Spatial Pattern of Socio-economic Landslide Vulnerability and its ...

paddy field. Agricultural activity was dominant activity in the hilly area. Almost 60% of the
respondents in the hilly area worked in agricultural sector.
The second type of settlement pattern was clustered linear village settlement around road. It was
usually characterized by engineered-semi engineered traditional brick with reinforced concrete
column. Most of them were working in service sector and categorized as medium to high household
income. They were mostly educated people and had more capability to cope with disaster. Besides
of livestock as a saving system, they also saved their money in the bank. This social behavior was
totally different with the people living in the hilly and remote area that had livestock only for their
saving. This type of settlement pattern was concentrated in the western part and south-eastern part
of Kayangan Catchment which were dominated by low topography. This place can be considered as
a central economic, education, and local government activity. Those were also classified as low to
medium socio-economic vulnerability level. Both spatial settlement patterns were illustrated in
Figure 5.
5. CONCLUSION
Spatial pattern analysis had play important role to analyze socio-economic vulnerability in the rural area.
Classified as a rural area, Kayangan Catchment is less experienced with agricultural modernization,
industrialization and deindustrialization, and commodification of rural landscapes. Thus, it reflects the
societal character of rural behavior including social structure and culture. Since the nature of people, social
structure and culture of Kayangan Catchment were less influenced by the development of technology and
modernization, the natural feature would more dominantly influence the socio-economic vulnerability in
Kayangan Catchment. Determining environmental factors influencing socio-economic vulnerability was very
helpful to predict spatial distribution of socio-economic vulnerability through fuzzy logic technique. Fuzzy
membership function is generated by relating map classes of environmental variable to membership value.
The fuzzy operator Or, Sum and high gamma value were successfully applied to predict spatial distribution
of socio-economic vulnerability level. The result coincided with the economic, social and ecological
dimensions of livelihood in Kayangan Catchment.
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