Abstract
| Original language | English (US) |
|---|---|
| Pages (from-to) | 100-114 |
| Number of pages | 15 |
| Journal | Civil Engineering and Environmental Systems |
| Volume | 36 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 1 2019 |
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Keywords
- big data analytics
- Hazard management
- spatial capability approach
Cite this
Using opportunities in big data analytics to more accurately predict societal consequences of natural disasters. / Boakye, Jessica; Gardoni, Paolo; Murphy, Colleen.
In: Civil Engineering and Environmental Systems, Vol. 36, No. 1, 01.03.2019, p. 100-114.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Using opportunities in big data analytics to more accurately predict societal consequences of natural disasters.
AU - Boakye, Jessica
AU - Gardoni, Paolo
AU - Murphy, Colleen
PY - 2019/3/1
Y1 - 2019/3/1
N2 - The availability of data sources has greatly increased due to advances in technology and data sharing. With these new data sources and significantly larger volume of data, engineers have been presented with a unique opportunity to create more realistic and informative models that can be used in real world applications. This paper presents a probabilistic framework for using big data to assess and predict the well-being of individuals before and in the aftermath of a hazard. Data are used to inform a Capability Approach (CA) where capabilities are defined as important dimensions of well-being reflecting what individuals have a genuine opportunity to do or become. The paper also addresses three of the grand challenges presented by big data: privacy, source validity, and accuracy. As an example, the probabilistic framework is used to study the ability of households in a coastal community to be sheltered in the aftermath of a hypothetical earthquake.
AB - The availability of data sources has greatly increased due to advances in technology and data sharing. With these new data sources and significantly larger volume of data, engineers have been presented with a unique opportunity to create more realistic and informative models that can be used in real world applications. This paper presents a probabilistic framework for using big data to assess and predict the well-being of individuals before and in the aftermath of a hazard. Data are used to inform a Capability Approach (CA) where capabilities are defined as important dimensions of well-being reflecting what individuals have a genuine opportunity to do or become. The paper also addresses three of the grand challenges presented by big data: privacy, source validity, and accuracy. As an example, the probabilistic framework is used to study the ability of households in a coastal community to be sheltered in the aftermath of a hypothetical earthquake.
KW - big data analytics
KW - Hazard management
KW - spatial capability approach
U2 - 10.1080/10286608.2019.1615480
DO - 10.1080/10286608.2019.1615480
M3 - Article
VL - 36
SP - 100
EP - 114
JO - Civil Engineering and Environmental Systems
JF - Civil Engineering and Environmental Systems
SN - 1028-6608
IS - 1
ER -