The parameters for this study included the social component indicators such as population density, and social sensitivity. As building to physical impacts (e.g., houses, public facilities and critical facilities), the term “building construction cost values”, in this study, relates to flood damage, it takes into account both cost damages based the area of building according to the assumed local values.
The secondary data concern the economic and environmental component indicators. The land-use data were extracted from the developed land cover map (with a 50 m resolution) using spatial analysis tools. Vegetation cover was extracted from a land cover data provided by local government.
4.2.3.1 Social vulnerability related database layers
Data is collected from available government, geospatial and satellite data, and observation of statistical databases. In the spatial analysis, research is addressed regarding annual statistical data provided by the government of Makassar City, population information extraction, GIS processing, and vulnerability indicator analysis. It is to deal with population data in 2012 for sub-districts scale for identification and population density, poverty ratio, vulnerable age ratio, gender ratio, and disability ratio. In this study, population data, etc. are created based on the administration boundary of sub-districts, as shown in Figure 4.18. The Jenks natural breaks classification method in GIS is applied to estimate the distribution data in maps. The resulting BNPB score classification of spatial analysis identified the sub-districts most vulnerable areas.
It is found that the urban poor living along the coast and along rivers are among the most vulnerable, as the people live in areas most affected by current flood hazards. Flooding threatens their livelihoods and physical safety, and this compounds their existing social vulnerabilities of low income peoples and lack of access to water which influence to the human health. Finally, through observation data, an analysis was carried out represents the gender ratio, poverty ratio, age ratio and disability ratio shows how vulnerability affects some sub-districts in the Makassar region.
4.2.3.2 Physical vulnerability related database layers
The recent increase in frequency and severity of flooding in the Makassar City has led to a shift in the perception of risk associated with flood hazards. This has extended to the risks posed to importance of buildings that suffer from flooding are particularly concerning for those charged with maintaining such buildings. In this study, building features are created based on the spatial database of the RTRW (Spatial Urban Planning) of the Makassar, as shown in Figure 4.19.
(Urban population density)
(BNBP scoring of urban population density)
Fig. 4.18aRelevant spatial indicator layers for social vulnerability component
(The percentage of poverty)
(BNBP scoring of the percentage of poverty)
Fig. 4.18bRelevant spatial indicator layers for social vulnerability component
(The percentage of ages)
(BNBP scoring of the percentage of ages)
Fig. 4.18cRelevant spatial indicator layers for social vulnerability component
(The percentage of gender)
(BNBP scoring of the percentage of gender)
Fig. 4.18dRelevant spatial indicator layers for social vulnerability component
(The percentage of disability)
(BNBP scoring of the percentage of disability)
Fig. 4.18eRelevant spatial indicator layers for social vulnerability component
Methodology is carried out using the results of the building€s technical and functional analysis which provides guidance for classification of buildings (PU, 2006), as shown in Table 4.9. This occurs through appraisal of vulnerability indicators related to the physical building and their function values.
Table 4.9Building classifications and it estimated local values (PU, 2006)
Building
classifications Weight Building
categories Explanation
Estimated cost values (Rp) per
area (m2)
Houses 40%
Simple Building area less than or equal 70 square meter
1,000,000 ~ 2,500,000 Complex Building area more than 70
square meter
2,500,000 ~ 5,000,000
Public
facilities 30%
Commerce
Building commerce e.q.
markets, shopping malls, restaurants
5, 000,000 ~ 10,000,000 Industry Building industries e.q.
factories
Hospitality Building hospitality e.q.
hotels, motels, inns Tourist
attraction
Building tourist attraction e.q. cinema, swimming pool
Storage Building storage e.q.
warehouse
Laboratory Building for laboratory Worship place
Building for worship places e.q. mosques, churches, temples Offices
Building offices e.q.
governmental offices, banks
Terminal Building terminal e.q.
station bus, airport, sea port Educational
service
Building for educational services e.q. Universities, schools
Health service
Building for educational services e.q. hospital, polyclinic, maternity Culture Culture building e.q.
museums, arts
Sport service Building for sport services e.q. stadium
Memorial Building for cemetery e.q.
monument
Basic public service
Building for basic public services e.q. electricity, water treatment plant, telecommunication, waste management
Critical
facility 30% Defense Building for defenses e.q.
military, polices
10,000,000 ~ 15,000,000
(Building cost values)
(BNPB scoring of the building cost values)
Fig. 4.19Relevant spatial indicator layers for physical vulnerability component
(Productive land)
(BNPB scoring of productive land)
Fig. 4.20aRelevant spatial indicator layers for economic vulnerability component
(Land resource base of agriculture (PDRB))
(BNPB scoring of land resource base)
Fig. 4.20bRelevant spatial indicator layers for economic vulnerability component
(Natural forest)
(BNPB scoring of natural forest)
Fig. 4.21aRelevant spatial indicator layers for environmental vulnerability component
(Mangroves)
(BNPB scoring of mangroves)
Fig. 4.21bRelevant spatial indicator layers for environmental vulnerability component
(Shrubs)
(BNPB scoring of shrubs)
Fig. 4.21cRelevant spatial indicator layers for environmental vulnerability component
4.2.3.3 Economic vulnerability related database layers
In this study, the land-use map in 2012 was developed from the availability of digital topographic maps of 1:50.000 scales provided by the Regional Development Planning Agency of Makassar. Land-use division was determined based on land-use boundary line of the topographic maps. The land-use divisions for 1997 and 2012 were reclassified into 10 categories (Indrayani et al., 2016). By utilizing the developed land-use map, an analysis of land-use values based on 0.25 hectares area size was performed to identify the productive land such as paddy field, garden field, and fishpond. It is also to deal with population data in 2012 for sub-districts scale for identification of land resource base value (PDRB) and agriculture values. The database layers related to the economic vulnerability components are shown inFig. 4.20.
4.2.3.4 Environmental vulnerability related database layers
The vulnerability assessment involved measuring and mapping by neighborhood the susceptibility to floods and an assessment of environmental vulnerability focusing on natural forests, mangroves and shrubs, which play an essential role in minimizing impact to ecology. Relevant spatial indicators were developed using a land cover data, is shown inFig. 4.21.