Centre for Geographical Studies, Institute of Geography and Spatial Planning, Universidade de Lisboa, Lisbon, 1600-276, Portugal
Received: 03 Jun 2016 – Discussion started: 07 Jun 2016
Abstract. Assessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occur at the local scale, such as with landslides. The present study aims to apply dasymetric cartography to improving population spatial resolution and to assess the potentially exposed population. An additional objective is to compare the results with those obtained with a more common approach that uses, as spatial units, basic census units, which are the best spatial data disaggregation and detailed information available for regional studies in Portugal. Considering the Portuguese census data and a layer of residential building footprint, which was used as ancillary information, the number of exposed inhabitants differs significantly according to the approach used. When the census unit approach is used, considering the three highest landslide susceptible classes, the number of exposed inhabitants is in general overestimated. Despite the associated uncertainties of a general cost–benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment.
Revised: 14 Nov 2016 – Accepted: 22 Nov 2016 – Published: 19 Dec 2016
Garcia, R. A. C., Oliveira, S. C., and Zêzere, J. L.: Assessing population exposure for landslide risk analysis using dasymetric cartography, Nat. Hazards Earth Syst. Sci., 16, 2769-2782, doi:10.5194/nhess-16-2769-2016, 2016.