Construction of a Composite Vulnerability Index to Map Peripheralization Risk in Urban and Metropolitan Areas

As cities and poverty continue to grow worldwide, both spatial and a-spatial peripheralization processes expose entire urban and metropolitan areas at risk of degradation, not just traditional peripheries. The main aim of this paper is to propose a methodology for peripheralization risk assessment, according to the general theory of territorial risk, in order to identify priority areas where mitigation actions should be envisaged through urban and territorial planning. Such an approach constitutes the novelty of the work. So, peripheralization risk is defined for the first time, depending on aggregated vulnerability and exposure. Based on a literature review, a set of vulnerability indicators structured in three dimensions is defined in order to construct the composite vulnerability index in the Italian geographical context. Due to the absence of well-established threshold values, an aggregation method based on fuzzy logic is used. The methodology was applied to a conurbation of 16 municipalities in Campania Region (Italy). Obtained results showed that areas most at risk can be both peripheral and central neighborhoods, but also entire municipalities, demonstrating how mitigation actions are needed at different planning levels. Since the necessary input data are ordinarily available in planning processes, the proposed methodology can be transferred to other geographical contexts.

Vulnerability Index Analysis of Bepondi Island as a Reference for Small and Outer Islands Management in Indonesian

Indonesia is an archipelagic country with many small islands as the outer border of the territory. Special attention and development programs are important due to it relates to the improvement of public welfare and national sovereignty. Therefore, the vulnerability study for small and outer islands is urgently conducted as an initial step for regional development programs. This study aims to analyze the vulnerability level of Bepondi Island, West Papua from various threats either directly from nature by biologically, geologically, climate change effect, or anthropological and social-economic. To determine the small and outer island’s vulnerability, composite vulnerability index (CVI) has been applied. Several ecological indexes have been composited were coastal index (CI), Isolation Index (II), Land-used degradation index (LDI), Ecosystem degradation index, and Sea Level Rise Index (SLRI). The results showed that Bepondi Island has CVI calculated for 0.47, which means the island was exposed to medium-high vulnerability. This was caused by the threat from abrasion, potential landslide, and isolation. On the other hand, this island has a fairly high fishery potential. Therefore, mitigation plans to cope with disasters were urgently needed and communication infrastructures must be promptly built as a countermeasure for the island’s isolation problem.

Mapping a Climate Change Vulnerability Index: An Assessment in Agricultural, Geological and Demographic Sectors across the Districts of Karnataka (India)

Climate change is a continuous phenomenon and over hundreds of years, the atmosphere has changed considerably around the world. Karnataka has the second largest drought prone area in the country next only to Rajasthan. Assessment of vulnerability index could play a major role in designing appropriate mitigation and adaptation policies to overcome the impacts of climate change. The vulnerability assessment is an exhaustive procedure determined by a large number of indicators. This study attempted to capture a picture of composite vulnerability index of different districts of Karnataka by considering agronomic, climatic and demographic indicators. The secondary data on climatic, agronomic and demographic factors were collected from various sources for the year 2017-18. The findings of the study as shown that the average vulnerability index for 30 districts is 0.577 and 16 districts placed above the average composite vulnerability index level. Bidar (0.655) is the most vulnerable district followed by Kolar (0.658) and Yadgir (0.638) districts. Shivamogga (0.440), Davanagere (0.486) and Udupi (0.486) districts exhibit the least vulnerability to changing climate. The results suggest that agricultural and climatic indicators are the major factors which influence vulnerability. So special attention should be given to agricultural and climatic sectors to minimize the impacts of climatic change in the most vulnerable districts.

Assessment of India’s Fiscal and External Sector Vulnerability: A Balance Sheet Approach

The article is an attempt to assess India’s fiscal and external sector vulnerability in the context of the deterioration in major macroeconomic indicators in recent years. The balance sheet approach (BSA) developed mainly by the International Monetary Fund (IMF) is applied to analyse episodes of major fiscal, financial and external payment crises in developing countries between the late 1990s to early 2000. The present work assesses the vulnerability in India’s fiscal and external sectors by descriptive and comparative analyses of relevant indicators and developing a composite vulnerability index (CVI) consisting of the indicators under study. Fiscal or external sector vulnerability can also be assessed by how easily or smoothly a government or a nation can finance its budgetary deficit or rollover of debt or the external sector funding needs. The method of financing and management of debt-related liabilities become important in this context. This may get reflected in currency composition, maturity pattern and ownership pattern of liabilities. The CVI score and favourable currency composition, maturity pattern and ownership pattern of liabilities largely helped India reduce both fiscal and external sector liabilities significantly in recent years. JEL Classification: E60, F34, H63

Does social vulnerability for caries predict caries status of children in sub-urban Nigeria?

It is important to identify groups of people vulnerable to a disease condition. Aim: To determine the association between social vulnerability to caries and caries status of children in Ile-Ife, Nigeria. Methods: A composite vulnerability index for caries was developed using data generated for 992 children. Wilks’ Lambda test to verify relationship between vulnerability and its variables. Logistic regression analysis was conducted to determine if the social vulnerability for caries index was a good predictor for caries status. Results: The social vulnerability to caries index could not predict caries status. The study found that sex, age and number of siblings were the significant predictors of caries status in the study population. Females (AOR: 1.63; 95%CI: 1.08 – 2.46; p=0.02) and children with more than two siblings had higher odds of having caries (AOR: 2.61; 95%CI: 1.61 – 4.24; p<0.001) while children below 5 years had lower odds of having caries (AOR: 0.62; 95%CI: 0.39 – 1.00; p=0.05) Conclusions: The social vulnerability index for caries could not predict the caries status of children in the study population. Sensitive tools to identify children with caries in the study population should be developed.

Analisis Kerentanan Pulau-Pulau Kecil di Kecamatan Togean Kabupaten Tojo Una Una Provinsi Sulawesi Tengah (Studi Kasus P. Kukumbi, P. Enam, P. Mogo, P. Kadidiri, P. Pagempa, P. Tongkabo)

This research was conducted in small islands area to Togean District, TojoUna-Una Regency Central Celebes by ecological and sosio-economic approach. Methods those used in this research were vulnerability index, MCDM (multi criteria dimension making) and Geographycal information system (SIG) approach. Data was collected bt participative and explorative approach. Data analysed parameters using vulnerability, assessment method involved vulnerability variable parameters i.e. area characteristic, area degradation, sea level rise, human impact, economic exposure, economic remoteness. The results shows the range ofcomposit vulnerability index for ecological (CVI-Ek) is 0.00-0.77, economic (CVI-En) is 0.00-0.75, and composite vulnerability ecological-economic (CVI-EE) is 0.00-0.76. Enam island (0.76)and tongkabo island (0.66) is rated to high vulnerable (0.67), Mogo Island (0.14), Kukumbi Island (0.12), Pagempa Island (0.09) and Kadidiri Island (0.07), is considerednon vulnerable. MCDM analysis result that is used to determine small island management model in Togean District, shows ecological criteria is most important compared with economy criteria and social criteria. Analysis of SMART technique shows the type small islands sustainability management scenario in Togean District, those are scenario A (adaptation, 0.94) and scenario B ( without adaptation, 0.55).Keywords : small island, composite vulnerability index, sustainability, togean district.