

2010-05-01

The island of Hawaii is susceptible to numerous natural hazards such as tsunamis, flooding, lava flow, earthquakes, hurricanes, landslides, wildfires and storm surge. The impact of a natural disaster on the island's communities has the potential to endanger peoples' lives and threaten critical infrastructure, homes, businesses and economic drivers such as tourism. A Geographic Information System (GIS) has the ability to assess community vulnerabilities by examining the spatial relationships between hazard zones, socioeconomic infrastructure and demographic data. By drawing together existing datasets, GIS was used to examine a number of community vulnerabilities. Key areas of interest were government services, utilities, property assets, industry and transportation. GIS was also used to investigate population dynamics in hazard zones. Identification of community vulnerabilities from GIS analysis can support mitigation measures and assist planning and response measures to natural hazards.

Chronic Glucocorticoids Increase Hippocampal Vulnerability to Neurotoxicity under Conditions That Produce CA3 Dendritic Retraction But Fail to Impair Spatial Recognition Memory

PubMed Central

Conrad, Cheryl D.; McLaughlin, Katie J.; Harman, James S.; Foltz, Cainan; Wieczorek, Lindsay; Lightner, Elizabeth; Wright, Ryan L.

2007-01-01

We previously found that chronic stress conditions producing CA3 dendritic retraction and spatial memory deficits make the hippocampus vulnerable to the neurotoxin ibotenic acid (IBO). The purpose of this study was to determine whether exposure to chronic corticosterone (CORT) under conditions that produce CA3 dendritic retraction would enhance CA3 susceptibility to IBO. Male Sprague Dawley rats were chronically treated for 21 d with CORT in drinking water (400 μg/ml), and half were given daily injections of phenytoin (40 mg/kg), an antiepileptic drug that prevents CA3 dendritic retraction. Three days after treatments stopped, IBO was infused into the CA3 region. Conditions producing CA3 dendritic retraction (CORT and vehicle) exacerbated IBO-induced CA3 damage compared with conditions in which CA3 dendritic retraction was not observed (vehicle and vehicle, vehicle and phenytoin, CORT and phenytoin). Additionally, spatial recognition memory was assessed using the Y-maze, revealing that conditions producing CA3 dendritic retraction failed to impair spatial recognition memory. Furthermore, CORT levels in response to a potentially mild stressor (injection and Y-maze exposure) stayed at basal levels and failed to differ among key groups (vehicle and vehicle, CORT and vehicle, CORT and phenytoin), supporting the interpretations that CORT levels were unlikely to have been elevated during IBO infusion and that the neuroprotective actions of phenytoin were not through CORT alterations. These data are the first to show that conditions with prolonged glucocorticoid elevations leading to structural changes in hippocampal dendritic arbors can make the hippocampus vulnerable to neurotoxic challenges. These findings have significance for many disorders with elevated glucocorticoids that include depression, schizophrenia, Alzheimer’s disease, and Cushing’s disease. PMID:17670974

The geography of mortality from Hurricane Katrina in New Orleans

NASA Astrophysics Data System (ADS)

Mutter, J. C.; Mara, V.; Jayaprakash, S.; None

2011-12-01

Hurricane Katrina was one of the highest mortality disasters in US history. Typical hurricanes of the same strength take very few lives. Katrina's mortality is exceeded only by the so-called Galveston Flood (a hurricane) of 1900 that occurred at a time when forecasting was poor and evacuation was possible only by train or horse. The levee failures in New Orleans were a major contributing factor unique to Katrina. An examination of the characteristics of mortality may give insight into the cause of the great scope of the tragedy and the special vulnerability of those who died. We examine the spatial aspects of mortality. The locations of deceased victims were matched with victim information including age, race and gender for approximately 800 victims (data from Louisiana Department of Health and Hospitals). From this we can analyze for spatial clustering of mortality. We know that Katrina took a particularly heavy toll on the elderly so we can analyze, for instance, whether the elderly were more likely to die in some locations than in others. Similarly, we analyze for gender and race against age (dividing age into five groups this gives 20 categories) as a factory in the geographic distribution of mortality as a way to recover measures of vulnerability. We can also correlate the spatial characteristics of mortality with underlying causes that might contribute to vulnerability. Data is available at a census block level on household income, poverty rates, education, home ownership, car ownership and a variety of other factors that can be correlated with the spatial mortality data. This allows for a multi-parameter estimation of factors that govern mortality in this unusually high mortality event.

Temporal scaling and spatial statistical analyses of groundwater level fluctuations

NASA Astrophysics Data System (ADS)

Sun, H.; Yuan, L., Sr.; Zhang, Y.

2017-12-01

Natural dynamics such as groundwater level fluctuations can exhibit multifractionality and/or multifractality due likely to multi-scale aquifer heterogeneity and controlling factors, whose statistics requires efficient quantification methods. This study explores multifractionality and non-Gaussian properties in groundwater dynamics expressed by time series of daily level fluctuation at three wells located in the lower Mississippi valley, after removing the seasonal cycle in the temporal scaling and spatial statistical analysis. First, using the time-scale multifractional analysis, a systematic statistical method is developed to analyze groundwater level fluctuations quantified by the time-scale local Hurst exponent (TS-LHE). Results show that the TS-LHE does not remain constant, implying the fractal-scaling behavior changing with time and location. Hence, we can distinguish the potentially location-dependent scaling feature, which may characterize the hydrology dynamic system. Second, spatial statistical analysis shows that the increment of groundwater level fluctuations exhibits a heavy tailed, non-Gaussian distribution, which can be better quantified by a Lévy stable distribution. Monte Carlo simulations of the fluctuation process also show that the linear fractional stable motion model can well depict the transient dynamics (i.e., fractal non-Gaussian property) of groundwater level, while fractional Brownian motion is inadequate to describe natural processes with anomalous dynamics. Analysis of temporal scaling and spatial statistics therefore may provide useful information and quantification to understand further the nature of complex dynamics in hydrology.

Putting vulnerability to climate change on the map: a review of approaches, benefits, and risks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Preston, Benjamin L

2011-01-01

There is growing demand among stakeholders across public and private institutions for spatially-explicit information regarding vulnerability to climate change at the local scale. However, the challenges associated with mapping the geography of climate change vulnerability are non-trivial, both conceptually and technically, suggesting the need for more critical evaluation of this practice. Here, we review climate change vulnerability mapping in the context of four key questions that are fundamental to assessment design. First, what are the goals of the assessment? A review of published assessments yields a range of objective statements that emphasize problem orientation or decision-making about adaptation actions. Second,more » how is the assessment of vulnerability framed? Assessments vary with respect to what values are assessed (vulnerability of what) and the underlying determinants of vulnerability that are considered (vulnerability to what). The selected frame ultimately influences perceptions of the primary driving forces of vulnerability as well as preferences regarding management alternatives. Third, what are the technical methods by which an assessment is conducted? The integration of vulnerability determinants into a common map remains an emergent and subjective practice associated with a number of methodological challenges. Fourth, who participates in the assessment and how will it be used to facilitate change? Assessments are often conducted under the auspices of benefiting stakeholders, yet many lack direct engagement with stakeholders. Each of these questions is reviewed in turn by drawing on an illustrative set of 45 vulnerability mapping studies appearing in the literature. A number of pathways for placing vulnerability« less

Time gradient for post-test vulnerability to scopolamine-induced amnesia following the initial acquisition session of a spatial reference memory task in mice.

PubMed

Toumane, A; Durkin, T P

1993-09-01

The time course for vulnerability to the amnestic effects of the cholinergic antagonist, scopolamine, during the postacquisition period has been investigated. We have examined the effects of post-test injections of scopolamine (1 mg/kg ip) given at different times from 30 s for up to 6 h following the end of the first acquisition session of a concurrent spatial discrimination (reference memory) protocol in an 8-arm radial maze on subsequent long-term (24 h) retention performance in C57BL/6 mice. Results show that the immediate (30 s) post-test injection of scopolamine-HCl on Day 1 produces marked perturbation (amnesia) of long-term retention as attested to by significant deficits in various indices of spatial discrimination performance gain on Day 2 as compared to control subjects injected either with scopolamine-MBr or saline. The severity of this scopolamine-induced amnesia declines only slightly as a function of the treatment period 30 s-3 h post-test. However, no evidence for amnesia is observed if scopolamine-HCl injections are delayed for 6 h postsession. This important latter observation attests to the absence of any significant proactive effects of scopolamine on the ability of mice to perform the retention test via possible long-term effects on attention, motivation, or locomotor performance. These results thus constitute evidence for the existence of a limited (30 s-3 h) time gradient for vulnerability of the early memory trace to disruption by scopolamine. The present results are discussed in relation to our previous direct neurochemical observations describing the differential time courses of intervention of the ascending septohippocampal and nBM-cortical cholinergic pathways in the postlearning period. In particular, the presently observed time window concerning post-test vulnerability to scopolamine-induced amnesia corresponds more closely to the time course of the acute activation of the nBM-cortical cholinergic pathway, induced by testing with the same spatial memory protocol as used in the present study in mice.

Diffuse optical microscopy for quantification of depth-dependent epithelial backscattering in the cervix

NASA Astrophysics Data System (ADS)

Bodenschatz, Nico; Lam, Sylvia; Carraro, Anita; Korbelik, Jagoda; Miller, Dianne M.; McAlpine, Jessica N.; Lee, Marette; Kienle, Alwin; MacAulay, Calum

2016-06-01

A fiber optic imaging approach is presented using structured illumination for quantification of almost pure epithelial backscattering. We employ multiple spatially modulated projection patterns and camera-based reflectance capture to image depth-dependent epithelial scattering. The potential diagnostic value of our approach is investigated on cervical ex vivo tissue specimens. Our study indicates a strong backscattering increase in the upper part of the cervical epithelium caused by dysplastic microstructural changes. Quantization of relative depth-dependent backscattering is confirmed as a potentially useful diagnostic feature for detection of precancerous lesions in cervical squamous epithelium.

Individual stress vulnerability is predicted by short-term memory and AMPA receptor subunit ratio in the hippocampus.

PubMed

Schmidt, Mathias V; Trümbach, Dietrich; Weber, Peter; Wagner, Klaus; Scharf, Sebastian H; Liebl, Claudia; Datson, Nicole; Namendorf, Christian; Gerlach, Tamara; Kühne, Claudia; Uhr, Manfred; Deussing, Jan M; Wurst, Wolfgang; Binder, Elisabeth B; Holsboer, Florian; Müller, Marianne B

2010-12-15

Increased vulnerability to aversive experiences is one of the main risk factors for stress-related psychiatric disorders as major depression. However, the molecular bases of vulnerability, on the one hand, and stress resilience, on the other hand, are still not understood. Increasing clinical and preclinical evidence suggests a central involvement of the glutamatergic system in the pathogenesis of major depression. Using a mouse paradigm, modeling increased stress vulnerability and depression-like symptoms in a genetically diverse outbred strain, and we tested the hypothesis that differences in AMPA receptor function may be linked to individual variations in stress vulnerability. Vulnerable and resilient animals differed significantly in their dorsal hippocampal AMPA receptor expression and AMPA receptor binding. Treatment with an AMPA receptor potentiator during the stress exposure prevented the lasting effects of chronic social stress exposure on physiological, neuroendocrine, and behavioral parameters. In addition, spatial short-term memory, an AMPA receptor-dependent behavior, was found to be predictive of individual stress vulnerability and response to AMPA potentiator treatment. Finally, we provide evidence that genetic variations in the AMPA receptor subunit GluR1 are linked to the vulnerable phenotype. Therefore, we propose genetic variations in the AMPA receptor system to shape individual stress vulnerability. Those individual differences can be predicted by the assessment of short-term memory, thereby opening up the possibility for a specific treatment by enhancing AMPA receptor function.

Development of EPA OTM 10 for Landfill Applications, Interim Report

EPA Science Inventory

Quantification of greenhouse gas emissions from area sources is of increasing importance. Due to the spatial extent and non homogenous nature of many area sources, assessment of fugitive emissions using traditional point sampling techniques can be problematic. To address this, th...

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

On-chip multiplexed solid-phase nucleic acid hybridization assay using spatial profiles of immobilized quantum dots and fluorescence resonance energy transfer.

PubMed

Noor, M Omair; Tavares, Anthony J; Krull, Ulrich J

2013-07-25

A microfluidic based solid-phase assay for the multiplexed detection of nucleic acid hybridization using quantum dot (QD) mediated fluorescence resonance energy transfer (FRET) is described herein. The glass surface of hybrid glass-polydimethylsiloxane (PDMS) microfluidic channels was chemically modified to assemble the biorecognition interface. Multiplexing was demonstrated using a detection system that was comprised of two colors of immobilized semi-conductor QDs and two different oligonucleotide probe sequences. Green-emitting and red-emitting QDs were paired with Cy3 and Alexa Fluor 647 (A647) labeled oligonucleotides, respectively. The QDs served as energy donors for the transduction of dye labeled oligonucleotide targets. The in-channel assembly of the biorecognition interface and the subsequent introduction of oligonucleotide targets was accomplished within minutes using a combination of electroosmotic flow and electrophoretic force. The concurrent quantification of femtomole quantities of two target sequences was possible by measuring the spatial coverage of FRET sensitized emission along the length of the channel. In previous reports, multiplexed QD-FRET hybridization assays that employed a ratiometric method for quantification had challenges associated with lower analytical sensitivity arising from both donor and acceptor dilution that resulted in reduced energy transfer pathways as compared to single-color hybridization assays. Herein, a spatial method for quantification that is based on in-channel QD-FRET profiles provided higher analytical sensitivity in the multiplexed assay format as compared to single-color hybridization assays. The selectivity of the multiplexed hybridization assays was demonstrated by discrimination between a fully-complementary sequence and a 3 base pair sequence at a contrast ratio of 8 to 1. Copyright © 2013 Elsevier B.V. All rights reserved.

Spatially Resolved MR-Compatible Doppler Ultrasound: Proof of Concept for Triggering of Diagnostic Quality Cardiovascular MRI for Function and Flow Quantification at 3T.

PubMed

Crowe, Lindsey Alexandra; Manasseh, Gibran; Chmielewski, Aneta; Hachulla, Anne-Lise; Speicher, Daniel; Greiser, Andreas; Muller, Hajo; de Perrot, Thomas; Vallee, Jean-Paul; Salomir, Rares

2018-02-01

We demonstrate the use of a magnetic-resonance (MR)-compatible ultrasound (US) imaging probe using spatially resolved Doppler for diagnostic quality cardiovascular MR imaging (MRI) as an initial step toward hybrid US/MR fetal imaging. A newly developed technology for a dedicated MR-compatible phased array ultrasound-imaging probe acquired pulsed color Doppler carotid images, which were converted in near-real time to a trigger signal for cardiac cine and flow quantification MRI. Ultrasound and MR data acquired simultaneously were interference free. Conventional electrocardiogram (ECG) and the proposed spatially resolved Doppler triggering were compared in 10 healthy volunteers. A synthetic "false-triggered" image was retrospectively processed using metric optimized gating (MOG). Images were scored by expert readers, and sharpness, cardiac function and aortic flow were quantified. Four-dimensional (4-D) flow (two volunteers) showed feasibility of Doppler triggering over a long acquisition time. Imaging modalities were compatible. US probe positioning was stable and comfortable. Image quality scores and quantified sharpness were statistically equal for Doppler- and ECG-triggering (p ). ECG-, Doppler-triggered, and MOG ejection fractions were equivalent (p ), with false-triggered values significantly lower (p < 0.0005). Aortic flow showed no difference between ECG- and Doppler-triggered and MOG (p > 0.05). 4-D flow quantification gave consistent results between ECG and Doppler triggering. We report interference-free pulsed color Doppler ultrasound during MR data acquisition. Cardiovascular MRI of diagnostic quality was successfully obtained with pulsed color Doppler triggering. The hardware platform could further enable advanced free-breathing cardiac imaging. Doppler ultrasound triggering is applicable where ECG is compromised due to pathology or interference at higher magnetic fields, and where direct ECG is impossible, i.e., fetal imaging.

County-level heat vulnerability of urban and rural residents in Tibet, China.

PubMed

Bai, Li; Woodward, Alistair; Cirendunzhu; Liu, Qiyong

2016-01-12

Tibet is especially vulnerable to climate change due to the relatively rapid rise of temperature over past decades. The effects on mortality and morbidity of extreme heat in Tibet have been examined in previous studies; no heat adaptation initiatives have yet been implemented. We estimated heat vulnerability of urban and rural populations in 73 Tibetan counties and identified potential areas for public health intervention and further research. According to data availability and vulnerability factors identified previously in Tibet and elsewhere, we selected 10 variables related to advanced age, low income, illiteracy, physical and mental disability, small living spaces and living alone. We separately created and mapped county-level cumulative heat vulnerability indices for urban and rural residents by summing up factor scores produced by a principal components analysis (PCA). For both study populations, PCA yielded four factors with similar structure. The components for rural and urban residents explained 76.5 % and 77.7 % respectively of the variability in the original vulnerability variables. We found spatial variability of heat vulnerability across counties, with generally higher vulnerability in high-altitude counties. Although we observed similar median values and ranges of the cumulative heat vulnerability index values among urban and rural residents overall, the pattern varied strongly from one county to another. We have developed a measure of population vulnerability to high temperatures in Tibet. These are preliminary findings, but they may assist targeted adaptation plans in response to future rapid warming in Tibet.

A GIS-based DRASTIC model for assessing intrinsic groundwater vulnerability in northeastern Missan governorate, southern Iraq

NASA Astrophysics Data System (ADS)

Al-Abadi, Alaa M.; Al-Shamma'a, Ayser M.; Aljabbari, Mukdad H.

2017-03-01

In this study, intrinsic groundwater vulnerability for the shallow aquifer in northeastern Missan governorate, south of Iraq is evaluated using commonly used DRASTIC model in framework of GIS environment. Preparation of DRASTIC parameters is attained through gathering data from different sources including field survey, geological and meteorological data, a digital elevation model DEM of the study area, archival database, and published research. The different data used to build DRASTIC model are arranged in a geospatial database using spatial analyst extension of ArcGIS 10.2 software. The obtained results related to the vulnerability to general contaminants show that the study area is characterized by two vulnerability zones: low and moderate. Ninety-four percentage (94 %) of the study area has a low class of groundwater vulnerability to contamination, whereas a total of (6 %) of the study area has moderate vulnerability. The pesticides DRASTIC index map shows that the study area is also characterized by two zones of vulnerability: low and moderate. The DRASTIC map of this version clearly shows that small percentage (13 %) of the study area has low vulnerability to contamination, and most parts have moderate vulnerability (about 87 %). The final results indicate that the aquifer system in the interested area is relatively protected from contamination on the groundwater surface. To mitigate the contamination risks in the moderate vulnerability zones, a protective measure must be put before exploiting the aquifer and before comprehensive agricultural activities begin in the area.

Capturing subregional variability in regional-scale climate change vulnerability assessments of natural resources.

PubMed

Buotte, Polly C; Peterson, David L; McKelvey, Kevin S; Hicke, Jeffrey A

2016-03-15

Natural resource vulnerability to climate change can depend on the climatology and ecological conditions at a particular site. Here we present a conceptual framework for incorporating spatial variability in natural resource vulnerability to climate change in a regional-scale assessment. The framework was implemented in the first regional-scale vulnerability assessment conducted by the US Forest Service. During this assessment, five subregional workshops were held to capture variability in vulnerability and to develop adaptation tactics. At each workshop, participants answered a questionnaire to: 1) identify species, resources, or other information missing from the regional assessment, and 2) describe subregional vulnerability to climate change. Workshop participants divided into six resource groups; here we focus on wildlife resources. Participants identified information missing from the regional assessment and multiple instances of subregional variability in climate change vulnerability. We provide recommendations for improving the process of capturing subregional variability in a regional vulnerability assessment. We propose a revised conceptual framework structured around pathways of climate influence, each with separate rankings for exposure, sensitivity, and adaptive capacity. These revisions allow for a quantitative ranking of species, pathways, exposure, sensitivity, and adaptive capacity across subregions. Rankings can be used to direct the development and implementation of future regional research and monitoring programs. The revised conceptual framework is equally applicable as a stand-alone model for assessing climate change vulnerability and as a nested model within a regional assessment for capturing subregional variability in vulnerability. Copyright © 2015 Elsevier Ltd. All rights reserved.

AIRWAY IDENTIFICATION WITHIN PLANAR GAMMA CAMERA IMAGES USING COMPUTER MODELS OF LUNG MORPHOLOGY

EPA Science Inventory

The quantification of inhaled aerosols could be improved if a more comprehensive assessment of their spatial distribution patterns among lung airways were obtained. A common technique for quantifying particle deposition in human lungs is with planar gamma scintigraphy. However, t...

A nanobuffer reporter library for fine-scale imaging and perturbation of endocytic organelles

PubMed Central

Wang, Chensu; Wang, Yiguang; Li, Yang; Bodemann, Brian; Zhao, Tian; Ma, Xinpeng; Huang, Gang; Hu, Zeping; DeBerardinis, Ralph J.; White, Michael A.; Gao, Jinming

2015-01-01

Endosomes, lysosomes and related catabolic organelles are a dynamic continuum of vacuolar structures that impact a number of cell physiological processes such as protein/lipid metabolism, nutrient sensing and cell survival. Here we develop a library of ultra-pH-sensitive fluorescent nanoparticles with chemical properties that allow fine-scale, multiplexed, spatio-temporal perturbation and quantification of catabolic organelle maturation at single organelle resolution to support quantitative investigation of these processes in living cells. Deployment in cells allows quantification of the proton accumulation rate in endosomes; illumination of previously unrecognized regulatory mechanisms coupling pH transitions to endosomal coat protein exchange; discovery of distinct pH thresholds required for mTORC1 activation by free amino acids versus proteins; broad-scale characterization of the consequence of endosomal pH transitions on cellular metabolomic profiles; and functionalization of a context-specific metabolic vulnerability in lung cancer cells. Together, these biological applications indicate the robustness and adaptability of this nanotechnology-enabled ‘detection and perturbation' strategy. PMID:26437053

Patterns of Freshwater Species Richness, Endemism, and Vulnerability in California

PubMed Central

Furnish, Joseph; Gardali, Thomas; Grantham, Ted; Katz, Jacob V. E.; Kupferberg, Sarah; McIntyre, Patrick; Moyle, Peter B.; Ode, Peter R.; Peek, Ryan; Quiñones, Rebecca M.; Rehn, Andrew C.; Santos, Nick; Schoenig, Steve; Serpa, Larry; Shedd, Jackson D.; Slusark, Joe; Viers, Joshua H.; Wright, Amber; Morrison, Scott A.

2015-01-01

The ranges and abundances of species that depend on freshwater habitats are declining worldwide. Efforts to counteract those trends are often hampered by a lack of information about species distribution and conservation status and are often strongly biased toward a few well-studied groups. We identified the 3,906 vascular plants, macroinvertebrates, and vertebrates native to California, USA, that depend on fresh water for at least one stage of their life history. We evaluated the conservation status for these taxa using existing government and non-governmental organization assessments (e.g., endangered species act, NatureServe), created a spatial database of locality observations or distribution information from ~400 data sources, and mapped patterns of richness, endemism, and vulnerability. Although nearly half of all taxa with conservation status (n = 1,939) are vulnerable to extinction, only 114 (6%) of those vulnerable taxa have a legal mandate for protection in the form of formal inclusion on a state or federal endangered species list. Endemic taxa are at greater risk than non-endemics, with 90% of the 927 endemic taxa vulnerable to extinction. Records with spatial data were available for a total of 2,276 species (61%). The patterns of species richness differ depending on the taxonomic group analyzed, but are similar across taxonomic level. No particular taxonomic group represents an umbrella for all species, but hotspots of high richness for listed species cover 40% of the hotspots for all other species and 58% of the hotspots for vulnerable freshwater species. By mapping freshwater species hotspots we show locations that represent the top priority for conservation action in the state. This study identifies opportunities to fill gaps in the evaluation of conservation status for freshwater taxa in California, to address the lack of occurrence information for nearly 40% of freshwater taxa and nearly 40% of watersheds in the state, and to implement adequate protections for freshwater taxa where they are currently lacking. PMID:26147215

Varying geospatial analyses to assess climate risk and adaptive capacity in a hotter, drier Southwestern United States

NASA Astrophysics Data System (ADS)

Elias, E.; Reyes, J. J.; Steele, C. M.; Rango, A.

2017-12-01

Assessing vulnerability of agricultural systems to climate variability and change is vital in securing food systems and sustaining rural livelihoods. Farmers, ranchers, and forest landowners rely on science-based, decision-relevant, and localized information to maintain production, ecological viability, and economic returns. This contribution synthesizes a collection of research on the future of agricultural production in the American Southwest (SW). Research was based on a variety of geospatial methodologies and datasets to assess the vulnerability of rangelands and livestock, field crops, specialty crops, and forests in the SW to climate-risk and change. This collection emerged from the development of regional vulnerability assessments for agricultural climate-risk by the U.S. Department of Agriculture (USDA) Climate Hub Network, established to deliver science-based information and technologies to enable climate-informed decision-making. Authors defined vulnerability differently based on their agricultural system of interest, although each primarily focuses on biophysical systems. We found that an inconsistent framework for vulnerability and climate risk was necessary to adequately capture the diversity, variability, and heterogeneity of SW landscapes, peoples, and agriculture. Through the diversity of research questions and methodologies, this collection of articles provides valuable information on various aspects of SW vulnerability. All articles relied on geographic information systems technology, with highly variable levels of complexity. Agricultural articles used National Agricultural Statistics Service data, either as tabular county level summaries or through the CropScape cropland raster datasets. Most relied on modeled historic and future climate information, but with differing assumptions regarding spatial resolution and temporal framework. We assert that it is essential to evaluate climate risk using a variety of complementary methodologies and perspectives. In addition, we found that spatial analysis supports informed adaptation, within and outside the SW United States. The persistence and adaptive capacity of agriculture in the water-limited Southwest serves as an instructive example and may offer solutions to reduce future climate risk.

Assessing influences on social vulnerability to wildfire using surveys, spatial data and wildfire simulations.

PubMed

Paveglio, Travis B; Edgeley, Catrin M; Stasiewicz, Amanda M

2018-05-01

A growing body of research focuses on identifying patterns among human populations most at risk from hazards such as wildfire and the factors that help explain performance of mitigations that can help reduce that risk. Emerging policy surrounding wildfire management emphasizes the need to better understand such social vulnerability-or human populations' potential exposure to and sensitivity from wildfire-related impacts, including their ability to reduce negative impacts from the hazard. Studies of social vulnerability to wildfire often pair secondary demographic data with a variety of vegetation and wildfire simulation models to map potential risk. However, many of the assumptions made by those researchers about the demographic, spatial or perceptual factors that influence social vulnerability to wildfire have not been fully evaluated or tested against objective measures of potential wildfire risk. The research presented here utilizes self-reported surveys, GIS data, and wildfire simulations to test the relationships between select perceptual, demographic, and property characteristics of property owners against empirically simulated metrics for potential wildfire related damages or exposure. We also evaluate how those characteristics relate to property owners' performance of mitigations or support for fire management. Our results suggest that parcel characteristics provide the most significant explanation of variability in wildfire exposure, sensitivity and overall wildfire risk, while the positive relationship between income or property values and components of social vulnerability stands in contrast to typical assumptions from existing literature. Respondents' views about agency or government management helped explain a significant amount of variance in wildfire sensitivity, while the importance of wildfire risk in selecting a residence was an important influence on mitigation action. We use these and other results from our effort to discuss updated considerations for determining social vulnerability to wildfire and articulate alternative means to collect such information. Copyright © 2018 Elsevier Ltd. All rights reserved.

Projecting Drivers of Human Vulnerability under the Shared Socioeconomic Pathways

PubMed Central

2018-01-01

The Shared Socioeconomic Pathways (SSPs) are the new set of alternative futures of societal development that inform global and regional climate change research. They have the potential to foster the integration of socioeconomic scenarios within assessments of future climate-related health impacts. To date, such assessments have primarily superimposed climate scenarios on current socioeconomic conditions only. Until now, the few assessments of future health risks that employed the SSPs have focused on future human exposure—i.e., mainly future population patterns—, neglecting future human vulnerability. This paper first explores the research gaps—mainly linked to the paucity of available projections—that explain such a lack of consideration of human vulnerability under the SSPs. It then highlights the need for projections of socioeconomic variables covering the wide range of determinants of human vulnerability, available at relevant spatial and temporal scales, and accounting for local specificities through sectoral and regional extended versions of the global SSPs. Finally, this paper presents two innovative methods of obtaining and computing such socioeconomic projections under the SSPs—namely the scenario matching approach and an approach based on experts’ elicitation and correlation analyses—and applies them to the case of Europe. They offer a variety of possibilities for practical application, producing projections at sub-national level of various drivers of human vulnerability such as demographic and social characteristics, urbanization, state of the environment, infrastructure, health status, and living arrangements. Both the innovative approaches presented in this paper and existing methods—such as the spatial disaggregation of existing projections and the use of sectoral models—show great potential to enhance the availability of relevant projections of determinants of human vulnerability. Assessments of future climate-related health impacts should thus rely on these methods to account for future human vulnerability—under varying levels of socioeconomic development—and to explore its influence on future health risks under different degrees of climate change. PMID:29562727

Spatial Intensity Duration Frequency Relationships Using Hierarchical Bayesian Analysis for Urban Areas

NASA Astrophysics Data System (ADS)

Rupa, Chandra; Mujumdar, Pradeep

2016-04-01

In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings algorithm within a Gibbs sampler) is used to obtain the samples of parameters from the posterior distribution of parameters. The spatial maps of return levels for specified return periods, along with the associated uncertainties, are obtained for the summer, monsoon and annual maxima rainfall. Considering various covariates, the best fit model is selected using Deviance Information Criteria. It is observed that the geographical covariates outweigh the climatological covariates for the monsoon maxima rainfall (latitude and longitude). The best covariates for summer maxima and annual maxima rainfall are mean summer precipitation and mean monsoon precipitation respectively, including elevation for both the cases. The scale invariance theory, which states that statistical properties of a process observed at various scales are governed by the same relationship, is used to disaggregate the daily rainfall to hourly scales. The spatial maps of the scale are obtained for the study area. The spatial maps of IDF relationships thus generated are useful in storm water designs, adequacy analysis and identifying the vulnerable flooding areas.

Temporal trends in physical violence, gender differences and spatial vulnerability of the location of victim's residences.

PubMed

Cavalcante, Gigliana Maria Sobral; de Macedo Bernardino, Ítalo; da Nóbrega, Lorena Marques; Ferreira, Raquel Conceição; Ferreira E Ferreira, Efigênia; d'Avila, Sérgio

2018-06-01

The aim of study was to describe trends in physical violence among Brazilian victims and investigate spatial vulnerability of the location of victim's residences. This study performed an ecological-level longitudinal analysis, examining violence rates over 4 years. Cases of 4795 victims of physical aggression attended at a Center of Legal Medicine were investigated. Trend analysis was used to evaluate the data, with the creation of polynomial regression models (p < 0.05). Violence rates showed significant temporal variations according to sociodemographic characteristics of victims (p < 0.05) and the circumstances of aggressions (p < 0.05). Moreover, there was a significant increase in violence rate in the North (R 2  = 16.1%; p = 0.019) and South (R 2  = 18.4%; p = 0.010), whereas the rural zone (R 2  = 10.1%; p = 0.028) presented a decrease. The findings highlight the need for protection policies that address spatial-temporal aspects. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial screening methods for evaluating environmental contaminant hazards and exposure vulnerability

NASA Astrophysics Data System (ADS)

Jones, D. K.

2016-12-01

Human and biotic communities are becoming increasingly vulnerable to sea-level rise and severe storms due to climate change. These events enhance the dispersion and concentration of natural and anthropogenic chemicals and pathogenic microorganisms, which could adversely impact the health and resilience of coastal communities and ecosystems in coming years. The U.S. Geological Survey (USGS) has developed spatial screening methods to identify and map contaminant sources and potential exposure pathways for human and ecological receptors. These methods have been applied within the northeastern U.S. to document contaminants of emerging concern, highlight vulnerable communities, and prioritize locations for future sampling campaigns. Integration of this information provides a means to better assess the baseline status of a complex system and the significance of changes in contaminant hazards due to storm-induced (episodic) and sea-level rise (incremental) disturbances. This presentation will provide an overview of a decision support tool developed by the USGS to document contaminants in the environment relative to key receptor populations and historic storm vulnerabilities. The support tool is designed to accommodate a broad array of geologic, land-use, and climatic variables and utilizes public, nationally available data sources to define contaminant sources and storm vulnerabilities. By employing a flexible and adaptable strategy built upon publicly available data, the method can readily be applied to other site selection or landscape evaluation efforts. Examples will be presented including the Sediment-bound Contaminant Resiliency and Response pilot study (see http://toxics.usgs.gov/scorr/), and investigations of endocrine disruption in the Chesapeake Bay. Key limitations and future applications will be discussed in addition to ongoing method developments to accommodate non-coastal disaster scenarios and more refined contaminant definitions.

Assessing species vulnerability to climate change

NASA Astrophysics Data System (ADS)

Pacifici, Michela; Foden, Wendy B.; Visconti, Piero; Watson, James E. M.; Butchart, Stuart H. M.; Kovacs, Kit M.; Scheffers, Brett R.; Hole, David G.; Martin, Tara G.; Akçakaya, H. Resit; Corlett, Richard T.; Huntley, Brian; Bickford, David; Carr, Jamie A.; Hoffmann, Ary A.; Midgley, Guy F.; Pearce-Kelly, Paul; Pearson, Richard G.; Williams, Stephen E.; Willis, Stephen G.; Young, Bruce; Rondinini, Carlo

2015-03-01

The effects of climate change on biodiversity are increasingly well documented, and many methods have been developed to assess species' vulnerability to climatic changes, both ongoing and projected in the coming decades. To minimize global biodiversity losses, conservationists need to identify those species that are likely to be most vulnerable to the impacts of climate change. In this Review, we summarize different currencies used for assessing species' climate change vulnerability. We describe three main approaches used to derive these currencies (correlative, mechanistic and trait-based), and their associated data requirements, spatial and temporal scales of application and modelling methods. We identify strengths and weaknesses of the approaches and highlight the sources of uncertainty inherent in each method that limit projection reliability. Finally, we provide guidance for conservation practitioners in selecting the most appropriate approach(es) for their planning needs and highlight priority areas for further assessments.

Developing a Climate-Induced Social Vulnerability Index for Urban Areas: A Case Study of East Tennessee

DOE Office of Scientific and Technical Information (OSTI.GOV)

Omitaomu, Olufemi A.; Carvalhaes, Thomaz M.

Census American Community Survey 2008-2012 data are used to construct a spatially explicit Climate-Induced Social Vulnerability Index (CSVI) for the East Tennessee area. This CSVI is a combination of a Social Vulnerability Index (SVI) and a Climate Index. A method is replicated and adapted to derive a custom SVI by Census tract for the counties participating in the East Tennessee Index, and a Climate Index is developed for the same area based on indicators for climate hazards. The resulting datasets are exported as a raster to be integrated and combined within the Urban Climate Adaptation Tool (Urban-CAT) to act asmore » an indicator for communities which may be differentially vulnerable to changes in climate. Results for the SVI are mapped separately from the complete CSVI in this document as results for the latter are in development.« less

Population Vulnerability to Biannual Cholera Outbreaks and Associated Macro-Scale Drivers in the Bengal Delta

PubMed Central

Akanda, Ali Shafqat; Jutla, Antarpreet S.; Gute, David M.; Sack, R. Bradley; Alam, Munirul; Huq, Anwar; Colwell, Rita R.; Islam, Shafiqul

2013-01-01

The highly populated floodplains of the Bengal Delta have a long history of endemic and epidemic cholera outbreaks, both coastal and inland. Previous studies have not addressed the spatio-temporal dynamics of population vulnerability related to the influence of underlying large-scale processes. We analyzed spatial and temporal variability of cholera incidence across six surveillance sites in the Bengal Delta and their association with regional hydroclimatic and environmental drivers. More specifically, we use salinity and flood inundation modeling across the vulnerable districts of Bangladesh to test earlier proposed hypotheses on the role of these environmental variables. Our results show strong influence of seasonal and interannual variability in estuarine salinity on spring outbreaks and inland flooding on fall outbreaks. A large segment of the population in the Bengal Delta floodplains remain vulnerable to these biannual cholera transmission mechanisms that provide ecologic and environmental conditions for outbreaks over large geographic regions. PMID:24019441

Locating Spatial Variation in the Association Between Wildland Fire Risk and Social Vulnerability Across Six Southern States

NASA Astrophysics Data System (ADS)

Poudyal, Neelam C.; Johnson-Gaither, Cassandra; Goodrick, Scott; Bowker, J. M.; Gan, Jianbang

2012-03-01

Wildland fire in the South commands considerable attention, given the expanding wildland urban interface (WUI) across the region. Much of this growth is propelled by higher income retirees and others desiring natural amenity residential settings. However, population growth in the WUI increases the likelihood of wildfire fire ignition caused by people, as humans account for 93% of all wildfires fires in the South. Coexisting with newly arrived, affluent WUI populations are working class, poor or otherwise socially vulnerable populations. The latter groups typically experience greater losses from environmental disasters such as wildfire because lower income residents are less likely to have established mitigation programs in place to help absorb loss. We use geographically weighted regression to examine spatial variation in the association between social vulnerability (SOVUL) and wildfire risk. In doing so, we identify "hot spots" or geographical clusters where SOVUL varies positively with wildfire risk across six Southern states—Alabama, Arkansas, Florida, Georgia, Mississippi, and South Carolina. These clusters may or may not be located in the WUI. These hot spots are most prevalent in South Carolina and Florida. Identification of these population clusters can aid wildfire managers in deciding which communities to prioritize for mitigation programming.

Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prado, T. L.; Galuzio, P. P.; Lopes, S. R.

Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with amore » better control over the spurious fragments in the image.« less

Calibration of groundwater vulnerability mapping using the generalized reduced gradient method.

PubMed

Elçi, Alper

2017-12-01

Groundwater vulnerability assessment studies are essential in water resources management. Overlay-and-index methods such as DRASTIC are widely used for mapping of groundwater vulnerability, however, these methods mainly suffer from a subjective selection of model parameters. The objective of this study is to introduce a calibration procedure that results in a more accurate assessment of groundwater vulnerability. The improvement of the assessment is formulated as a parameter optimization problem using an objective function that is based on the correlation between actual groundwater contamination and vulnerability index values. The non-linear optimization problem is solved with the generalized-reduced-gradient (GRG) method, which is numerical algorithm based optimization method. To demonstrate the applicability of the procedure, a vulnerability map for the Tahtali stream basin is calibrated using nitrate concentration data. The calibration procedure is easy to implement and aims the maximization of correlation between observed pollutant concentrations and groundwater vulnerability index values. The influence of each vulnerability parameter in the calculation of the vulnerability index is assessed by performing a single-parameter sensitivity analysis. Results of the sensitivity analysis show that all factors are effective on the final vulnerability index. Calibration of the vulnerability map improves the correlation between index values and measured nitrate concentrations by 19%. The regression coefficient increases from 0.280 to 0.485. It is evident that the spatial distribution and the proportions of vulnerability class areas are significantly altered with the calibration process. Although the applicability of the calibration method is demonstrated on the DRASTIC model, the applicability of the approach is not specific to a certain model and can also be easily applied to other overlay-and-index methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Calibration of groundwater vulnerability mapping using the generalized reduced gradient method

NASA Astrophysics Data System (ADS)

Elçi, Alper

2017-12-01

Groundwater vulnerability assessment studies are essential in water resources management. Overlay-and-index methods such as DRASTIC are widely used for mapping of groundwater vulnerability, however, these methods mainly suffer from a subjective selection of model parameters. The objective of this study is to introduce a calibration procedure that results in a more accurate assessment of groundwater vulnerability. The improvement of the assessment is formulated as a parameter optimization problem using an objective function that is based on the correlation between actual groundwater contamination and vulnerability index values. The non-linear optimization problem is solved with the generalized-reduced-gradient (GRG) method, which is numerical algorithm based optimization method. To demonstrate the applicability of the procedure, a vulnerability map for the Tahtali stream basin is calibrated using nitrate concentration data. The calibration procedure is easy to implement and aims the maximization of correlation between observed pollutant concentrations and groundwater vulnerability index values. The influence of each vulnerability parameter in the calculation of the vulnerability index is assessed by performing a single-parameter sensitivity analysis. Results of the sensitivity analysis show that all factors are effective on the final vulnerability index. Calibration of the vulnerability map improves the correlation between index values and measured nitrate concentrations by 19%. The regression coefficient increases from 0.280 to 0.485. It is evident that the spatial distribution and the proportions of vulnerability class areas are significantly altered with the calibration process. Although the applicability of the calibration method is demonstrated on the DRASTIC model, the applicability of the approach is not specific to a certain model and can also be easily applied to other overlay-and-index methods.

Preliminary Magnitude of Completeness Quantification of Improved BMKG Catalog (2008-2016) in Indonesian Region

NASA Astrophysics Data System (ADS)

Diantari, H. C.; Suryanto, W.; Anggraini, A.; Irnaka, T. M.; Susilanto, P.; Ngadmanto, D.

2018-03-01

We present a magnitude of completeness (Mc) quantification based on BMKG improved earthquake catalog which generated from Ina-TEWS seismograph network. The Mc quantification can help us determine the lowest magnitude which can be recorded perfectly as a function of space and time. We use the BMKG improved earthquake catalog from 2008 to 2016 which has been converted to moment magnitude (Mw) and declustered. The value of Mc is computed by determining the initial point of deviation patterns in Frequency Magnitude Distribution (FMD) chart following the Gutenberg-Richter equations. In the next step, we calculate the temporal variation of Mc and b-value using maximum likelihood method annually. We found that the Mc value is decreasing and produced a varying b-value. It indicates that the development of seismograph network from 2008 to 2016 can affect the value of Mc although it is not significant. We analyze temporal variation of Mc value, and correlate it with the spatial distribution of seismograph in Indonesia. The spatial distribution of seismograph installation shows that the western part of Indonesia has more dense seismograph compared to the eastern region. However, the eastern part of Indonesia has a high level of seismicity compared to the western region. Based upon the results, additional seismograph installation in the eastern part of Indonesia should be taken into consideration.

Full-field transient vibrometry of the human tympanic membrane by local phase correlation and high-speed holography

PubMed Central

Dobrev, Ivo; Furlong, Cosme; Cheng, Jeffrey T.; Rosowski, John J.

2014-01-01

Abstract. Understanding the human hearing process would be helped by quantification of the transient mechanical response of the human ear, including the human tympanic membrane (TM or eardrum). We propose a new hybrid high-speed holographic system (HHS) for acquisition and quantification of the full-field nanometer transient (i.e., >10  kHz) displacement of the human TM. We have optimized and implemented a 2+1 frame local correlation (LC) based phase sampling method in combination with a high-speed (i.e., >40  K fps) camera acquisition system. To our knowledge, there is currently no existing system that provides such capabilities for the study of the human TM. The LC sampling method has a displacement difference of <11  nm relative to measurements obtained by a four-phase step algorithm. Comparisons between our high-speed acquisition system and a laser Doppler vibrometer indicate differences of <10  μs. The high temporal (i.e., >40  kHz) and spatial (i.e., >100  k data points) resolution of our HHS enables parallel measurements of all points on the surface of the TM, which allows quantification of spatially dependent motion parameters, such as modal frequencies and acoustic delays. Such capabilities could allow inferring local material properties across the surface of the TM. PMID:25191832

Urban Vulnerability Assessment to Seismic Hazard through Spatial Multi-Criteria Analysis. Case Study: the Bucharest Municipality/Romania

NASA Astrophysics Data System (ADS)

Armas, Iuliana; Dumitrascu, Silvia; Bostenaru, Maria

2010-05-01

In the context of an explosive increase in value of the damage caused by natural disasters, an alarming challenge in the third millennium is the rapid growth of urban population in vulnerable areas. Cities are, by definition, very fragile socio-ecological systems with a high level of vulnerability when it comes to environmental changes and that are responsible for important transformations of the space, determining dysfunctions shown in the state of the natural variables (Parker and Mitchell, 1995, The OFDA/CRED International Disaster Database). A contributing factor is the demographic dynamic that affects urban areas. The aim of this study is to estimate the overall vulnerability of the urban area of Bucharest in the context of the seismic hazard, by using environmental, socio-economic, and physical measurable variables in the framework of a spatial multi-criteria analysis. For this approach the capital city of Romania was chosen based on its high vulnerability due to the explosive urban development and the advanced state of degradation of the buildings (most of the building stock being built between 1940 and 1977). Combining these attributes with the seismic hazard induced by the Vrancea source, Bucharest was ranked as the 10th capital city worldwide in the terms of seismic risk. Over 40 years of experience in the natural risk field shows that the only directly accessible way to reduce the natural risk is by reducing the vulnerability of the space (Adger et al., 2001, Turner et al., 2003; UN/ISDR, 2004, Dayton-Johnson, 2004, Kasperson et al., 2005; Birkmann, 2006 etc.). In effect, reducing the vulnerability of urban spaces would imply lower costs produced by natural disasters. By applying the SMCA method, the result reveals a circular pattern, signaling as hot spots the Bucharest historic centre (located on a river terrace and with aged building stock) and peripheral areas (isolated from the emergency centers and defined by precarious social and economic conditions). In effect, the example of Bucharest demonstrates how the results shape the ‘vulnerability to seismic hazard profile of the city, based on which decision makers could develop proper mitigation strategies. To sum up, the use of an analytical framework as the standard Spatial Multi-Criteria Analysis (SMCA) - despite all difficulties in creating justifiable weights (Yeh et al., 1999) - results in accurate estimations of the state of the urban system. Although this method was often mistrusted by decision makers (Janssen, 2001), we consider that the results can represent, based on precisely the level of generalization, a decision support framework for policy makers to critically reflect on possible risk mitigation plans. Further study will lead to the improvement of the analysis by integrating a series of daytime and nighttime scenarios and a better definition of the constructed space variables.

A Preliminary Tsunami vulnerability analysis for Bakirkoy district in Istanbul

NASA Astrophysics Data System (ADS)

Tufekci, Duygu; Lutfi Suzen, M.; Cevdet Yalciner, Ahmet; Zaytsev, Andrey

2016-04-01

Resilience of coastal utilities after earthquakes and tsunamis has major importance for efficient and proper rescue and recovery operations soon after the disasters. Vulnerability assessment of coastal areas under extreme events has major importance for preparedness and development of mitigation strategies. The Sea of Marmara has experienced numerous earthquakes as well as associated tsunamis. There are variety of coastal facilities such as ports, small craft harbors, and terminals for maritime transportation, water front roads and business centers mainly at North Coast of Marmara Sea in megacity Istanbul. A detailed vulnerability analysis for Yenikapi region and a detailed resilience analysis for Haydarpasa port in Istanbul have been studied in previously by Cankaya et al., (2015) and Aytore et al., (2015) in SATREPS project. In this study, the methodology of vulnerability analysis under tsunami attack given in Cankaya et al., (2015) is modified and applied to Bakirkoy district of Istanbul. Bakirkoy district is located at western part of Istanbul and faces to the North Coast of Marmara Sea from 28.77oE to 28.89oE. High resolution spatial dataset of Istanbul Metropolitan Municipality (IMM) is used and analyzed. The bathymetry and topography database and the spatial dataset containing all buildings/structures/infrastructures in the district are collated and utilized for tsunami numerical modeling and following vulnerability analysis. The tsunami parameters from deterministically defined worst case scenarios are computed from the simulations using tsunami numerical model NAMI DANCE. The vulnerability assessment parameters in the district according to vulnerability and resilience are defined; and scored by implementation of a GIS based TVA with appropriate MCDA methods. The risk level is computed using tsunami intensity (level of flow depth from simulations) and TVA results at every location in Bakirkoy district. The preliminary results are presented and discussed. Acknowledgements: Partial support by Japan-Turkey Joint Research Project by JICA on earthquakes and tsunamis in Marmara Region in (JICA SATREPS - MarDiM Project), 603839 ASTARTE Project of EU, UDAP-C-12-14 project of AFAD, Turkey, 108Y227, 113M556, 213M534 projects of TUBITAK Turkey, RAPSODI (CONCERT_Dis-021) of CONCERT-Japan Joint Call and Istanbul Metropolitan Municipality are acknowledged.

Crop vulnerability: Carya

USDA-ARS?s Scientific Manuscript database

Long established native tree populations reflect local adaptations. Representation of diverse populations in accessible ex situ collections that link information on phenotypic expression to information on spatial and temporal origination is the most efficient means of preserving and exploring genet...

Multi-tissue partial volume quantification in multi-contrast MRI using an optimised spectral unmixing approach.

PubMed

Collewet, Guylaine; Moussaoui, Saïd; Deligny, Cécile; Lucas, Tiphaine; Idier, Jérôme

2018-06-01

Multi-tissue partial volume estimation in MRI images is investigated with a viewpoint related to spectral unmixing as used in hyperspectral imaging. The main contribution of this paper is twofold. It firstly proposes a theoretical analysis of the statistical optimality conditions of the proportion estimation problem, which in the context of multi-contrast MRI data acquisition allows to appropriately set the imaging sequence parameters. Secondly, an efficient proportion quantification algorithm based on the minimisation of a penalised least-square criterion incorporating a regularity constraint on the spatial distribution of the proportions is proposed. Furthermore, the resulting developments are discussed using empirical simulations. The practical usefulness of the spectral unmixing approach for partial volume quantification in MRI is illustrated through an application to food analysis on the proving of a Danish pastry. Copyright © 2018 Elsevier Inc. All rights reserved.

Dynamics of leaf hydraulic conductance with water status: quantification and analysis of species differences under steady state

PubMed Central

Scoffoni, Christine; McKown, Athena D.; Rawls, Michael; Sack, Lawren

2012-01-01

Leaf hydraulic conductance (Kleaf) is a major determinant of photosynthetic rate in well-watered and drought-stressed plants. Previous work assessed the decline of Kleaf with decreasing leaf water potential (Ψleaf), most typically using rehydration kinetics methods, and found that species varied in the shape of their vulnerability curve, and that hydraulic vulnerability correlated with other leaf functional traits and with drought sensitivity. These findings were tested and extended, using a new steady-state evaporative flux method under high irradiance, and the function for the vulnerability curve of each species was determined individually using maximum likelihood for 10 species varying strongly in drought tolerance. Additionally, the ability of excised leaves to recover in Kleaf with rehydration was assessed, and a new theoretical framework was developed to estimate how rehydration of measured leaves may affect estimation of hydraulic parameters. As hypothesized, species differed in their vulnerability function. Drought-tolerant species showed shallow linear declines and more negative Ψleaf at 80% loss of Kleaf (P80), whereas drought-sensitive species showed steeper, non-linear declines, and less negative P80. Across species, the maximum Kleaf was independent of hydraulic vulnerability. Recovery of Kleaf after 1 h rehydration of leaves dehydrated below their turgor loss point occurred only for four of 10 species. Across species without recovery, a more negative P80 correlated with the ability to maintain Kleaf through both dehydration and rehydration. These findings indicate that resistance to Kleaf decline is important not only in maintaining open stomata during the onset of drought, but also in enabling sustained function during drought recovery. PMID:22016424

Freshwater Vulnerability beyond Local Water Stress: Heterogeneous Effects of Water-Electricity Nexus Across the Continental United States.

PubMed

Wang, Ranran; Zimmerman, Julie B; Wang, Chunyan; Font Vivanco, David; Hertwich, Edgar G

2017-09-05

Human health and economic prosperity are vulnerable to freshwater shortage in many parts of the world. Despite a growing literature that examines the freshwater vulnerability in various spatiotemporal contexts, existing knowledge has been conventionally constrained by a territorial perspective. On the basis of spatial analyses of monthly water and electricity flows across 2110 watersheds and three interconnected power systems, this study investigates the water-electricity nexus (WEN)'s transboundary effects on freshwater vulnerability in the continental United States in 2014. The effects are shown to be considerable and heterogeneous across time and space. For at least one month a year, 58 million people living in water-abundant watersheds were exposed to additional freshwater vulnerability by relying on electricity generated by freshwater-cooled thermal energy conversion cycles in highly stressed watersheds; for 72 million people living in highly stressed watersheds, their freshwater vulnerability was mitigated by using imported electricity generated in water-abundant watersheds or power plants running dry cooling or using nonfreshwater for cooling purposes. On the country scale, the mitigation effects were the most significant during September and October, while the additional freshwater vulnerability was more significant in February, March, and December. Due to the WEN's transboundary effects, overall, the freshwater vulnerability was slightly worsened within the Eastern Interconnection, substantially improved within the Western Interconnection, and least affected within the ERCOT Interconnection.

Vulnerability assessment of urban ecosystems driven by water resources, human health and atmospheric environment

NASA Astrophysics Data System (ADS)

Shen, Jing; Lu, Hongwei; Zhang, Yang; Song, Xinshuang; He, Li

2016-05-01

As ecosystem management is a hotspot and urgent topic with increasing population growth and resource depletion. This paper develops an urban ecosystem vulnerability assessment method representing a new vulnerability paradigm for decision makers and environmental managers, as it's an early warning system to identify and prioritize the undesirable environmental changes in terms of natural, human, economic and social elements. The whole idea is to decompose a complex problem into sub-problem, and analyze each sub-problem, and then aggregate all sub-problems to solve this problem. This method integrates spatial context of Geographic Information System (GIS) tool, multi-criteria decision analysis (MCDA) method, ordered weighted averaging (OWA) operators, and socio-economic elements. Decision makers can find out relevant urban ecosystem vulnerability assessment results with different vulnerable attitude. To test the potential of the vulnerability methodology, it has been applied to a case study area in Beijing, China, where it proved to be reliable and consistent with the Beijing City Master Plan. The results of urban ecosystem vulnerability assessment can support decision makers in evaluating the necessary of taking specific measures to preserve the quality of human health and environmental stressors for a city or multiple cities, with identifying the implications and consequences of their decisions.

[The social vulnerability index regarding Medellín's disabled population].

PubMed

Cardona-Arango, Doris; Agudelo-Martínez, Alejandra; Restrepo-Molina, Lucas; Segura-Cardona, Angela M

2014-01-01

Constructing a social vulnerability index (SVI) for Medellín's disabled population during 2008 aimed at determining areas which were reducing opportunities for this population to use their tangible and intangible assets, thus impairing their quality of life. This descriptive cross-sectional study drew on a source of secondary information regarding people having some kind of limitation recorded in the Quality of Life Survey, 2008. Physical, human and social variables were grouped when constructing the SVI; the models were run in principal component analysis to determine their degree of vulnerability, defined by the number of negative factors identified (high category=4 or 5, medium=2 or 3 and low=1 or none). Such classification led to identifying non-causal relationships with demographic variables through Mann-Whitney, Chi-square and Kruskal-Wallis tests (5.0 % statistical significance level); multinomial logistic regression was used for calculating adjusted measures for epidemiological measurement, such as opportunity ratios and confidence intervals. A degree of medium vulnerability predominated in disabled people living in Medellín (60.3 %) followed by low vulnerability (28.7 %) and high vulnerability populations (11.0 %). The proposed ISV classified the city's communes according to high, medium or low vulnerability, supported by the use of statistical and spatial location techniques.

Vulnerability assessment of atmospheric environment driven by human impacts.

PubMed

Zhang, Yang; Shen, Jing; Ding, Feng; Li, Yu; He, Li

2016-11-15

Atmospheric environment quality worsening is a substantial threat to public health worldwide, and in many places, air pollution due to the intensification of the human activity is increasing dramatically. However, no studies have been investigated the integration of vulnerability assessment and atmospheric environment driven by human impacts. The objective of this study was to identify and prioritize the undesirable environmental changes as an early warning system for environment managers and decision makers in term of human, atmospheric environment, and social economic elements. We conduct a vulnerability assessment method of atmospheric environment associated with human impact, this method integrates spatial context of Geographic Information System (GIS) tool, multi-criteria decision analysis (MCDA) method, ordered weighted averaging (OWA) operators under the Exposure-Sensitivity- Adaptive Capacity (ESA) framework. Decision makers can find out relevant vulnerability assessment results with different vulnerable attitudes. In the Beijing-Tianjin-Hebei (BTH) region, China, we further applied this developed method and proved it to be reliable and consistent with the China Environmental Status Bulletin. Results indicate that the vulnerability of atmospheric environment in the BTH region is not optimistic, and environment managers should do more about air pollution. Thus, the most appropriate strategic decision and development program of city or state can be picked out assisting by the vulnerable results. Copyright © 2016 Elsevier B.V. All rights reserved.

Soil physical property estimation from soil strength and apparent electrical conductivity sensor data

USDA-ARS?s Scientific Manuscript database

Quantification of soil physical properties through soil sampling and laboratory analyses is time-, cost-, and labor-consuming, making it difficult to obtain the spatially-dense data required for precision agriculture. Proximal soil sensing is an attractive alternative, but many currently available s...

Bush encroachment dynamics and rangeland management implications in the Horn of Africa

USDA-ARS?s Scientific Manuscript database

Rangelands in the Horn of Africa have been undergoing a rapid shift from herbaceous to woody plant dominance in the past decades, threatening subsistence livestock herding and pastoral food security. Despite of significant rangeland management implications, quantification of the spatial extent of en...

Probabilistic assessment of beach and dune changes

USGS Publications Warehouse

Sallenger, A.H.; Stockdon, H.; Haines, J.; Krabill, W.; Swift, R.; Brock, J.

2004-01-01

The recent availability of spatially-dense airborne lidar data makes assessment of the vulnerability of beaches and dunes to storm impacts practical over long reaches of coast. As an initial test, elevations of the tops (D high) and bases (Dlow) of foredune ridges along a 55-km reach on the northern Outer Banks, NC were found to have considerable spatial variability suggesting that different parts of the barrier island would respond differently to storms. Comparing statistics of storm wave runup to D high and Dlow, we found that net erosion due to overwash and dune retreat should be greatest at the northern and southern ends of the study area and least in the central section. This predicted spatial pattern of storm-induced erosion is similar to the spatial pattern of long-term erosion of the shoreline which may be controlled by additional processes (such as gradients in longshore transport) as well as the cross-shore processes considered here. However, consider feedback where at erosional hot spots there is a deficit of sand (caused by gradients in longshore transport) which lead to lower dunes and enhanced erosional cross-shore processes, such as overwash. Hence, the erosional hot spots would be exacerbated, further increasing the vulnerability of the beach and dunes to net erosion.

Coastal Vulnerability to Sea Level Rise and Erosion in Northwest Alaska (Invited)

NASA Astrophysics Data System (ADS)

Gorokhovich, Y.; Leiserowitz, A.

2009-12-01

Northwest Alaska is experiencing significant climate change and human impacts. The study area includes the coastal zone of Kotzebue Sound and the Chukchi Sea and provides the local population (predominantly Inupiaq Eskimo) with critical subsistence resources of meat, fish, berries, herbs, and wood. The geomorphology of the coast includes barrier islands, inlets, estuaries, deltas, cliffs, bluffs, and beaches that host modern settlements and infrastructure. Coastal dynamics and sea-level rise are contributing to erosion, intermittent erosion/accretion patterns, landslides, slumps and coastal retreat. These factors are causing the sedimentation of deltas and lagoons, and changing local bathymetry, morphological parameters of beaches and underwater slopes, rates of coastal dynamics, and turbidity and nutrient cycling in coastal waters. This study is constructing vulnerability maps to help local people and federal officials understand the potential consequences of sea-level rise and coastal erosion on local infrastructure, subsistence resources, and culturally important sites. A lack of complete and uniform data (in terms of methods of collection, geographic scale and spatial resolution) creates an additional level of uncertainty that complicates geographic analysis. These difficulties were overcome by spatial modeling with selected spatial resolution using extrapolation methods. Data include subsistence resource maps obtained using Participatory GIS with local hunters and elders, geological and geographic data on coastal dynamics from satellite imagery, aerial photos, bathymetry and topographic maps, and digital elevation models. These data were classified and ranked according to the level of coastal vulnerability (Figure 1). The resulting qualitative multicriteria model helps to identify the coastal areas with the greatest vulnerability to coastal erosion and of the potential loss of subsistence resources. Acknowldgements: Dr. Ron Abileah (private consultant, jOmegak) helped in preliminary analysis of Landsat imagery, Mr. Alex Whiting provided valuable information on subsistence resources in Kotzebue region, hunters and elders of villages in Kivalina, Kotzebue, Selawik and Deering provided input in GIS database on subsistence resources.

Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China.

PubMed

Chen, Qian; Ding, Mingjun; Yang, Xuchao; Hu, Kejia; Qi, Jiaguo

2018-05-25

The increase in the frequency and intensity of extreme heat events, which are potentially associated with climate change in the near future, highlights the importance of heat health risk assessment, a significant reference for heat-related death reduction and intervention. However, a spatiotemporal mismatch exists between gridded heat hazard and human exposure in risk assessment, which hinders the identification of high-risk areas at finer scales. A human settlement index integrated by nighttime light images, enhanced vegetation index, and digital elevation model data was utilized to assess the human exposure at high spatial resolution. Heat hazard and vulnerability index were generated by land surface temperature and demographic and socioeconomic census data, respectively. Spatially explicit assessment of heat health risk and its driving factors was conducted in the Yangtze River Delta (YRD), east China at 250 m pixel level. High-risk areas were mainly distributed in the urbanized areas of YRD, which were mostly driven by high human exposure and heat hazard index. In some less-urbanized cities and suburban and rural areas of mega-cities, the heat health risks are in second priority. The risks in some less-developed areas were high despite the low human exposure index because of high heat hazard and vulnerability index. This study illustrated a methodology for identifying high-risk areas by combining freely available multi-source data. Highly urbanized areas were considered hotspots of high heat health risks, which were largely driven by the increasing urban heat island effects and population density in urban areas. Repercussions of overheating were weakened due to the low social vulnerability in some central areas benefitting from the low proportion of sensitive population or the high level of socioeconomic development. By contrast, high social vulnerability intensifies heat health risks in some less-urbanized cities and suburban areas of mega-cities.

Vulnerability to Climate Change of Mangroves: Assessment from Cameroon, Central Africa

PubMed Central

Ellison, Joanna C.; Zouh, Isabella

2012-01-01

Intertidal mangrove ecosystems are sensitive to climate change impacts, particularly to associated relative sea level rise. Human stressors and low tidal range add to vulnerability, both characteristics of the Doula Estuary, Cameroon. To investigate vulnerability, spatial techniques were combined with ground surveys to map distributions of mangrove zones, and compare with historical spatial records to quantify change over the last few decades. Low technology techniques were used to establish the tidal range and relative elevation of the mapped mangrove area. Stratigraphic coring and palaeobiological reconstruction were used to show the longer term biological history of mangroves and net sedimentation rate, and oral history surveys of local communities were used to provide evidence of recent change and identify possible causes. Results showed that the seaward edge of mangroves had over two thirds of the shoreline experienced dieback at up to 3 m per year over the last three decades, and an offshore mangrove island had suffered 89% loss. Results also showed low net sedimentation rates under seaward edge mangroves, and restricted intertidal elevation habitats of all mangroves, and Avicennia and Laguncularia in particular. To reduce vulnerability, adaptation planning can be improved by reducing the non-climate stressors on the mangrove area, particularly those resulting from human impacts. Other priorities for adaptation planning in mangrove areas that are located in such low tidal range regions are to plan inland migration areas and strategic protected areas for mangroves, and to undertake management activities that enhance accretion within the mangroves. PMID:24832511

Predicting the Texas Windstorm Insurance Association claim payout of commercial buildings from Hurricane Ike

NASA Astrophysics Data System (ADS)

Kim, J. M.; Woods, P. K.; Park, Y. J.; Son, K.

2013-08-01

Following growing public awareness of the danger from hurricanes and tremendous demands for analysis of loss, many researchers have conducted studies to develop hurricane damage analysis methods. Although researchers have identified the significant indicators, there currently is no comprehensive research for identifying the relationship among the vulnerabilities, natural disasters, and economic losses associated with individual buildings. To address this lack of research, this study will identify vulnerabilities and hurricane indicators, develop metrics to measure the influence of economic losses from hurricanes, and visualize the spatial distribution of vulnerability to evaluate overall hurricane damage. This paper has utilized the Geographic Information System to facilitate collecting and managing data, and has combined vulnerability factors to assess the financial losses suffered by Texas coastal counties. A multiple linear regression method has been applied to develop hurricane economic damage predicting models. To reflect the pecuniary loss, insured loss payment was used as the dependent variable to predict the actual financial damage. Geographical vulnerability indicators, built environment vulnerability indicators, and hurricane indicators were all used as independent variables. Accordingly, the models and findings may possibly provide vital references for government agencies, emergency planners, and insurance companies hoping to predict hurricane damage.

A systematic review of dynamics in climate risk and vulnerability assessments

NASA Astrophysics Data System (ADS)

Jurgilevich, Alexandra; Räsänen, Aleksi; Groundstroem, Fanny; Juhola, Sirkku

2017-01-01

Understanding climate risk is crucial for effective adaptation action, and a number of assessment methodologies have emerged. We argue that the dynamics of the individual components in climate risk and vulnerability assessments has received little attention. In order to highlight this, we systematically reviewed 42 sub-national climate risk and vulnerability assessments. We analysed the assessments using an analytical framework with which we evaluated (1) the conceptual approaches to vulnerability and exposure used, (2) if current or future risks were assessed, and (3) if and how changes over time (i.e. dynamics) were considered. Of the reviewed assessments, over half addressed future risks or vulnerability; and of these future-oriented studies, less than 1/3 considered both vulnerability and exposure dynamics. While the number of studies that include dynamics is growing, and while all studies included socio-economic aspects, often only biophysical dynamics was taken into account. We discuss the challenges of assessing socio-economic and spatial dynamics, particularly the poor availability of data and methods. We suggest that future-oriented studies assessing risk dynamics would benefit from larger stakeholder involvement, discussion of the assessment purpose, the use of multiple methods, inclusion of uncertainty/sensitivity analyses and pathway approaches.

Participatory flood vulnerability assessment: a multi-criteria approach

NASA Astrophysics Data System (ADS)

Madruga de Brito, Mariana; Evers, Mariele; Delos Santos Almoradie, Adrian

2018-01-01

This paper presents a participatory multi-criteria decision-making (MCDM) approach for flood vulnerability assessment while considering the relationships between vulnerability criteria. The applicability of the proposed framework is demonstrated in the municipalities of Lajeado and Estrela, Brazil. The model was co-constructed by 101 experts from governmental organizations, universities, research institutes, NGOs, and private companies. Participatory methods such as the Delphi survey, focus groups, and workshops were applied. A participatory problem structuration, in which the modellers work closely with end users, was used to establish the structure of the vulnerability index. The preferences of each participant regarding the criteria importance were spatially modelled through the analytical hierarchy process (AHP) and analytical network process (ANP) multi-criteria methods. Experts were also involved at the end of the modelling exercise for validation. The final product is a set of individual and group flood vulnerability maps. Both AHP and ANP proved to be effective for flood vulnerability assessment; however, ANP is preferred as it considers the dependences among criteria. The participatory approach enabled experts to learn from each other and acknowledge different perspectives towards social learning. The findings highlight that to enhance the credibility and deployment of model results, multiple viewpoints should be integrated without forcing consensus.

Assessment of vulnerability in karst aquifers using a quantitative integrated numerical model: catchment characterization and high resolution monitoring - Application to semi-arid regions- Lebanon.

NASA Astrophysics Data System (ADS)

Doummar, Joanna; Aoun, Michel; Andari, Fouad

2016-04-01

Karst aquifers are highly heterogeneous and characterized by a duality of recharge (concentrated; fast versus diffuse; slow) and a duality of flow which directly influences groundwater flow and spring responses. Given this heterogeneity in flow and infiltration, karst aquifers do not always obey standard hydraulic laws. Therefore the assessment of their vulnerability reveals to be challenging. Studies have shown that vulnerability of aquifers is highly governed by recharge to groundwater. On the other hand specific parameters appear to play a major role in the spatial and temporal distribution of infiltration on a karst system, thus greatly influencing the discharge rates observed at a karst spring, and consequently the vulnerability of a spring. This heterogeneity can only be depicted using an integrated numerical model to quantify recharge spatially and assess the spatial and temporal vulnerability of a catchment for contamination. In the framework of a three-year PEER NSF/USAID funded project, the vulnerability of a karst catchment in Lebanon is assessed quantitatively using a numerical approach. The aim of the project is also to refine actual evapotranspiration rates and spatial recharge distribution in a semi arid environment. For this purpose, a monitoring network was installed since July 2014 on two different pilot karst catchment (drained by Qachqouch Spring and Assal Spring) to collect high resolution data to be used in an integrated catchment numerical model with MIKE SHE, DHI including climate, unsaturated zone, and saturated zone. Catchment characterization essential for the model included geological mapping and karst features (e.g., dolines) survey as they contribute to fast flow. Tracer experiments were performed under different flow conditions (snow melt and low flow) to delineate the catchment area, reveal groundwater velocities and response to snowmelt events. An assessment of spring response after precipitation events allowed the estimation of the fast infiltration component. A series of laboratory tests were performed to acquire physical values to be used as a benchmark for model parameterization, such as laboratory tests on soils for conductivity at saturation and grain size analysis. Time series used for input or calibration were collected and computed from continuous high resolution monitoring of climatic data, moisture variation in the soil, and discharge at the investigated spring. This similar model approach used on a catchment site in Germany is to be applied and validated on two pilot karst catchments in Lebanon governed by semi-arid climatic conditions. References Doummar J., Sauter M., Geyer T., 2012. Simulation of flow processes in a large scale karst system with an integrated catchment model (Mike She) - Identification of relevant parameters influencing spring discharge. Journal of Hydrology, v. 426-427- p 112-123. Jukić, D., and Denić-Jukić, V., 2009. Groundwater balance estimation in karst by using a conceptual rainfall-runoff model. Journal of Hydrology, v. 373- p 302-315

Vulnerability analysis for a drought Early Warning System

NASA Astrophysics Data System (ADS)

Angeluccetti, Irene; Demarchi, Alessandro; Perez, Francesca

2014-05-01

Early Warning Systems (EWS) for drought are often based on risk models that do not, or marginally, take into account the vulnerability factor. The multifaceted nature of drought (hydrological, meteorological, and agricultural) is source of coexistence for different ways to measure this phenomenon and its effects. The latter, together with the complexity of impacts generated by this hazard, causes the current underdevelopment of drought EWS compared to other hazards. In Least Developed Countries, where drought events causes the highest numbers of affected people, the importance of correct monitoring and forecasting is considered essential. Existing early warning and monitoring systems for drought produced at different geographic levels, provide only in a few cases an actual spatial model that tries to describe the cause-effect link between where the hazard is detected and where impacts occur. Integrate vulnerability information in such systems would permit to better estimate affected zones and livelihoods, improving the effectiveness of produced hazard-related datasets and maps. In fact, the need of simplification and, in general, of a direct applicability of scientific outputs is still a matter of concern for field experts and early warning products end-users. Even if the surplus of hazard related information produced right after catastrophic events has, in some cases, led to the creation of specific data-sharing platforms, the conveyed meaning and usefulness of each product has not yet been addressed. The present work is an attempt to fill this gap which is still an open issue for the scientific community as well as for the humanitarian aid world. The study aims at conceiving a simplified vulnerability model to embed into an existing EWS for drought, which is based on the monitoring of vegetation phenological parameters and the Standardized Precipitation Index, both produced using free satellite derived datasets. The proposed vulnerability model includes (i) a pure agricultural vulnerability and (ii) a systemic vulnerability. The first considers the agricultural potential of terrains, the diversity of cultivated crops and the percentage of irrigated area as main driving factors. The second vulnerability aspect consists of geographic units in which a set of socio-economic factors are modeled geographically on the basis of the physical accessibility to market centers in one case, and according to a spatial gravity model of market areas in another case. Results of the model applied to a case study (Niger) and evaluated with food insecurity data, are presented.

Vulnerability to the transmission of human visceral leishmaniasis in a Brazilian urban area.

PubMed

Toledo, Celina Roma Sánchez de; Almeida, Andréa Sobral de; Chaves, Sergio Augusto de Miranda; Sabroza, Paulo Chagastelles; Toledo, Luciano Medeiros; Caldas, Jefferson Pereira

2017-05-15

To analyze the determinants for the occurrence of human visceral leishmaniasis linked to the conditions of vulnerability. This is an ecological study, whose spatial analysis unit was the Territorial Analysis Unit in Araguaína, State of Tocantins, Brazil, from 2007 to 2012. We have carried out an analysis of the sociodemographic and urban infrastructure situation of the municipality. Normalized primary indicators were calculated and used to construct the indicators of vulnerability of the social structure, household structure, and urban infrastructure. From them, we have composed a vulnerability index. Kernel density estimation was used to evaluate the density of cases of human visceral leishmaniasis, based on the coordinates of the cases. Bivariate global Moran's I was used to verify the existence of spatial autocorrelation between the incidence of human visceral leishmaniasis and the indicators and index of vulnerability. Bivariate local Moran's I was used to identify spatial clusters. We have observed a pattern of centrifugal spread of human visceral leishmaniasis in the municipality, where outbreaks of the disease have progressively reached central and peri-urban areas. There has been no correlation between higher incidences of human visceral leishmaniasis and worse living conditions. Statistically significant clusters have been observed between the incidences of human visceral leishmaniasis in both periods analyzed (2007 to 2009 and 2010 to 2012) and the indicators and index of vulnerability. The environment in circumscribed areas helps as protection factor or increases the local vulnerability to the occurrence of human visceral leishmaniasis. The use of methodology that analyzes the conditions of life of the population and the spatial distribution of human visceral leishmaniasis is essential to identify the most vulnerable areas to the spread/maintenance of the disease. Analisar determinantes para a ocorrência da leishmaniose visceral humana vinculados às condições de vulnerabilidade. Estudo ecológico, cuja unidade de análise espacial foi a Unidade de Análise Territorial em Araguaína, TO, de 2007 a 2012. Foi realizada análise da situação sociodemográfica e de infraestrutura urbana no município. Indicadores primários normalizados foram calculados e utilizados na construção de indicadores de vulnerabilidade de estrutura social, de estrutura domiciliar e de infraestrutura urbana. A partir deles, foi composto um índice de vulnerabilidade. A estimativa de Kernel foi utilizada para avaliar a densidade de casos de leishmaniose visceral humana, com base nas coordenadas dos casos. O I-Moran Global Bivariado foi empregado para verificar a existência de autocorrelação espacial entre a incidência de leishmaniose visceral humana e os indicadores e índice de vulnerabilidade. I-Moran Local Bivariado foi utilizado para identificar clusters espaciais. Foi observado um padrão de disseminação centrífuga da leishmaniose visceral humana no município, em que surtos da doença atingiram progressivamente áreas centrais e periurbanas. Houve correlação entre maiores incidências de leishmaniose visceral humana e piores condições de vida. Foram observados clusters estatisticamente significativos entre as incidências de leishmaniose visceral humana nos dois períodos analisados (2007 a 2009 e 2010 a 2012) e os indicadores e índice de vulnerabilidade. O ambiente em áreas circunscritas contribui como fator de proteção ou aumenta a vulnerabilidade local à ocorrência de leishmaniose visceral humana. O uso de metodologia que analisa as condições de vida da população e distribuição espacial da leishmaniose visceral humana é essencial na identificação de áreas mais vulneráveis à disseminação/manutenção da doença.

[Integrated assessment of eco-environmental vulnerability in Pearl River Delta based on RS and GIS].

PubMed

Xu, Qing-Yong; Huang, Mei; Liu, Hong-Sheng; Yan, Hui-Min

2011-11-01

Based on the remote sensing data and with the help of geographic information system, an integrated assessment was conducted on the eco-environmental vulnerability of Pearl River Delta in 2004-2008. Spatial principal component analysis was used to generate the evaluation indicators, and analytic hierarchy process (AHP) was applied to determine the weights of the evaluation factors. The reasons causing the vulnerability of the eco- environment in Pearl River Delta were discussed. In the study area, its middle part was the most vulnerable region, occupying 34.0% of the total, eastern part was the moderately vulnerable region, accounting for 25.5%, and western part was the lightly and slightly vulnerable areas, accounting for 28.7 and 11.8%, respectively. Totally, the moderately and lightly vulnerable areas occupied 54.2%, indicating that a majority of the Delta was under moderate and light vulnerability. The natural factors affecting the eco-environmental vulnerability of the Delta were altitude, heavy rain days, water and soil erosion rate, flooded infield rate, normalized difference vegetation index (ND VI) and landscape diversity index, whereas the human factors were population density, waste discharge per unit area, exhaust emission per unit area, land use change, chemical fertilization intensity, pesticide application intensity, amount of motor vehicles possessed by ten thousands people, and index of environmental protection investment. The main characteristics of the extremely and heavily vulnerable regions were low altitude, high frequency of flood disaster, large flooded infield, serious vegetation degradation, high pollution level and low environment protection investment index.

An Ambulatory Method of Identifying Anterior Cruciate Ligament Reconstructed Gait Patterns

PubMed Central

Patterson, Matthew R.; Delahunt, Eamonn; Sweeney, Kevin T.; Caulfield, Brian

2014-01-01

The use of inertial sensors to characterize pathological gait has traditionally been based on the calculation of temporal and spatial gait variables from inertial sensor data. This approach has proved successful in the identification of gait deviations in populations where substantial differences from normal gait patterns exist; such as in Parkinsonian gait. However, it is not currently clear if this approach could identify more subtle gait deviations, such as those associated with musculoskeletal injury. This study investigates whether additional analysis of inertial sensor data, based on quantification of gyroscope features of interest, would provide further discriminant capability in this regard. The tested cohort consisted of a group of anterior cruciate ligament reconstructed (ACL-R) females and a group of non-injured female controls, each performed ten walking trials. Gait performance was measured simultaneously using inertial sensors and an optoelectronic marker based system. The ACL-R group displayed kinematic and kinetic deviations from the control group, but no temporal or spatial deviations. This study demonstrates that quantification of gyroscope features can successfully identify changes associated with ACL-R gait, which was not possible using spatial or temporal variables. This finding may also have a role in other clinical applications where small gait deviations exist. PMID:24451464

Estimation and impact assessment of input and parameter uncertainty in predicting groundwater flow with a fully distributed model

NASA Astrophysics Data System (ADS)

Touhidul Mustafa, Syed Md.; Nossent, Jiri; Ghysels, Gert; Huysmans, Marijke

2017-04-01

Transient numerical groundwater flow models have been used to understand and forecast groundwater flow systems under anthropogenic and climatic effects, but the reliability of the predictions is strongly influenced by different sources of uncertainty. Hence, researchers in hydrological sciences are developing and applying methods for uncertainty quantification. Nevertheless, spatially distributed flow models pose significant challenges for parameter and spatially distributed input estimation and uncertainty quantification. In this study, we present a general and flexible approach for input and parameter estimation and uncertainty analysis of groundwater models. The proposed approach combines a fully distributed groundwater flow model (MODFLOW) with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. To avoid over-parameterization, the uncertainty of the spatially distributed model input has been represented by multipliers. The posterior distributions of these multipliers and the regular model parameters were estimated using DREAM. The proposed methodology has been applied in an overexploited aquifer in Bangladesh where groundwater pumping and recharge data are highly uncertain. The results confirm that input uncertainty does have a considerable effect on the model predictions and parameter distributions. Additionally, our approach also provides a new way to optimize the spatially distributed recharge and pumping data along with the parameter values under uncertain input conditions. It can be concluded from our approach that considering model input uncertainty along with parameter uncertainty is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds.

Is a clean river fun for all? Recognizing social vulnerability in watershed planning.

PubMed

Cutts, Bethany B; Greenlee, Andrew J; Prochaska, Natalie K; Chantrill, Carolina V; Contractor, Annie B; Wilhoit, Juliana M; Abts, Nancy; Hornik, Kaitlyn

2018-01-01

Watershed planning can lead to policy innovation and action toward environmental protection. However, groups often suffer from low engagement with communities that experience disparate impacts from flooding and water pollution. This can limit the capacity of watershed efforts to dismantle pernicious forms of social inequality. As a result, the benefits of environmental changes often flow to more empowered residents, short-changing the power of watershed-based planning as a tool to transform ecological, economic, and social relationships. The objectives of this paper are to assess whether the worldview of watershed planning actors are sufficiently attuned to local patterns of social vulnerability and whether locally significant patterns of social vulnerability can be adequately differentiated using conventional data sources. Drawing from 35 in-depth interviews with watershed planners and community stakeholders in the Milwaukee River Basin (WI, USA), we identify five unique definitions of social vulnerability. Watershed planners in our sample articulate a narrower range of social vulnerability definitions than other participants. All five definitions emphasize spatial and demographic characteristics consistent with existing ways of measuring social vulnerability. However, existing measures do not adequately differentiate among the spatio-temporal dynamics used to distinguish definitions. In response, we develop two new social vulnerability measures. The combination of interviews and demographic analyses in this study provides an assessment technique that can help watershed planners (a) understand the limits of their own conceptualization of social vulnerability and (b) acknowledge the importance of place-based vulnerabilities that may otherwise be obscured. We conclude by discussing how our methods can be a useful tool for identifying opportunities to disrupt social vulnerability in a watershed by evaluating how issue frames, outreach messages, and engagement tactics. The approach allows watershed planners to shift their own culture in order to consider socially vulnerable populations comprehensively.

Is a clean river fun for all? Recognizing social vulnerability in watershed planning

PubMed Central

Greenlee, Andrew J.; Prochaska, Natalie K.; Chantrill, Carolina V.; Contractor, Annie B.; Wilhoit, Juliana M.; Abts, Nancy; Hornik, Kaitlyn

2018-01-01

Watershed planning can lead to policy innovation and action toward environmental protection. However, groups often suffer from low engagement with communities that experience disparate impacts from flooding and water pollution. This can limit the capacity of watershed efforts to dismantle pernicious forms of social inequality. As a result, the benefits of environmental changes often flow to more empowered residents, short-changing the power of watershed-based planning as a tool to transform ecological, economic, and social relationships. The objectives of this paper are to assess whether the worldview of watershed planning actors are sufficiently attuned to local patterns of social vulnerability and whether locally significant patterns of social vulnerability can be adequately differentiated using conventional data sources. Drawing from 35 in-depth interviews with watershed planners and community stakeholders in the Milwaukee River Basin (WI, USA), we identify five unique definitions of social vulnerability. Watershed planners in our sample articulate a narrower range of social vulnerability definitions than other participants. All five definitions emphasize spatial and demographic characteristics consistent with existing ways of measuring social vulnerability. However, existing measures do not adequately differentiate among the spatio-temporal dynamics used to distinguish definitions. In response, we develop two new social vulnerability measures. The combination of interviews and demographic analyses in this study provides an assessment technique that can help watershed planners (a) understand the limits of their own conceptualization of social vulnerability and (b) acknowledge the importance of place-based vulnerabilities that may otherwise be obscured. We conclude by discussing how our methods can be a useful tool for identifying opportunities to disrupt social vulnerability in a watershed by evaluating how issue frames, outreach messages, and engagement tactics. The approach allows watershed planners to shift their own culture in order to consider socially vulnerable populations comprehensively. PMID:29715285

SOURCE ATTRIBUTION OF RADIATIVE FORCING FROM SHORT LIVED CLIMATE FORCING AGENTS

EPA Science Inventory

The immediate project result is quantification of the pre-industrial to present forcing for anthropogenic emissions, the radiative effects of natural emissions, and spatial distribution of the radiative forcing efficiency for key aerosol and O3 precursors (i.e., mW/m^2<...

Development of Mobile Tracer Correlation Strategies for Quantification of Emissions from Landfills and Other Large Area Sources

EPA Science Inventory

Emission measurements from large area sources such as landfills are complicated by their spatial extent and heterogeneous nature. In recent years, an on-site optical remote sensing (ORS) technique for characterizing emissions from area sources was described in an EPA-published p...

Vulnerability to Climate Change in Rural Nicaragua

NASA Astrophysics Data System (ADS)

Byrne, T. R.; Townshend, I.; Byrne, J. M.; McDaniel, S. A.

2013-12-01

While there is a growing recognition of the impact that climate change may have on human development, there has been a shift in focus from an impacts-led assessment approach towards a vulnerability-led assessment approach. This research operationalizes the IPCC's definition of vulnerability in a sub-national assessment to understand how different factors that shape vulnerability to climate change vary spatially across rural Nicaragua. The research utilizes the Food and Agriculture Organization of the United Nations' (FAO UN) CropWat model to evaluate how the annual yield of two of Nicaragua's staple crops may change under projected changes in temperature and precipitation. This analysis of agricultural sensitivity under exposure to climate change is then overlain with an indicator-based assessment of adaptive capacity in rural Nicaraguan farming households. Adaptive capacity was evaluated using household survey data from the 2001 National Household Survey on Living Standards Measurement, which was provided to us by the FAO UN. The result is a map representing current vulnerability to future climate change, and can serve as a basis for targeting policy interventions in rural Nicaragua.

Using Fuzzy Analytic Hierarchy Process multicriteria and Geographical information system for coastal vulnerability analysis in Morocco: The case of Mohammedia

NASA Astrophysics Data System (ADS)

Tahri, Meryem; Maanan, Mohamed; Hakdaoui, Mustapha

2016-04-01

This paper shows a method to assess the vulnerability of coastal risks such as coastal erosion or submarine applying Fuzzy Analytic Hierarchy Process (FAHP) and spatial analysis techniques with Geographic Information System (GIS). The coast of the Mohammedia located in Morocco was chosen as the study site to implement and validate the proposed framework by applying a GIS-FAHP based methodology. The coastal risk vulnerability mapping follows multi-parametric causative factors as sea level rise, significant wave height, tidal range, coastal erosion, elevation, geomorphology and distance to an urban area. The Fuzzy Analytic Hierarchy Process methodology enables the calculation of corresponding criteria weights. The result shows that the coastline of the Mohammedia is characterized by a moderate, high and very high level of vulnerability to coastal risk. The high vulnerability areas are situated in the east at Monika and Sablette beaches. This technical approach is based on the efficiency of the Geographic Information System tool based on Fuzzy Analytical Hierarchy Process to help decision maker to find optimal strategies to minimize coastal risks.

Physically-based modelling of high magnitude torrent events with uncertainty quantification

NASA Astrophysics Data System (ADS)

Wing-Yuen Chow, Candace; Ramirez, Jorge; Zimmermann, Markus; Keiler, Margreth

2017-04-01

High magnitude torrent events are associated with the rapid propagation of vast quantities of water and available sediment downslope where human settlements may be established. Assessing the vulnerability of built structures to these events is a part of consequence analysis, where hazard intensity is related to the degree of loss sustained. The specific contribution of the presented work describes a procedure simulate these damaging events by applying physically-based modelling and to include uncertainty information about the simulated results. This is a first step in the development of vulnerability curves based on several intensity parameters (i.e. maximum velocity, sediment deposition depth and impact pressure). The investigation process begins with the collection, organization and interpretation of detailed post-event documentation and photograph-based observation data of affected structures in three sites that exemplify the impact of highly destructive mudflows and flood occurrences on settlements in Switzerland. Hazard intensity proxies are then simulated with the physically-based FLO-2D model (O'Brien et al., 1993). Prior to modelling, global sensitivity analysis is conducted to support a better understanding of model behaviour, parameterization and the quantification of uncertainties (Song et al., 2015). The inclusion of information describing the degree of confidence in the simulated results supports the credibility of vulnerability curves developed with the modelled data. First, key parameters are identified and selected based on literature review. Truncated a priori ranges of parameter values were then defined by expert solicitation. Local sensitivity analysis is performed based on manual calibration to provide an understanding of the parameters relevant to the case studies of interest. Finally, automated parameter estimation is performed to comprehensively search for optimal parameter combinations and associated values, which are evaluated using the observed data collected in the first stage of the investigation. O'Brien, J.S., Julien, P.Y., Fullerton, W. T., 1993. Two-dimensional water flood and mudflow simulation. Journal of Hydraulic Engineering 119(2): 244-261.
 Song, X., Zhang, J., Zhan, C., Xuan, Y., Ye, M., Xu C., 2015. Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical frameworks, Journal of Hydrology 523: 739-757.

Spatial resolution properties of motion-compensated tomographic image reconstruction methods.

PubMed

Chun, Se Young; Fessler, Jeffrey A

2012-07-01

Many motion-compensated image reconstruction (MCIR) methods have been proposed to correct for subject motion in medical imaging. MCIR methods incorporate motion models to improve image quality by reducing motion artifacts and noise. This paper analyzes the spatial resolution properties of MCIR methods and shows that nonrigid local motion can lead to nonuniform and anisotropic spatial resolution for conventional quadratic regularizers. This undesirable property is akin to the known effects of interactions between heteroscedastic log-likelihoods (e.g., Poisson likelihood) and quadratic regularizers. This effect may lead to quantification errors in small or narrow structures (such as small lesions or rings) of reconstructed images. This paper proposes novel spatial regularization design methods for three different MCIR methods that account for known nonrigid motion. We develop MCIR regularization designs that provide approximately uniform and isotropic spatial resolution and that match a user-specified target spatial resolution. Two-dimensional PET simulations demonstrate the performance and benefits of the proposed spatial regularization design methods.

Spatial heterogeneity in human activities favors the persistence of wolves in agroecosystems.

PubMed

Ahmadi, Mohsen; López-Bao, José Vicente; Kaboli, Mohammad

2014-01-01

As human populations expand, there is increasing demand and pressure for land. Under this scenario, behavioural flexibility and adaptation become important processes leading to the persistence of large carnivores in human-dominated landscapes such as agroecosystems. A growing interest has recently emerged on the outcome of the coexistence between wolves and humans in these systems. It has been suggested that spatial heterogeneity in human activities would be a major environmental factor modulating vulnerability and persistence of this contentious species in agroecosystems. Here, we combined information from 35 den sites detected between 2011 and 2012 in agroecosystems of western Iran (Hamedan province), a set of environmental variables measured at landscape and fine spatial scales, and generalized linear models to identify patterns of den site selection by wolves in a highly-modified agroecosystem. On a landscape level, wolves selected a mixture of rangelands with scattered dry-farms on hillsides (showing a low human use) to locate their dens, avoiding areas with high densities of settlements and primary roads. On a fine spatial scale, wolves primarily excavated dens into the sides of elevated steep-slope hills with availability of water bodies in the vicinity of den sites, and wolves were relegated to dig in places with coarse-soil particles. Our results suggest that vulnerability of wolves in human-dominated landscapes could be compensated by the existence of spatial heterogeneity in human activities. Such heterogeneity would favor wolf persistence in agroecosystems favoring a land sharing model of coexistence between wolves and people.

Spatial Heterogeneity in Human Activities Favors the Persistence of Wolves in Agroecosystems

PubMed Central

Ahmadi, Mohsen; López-Bao, José Vicente; Kaboli, Mohammad

2014-01-01

As human populations expand, there is increasing demand and pressure for land. Under this scenario, behavioural flexibility and adaptation become important processes leading to the persistence of large carnivores in human-dominated landscapes such as agroecosystems. A growing interest has recently emerged on the outcome of the coexistence between wolves and humans in these systems. It has been suggested that spatial heterogeneity in human activities would be a major environmental factor modulating vulnerability and persistence of this contentious species in agroecosystems. Here, we combined information from 35 den sites detected between 2011 and 2012 in agroecosystems of western Iran (Hamedan province), a set of environmental variables measured at landscape and fine spatial scales, and generalized linear models to identify patterns of den site selection by wolves in a highly-modified agroecosystem. On a landscape level, wolves selected a mixture of rangelands with scattered dry-farms on hillsides (showing a low human use) to locate their dens, avoiding areas with high densities of settlements and primary roads. On a fine spatial scale, wolves primarily excavated dens into the sides of elevated steep-slope hills with availability of water bodies in the vicinity of den sites, and wolves were relegated to dig in places with coarse-soil particles. Our results suggest that vulnerability of wolves in human-dominated landscapes could be compensated by the existence of spatial heterogeneity in human activities. Such heterogeneity would favor wolf persistence in agroecosystems favoring a land sharing model of coexistence between wolves and people. PMID:25251567

Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clair, Geremy; Piehowski, Paul D.; Nicola, Teodora

Global proteomics approaches allow characterization of whole tissue lysates to an impressive depth. However, it is now increasingly recognized that to better understand the complexity of multicellular organisms, global protein profiling of specific spatially defined regions/substructures of tissues (i.e. spatially-resolved proteomics) is essential. Laser capture microdissection (LCM) enables microscopic isolation of defined regions of tissues preserving crucial spatial information. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, and that impact measurement robustness, quantification, and throughput. Here, we coupled LCM with a fully automated sample preparation workflow thatmore » with a single manual step allows: protein extraction, tryptic digestion, peptide cleanup and LC-MS/MS analysis of proteomes from microdissected tissues. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis, our approach demonstrated significant improvements in quantification and throughput. Using our LCM-SNaPP proteomics approach, we characterized to a depth of more than 3,400 proteins, the ontogeny of protein changes during normal lung development in laser capture microdissected alveolar tissue containing ~4,000 cells per sample. Importantly, the data revealed quantitative changes for 350 low abundance transcription factors and signaling molecules, confirming earlier transcript-level observations and defining seven modules of coordinated transcription factor/signaling molecule expression patterns, suggesting that a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. Our LCM-proteomics approach facilitates efficient, spatially-resolved, ultrasensitive global proteomics analyses in high-throughput that will be enabling for several clinical and biological applications.« less

Future Midwestern Landscapes Environmental Decision Toolkit Prototype

EPA Science Inventory

Here you can explore spatial data describing environmental conditions across EPA’s regions, view assessment results on overall conditions and vulnerabilities for the region, create indices to represent certain perspectives or identify specific areas for management actions, and co...

[Effects of land use change on landscape pattern vulnerability in Yinchuan Basin, Northwest China].

PubMed

Ren, Zhi-yuan; Zhang, Han

2016-01-01

Landscape pattern vulnerability reflects the instability and sensitivity of ecological system to external disturbances and helps to understand the status and trend of ecological environment. This paper used landscape sensitivity index and landscape adaptability index to construct the landscape pattern vulnerability index of Yinchuan Basin, and got the distribution of the landscape pattern vulnerability in 2001 and 2013. Our study explored the effect of the land use degree composite index, the integrated land use dynamic degree, the importance index of land use change and various types of land transfer on landscape pattern vulnerability. Results showed that the land use degree composite index was mainly caused by the increase of the arable land, forest and the construction land. The higher proportion of the arable land or forest, the lower the vulnerability was, and the construction land had the opposite effect. With the increase of integrated land use dynamic degree, the construction land significantly increased the vulnerability, followed by grassland, and the forest significantly decreased the vulnerability, followed by the arable land. As the importance index of land use change increasing, the arable land could significantly decrease the vulnerability, followed by the forest, the grassland had a weaker trend with no obvious pattern, and the construction land significantly increased the vulnerability. When the arable land, forest and the grassland were the maintypes of land use transfer, the increasing proportion of the construction land increased the vulnerability. When the construction land was the main type of land use transfer, the grassland and forest improved the vulnerability and the arable land had the opposite effect. Changes in the number of land use types influenced the spatial structure of land use to a certain extent, which could offer a reference on using and developing the land resources scientifically. The ternary diagram could reflect the impact of various types of and use change on the landscape vulnerability, which diagram enriched the content of the research on the land use and change.

Conflict of spatial development and water supply under climate change in case of water dependent ecosystem of Ljubljana Moor

NASA Astrophysics Data System (ADS)

Bračič Železnik, Branka; Souvent, Petra; Čenčur Curk, Barbara

2013-04-01

Water resources are vulnerable to climate change and to many other socio-economic drivers of change. A key aspect of vulnerability is that it is spatially variable, reflecting variations of physical and socio-economic conditions. Given the real representation of vulnerability and a set of climate change adaptation options there is need to develop a common transnational strategy for vulnerability reduction. The latter is the goal of SEE CC-WARE project. Among others, ecosystem services, land use change, improving water use efficiency and economic incentives for water management have large potentials to decrease water resources vulnerability. Especially, forests, wetlands and grasslands are important ecosystems, which together with their management emerged as an important means for a sustainable future drinking water supply. The Ljubljana Moor is one of the biggest and most important complexes of wet meadows in Slovenia, which have, due to land use high biodiversity. The Ljubljana Moor extends from the southern part of Ljubljana, the capital of Slovenia, where in the last two centuries extensive irrigation and river regulation projects were implemented to develop agricultural land. Biodiversity of the area is high due to large zones of wet meadows, some flood forest patches, bog areas, and open water courses habitats. The Ljubljana Moor is therefore protected as Natura 2000 site. The Ljubljana Moor is changing very fast and impacts are especially intense in the present years, mostly due to spreading of urbanization and monocultures. In this area the water well field Brest has been designed as important future drinking water source for Ljubljana, pumping mainly water from confined aquifer. The pressure from urbanisation and agriculture and high subsidence that are noticed in the central and eastern part of the aquifer, those two phenomena pose high risk to stable drinking water supply and wetland habitats that are protected as NATURA 2000. Water protection areas with limitation of land use were delineated for protection of drinking water from Brest pumping station. A part of Ljubljana Moor area is also protected as Landscape Park. These legal acts are in conflict with existing agricultural practices, spatial development plans and further urbanisation processes (including new and larger roads, flood areas disconnections and destruction). No attention has been given yet to integrated water management and there is no consideration of long term hydrological and hydrogeological processes.

Modelling social vulnerability in sub-Saharan West Africa using a geographical information system

PubMed Central

Arokoyu, Samuel B.

2015-01-01

In recent times, disasters and risk management have gained significant attention, especially with increasing awareness of the risks and increasing impact of natural and other hazards especially in the developing world. Vulnerability, the potential for loss of life or property from disaster, has biophysical or social dimensions. Social vulnerability relates to societal attributes which has negative impacts on disaster outcomes. This study sought to develop a spatially explicit index of social vulnerability, thus addressing the dearth of research in this area in sub-Saharan Africa. Nineteen variables were identified covering various aspects. Descriptive analysis of these variables revealed high heterogeneity across the South West region of Nigeria for both the state and the local government areas (LGAs). Feature identification using correlation analysis identified six important variables. Factor analysis identified two dimensions, namely accessibility and socioeconomic conditions, from this subset. A social vulnerability index (SoVI) showed that Ondo and Ekiti have more vulnerable LGAs than other states in the region. About 50% of the LGAs in Osun and Ogun have a relatively low social vulnerability. Distribution of the SoVI shows that there are great differences within states as well as across regions. Scores of population density, disability and poverty have a high margin of error in relation to mean state scores. The study showed that with a geographical information system there are opportunities to model social vulnerability and monitor its evolution and dynamics across the continent.

Vulnerability of forest vegetation to anthropogenic climate change in China.

PubMed

Wan, Ji-Zhong; Wang, Chun-Jing; Qu, Hong; Liu, Ran; Zhang, Zhi-Xiang

2018-04-15

China has large areas of forest vegetation that are critical to biodiversity and carbon storage. It is important to assess vulnerability of forest vegetation to anthropogenic climate change in China because it may change the distributions and species compositions of forest vegetation. Based on the equilibrium assumption of forest communities across different spatial and temporal scales, we used species distribution modelling coupled with endemics-area relationship to assess the vulnerability of 204 forest communities across 16 vegetation types under different climate change scenarios in China. By mapping the vulnerability of forest vegetation to climate change, we determined that 78.9% and 61.8% of forest vegetation should be relatively stable in the low and high concentration scenarios, respectively. There were large vulnerable areas of forest vegetation under anthropogenic climate change in northeastern and southwestern China. The vegetation of subtropical mixed broadleaf evergreen and deciduous forest, cold-temperate and temperate mountains needleleaf forest, and temperate mixed needleleaf and broadleaf deciduous forest types were the most vulnerable under climate change. Furthermore, the vulnerability of forest vegetation may increase due to high greenhouse gas concentrations. Given our estimates of forest vegetation vulnerability to anthropogenic climate change, it is critical that we ensure long-term monitoring of forest vegetation responses to future climate change to assess our projections against observations. We need to better integrate projected changes of temperature and precipitation into climate-adaptive conservation strategies for forest vegetation in China. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying human vulnerability in rural areas: case study of Tutova Hills (Eastern Romania)

NASA Astrophysics Data System (ADS)

Stângă, I. C.; Grozavu, A.

2012-06-01

This paper aims to assess the vulnerability at regional level, the model and the proposed indicators being explicitly intended for an essentially rural region, in this case-Tutova Hills (Eastern Romania). Five categories of variables were taken into account to define the vulnerability components: rural habitat, demographic features, agriculture, environmental quality and emergency situations. For each one, five variables were analyzed and ranked based on the level of determination or subordination. In order to ensure the flexibility of the model and to avoid the criteria duplication in assessing vulnerability, only a single indicator of each category was retained and included in analysis: total number of inhabitants, dependency ratio, weight of arable land on slope categories, weight of land under forestry and road accessibility of villages. The selected indicators were mathematically processed in order to maximize their relevance and to unitary express the results in the spread 0-1. Also, values of each indicator were grouped into four classes, corresponding to the level of vulnerability: low, medium, high and very high. A general index was obtained through the integration of vulnerability factors in an equation based on the geometric mean. Spatial analysis was based on features of the MicroImages TNTmips 7.3. software, which allow the vulnerability mapping. This approach argues and states that vulnerability assessment through indicator-based methods can be made only according to the level and scale of analysis and related to natural or human conditions of a region.

Mapping eco-environmental vulnerability patterns: An assessment framework based on remote sensing, GIS, and AHP

NASA Astrophysics Data System (ADS)

Anh, N. K.; Liou, Y. A.; Li, M. H.

2016-12-01

The motivation for this study is assessment of the eco-environment vulnerability based on four independent determinants: hydro-meteorology, topography, land resources, and human activities. An assessment framework is proposed to assess the vulnerable eco-environment by using 16 variables with 6 of them constructed from Landsat 8 satellite images. The remaining variables were extracted from digital maps. Each variable was evaluated and spatially mapped with the aid of an analytical hierarchy process (AHP) and geographical information system (GIS). The Thua Thien - Hue Province that has been experiencing natural disasters and urbanization in the recent decades is selected as our study area. An eco-environmental vulnerability map is assorted into six vulnerable levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities, representing 14%, 27%, 17%, 26%, 13%, 3% of the study area, respectively. It is found that heavy and very heavy vulnerable areas appear mainly in the low and medium lands with high intensification of social-economic activities and often suffer from flooding. Tiny percentages of medium and heavy vulnerable levels occur in high land areas probably caused by agricultural practices in highlands, slash and burn cultivation and removal of natural forests with new plantation forests and these regions are usually influenced by landslides, flash flooding. Based on our results, three ecological zones requiring different development and protection solutions are proposed to restore local eco-environment toward sustainable development. Our findings support the idea that eco-environmental vulnerability is driven by anthropogenic processes and enhanced by natural disaster in the Thua Thien-Hue Province.

Spatial Uncertainty Modeling of Fuzzy Information in Images for Pattern Classification

PubMed Central

Pham, Tuan D.

2014-01-01

The modeling of the spatial distribution of image properties is important for many pattern recognition problems in science and engineering. Mathematical methods are needed to quantify the variability of this spatial distribution based on which a decision of classification can be made in an optimal sense. However, image properties are often subject to uncertainty due to both incomplete and imprecise information. This paper presents an integrated approach for estimating the spatial uncertainty of vagueness in images using the theory of geostatistics and the calculus of probability measures of fuzzy events. Such a model for the quantification of spatial uncertainty is utilized as a new image feature extraction method, based on which classifiers can be trained to perform the task of pattern recognition. Applications of the proposed algorithm to the classification of various types of image data suggest the usefulness of the proposed uncertainty modeling technique for texture feature extraction. PMID:25157744

A study on agricultural drought vulnerability at disaggregated level in a highly irrigated and intensely cropped state of India.

PubMed

Murthy, C S; Yadav, Manoj; Mohammed Ahamed, J; Laxman, B; Prawasi, R; Sesha Sai, M V R; Hooda, R S

2015-03-01

Drought is an important global hazard, challenging the sustainable agriculture and food security of nations. Measuring agricultural drought vulnerability is a prerequisite for targeting interventions to improve and sustain the agricultural performance of both irrigated and rain-fed agriculture. In this study, crop-generic agricultural drought vulnerability status is empirically measured through a composite index approach. The study area is Haryana state, India, a prime agriculture state of the country, characterised with low rainfall, high irrigation support and stable cropping pattern. By analysing the multiyear rainfall and crop condition data of kharif crop season (June-October) derived from satellite data and soil water holding capacity and groundwater quality, nine contributing indicators were generated for 120 blocks (sub-district administrative units). Composite indices for exposure, sensitivity and adaptive capacity components were generated after assigning variance-based weightages to the respective input indicators. Agricultural Drought Vulnerability Index (ADVI) was developed through a linear combination of the three component indices. ADVI-based vulnerability categorisation revealed that 51 blocks are with vulnerable to very highly vulnerable status. These blocks are located in the southern and western parts of the state, where groundwater quality is saline and water holding capacity of soils is less. The ADVI map has effectively captured the spatial pattern of agricultural drought vulnerability in the state. Districts with large number of vulnerable blocks showed considerably larger variability of de-trended crop yields. Correlation analysis reveals that crop condition variability, groundwater quality and soil factors are closely associated with ADVI. The vulnerability index is useful to prioritise the blocks for implementation of long-term drought management plans. There is scope for improving the methodology by adding/fine-tuning the indicators and by optimising the weights.

Spatial-temporal eco-environmental vulnerability assessment and its influential factors based on Landsat data

NASA Astrophysics Data System (ADS)

Anh, N. K.; Liou, Y. A.; Ming-Hsu, L.

2016-12-01

Regional land use/land cover (LULC) changes lead to various changes in ecological processes and, in turn, alter regional micro-climate. To understand eco-environmental responses to LULC changes, eco-environmental evaluation is thus required with aims to identify vulnerable regions and influential factors, so that practical measures for environmental protection and management may be proposed. The Thua Thien - Hue Province has been experiencing urbanization at a rapid rate in both population and physical size. The urban land, agricultural land, and aquaculture activities have been invasively into natural space and caused eco-environment deterioration by land desertification, soil erosion, shrinking forest resources,…etc. In this study, an assessment framework that is composed by 11 variables with 9 of them constructed from Landsat time series is proposed to serve as basis to examine eco-environmental vulnerability in the Thua Thien - Hue Province in years 1989, 2003, and 2014. An eco-environmental vulnerability map is assorted into six vulnerability levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities. Result shows that there is an increasing trend in eco-environmental vulnerability in general with expected evolving distributions in heavy and very heavy vulnerability levels, which mainly lying on developed land, bare land, semi bare land, agricultural land, and poor and recovery forests. In contrast, there is a significant decline in potential vulnerability level. The contributing factors of an upward trend in medium, heavy, and very heavy levels include: (i) a large natural forest converted to plantation forest and agriculture land; and (ii) significant expansion of developed land leading to difference in thermal signatures in urban areas as compared with those of the surrounding areas. It is concluded that anthropogenic processes with transformation on LULC has amplified the vulnerability of eco-environment in the study area.

The landscape of fear as an emergent property of heterogeneity: Contrasting patterns of predation risk in grassland ecosystems.

PubMed

Atuo, Fidelis Akunke; O'Connell, Timothy John

2017-07-01

The likelihood of encountering a predator influences prey behavior and spatial distribution such that non-consumptive effects can outweigh the influence of direct predation. Prey species are thought to filter information on perceived predator encounter rates in physical landscapes into a landscape of fear defined by spatially explicit heterogeneity in predation risk. The presence of multiple predators using different hunting strategies further complicates navigation through a landscape of fear and potentially exposes prey to greater risk of predation. The juxtaposition of land cover types likely influences overlap in occurrence of different predators, suggesting that attributes of a landscape of fear result from complexity in the physical landscape. Woody encroachment in grasslands furnishes an example of increasing complexity with the potential to influence predator distributions. We examined the role of vegetation structure on the distribution of two avian predators, Red-tailed Hawk ( Buteo jamaicensis ) and Northern Harrier ( Circus cyaneus ), and the vulnerability of a frequent prey species of those predators, Northern Bobwhite ( Colinus virginianus ). We mapped occurrences of the raptors and kill locations of Northern Bobwhite to examine spatial vulnerability patterns in relation to landscape complexity. We use an offset model to examine spatially explicit habitat use patterns of these predators in the Southern Great Plains of the United States, and monitored vulnerability patterns of their prey species based on kill locations collected during radio telemetry monitoring. Both predator density and predation-specific mortality of Northern Bobwhite increased with vegetation complexity generated by fine-scale interspersion of grassland and woodland. Predation pressure was lower in more homogeneous landscapes where overlap of the two predators was less frequent. Predator overlap created areas of high risk for Northern Bobwhite amounting to 32% of the land area where landscape complexity was high and 7% where complexity was lower. Our study emphasizes the need to evaluate the role of landscape structure on predation dynamics and reveals another threat from woody encroachment in grasslands.

Integrated Ground-based Hyperspectral Imaging and Geochemical Study of the Eagle Ford Group in West Texas

NASA Astrophysics Data System (ADS)

Sun, L.; Khan, S.; Godet, A.

2017-12-01

This study used ground-based hyperspectral imaging to map an outcrop of the Eagle Ford Group in west Texas. The Eagle Ford Group consists of alternating layers of mudstone - wackestone, grainstone - packstone facies and volcanic ash deposits with high total organic carbon content deposited during the Late Cenomanian - Turonian time period. It is one of the few unconventional source rock and reservoirs that have surface representations. Ground-based hyperspectral imaging scanned an outcrop and hand samples at close ranges with very fine spatial resolution (centimeter to sub-millimeter). Spectral absorption modeling of clay minerals and calcite with the modified Gaussian model (MGM) allowed quantification of variations of mineral abundances. Petrographic analysis confirmed mineral identifications and shed light on sedimentary textures. Major element geochemistry confirmed the mineral quantification. Enrichment of molybdenum (Mo) and uranium (U) indicated "unrestricted marine" paleo-hydrogeology and anoxic to euxinic paleo-redox bottom water conditions. Mineral quantification resulted in mapping of mudstone - wackestone, grainstone - packstone facies and claystones (volcanic ash beds). The lack of spatial associations between the grainstones and claystones on the outcrop calls into question the hypothesis that the primary productivity is controlled by iron availability from volcanic ash beds. Hyperspectral remote sensing data also helped in creating a virtual outcrop model with detailed mineralogical compositions, and provided reservoir analog to extract compositional and geo-mechanical characteristics and variations. The utilization of these new techniques in geo-statistical analysis provides a workflow for employing remote sensing in resource exploration and exploitation.

Integrated ground-based hyperspectral imaging and geochemical study of the Eagle Ford Group in West Texas

NASA Astrophysics Data System (ADS)

Sun, Lei; Khan, Shuhab; Godet, Alexis

2018-01-01

This study used ground-based hyperspectral imaging to map an outcrop of the Eagle Ford Group in west Texas. The Eagle Ford Group consists of alternating layers of mudstone - wackestone, grainstone - packstone facies and volcanic ash deposits with high total organic content deposited during the Cenomanian - Turonian time period. It is one of the few unconventional source rock and reservoirs that have surface representations. Ground-based hyperspectral imaging scanned an outcrop and hand samples at close ranges with very fine spatial resolution (centimeter to sub-millimeter). Spectral absorption modeling of clay minerals and calcite with the modified Gaussian model (MGM) allowed quantification of variations of mineral abundances. Petrographic analysis confirmed mineral identifications and shed light on sedimentary textures, and major element geochemistry supported the mineral quantification. Mineral quantification resulted in mapping of mudstone - wackestone, grainstone - packstone facies and bentonites (volcanic ash beds). The lack of spatial associations between the grainstones and bentonites on the outcrop calls into question the hypothesis that the primary productivity is controlled by iron availability from volcanic ash beds. Enrichment of molybdenum (Mo) and uranium (U) indicated "unrestricted marine" paleo-hydrogeology and anoxic to euxinic paleo-redox bottom water conditions. Hyperspectral remote sensing data also helped in creating a virtual outcrop model with detailed mineralogical compositions, and provided reservoir analog to extract compositional and geo-mechanical characteristics and variations. The utilization of these new techniques in geo-statistical analysis provides a workflow for employing remote sensing in resource exploration and exploitation.

A Scenario Based Assessment of Future Groundwater Resources in the Phoenix Active Management Area

NASA Astrophysics Data System (ADS)

Escobar, V. M.; Lant, T. W.

2007-12-01

The availability of future water supplies in central Arizona depends on the interaction of multiple physical and human systems: climate, hydrology, water and land-use policy, urbanization, and regulation. The problem in assessing future water supplies requires untangling these drivers and recasting the issue in a way that acknowledges the inherent uncertainties in climate and population growth predictions while offering meaningful metrics for outcomes under alternative scenarios. Further, the drivers, policy options, and outcomes are spatially heterogeneous - surface water supplies, new urban developments and changes in land-use will not be shared uniformly across the region. Consequently, different geographic regions of the Phoenix metropolitan area will be more vulnerable to shortages in water availability, and these potential vulnerabilities will be more or less severe depending on which factors cause the shortage. The results of this research will make several contributions to existing literature and research products for groundwater conservation and future urban planning. It will provide location specific metrics of water vulnerability and offer a novel approach to groundwater analysis; it will demonstrate the XLRM framework with an application to central Arizona Water resources. Lastly, it will add to the WaterSim climate model by spatializing the groundwater component for the Phoenix Active Management Area.

Species distribution models of two critically endangered deep-sea octocorals reveal fishing impacts on vulnerable marine ecosystems in central Mediterranean Sea.

PubMed

Lauria, V; Garofalo, G; Fiorentino, F; Massi, D; Milisenda, G; Piraino, S; Russo, T; Gristina, M

2017-08-14

Deep-sea coral assemblages are key components of marine ecosystems that generate habitats for fish and invertebrate communities and act as marine biodiversity hot spots. Because of their life history traits, deep-sea corals are highly vulnerable to human impacts such as fishing. They are an indicator of vulnerable marine ecosystems (VMEs), therefore their conservation is essential to preserve marine biodiversity. In the Mediterranean Sea deep-sea coral habitats are associated with commercially important crustaceans, consequently their abundance has dramatically declined due to the effects of trawling. Marine spatial planning is required to ensure that the conservation of these habitats is achieved. Species distribution models were used to investigate the distribution of two critically endangered octocorals (Funiculina quadrangularis and Isidella elongata) in the central Mediterranean as a function of environmental and fisheries variables. Results show that both species exhibit species-specific habitat preferences and spatial patterns in response to environmental variables, but the impact of trawling on their distribution differed. In particular F. quadrangularis can overlap with fishing activities, whereas I. elongata occurs exclusively where fishing is low or absent. This study represents the first attempt to identify key areas for the protection of soft and compact mud VMEs in the central Mediterranean Sea.

Monitoring Seasonal Evapotranspiration in Vulnerable Agriculture using Time Series VHSR Satellite Data

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2015-04-01

The research work stems from the hypothesis that it is possible to perform an estimation of seasonal water needs of olive tree farms under drought periods by cross correlating high spatial, spectral and temporal resolution (~monthly) of satellite data, acquired at well defined time intervals of the phenological cycle of crops, with ground-truth information simultaneously applied during the image acquisitions. The present research is for the first time, demonstrating the coordinated efforts of space engineers, satellite mission control planners, remote sensing scientists and ground teams to record at specific time intervals of the phenological cycle of trees from ground "zero" and from 770 km above the Earth's surface, the status of plants for subsequent cross correlation and analysis regarding the estimation of the seasonal evapotranspiration in vulnerable agricultural environment. The ETo and ETc derived by Penman-Montieth equation and reference Kc tables, compared with new ETd using the Kc extracted from the time series satellite data. Several vegetation indices were also used especially the RedEdge and the chlorophyll one based on WorldView-2 RedEdge and second NIR bands to relate the tree status with water and nutrition needs. Keywords: Evapotransipration, Very High Spatial Resolution - VHSR, time series, remote sensing, vulnerability, agriculture, vegetation indeces.

Spatial Vulnerability: Bacterial Arrangements, Microcolonies, and Biofilms as Responses to Low Rather than High Phage Densities

PubMed Central

Abedon, Stephen T.

2012-01-01

The ability of bacteria to survive and propagate can be dramatically reduced upon exposure to lytic bacteriophages. Study of this impact, from a bacterium’s perspective, tends to focus on phage-bacterial interactions that are governed by mass action, such as can be observed within continuous flow or similarly planktonic ecosystems. Alternatively, bacterial molecular properties can be examined, such as specific phage‑resistance adaptations. In this study I address instead how limitations on bacterial movement, resulting in the formation of cellular arrangements, microcolonies, or biofilms, could increase the vulnerability of bacteria to phages. Principally: (1) Physically associated clonal groupings of bacteria can represent larger targets for phage adsorption than individual bacteria; and (2), due to a combination of proximity and similar phage susceptibility, individual bacteria should be especially vulnerable to phages infecting within the same clonal, bacterial grouping. Consistent with particle transport theory—the physics of movement within fluids—these considerations are suggestive that formation into arrangements, microcolonies, or biofilms could be either less profitable to bacteria when phage predation pressure is high or require more effective phage-resistance mechanisms than seen among bacteria not living within clonal clusters. I consider these ideas of bacterial ‘spatial vulnerability’ in part within a phage therapy context. PMID:22754643

Spatial modeling for estimation of earthquakes economic loss in West Java

NASA Astrophysics Data System (ADS)

Retnowati, Dyah Ayu; Meilano, Irwan; Riqqi, Akhmad; Hanifa, Nuraini Rahma

2017-07-01

Indonesia has a high vulnerability towards earthquakes. The low adaptive capacity could make the earthquake become disaster that should be concerned. That is why risk management should be applied to reduce the impacts, such as estimating the economic loss caused by hazard. The study area of this research is West Java. The main reason of West Java being vulnerable toward earthquake is the existence of active faults. These active faults are Lembang Fault, Cimandiri Fault, Baribis Fault, and also Megathrust subduction zone. This research tries to estimates the value of earthquakes economic loss from some sources in West Java. The economic loss is calculated by using HAZUS method. The components that should be known are hazard (earthquakes), exposure (building), and the vulnerability. Spatial modeling is aimed to build the exposure data and make user get the information easier by showing the distribution map, not only in tabular data. As the result, West Java could have economic loss up to 1,925,122,301,868,140 IDR ± 364,683,058,851,703.00 IDR, which is estimated from six earthquake sources with maximum possibly magnitude. However, the estimation of economic loss value in this research is the worst case earthquakes occurrence which is probably over-estimated.

Electrical resistivity tomography determines the spatial distribution of clay layer thickness and aquifer vulnerability, Kandal Province, Cambodia

NASA Astrophysics Data System (ADS)

Uhlemann, Sebastian; Kuras, Oliver; Richards, Laura A.; Naden, Emma; Polya, David A.

2017-10-01

Despite being rich in water resources, many areas of South East Asia face difficulties in securing clean water supply. This is particularly problematic in regions with a rapidly growing population. In this study, the spatial variability of the thickness of a clay layer, controlling surface - groundwater interactions that affect aquifer vulnerability, was investigated using electrical resistivity tomography (ERT). Data were acquired along two transects, showing significant differences in the imaged resistivities. Borehole samples were analyzed regarding particle density and composition, and linked to their resistivity. The obtained relationships were used to translate the field electrical resistivities into lithologies. Those revealed considerable variations in the thickness of the clay layer, ranging from 0 m up to 25 m. Geochemical data, highlighting zones of increased ingress of surface water into the groundwater, confirmed areas of discontinuities in the clay layer, which act as preferential flow paths. The results may guide urban planning of the Phnom Penh city expansion, in order to supply the growing population with safe water. The presented approach of using geophysics to estimate groundwater availability, accessibility, and vulnerability is not only applicable to Kandal Province, Cambodia, but also to many other areas of fast urbanization in South East Asia and beyond.

LOOKING INTO THE FUTURE OF A REGION

EPA Science Inventory

The U .S. EP A's Regional Vulnerability Assessment (ReVA) program addresses the latter phases of an integrated ecological risk assessment (U .S. EP A 1998) by building on available monitoring data, focusing on synthesizing information on spatial patterns, analyzing and displaying...

A new framework for UAV-based remote sensing data processing and its application in almond water stress quantification

USDA-ARS?s Scientific Manuscript database

With the rapid development of small imaging sensors and unmanned aerial vehicles (UAVs), remote sensing is undergoing a revolution with greatly increased spatial and temporal resolutions. While more relevant detail becomes available, it is a challenge to analyze the large number of images to extract...

Construction of sediment budgets for drainage basins

Treesearch

William E. Dietrich; Thomas Dunne; Neil F. Humphrey; Leslie M. Reid

1982-01-01

Abstract - A sediment budget for a drainage basin is a quantitative statement of the rates of production, transport, and discharge of detritus. To construct a sediment budget for a drainage basin, one must integrate the temporal and spatial variations of transport and storage processes. This requires: recognition and quantification of transport processes, recognition...

Spatial and temporal quantification of forest residue volumes and delivered costs

Treesearch

Lucas A. Wells; Woodam Chung; Nathaniel M. Anderson; John S. Hogland

2016-01-01

Growing demand for bioenergy, biofuels, and bioproducts has increased interests in the utilization of biomass residues from forest treatments as feedstock. In areas with limited history of industrial biomass utilization, uncertainties in the quantity, distribution, and cost of biomass production and logistics can hinder the development of new bio-based...

Forest Stand Canopy Structure Attribute Estimation from High Resolution Digital Airborne Imagery

Treesearch

Demetrios Gatziolis

2006-01-01

A study of forest stand canopy variable assessment using digital, airborne, multispectral imagery is presented. Variable estimation involves stem density, canopy closure, and mean crown diameter, and it is based on quantification of spatial autocorrelation among pixel digital numbers (DN) using variogram analysis and an alternative, non-parametric approach known as...

Quantification of Dynamic [18F]FDG Pet Studies in Acute Lung Injury.

PubMed

Grecchi, Elisabetta; Veronese, Mattia; Moresco, Rosa Maria; Bellani, Giacomo; Pesenti, Antonio; Messa, Cristina; Bertoldo, Alessandra

2016-02-01

This work aims to investigate lung glucose metabolism using 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) positron emission tomography (PET) imaging in acute lung injury (ALI) patients. Eleven ALI patients and five healthy controls underwent a dynamic [(18)F]FDG PET/X-ray computed tomography (CT) scan. The standardized uptake values (SUV) and three different methods for the quantification of glucose metabolism (i.e., ratio, Patlak, and spectral analysis iterative filter, SAIF) were applied both at the region and the voxel levels. SUV reported a lower correlation than the ratio with the net tracer uptake. Patlak and SAIF analyses did not show any significant spatial or quantitative (R(2) > 0.80) difference. The additional information provided by SAIF showed that in lung inflammation, elevated tracer uptake is coupled with abnormal tracer exchanges within and between lung tissue compartments. Full kinetic modeling provides a multi-parametric description of glucose metabolism in the lungs. This allows characterizing the spatial distribution of lung inflammation as well as returning the functional state of the tissues.

Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

NASA Astrophysics Data System (ADS)

Lee, G.; Jun, K. S.; Cung, E. S.

2014-09-01

This study proposes an improved group decision making (GDM) framework that combines VIKOR method with fuzzified data to quantify the spatial flood vulnerability including multi-criteria evaluation indicators. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. Triangular fuzzy numbers are used to consider the uncertainty of weights and the crisp data of proxy variables. This approach can effectively propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the south Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the results from general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods, such as those developed by Borda, Condorcet, and Copeland. The evaluated priorities were significantly dependent on the employed decision-making method. The proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

The mechanisms of neurotoxicity and the selective vulnerability of nervous system sites.

PubMed

Maurer, Laura L; Philbert, Martin A

2015-01-01

The spatial heterogeneity of the structure, function, and cellular composition of the nervous system confers extraordinary complexity and a multiplicity of mechanisms of chemical neurotoxicity. Because of its relatively high metabolic demands and functional dependence on postmitotic neurons, the nervous system is vulnerable to a variety of xenobiotics that affect essential homeostatic mechanisms that support function. Despite protection from the neuroglia and blood-brain barrier, the central nervous system is prone to attack from lipophilic toxicants and those that hijack endogenous transport, receptor, metabolic, and other biochemical systems. The inherent predilection of chemicals for highly conserved biochemical systems confers selective vulnerability of the nervous system to neurotoxicants. This chapter discusses selective vulnerability of the nervous system in the context of neuron-specific decrements (axonopathy, myelinopathy, disruption of neurotransmission), and the degree to which neuronal damage is facilitated or ameliorated by surrounding nonneural cells in both the central and peripheral nervous systems. © 2015 Elsevier B.V. All rights reserved.

Ground-water vulnerability to nitrate contamination in the mid-atlantic region

USGS Publications Warehouse

Greene, Earl A.; LaMotte, Andrew E.; Cullinan, Kerri-Ann; Smith, Elizabeth R.

2005-01-01

The U.S. Environmental Protection Agency?s (USEPA) Regional Vulnerability Assessment (ReVA) Program has developed a set of statistical tools to support regional-scale, integrated ecological risk-assessment studies. One of these tools, developed by the U.S. Geological Survey (USGS), is used with available water-quality data obtained from USGS National Water-Quality Assessment (NAWQA) and other studies in association with land cover, geology, soils, and other geographic data to develop logistic-regression equations that predict the vulnerability of ground water to nitrate concentrations exceeding specified thresholds in the Mid-Atlantic Region. The models were developed and applied to produce spatial probability maps showing the likelihood of elevated concentrations of nitrate in the region. These maps can be used to identify areas that currently are at risk and help identify areas where ground water has been affected by human activities. This information can be used by regional and local water managers to protect water supplies and identify land-use planning solutions and monitoring programs in these vulnerable areas.

Quantification of asymmetric microtubule nucleation at sub-cellular structures

PubMed Central

Zhu, Xiaodong; Kaverina, Irina

2012-01-01

Cell polarization is important for multiple physiological processes. In polarized cells, microtubules (MTs) are organized into a spatially polarized array. Generally, in non-differentiated cells, it is assumed that MTs are symmetrically nucleated exclusively from centrosome (microtubule organizing center, MTOC) and then reorganized into the asymmetric array. We have recently identified the Golgi complex as an additional MTOC that asymmetrically nucleates MTs toward one side of the cell. Methods used for alternative MTOC identification include microtubule re-growth after complete drug-induced depolymerization and tracking of growing microtubules using fluorescence labeled MT +TIP binding proteins in living cells. These approaches can be used for quantification of MT nucleation sites at diverse sub-cellular structures. PMID:21773933

Assessment of Climate Change Vulnerability at the Local Level: A Case Study on the Dniester River Basin (Moldova)

PubMed Central

Sîrodoev, Igor; Koeppel, Sonja; Denisov, Nickolai; Sîrodoev, Ghennadi

2013-01-01

Vulnerability to climate change of the Moldavian part of the Dniester river was assessed as the function of exposure, sensitivity, and adaptive capacity of its basin's natural and socioeconomic systems. As a spatial “scale” of the assessment, Moldova's administrative-territorial units (ATUs) were selected. The exposure assessment was based on the climatic analysis of baseline (1971–2000) temperature and precipitation and projections of their changes in 2021–2050, separately for cold and warm periods. The sensitivity assessment included physiographical and socioeconomic characteristics, described by a set of specific indicators. The adaptive capacity was expressed by general economic and agricultural indicators, taking into consideration the medical provision and housing conditions. Through a ranking approach, the relative vulnerability of each ATU was calculated by summing its sensitivity and adaptive capacity ranks; the latter were obtained as combinations of their primary indicator ranks, arranged in an increasing and decreasing order, respectively. Due to lack of sound knowledge on these components' importance in overall assessment of vulnerability, their weights were taken as conventionally equal. Mapping of vulnerability revealed that ATUs neighboring to municipalities are the most vulnerable and need special attention in climate change adaptation. The basin's “hotspots” were discussed with public participation. PMID:23766677

Quantification of submarine groundwater discharge and its short-term dynamics by linking time-variant end-member mixing analysis and isotope mass balancing (222-Rn)

NASA Astrophysics Data System (ADS)

Petermann, Eric; Knöller, Kay; Stollberg, Reiner; Scholten, Jan; Rocha, Carlos; Weiß, Holger; Schubert, Michael

2017-04-01

Submarine groundwater discharge (SGD) plays a crucial role for the water quality of coastal waters due to associated fluxes of nutrients, organic compounds and/or heavy-metals. Thus, the quantification of SGD is essential for evaluating the vulnerability of coastal water bodies with regard to groundwater pollution as well as for understanding the matter cycles of the connected water bodies. Here, we present a scientific approach for quantifying discharge of fresh groundwater (GWf) and recirculated seawater (SWrec), including its short-term temporal dynamics, into the tide-affected Knysna estuary, South Africa. For a time-variant end-member mixing analysis we conducted time-series observations of radon (222Rn) and salinity within the estuary over two tidal cycles in combination with estimates of the related end-members for seawater, river water, GWf and SWrec. The mixing analysis was treated as constrained optimization problem for finding an end-member mixing ratio that simultaneously fits the observed data for radon and salinity best for every time-step. Uncertainty of each mixing ratio was quantified by Monte Carlo simulations of the optimization procedure considering uncertainty in end-member characterization. Results reveal the highest GWf and SWrec fraction in the estuary during peak low tide with averages of 0.8 % and 1.4 %, respectively. Further, we calculated a radon mass balance that revealed a daily radon flux of 4.8 * 108 Bq into the estuary equivalent to a GWf discharge of 29.000 m3/d (9.000-59.000 m3/d for 25th-75th percentile range) and a SWrec discharge of 80.000 m3/d (45.000-130.000 m3/d for 25th-75th percentile range). The uncertainty of SGD reflects the end-member uncertainty, i.e. the spatial heterogeneity of groundwater composition. The presented approach allows the calculation of mixing ratios of multiple uncertain end-members for time-series measurements of multiple parameters. Linking these results with a tracer mass balance allows conversion of end-member fractions to end-member fluxes.

The role of PET quantification in cardiovascular imaging.

PubMed

Slomka, Piotr; Berman, Daniel S; Alexanderson, Erick; Germano, Guido

2014-08-01

Positron Emission Tomography (PET) has several clinical and research applications in cardiovascular imaging. Myocardial perfusion imaging with PET allows accurate global and regional measurements of myocardial perfusion, myocardial blood flow and function at stress and rest in one exam. Simultaneous assessment of function and perfusion by PET with quantitative software is currently the routine practice. Combination of ejection fraction reserve with perfusion information may improve the identification of severe disease. The myocardial viability can be estimated by quantitative comparison of fluorodeoxyglucose ( 18 FDG) and rest perfusion imaging. The myocardial blood flow and coronary flow reserve measurements are becoming routinely included in the clinical assessment due to enhanced dynamic imaging capabilities of the latest PET/CT scanners. Absolute flow measurements allow evaluation of the coronary microvascular dysfunction and provide additional prognostic and diagnostic information for coronary disease. Standard quantitative approaches to compute myocardial blood flow from kinetic PET data in automated and rapid fashion have been developed for 13 N-ammonia, 15 O-water and 82 Rb radiotracers. The agreement between software methods available for such analysis is excellent. Relative quantification of 82 Rb PET myocardial perfusion, based on comparisons to normal databases, demonstrates high performance for the detection of obstructive coronary disease. New tracers, such as 18 F-flurpiridaz may allow further improvements in the disease detection. Computerized analysis of perfusion at stress and rest reduces the variability of the assessment as compared to visual analysis. PET quantification can be enhanced by precise coregistration with CT angiography. In emerging clinical applications, the potential to identify vulnerable plaques by quantification of atherosclerotic plaque uptake of 18 FDG and 18 F-sodium fluoride tracers in carotids, aorta and coronary arteries has been demonstrated.

A Statistical Graphical Model of the California Reservoir System

NASA Astrophysics Data System (ADS)

Taeb, A.; Reager, J. T.; Turmon, M.; Chandrasekaran, V.

2017-11-01

The recent California drought has highlighted the potential vulnerability of the state's water management infrastructure to multiyear dry intervals. Due to the high complexity of the network, dynamic storage changes in California reservoirs on a state-wide scale have previously been difficult to model using either traditional statistical or physical approaches. Indeed, although there is a significant line of research on exploring models for single (or a small number of) reservoirs, these approaches are not amenable to a system-wide modeling of the California reservoir network due to the spatial and hydrological heterogeneities of the system. In this work, we develop a state-wide statistical graphical model to characterize the dependencies among a collection of 55 major California reservoirs across the state; this model is defined with respect to a graph in which the nodes index reservoirs and the edges specify the relationships or dependencies between reservoirs. We obtain and validate this model in a data-driven manner based on reservoir volumes over the period 2003-2016. A key feature of our framework is a quantification of the effects of external phenomena that influence the entire reservoir network. We further characterize the degree to which physical factors (e.g., state-wide Palmer Drought Severity Index (PDSI), average temperature, snow pack) and economic factors (e.g., consumer price index, number of agricultural workers) explain these external influences. As a consequence of this analysis, we obtain a system-wide health diagnosis of the reservoir network as a function of PDSI.

Development of a process-oriented vulnerability concept for water travel time in karst aquifers-case study of Tanour and Rasoun springs catchment area.

NASA Astrophysics Data System (ADS)

Hamdan, Ibraheem; Sauter, Martin; Ptak, Thomas; Wiegand, Bettina; Margane, Armin; Toll, Mathias

2017-04-01

Key words: Karst aquifer, water travel time, vulnerability assessment, Jordan. The understanding of the groundwater pathways and movement through karst aquifers, and the karst aquifer response to precipitation events especially in the arid to semi-arid areas is fundamental to evaluate pollution risks from point and non-point sources. In spite of the great importance of the karst aquifer for drinking purposes, karst aquifers are highly sensitive to contamination events due to the fast connections between the land-surface and the groundwater (through the karst features) which is makes groundwater quality issues within karst systems very complicated. Within this study, different methods and approaches were developed and applied in order to characterise the karst aquifer system of the Tanour and Rasoun springs (NW-Jordan) and the flow dynamics within the aquifer, and to develop a process-oriented method for vulnerability assessment based on the monitoring of different multi-spatially variable parameters of water travel time in karst aquifer. In general, this study aims to achieve two main objectives: 1. Characterization of the karst aquifer system and flow dynamics. 2. Development of a process-oriented method for vulnerability assessment based on spatially variable parameters of travel time. In order to achieve these aims, different approaches and methods were applied starting from the understanding of the geological and hydrogeological characteristics of the karst aquifer and its vulnerability against pollutants, to using different methods, procedures and monitored parameters in order to determine the water travel time within the aquifer and investigate its response to precipitation event and, finally, with the study of the aquifer response to pollution events. The integrated breakthrough signal obtained from the applied methods and procedures including the using of stable isotopes of oxygen and hydrogen, the monitoring of multi qualitative and quantitative parameters using automated probes and data loggers, and the development of travel time physics-based vulnerability assessment method shows good agreement as an applicable methods to determine the water travel time in karst aquifers, and to investigate its response to precipitation and pollution events.

Impacts of Present and Future Climate Variability on Forest Ecosystem in Mediterranean Region

NASA Astrophysics Data System (ADS)

Ozcan, O.; Musaoglu, N.; Türkeş, M.

2017-12-01

The concept of `climate change vulnerability' helps us to better comprehend the cause/effect relationships behind climate change and its impact on human societies, socioeconomic sectors, physiographical and ecological systems. Herein, multifactorial spatial modeling was applied to evaluate the vulnerability of a Mediterranean forest ecosystem to climate change. Thus, the geographical distribution of the final Environmental Vulnerability Areas (EVAs) of the forest ecosystem are based on the estimated final Environmental Vulnerability Index (EVI) values. This revealed that at current levels of environmental degradation, physical, geographical, policy enforcement and socioeconomic conditions, the area with a "very low" vulnerability degree covered mainly the town, its surrounding settlements and the agricultural lands found mainly over the low and flat travertine plateau and the plains at the east and southeast of the district. The spatial magnitude of the EVAs over the forest ecosystem under the current environmental degradation was also determined. This revealed that the EVAs classed as "very low" account for 21% of the total area of the forest ecosystem, those classed as "low" account for 36%, those classed as "medium" account for 20%, and those classed as "high" account for 24%. Based on regionally averaged future climate assessments and projected future climate indicators, both the study site and the western Mediterranean sub-region of Turkey will probably become associated with a drier, hotter, more continental and more water-deficient climate. This analysis holds true for all future scenarios, with the exception of RCP4.5 for the period from 2015 to 2030. However, the present dry-sub humid climate dominating this sub-region and the study area shows a potential for change towards more dry climatology and for it to become a semiarid climate in the period between 2031 and 2050 according to the RCP8.5 high emission scenario. All the observed and estimated results show clearly that the densest forest ecosystem in the southern part of the study site, which is characterized by mainly Mediterranean coniferous and some mixed forest and the maquis vegetation, will very likely be influenced by medium and high degrees of vulnerability to future environmental degradation, climate change and variability.

Image-guided spatial localization of heterogeneous compartments for magnetic resonance

PubMed Central

An, Li; Shen, Jun

2015-01-01

Purpose: Image-guided localization SPectral Localization Achieved by Sensitivity Heterogeneity (SPLASH) allows rapid measurement of signals from irregularly shaped anatomical compartments without using phase encoding gradients. Here, the authors propose a novel method to address the issue of heterogeneous signal distribution within the localized compartments. Methods: Each compartment was subdivided into multiple subcompartments and their spectra were solved by Tikhonov regularization to enforce smoothness within each compartment. The spectrum of a given compartment was generated by combining the spectra of the components of that compartment. The proposed method was first tested using Monte Carlo simulations and then applied to reconstructing in vivo spectra from irregularly shaped ischemic stroke and normal tissue compartments. Results: Monte Carlo simulations demonstrate that the proposed regularized SPLASH method significantly reduces localization and metabolite quantification errors. In vivo results show that the intracompartment regularization results in ∼40% reduction of error in metabolite quantification. Conclusions: The proposed method significantly reduces localization errors and metabolite quantification errors caused by intracompartment heterogeneous signal distribution. PMID:26328977

X-ray fluorescence at nanoscale resolution for multicomponent layered structures: A solar cell case study

DOE Office of Scientific and Technical Information (OSTI.GOV)

West, Bradley M.; Stuckelberger, Michael; Jeffries, April

The study of a multilayered and multicomponent system by spatially resolved X-ray fluorescence microscopy poses unique challenges in achieving accurate quantification of elemental distributions. This is particularly true for the quantification of materials with high X-ray attenuation coefficients, depth-dependent composition variations and thickness variations. A widely applicable procedure for use after spectrum fitting and quantification is described. This procedure corrects the elemental distribution from the measured fluorescence signal, taking into account attenuation of the incident beam and generated fluorescence from multiple layers, and accounts for sample thickness variations. Deriving from Beer–Lambert's law, formulae are presented in a general integral formmore » and numerically applicable framework. Here, the procedure is applied using experimental data from a solar cell with a Cu(In,Ga)Se 2 absorber layer, measured at two separate synchrotron beamlines with varied measurement geometries. This example shows the importance of these corrections in real material systems, which can change the interpretation of the measured distributions dramatically.« less

X-ray fluorescence at nanoscale resolution for multicomponent layered structures: A solar cell case study

DOE PAGES

West, Bradley M.; Stuckelberger, Michael; Jeffries, April; ...

2017-01-01

The study of a multilayered and multicomponent system by spatially resolved X-ray fluorescence microscopy poses unique challenges in achieving accurate quantification of elemental distributions. This is particularly true for the quantification of materials with high X-ray attenuation coefficients, depth-dependent composition variations and thickness variations. A widely applicable procedure for use after spectrum fitting and quantification is described. This procedure corrects the elemental distribution from the measured fluorescence signal, taking into account attenuation of the incident beam and generated fluorescence from multiple layers, and accounts for sample thickness variations. Deriving from Beer–Lambert's law, formulae are presented in a general integral formmore » and numerically applicable framework. Here, the procedure is applied using experimental data from a solar cell with a Cu(In,Ga)Se 2 absorber layer, measured at two separate synchrotron beamlines with varied measurement geometries. This example shows the importance of these corrections in real material systems, which can change the interpretation of the measured distributions dramatically.« less

Tree-based approach for exploring marine spatial patterns with raster datasets.

PubMed

Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen

2017-01-01

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.

The association between landscape features and transportation corridors on movements and habitat-use patterns of wolverines.

DOT National Transportation Integrated Search

2006-06-01

"Abstract: Wolverines are a rare carnivore that live at low densities and have large spatial : requirements; characteristics that leave them vulnerable to both direct and indirect effects of : highways. Maintaining connectivity between sub-population...

Spatial context learning approach to automatic segmentation of pleural effusion in chest computed tomography images

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Casas, Rafael; Linguraru, Marius G.

2016-03-01

Pleural effusion is an abnormal collection of fluid within the pleural cavity. Excessive accumulation of pleural fluid is an important bio-marker for various illnesses, including congestive heart failure, pneumonia, metastatic cancer, and pulmonary embolism. Quantification of pleural effusion can be indicative of the progression of disease as well as the effectiveness of any treatment being administered. Quantification, however, is challenging due to unpredictable amounts and density of fluid, complex topology of the pleural cavity, and the similarity in texture and intensity of pleural fluid to the surrounding tissues in computed tomography (CT) scans. Herein, we present an automated method for the segmentation of pleural effusion in CT scans based on spatial context information. The method consists of two stages: first, a probabilistic pleural effusion map is created using multi-atlas segmentation. The probabilistic map assigns a priori probabilities to the presence of pleural uid at every location in the CT scan. Second, a statistical pattern classification approach is designed to annotate pleural regions using local descriptors based on a priori probabilities, geometrical, and spatial features. Thirty seven CT scans from a diverse patient population containing confirmed cases of minimal to severe amounts of pleural effusion were used to validate the proposed segmentation method. An average Dice coefficient of 0.82685 and Hausdorff distance of 16.2155 mm was obtained.

Optically based quantification of absolute cerebral metabolic rate of oxygen (CMRO2) with high spatial resolution in rodents

NASA Astrophysics Data System (ADS)

Yaseen, Mohammad A.; Srinivasan, Vivek J.; Sakadžić, Sava; Vinogradov, Sergei A.; Boas, David A.

2010-02-01

Measuring oxygen delivery in brain tissue is important for identifying the pathophysiological changes associated with brain injury and various diseases such as cancer, stroke, and Alzheimer's disease. We have developed a multi-modal imaging system for minimally invasive measurement of cerebral oxygenation and blood flow in small animals with high spatial resolution. The system allows for simultaneous measurement of blood flow using Fourier-domain optical coherence tomography, and oxygen partial pressure (pO2) using either confocal or multiphoton phosphorescence lifetime imaging with exogenous porphyrin-based dyes sensitive to dissolved oxygen. Here we present the changes in pO2 and blood flow in superficial cortical vessels of Sprague Dawley rats in response to conditions such as hypoxia, hyperoxia, and functional stimulation. pO2 measurements display considerable heterogeneity over distances that cannot be resolved with more widely used oxygen-monitoring techniques such as BOLD-fMRI. Large increases in blood flow are observed in response to functional stimulation and hypoxia. Our system allows for quantification of cerebral metabolic rate of oxygen (CMRO2) with high spatial resolution, providing a better understanding of metabolic dynamics during functional stimulation and under various neuropathologies. Ultimately, better insight into the underlying mechanisms of neuropathologies will facilitate the development of improved therapeutic strategies to minimize damage to brain tissue.

A Quantitative Three-Dimensional Image Analysis Tool for Maximal Acquisition of Spatial Heterogeneity Data.

PubMed

Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios

2017-02-01

Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.

MERINOVA: Meteorological risks as drivers of environmental innovation in agro-ecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Oger, Robert; Marlier, Catherine; Van De Vijver, Hans; Vandermeulen, Valerie; Van Huylenbroeck, Guido; Zamani, Sepideh; Curnel, Yannick; Mettepenningen, Evi

2013-04-01

The BELSPO funded project 'MERINOVA' deals with risks associated with extreme weather phenomena and with risks of biological origin such as pests and diseases. The major objectives of the proposed project are to characterise extreme meteorological events, assess the impact on Belgian agro-ecosystems, characterise their vulnerability and resilience to these events, and explore innovative adaptation options to agricultural risk management. The project comprises of five major parts that reflect the chain of risks: (i) Hazard: Assessing the likely frequency and magnitude of extreme meteorological events by means of probability density functions; (ii) Impact: Analysing the potential bio-physical and socio-economic impact of extreme weather events on agro-ecosystems in Belgium using process-based modelling techniques commensurate with the regional scale; (iii) Vulnerability: Identifying the most vulnerable agro-ecosystems using fuzzy multi-criteria and spatial analysis; (iv) Risk Management: Uncovering innovative risk management and adaptation options using actor-network theory and fuzzy cognitive mapping techniques; and, (v) Communication: Communicating to research, policy and practitioner communities using web-based techniques. The different tasks of the MERINOVA project require expertise in several scientific disciplines: meteorology, statistics, spatial database management, agronomy, bio-physical impact modelling, socio-economic modelling, actor-network theory, fuzzy cognitive mapping techniques. These expertises are shared by the four scientific partners who each lead one work package. The MERINOVA project will concentrate on promoting a robust and flexible framework by demonstrating its performance across Belgian agro-ecosystems, and by ensuring its relevance to policy makers and practitioners. Impacts developed from physically based models will not only provide information on the state of the damage at any given time, but also assist in understanding the links between different factors causing damage and determining bio-physical vulnerability. Socio-economic impacts will enlarge the basis for vulnerability mapping, risk management and adaptation options. A strong expert and end-user network will be established to help disseminating and exploiting project results to meet user needs.

Can animal habitat use patterns influence their vulnerability to extreme climate events? An estuarine sportfish case study.

PubMed

Boucek, Ross E; Heithaus, Michael R; Santos, Rolando; Stevens, Philip; Rehage, Jennifer S

2017-10-01

Global climate forecasts predict changes in the frequency and intensity of extreme climate events (ECEs). The capacity for specific habitat patches within a landscape to modulate stressors from extreme climate events, and animal distribution throughout habitat matrices during events, could influence the degree of population level effects following the passage of ECEs. Here, we ask (i) does the intensity of stressors of an ECE vary across a landscape? And (ii) Do habitat use patterns of a mobile species influence their vulnerability to ECEs? Specifically, we measured how extreme cold spells might interact with temporal variability in habitat use to affect populations of a tropical, estuarine-dependent large-bodied fish Common Snook, within Everglades National Park estuaries (FL US). We examined temperature variation across the estuary during cold disturbances with different degrees of severity, including an extreme cold spell. Second, we quantified Snook distribution patterns when the passage of ECEs is most likely to occur from 2012 to 2016 using passive acoustic tracking. Our results revealed spatial heterogeneity in the intensity of temperature declines during cold disturbances, with some habitats being consistently 3-5°C colder than others. Surprisingly, Snook distributions during periods of greatest risk to experience an extreme cold event varied among years. During the winters of 2013-2014 and 2014-2015 a greater proportion of Snook occurred in the colder habitats, while the winters of 2012-2013 and 2015-2016 featured more Snook observed in the warmest habitats. This study shows that Snook habitat use patterns could influence vulnerability to extreme cold events, however, whether Snook habitat use increases or decreases their vulnerability to disturbance depends on the year, creating temporally dynamic vulnerability. Faunal global change research should address the spatially explicit nature of extreme climate events and animal habitat use patterns to identify potential mechanisms that may influence population effects following these disturbances. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Deep-sea seabed habitats: Do they support distinct mega-epifaunal communities that have different vulnerabilities to anthropogenic disturbance?

NASA Astrophysics Data System (ADS)

Bowden, David A.; Rowden, Ashley A.; Leduc, Daniel; Beaumont, Jennifer; Clark, Malcolm R.

2016-01-01

Growing economic interest in seabed resources in the deep-sea highlights the need for information about the spatial distribution and vulnerability to disturbance of benthic habitats and fauna. Categorisation of seabed habitats for management is often based on topographic features such as canyons and seamounts that can be distinguished using regional bathymetry ('mega-habitats'). This is practical but because such habitats are contiguous with others, there is potential for overlap in the communities associated with them. Because concepts of habitat and community vulnerability are based on the traits of individual taxa, the nature and extent of differences between communities have implications for strategies to manage the environmental effects of resource use. Using towed video camera transects, we surveyed mega-epifaunal communities of three topographically-defined habitats (canyon, seamount or knoll, and continental slope) and two physico-chemically defined meso-scale habitats (cold seep and hydrothermal vent) in two regions off New Zealand to assess whether each supports a distinct type of community. Cold seep and hydrothermal vent communities were strongly distinct from those in other habitats. Across the other habitats, however, distinctions between communities were often weak and were not consistent between regions. Dissimilarities among communities across all habitats were stronger and the density of filter-feeding taxa was higher in the Bay of Plenty than on the Hikurangi Margin, whereas densities of predatory and scavenging taxa were higher on the Hikurangi Margin. Substratum diversity at small spatial scales (<1 km) and trawl history were significantly correlated with community composition in both regions. We conclude that, (1) a lack of consistent distinction between communities raises questions about the general utility of topographically-defined mega-habitats in environmental management, (2) fine-scale survey of individual features is necessary to identify the locations, characteristics, and extents of ecologically important or vulnerable seabed communities, and (3) evaluation of habitat vulnerability to future events should be in the context of previous and current disturbances.

Noninvasive Measurement of Vulnerability to Drought-Induced Embolism by X-Ray Microtomography1

PubMed Central

Choat, Brendan; Cochard, Herve; Jansen, Steven

2016-01-01

Hydraulic failure induced by xylem embolism is one of the primary mechanisms of plant dieback during drought. However, many of the methods used to evaluate the vulnerability of different species to drought-induced embolism are indirect and invasive, increasing the possibility that measurement artifacts may occur. Here, we utilize x-ray computed microtomography (microCT) to directly visualize embolism formation in the xylem of living, intact plants with contrasting wood anatomy (Quercus robur, Populus tremula × Populus alba, and Pinus pinaster). These observations were compared with widely used centrifuge techniques that require destructive sampling. MicroCT imaging provided detailed spatial information regarding the dimensions and functional status of xylem conduits during dehydration. Vulnerability curves based on microCT observations of intact plants closely matched curves based on the centrifuge technique for species with short vessels (P. tremula × P. alba) or tracheids (P. pinaster). For ring porous Q. robur, the centrifuge technique significantly overestimated vulnerability to embolism, indicating that caution should be used when applying this technique to species with long vessels. These findings confirm that microCT can be used to assess the vulnerability to embolism on intact plants by direct visualization. PMID:26527655

Noninvasive Measurement of Vulnerability to Drought-Induced Embolism by X-Ray Microtomography.

PubMed

Choat, Brendan; Badel, Eric; Burlett, Regis; Delzon, Sylvain; Cochard, Herve; Jansen, Steven

2016-01-01

Hydraulic failure induced by xylem embolism is one of the primary mechanisms of plant dieback during drought. However, many of the methods used to evaluate the vulnerability of different species to drought-induced embolism are indirect and invasive, increasing the possibility that measurement artifacts may occur. Here, we utilize x-ray computed microtomography (microCT) to directly visualize embolism formation in the xylem of living, intact plants with contrasting wood anatomy (Quercus robur, Populus tremula × Populus alba, and Pinus pinaster). These observations were compared with widely used centrifuge techniques that require destructive sampling. MicroCT imaging provided detailed spatial information regarding the dimensions and functional status of xylem conduits during dehydration. Vulnerability curves based on microCT observations of intact plants closely matched curves based on the centrifuge technique for species with short vessels (P. tremula × P. alba) or tracheids (P. pinaster). For ring porous Q. robur, the centrifuge technique significantly overestimated vulnerability to embolism, indicating that caution should be used when applying this technique to species with long vessels. These findings confirm that microCT can be used to assess the vulnerability to embolism on intact plants by direct visualization. © 2016 American Society of Plant Biologists. All Rights Reserved.

Development of a socio-ecological environmental justice model for watershed-based management

NASA Astrophysics Data System (ADS)

Sanchez, Georgina M.; Nejadhashemi, A. Pouyan; Zhang, Zhen; Woznicki, Sean A.; Habron, Geoffrey; Marquart-Pyatt, Sandra; Shortridge, Ashton

2014-10-01

The dynamics and relationships between society and nature are complex and difficult to predict. Anthropogenic activities affect the ecological integrity of our natural resources, specifically our streams. Further, it is well-established that the costs of these activities are born unequally by different human communities. This study considered the utility of integrating stream health metrics, based on stream health indicators, with socio-economic measures of communities, to better characterize these effects. This study used a spatial multi-factor model and bivariate mapping to produce a novel assessment for watershed management, identification of vulnerable areas, and allocation of resources. The study area is the Saginaw River watershed located in Michigan. In-stream hydrological and water quality data were used to predict fish and macroinvertebrate measures of stream health. These measures include the Index of Biological Integrity (IBI), Hilsenhoff Biotic Index (HBI), Family IBI, and total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa. Stream health indicators were then compared to spatially coincident socio-economic data, obtained from the United States Census Bureau (2010), including race, income, education, housing, and population size. Statistical analysis including spatial regression and cluster analysis were used to examine the correlation between vulnerable human populations and environmental conditions. Overall, limited correlation was observed between the socio-economic data and ecological measures of stream health, with the highest being a negative correlation of 0.18 between HBI and the social parameter household size. Clustering was observed in the datasets with urban areas representing a second order clustering effect over the watershed. Regions with the worst stream health and most vulnerable social populations were most commonly located nearby or down-stream to highly populated areas and agricultural lands.

Modeling Electricity Sector Vulnerabilities and Costs Associated with Water Temperatures Under Scenarios of Climate Change

NASA Astrophysics Data System (ADS)

Macknick, J.; Miara, A.; Brinkman, G.; Ibanez, E.; Newmark, R. L.

2014-12-01

The reliability of the power sector is highly vulnerable to variability in the availability and temperature of water resources, including those that might result from potential climatic changes or from competition from other users. In the past decade, power plants throughout the United States have had to shut down or curtail generation due to a lack of available water or from elevated water temperatures. These disruptions in power plant performance can have negative impacts on energy security and can be costly to address. Analysis of water-related vulnerabilities requires modeling capabilities with high spatial and temporal resolution. This research provides an innovative approach to energy-water modeling by evaluating the costs and reliability of a power sector region under policy and climate change scenarios that affect water resource availability and temperatures. This work utilizes results from a spatially distributed river water temperature model coupled with a thermoelectric power plant model to provide inputs into an electricity production cost model that operates on a high spatial and temporal resolution. The regional transmission organization ISO-New England, which includes six New England states and over 32 Gigawatts of power capacity, is utilized as a case study. Hydrological data and power plant operations are analyzed over an eleven year period from 2000-2010 under four scenarios that include climate impacts on water resources and air temperatures as well as strict interpretations of regulations that can affect power plant operations due to elevated water temperatures. Results of these model linkages show how the power sector's reliability and economic performance can be affected by changes in water temperatures and water availability. The effective reliability and capacity value of thermal electric generators are quantified and discussed in the context of current as well as potential future water resource characteristics.

A Global Geospatial Database of 5000+ Historic Flood Event Extents

NASA Astrophysics Data System (ADS)

Tellman, B.; Sullivan, J.; Doyle, C.; Kettner, A.; Brakenridge, G. R.; Erickson, T.; Slayback, D. A.

2017-12-01

A key dataset that is missing for global flood model validation and understanding historic spatial flood vulnerability is a global historical geo-database of flood event extents. Decades of earth observing satellites and cloud computing now make it possible to not only detect floods in near real time, but to run these water detection algorithms back in time to capture the spatial extent of large numbers of specific events. This talk will show results from the largest global historical flood database developed to date. We use the Dartmouth Flood Observatory flood catalogue to map over 5000 floods (from 1985-2017) using MODIS, Landsat, and Sentinel-1 Satellites. All events are available for public download via the Earth Engine Catalogue and via a website that allows the user to query floods by area or date, assess population exposure trends over time, and download flood extents in geospatial format.In this talk, we will highlight major trends in global flood exposure per continent, land use type, and eco-region. We will also make suggestions how to use this dataset in conjunction with other global sets to i) validate global flood models, ii) assess the potential role of climatic change in flood exposure iii) understand how urbanization and other land change processes may influence spatial flood exposure iv) assess how innovative flood interventions (e.g. wetland restoration) influence flood patterns v) control for event magnitude to assess the role of social vulnerability and damage assessment vi) aid in rapid probabilistic risk assessment to enable microinsurance markets. Authors on this paper are already using the database for the later three applications and will show examples of wetland intervention analysis in Argentina, social vulnerability analysis in the USA, and micro insurance in India.

Two-stream Convolutional Neural Network for Methane Emissions Quantification

NASA Astrophysics Data System (ADS)

Wang, J.; Ravikumar, A. P.; McGuire, M.; Bell, C.; Tchapmi, L. P.; Brandt, A. R.

2017-12-01

Methane, a key component of natural gas, has a 25x higher global warming potential than carbon dioxide on a 100-year basis. Accurately monitoring and mitigating methane emissions require cost-effective detection and quantification technologies. Optical gas imaging, one of the most commonly used leak detection technology, adopted by Environmental Protection Agency, cannot estimate leak-sizes. In this work, we harness advances in computer science to allow for rapid and automatic leak quantification. Particularly, we utilize two-stream deep Convolutional Networks (ConvNets) to estimate leak-size by capturing complementary spatial information from still plume frames, and temporal information from plume motion between frames. We build large leak datasets for training and evaluating purposes by collecting about 20 videos (i.e. 397,400 frames) of leaks. The videos were recorded at six distances from the source, covering 10 -60 ft. Leak sources included natural gas well-heads, separators, and tanks. All frames were labeled with a true leak size, which has eight levels ranging from 0 to 140 MCFH. Preliminary analysis shows that two-stream ConvNets provides significant accuracy advantage over single steam ConvNets. Spatial stream ConvNet can achieve an accuracy of 65.2%, by extracting important features, including texture, plume area, and pattern. Temporal stream, fed by the results of optical flow analysis, results in an accuracy of 58.3%. The integration of the two-stream ConvNets gives a combined accuracy of 77.6%. For future work, we will split the training and testing datasets in distinct ways in order to test the generalization of the algorithm for different leak sources. Several analytic metrics, including confusion matrix and visualization of key features, will be used to understand accuracy rates and occurrences of false positives. The quantification algorithm can help to find and fix super-emitters, and improve the cost-effectiveness of leak detection and repair programs.

Spatial-temporal analysis of dengue deaths: identifying social vulnerabilities.

PubMed

Silva, Maria do Socorro da; Branco, Maria Dos Remédios Freitas Carvalho; Aquino, José; Queiroz, Rejane Christine de Sousa; Bani, Emanuele; Moreira, Emnielle Pinto Borges; Medeiros, Maria Nilza Lima; Rodrigues, Zulimar Márita Ribeiro

2017-01-01

Currently, dengue fever, chikungunya fever, and zika virus represent serious public health issues in Brazil, despite efforts to control the vector, the Aedes aegypti mosquito. This was a descriptive and ecological study of dengue deaths occurring from 2002 to 2013 in São Luis, Maranhão, Brazil. Geoprocessing software was used to draw maps, linking the geo-referenced deaths with urban/social data at census tract level. There were 74 deaths, concentrated in areas of social vulnerability. The use of geo-technology tools pointed to a concentration of dengue deaths in specific intra-urban areas.

Restoration of the Mississippi Delta: Lessons from Hurricanes Katrina and Rita

NASA Astrophysics Data System (ADS)

Day, John W.; Boesch, Donald F.; Clairain, Ellis J.; Kemp, G. Paul; Laska, Shirley B.; Mitsch, William J.; Orth, Kenneth; Mashriqui, Hassan; Reed, Denise J.; Shabman, Leonard; Simenstad, Charles A.; Streever, Bill J.; Twilley, Robert R.; Watson, Chester C.; Wells, John T.; Whigham, Dennis F.

2007-03-01

Hurricanes Katrina and Rita showed the vulnerability of coastal communities and how human activities that caused deterioration of the Mississippi Deltaic Plain (MDP) exacerbated this vulnerability. The MDP formed by dynamic interactions between river and coast at various temporal and spatial scales, and human activity has reduced these interactions at all scales. Restoration efforts aim to re-establish this dynamic interaction, with emphasis on reconnecting the river to the deltaic plain. Science must guide MDP restoration, which will provide insights into delta restoration elsewhere and generally into coasts facing climate change in times of resource scarcity.

Coastal vulnerability assessment using Fuzzy Logic and Bayesian Belief Network approaches

NASA Astrophysics Data System (ADS)

Valentini, Emiliana; Nguyen Xuan, Alessandra; Filipponi, Federico; Taramelli, Andrea

2017-04-01

Natural hazards such as sea surge are threatening low-lying coastal plains. In order to deal with disturbances a deeper understanding of benefits deriving from ecosystem services assessment, management and planning can contribute to enhance the resilience of coastal systems. In this frame assessing current and future vulnerability is a key concern of many Systems Of Systems SOS (social, ecological, institutional) that deals with several challenges like the definition of Essential Variables (EVs) able to synthesize the required information, the assignment of different weight to be attributed to each considered variable, the selection of method for combining the relevant variables. It is widely recognized that ecosystems contribute to human wellbeing and then their conservation increases the resilience capacities and could play a key role in reducing climate related risk and thus physical and economic losses. A way to fully exploit ecosystems potential, i.e. their so called ecopotential (see H2020 EU funded project "ECOPOTENTIAL"), is the Ecosystem based Adaptation (EbA): the use of ecosystem services as part of an adaptation strategy. In order to provide insight in understanding regulating ecosystem services to surge and which variables influence them and to make the best use of available data and information (EO products, in situ data and modelling), we propose a multi-component surge vulnerability assessment, focusing on coastal sandy dunes as natural barriers. The aim is to combine together eco-geomorphological and socio-economic variables with the hazard component on the base of different approaches: 1) Fuzzy Logic; 2) Bayesian Belief Networks (BBN). The Fuzzy Logic approach is very useful to get a spatialized information and it can easily combine variables coming from different sources. It provides information on vulnerability moving along-shore and across-shore (beach-dune transect), highlighting the variability of vulnerability conditions in the spatial dimension. According to the results using fuzzy operators, the analysis greatest weakness is the limited capacity to represent the relation among the different considered variables. The BBN approach, based on the definition of conditional probabilities, has allowed determining the trend of distributions of vulnerability along-shore, highlighting which parts of the coast are most likely to have higher or lower vulnerability than others. In BBN analysis, the greatest weakness emerge in the case of arbitrary definition of conditional probabilities (i.e. when there is a lack of information on the past hazardous events) because it is not possible to derive the individual contribution of each variable. As conclusion, the two approaches could be used together in the perspective of enhancing the multiple components in vulnerability assessment: the BBN as a preliminary assessment to provide a coarse description of the vulnerability distribution, and the Fuzzy Logic as an extended assessment to provide more space based information.

Development and implementation of a Bayesian-based aquifer vulnerability assessment in Florida

USGS Publications Warehouse

Arthur, J.D.; Wood, H.A.R.; Baker, A.E.; Cichon, J.R.; Raines, G.L.

2007-01-01

The Florida Aquifer Vulnerability Assessment (FAVA) was designed to provide a tool for environmental, regulatory, resource management, and planning professionals to facilitate protection of groundwater resources from surface sources of contamination. The FAVA project implements weights-of-evidence (WofE), a data-driven, Bayesian-probabilistic model to generate a series of maps reflecting relative aquifer vulnerability of Florida's principal aquifer systems. The vulnerability assessment process, from project design to map implementation is described herein in reference to the Floridan aquifer system (FAS). The WofE model calculates weighted relationships between hydrogeologic data layers that influence aquifer vulnerability and ambient groundwater parameters in wells that reflect relative degrees of vulnerability. Statewide model input data layers (evidential themes) include soil hydraulic conductivity, density of karst features, thickness of aquifer confinement, and hydraulic head difference between the FAS and the watertable. Wells with median dissolved nitrogen concentrations exceeding statistically established thresholds serve as training points in the WofE model. The resulting vulnerability map (response theme) reflects classified posterior probabilities based on spatial relationships between the evidential themes and training points. The response theme is subjected to extensive sensitivity and validation testing. Among the model validation techniques is calculation of a response theme based on a different water-quality indicator of relative recharge or vulnerability: dissolved oxygen. Successful implementation of the FAVA maps was facilitated by the overall project design, which included a needs assessment and iterative technical advisory committee input and review. Ongoing programs to protect Florida's springsheds have led to development of larger-scale WofE-based vulnerability assessments. Additional applications of the maps include land-use planning amendments and prioritization of land purchases to protect groundwater resources. ?? International Association for Mathematical Geology 2007.

Assessment of coastal vulnerability to climate change hazards at the regional scale: the case study of the North Adriatic Sea

NASA Astrophysics Data System (ADS)

Torresan, S.; Critto, A.; Rizzi, J.; Marcomini, A.

2012-07-01

Sea level rise, changes in storms and wave climate as a consequence of global climate change are expected to increase the size and magnitude of flooded and eroding coastal areas, thus having profound impacts on coastal communities and ecosystems. River deltas, beaches, estuaries and lagoons are considered particularly vulnerable to the adverse effects of climate change, which should be studied at the regional/local scale. This paper presents a regional vulnerability assessment (RVA) methodology developed to analyse site-specific spatial information on coastal vulnerability to the envisaged effects of global climate change, and assist coastal communities in operational coastal management and conservation. The main aim of the RVA is to identify key vulnerable receptors (i.e. natural and human ecosystems) in the considered region and localize vulnerable hot spot areas, which could be considered as homogeneous geographic sites for the definition of adaptation strategies. The application of the RVA methodology is based on a heterogeneous subset of bio-geophysical and socio-economic vulnerability indicators (e.g. coastal topography, geomorphology, presence and distribution of vegetation cover, location of artificial protection), which are a measure of the potential harm from a range of climate-related impacts (e.g. sea level rise inundation, storm surge flooding, coastal erosion). Based on a system of numerical weights and scores, the RVA provides relative vulnerability maps that allow to prioritize more vulnerable areas and targets of different climate-related impacts in the examined region and to support the identification of suitable areas for human settlements, infrastructures and economic activities, providing a basis for coastal zoning and land use planning. The implementation, performance and results of the methodology for the coastal area of the North Adriatic Sea (Italy) are fully described in the paper.

Assessing the vulnerability of human and biological communities to changing ecosystem services using a GIS-based multi-criteria decision support tool

USGS Publications Warehouse

Villarreal, Miguel; Norman, Laura M.; Labiosa, William B.

2012-01-01

In this paper we describe an application of a GIS-based multi-criteria decision support web tool that models and evaluates relative changes in ecosystem services to policy and land management decisions. The Santa Cruz Watershed Ecosystem Portfolio (SCWEPM) was designed to provide credible forecasts of responses to ecosystem drivers and stressors and to illustrate the role of land use decisions on spatial and temporal distributions of ecosystem services within a binational (U.S. and Mexico) watershed. We present two SCWEPM sub-models that when analyzed together address bidirectional relationships between social and ecological vulnerability and ecosystem services. The first model employs the Modified Socio-Environmental Vulnerability Index (M-SEVI), which assesses community vulnerability using information from U.S. and Mexico censuses on education, access to resources, migratory status, housing situation, and number of dependents. The second, relating land cover change to biodiversity (provisioning services), models changes in the distribution of terrestrial vertebrate habitat based on multitemporal vegetation and land cover maps, wildlife habitat relationships, and changes in land use/land cover patterns. When assessed concurrently, the models exposed some unexpected relationships between vulnerable communities and ecosystem services provisioning. For instance, the most species-rich habitat type in the watershed, Desert Riparian Forest, increased over time in areas occupied by the most vulnerable populations and declined in areas with less vulnerable populations. This type of information can be used to identify ecological conservation and restoration targets that enhance the livelihoods of people in vulnerable communities and promote biodiversity and ecosystem health.

Drinking water vulnerability to climate change and alternatives for adaptation in coastal South and South East Asia.

PubMed

Hoque, M A; Scheelbeek, P F D; Vineis, P; Khan, A E; Ahmed, K M; Butler, A P

Drinking water in much of Asia, particularly in coastal and rural settings, is provided by a variety of sources, which are widely distributed and frequently managed at an individual or local community level. Coastal and near-inland drinking water sources in South and South East (SSE) Asia are vulnerable to contamination by seawater, most dramatically from tropical cyclone induced storm surges. This paper assesses spatial vulnerabilities to salinisation of drinking water sources due to meteorological variability and climate change along the (ca. 6000 km) coastline of SSE Asia. The risks of increasing climatic stresses are first considered, and then maps of relative vulnerability along the entire coastline are developed, using data from global scale land surface models, along with an overall vulnerability index. The results show that surface and near-surface drinking water in the coastal areas of the mega-deltas in Vietnam and Bangladesh-India are most vulnerable, putting more than 25 million people at risk of drinking 'saline' water. Climate change is likely to exacerbate this problem, with adverse consequences for health, such as prevalence of hypertension and cardiovascular diseases. There is a need for identifying locations that are most at risk of salinisation in order for policy makers and local officials to implement strategies for reducing these health impacts. To counter the risks associated with these vulnerabilities, possible adaptation measures are also outlined. We conclude that detailed and fine scale vulnerability assessments may become crucial for planning targeted adaptation programmes along these coasts.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales

USGS Publications Warehouse

Kay, Shannon L.; Fischer, Justin W.; Monaghan, Andrew J.; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S.; Hartley, Stephen B.; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; Vercauteren, Kurt C.; Pipen, Kim M

2017-01-01

The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Lung sound analysis for wheeze episode detection.

PubMed

Jain, Abhishek; Vepa, Jithendra

2008-01-01

Listening and interpreting lung sounds by a stethoscope had been an important component of screening and diagnosing lung diseases. However this practice has always been vulnerable to poor audibility, inter-observer variations (between different physicians) and poor reproducibility. Thus computerized analysis of lung sounds for objective diagnosis of lung diseases is seen as a probable aid. In this paper we aim at automatic analysis of lung sounds for wheeze episode detection and quantification. The proposed algorithm integrates and analyses the set of parameters based on ATS (American Thoracic Society) definition of wheezes. It is very robust, computationally simple and yielded sensitivity of 84% and specificity of 86%.

Migration in the context of vulnerability and adaptation to climate change: insights from analogues

PubMed Central

McLeman, Robert A.; Hunter, Lori M.

2011-01-01

Migration is one of the variety of ways by which human populations adapt to environmental changes. The study of migration in the context of anthropogenic climate change is often approached using the concept of vulnerability and its key functional elements: exposure, system sensitivity, and adaptive capacity. This article explores the interaction of climate change and vulnerability through review of case studies of dry-season migration in the West African Sahel, hurricane-related population displacements in the Caribbean basin, winter migration of ‘snowbirds’ to the US Sun-belt, and 1930s drought migration on the North American Great Plains. These examples are then used as analogues for identifying general causal, temporal, and spatial dimensions of climate migration, along with potential considerations for policy-making and future research needs. PMID:22022342

An analysis of the accessibility of video lottery terminals: the case of Montréal.

PubMed

Robitaille, Eric; Herjean, Patrick

2008-01-18

Researchers and public health officials in Canada, the United States and Australia have for some time noted broader geographic accessibility to gambling establishments, above all in socioeconomically underprivileged communities. This increase in availability could lead to more and more gambling problems. This article focuses, in an ecological perspective, in particular on a spatial analysis of the geographic accessibility of sites possessing a VLT permit in the Montréal area, i.e. Montréal Island, the South Shore and Laval, from the standpoint of the development of an indicator of the vulnerability (socioeconomic components and demographic components) to gambling of populations at the level of certain neighbourhood units (dissemination areas). With the recent development of geographic information systems (GIS), it is now possible to ascertain accessibility to services much more accurately, for example by taking into account the configuration of the road network. The findings of our analysis reveal widespread geographic accessibility to sites possessing a VLT permit in the downtown area and in pericentral districts. In some neighbourhood units, a site possessing a VLT permit may be within a three-minute walk. In the region studied overall, average walking time to a VLT site is nine minutes. Access to this type of service on foot is usually limited in the outskirts. However, a number of groups of sites possessing VLT permits are found along certain axial highways. According to local spatial self-correlation analyses, the findings suggest a significant link between walking accessibility to sites possessing VLT permits and the vulnerability of the communities. In a number of neighbourhood units with ready access to VLT's the populations display high vulnerability. These findings reveal that accessibility to sites possessing a VLT permit is often linked to the vulnerability (socioeconomic and demographic components) of communities. Reliance in our analyses on neighbourhood units with fairly small areas enabled us to emphasize the rectilinear dimension of the spatial distribution of sites possessing VLT permits. This is a significant link that public health officials must consider when elaborating programs to combat pathological gambling.

Detection of the fracture zone by the method of recurrence plot

NASA Astrophysics Data System (ADS)

Hilarov, V. L.

2017-12-01

Recurrence plots (RPs) and recurrence quantification analysis (RQA) characteristics for the normal component of the displacement vector upon excitation of a defect steel plate by a sound pulse are analyzed. Different cases of spatial distribution of defects (uniform and normal) are considered, and a difference in the RQA parameters in these cases is revealed.

Temporal and nonlinear dispersal patterns of Ludwigia hexapetala in a regulated river

USDA-ARS?s Scientific Manuscript database

Rivers are vulnerable to biological invasion due to hydrologic connectivity, which facilitates post-entry movement of aquatic plant propagules by water currents. Ecological and watershed factors may influence spatial and temporal dispersal patterns. Field-based data on dispersal could improve risk...

Drought vulnerability assessment for prioritising drought warning implementation

NASA Astrophysics Data System (ADS)

Naumann, Gustavo; Faneca Sànchez, Marta; Mwangi, Emmah; Barbosa, Paulo; Iglesias, Ana; Garrote, Luis; Werner, Micha

2014-05-01

Drought warning provides a potentially efficient approach to mitigation of drought impacts, and should be targeted at areas most vulnerable to being adversely impacted. Assessing drought vulnerability is, however, complex and needs to consider susceptibility to drought impact as well as the capacity to cope with drought. In this paper a Drought Vulnerability Index (DVI) is proposed that considers four primary components that reflect the capacity of society to adapt to drought; the renewable natural capital, the economic capacity, the human and civic resources, and the available infrastructure and technology. The DVI is established as a weighted combination of these four components, each a composite of selected indicators. Constituent indicators are calculated based on national and/or regional census data and statistics, and while the resulting DVI should not be considered an absolute measure of drought vulnerability it does provide for a prioritisation of areas that can be used to target drought warning efforts. Sensitivity analysis of weights applied show the established DVI to be robust. Through the DVI the development of drought forecasting and warning can be targeted at the most vulnerable areas. The proposed DVI is applied at both the continental scale in Africa to assess drought vulnerability of the different nations across Africa, and at the national level in Kenya, allowing for prioritisation of the counties within Kenya to drought vulnerability. Results show the relative vulnerability of countries and counties vulnerable to drought. At the continental scale, Somalia, Burundi, Niger, Ethiopia, Mali and Chad are found to be the countries most vulnerable to drought. At the national level, the relative vulnerability of the counties across Kenya is found, with counties in the North-East of Kenya having the highest values of DVI. At the country level results were compared with drought disaster information from the EM-DAT disaster database, showing a good agreement between recorded drought impact and the established DVI classes. Kenya counties most vulnerable to drought are primarily located in the North-East of the country, showing a reasonable agreement with the spatial distribution of impacts of the 2010/2011 drought, despite the drought itself being more widespread.

Advances in Parameter and Uncertainty Quantification Using Bayesian Hierarchical Techniques with a Spatially Referenced Watershed Model (Invited)

NASA Astrophysics Data System (ADS)

Alexander, R. B.; Boyer, E. W.; Schwarz, G. E.; Smith, R. A.

2013-12-01

Estimating water and material stores and fluxes in watershed studies is frequently complicated by uncertainties in quantifying hydrological and biogeochemical effects of factors such as land use, soils, and climate. Although these process-related effects are commonly measured and modeled in separate catchments, researchers are especially challenged by their complexity across catchments and diverse environmental settings, leading to a poor understanding of how model parameters and prediction uncertainties vary spatially. To address these concerns, we illustrate the use of Bayesian hierarchical modeling techniques with a dynamic version of the spatially referenced watershed model SPARROW (SPAtially Referenced Regression On Watershed attributes). The dynamic SPARROW model is designed to predict streamflow and other water cycle components (e.g., evapotranspiration, soil and groundwater storage) for monthly varying hydrological regimes, using mechanistic functions, mass conservation constraints, and statistically estimated parameters. In this application, the model domain includes nearly 30,000 NHD (National Hydrologic Data) stream reaches and their associated catchments in the Susquehanna River Basin. We report the results of our comparisons of alternative models of varying complexity, including models with different explanatory variables as well as hierarchical models that account for spatial and temporal variability in model parameters and variance (error) components. The model errors are evaluated for changes with season and catchment size and correlations in time and space. The hierarchical models consist of a two-tiered structure in which climate forcing parameters are modeled as random variables, conditioned on watershed properties. Quantification of spatial and temporal variations in the hydrological parameters and model uncertainties in this approach leads to more efficient (lower variance) and less biased model predictions throughout the river network. Moreover, predictions of water-balance components are reported according to probabilistic metrics (e.g., percentiles, prediction intervals) that include both parameter and model uncertainties. These improvements in predictions of streamflow dynamics can inform the development of more accurate predictions of spatial and temporal variations in biogeochemical stores and fluxes (e.g., nutrients and carbon) in watersheds.

Big Data Geo-Analytical Tool Development for Spatial Analysis Uncertainty Visualization and Quantification Needs

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J. R.; Baker, D. V.

2015-12-01

As big data computing capabilities are increasingly paired with spatial analytical tools and approaches, there is a need to ensure uncertainty associated with the datasets used in these analyses is adequately incorporated and portrayed in results. Often the products of spatial analyses, big data and otherwise, are developed using discontinuous, sparse, and often point-driven data to represent continuous phenomena. Results from these analyses are generally presented without clear explanations of the uncertainty associated with the interpolated values. The Variable Grid Method (VGM) offers users with a flexible approach designed for application to a variety of analyses where users there is a need to study, evaluate, and analyze spatial trends and patterns while maintaining connection to and communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations. In this presentation we will show how we are utilizing Hadoop to store and perform spatial analysis through the development of custom Spark and MapReduce applications that incorporate ESRI Hadoop libraries. The team will present custom 'Big Data' geospatial applications that run on the Hadoop cluster and integrate with ESRI ArcMap with the team's probabilistic VGM approach. The VGM-Hadoop tool has been specially built as a multi-step MapReduce application running on the Hadoop cluster for the purpose of data reduction. This reduction is accomplished by generating multi-resolution, non-overlapping, attributed topology that is then further processed using ESRI's geostatistical analyst to convey a probabilistic model of a chosen study region. Finally, we will share our approach for implementation of data reduction and topology generation via custom multi-step Hadoop applications, performance benchmarking comparisons, and Hadoop-centric opportunities for greater parallelization of geospatial operations. The presentation includes examples of the approach being applied to a range of subsurface, geospatial studies (e.g. induced seismicity risk).

An approach for quantification of platinum distribution in tissues by LA-ICP-MS imaging using isotope dilution analysis.

PubMed

Moraleja, I; Mena, M L; Lázaro, A; Neumann, B; Tejedor, A; Jakubowski, N; Gómez-Gómez, M M; Esteban-Fernández, D

2018-02-01

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been revealed as a convenient technique for trace elemental imaging in tissue sections, providing elemental 2D distribution at a quantitative level. For quantification purposes, in the last years several approaches have been proposed in the literature such as the use of CRMs or matrix matched standards. The use of Isotope Dilution (ID) for quantification by LA-ICP-MS has been also described, being mainly useful for bulk analysis but not feasible for spatial measurements so far. In this work, a quantification method based on ID analysis was developed by printing isotope-enriched inks onto kidney slices from rats treated with antitumoral Pt-based drugs using a commercial ink-jet device, in order to perform an elemental quantification in different areas from bio-images. For the ID experiments 194 Pt enriched platinum was used. The methodology was validated by deposition of natural Pt standard droplets with a known amount of Pt onto the surface of a control tissue, where could be quantified even 50pg of Pt, with recoveries higher than 90%. The amount of Pt present in the whole kidney slices was quantified for cisplatin, carboplatin and oxaliplatin-treated rats. The results obtained were in accordance with those previously reported. The amount of Pt distributed between the medullar and cortical areas was also quantified, observing different behavior for the three drugs. Copyright © 2017 Elsevier B.V. All rights reserved.

Recognition and Quantification of Area Damaged by Oligonychus Perseae in Avocado Leaves

NASA Astrophysics Data System (ADS)

Díaz, Gloria; Romero, Eduardo; Boyero, Juan R.; Malpica, Norberto

The measure of leaf damage is a basic tool in plant epidemiology research. Measuring the area of a great number of leaves is subjective and time consuming. We investigate the use of machine learning approaches for the objective segmentation and quantification of leaf area damaged by mites in avocado leaves. After extraction of the leaf veins, pixels are labeled with a look-up table generated using a Support Vector Machine with a polynomial kernel of degree 3, on the chrominance components of YCrCb color space. Spatial information is included in the segmentation process by rating the degree of membership to a certain class and the homogeneity of the classified region. Results are presented on real images with different degrees of damage.

PET/MRI for neurologic applications.

PubMed

Catana, Ciprian; Drzezga, Alexander; Heiss, Wolf-Dieter; Rosen, Bruce R

2012-12-01

PET and MRI provide complementary information in the study of the human brain. Simultaneous PET/MRI data acquisition allows the spatial and temporal correlation of the measured signals, creating opportunities impossible to realize using stand-alone instruments. This paper reviews the methodologic improvements and potential neurologic and psychiatric applications of this novel technology. We first present methods for improving the performance and information content of each modality by using the information provided by the other technique. On the PET side, we discuss methods that use the simultaneously acquired MRI data to improve the PET data quantification. On the MRI side, we present how improved PET quantification can be used to validate several MRI techniques. Finally, we describe promising research, translational, and clinical applications that can benefit from these advanced tools.

Decision-support tools for Extreme Weather and Climate Events in the Northeast United States

NASA Astrophysics Data System (ADS)

Kumar, S.; Lowery, M.; Whelchel, A.

2013-12-01

Decision-support tools were assessed for the 2013 National Climate Assessment technical input document, "Climate Change in the Northeast, A Sourcebook". The assessment included tools designed to generate and deliver actionable information to assist states and highly populated urban and other communities in assessment of climate change vulnerability and risk, quantification of effects, and identification of adaptive strategies in the context of adaptation planning across inter-annual, seasonal and multi-decadal time scales. State-level adaptation planning in the Northeast has generally relied on qualitative vulnerability assessments by expert panels and stakeholders, although some states have undertaken initiatives to develop statewide databases to support vulnerability assessments by urban and local governments, and state agencies. The devastation caused by Superstorm Sandy in October 2012 has raised awareness of the potential for extreme weather events to unprecedented levels and created urgency for action, especially in coastal urban and suburban communities that experienced pronounced impacts - especially in New Jersey, New York and Connecticut. Planning approaches vary, but any adaptation and resiliency planning process must include the following: - Knowledge of the probable change in a climate variable (e.g., precipitation, temperature, sea-level rise) over time or that the climate variable will attain a certain threshold deemed to be significant; - Knowledge of intensity and frequency of climate hazards (past, current or future events or conditions with potential to cause harm) and their relationship with climate variables; - Assessment of climate vulnerabilities (sensitive resources, infrastructure or populations exposed to climate-related hazards); - Assessment of relative risks to vulnerable resources; - Identification and prioritization of adaptive strategies to address risks. Many organizations are developing decision-support tools to assist in the urban planning process by addressing some of these needs. In this paper we highlight the decision tools available today, discuss their application in selected case studies, and present a gap analysis with opportunities for innovation and future work.

Quantitative proteomics of synaptic and nonsynaptic mitochondria: insights for synaptic mitochondrial vulnerability.

PubMed

Stauch, Kelly L; Purnell, Phillip R; Fox, Howard S

2014-05-02

Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage.

Quantitative Proteomics of Synaptic and Nonsynaptic Mitochondria: Insights for Synaptic Mitochondrial Vulnerability

PubMed Central

2015-01-01

Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage. PMID:24708184

Shoreline changes and Coastal Flooding impacts: South Gujarat coast (India)

NASA Astrophysics Data System (ADS)

Parihar, S. B.

2016-12-01

South Gujarat coast (India) is experiencing increased coastal inundation and erosion caused by sea-level rise affecting the population, infrastructure, and environment. The area falls under low elevation coastal zone (LEZ) and its topography of the area is also making coast highly susceptible to flooding, especially at high tides and during the rainy season. As part of studies on shoreline changes field trip carried on the coastal taluka's of South Gujarat coast i.e. Surat, Navsari and Valsad shows various temporal changes is taking place at coastal belt. There are ample of studies on coastal dynamics and impacts. The study focus on spatial temporal analysis shows the vulnerable zones covering various physical elements at risk. These coastal areas are attractive in nature for all kind of economic development and growth because of availability of the water & fertile land for house hold use, fishing and transportation. On the contrary, South Gujarat coast being tectonically active; makes this region high vulnerable for any kind of infrastructure development. The region had also witnessed loss of life and property, disruptions to transport & power and incidences of epidemics during the floods of 2006 in Surat. Coastal flooding would, under these scenarios, threaten region that are home of 370,000 approx (Census, 2011) people in seven coastal taluka's of Surat, Navsari and Valsad district. Among the people residing in the region, the most vulnerable communities are fishermen, farmer and industrial labours. The wide range of infrastructure such as roads, hospitals, schools, power plants, industries and port will also be at risk. Shoreline changes are inevitably changing the characteristics of south Gujarat coast; practices and policies should be put in place to mitigate the potentially adverse impacts on environment and human settlements. Key words: sea level rise, LEZ, vulnerable, erosion, inundation, spatial temporal analysis, landuse changes.

Accounting for adaptive capacity and uncertainty in assessments of species' climate-change vulnerability.

PubMed

Wade, Alisa A; Hand, Brian K; Kovach, Ryan P; Luikart, Gordon; Whited, Diane C; Muhlfeld, Clint C

2017-02-01

Climate-change vulnerability assessments (CCVAs) are valuable tools for assessing species' vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. We took a more comprehensive approach that incorporates exposure, sensitivity, and capacity to adapt to climate change. We applied our approach to anadromous steelhead trout (Oncorhynchus mykiss) and nonanadromous bull trout (Salvelinus confluentus), threatened salmonids within the Columbia River Basin (U.S.A.). We quantified exposure on the basis of scenarios of future stream temperature and flow, and we represented sensitivity and capacity to adapt to climate change with metrics of habitat quality, demographic condition, and genetic diversity. Both species were found to be highly vulnerable to climate change at low elevations and in their southernmost habitats. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the 2 species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multispecies conservation. Based on our results, we suggest that CCVAs be considered within a broader conceptual and computational framework and be used to refine hypotheses, guide research, and compare plausible scenarios of species' vulnerability to climate change. © 2016 Society for Conservation Biology.

High-speed holographic system for full-field transient vibrometry of the human tympanic membrane

NASA Astrophysics Data System (ADS)

Dobrev, I.; Harrington, E. J.; Cheng, T.; Furlong, C.; Rosowski, J. J.

2014-07-01

Understanding of the human hearing process requires the quantification of the transient response of the human ear and the human tympanic membrane (TM or eardrum) in particular. Current state-of-the-art medical methods to quantify the transient acousto-mechanical response of the TM provide only averaged acoustic or local information at a few points. This may be insufficient to fully describe the complex patterns unfolding across the full surface of the TM. Existing engineering systems for full-field nanometer measurements of transient events, typically based on holographic methods, constrain the maximum sampling speed and/or require complex experimental setups. We have developed and implemented of a new high-speed (i.e., > 40 Kfps) holographic system (HHS) with a hybrid spatio-temporal local correlation phase sampling method that allows quantification of the full-field nanometer transient (i.e., > 10 kHz) displacement of the human TM. The HHS temporal accuracy and resolution is validated versus a LDV on both artificial membranes and human TMs. The high temporal (i.e., < 24 μs) and spatial (i.e., >100k data points) resolution of our HHS enables simultaneous measurement of the time waveform of the full surface of the TM. These capabilities allow for quantification of spatially-dependent motion parameters such as energy propagation delays surface wave speeds, which can be used to infer local material properties across the surface of the TM. The HHS could provide a new tool for the investigation of the auditory system with applications in medical research, in-vivo clinical diagnosis as well as hearing aids design.

Computer-aided Assessment of Regional Abdominal Fat with Food Residue Removal in CT

PubMed Central

Makrogiannis, Sokratis; Caturegli, Giorgio; Davatzikos, Christos; Ferrucci, Luigi

2014-01-01

Rationale and Objectives Separate quantification of abdominal subcutaneous and visceral fat regions is essential to understand the role of regional adiposity as risk factor in epidemiological studies. Fat quantification is often based on computed tomography (CT) because fat density is distinct from other tissue densities in the abdomen. However, the presence of intestinal food residues with densities similar to fat may reduce fat quantification accuracy. We introduce an abdominal fat quantification method in CT with interest in food residue removal. Materials and Methods Total fat was identified in the feature space of Hounsfield units and divided into subcutaneous and visceral components using model-based segmentation. Regions of food residues were identified and removed from visceral fat using a machine learning method integrating intensity, texture, and spatial information. Cost-weighting and bagging techniques were investigated to address class imbalance. Results We validated our automated food residue removal technique against semimanual quantifications. Our feature selection experiments indicated that joint intensity and texture features produce the highest classification accuracy at 95%. We explored generalization capability using k-fold cross-validation and receiver operating characteristic (ROC) analysis with variable k. Losses in accuracy and area under ROC curve between maximum and minimum k were limited to 0.1% and 0.3%. We validated tissue segmentation against reference semimanual delineations. The Dice similarity scores were as high as 93.1 for subcutaneous fat and 85.6 for visceral fat. Conclusions Computer-aided regional abdominal fat quantification is a reliable computational tool for large-scale epidemiological studies. Our proposed intestinal food residue reduction scheme is an original contribution of this work. Validation experiments indicate very good accuracy and generalization capability. PMID:24119354

Computer-aided assessment of regional abdominal fat with food residue removal in CT.

PubMed

Makrogiannis, Sokratis; Caturegli, Giorgio; Davatzikos, Christos; Ferrucci, Luigi

2013-11-01

Separate quantification of abdominal subcutaneous and visceral fat regions is essential to understand the role of regional adiposity as risk factor in epidemiological studies. Fat quantification is often based on computed tomography (CT) because fat density is distinct from other tissue densities in the abdomen. However, the presence of intestinal food residues with densities similar to fat may reduce fat quantification accuracy. We introduce an abdominal fat quantification method in CT with interest in food residue removal. Total fat was identified in the feature space of Hounsfield units and divided into subcutaneous and visceral components using model-based segmentation. Regions of food residues were identified and removed from visceral fat using a machine learning method integrating intensity, texture, and spatial information. Cost-weighting and bagging techniques were investigated to address class imbalance. We validated our automated food residue removal technique against semimanual quantifications. Our feature selection experiments indicated that joint intensity and texture features produce the highest classification accuracy at 95%. We explored generalization capability using k-fold cross-validation and receiver operating characteristic (ROC) analysis with variable k. Losses in accuracy and area under ROC curve between maximum and minimum k were limited to 0.1% and 0.3%. We validated tissue segmentation against reference semimanual delineations. The Dice similarity scores were as high as 93.1 for subcutaneous fat and 85.6 for visceral fat. Computer-aided regional abdominal fat quantification is a reliable computational tool for large-scale epidemiological studies. Our proposed intestinal food residue reduction scheme is an original contribution of this work. Validation experiments indicate very good accuracy and generalization capability. Published by Elsevier Inc.

Using hydrologic landscape classification to assess streamflow vulnerability to changes in climate

EPA Science Inventory

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

An assessment of streamflow vulnerability to climate using Hydrologic Landscape classification

EPA Science Inventory

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

Manipulative parasites may not alter intermediate host distribution but still enhance their transmission: field evidence for increased vulnerability to definitive hosts and non-host predator avoidance.

PubMed

Lagrue, C; Güvenatam, A; Bollache, L

2013-02-01

Behavioural alterations induced by parasites in their intermediate hosts can spatially structure host populations, possibly resulting in enhanced trophic transmission to definitive hosts. However, such alterations may also increase intermediate host vulnerability to non-host predators. Parasite-induced behavioural alterations may thus vary between parasite species and depend on each parasite definitive host species. We studied the influence of infection with 2 acanthocephalan parasites (Echinorhynchus truttae and Polymorphus minutus) on the distribution of the amphipod Gammarus pulex in the field. Predator presence or absence and predator species, whether suitable definitive host or dead-end predator, had no effect on the micro-distribution of infected or uninfected G. pulex amphipods. Although neither parasite species seem to influence intermediate host distribution, E. truttae infected G. pulex were still significantly more vulnerable to predation by fish (Cottus gobio), the parasite's definitive hosts. In contrast, G. pulex infected with P. minutus, a bird acanthocephalan, did not suffer from increased predation by C. gobio, a predator unsuitable as host for P. minutus. These results suggest that effects of behavioural changes associated with parasite infections might not be detectable until intermediate hosts actually come in contact with predators. However, parasite-induced changes in host spatial distribution may still be adaptive if they drive hosts into areas of high transmission probabilities.

Localised hydrodynamics influence vulnerability of coral communities to environmental disturbances

NASA Astrophysics Data System (ADS)

Shedrawi, George; Falter, James L.; Friedman, Kim J.; Lowe, Ryan J.; Pratchett, Morgan S.; Simpson, Christopher J.; Speed, Conrad W.; Wilson, Shaun K.; Zhang, Zhenlin

2017-09-01

The movement of water can have a significant influence on the vulnerability of hermatypic corals to environmental disturbances such as cyclone damage, heat stress and anoxia. Here, we explore the relationship between small reef-scale water circulation patterns and measured differences in the abundance, composition and vulnerability of coral assemblages over decades. Changes in coral cover and community structure within Bill's Bay (Ningaloo Reef, Western Australia) over a 22-yr period, during which multiple disturbance events (including mass bleaching, anoxia, and tropical cyclones) have impacted the area, were compared with spatial variation in water residence times (WRT). We found that reef sites associated with longer water residence times (WRT >15 h) experienced higher rates of coral mortality during acute environmental disturbances compared to reef sites with shorter WRT. Shifts in coral community composition from acroporid to faviid-dominated assemblages were also more prominent at sites with long WRT compared to reef sites with shorter WRT, although shifts in community composition were also observed at sites close to shore. Interestingly, these same long-WRT sites also tended to have the fastest recovery rates so that coral cover was returned to original levels of approximately 20% over two decades. This study provides empirical evidence that spatial patterns in water circulation and flushing can influence the resilience of coral communities, thus identifying areas sensitive to emerging threats associated with global climate change.

Life history and spatial traits predict extinction risk due to climate change

NASA Astrophysics Data System (ADS)

Pearson, Richard G.; Stanton, Jessica C.; Shoemaker, Kevin T.; Aiello-Lammens, Matthew E.; Ersts, Peter J.; Horning, Ned; Fordham, Damien A.; Raxworthy, Christopher J.; Ryu, Hae Yeong; McNees, Jason; Akçakaya, H. Reşit

2014-03-01

There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change based on the expectation that established assessments such as the IUCN Red List need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

The characterisation and management of greenhouse gas emissions from fires in northern Australian savannas

NASA Astrophysics Data System (ADS)

Cook, G. D.; Liedloff, A. C.; Richards, A. E.; Meyer, M.

2016-12-01

Australia is the only OECD country with a significant area of tropical savannas within it borders. Approximately 220 000 km2 of these savannas burn every year releasing 2 to 4 % of Australia's accountable greenhouse gas emissions. Reduction in uncertainty in the quantification of these emissions of methane and nitrous has been fundamental to improving both the national GHG inventory and developing approaches to better manage land to reduce these emissions. Projects to reduce pyrogenic emissions have been adopted across 30% of Australia's high rainfall savannas. Recent work has focussed on quantifying the additional benefit of increased carbon stocks in fine fuel and coarse woody debris (CWD) resulting from improvements in fire management. An integrated set of equations have been developed to enable seemless quantification of emissions and sequestration in these frequently burnt savannas. These show that increases in carbon stored in fine fuel and CWD comprises about 3 times the emissions abatement from improvements in fire management that have been achieved in a project area of 28 000 km2. Future work is focussing on improving the understanding of spatial and temporal variation in fire behaviour across Australia's savanna biome, improvements in quantification of carbon dynamics of CWD and improved quantification of the effects of fire on carbon dynamics in soils of the savannas.

Analysis of the spatial distribution of dengue cases in the city of Rio de Janeiro, 2011 and 2012

PubMed Central

Carvalho, Silvia; Magalhães, Mônica de Avelar Figueiredo Mafra; Medronho, Roberto de Andrade

2017-01-01

ABSTRACT OBJECTIVE Analyze the spatial distribution of classical dengue and severe dengue cases in the city of Rio de Janeiro. METHODS Exploratory study, considering cases of classical dengue and severe dengue with laboratory confirmation of the infection in the city of Rio de Janeiro during the years 2011/2012. The georeferencing technique was applied for the cases notified in the Notification Increase Information System in the period of 2011 and 2012. For this process, the fields “street” and “number” were used. The ArcGis10 program’s Geocoding tool’s automatic process was performed. The spatial analysis was done through the kernel density estimator. RESULTS Kernel density pointed out hotspots for classic dengue that did not coincide geographically with severe dengue and were in or near favelas. The kernel ratio did not show a notable change in the spatial distribution pattern observed in the kernel density analysis. The georeferencing process showed a loss of 41% of classic dengue registries and 17% of severe dengue registries due to the address in the Notification Increase Information System form. CONCLUSIONS The hotspots near the favelas suggest that the social vulnerability of these localities can be an influencing factor for the occurrence of this aggravation since there is a deficiency of the supply and access to essential goods and services for the population. To reduce this vulnerability, interventions must be related to macroeconomic policies. PMID:28832752

A Probabilistic Analysis of Surface Water Flood Risk in London.

PubMed

Jenkins, Katie; Hall, Jim; Glenis, Vassilis; Kilsby, Chris

2018-06-01

Flooding in urban areas during heavy rainfall, often characterized by short duration and high-intensity events, is known as "surface water flooding." Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively. © 2017 Society for Risk Analysis.

Regional vulnerability of the hippocampus to repeated motor activity deprivation.

PubMed

Faraji, Jamshid; Soltanpour, Nabiollah; Moeeini, Reza; Hosseini, Seyed Abedin; Pakdel, Shiva; Moharrerie, Alireza; Arjang, Kaveh; Soltanpour, Nasrin; Metz, Gerlinde A S

2016-03-15

Spontaneous vertical and horizontal exploratory movements are integral components of rodent behavior. Little is known, however, about the structural and functional consequences of restricted spontaneous exploration. Here, we report two experiments to probe whether restriction in vertical activity (rearing) in rats could induce neuro-hormonal and behavioral disturbances. Rearing movements in rats were deprived for 3h/day for 30 consecutive days by placing the animal into a circular tunnel task. Rats temporarily deprived of rearing behavior showed elevated plasma corticosterone levels but no detectable psychological distress and/or anxiety-related behavior within an elevated plus maze. However, rats emitted a greater number of 22-kHz ultrasonic vocalizations and spent significantly more time vocalizing than controls when deprived of their rearing behavior. Despite intact spatial performance within wet- and dry-land spatial tasks, rearing-deprived rats also exhibited a significant alteration in search strategies within both spatial tasks along with reduced volume and neuron number in the hippocampal subregion CA2. These data suggest a new approach to test the importance of free exploratory behavior in endocrine and structural manifestations. The results support a central role of the CA2 in spontaneous exploratory behavior and vulnerability to psychological stress. Copyright © 2015 Elsevier B.V. All rights reserved.

Epidemiological characteristics of cases of death from tuberculosis and vulnerable territories1

PubMed Central

Yamamura, Mellina; Santos-Neto, Marcelino; dos Santos, Rebeca Augusto Neman; Garcia, Maria Concebida da Cunha; Nogueira, Jordana de Almeida; Arcêncio, Ricardo Alexandre

2015-01-01

Objective: to characterize the differences in the clinical and epidemiological profile of cases of death that had tuberculosis as an immediate or associated cause, and to analyze the spatial distribution of the cases of death from tuberculosis within the territories of Ribeirão Preto, Brazil. Method: an ecological study, in which the population consisted of 114 cases of death from tuberculosis. Bivariate analysis was carried out, as well as point density analysis, defined with the Kernel estimate. Results: of the cases of death from tuberculosis, 50 were the immediate cause and 64 an associated cause. Age (p=.008) and sector responsible for the death certificate (p=.003) were the variables that presented statistically significant associations with the cause of death. The spatial distribution, in both events, did not occur randomly, forming clusters in areas of the municipality. Conclusion: the difference in the profiles of the cases of death from tuberculosis, as a basic cause and as an associated cause, was governed by the age and the sector responsible for the completion of the death certificate. The non-randomness of the spatial distribution of the cases suggests areas that are vulnerable to these events. Knowing these areas can contribute to the choice of disease control strategies. PMID:26487142

The Hestia Project: High Spatial Resolution Fossil Fuel Carbon Dioxide Emissions Quantification at Hourly Scale in Indianapolis, USA

NASA Astrophysics Data System (ADS)

Zhou, Y.; Gurney, K. R.

2009-12-01

In order to advance the scientific understanding of carbon exchange with the land surface and contribute to sound, quantitatively-based U.S. climate change policy interests, quantification of greenhouse gases emissions drivers at fine spatial and temporal scales is essential. Quantification of fossil fuel CO2 emissions, the primary greenhouse gases, has become a key component to cost-effective CO2 emissions mitigation options and a carbon trading system. Called the ‘Hestia Project’, this pilot study generated CO2 emissions down to high spatial resolution and hourly scale for the greater Indianapolis region in the USA through the use of air quality and traffic monitoring data, remote sensing, GIS, and building energy modeling. The CO2 emissions were constructed from three data source categories: area, point, and mobile. For the area source emissions, we developed an energy consumption model using DOE/EIA survey data on building characteristics and energy consumption. With the Vulcan Project’s county-level CO2 emissions and simulated building energy consumption, we quantified the CO2 emissions for each individual building by allocating Vulcan emissions to roughly 50,000 structures in Indianapolis. The temporal pattern of CO2 emissions in each individual building was developed based on temporal patterns of energy consumption. The point sources emissions were derived from the EPA National Emissions Inventory data and effluent monitoring of electricity producing facilities. The mobile source CO2 emissions were estimated at the month/county scale using the Mobile6 combustion model and the National Mobile Inventory Model database. The month/county scale mobile source CO2 emissions were downscaled to the “native” spatial resolution of road segments every hour using a GIS road atlas and traffic monitoring data. The result is shown in Figure 1. The resulting urban-scale inventory can serve as a baseline of current CO2 emissions and should be of immediate use to city environmental managers and regional industry as they plan emission mitigation options and project future emission trends. The results obtained here will also be a useful comparison to atmospheric CO2 monitoring efforts from the top-down. Figure 1. Location of the study area, the building level and mobile CO2 emissions, and an enlarged example neighborhood

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Brian W.; Frost, Sophia; Frayo, Shani

Abstract Alpha emitting radionuclides exhibit a potential advantage for cancer treatments because they release large amounts of ionizing energy over a few cell diameters (50–80 μm) causing localized, irreparable double-strand DNA breaks that lead to cell death. Radioimmunotherapy (RIT) approaches using monoclonal antibodies labeled with alpha emitters may inactivate targeted cells with minimal radiation damage to surrounding tissues. For accurate dosimetry in alpha-RIT, tools are needed to visualize and quantify the radioactivity distribution and absorbed dose to targeted and non-targeted cells, especially for organs and tumors with heterogeneous radionuclide distributions. The aim of this study was to evaluate and characterizemore » a novel single-particle digital autoradiography imager, iQID (ionizing-radiation Quantum Imaging Detector), for use in alpha-RIT experiments. Methods: The iQID camera is a scintillator-based radiation detection technology that images and identifies charged-particle and gamma-ray/X-ray emissions spatially and temporally on an event-by-event basis. It employs recent advances in CCD/CMOS cameras and computing hardware for real-time imaging and activity quantification of tissue sections, approaching cellular resolutions. In this work, we evaluated this system’s characteristics for alpha particle imaging including measurements of spatial resolution and background count rates at various detector configurations and quantification of activity distributions. The technique was assessed for quantitative imaging of astatine-211 (211At) activity distributions in cryosections of murine and canine tissue samples. Results: The highest spatial resolution was measured at ~20 μm full width at half maximum (FWHM) and the alpha particle background was measured at a rate of (2.6 ± 0.5) × 10–4 cpm/cm2 (40 mm diameter detector area). Simultaneous imaging of multiple tissue sections was performed using a large-area iQID configuration (ø 11.5 cm). Estimation of the 211At activity distribution was demonstrated at mBq/μg levels. Conclusion: Single-particle digital autoradiography of alpha emitters has advantages over traditional autoradiographic techniques in terms of spatial resolution, sensitivity, and activity quantification capability. The system features and characterization results presented in this study show that iQID is a promising technology for microdosimetry, because it provides necessary information for interpreting alpha-RIT outcomes and for predicting the therapeutic efficacy of cell-targeted approaches using alpha emitters.« less

Negligible influence of spatial autocorrelation in the assessment of fire effects in a mixed conifer forest

USGS Publications Warehouse

van Mantgem, P.J.; Schwilk, D.W.

2009-01-01

Fire is an important feature of many forest ecosystems, although the quantification of its effects is compromised by the large scale at which fire occurs and its inherent unpredictability. A recurring problem is the use of subsamples collected within individual burns, potentially resulting in spatially autocorrelated data. Using subsamples from six different fires (and three unburned control areas) we show little evidence for strong spatial autocorrelation either before or after burning for eight measures of forest conditions (both fuels and vegetation). Additionally, including a term for spatially autocorrelated errors provided little improvement for simple linear models contrasting the effects of early versus late season burning. While the effects of spatial autocorrelation should always be examined, it may not always greatly influence assessments of fire effects. If high patch scale variability is common in Sierra Nevada mixed conifer forests, even following more than a century of fire exclusion, treatments designed to encourage further heterogeneity in forest conditions prior to the reintroduction of fire will likely be unnecessary.

[Vulnerability assessment on the coastal wetlands in the Yangtze Estuary under sea-level rise].

PubMed

Cui, Li-Fang; Wang, Ning; Ge, Zhen-Ming; Zhang, Li-Quan

2014-02-01

To study the response of coastal wetlands to climate change, assess the impacts of climate change on the coastal wetlands and formulate feasible and practical mitigation strategies are the important prerequisite for securing coastal ecosystems. In this paper, the possible impacts of sea level rise caused by climate change on the coastal wetlands in the Yangtze Estuary were analyzed by the Source-Pathway-Receptor-Consequence (SPRC) model and IPCC definition on the vulnerability. An indicator system for vulnerability assessment was established, in which sea-level rise rate, subsidence rate, habitat elevation, inundation threshold of habitat and sedimentation rate were selected as the key indicators. A quantitatively spatial assessment method based on the GIS platform was established by quantifying each indicator, calculating the vulnerability index and grading the vulnerability index for the assessment of coastal wetlands in the Yangtze Estuary under the scenarios of sea-level rise. The vulnerability assessments on the coastal wetlands in the Yangtze Estuary in 2030 and 2050 were performed under two sea-level rise scenarios (the present sea-level rise trend over recent 30 years and IPCC A1F1 scenario). The results showed that with the projection in 2030 under the present trend of sea-level rise (0.26 cm x a(-1)), 6.6% and 0.1% of the coastal wetlands were in the low and moderate vulnerabilities, respectively; and in 2050, 9.8% and 0.2% of the coastal wetlands were in low and moderate vulnerabilities, respectively. With the projection in 2030 under the A1F1 scenario (0.59 cm x a(-1)), 9.0% and 0.1% of the coastal wetlands were in the low and moderate vulnerabilities, respectively; and in 2050, 9.5%, 1.0% and 0.3% of the coastal wetlands were in the low, moderate and high vulnerabilities, respectively.

Geospatial approach for assessment of biophysical vulnerability to agricultural drought and its intra-seasonal variations.

PubMed

Sehgal, Vinay Kumar; Dhakar, Rajkumar

2016-03-01

The study presents a methodology to assess and map agricultural drought vulnerability during main kharif crop season at local scale and compare its intra-seasonal variations. A conceptual model of vulnerability based on variables of exposure, sensitivity, and adaptive capacity was adopted, and spatial datasets of key biophysical factors contributing to vulnerability were generated using remote sensing and GIS for Rajasthan State of India. Hazard exposure was based on frequency and intensity of gridded standardized precipitation index (SPI). Agricultural sensitivity was based on soil water holding capacity as well as on frequency and intensity of normalized difference vegetation index (NDVI)-derived trend adjusted vegetation condition index (VCITadj). Percent irrigated area was used as a measure of adaptive capacity. Agricultural drought vulnerability was derived separately for early, mid, late, and whole kharif seasons by composting rating of factors using linear weighting scheme and pairwise comparison of multi-criteria evaluation. The regions showing very low to extreme rating of hazard exposure, drought sensitivity, and agricultural vulnerability were identified at all four time scales. The results indicate that high to extreme vulnerability occurs in more than 50% of net sown area in the state and such areas mostly occur in western, central, and southern parts. The higher vulnerability is on account of non-irrigated croplands, moderate to low water holding capacity of sandy soils, resulting in higher sensitivity, and located in regions with high probability of rainfall deficiency. The mid and late season vulnerability has been found to be much higher than that during early and whole season. Significant correlation of vulnerability rating with food grain productivity, drought recurrence period, crop area damaged in year 2009 and socioeconomic indicator of human development index (HDI) proves the general soundness of methodology. Replication of this methodology in other areas is expected to lead to better preparedness and mitigation-oriented management of droughts.

Past landscape dynamics in mountain territories: historical trajectory of vulnerability in the Vars catchment (French Alps)

NASA Astrophysics Data System (ADS)

Puissant, Anne; Cioloboc, Florin; Schlosser, Arnaud; Gazo, Aurelien; Martin, Brice; Malet, Jean-Philippe

2016-04-01

Over the last decades and centuries, mountain landscapes have experiment natural and man-made landcover/use changes with mainly the development of tourism activities and the reduction of agro-pastoral activities. These transformations have directly influenced the spatial organization of mountain landscapes. To better anticipate the future exposure of the territory to natural hazards, decision-makers need retrospective analyses of the past changes. In the frame of the SAMCO project, whose objective is to propose mountain risk assessment methodologies in the context of global changes, this research presents a retrospective analysis of land cover/use changes (from 1948 to 2013) in the Vars catchment (French South Alps) submitted to several natural hazards (rockfall, landslide, and flood). Database of elements at risk has been built for five dates and evolution of vulnerability is performed through a versatile GIS-based analysis tool developed for the estimation of vulnerability indicators (physical, economical, social) at a fine scale (1:5000). Results allow identifying several areas with different trajectories of vulnerability which can be use as input data for risk analysis and define future trends.

Vulnerability Analysis and Passenger Source Prediction in Urban Rail Transit Networks

PubMed Central

Wang, Junjie; Li, Yishuai; Liu, Jingyu; He, Kun; Wang, Pu

2013-01-01

Based on large-scale human mobility data collected in San Francisco and Boston, the morning peak urban rail transit (URT) ODs (origin-destination matrix) were estimated and the most vulnerable URT segments, those capable of causing the largest service interruptions, were identified. In both URT networks, a few highly vulnerable segments were observed. For this small group of vital segments, the impact of failure must be carefully evaluated. A bipartite URT usage network was developed and used to determine the inherent connections between urban rail transits and their passengers' travel demands. Although passengers' origins and destinations were easy to locate for a large number of URT segments, a few show very complicated spatial distributions. Based on the bipartite URT usage network, a new layer of the understanding of a URT segment's vulnerability can be achieved by taking the difficulty of addressing the failure of a given segment into account. Two proof-of-concept cases are described here: Possible transfer of passenger flow to the road network is here predicted in the cases of failures of two representative URT segments in San Francisco. PMID:24260355

Social vulnerability and climate variability in southern Brazil: a TerraPop case study

NASA Astrophysics Data System (ADS)

Adamo, S. B.; Fitch, C. A.; Kugler, T.; Doxsey-Whitfield, E.

2014-12-01

Climate variability is an inherent characteristic of the Earth's climate, including but not limited to climate change. It affects and impacts human society in different ways, depending on the underlying socioeconomic vulnerability of specific places, social groups, households and individuals. This differential vulnerability presents spatial and temporal variations, and is rooted in historical patterns of development and relations between human and ecological systems. This study aims to assess the impact of climate variability on livelihoods and well-being, as well as their changes over time and across space, and for rural and urban populations. The geographic focus is Southern Brazil-the states of Parana, Santa Catarina and Rio Grande do Sul-- and the objectives include (a) to identify and map critical areas or hotspots of exposure to climate variability (temperature and precipitation), and (b) to identify internal variation or differential vulnerability within these areas and its evolution over time (1980-2010), using newly available integrated data from the Terra Populus project. These data include geo-referenced climate and agricultural data, and data describing demographic and socioeconomic characteristics of individuals, households and places.

Prediction of groundwater inrush into coal mines from aquifers underlying the coal seams in China: application of vulnerability index method to Zhangcun Coal Mine, China

NASA Astrophysics Data System (ADS)

Wu, Qiang; Zhou, Wanfang; Wang, Jinhua; Xie, Shuhan

2009-05-01

Groundwater inrush is a geohazard that can significantly impact safe operations of the coal mines in China. Its occurrence is controlled by many factors and processes are often not amenable to mathematical expressions. To evaluate the water inrush risk, Professor Wu and his colleagues have proposed the vulnerability index approach by coupling the artificial neural network (ANN) and geographic information system (GIS). The detailed procedures of using this innovative approach are shown in a case study. Firstly, the powerful spatial data analysis functions of GIS was used to establish the thematic layer of each of the main factors that control the water inrush, and then to choose the training sample on the thematic layer with the ANN-BP Arithmetic. Secondly, the ANN evaluation model of the water inrush was established to determine the threshold value for each risk level with a histogram of the water inrush vulnerability index. As a result, the mine area was divided into four regions with different vulnerability levels and they served as the general guidelines for the mine operations.

Spatial learning impairment induced by chronic stress is related to individual differences in novelty reactivity: search for neurobiological correlates.

PubMed

Touyarot, K; Venero, C; Sandi, C

2004-02-01

Although chronic stress has been reported to induce deleterious effects on hippocampal structure and function, the possible existence of individual differences in the vulnerability to develop stress-induced cognitive alterations was hypothesized. This study was designed to evaluate (i) whether individual variability in behavioural reactivity to novelty could be related to a differential vulnerability to show spatial learning deficits after chronic stress in young adult rats, and (ii) to what extent, could individual differences in stress-induced cognitive alterations be related to alterations in specific neurobiological substrates. Four month-old Wistar male rats were classified according to their locomotor reactivity to a novel environment, as either low (LR) or highly (HR) reactive, and then either submitted to psychosocial stress for 21-days (consisting of the daily cohabitation of each young adult rat with a new middle-aged rat) or left undisturbed. The results showed that psychosocial stress induced a marked deficit in spatial learning in the water maze in HR, but not in LR, rats. Then, a second experiment investigated the possible differential expression of corticosteroid receptors (MR and GR) and cell adhesion molecules (NCAM and L1) in the hippocampus of HR and LR rats, both under basal conditions and after exposure to chronic social stress. Although chronic stress induced a reduction on the hippocampal expression of MRs and the NCAM-140 isoform, the levels of these molecules did not differ between stressed rats with and without spatial learning impairments; i.e., between HR- and LR-stressed rats, respectively. Nevertheless, it should be noted that the reduction of the hippocampal expression of NCAM-140 induced by psychosocial stress was particularly marked in HR stressed rats. However, the expression of GRs, NCAM-120 and NCAM-180 isoforms, and L1, was not affected by stress, regardless of the reactivity of the animals. Therefore, although we failed to find a neurobiological substrate that specifically correlated with the differential cognitive vulnerability to chronic stress shown by animals with a different novelty reactivity, this study confirms the hypothesis that rats differ in their susceptibility to display stress-induced impairments in hippocampus-dependent spatial learning tasks. In addition, it provides a model to further search for the neurobiological substrate(s) involved in the differential susceptibility to develop stress-induced cognitive impairments.

Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

PubMed

Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

2016-12-01

Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

Assessing vulnerability to drought: identifying underlying factors across Europe

NASA Astrophysics Data System (ADS)

Urquijo, Julia; Gonzalez Tánago, Itziar; Ballesteros, Mario; De Stefano, Lucia

2015-04-01

Drought is considered one of the most severe and damaging natural hazards in terms of people and sectors affected and associated losses. Drought is a normal and recurrent climatic phenomenon that occurs worldwide, although its spatial and temporal characteristics vary significantly among climates. In the case of Europe, in the last thirty years, the region has suffered several drought events that have caused estimated economic damages over a €100 billion and have affected almost 20% of its territory and population. In recent years, there has been a growing awareness among experts and authorities of the need to shift from a reactive crisis approach to a drought risk management approach, as well as of the importance of designing and implementing policies, strategies and plans at country and river basin levels to deal with drought. The identification of whom and what is vulnerable to drought is a central aspect of drought risk mitigation and planning and several authors agree that societal vulnerability often determines drought risk more than the actual precipitation shortfalls. The final aim of a drought vulnerability assessment is to identify the underlying sources of drought impact, in order to develop policy options that help to enhance coping capacity and therefore to prevent drought impact. This study identifies and maps factors underlying vulnerability to drought across Europe. The identification of factors influencing vulnerability starts from the analysis of past drought impacts in four European socioeconomic sectors. This analysis, along with an extensive literature review, led to the selection of vulnerability factors that are both relevant and adequate for the European context. Adopting the IPCC model, vulnerability factors were grouped to describe exposure, sensitivity and adaptive capacity. The aggregation of these components has resulted in the mapping of vulnerability to drought across Europe at NUTS02 level. Final results have been compared with data from the European Drought Impact Report Inventory. For specific hotpots vulnerability factors are presented also through spider diagrams in order to allow policy and decision makers to identify underlying sources of vulnerability in the European context. This assessment offers an overall picture at a European level that strives to contribute to enhance the understanding of drought vulnerability across Europe.

Dasymetric high resolution population distribution estimates for improved decision making, with a case study of sea-level rise vulnerability in Boca Raton, Florida

NASA Astrophysics Data System (ADS)

Ziegler, Hannes Moritz

Planners and managers often rely on coarse population distribution data from the census for addressing various social, economic, and environmental problems. In the analysis of physical vulnerabilities to sea-level rise, census units such as blocks or block groups are coarse relative to the required decision-making application. This study explores the benefits offered from integrating image classification and dasymetric mapping at the household level to provide detailed small area population estimates at the scale of residential buildings. In a case study of Boca Raton, FL, a sea-level rise inundation grid based on mapping methods by NOAA is overlaid on the highly detailed population distribution data to identify vulnerable residences and estimate population displacement. The enhanced spatial detail offered through this method has the potential to better guide targeted strategies for future development, mitigation, and adaptation efforts.

Vulnerability and adaptation of US shellfisheries to ocean acidification

NASA Astrophysics Data System (ADS)

Ekstrom, Julia A.; Suatoni, Lisa; Cooley, Sarah R.; Pendleton, Linwood H.; Waldbusser, George G.; Cinner, Josh E.; Ritter, Jessica; Langdon, Chris; van Hooidonk, Ruben; Gledhill, Dwight; Wellman, Katharine; Beck, Michael W.; Brander, Luke M.; Rittschof, Dan; Doherty, Carolyn; Edwards, Peter E. T.; Portela, Rosimeiry

2015-03-01

Ocean acidification is a global, long-term problem whose ultimate solution requires carbon dioxide reduction at a scope and scale that will take decades to accomplish successfully. Until that is achieved, feasible and locally relevant adaptation and mitigation measures are needed. To help to prioritize societal responses to ocean acidification, we present a spatially explicit, multidisciplinary vulnerability analysis of coastal human communities in the United States. We focus our analysis on shelled mollusc harvests, which are likely to be harmed by ocean acidification. Our results highlight US regions most vulnerable to ocean acidification (and why), important knowledge and information gaps, and opportunities to adapt through local actions. The research illustrates the benefits of integrating natural and social sciences to identify actions and other opportunities while policy, stakeholders and scientists are still in relatively early stages of developing research plans and responses to ocean acidification.

A global standard for monitoring coastal wetland vulnerability to accelerated sea-level rise

USGS Publications Warehouse

Webb, Edward L.; Friess, Daniel A.; Krauss, Ken W.; Cahoon, Donald R.; Guntenspergen, Glenn R.; Phelps, Jacob

2013-01-01

Sea-level rise threatens coastal salt-marshes and mangrove forests around the world, and a key determinant of coastal wetland vulnerability is whether its surface elevation can keep pace with rising sea level. Globally, a large data gap exists because wetland surface and shallow subsurface processes remain unaccounted for by traditional vulnerability assessments using tide gauges. Moreover, those processes vary substantially across wetlands, so modelling platforms require relevant local data. The low-cost, simple, high-precision rod surface-elevation table–marker horizon (RSET-MH) method fills this critical data gap, can be paired with spatial data sets and modelling and is financially and technically accessible to every country with coastal wetlands. Yet, RSET deployment has been limited to a few regions and purposes. A coordinated expansion of monitoring efforts, including development of regional networks that could support data sharing and collaboration, is crucial to adequately inform coastal climate change adaptation policy at several scales.

Coastal Vulnerability to Erosion Processes: Study Cases from Different Countries

NASA Astrophysics Data System (ADS)

Anfuso, Giorgio; Martinez Del Pozo, Jose Angel; Rangel-Buitrago, Nelson

2010-05-01

When natural processes affect or threaten human activities or infrastructures they become a natural hazard. In order to prevent the natural hazards impact and the associated economic and human losses, coastal managers need to know the intrinsic vulnerability of the littoral, using information on the physical and ecological coastal features, human occupation and present and future shoreline trends. The prediction of future coastline positions can be based on the study of coastal changes which have occurred over recent decades. Vertical aerial photographs, satellite imagery and maps are very useful data sources for the reconstruction of coast line changes at long (>60 years) and medium (between 60 and 10 years) temporal and spatial scales. Vulnerability maps have been obtained for several coastal sectors around the world through the use of Geographical Information Systems (GIS), computer-assisted multivariate analysis and numerical models. In the USA, "Flood Insurance Rate Maps" have been created by the government and "Coastal Zone Hazard Maps" have been prepared for coastal stretches affected by hurricane Hugo. In Spain, the vulnerability of the Ebro and an Andalusia coastal sector were investigated over different time scales. McLaughlin et al., (2002) developed a GIS based coastal vulnerability index for the Northern Ireland littoral that took into account socio-economic activities and coastal resistance to erosion and energetic characteristics. Lizárraga et al., (2001) combined beach reduction at Rosario (Mexico) with the probability of damage to landward structures, obtaining a vulnerability matrix. In this work several coastal vulnerability maps have also been created by comparing data on coastal erosion/accretion and land use along different coastal sectors in Italy, Morocco and Colombia. Keywords: Hazard, Vulnerability, Coastal Erosion, Italy, Morocco, Colombia.

The hydrological vulnerability of western North American boreal tree species based on ground-based observations of tree mortality

NASA Astrophysics Data System (ADS)

Hember, R. A.; Kurz, W. A.; Coops, N. C.

2017-12-01

Several studies indicate that climate change has increased rates of tree mortality, adversely affecting timber supply and carbon storage in western North American boreal forests. Statistical models of tree mortality can play a complimentary role in detecting and diagnosing forest change. Yet, such models struggle to address real-world complexity, including expectations that hydrological vulnerability arises from both drought stress and excess-water stress, and that these effects vary by species, tree size, and competitive status. Here, we describe models that predict annual probability of tree mortality (Pm) of common boreal tree species based on tree height (H), biomass of larger trees (BLT), soil water content (W), reference evapotranspiration (E), and two-way interactions. We show that interactions among H and hydrological variables are consistently significant. Vulnerability to extreme droughts consistently increases as H approaches maximum observed values of each species, while some species additionally show increasing vulnerability at low H. Some species additionally show increasing vulnerability to low W under high BLT, or increasing drought vulnerability under low BLT. These results suggest that vulnerability of trees to increasingly severe droughts depends on the hydraulic efficiency, competitive status, and microclimate of individual trees. Static simulations of Pm across a 1-km grid (i.e., with time-independent inputs of H, BLT, and species composition) indicate complex spatial patterns in the time trends during 1965-2014 and a mean change in Pm of 42 %. Lastly, we discuss how the size-dependence of hydrological vulnerability, in concert with increasingly severe drought events, may shape future responses of stand-level biomass production to continued warming and increasing carbon dioxide concentration in the region.

Scaling-up of CO2 fluxes to assess carbon sequestration in rangelands of Central Asia

Treesearch

Bruce K. Wylie; Tagir G. Gilmanov; Douglas A. Johnson; Nicanor Z. Saliendra; Larry L. Tieszen; Ruth Anne F. Doyle; Emilio A. Laca

2006-01-01

Flux towers provide temporal quantification of local carbon dynamics at specific sites. The number and distribution of flux towers, however, are generally inadequate to quantify carbon fluxes across a landscape or ecoregion. Thus, scaling up of flux tower measurements through use of algorithms developed from remote sensing and GIS data is needed for spatial...

Approximating prediction uncertainty for random forest regression models

Treesearch

John W. Coulston; Christine E. Blinn; Valerie A. Thomas; Randolph H. Wynne

2016-01-01

Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables. Random forest is a non-parametric ensemble approach, and unlike traditional regression approaches there is no direct quantification of prediction error. Understanding prediction uncertainty is important when using model-based continuous maps as...

Surface metrics: An alternative to patch metrics for the quantification of landscape structure

Treesearch

Kevin McGarigal; Sermin Tagil; Samuel A. Cushman

2009-01-01

Modern landscape ecology is based on the patch mosaic paradigm, in which landscapes are conceptualized and analyzed as mosaics of discrete patches. While this model has been widely successful, there are many situations where it is more meaningful to model landscape structure based on continuous rather than discrete spatial heterogeneity. The growing field of surface...

The influence of landscape characteristics and home-range size on the quantification of landscape-genetics relationships

Treesearch

Tabitha A. Graves; Tzeidle N. Wasserman; Milton Cezar Ribeiro; Erin L. Landguth; Stephen F. Spear; Niko Balkenhol; Colleen B. Higgins; Marie-Josee Fortin; Samuel A. Cushman; Lisette P. Waits

2012-01-01

A common approach used to estimate landscape resistance involves comparing correlations of ecological and genetic distances calculated among individuals of a species. However, the location of sampled individuals may contain some degree of spatial uncertainty due to the natural variation of animals moving through their home range ormeasurement error in plant or animal...

Detection of the Coupling between Vegetation Leaf Area and Climate in a Multifunctional Watershed, Northwestern China

Treesearch

Lu Hao; Cen Pan; Peilong Liu; Decheng Zhou; Liangxia Zhang; Zhe Xiong; Yongqiang Liu; Ge Sun

2016-01-01

Accurate detection and quantification of vegetation dynamics and drivers of observed climatic and anthropogenic change in space and time is fundamental for our understanding of the atmosphere–biosphere interactions at local and global scales. This case study examined the coupled spatial patterns of vegetation dynamics and climatic variabilities during the past...

Use of Landsat and environmental satellite data in evapotranspiration estimation from a wildland area

NASA Technical Reports Server (NTRS)

Khorram, S.; Smith, H. G.

1979-01-01

A remote sensing-aided procedure was applied to the watershed-wide estimation of water loss to the atmosphere (evapotranspiration, ET). The approach involved a spatially referenced databank based on both remotely sensed and ground-acquired information. Physical models for both estimation of ET and quantification of input parameters are specified, and results of the investigation are outlined.

Bio-metals imaging and speciation in cells using proton and synchrotron radiation X-ray microspectroscopy

PubMed Central

Ortega, Richard; Devès, Guillaume; Carmona, Asunción

2009-01-01

The direct detection of biologically relevant metals in single cells and of their speciation is a challenging task that requires sophisticated analytical developments. The aim of this article is to present the recent achievements in the field of cellular chemical element imaging, and direct speciation analysis, using proton and synchrotron radiation X-ray micro- and nano-analysis. The recent improvements in focusing optics for MeV-accelerated particles and keV X-rays allow application to chemical element analysis in subcellular compartments. The imaging and quantification of trace elements in single cells can be obtained using particle-induced X-ray emission (PIXE). The combination of PIXE with backscattering spectrometry and scanning transmission ion microscopy provides a high accuracy in elemental quantification of cellular organelles. On the other hand, synchrotron radiation X-ray fluorescence provides chemical element imaging with less than 100 nm spatial resolution. Moreover, synchrotron radiation offers the unique capability of spatially resolved chemical speciation using micro-X-ray absorption spectroscopy. The potential of these methods in biomedical investigations will be illustrated with examples of application in the fields of cellular toxicology, and pharmacology, bio-metals and metal-based nano-particles. PMID:19605403

Reconstruction of explicit structural properties at the nanoscale via spectroscopic microscopy

NASA Astrophysics Data System (ADS)

Cherkezyan, Lusik; Zhang, Di; Subramanian, Hariharan; Taflove, Allen; Backman, Vadim

2016-02-01

The spectrum registered by a reflected-light bright-field spectroscopic microscope (SM) can quantify the microscopically indiscernible, deeply subdiffractional length scales within samples such as biological cells and tissues. Nevertheless, quantification of biological specimens via any optical measures most often reveals ambiguous information about the specific structural properties within the studied samples. Thus, optical quantification remains nonintuitive to users from the diverse fields of technique application. In this work, we demonstrate that the SM signal can be analyzed to reconstruct explicit physical measures of internal structure within label-free, weakly scattering samples: characteristic length scale and the amplitude of spatial refractive-index (RI) fluctuations. We present and validate the reconstruction algorithm via finite-difference time-domain solutions of Maxwell's equations on an example of exponential spatial correlation of RI. We apply the validated algorithm to experimentally measure structural properties within isolated cells from two genetic variants of HT29 colon cancer cell line as well as within a prostate tissue biopsy section. The presented methodology can lead to the development of novel biophotonics techniques that create two-dimensional maps of explicit structural properties within biomaterials: the characteristic size of macromolecular complexes and the variance of local mass density.

Phase-encoded single-voxel magnetic resonance spectroscopy for suppressing outer volume signals at 7 Tesla.

PubMed

Li, Ningzhi; An, Li; Johnson, Christopher; Shen, Jun

2017-01-01

Due to imperfect slice profiles, unwanted signals from outside the selected voxel may significantly contaminate metabolite signals acquired using in vivo magnetic resonance spectroscopy (MRS). The use of outer volume suppression may exceed the SAR threshold, especially at high field. We propose using phase-encoding gradients after radiofrequency (RF) excitation to spatially encode unwanted signals originating from outside of the selected single voxel. Phase-encoding gradients were added to a standard single voxel point-resolved spectroscopy (PRESS) sequence which selects a 2 × 2 × 2 cm 3 voxel. Subsequent spatial Fourier transform was used to encode outer volume signals. Phantom and in vivo experiments were performed using both phase-encoded PRESS and standard PRESS at 7 Tesla. Quantification was performed using fitting software developed in-house. Both phantom and in vivo studies showed that spectra from the phase-encoded PRESS sequence were relatively immune from contamination by oil signals and have more accurate quantification results than spectra from standard PRESS spectra of the same voxel. The proposed phase-encoded single-voxel PRESS method can significantly suppress outer volume signals that may appear in the spectra of standard PRESS without increasing RF power deposition.

In vivo visualizations of drought-induced embol 35 ism spread in Vitis vinifera

USDA-ARS?s Scientific Manuscript database

Long distance water transport through plant xylem is vulnerable to hydraulic dysfunction during periods of increased tension on the xylem sap, often coinciding with drought. While the effects of local and systemic embolism on plant water transport and physiology are well documented, the spatial patt...

MULTI-SCALED VULNERABILITY ANALYSES: IMPROVING DECISION-MAKING AT REGIONAL TO LOCAL LEVELS THROUGH PARTNERSHIP

EPA Science Inventory

Decision-makers at all scales are faced with setting priorities for both use of limited resources and for risk management. While there are all kinds of monitoring data and models to project conditions at different spatial and temporal scales, synthesized information to establish ...

Scaling Properties and Spatial Interpolation of Soil Moisture

DTIC Science & Technology

2004-08-24

the sensitivities is useful not only for characterizing soil moisture but also for forecasting the vulnerability of a region’s water cycle to climate...regional water balance was presented that can be used to assess the impact of climatic fluctuations and changes on the water cycle of a region. In

Modeling the South American range of the cerulean warbler

Treesearch

S. Barker; S. Benítez; J. Baldy; D. Cisneros Heredia; G. Colorado Zuluaga; F. Cuesta; I. Davidson; D. Díaz; A. Ganzenmueller; S. García; M. K. Girvan; E. Guevara; P. Hamel; A. B. Hennessey; O. L. Hernández; S. Herzog; D. Mehlman; M. I. Moreno; E. Ozdenerol; P. Ramoni-Perazzi; M. Romero; D. Romo; P. Salaman; T. Santander; C. Tovar; M. Welton; T. Will; C. Pedraza; G. Galindo

2006-01-01

Successful conservation of rare species requires detailed knowledge of the species’ distribution. Modeling spatial distribution is an efficient means of locating potential habitats. Cerulean Warbler (Dendroica cerulea, Parulidae) was listed as a Vulnerable Species by the International Union for the Conservation of Nature and Natural Resources in...

Tidal wetland plant and algal assemblages in Oregon: spatial patterns of composition and vulnerability to climate change

EPA Science Inventory

Tidal wetlands support important ecosystem functions along the coast of the Pacific Northwest such as primary production and nutrient transformation. Sea-level rise (SLR) and elevated salinity due to climate change may affect the abundance, distribution, and diversity of plants a...

Putting Climate Adaptation on the Map: Developing Spatial Management Strategies for Whitebark Pine in the Greater Yellowstone Ecosystem.

PubMed

Ireland, Kathryn B; Hansen, Andrew J; Keane, Robert E; Legg, Kristin; Gump, Robert L

2018-06-01

Natural resource managers face the need to develop strategies to adapt to projected future climates. Few existing climate adaptation frameworks prescribe where to place management actions to be most effective under anticipated future climate conditions. We developed an approach to spatially allocate climate adaptation actions and applied the method to whitebark pine (WBP; Pinus albicaulis) in the Greater Yellowstone Ecosystem (GYE). WBP is expected to be vulnerable to climate-mediated shifts in suitable habitat, pests, pathogens, and fire. We spatially prioritized management actions aimed at mitigating climate impacts to WBP under two management strategies: (1) current management and (2) climate-informed management. The current strategy reflected management actions permissible under existing policy and access constraints. Our goal was to understand how consideration of climate might alter the placement of management actions, so the climate-informed strategies did not include these constraints. The spatial distribution of actions differed among the current and climate-informed management strategies, with 33-60% more wilderness area prioritized for action under climate-informed management. High priority areas for implementing management actions include the 1-8% of the GYE where current and climate-informed management agreed, since this is where actions are most likely to be successful in the long-term and where current management permits implementation. Areas where climate-informed strategies agreed with one another but not with current management (6-22% of the GYE) are potential locations for experimental testing of management actions. Our method for spatial climate adaptation planning is applicable to any species for which information regarding climate vulnerability and climate-mediated risk factors is available.

Putting Climate Adaptation on the Map: Developing Spatial Management Strategies for Whitebark Pine in the Greater Yellowstone Ecosystem

NASA Astrophysics Data System (ADS)

Ireland, Kathryn B.; Hansen, Andrew J.; Keane, Robert E.; Legg, Kristin; Gump, Robert L.

2018-06-01

Natural resource managers face the need to develop strategies to adapt to projected future climates. Few existing climate adaptation frameworks prescribe where to place management actions to be most effective under anticipated future climate conditions. We developed an approach to spatially allocate climate adaptation actions and applied the method to whitebark pine (WBP; Pinus albicaulis) in the Greater Yellowstone Ecosystem (GYE). WBP is expected to be vulnerable to climate-mediated shifts in suitable habitat, pests, pathogens, and fire. We spatially prioritized management actions aimed at mitigating climate impacts to WBP under two management strategies: (1) current management and (2) climate-informed management. The current strategy reflected management actions permissible under existing policy and access constraints. Our goal was to understand how consideration of climate might alter the placement of management actions, so the climate-informed strategies did not include these constraints. The spatial distribution of actions differed among the current and climate-informed management strategies, with 33-60% more wilderness area prioritized for action under climate-informed management. High priority areas for implementing management actions include the 1-8% of the GYE where current and climate-informed management agreed, since this is where actions are most likely to be successful in the long-term and where current management permits implementation. Areas where climate-informed strategies agreed with one another but not with current management (6-22% of the GYE) are potential locations for experimental testing of management actions. Our method for spatial climate adaptation planning is applicable to any species for which information regarding climate vulnerability and climate-mediated risk factors is available.

Incongruent genetic connectivity patterns for VME indicator taxa: implications for the management of New Zealand's vulnerable marine ecosystems

NASA Astrophysics Data System (ADS)

Clark, M. R.; Gardner, J.; Holland, L.; Zeng, C.; Hamilton, J. S.; Rowden, A. A.

2016-02-01

In the New Zealand region vulnerable marine ecosystems (VMEs) are at risk from commercial fishing activity and future seabed mining. Understanding connectivity among VMEs is important for the design of effective spatial management strategies, i.e. a network of protected areas. To date however, genetic connectivity in the New Zealand region has rarely been documented. As part of a project developing habitat suitability models and spatial management options for VMEs we used DNA sequence data and microsatellite genotyping to assess genetic connectivity for a range of VME indicator taxa, including the coral Desmophyllum dianthus, and the sponges Poecilastra laminaris and Penares palmatoclada. Overall, patterns of connectivity were inconsistent amonst taxa. Nonetheless, genetic data from each taxon were relevant to inform management at a variety of spatial scales. D. dianthus populations in the Kermadec volcanic arc and the Louisville Seamount Chain were indistinguishable, highlighting the importance of considering source-sink dynamics between populations beyond the EEZ in conservation planning. Poecilastra laminaris populations showed significant divergence across the Chatham Rise, in contrast to P. palmatoclada, which had a uniform haplotypic distribution. However, both sponge species exhibited the highest genetic diversity on the Chatham Rise, suggesting that this area is a genetic hotspot. The spatial heterogeneity of genetic patterns of structure suggest that inclusion of several taxa is necessary to facilitate understanding of regional connectivity patterns, variation in which may be attributed to alternate life history strategies, local hydrodynamic regimes, or in some cases, suboptimal sample sizes. Our findings provide important information for use by environmental managers, including summary maps of genetic diversity and barriers to gene flow, which will be used in spatial management decision-support tools.

Developing Spatial Management Options for the Protection of Vulnerable Marine Ecosystems in the South Pacific Ocean Region.

NASA Astrophysics Data System (ADS)

Rowden, A. A.; Lundquist, C. J.; Clark, M. R.; Anderson, O. F.; Guinotte, J. M.; Baird, S. J.; Roux, M. J.; Wadhwa, S.

2016-02-01

The South Pacific Regional Fisheries Management Organisation (SPRFMO) Convention includes specific provisions to protect vulnerable marine ecosystems (VMEs). The SPRFMO Commission has determined that the interim measures put in place to protect VMEs would be replaced by an improved system of fishable and closed areas. These closures would effectively represent a preliminary spatial management plan, whereby conservation and management measures are implemented that will result in sustainable fisheries and benthic protection. We used the conservation planning tool Zonation to develop spatial management options that balance the protection of VMEs with utilisation of high value areas for fishing. Input data included habitat suitability maps, and uncertainties associated with these model predictions, for eleven VME indicator taxa (4 Scleractinian coral species; 3 other cnidarian groups (Family Stylasteridae, Order Antipatharia, Order Pennatulacea; 2 classes of sponges (Demospongiae, Hexactinellidae), and 2 echninoderm groups (Crinoidea and Brisingida)) at bathyal depths across the entire SPRFMO area (divided into 1 km2 grid cells); New Zealand fishing catch data (for two different time periods and trawl types); naturalness (represented by proxy variable using the number of trawl tows); and a bioregionalisation scheme. Running various scenario models for spatial planning allowed for the cost to fishing to be determined, in terms of the amount of the trawl catch footprint lost if high priority areas for VME indicator taxa are protected. Generally, the cost to fishing was low given the relatively high proportion of suitable habitat for VME indicator taxa protected. The main outcome of the present study is a demonstration of the practical utility of using available data, including modelled data, and the Zonation conservation planning software tool to develop options for the spatial management of the SPRFMO area.

A flood risk assessment and mapping for Riga city

NASA Astrophysics Data System (ADS)

Bethers, U.; Sennikovs, J.; Virbulis, J.; Timuhins, A.

2009-04-01

Riga (population ca. 800,000) is the capital of Latvia. The city is located at the southern coast of Gulf of Riga along the lower stretch of the River Daugava. The water bodies adjacent or within the territory of the city are the River Daugava itself, its connection (Bullupe) to another major river - Lielupe, several minor tributaries of the River Daugava, as well as an interconnected lake system of estuarine origin. The flow in the lower stretch of the River Daugava is regulated by Riga hydropower plant which is situated approx. 25 kilometers upstream the river mouth. The lowest 12 kilometers of the river channel is dredged to ensure the operation of the Riga Freeport. The aims of the study were (1) the identification of the flood risk situations, (2) the quantification of the flooding scenarious of different return periods, (3) the building and calibration of the hydrodynamical mathematical model for the domain potentially vulnerable for flooding, (4) the calculation of flood events with different return period, and (5) the detailed (horizontal accuracy around 10 m) of the potentially flooded areas. The combination of storm surges in the southern part of Gulf of Riga with unfavorable regime of hydropower plant operation was found as the most dangerous flooding situation. The time series of water level at the mouth of the River Daugava was analysed for more than 130 year long time period. The significant trend was found in the annual peak water level. Five significant storm events were found in time period 2001-2007 which roughly correspond to storm surges with return period once in 5, 10, 20, 50 and 100 years. The model storm events were created by scaling waterlevel and meteorological conditions during these selected events, and superposing them with hydropowerplant operation regime. The finite-element based shallow water model was built for the area, potentially vulnerable for flooding. Heterogeneous depth/terrain information from various sources was integrated in the model. The linear objects (watercourses, dams, etc.) of hydraulic importance were included in the model. The typical spatial resolution of approx. 50-100 m was reached with total number of finite elements around 250,000. The hydrodynamical model was calibrated on the basis of water level observations in 5 different locations during 5 selected real storm events. The hydrodynamics of the flood scenarious were calculated for the model storm situations. The importance of the dynamical modeling of flooded areas was shown for the domain with a complex channel system and typical length of storm event below 18 hours. The method for the mapping of the results of hydrodynamical calculations on the digital terrain map of much higher (10 m) spatial resolution was proposed and applied.

Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

NASA Astrophysics Data System (ADS)

Broich, Mark

Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.

Structural and functional properties of spatially embedded scale-free networks.

PubMed

Emmerich, Thorsten; Bunde, Armin; Havlin, Shlomo

2014-06-01

Scale-free networks have been studied mostly as non-spatially embedded systems. However, in many realistic cases, they are spatially embedded and these constraints should be considered. Here, we study the structural and functional properties of a model of scale-free (SF) spatially embedded networks. In our model, both the degree and the length of links follow power law distributions as found in many real networks. We show that not all SF networks can be embedded in space and that the largest degree of a node in the network is usually smaller than in nonembedded SF networks. Moreover, the spatial constraints (each node has only few neighboring nodes) introduce degree-degree anticorrelations (disassortativity) since two high degree nodes cannot stay close in space. We also find significant effects of space embedding on the hopping distances (chemical distance) and the vulnerability of the networks.

Integrating socio-economic and infrastructural dimension to reveal hazard vulnerability of coastal districts

NASA Astrophysics Data System (ADS)

Mazumdar, Jublee; Paul, Saikat

2015-04-01

Losses of life and property due to natural hazards have intensified in the past decade, motivating an alteration of disaster management away from simple post event resettlement and rehabilitation. The degree of exposure to hazard for a homogeneous population is not entirely reliant upon nearness to the source of hazard event. Socio-economic factors and infrastructural capability play an important role in determining the vulnerability of a place. This study investigates the vulnerability of eastern coastal states of India from tropical cyclones. The record of past hundred years shows that the physical vulnerability of eastern coastal states is four times as compared to the western coastal states in terms of frequency and intensity of tropical cyclones. Nevertheless, these physical factors played an imperative role in determining the vulnerability of eastern coast. However, the socio-economic and infrastructural factors influence the risk of exposure exponentially. Inclusion of these indicators would provide better insight regarding the preparedness and resilience of settlements to hazard events. In this regard, the present study is an effort to develop an Integrated Vulnerability Model (IVM) based on socio-economic and infrastructural factors for the districts of eastern coastal states of India. A method is proposed for quantifying the socio-economic and infrastructural vulnerability to tropical cyclone in these districts. The variables included in the study are extracted from Census of India, 2011 at district level administrative unit. In the analysis, a large number of variables are reduced to a smaller number of factors by using principal component analysis that represents the socio-economic and infrastructure vulnerability to tropical cyclone. Subsequently, the factor scores in socio-economic Vulnerability Index (SeVI) and Infrastructure Vulnerability Index (InVI) are standardized from 0 to 1, indicating the range from low to high vulnerability. The factor scores are then mapped for spatial analysis. Utilizing SeVI and InVI, the highly vulnerable districts are demonstrated that are likely to face significant challenges in coping with tropical cyclone and require strategies to address the various aspects of socio-economic and infrastructural vulnerability. Moreover, this model can be incorporated not only for multi-level governance but also to integrate it with the real-time weather forecasts to identify the predictive areas of vulnerability.

On Information Metrics for Spatial Coding.

PubMed

Souza, Bryan C; Pavão, Rodrigo; Belchior, Hindiael; Tort, Adriano B L

2018-04-01

The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area

USGS Publications Warehouse

McKinney, Tim S.; Anning, David W.

2012-01-01

This product "Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area" is a 1:250,000-scale vector spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions.

Near-Infrared Imaging for Spatial Mapping of Organic Content in Petroleum Source Rocks

NASA Astrophysics Data System (ADS)

Mehmani, Y.; Burnham, A. K.; Vanden Berg, M. D.; Tchelepi, H.

2017-12-01

Natural gas from unconventional petroleum source rocks (shales) plays a key role in our transition towards sustainable low-carbon energy production. The potential for carbon storage (in adsorbed state) in these formations further aligns with efforts to mitigate climate change. Optimizing production and development from these resources requires knowledge of the hydro-thermo-mechanical properties of the rock, which are often strong functions of organic content. This work demonstrates the potential of near-infrared (NIR) spectral imaging in mapping the spatial distribution of organic content with O(100µm) resolution on cores that can span several hundred feet in depth (Mehmani et al., 2017). We validate our approach for the immature oil shale of the Green River Formation (GRF), USA, and show its applicability potential in other formations. The method is a generalization of a previously developed optical approach specialized to the GRF (Mehmani et al., 2016a). The implications of this work for spatial mapping of hydro-thermo-mechanical properties of excavated cores, in particular thermal conductivity, are discussed (Mehmani et al., 2016b). References:Mehmani, Y., A.K. Burnham, M.D. Vanden Berg, H. Tchelepi, "Quantification of organic content in shales via near-infrared imaging: Green River Formation." Fuel, (2017). Mehmani, Y., A.K. Burnham, M.D. Vanden Berg, F. Gelin, and H. Tchelepi. "Quantification of kerogen content in organic-rich shales from optical photographs." Fuel, (2016a). Mehmani, Y., A.K. Burnham, H. Tchelepi, "From optics to upscaled thermal conductivity: Green River oil shale." Fuel, (2016b).

Towards robust quantification and reduction of uncertainty in hydrologic predictions: Integration of particle Markov chain Monte Carlo and factorial polynomial chaos expansion

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Baetz, B. W.; Ancell, B. C.

2017-05-01

The particle filtering techniques have been receiving increasing attention from the hydrologic community due to its ability to properly estimate model parameters and states of nonlinear and non-Gaussian systems. To facilitate a robust quantification of uncertainty in hydrologic predictions, it is necessary to explicitly examine the forward propagation and evolution of parameter uncertainties and their interactions that affect the predictive performance. This paper presents a unified probabilistic framework that merges the strengths of particle Markov chain Monte Carlo (PMCMC) and factorial polynomial chaos expansion (FPCE) algorithms to robustly quantify and reduce uncertainties in hydrologic predictions. A Gaussian anamorphosis technique is used to establish a seamless bridge between the data assimilation using the PMCMC and the uncertainty propagation using the FPCE through a straightforward transformation of posterior distributions of model parameters. The unified probabilistic framework is applied to the Xiangxi River watershed of the Three Gorges Reservoir (TGR) region in China to demonstrate its validity and applicability. Results reveal that the degree of spatial variability of soil moisture capacity is the most identifiable model parameter with the fastest convergence through the streamflow assimilation process. The potential interaction between the spatial variability in soil moisture conditions and the maximum soil moisture capacity has the most significant effect on the performance of streamflow predictions. In addition, parameter sensitivities and interactions vary in magnitude and direction over time due to temporal and spatial dynamics of hydrologic processes.

Demonstration of Technologies for Remote and in Situ Sensing of Atmospheric Methane Abundances - a Controlled Release Experiment

NASA Astrophysics Data System (ADS)

Aubrey, A. D.; Thorpe, A. K.; Christensen, L. E.; Dinardo, S.; Frankenberg, C.; Rahn, T. A.; Dubey, M.

2013-12-01

It is critical to constrain both natural and anthropogenic sources of methane to better predict the impact on global climate change. Critical technologies for this assessment include those that can detect methane point and concentrated diffuse sources over large spatial scales. Airborne spectrometers can potentially fill this gap for large scale remote sensing of methane while in situ sensors, both ground-based and mounted on aerial platforms, can monitor and quantify at small to medium spatial scales. The Jet Propulsion Laboratory (JPL) and collaborators recently conducted a field test located near Casper, WY, at the Rocky Mountain Oilfield Test Center (RMOTC). These tests were focused on demonstrating the performance of remote and in situ sensors for quantification of point-sourced methane. A series of three controlled release points were setup at RMOTC and over the course of six experiment days, the point source flux rates were varied from 50 LPM to 2400 LPM (liters per minute). During these releases, in situ sensors measured real-time methane concentration from field towers (downwind from the release point) and using a small Unmanned Aerial System (sUAS) to characterize spatiotemporal variability of the plume structure. Concurrent with these methane point source controlled releases, airborne sensor overflights were conducted using three aircraft. The NASA Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) participated with a payload consisting of a Fourier Transform Spectrometer (FTS) and an in situ methane sensor. Two imaging spectrometers provided assessment of optical and thermal infrared detection of methane plumes. The AVIRIS-next generation (AVIRIS-ng) sensor has been demonstrated for detection of atmospheric methane in the short wave infrared region, specifically using the absorption features at ~2.3 μm. Detection of methane in the thermal infrared region was evaluated by flying the Hyperspectral Thermal Emission Spectrometer (HyTES), retrievals which interrogate spectral features in the 7.5 to 8.5 μm region. Here we discuss preliminary results from the JPL activities during the RMOTC controlled release experiment, including capabilities of airborne sensors for total columnar atmospheric methane detection and comparison to results from ground measurements and dispersion models. Potential application areas for these remote sensing technologies include assessment of anthropogenic and natural methane sources over wide spatial scales that represent significant unconstrained factors to the global methane budget.

A Comparative Study on Physical Vulnerability of Urban Area against Natural Hazards: Importance of Health Promoting Approach in Civil Engineering.

PubMed

Ahadnezhad Reveshty, Mohsen; Kamelifar, Mohammad Javad; Ranjbarnia, Behzad; Pashaiifar, Alireza

2014-01-01

Estimation of urban vulnerability to earthquakes can be consid-ered as an Ill-structured problem in urban in both unplanned and planned areas. Multi-criteria evaluation (MCE) provides a way to integrate different spatial data layers in a geographic information system to create composite maps representing risk. We utilized MCE in a raster Geographic Information System (GIS) to evaluate risk in vulnerable tissues of Tabriz, Iran zone. In this MCE physical risk factors and sub-factors were included and were weighted by experts. Afterward data entered to GIS and then the layers of the criteria were exported. The obtained results were entered to IDRISI and fuzzified. Ultimately the final map of physical vulnerability was outputted by overlaying order. Vulnerable tissues are highly consistent to non-official areas. However, the planned area which is called Valiasr is in low risky condition and this condition is desirable in crisis times. Here, we observe the preference of physical pre-planning operations. The links between urban planning and health are many and varied. Environmental, social and economic conditions in cities can have both positive and negative influences on human health and centre. Urban planning and related professions play an important role in shaping those conditions.

A Comparative Study on Physical Vulnerability of Urban Area against Natural Hazards: Importance of Health Promoting Approach in Civil Engineering

PubMed Central

Ahadnezhad Reveshty, Mohsen; Kamelifar, Mohammad Javad; Ranjbarnia, Behzad; Pashaiifar, Alireza

2014-01-01

Background: Estimation of urban vulnerability to earthquakes can be consid­ered as an Ill-structured problem in urban in both unplanned and planned areas. Multi-criteria evaluation (MCE) provides a way to integrate different spatial data layers in a geographic information system to create composite maps representing risk. We utilized MCE in a raster Geographic Information System (GIS) to evaluate risk in vulnerable tissues of Tabriz, Iran zone. Methods: In this MCE physical risk factors and sub-factors were included and were weighted by experts. Afterward data entered to GIS and then the layers of the criteria were exported. The obtained results were entered to IDRISI and fuzzified. Ultimately the final map of physical vulnerability was outputted by overlaying order. Results: Vulnerable tissues are highly consistent to non-official areas. However, the planned area which is called Valiasr is in low risky condition and this condition is desirable in crisis times. Here, we observe the preference of physical pre-planning operations. Conclusion: The links between urban planning and health are many and varied. Environmental, social and economic conditions in cities can have both positive and negative influences on human health and centre. Urban planning and related professions play an important role in shaping those conditions. PMID:25097846

How useful are Swiss flood insurance data for flood vulnerability assessments?

NASA Astrophysics Data System (ADS)

Röthlisberger, Veronika; Bernet, Daniel; Zischg, Andreas; Keiler, Margreth

2015-04-01

The databases of Swiss flood insurance companies build a valuable but to date rarely used source of information on physical flood vulnerability. Detailed insights into the Swiss flood insurance system are crucial for using the full potential of the different databases for research on flood vulnerability. Insurance against floods in Switzerland is a federal system, the modalities are manly regulated on cantonal level. However there are some common principles that apply throughout Switzerland. First of all coverage against floods (and other particular natural hazards) is an integral part of every fire insurance policy for buildings or contents. This coupling of insurance as well as the statutory obligation to insure buildings in most of the cantons and movables in some of the cantons lead to a very high penetration. Second, in case of damage, the reinstatement costs (value as new) are compensated and third there are no (or little) deductible and co-pay. High penetration and the fact that the compensations represent a large share of the direct, tangible losses of the individual policy holders make the databases of the flood insurance companies a comprehensive and therefore valuable data source for flood vulnerability research. Insurance companies not only store electronically data about losses (typically date, amount of claims payment, cause of damage, identity of the insured object or policyholder) but also about insured objects. For insured objects the (insured) value and the details on the policy and its holder are the main feature to record. On buildings the insurance companies usually computerize additional information such as location, volume, year of construction or purpose of use. For the 19 (of total 26) cantons with a cantonal monopoly insurer the data of these insurance establishments have the additional value to represent (almost) the entire building stock of the respective canton. Spatial referenced insurance data can be used for many aspects of vulnerability and resilience assessments. For instance, the collation of insurance loss data with event documentations containing information on flood intensity allows to develop damage curves. Flood damage curves are fundamental for many risk analysis methodologies but to date only few are published and the spatial and temporal scope of their applicability is subject of discussion. Another possibility of using insurance data lies in the field of assessment exposure, where the analysis of comprehensive insurance portfolio data can improve the understanding of the physical but also the socio-economical vulnerability of a society. The poster spotlights key opportunities and challenges scientists are facing when using insurance data for flood vulnerability assessments.

Quantification and micron-scale imaging of spatial distribution of trace beryllium in shrapnel fragments and metallurgic samples with correlative fluorescence detection method and secondary ion mass spectrometry (SIMS)

PubMed Central

Abraham, Jerrold L.; Chandra, Subhash; Agrawal, Anoop

2014-01-01

Recently, a report raised the possibility of shrapnel-induced chronic beryllium disease (CBD) from long-term exposure to the surface of retained aluminum shrapnel fragments in the body. Since the shrapnel fragments contained trace beryllium, methodological developments were needed for beryllium quantification and to study its spatial distribution in relation to other matrix elements, such as aluminum and iron, in metallurgic samples. In this work, we developed methodology for quantification of trace beryllium in samples of shrapnel fragments and other metallurgic sample-types with main matrix of aluminum (aluminum cans from soda, beer, carbonated water, and aluminum foil). Sample preparation procedures were developed for dissolving beryllium for its quantification with the fluorescence detection method for homogenized measurements. The spatial distribution of trace beryllium on the sample surface and in 3D was imaged with a dynamic secondary ion mass spectrometry (SIMS) instrument, CAMECA IMS 3f SIMS ion microscope. The beryllium content of shrapnel (~100 ppb) was the same as the trace quantities of beryllium found in aluminum cans. The beryllium content of aluminum foil (~25 ppb) was significantly lower than cans. SIMS imaging analysis revealed beryllium to be distributed in the form of low micron-sized particles and clusters distributed randomly in X-Y-and Z dimensions, and often in association with iron, in the main aluminum matrix of cans. These observations indicate a plausible formation of Be-Fe or Al-Be alloy in the matrix of cans. Further observations were made on fluids (carbonated water) for understanding if trace beryllium in cans leached out and contaminated the food product. A direct comparison of carbonated water in aluminum cans and plastic bottles revealed that beryllium was below the detection limits of the fluorescence detection method (~0.01 ppb). These observations indicate that beryllium present in aluminum matrix was either present in an immobile form or its mobilization into the food product was prevented by a polymer coating on the inside of cans, a practice used in food industry to prevent contamination of food products. The lack of such coating in retained shrapnel fragments renders their surface a possible source of contamination for long-term exposure of tissues and fluids and induction of disease, as characterized in a recent study. Methodological developments reported here can be extended to studies of beryllium in electronics devices and components. PMID:25146877

Quantification and micron-scale imaging of spatial distribution of trace beryllium in shrapnel fragments and metallurgic samples with correlative fluorescence detection method and secondary ion mass spectrometry (SIMS).

PubMed

Abraham, J L; Chandra, S; Agrawal, A

2014-11-01

Recently, a report raised the possibility of shrapnel-induced chronic beryllium disease from long-term exposure to the surface of retained aluminum shrapnel fragments in the body. Since the shrapnel fragments contained trace beryllium, methodological developments were needed for beryllium quantification and to study its spatial distribution in relation to other matrix elements, such as aluminum and iron, in metallurgic samples. In this work, we developed methodology for quantification of trace beryllium in samples of shrapnel fragments and other metallurgic sample-types with main matrix of aluminum (aluminum cans from soda, beer, carbonated water and aluminum foil). Sample preparation procedures were developed for dissolving beryllium for its quantification with the fluorescence detection method for homogenized measurements. The spatial distribution of trace beryllium on the sample surface and in 3D was imaged with a dynamic secondary ion mass spectrometry instrument, CAMECA IMS 3f secondary ion mass spectrometry ion microscope. The beryllium content of shrapnel (∼100 ppb) was the same as the trace quantities of beryllium found in aluminum cans. The beryllium content of aluminum foil (∼25 ppb) was significantly lower than cans. SIMS imaging analysis revealed beryllium to be distributed in the form of low micron-sized particles and clusters distributed randomly in X-Y- and Z dimensions, and often in association with iron, in the main aluminum matrix of cans. These observations indicate a plausible formation of Be-Fe or Al-Be alloy in the matrix of cans. Further observations were made on fluids (carbonated water) for understanding if trace beryllium in cans leached out and contaminated the food product. A direct comparison of carbonated water in aluminum cans and plastic bottles revealed that beryllium was below the detection limits of the fluorescence detection method (∼0.01 ppb). These observations indicate that beryllium present in aluminum matrix was either present in an immobile form or its mobilization into the food product was prevented by a polymer coating on the inside of cans, a practice used in food industry to prevent contamination of food products. The lack of such coating in retained shrapnel fragments renders their surface a possible source of contamination for long-term exposure of tissues and fluids and induction of disease, as characterized in a recent study. Methodological developments reported here can be extended to studies of beryllium in electronics devices and components. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model.

PubMed

Kaliraj, S; Chandrasekar, N; Peter, T Simon; Selvakumar, S; Magesh, N S

2015-01-01

The south west coast of Kanyakumari district in Tamil Nadu, India, is significantly affected by seawater intrusion and diffusion of pollutants into the aquifers due to unregulated beach placer mining and other anthropogenic activities. The present study investigates the vulnerability of the coastal aquifers using Geographic Information System (GIS)-based DRASTIC model. The seven DRASTIC parameters have been analyzed using the statistical equation of this model to demarcate the vulnerable zones for aquifer contamination. The vulnerability index map is prepared from the weighted spatial parameters, and an accounting of total index value ranged from 85 to 213. Based on the categorization of vulnerability classes, the high vulnerable zones are found near the beach placer mining areas between Manavalakurichi and Kodimanal coastal stretches. The aquifers associated with settlements and agricultural lands in the middle-eastern part have experienced high vulnerability due to contaminated water bodies. Similarly, the coastal areas of Thengapattinam and Manakudi estuary and around the South Tamaraikulam have also been falling under high vulnerability condition due to backwater and saltpan. In general, the nearshore region except the placer mining zone and the backwater has a moderately vulnerable condition, and the vulnerability index values range from 149 to180. Significantly, the northern and northeastern uplands and some parts of deposition zones in the middle-south coast have been identified as low to no vulnerable conditions. They are structurally controlled by various geological features such as charnockite, garnet biotite gneiss and granites, and sand dunes, respectively. The aquifer vulnerability assessment has been cross-verified by geochemical indicators such as total dissolved solids (TDS), Cl(-), HCO₃(-), and Cl(-)/HCO₃(-) ratio. The high ranges of TDS (1,842--3,736 mg/l) and Cl(-) (1,412--2,112 mg/l) values are well correlated with the observed high vulnerable zones in the study area. The Cl(-)/HCO₃(-) ratio (7.13 to 12.18) of the high vulnerable zone obviously indicates deterioration of the aquifer contamination. Sensitivity analysis has also been performed to evaluate sensitivity of the individual DRASTIC parameters to aquifer vulnerability. This reveals the net recharge rate and groundwater table depth are becoming more sensitive to aquifer contamination. It is realized that the GIS is an effective platform for aquifer vulnerability mapping with reliable accuracy, and hence, the study is more useful for sustainable water resource management and the aquifer conservation.

Urban planning and interactions with atmospheric pollution in Arve valley

NASA Astrophysics Data System (ADS)

Langlois de Septenville, William; Cossart, Étienne

2017-04-01

Atmospheric pollution is a major concern of urbanised areas and territory managers have to conduct efficient policies to decrease population exposure and vulnerability. Even if pollution peaks are subject to an important mediatisation and to a large part of preventive actions, background pollution remains responsible of the largest sanitary effects. They depend on (1) the concentration and the duration of the exposure and (2) to the kind of pollutants considered. Many sources of pollutants can be identified in urban areas as heating, industry or traffic; and each of them generates specific particles. Currently, the major part of pollution risk studies focuses on modelling particle emissions and their dissemination in the environment. These kinds of studies highlight the hazard intensity and its spatiality, commonly named the hazard exposure. Another part of risk studies, less frequent, considers the vulnerability. Vulnerability is a complex concept that involves a wide range of scales and objects ranging from biophysical parameters to social characteristics. They notably concern accessibility to information, knowledge and perceptions about the risk. The Arve valley (south-east of France) is subject to heavy pollution concentrations. High levels recording in this area have imposed the implementation of an Atmosphere Protection Plan. This type of plan is triggered if a peak occurs and enforces provisional binding measures for polluters, such as highway speed limitation for traffic emissions. These measures are only focused on emissions and have no effect for reducing vulnerability and exposition, for a long- and short-term time scales. An opportunity to ensure this objective is to consider how local urban morphologies can combine exposition and vulnerability situations. Indeed, cities have been planned without taking into account atmospheric pollution and morphologies. This context may conduct to the increase in both of these two risk components and producing hotspots of air pollution risk situations. In this poster, we purpose to present a methodology for analysing the relationships between actual city morphologies and pollutants. To ensure this objective, we consider the spatial characteristics of vulnerabilities. We also consider urban morphology responsible for a large part of the population exposure, particularly because it influences people's mobility and the frequentation of specific areas. Last part of the analysis will integrate the local street morphologies and their ability to concentrate pollutants, mainly focusing on traffic emissions. For example, close and large buildings may create areas where the low ventilation increases concentration of pollutants.

A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siqueira, Hygor Evangelista; Pissarra, Teresa Cristina Tarlé; Farias do Valle Junior, Renato

Road spills of hazardous substances are common in developing countries due to increasing industrialization and traffic accidents, and represent a serious threat to soils and water in catchments. There is abundant literature on equations describing the wash-off of pollutants from roads during a storm event and there are a number of watershed models incorporating those equations in storm water quality algorithms that route runoff and pollution yields through a drainage system towards the catchment outlet. However, methods describing catchment vulnerability to contamination by road spills based solely on biophysical parameters are scarce. These methods could be particularly attractive to managersmore » because they can operate with a limited amount of easily collectable data, while still being able to provide important insights on the areas more prone to contamination within the studied watershed. The purpose of this paper was then to contribute with a new vulnerability model. To accomplish the goal, a selection of medium properties appearing in wash-off equations and routing algorithms were assembled and processed in a parametric framework based on multi criteria analysis to define the watershed vulnerability. However, parameters had to be adapted because wash-off equations and water quality models have been developed to operate primarily in the urban environment while the vulnerability model is meant to run in rural watersheds. The selected parameters were hillside slope, ground roughness (depending on land use), soil permeability (depending on soil type), distance to water courses and stream density. The vulnerability model is a spatially distributed algorithm that was prepared to run under the IDRISI Selva software, a GIS platform capable of handling spatial and alphanumeric data and execute the necessary terrain model, hydrographic and thematic analyses. For illustrative purposes, the vulnerability model was applied to the legally protected Environmental Protection Area (APA), located in the Uberaba region, state of Minas Gerais, Brazil. In this region, the risk of accidents causing chemical spills is preoccupying because large quantities of dangerous materials are transported in two important distribution highways while the APA is fundamental for the protection of water resources, the riverine ecosystems and remnants of native vegetation. In some tested scenarios, model results show 60% of vulnerable areas within the studied area. The most sensitive parameter to vulnerability is soil type. To prevent soils from contamination, specific measures were proposed involving minimization of land use conflicts that would presumably raise the soil's organic matter and in the sequel restore the soil's structural functions. Additionally, the present study proposed the preservation and reinforcement of riparian forests as one measure to protect the quality of surface water. - Highlights: • A multi criteria analog model was developed to assess rural catchment vulnerability along roads. • Model parameters were defined by analogy with urban wash-off equations and routing algorithms. • The model mixes up various biophysical and socio-economic parameters. • Model application was based on a scenario analysis. • The study is focused on the Environmental Protection Area of Uberaba River, Brazil.« less