Social Science Research Needs: Focus on Vulnerable Populations, Forecasting, and Warnings

Phillips, Brenda D.; Morrow, Betty Hearn

doi:10.1061/(asce)1527-6988(2007)8:3(61)

Cited by 147 publications

(100 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This decision process is affected by multiple factors, such as the characteristics of a household [44][45][46][47][48][49][50][51][52], conditions in which they reside (e.g., income, type of house, vehicle ownership, time of day) [49,50,53,54], warning time [55,56], perceived information [57][58][59][60][61][62] and personal risk perception [63][64][65][66][67][68].…”

Section: Hurricane Evacuation Response Ratementioning

confidence: 99%

See 1 more Smart Citation

Optimization of Evacuation Warnings Prior to a Hurricane Disaster

et al. 2017

View full text Add to dashboard Cite

Abstract:The key purpose of this paper is to demonstrate that optimization of evacuation warnings by time period and impacted zone is crucial for efficient evacuation of an area impacted by a hurricane. We assume that people behave in a manner consistent with the warnings they receive. By optimizing the issuance of hurricane evacuation warnings, one can control the number of evacuees at different time intervals to avoid congestion in the process of evacuation. The warning optimization model is applied to a case study of Hurricane Sandy using the study region of Brooklyn. We first develop a model for shelter assignment and then use this outcome to model hurricane evacuation warning optimization, which prescribes an evacuation plan that maximizes the number of evacuees. A significant technical contribution is the development of an iterative greedy heuristic procedure for the nonlinear formulation, which is shown to be optimal for the case of a single evacuation zone with a single evacuee type case, while it does not guarantee optimality for multiple zones under unusual circumstances. A significant applied contribution is the demonstration of an interface of the evacuation warning method with a public transportation scheme to facilitate evacuation of a car-less population. This heuristic we employ can be readily adapted to the case where response rate is a function of evacuation number in prior periods and other variable factors. This element is also explored in the context of our experiment.

show abstract

Section: Hurricane Evacuation Response Ratementioning

confidence: 99%

“…Among the factors, the characteristics of the household show a significant effect on the evacuation decisions [44][45][46][47][48][49][50], including its timing [51,68], destination [28,67] and mode [52]. One reason is that the characteristics of the household are consistently associated with risk perception.…”

Section: Hurricane Evacuation Response Ratementioning

confidence: 99%

Optimization of Evacuation Warnings Prior to a Hurricane Disaster

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Underlying causes of vulnerability to TCs, such as lack of access to resources (or lack of capacity to use resources to secure livelihood), lack of education and training, and fragmentation in the community (Alam & Collins, 2010;Asgary & Halim, 2011;Letson, Mileti, & Lazo, 2007;Phillips & Morrow, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…Though various studies have identified the technical and the residents' response processes to be important in determining the effectiveness of a cyclone early warning system (Brady, 2005;Letson et al, 2007;Phillips & Morrow, 2007), the two processes have not been considered together in the same study when evaluating early warning systems.…”

Section: Introductionmentioning

confidence: 99%

“…For example, the location and the condition of houses, the availability and condition of cyclone shelters, and the availability of road and other transportation facility (Asgary & Halim, 2011;C. E. Haque & Blair, 1992).Underlying causes of vulnerability to TCs, such as lack of access to resources (or lack of capacity to use resources to secure livelihood), lack of education and training, and fragmentation in the community (Alam & Collins, 2010;Asgary & Halim, 2011;Letson, Mileti, & Lazo, 2007;Phillips & Morrow, 2007).Though various studies have identified the technical and the residents' response processes to be important in determining the effectiveness of a cyclone early warning system (Brady, 2005;Letson et al, 2007;Phillips & Morrow, 2007), the two processes have not been considered together in the same study when evaluating early warning systems. …”

mentioning

confidence: 99%

See 1 more Smart Citation

An Informed System Development Approach to Tropical Cyclone Track and Intensity Forecasting

Roy

2016

Linköping Studies in Science and Technology. Dissertations

View full text Add to dashboard Cite

Introduction: Tropical Cyclones (TCs) inflict considerable damage to life and property every year. A major problem is that residents often hesitate to follow evacuation orders when the early warning messages are perceived as inaccurate or uninformative. The root problem is that providing accurate early forecasts can be difficult, especially in countries with less economic and technical means. Aim:The aim of the thesis is to investigate how cyclone early warning systems can be technically improved. This means, first, identifying problems associated with the current cyclone early warning systems, and second, investigating if biologically based Artificial Neural Networks (ANNs) are feasible to solve some of the identified problems.Method: First, for evaluating the efficiency of cyclone early warning systems, Bangladesh was selected as study area, where a questionnaire survey and an in-depth interview were administered. Second, a review of currently operational TC track forecasting techniques was conducted to gain a better understanding of various techniques' prediction performance, data requirements, and computational resource requirements. Third, a technique using biologically based ANNs was developed to produce TC track and intensity forecasts. Systematic testing was used to find optimal values for simulation parameters, such as feature-detector receptive field size, the mixture of unsupervised and supervised learning, and learning rate schedule. Five types of 2D data were used for training. The networks were tested on two types of novel data, to assess their generalization performance. Results:A major problem that is identified in the thesis is that the meteorologists at the Bangladesh Meteorological Department are currently not capable of providing accurate TC forecasts. This is an important contributing factor to residents' reluctance to evacuate. To address this issue, an ANN-based TC track and intensity forecasting technique was developed that can produce early and accurate forecasts, uses freely available satellite images, and does not require extensive computational resources to run. Bidirectional connections, combined supervised and unsupervised learning, and a deep hierarchical structure assists the parallel extraction of useful features from five types of 2D data. The trained networks were tested on two types of novel data: First, tests were performed with novel data covering the end of the lifecycle of trained cyclones; for these test data, the forecasts produced by the networks were correct in 91-100% of the cases. Second, the networks were tested with data of a novel TC; in this case, the networks performed with between 30% and 45% accuracy (for intensity forecasts). Conclusions:The ANN technique developed in this thesis could, with further extensions and up-scaling, using additional types of input images of a greater number of TCs, improve the efficiency of cyclone early warning systems in countries with less economic and technical means. The thesis work also creates opportunities for furthe...

show abstract

Ways to Be Part of the Transformation to Integrated Weather Studies

2017

Weather and Society

View full text Add to dashboard Cite

Social Science Research Needs: Focus on Vulnerable Populations, Forecasting, and Warnings

Cited by 147 publications

References 25 publications

Optimization of Evacuation Warnings Prior to a Hurricane Disaster

Optimization of Evacuation Warnings Prior to a Hurricane Disaster

An Informed System Development Approach to Tropical Cyclone Track and Intensity Forecasting

Ways to Be Part of the Transformation to Integrated Weather Studies

Contact Info

Product

Resources

About