Disaggregation of census districts: better population information for urban risk management

The vulnerability of population in urban areas, especially in developing countries, under the effects of natural and man-induced hazards, is a major reason for concern. The potential consequences of such hazards require risk management to reduce vulnerability and mitigate disasters. Information on population, required for risk management, has an essential spatial component and, particularly in urban areas, is changing continuously. Access to timely and
trustworthy spatial data is an essential element in urban risk management. The tools Remote Sensing and Geographic Information Systems are most appropriate to play an important role in the risk data collection and information management.
The paper will first discuss briefly the multi-disciplinary research project Strengthening Local Authorities in Risk Management (SLARIM), being implemented by ITC, with three case study cities in Asia. The paper then will focus on population data. The census district is the common basis for collecting population data. However, in many cases the census district is too large and too heterogeneous to provide a good insight into the spatial distribution of the population at risk. The question then is: how can population data in census districts be disaggregated using remote sensing imagery and (mobile) GIS. Land uses, building types, floor space, densities and household sizes are variables to be studied. Examples from the Asian case study cities will be used, in particular from Lalitpur, Kathmandu Valley, Nepal.