Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 689-694, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/689/2016/
doi:10.5194/isprs-archives-XLI-B2-689-2016
 
08 Jun 2016
GEOMATICS FOR SMART CITIES: OBTAINING THE URBAN PLANNING BAF INDEX FROM EXISTING DIGITAL MAPS
V. Casella, M. Franzini, and R. De Lotto Department of Civil Engineering and Architecture, University of Pavia, Italy
Keywords: geo-information, urban planning, geoprocessing, BAF, biotope area factor, smart city, urban analytics Abstract. The urban analytics expression is spreading out. To our understanding, it deals with the capability of measuring cities and their communities, as a support to their effective planning and management. In other words, being an analytically well-known city is a precondition for pursuing smartness. Urban planning is a very important item for city management and is interrelated with many layers, including urban environmental quality, air quality and well-being. Effective urban planning is based on the knowledge of quantitative parameters such as the biotope area factor (BAF), which was originally proposed for the city of Berlin and is currently used in other cities. The BAF index is used to evaluate the degree of soil permeability and measures, to a certain extent and from a specific point of view, how a city is eco-friendly. The usual way of evaluating the BAF is based on the manual construction of dedicated maps, using existing orthophotos and oblique imagery as a support. But this method is expensive, time-consuming and non-objective, as it is prone to different interpretations. The paper presents a newly-developed methodology for calculating the BAF. It is based on the use of existing digital cartography and on the application of geoprocessing techniques from GIS science: it is therefore fully automated and objective. The Pavia city (Northern Italy) is used as a testsite and a careful validation of the developed methodology is carried out, by comparison to 12 manually surveyed test areas, corresponding to 5% of the built-up areas of the municipality.
Conference paper (PDF, 1226 KB)


Citation: Casella, V., Franzini, M., and De Lotto, R.: GEOMATICS FOR SMART CITIES: OBTAINING THE URBAN PLANNING BAF INDEX FROM EXISTING DIGITAL MAPS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 689-694, doi:10.5194/isprs-archives-XLI-B2-689-2016, 2016.

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