Planning Resilient and Sustainable Cities: Identifying and Targeting Social Vulnerability to Climate Change

Yi, Ge; Dou, Wenbin; Liu, Ning

doi:10.3390/su9081394

Cited by 26 publications

(29 citation statements)

References 58 publications

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“…Cities are livelihood and business centers catering to tens of millions of people. Urban ecosystems as a result are vulnerable to climate change impacts [5][6][7] and are in turn also capable of modifying its climate [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Land-Air Interactions over Urban-Rural Transects Using Satellite Observations: Analysis over Delhi, India from 1991–2016

2017

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Abstract:Over the past four decades Delhi, India, has witnessed rapid urbanization and change in land use land cover (LULC) pattern, with most of the cultivable areas and wasteland being converted into built-up areas. Presently around 40% land is under built-up area, a drastic rise of 30% from 1977. The effect of changing LULC, at a local scale, on various variables-land surface temperature (LST), normalized difference vegetation index (NDVI), emissivity, albedo, evaporation, Bowen ratio, and planetary boundary layer (PBL) height, from 1991-2016, is investigated. To assess the spatio-temporal dynamics of land-air interactions, we select two different 100 km transects covering the NE-SW and NW-SE expanse of Delhi and its adjoining areas. High NDVI and emissivity is found for regions with green cover and drastic reduction is noted in built-up area clusters. In both of the transects, land surface variations manifest itself in patterns of LST variation. Parametric and non-parametric correlations are able to statistically establish the land-air interactions in the city. NDVI, an indirect indicator for LULC classes, significantly helps in understanding the modifications in LST and ultimately air temperature. Significant, strong positive relationships exist between skin temperature and evaporation, skin temperature and PBL height, and PBL height and evaporation, providing insights into the meteorological changes that are associated with urbanization.

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Section: Introductionmentioning

confidence: 99%

Land-Air Interactions over Urban-Rural Transects Using Satellite Observations: Analysis over Delhi, India from 1991–2016

2017

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“…The study area ( Figure 1) consisted of 292 county-level units, including counties, county-level cities, and city districts, which are in the third level of Chinese administrative hierarchy [48]. Hong Kong, Macao, and Taiwan were excluded because of their distinct political and economic environment.…”

Section: Study Areamentioning

confidence: 99%

“…For example, 345 tropical cyclones hit the Chinese coastal zone between 1961 and 2008 [65], posing a great threat to the safety of people's lives and property. China Statistical Yearbook 2011 indicates that the coastal region contributes approximately 18% of the total population and 35% of the national GDP compared with nearly 4% occupation of land area [47,48]. The developed but highly vulnerable area can be effectively managed on the basis of the social vulnerability measurement to combat natural disaster risks, which was the purpose of this case study.…”

Section: Study Areamentioning

confidence: 99%

Spatially Explicit Assessment of Social Vulnerability in Coastal China

et al. 2019

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Social vulnerability assessment has been recognized as a reliable and effective measure for informing coastal hazard management. Although significant advances have been made in the study of social vulnerability for over two decades, China's social vulnerability profiles are mainly based on administrative unit. Consequently, no detailed distribution is provided, and the capability to diagnose human risks is hindered. In this study, we established a social vulnerability index (SoVI) in 2000 and 2010 at a spatial resolution of 250 m for China's coastal zone by combining the potential exposure index (PEI) and social resilience index (SRI). The PEI with a 250 m resolution was obtained by fitting the census data and multisource remote sensing data in random forest model. The county-level SRI was evaluated through principal component analysis based on 33 socioeconomic variables. For identifying the spatiotemporal change, we used global and local Moran's I to map clusters of SoVI and its percent change in the decade. The results suggest the following: (1) Counties in the Yangtze River Delta, Pearl River Delta, and eastern Guangzhou, except several small hot spots, exhibited the most vulnerability, especially in urban areas, whereas those in Hainan and southern Liaoning presented the least vulnerability. (2) Notable increases were emphasized in Tianjin, Yangtze River Delta, and Pearl River Delta. The spatiotemporal variation and heterogeneity in social vulnerability obtained through this analysis will provide a scientific basis to decision-makers to focus risk mitigation effort.

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“…The Exposure-Sensitivity-Resilience framework describes the complexity and interactions involved in vulnerability analysis. In this model, vulnerability emerges in a specific place, whereas, it is influenced by a human-environment system at broader scales such as regional and global levels [20,37]. The BBC framework indicates that vulnerability is a dynamic process and consists of two elements: exposed and vulnerable elements, and coping capacity.…”

Section: Literature Review: Conceptual Basis and Evolution Of Vulneramentioning

confidence: 99%

“…As one important aspect of vulnerability, social vulnerability refers to the predisposition and inner state of individuals, organizations, or societies that affect the way they withstand adverse impacts from disruptive events such as natural hazards, climate change, or other dangerous incidences [18][19][20]. In essence, social vulnerability is a by-product of social stratification and social inequalities among different communities and different places from the built environment [21][22][23].…”

Section: Literature Review: Conceptual Basis and Evolution Of Vulneramentioning

confidence: 99%

A New Framework for Understanding Urban Social Vulnerability from a Network Perspective

Dou

Zhang

2017

Sustainability

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Rapid urbanization in China has strengthened the connection and cooperation among cities and has also led urban residents to be more vulnerable in adverse environmental conditions. Vulnerability research has been an important foundation in urban risk management. To make cities safe and resilient, it is also necessary to integrate the connection among cities into a vulnerability assessment. Therefore, this paper proposed a new conceptual framework for urban social vulnerability assessment based on network theory, where a new dimension of social vulnerability (connectivity) was added into the framework. Using attribute data, the traditional social vulnerability index of a city (SVI node ) was calculated via the projection pursuit cluster (PPC) model. With the relational data retrieved from the Baidu search index, a new dimension (connectivity) of social vulnerability (SVI connectivity ) was evaluated. Finally, an integrated social vulnerability index (SVI urban ) was measured combined with SVI node and SVI connectivity . This method was applied in the Yangtze River Delta region of China, where the top three high values of SVI node belonged to the cities of Taizhou (Z), Jiaxing, and Huzhou. The three lowest cities were Hangzhou, Nanjing, and Shanghai. For SVI urban , the social vulnerability of cities in different hierarchies behaved differently. For Hierarchies 2 and 3, when compared to SVI node , the SVI urban was significantly reduced. However, the variation between SVI node and SVI urban in Hierarchy 4 was slight. Furthermore, an increase for the city of Taizhou (J) in its social vulnerability was achieved after connecting to the network. Huzhou, in Hierarchy 5, increased its social vulnerability the most when adding connectivity in the social vulnerability assessment. Based on the results of our case study, a conclusion was drawn that network connectivity had an influence on social vulnerability. However, when connectivity was strong enough, it could help cities to mitigate their traditional social vulnerability, whereas a loose connection in the network aggregated their traditional social vulnerability. Hence, the latter should be emphasized in future urban risk management.

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Planning Resilient and Sustainable Cities: Identifying and Targeting Social Vulnerability to Climate Change

Abstract: This research offers a new framework for assessing social vulnerability to climate change.

Cited by 26 publications

References 58 publications

Land-Air Interactions over Urban-Rural Transects Using Satellite Observations: Analysis over Delhi, India from 1991–2016

Land-Air Interactions over Urban-Rural Transects Using Satellite Observations: Analysis over Delhi, India from 1991–2016

Spatially Explicit Assessment of Social Vulnerability in Coastal China

A New Framework for Understanding Urban Social Vulnerability from a Network Perspective

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