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Agriculture land has been treated as the urban reserved land which has potential value for transformation. Especially for the land development strategy by “Developmental Government”, agriculture land’s value is twisted and encouraging trading activity, that result in lower production and short in food supply. The threats from extreme weather and environmental change has increased the potential hazards of landuse and challenges toward town planning. This study uses environmental diagnosis and field survey with in-depth interviews, along with the result from FLO-2D flood model and GIS overlay of hazard risk maps, to proceed with a case of “property-led development” in (Taiwan, Xinzhu) Zhubei city. The findings indicate that run-off volume of some area has changed and the flooding depth / area has increased. By interpreting the empirical results, it has exposed the environmental hazard issues and land commodification by the failure of urban planning policy in Zhubei city.

The degree of social vulnerability may vary according to the conditions and backgrounds of different locations, yet spatial clustering phenomena may exist when nearby spatial units exhibit similar characteristics. This study applied spatial autocorrelation statistics to analyze the spatial association of vulnerability among townships in Taiwan. The vulnerability was first assessed on the basis of a social vulnerability index that was constructed using Fuzzy Delphi and analytic hierarchy process methods. Subsequently, the corresponding indicator variables were applied to calculate standardized vulnerability assessment scores by using government data. According to the results of the vulnerability assessment in which T scores were normalized, the distribution of social vulnerabilities varied among the townships. The scores were further analyzed using spatial autocorrelation statistics for spatial clustering of vulnerability distribution. The Local G statistic identified 42 significant spatial association pockets, whereas the Global G statistic indicated no spatial phenomenon of clustering. This phenomenon was verified and explained by applying Moran's I statistics to examine the homogeneity and heterogeneity of spatial associations. Although both statistics were originally designed to identify the existence of spatial clustering, they serve diverse purposes, and the results can be compared to obtain additional insights into the distribution patterns of social vulnerability.

The case of Chun-You Street fire in downtown Nan-Gan Township revealed problems in Lien-Chiang County (also known as the Matsu Islands), such as conflicts in reconstructing post-disaster historical areas and the socioeconomic vulnerability to disasters. The changing urban form during previous decades generated politically oriented planning policies, tourism development policies, a unique population, and socioeconomic vulnerability. This study used a participatory observation methodology and in-depth interviews to investigate the following issues of the Chun-You Street fire: (1) the diversity of the county emergency management system during the response stage and the unique recovery process of a historical site that is based on the clan system, (2) the vulnerabilities caused by residents’ experiences in lacking daily supplies and the custom to store great amounts of materials, and (3) victims’ unclear property rights and land uses pertaining to past verbal agreements creating an obstacle to the recovery of a historical area.