Using Geographic Information to Assess Urban Environmental Indicators in the City of Lisbon

Cities are complex and dynamic systems that reproduce the interactions between socio-economic and environmental processes at a local and global scale. This complexity constitutes a significant challenge for urban planning. One effective source of information about the urban environment is remote sensing data. Sealed surfaces generate intense rainwater run-off which the drainage network cannot accommodate, thus promoting flooding events. Mapping urban flood risk implies knowing the spatial distribution and extent of the pervious and impervious areas in the city. These are important variables for planning, mitigation, preparedness and response to potential events. Green areas are an important land use in urban areas, performing relevant environment functions, such as improving urban climate, reducing atmospheric pollution, providing amenities, aesthetical benefits and a good environment for urban populations. However, the urbanization process generally occurs at the expense of agricultural or forested areas, thus contributing to degrade the urban environment quality. The present case study addresses the quantification of impervious land at the city scale through remote sensing data. A methodology for generating a large-scale Land Cover Map for the city of Lisbon, Portugal is proposed. The data source is Very-High Resolution (VHR) IKONOS pansharp image, from 2008, with a spatial resolution of 1 m, and a normalized Digital Surface Model (nDSM) from 2006. The methodology was based on the object-based extraction of features of interest, namely: vegetation, soil and impervious surfaces. After deriving the land cover information from remote sensing data, several applications can be implemented. Indicators on land sealing area, quantification of green area, or the available vacant soil in the city, are ecological measures that can be used as tools for cities to assess and communicate different environmental risks, and promote strategies and measures of sustainable urban development and disaster risk management. It is demonstrated that using a methodology based on large-scale geographic information, quick updating of detailed land cover information is possible and can be used to support decisions in a crisis situation where official maps are generally outdated, or to evaluate the quality of the urban environment.