Abstract
Abstract. Urban indicators are efficient tools designed to simplify, quantify and communicate relevant information for land planners. Since urban data has a strong spatial representation, one can use geographical data as the basis for constructing information regarding urban environments. One important source of information about the land status is imagery collected through remote sensing. Afterwards, using digital image processing techniques, thematic detail can be extracted from those images and used to build urban indicators. Most common metrics are based on area (2D) measurements. These include indicators like impervious area per capita or surface occupied by green areas, having usually as primary source a spectral image obtained through a satellite or airborne camera. More recently, laser scanning data has become available for large-scale applications. Such sensors acquire altimetric information and are used to produce Digital Surface Models (DSM). In this context, LiDAR data available for the city is explored along with demographic information, and a framework to produce volumetric (3D) urban indexes is proposed, and measures like Built Volume per capita, Volumetric Density and Volumetric Homogeneity are computed.
Highlights
Cities are complex and dynamic systems that constitute a significant challenge to urban planning
The results presented in this paper are a product of an on-going research about the use of Very-High Resolution (VHR) imagery to expedite the production of geographic information for municipal planning and land monitoring
These effects result from the fact that the Digital Terrain Model (DTM) is not as accurate and detailed as the Digital Surface Model (DSM) in such situations. Such circumstances, require further processing in order to correctly model the terrain by introducing break lines that reflect abrupt changes in the terrain and control surface behaviour by acting as a barrier to the interpolation of the Triangulated Irregular Network (TIN) model (Pfeifer, 2005). These errors were already expected since they can appear in two situations: 1) when the DSM and the DTM are acquired in different dates or, 2) when the collection method differs (e.g., LiDAR flight or photogrammetric methods)
Summary
Cities are complex and dynamic systems that constitute a significant challenge to urban planning. Systems based on different urban indicators can be used as tools for cities to communicate different environmental risks, and promote strategies and measures of sustainable urban development and disaster risk management. Monitoring indicators of key processes in land use and economic development is essential for evaluating policy measures. To build such indicators, information about the urban environment is required. Remote sensing is an efficient way of collecting that information. The constantly increasing availability and accessibility of modern remote sensing technologies has provided new opportunities for urban applications
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