Dynamic Model of Displacement

Martin, Stacey S.; Singh, Lisa; Taylor, Ashby B.; Wahedi, L

doi:10.31234/osf.io/mb9zt

Cited by 3 publications

(5 citation statements)

References 52 publications

(62 reference statements)

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“…Assessing the directional effects of vulnerability factors on displacement is complex and context‐specific, as many key variables (e.g. poverty, informal land and housing tenure, irregular migration status) present both a positive and negative effect on the likelihood of being displaced (Esnard et al, 2011; IIED & UNDRR, 2021; Martin et al, 2021). This fact is however not always recognized in relevant work (Thalheimer et al, 2021; UNDRR, 2019a).…”

Section: Limitations Of “Displacement Risk” As “The Risk Of Displacem...mentioning

confidence: 99%

Displacement risk: Unpacking a problematic concept for disaster risk reduction

Guadagno

Yonetani

2022

International Migration

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Abstract“Displacement risk” is increasingly central to global policy discourse on disaster risk reduction (DRR), despite its vague formulation and inconsistent use. Different understandings of displacement, its complex relationship with vulnerability, and its ambiguous role as a necessary survival strategy for people in harm's way that also creates or exacerbates risk, hinder its clear conceptualization. This limits the clarity and value of recommendations to “reduce displacement risk” for DRR. The explicit consideration of two complementary aspects of risk related to displacement could support more comprehensive, actionable discourses: (1) the “risk stemming from displacement”, that is, any negative impact people might experience due to displacement, and (2) the “risk of remaining displaced”, that is, of people being displaced for a long time. Consideration of these aspects would allow to better include protection and durable solution perspectives within DRR, integrate displacement in disaster risk and loss assessments and add value to existing DRR efforts.

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Section: Limitations Of “Displacement Risk” As “The Risk Of Displacem...mentioning

confidence: 99%

Displacement risk: Unpacking a problematic concept for disaster risk reduction

Guadagno

Yonetani

2022

International Migration

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“…A wide range of factors influence which mobility patterns will occur in the context of environmental change, as illustrated in Figure 1: dynamic model of migration (DMM; Martin et al, 2021), which builds on the causal model developed during the Foresight Project on environmental change and migration (Government Office for Science, 2011). It captures macrodrivers, of which environmental ones are only one dimension although they may have an impact upon the others.…”

Section: Causal Factors In the Context Of Environmental Changementioning

confidence: 99%

“…1. 1. For other research on big data and mobility, see Martin et al (2021); Mazzoli et al (2020); Urchs et al (2015); Zagheni et al (2014). …”

mentioning

confidence: 99%

“…. For other research on big data and mobility, seeMartin et al (2021);Mazzoli et al (2020);Urchs et al (2015);Zagheni et al (2014).2. Humanitarian crises are defined as any situation in which there is a widespread threat to life, physical safety, health or basic subsistence that is beyond the coping capacity of individuals and the communities in which they reside.…”

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confidence: 99%

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Environmental change and human mobility: Opportunities and challenges of big data

Martin

Singh

2022

International Migration

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This paper explores the use of big data in understanding population movements in the context of environmental change, with particular attention to publicly available information from social media and newspapers. After discussing causal factors, the paper discusses the benefits and challenges of using big data, and mathematical models that may help capture the complexity of human mobility in the context of environmental change. We conclude that big data can be an important part of a toolkit in discerning drivers of migration and displacement. It is no panacea, however; the paper discusses potential problems in its use, particularly if big data are analysed to prevent people from moving out of harm's way. Therefore, partnerships between computer scientists and subject matter experts and practitioners are essential to ensuring that what is gathered from big data is usable, credible, and protects the privacy and rights of those who may be displaced.

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“…These methods sift through large volumes of data to generate estimates of displacement figures. For instance, Martin et al (2021) developed the Dynamic Model of Displacement (DMD) using machine learning techniques to understand the factors influencing decision-making and the consequences of disaster displacement.…”

Section: Introductionmentioning

confidence: 99%

A new methodology for probabilistic flood displacement risk assessment: the case of Fiji and Vanuatu

Rossi,

Ponserre,

Trasforini

et al. 2024

Front. Clim.

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This paper presents an enhanced probabilistic flood displacement risk assessment methodology. Several techniques have been proposed to estimate the number of people at risk of being displaced triggered due to climatic extremes. Among these methods, the probabilistic approach is promising for its quantitative nature and versatility at different scales. However, it has so far been limited to assessing loss of housing as the sole cause of displacement. The proposed methodology addresses this limitation by considering two additional elements beyond the traditional evaluation of housing loss: the likelihood of losing means of livelihood, directly included in the computation, and the likelihood of losing access to essential services, such as schools and health centers, provided as a factor to increase the propensity to displace. This new methodology is applied to assess flood disaster displacement risk in Fiji and Vanuatu, where climate change, coupled with the vulnerability of exposed assets, poses an existential threat to these Pacific islands, potentially leading to internal and cross-border population movements. Different climate scenarios were considered: current climate conditions (1979–2016 period), medium-term projected climate conditions (2016–2060), and long-term projected climate conditions (2061–2100). The average annual displacement increases in Fiji and Vanuatu by a factor of 3 and 4, respectively, in the projected long-term pessimistic climate scenario compared to current conditions. Depending on the country and climate change scenario, 20 to 40% of these displacements stem from loss of livelihoods as a dominant factor, highlighting the importance of considering this aspect in the vulnerability approach. The outcomes of these scenarios serve as the foundation for implementing displacement risk adaptation and management measures. This novel quantitative methodology holds significant potential for applications in larger domains and even globally.

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Dynamic Model of Displacement

Cited by 3 publications

References 52 publications

Displacement risk: Unpacking a problematic concept for disaster risk reduction

Displacement risk: Unpacking a problematic concept for disaster risk reduction

Environmental change and human mobility: Opportunities and challenges of big data

A new methodology for probabilistic flood displacement risk assessment: the case of Fiji and Vanuatu

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