Georeferencing social spatial data and intra-urban property price modelling in a data-poor context: a case study for Shanghai
Despite enormous progress in GIS techniques, the lack of geo-referenced spatial data is still a major constraint to the development of more accurate and in-depth/sophisticated spatial analysis in developing countries. Even when some spatial data are available in theory, the use of geo-referenced data is constrained due to two reasons. First, the digital data may not be available to researchers (especially for those are not affiliated to a local institution) for the sake of confidentiality. For example, in the case of China, population census is not released to the public at the sub-district, i.e. Street Office level or lower levels. Even at the sub-district level, the data are not publicly available except for the total population. However, the sub-district is probably equivalent to wards rather than enumeration districts (EDs) in UK, which is still too coarse for the purpose of examining subtle intra-urban spatial variation. Ideally, disaggregated data should be obtained for urban and rural settlements because residential quality varies at the scale of neighbourhoods. In case of China, these units are residents’ and villagers’ committees.