Urban and Regional Planning Review Vol. 3(2016)

Uncontrolled growth in Greater Jakarta has reduced the green area in Jakarta’s neighboring municipalities. Projected population growth and associated growth in housing will cause further loss of green areas. Spatial planning laws in these municipalities and the application of a national target for urban green areas in each city have been implemented in an attempt to mitigate the loss of green areas. However, further loss of green areas since these laws were issued shows that there are underlying problems in their enactment. Tangerang Selatan has been nominated as a new center for residential, service and trading activities, which provides an opportunity for policy change to mitigate the loss of urban green space in peripheral municipalities. This paper aims to mitigate further loss of green areas in Tangerang Selatan by identifying the underlying problems for green area provision in Tangerang Selatan through analysis of the current regulations and their implementation in different types of development.　Findings indicated that achieving sufficient urban green area is a challenge in Tangerang Selatan due to insufficient planning and monitoring capabilities. However, it is found that private sector has the potential for collaboration in green area provision.

Seniors without adequate access to public transportation suffer from a lack of mobility after they stop driving as they mostly depend on urban structure, denoted by population distribution. This study estimates past and future numbers and distribution of seniors facing a mobility crisis by applying spatial analysis to the greater Tokyo region, which could be severely impacted by this issue in the near future. In addition, we explore how the past migration contributes to the number and distribution of seniors with poor access to transit by cohort analysis. The data include the national census from 1980 to 2010, future population projections up to 2040, railway station locations, and bus routes. In conclusion, we have succeeded to estimate the number and distribution of seniors with poor access to transit in the subregional level. The total number increased from 324,702 in 1980 to 758,336 in 2010 and can reach 1,394,074 in 2040. In addition, the rates of the seniors without train access increased from 43% in 1980 to 46% in 2010 and can reach 49% in 2040, whereas those without rail or bus access were 15% in 1980, 10% in 2010, and can reach 12% in 2040. Moreover, the cohort analysis indicates that the number and distribution of seniors without access to transit largely depend on the migration of those who bought their house with poor access to transit at around 30 years and the gradual migration of those who bought their house with poor access to transit after that age.

A wide variety of microdata offer great potential for the advancement of small area demographic estimation. This study proposes a method to estimate residents’ attributes at the street block level using survey microdata and spatial microdata (GIS building data), demonstrating the method in a Tokyo ward area. The proposed method is shown to be superior to alternatives using limited microdata. This method includes (1) modeling housing composition for each block based on dwelling unit information from spatial microdata, (2) establishing the statistical relationship between housing and demographic attributes through a small area cross tabulation technique using survey microdata, and (3) allocating demographic attributes to street blocks based on this small area-specific relationship. Housing composition is defined by building type and dwelling size and is constrained by small area totals of the census. The Tokyo ward area contains high-density built-up districts and is characterized by vertical population extension and resident diversity. In spite of this complex residential structure, the accuracy assessment indicates that the proposed method performs well and presents a more accurate estimation than any other methods using limited microdata. This finding stresses the effectiveness of combining different types of microdata, which not only allows spatial refinement but also reflects neighborhood heterogeneity of the relationship between housing and demography.

This study observes the case study of the “Nakhon Sawan Community Development Organisation,” which is a network of 21 low-income communities in Nakhon Sawan City Municipality in Thailand. This network’s adaptive activities before, during, and after the mega flood in Thailand in 2011 are considered to be progressive. This study tries to investigate 1) What types of social network/capital can promote building adaptive capacities to flooding in low-income communities, and 2) Poor urban communities’ processes and conditions to form social capital that lead to building adaptive capacity. In this study, three types of social capital–bonding, bridging, and linking social capital–are used for analysis, and these three types are classified at three levels: local, national, and international. From the research, it is revealed that 1) From normal time to during and after the flood, bonding social capital, or the community network, is the basis of adaptive activities, 2) Bonding social capital can carry out adaptive activities in combination with linking and bridging social capital at national and international levels, 3) Low-income communities’ first step to expand its social networks with other organizations is uniting within a community and collaborating with neighborhood communities, and 4) A multi-layered, low-income community network system is effective for disaster management.