5.1 D YNAMIC E XPOSURE OF THE P OPULATION
5.1.3 Exposure of People according to Different Socio-economic Status
Further, it is interesting to identify which social groups are actually living in the exposed areas. Since there was no micro level information on the household income or poverty level, data from remote sensing analysis and participatory mapping exercise was used to give a rough picture of the socio‐
economic patterns in the exposed areas. Figure 5‐5 compares the results of socio‐economic classification obtained applying two analytical methods. Using the semantic classification based on the remote sensing analysis, the proportion of exposed population with various socio‐economic levels could be estimated: 2% in high class buildings, 50.1% in middle class buildings, 28.7% in low/middle class buildings, 5.4% in suburb/low class buildings, 13.6% in slums, and 0.2% unclassified rest.
While the remote sensing analysis provides more precise spatial location / coverage of each class and finer classification especially for the low and middle classes, the qualitative analysis by means of participatory mapping exercises with local experts provided additional information such as the location of special groups (fishermen community and households with majority of customary landownership), and identified non‐residential buildings e.g. warehouses, which would have been identified as settlement buildings in remote sensing analysis. Nevertheless, both results point out that in the most exposed areas in the direct vicinity of the coast, there are identifiable spots of people with lower socio‐economic level.
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Figure 5-5 Semantic classification of the settlement areas based on socio-economic characteristics
Source: Remote sensing data and analysis DLR/Last‐Mile and own qualitative analysis based on participatory mapping 2009
The challenges of mobility of various social groups identified above are shown by the data analysis of the UNU‐EHS Household Survey 2008. As shown in the previous analysis (Chapter 5.1), the female population shows a relatively lower mobility (conducting more activities at home or in settlement areas) than the male population, since the female population has a higher proportion of people engaged in non‐working main activities than males. The daily mobility is also associated with the socio‐economic characteristics of people. The Household Survey found out significant correlations that the proportion of the respondents with daily activities outside the house / neighbourhood is lower for the ones with lower household income (Figure 5‐6) and of lower educational level (Figure 5‐7).
Remote sensing analysis Participatory mapping
Fishermen Community (Purus area)
hazards_buffer100
non_residential_wo_mixeduse Customary land
high class middle class
low class/low-middle class suburb/low class slum
rest
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Figure 5-6 Duration (hours per day) spent outside the house zone by household income
Source: own analysis based on UNU‐EHS Household Survey 2008 and spatial data
Figure 5-7 Duration (hours per day) spent outside the house zone by education level
Source: own analysis based on the UNU‐EHS Household Survey 2008 and spatial data
Additionally, a group discussion in the fishermen neighbourhood with low socio‐economic level in the Purus area derived a daily activity pattern of this particular group (see Figure 5‐8). Since the male family members were working during the time of the discussion (noon time), only the female and children family members were available to participate in the exercise. Nevertheless, they could provide information on the daily activities of the other family members.
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<= Rp.400000 Rp.400.001 ‐ 800.000 Rp.800.001‐ 1.600.000 Rp.1.600.000‐ 4.000.000 Rp.4.000.001‐ 10.000.000 Income class
only stay in housezone up to 6 hours up to 12 hours more than 12 hours
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no school No primary school finished
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only stay in housezone up to 6 hours up to 12 hours more than 12 hours
75 Figure 5-8 Daily activities of fishermen families
Source: Own analysis, based on group discussion (PRA) with fishermen wives February 9, 2008 The group discussion also revealed that most activities of the female family members are conducted at home or in the neighbourhood, which was consistent with the quantitative analysis results above.
The workplaces are mostly located in the coastal (exposed) areas. Also the places where they conduct their household activities like shopping for food are close by (still in exposed areas). For educational activities, it was mentioned that for children in primary school, the location of the school facilities was close to the place they live, while for the higher educational levels the locations were more varied. This may also be related to the fact that the schools at lower educational level are more and better spatially distributed, and that the higher the educational level the more varied the choice of location (better quality junior or senior high schools are located further away, whether private or public, etc.). For social activities, it is only occasionally that people travel further away to the eastern part of the city (less exposed areas) to visit extended family on school holidays, special events (weddings, Ramadan celebrations). For travel to areas further than the neighbourhood, the motorcycle is their common means of transport. This qualitative analysis also indicates a similar tendency to the quantitative results above in that households with lower income conduct less activities outside the house or have less mobility. This seems to suggest that people of the lower economic class, especially the female family members, would have rather similar day and night exposure in their settlement areas.