Spatial Hazard Research Articles

Increasing the resilience of air traffic networks using a network graph theory approach

Air traffic networks are essential to today’s global society. They are the fastest means of transporting physical goods and people and are a major contributor to the globalisation of the world’s economy. This increasing reliance requires these networks to have high resilience; however, previous events show that they can be susceptible to natural hazards. We assess two strategies to improve the resilience of air traffic networks and show an adaptive reconfiguration strategy is superior to a permanent re-routing solution. We find that, if traffic networks have fixed air routes, the geographical location of airports leaves them vulnerable to spatial hazard.

Statistical analysis of earthquakes after the 1999 MW 7.7 Chi-Chi, Taiwan, earthquake based on a modified Reasenberg–Jones model

We investigated the temporal–spatial hazard of the earthquakes after the 1999 September 21 MW=7.7 Chi-Chi shock in a continental region of Taiwan. The Reasenberg–Jones (RJ) model (Reasenberg and Jones, 1989, 1994) that combines the frequency-magnitude distribution (Gutenberg and Richter, 1944) and time-decaying occurrence rate (Utsu et al., 1995) is conventionally employed for assessing the earthquake hazard after a large shock. However, it is found that the b values in the frequency-magnitude distribution of the earthquakes in the study region dramatically decreased from background values after the Chi-Chi shock, and then gradually increased up. The observation of a time-dependent frequency-magnitude distribution motivated us to propose a modified RJ model (MRJ) to assess the earthquake hazard. To see how the models perform on assessing short-term earthquake hazard, the RJ and MRJ models were separately used to sequentially forecast earthquakes in the study region. To depict the potential rupture area for future earthquakes, we further constructed relative hazard (RH) maps based on the two models. The Receiver Operating Characteristics (ROC) curves (Swets, 1988) finally demonstrated that the RH map based on the MRJ model was, in general, superior to the one based on the original RJ model for exploring the spatial hazard of earthquakes in a short time after the Chi-Chi shock.

A first hazard analysis of the Quaternary Harrat Al-Madinah volcanic field, Saudi Arabia

The northern portion of the 20,000km2 Harrat Rahat basaltic field in NW Saudi Arabia (Harrat Al-Madinah) has hosted some of the most recent volcanic eruptions in the country. Rapid growth of the city of Al-Madinah has spread out onto the lava flows and scoria cones of the Harrat, increasing exposure to any potential renewed volcanism. We present here a first-order probabilistic hazard analysis related to new vent formation and subsequent lava flow from this volcanic field. The 501 visible eruption vent sites were integrated with aeromagnetic survey data (as representative of potential regions of buried volcanic vents) to develop a probability density function for new eruption sites using Gaussian kernel smoothing. This revealed a NNW striking zone of high spatial hazard terminating <10km south of the city. Using the properties of the AD1256 eruption lava flows and the spatial PDF, an analysis of lava hazard was carried out. Assuming a future lava-producing eruption, around 25% of the city of Al-Madinah is exposed to a probability of 0.001 to 0.005 of lava inundation. The temporal eruption recurrence rate is estimated at approximately one vent per 3300years, but the temporal record of the field is so poorly constrained that the lower and upper bounds for the recurrence interval are 13,300yrs and 70yrs, respectively. Applying a Poisson temporal model, this results in a worst-case lava inundation recurrence interval of approximately 14,300years.

Landslide susceptibility assessment by using a neuro-fuzzy model: a case study in the Rupestrian heritage rich area of Matera

Abstract. The complete assessment of landslide susceptibility needs uniformly distributed detailed information on the territory. This information, which is related to the temporal occurrence of landslide phenomena and their causes, is often fragmented and heterogeneous. The present study evaluates the landslide susceptibility map of the Natural Archaeological Park of Matera (Southern Italy) (Sassi and area Rupestrian Churches sites). The assessment of the degree of "spatial hazard" or "susceptibility" was carried out by the spatial prediction regardless of the return time of the events. The evaluation model for the susceptibility presented in this paper is very focused on the use of innovative techniques of artificial intelligence such as Neural Network, Fuzzy Logic and Neuro-fuzzy Network. The method described in this paper is a novel technique based on a neuro-fuzzy system. It is able to train data like neural network and it is able to shape and control uncertain and complex systems like a fuzzy system. This methodology allows us to derive susceptibility maps of the study area. These data are obtained from thematic maps representing the parameters responsible for the instability of the slopes. The parameters used in the analysis are: plan curvature, elevation (DEM), angle and aspect of the slope, lithology, fracture density, kinematic hazard index of planar and wedge sliding and toppling. Moreover, this method is characterized by the network training which uses a training matrix, consisting of input and output training data, which determine the landslide susceptibility. The neuro-fuzzy method was integrated to a sensitivity analysis in order to overcome the uncertainty linked to the used membership functions. The method was compared to the landslide inventory map and was validated by applying three methods: a ROC (Receiver Operating Characteristic) analysis, a confusion matrix and a SCAI method. The developed neuro-fuzzy method showed a good performance in the determination of the landslide susceptibility map.

Daily Variation in Natural Disaster Casualties: Information Flows, Safety, and Opportunity Costs in Tornado Versus Hurricane Strikes

Casualties from natural disasters may depend on the day of the week they strike. With data from the Spatial Hazard Events and Losses Database for the United States (SHELDUS), daily variation in hurricane and tornado casualties from 5,043 tornado and 2,455 hurricane time/place events is analyzed. Hurricane forecasts provide at-risk populations with considerable lead time. Such lead time allows strategic behavior in choosing protective measures under hurricane threat; opportunity costs in terms of lost income are higher during weekdays than during weekends. On the other hand, the lead time provided by tornadoes is near zero; hence tornados generate no opportunity costs. Tornado casualties are related to risk information flows, which are higher during workdays than during leisure periods, and are related to sheltering-in-place opportunities, which are better in permanent buildings like businesses and schools. Consistent with theoretical expectations, random effects negative binomial regression results indicate that tornado events occurring on the workdays of Monday through Thursday are significantly less lethal than tornados that occur on weekends. In direct contrast, and also consistent with theory, the expected count of hurricane casualties increases significantly with weekday occurrences. The policy implications of observed daily variation in tornado and hurricane events are considered.

Spatial Scale and Hazard Perception: An Exploratory Analysis

This study tests the relationship between spatial scale and hazard perception, accounting for selected sociodemographic and property-related factors. Results reveal significant relationships between spatial scale and wildfire hazard perceptions of survey respondents from Arizona's White Mountains. Hazard perception increased across four ascending spatial scalar levels (from home structure to community levels). Relationships between two (of eight) variables (property landscape hazard exposure, ecological knowledge) and hazard perception were significant when ignoring spatial scale; when accounting for spatial scale, however, significant relationships registered at specific levels for seven variables (home ignitability, property landscape hazard exposure, mitigation, property value, housing tenure, full-time/part-time residency, ecological knowledge). Residents with lower (vs. higher) home ignitability, residents of higher (vs. lower) value properties, and owner-occupants (vs. renters) had significantly lower hazard perceptions at the home structure level and higher hazard perceptions at the community level. Findings are novel to risk perception research and have important implications.

Separating spatial search and efficiency rates as components of predation risk

Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk--the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)--imposed by wolves (Canis lupus) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator-prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk.

Tier-based approaches for landslide susceptibility assessment in Europe

In the framework of the European Soil Thematic Strategy and the associated proposal of a Framework Directive on the protection and sustainable use of soil, landslides were recognised as a soil threat requiring specific strategies for priority area identification, spatial hazard assessment and management. This contribution outlines the general specifications for nested, Tier-based geographical landslide zonings at small spatial scales to identify priority areas susceptible to landslides (Tier 1) and to perform quantitative susceptibility evaluations within these (Tier 2). A heuristic, synoptic-scale Tier 1 assessment exploiting a reduced set of geoenvironmental factors derived from common pan-European data sources is proposed for the European Union and adjacent countries. Evaluation of the susceptibility estimate with national-level landslide inventory data suggests that a zonation of Europe according to, e.g. morphology and climate, and performing separate susceptibility assessments per zone could give more reliable results. To improve the Tier 1 assessment, a geomorphological terrain zoning and landslide typology differentiation are then applied for France. A multivariate landslide susceptibility assessment using additional information on landslide conditioning and triggering factors, together with a historical catalogue of landslides, is proposed for Tier 2 analysis. An approach is tested for priority areas in Italy using small administrative mapping units, allowing for relating socioeconomic census data with landslide susceptibility, which is mandatory for decision making regarding the adoption of landslide prevention and mitigation measures. The paper concludes with recommendations on further work to harmonise European landslide susceptibility assessments in the context of the European Soil Thematic Strategy.

The American Way of Land Use

This article examines the ability of proportional hazard models to evaluate changes in land use through time. There are three specific objectives: (a) to review previous research on the complexity of urbanization and explain how the spatial hazard framework accommodates that complexity; (b); to estimate a series of spatial hazard models characterizing land use in the twenty-five highest growth core-based statistical areas (CBSAs) of the United States in 1990, 2000, and 2006; and (c) to use the estimation results to track land use change region-by-region over the 16-year time frame. Overall, the analysis reveals that the spatial hazard framework offers a highly effective means of describing land use change. Along the way, it also illustrates that the classic model of urbanization continues to hold in an evermore-complex world—albeit, in an explicitly uncertain and inherently probabilistic manner.

Spatial and temporal controls on pyroclastic flow hazard at Arenal volcano, Costa Rica

Pyroclastic flows represent the greatest volcanic hazard at Arenal volcano, Costa Rica, due to their recurrence, unpredictability, potential run outs, high velocities and short emplacement times. The main pyroclastic flow events occurring at Arenal during the present period of eruptive activity have been characterized and simulated using the geophysical flow model TITAN2D. The simulations performed, coupled with analyses of the evolution of Arenal concerning the topographic and morphological development of the volcanic edifice and the eruptive activity; provide insight into various temporal and spatial patterns of pyroclastic flow hazard. Increased pyroclastic flow frequency is shown to be related to the vertical growth rate of the active crater. The topographic evolution of the volcanic edifice and of the morphology of the lava field explain several observed spatial hazard patterns relating to flow directionality and run-out, and lava effusion rates are shown to be related to pyroclastic flow magnitude and volume. Identified patterns highlight the dynamism of pyroclastic flow hazard at Arenal, and its close relationship to the evolution of the volcanic edifice and of the eruptive activity. The simulations performed also draw attention to the sensitivity of pyroclastic flow emplacement to topographic features and to topographic change, highlighting the importance of up to date and accurate representations of the topography (DEMs) of the volcano for related hazard assessments.

Guest Editors’ Introduction to the Special Issue on Family Business

This special issue of the Journal of Family and Economic Issues focuses on the operation of family businesses and their response to environmental conditions of adversity and change, as well as family relationships such as daughter succession, and intermingling of family and business resources. The seven papers reflect the breadth of family business firms operating around the world. They represent a variety of methodologies, modes of analysis, and theoretical models for examining the family firm. The data were collected from divergent sources ranging from case studies to the use of national samples of family firms. Each paper contributes to a more rich understanding of the family business research stream. The lead paper for this special issue by Yilmazer and Schrank uses systems theory to explain the financial interaction between small businesses and owning households. The authors merge literatures on financial bootstrapping and intermingling of small family businesses to provide a holistic understanding of business and household finances. In this critical review the authors discuss successful financing of a small business when owned by a household member. Key conclusions include that the health of the household affects the business, and that the use of owner resources is beneficial for family firms, but not advantageous for households. Pushkarskaya and Marshall’s research investigates a sample of rural households in Kentucky comprised of different family-farm systems (single females, single males, older farm couples, younger farm couples, married older farmers living with younger family members, and married younger farmers with children) to study the economic impact on business decisions following the tobacco buyout. The authors use both the Sustainable Family Business Model and Agricultural Household Model to analyze family-farm decision processes. The authors found the Sustainable Family Business Model to be a better predictor of family-farm adaptation to change from a current mode of operation to a different operational choice strategy. Analysis of correlations between family and farm business decision components aided in differentiating the effectiveness of alternative choice strategy models for farm families. The paper by Distelburg and Blow uses a dual General Systems Theory and Eco-systems perspective to explain that family businesses function better when they identify the value orientation of their business and align their resources towards these values. The author collected data from 11 family businesses and compared their responses with a national sample from the American Family Business Survey (AFBS). This paper also analyzed value systems in relation to family-first family businesses and business-first family businesses. Findings reveal that individuals in a family business are more satisfied with their business when personal values are consistent with the values set for the business. Stafford et al emphasize the importance of resources that move between the family and the firm during times of change. In their paper, the authors used National Family Business Panel data and Spatial Hazard Events and Losses Data for the U.S. to identify factors influencing family L. S. Niehm (&) Department of Apparel, Educational Studies, and Hospitality Management, Iowa State University, 1066 Le Baron Hall, Ames, IA 50011-1120, USA e-mail: niehmlin@iastate.edu

Factors Associated with Long-Term Survival of Family Businesses: Duration Analysis

This study identified factors influencing family business survival using National Family Business Panel and Spatial Hazard Events and Losses data. Sustainable Family Business Theory guided the use of a parametric duration model of long-term survival. Community characteristics, family achievements, family processes during change, business and owner characteristics, and business processes during stability affected long-term survival. Economic vulnerability of rural counties, family income from business, hiring temporary help, business size, viewing business as a way of life, and owner experience were associated with increased duration of business survival. Being home-based, a female owner, and customer-focused were associated with decreased duration of survival. Some family processes and achievements increased the duration of business survival; none decreased it.

Spatio-temporal hazard estimation in the Auckland Volcanic Field, New Zealand, with a new event-order model

The Auckland Volcanic Field (AVF) with 49 eruptive centres in the last c. 250 ka presents many challenges to our understanding of distributed volcanic field construction and evolution. We re-examine the age constraints within the AVF and perform a correlation exercise matching the well-dated record of tephras from cores distributed throughout the field to the most likely source volcanoes, using thickness and location information and a simple attenuation model. Combining this augmented age information with known stratigraphic constraints, we produce a new age-order algorithm for the field, with errors incorporated using a Monte Carlo procedure. Analysis of the new age model discounts earlier appreciations of spatio-temporal clustering in the AVF. Instead the spatial and temporal aspects appear independent; hence the location of the last eruption provides no information about the next location. The temporal hazard intensity in the field has been highly variable, with over 63% of its centres formed in a high-intensity period between 40 and 20 ka. Another, smaller, high-intensity period may have occurred at the field onset, while the latest event, at 504 ± 5 years B.P., erupted 50% of the entire field’s volume. This emphasises the lack of steady-state behaviour that characterises the AVF, which may also be the case in longer-lived fields with a lower dating resolution. Spatial hazard intensity in the AVF under the new age model shows a strong NE-SW structural control of volcanism that may reflect deep-seated crustal or subduction zone processes and matches the orientation of the Taupo Volcanic Zone to the south.

Assessment of ground subsidence using GIS and the weights-of-evidence model

The weights-of-evidence model, one of the Bayesian probability models was applied in evaluating a ground subsidence spatial hazard near abandoned underground coal mines (AUCMs) at Magyori area, Samcheok City in Korea using GIS. Using ground subsidence location and a spatial database containing information such as mining tunnel, borehole, topography, geology, and land use, the weights-of-evidence model was applied to calculate each relevant factor's rating for the Magyori area in Korea. Seven major factors controlling or related to ground subsidence were determined from the probability analysis of the existing ground subsidence area; depth of drift and distance from drift from the mining tunnel map, slope gradient obtained from the topographical map, ground water level and permeability from borehole data, geology and land use. Tests of conditional independence were performed for the selection of factors, allowing 6 combinations of factors to be analyzed. For the analysis of mapping ground subsidence spatial hazard, the contrast values, W + and W −, of each factor's rating were overlaid spatially. The results of the analysis were validated using receiver operating characteristic (ROC) with the previous ground subsidence locations. In the case of all factor used, the area under the ROC curve (AUC) showed 0.9667, which corresponds to an accuracy of 96.67%. In the case of the combinations, the case of distance from drift, depth of ground water and land use used, showed the 90.71% (AUC: 0.9071) accuracy which is the best result produced in this analysis. The results can be used for hazard prevention and land-use planning near AUCM areas.

Coming undone: A spatial hazard analysis of urban form in American metropolitan areas

AbstractThis paper explores the viability of using proportional hazard models to study spatial point patterns generated by urbanisation. The analysis demonstrates that the ‘spatial hazard’ framework is not only viable for studying urban form, but is extremely promising: the models do an excellent job of characterizing very different patterns of development, and they lend themselves directly to the kind of probative analysis needed to guide urban and regional policy. Compared to more traditional approaches to characterizing urban form – namely, density gradients – hazard models rest on a probabilistic worldview, and, so, they portray the built environment as a froth of stochastic transitions through which urban form unfolds in an irregular fashion until it at last comes undone. Several general conclusions and directions for future research follow from these findings.ResumenEste artículo explora la viabilidad del uso de modelos de riesgo proporcional para estudiar patrones de puntos espaciales generados por la urbanización. El análisis demuestra que el marco de “riesgo espacial” no es solo viable para el estudio de la forma urbana, sino que es extremadamente prometedor: los modelos hacen un trabajo excelente en caracterizar patrones de desarrollo muy diferentes, y se prestan directamente al tipo de análisis probatorio requerido para orientar las políticas urbanas y regionales. En comparación con los enfoques más tradicionales para caracterizar la forma urbana – es decir, gradientes de densidad – los modelos de riesgo se basan en una visión probabilística del mundo y, por tanto, representan el medio construido como una efervescencia de transiciones estocásticas a través de las cuales se despliega la forma urbana de manera irregular hasta que al final se despliega. A estos resultados le siguen varias conclusiones generales y orientación para futuras investigaciones.

When Do Losses Count?

Current global and national databases that monitor losses from natural hazards suffer from a number of limitations, which in turn lead to misinterpretation and fallacies concerning the “truthfulness” of hazard loss data. These biases often go undetected by end users and are generally a product of the type of information stored in loss databases and how they are constructed. This paper highlights some common shortcomings and root causes for data misinterpretation by asking what biases are present in existing databases and how these then manifest themselves in actual loss figures. For illustrative purposes, four widely used, nonproprietary, Web-based hazard databases are examined: the international Emergency Events Database (EM-DAT), the international Natural Hazards Assessment Network (NATHAN), the Spatial Hazard Events and Losses Database for the United States (SHELDUS), and the National Weather Service's Storm Events. We identify six general biases: hazard bias, temporal bias, threshold bias, accounting bias, geographic bias, and systemic bias. To achieve resilient and sustainable communities, we need systematic and comprehensive inventories at the national as well as international level, and data that are temporally and geographically comparable.

Spatial equity and transportation hazard along cross‐border trade corridors: The case of Ambos Nogales

Using a spatial perspective, this article explores the equity dimension of the North American Free Trade Agreement (NAFTA) in Nogales, Sonora and Nogales, Arizona, two of the U.S.‐Mexico border communities most impacted by trade after the implementation of the agreement in 1994. Ambos Nogales (Both Nogales) is a major hub within the cross‐border transportation corridor connecting northwestern Mexico with the United States and Canada and both cities are subject to intense trade‐related traffic, including the movement of hazardous materials and toxic waste generated by export‐oriented industries in Mexico. As a first step in this analysis, we classify and map residential areas in Ambos Nogales applying an index of socio‐environmental vulnerability. We then define the boundaries of existing hazard zones and their overlay with these areas in both cities. Finally, we contrast residential areas within the hazard zones with those outside to probe for patterns of social inequity both locally and across the border.

다기준 의사결정기법을 이용한 공간위험 순위산정

본 연구에서는 도시화로 인해 왜곡된 물순환을 치수, 이수, 수질관리 등의 측면에서 건전화시키기 위해 지속가능한 유역통합관리 계획을 수립하기 위한 10단계의 절차와 적용방법을 개발하여 제시하였으며 이 중 Step 2에 해당하는 문제점 도출 및 우선순위 결정 단계를 수행하였다. 유역의 잠재적인 위험도를 나타내는 홍수피해잠재능(PFD), 건천잠재능(PSD), 수질오염잠재능(PWQD), 유역평가지수(WEI)를 산정하기 위해 다기준 의사결정기법과 지속가능성평가지수 개념을 사용하였다. 사용된 다기준 의사결정 기법들은 복합계획법, 타협계획법, Regime, ELECTRE II, EVAMIX 방법이며 자료의 가용성과 목적(예비타당성, 타당성)에 따라 다르게 사용될 수 있다. This study developed a ten-step procedure of integrated watershed management (IWM) for sustainability to rehabilitate the distorted hydrologic cycle and identified spatial hazard ranking(step 2). Spatial hazard indices, Potential flood damage (PFD), potential streamflow depletion (PSD), potential water quality deterioration (PWQD), and watershed evaluation index (WEI) were developed using multi-criteria decision making (MCDM) techniques and sustainability evaluation concept(pressure-state-response model). The used MCDM techniques are composite programming, compromise programing, Regime method, and EVAMIX approach which are classified by data availability and objectives (prefeasibility and feasibility).

Spatial Data Management and Analysis System for Flood Hazard Mitigation of Poyang Lake Watershed, China

Flood hazard Prevention and mitigation of Poyang Lake watershed is an emergent environmental problem because Poyang Lake watershed is one of the regions exposed most frequently to flood hazard in China. In order to meet the need of disaster reduction decision making of Poyang Lake watershed, Spatial Data Management and Analysis System of China Land Territory (not include islands in South Sea of China)for Flood Hazard Mitigation(short for SMAS-FHM) has been established making use of the methodology of spatial database technology based on Oracle9i&ArcSDE9. This paper, probes into designing and implementation of multi-resources and scales massive spatial database management system about flood hazard, and integral management between hazard thematic data and spatial data. Especially, a bitmap index adapted to primal TM/ETM+ image has been put forwards and realized to accelerate data search in the spatial database, which is turned out to be efficient and effective. Based on carrying out experiment, this paper has been also researched the key issues, including massive spatial data and flood hazard thematic data organization and storage, spatial index creating, spatial data searching, and flood hazard analysis models realizing and their effective organizing, such as flooding areas computing, 3-dimension flooding simulation, refuge location selection, refugee evacuation path analysis and relief material dispensing. Finally, important applications of SMAS-FHM in flood hazard mitigation have been also discussed for Poyang Lake watershed.

A spatial hazard model for cluster detection on continuous indicators of disease: application to somatic cell score

Methods for spatial cluster detection dealing with diseases quantified by continuous variables are few, whereas several diseases are better approached by continuous indicators. For example, subclinical mastitis of the dairy cow is evaluated using a continuous marker of udder inflammation, the somatic cell score (SCS). Consequently, this study proposed to analyze spatialized risk and cluster components of herd SCS through a new method based on a spatial hazard model. The dataset included annual SCS for 34 142 French dairy herds for the year 2000, and important SCS risk factors: mean parity, percentage of winter and spring calvings, and herd size. The model allowed the simultaneous estimation of the effects of known risk factors and of potential spatial clusters on SCS, and the mapping of the estimated clusters and their range. Mean parity and winter and spring calvings were significantly associated with subclinical mastitis risk. The model with the presence of 3 clusters was highly significant, and the 3 clusters were attractive, i.e. closeness to cluster center increased the occurrence of high SCS. The three localizations were the following: close to the city of Troyes in the northeast of France; around the city of Limoges in the center-west; and in the southwest close to the city of Tarbes. The semi-parametric method based on spatial hazard modeling applies to continuous variables, and takes account of both risk factors and potential heterogeneity of the background population. This tool allows a quantitative detection but assumes a spatially specified form for clusters.