values us<strong>in</strong>g the chi-square method, <strong>and</strong> applied a logarithm transformation to adjust their distribution. ATLAS OF URBAN VULNERABILITY IN SPAIN. METHODOLOGY AND CONTENTS. PAG. 26
DOMAIN 4: URBAN VULNERABILITY SYNTHETIC INDEXES (MULTIPLE CRITERIA CLASSIFICATION) Multiple Criteria classification <strong>of</strong>fers synthetic Indexes <strong>of</strong> Vulnerability compos<strong>in</strong>g different simple <strong>vulnerability</strong> <strong>in</strong>dicators, which <strong>in</strong> our case are 20 +1, grouped <strong>in</strong>to four thematic categories. Multiple Criteria classification is an alternative method to traditional synthetic Indexes obta<strong>in</strong>ed by the def<strong>in</strong>ition <strong>of</strong> scalar type functions that comb<strong>in</strong>e the various <strong>in</strong>dicators <strong>of</strong> <strong>vulnerability</strong> by assign<strong>in</strong>g a proportional weight to each one <strong>of</strong> the <strong>in</strong>dicators 4 . The existence <strong>in</strong> the Atlas <strong>of</strong> 4 thematic categories <strong>of</strong> <strong>vulnerability</strong> <strong>in</strong>dicators, <strong>of</strong>fers the possibility to organise 4 thematic classifications for the partial subsets <strong>of</strong> criteria (Sociodemographic criteria Classification, Socioeconomic criteria Classification, Hous<strong>in</strong>g criteria Classification <strong>and</strong> Subjective perception criteria Classification) <strong>and</strong> a Global criteria Classification, encompass<strong>in</strong>g the 20 <strong>in</strong>dicators <strong>of</strong> <strong>vulnerability</strong> considered. ISVU-SD, Sociodemographic criteria Classification, <strong>in</strong>cludes the set <strong>of</strong> the 5 sociodemographic <strong>in</strong>dicators: (1) Percentage <strong>of</strong> elderly people aged 75 or more, (2) Percentage <strong>of</strong> households with only one person aged 64 or more, (3) Percentage <strong>of</strong> households with only one adult (s<strong>in</strong>gle-parent) <strong>and</strong> a one or more persons under 18 years old, (4) Percentage <strong>of</strong> foreign population, <strong>and</strong> (5) Percentage <strong>of</strong> foreign child population. ISVU-SE, Socioeconomic criteria Classification, <strong>in</strong>cludes a set <strong>of</strong> 5 socioeconomic <strong>in</strong>dicators: (6) Percentage <strong>of</strong> unemployed population. (Basic Indicator <strong>of</strong> Urban Vulnerability), (7) Percentage <strong>of</strong> unemployed young population, (8) Percentage <strong>of</strong> cont<strong>in</strong>gent workers, (9) Percentage <strong>of</strong> workers without qualification, <strong>and</strong> (10) Percentage <strong>of</strong> illiterate (or without basic education) population. (Basic Indicator <strong>of</strong> Urban Vulnerability). ISVU-R, Hous<strong>in</strong>g criteria Classification, <strong>in</strong>cludes the set <strong>of</strong> the 5 residential <strong>in</strong>dicators: (11) Percentage <strong>of</strong> dwell<strong>in</strong>gs with less than 30 m² <strong>of</strong> effective liv<strong>in</strong>g area, (12) Average effective liv<strong>in</strong>g area by <strong>in</strong>habitant (m²), (13) Percentage <strong>of</strong> population <strong>in</strong> dwell<strong>in</strong>gs without toilet or WC. (Basic Indicator <strong>of</strong> Urban Vulnerability), (14) Percentage <strong>of</strong> dwell<strong>in</strong>gs <strong>in</strong> ru<strong>in</strong>ed or deficient build<strong>in</strong>gs, <strong>and</strong> (15) Percentage <strong>of</strong> dwell<strong>in</strong>gs <strong>in</strong> build<strong>in</strong>gs built before 1951. ISVUN-S, Subjective perception criteria Classification, <strong>in</strong>cludes the set <strong>of</strong> the 5 subjective <strong>in</strong>dicators: (16) Percentage <strong>of</strong> population with external noises problems, (17) Percentage <strong>of</strong> population with air pollution problems <strong>in</strong> the neighbourhood, (18) Percentage <strong>of</strong> population with bad transport /communication <strong>in</strong>frastructures problem, (19) Percentage <strong>of</strong> population with lack <strong>of</strong> green open spaces problem, <strong>and</strong> (20) Percentage <strong>of</strong> population with del<strong>in</strong>quency problems <strong>in</strong> the neighbourhood. 4 The problem with this type <strong>of</strong> functions is precisely the subjectivity that exists <strong>in</strong> the assignment <strong>of</strong> "proportional weights" to each <strong>in</strong>dicator. Multiple Criteria classification allows to overcome this problem. ATLAS OF URBAN VULNERABILITY IN SPAIN. METHODOLOGY AND CONTENTS. PAG. 27
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