Thomas Leduc

Sensitivity of Spatial Indicators for Urban Terrain Characterization

To develop and manage urban territories and to analyze urbanisation impact on environment, an accurate knowledge of the city and its urban fabric is necessary. A physical description like building morphology or land cover/use allows some characterization of the urban terrain. A specific package for a GIS software is developed for urban analysis: UrbSAT (Urban Spatial Analysis Tool). It allows extracting knowledge from various data sources and gives some indicators to real applications (sustainable development, management policy, air quality improvement, etc). It raises issues such as database accuracy and quality, cell shape, size and orientation for the construction of spatial indicators. We present some tests to address those issues.

3D City Models and urban information: Current issues and perspectives

Considering sustainable development of cities implies investigating cities in a holistic way taking into account many interrelations between various urban or environmental issues. 3D city models are increasingly used in different cities and countries for an intended wide range of applications beyond mere visualization. Could these 3D City models be used to integrate urban and environmental knowledge? How could they be improved to fulfill such role? We believe that enriching the semantics of current 3D city models, would extend their functionality and usability; therefore, they could serve as integration platforms of the knowledge related to urban and environmental issues allowing a huge and significant improvement of city sustainable management and development. But which elements need to be added to 3D city models? What are the most efficient ways to realize such improvement / enrichment? How to evaluate the usability of these improved 3D city models? These were the questions tackled by the COST Action TU0801 Semantic enrichment of 3D city models for sustainable urban development . This book gathers various materials developed all along the four year of the Action and the significant breakthroughs.

Towards urban fabrics characterization based on buildings footprints

Urban fabric characterization is very useful in urban design, planning, modeling and simulation. It is traditionally considered as a descriptive task mainly based on visual inspection of urban plans. Cartographic databases and geographic information systems (GIS) capabilities make possible the analytical formalization of this issue. This paper proposes a renewed approach to characterize urban fabrics using buildings’ footprints data. This characterization method handles both architectural form and urban open space morphology since urban space can be intuitively and simply divided into built-up areas (buildings) and non-built-up areas (open spaces). First, we propose to build a mesh of the open space (a morphologic tessellation) and then we formalize relevant urban morphology properties and translate them into a set of indicators (using some common-used indispensable indicators and proposing a new formulation or generalization of a few others). This first step produces a highly dimensional data set for each footprint characterizing both the building and its surrounding open space. This data set is then reduced and classified using a spatial clustering process, the self-organizing maps in this case. Our method only requires buildings’ footprints as input data. It can be applied on huge datasets and is independent from urban contexts. The results show that the classification produced is more faithful to ground truth (highlighting the variety of urban morphologic structures) than traditional descriptive characterizations generally lacking open space properties.