Geospatial technologies for physical planning: Bridging the gap between earth science and planning

The application of geospatial information technologies has increased recently due to increase in data sources from the earth sciences. The systematic data collection, storage and processing together with data transformation require geospatial information technologies. Rapidly developing computer technology has become an effective tool in design and physical planning in international platforms. Especially, the availability of geospatial information technologies (remote sensing, GIS, spatial models and GPS) for diverse disciplines and the capability of these technologies in data conversion from two dimensions to the three dimensions provide great efficiency. Thus, this study explores how digital technologies are reshaping physical planning and design. While the potential of digital technologies is well documented within physical planning and visualization, its application within practice is far less understood. This paper highlights the role of the geospatial information technologies in encouraging a new planning and design logic that moves from the privileging of the visual to a focus on processes of formation, bridging the interface of the earth science and physical planning

Description and validation of a " non path-dependent " model for projecting contrasting urban growth futures

International audienceThis paper presents a model (SLEUTH*) for projecting contrasting urban growth futures.It is derived from the SLEUTH model, which has been modified in order to incorporate an additional spatially explicit factor, and to be used in a fully controlled forecasting mode. Our aim is to spatially allocate urban growth, its amount and pattern, according to predefined prospective scenarios and assuming a non path-dependency approach. This modelling approach aims at being used under a "story and simulation" (SAS) approach, which constrains the model validation. To assess model efficiency, three types of tests have been undertaken: (1) sensitivity tests; (2) reproduction of known changes over a past period; and (3) simulation of changes that break trends. Results show that SLEUTH* conveniently simulates expected urban changes for exploring contrasting scenarios that are the basis for land planning strategies

Assessing growth scenarios for their landscape ecological security impact, using the SLEUTH urban growth model

Rapid urban population growth and the associated expansion of urban areas in China (as elsewhere) present significant environmental challenges, and threaten urban and regional ecological security. Modeling land use changes is one way to aid the management of cities. Using remote sensing and geographic information system (GIS) software platforms, land use data for the years 1989, 1996, 2004, and 2010 for the area inside the Jinan third ring-road were interpreted. An urban green space network was developed, as a core strategy to ensure landscape ecological security, and subjected to ecological sensitivity analysis. The green space network and the result of the ecological sensitivity analysis were integrated into the exclusion/attraction layer of an existing cellular automaton model, SLEUTH (Slope, Land use, Exclusion/attraction, Urban extent, Transportation, and Hillshade). A development scenario for land use change was constructed that integrates these Landscape Ecological Security Development (LESD) strategies and reveals trends in urban growth for the different development scenarios between 2011 and 2040. The results of the LESD scenario were compared with those from two other development scenarios: the Historical Trend Development (HTD) and the Transit-Oriented Development (TOD). The study revealed three significant findings. First, change in the urban area in the study will be dominated by urban edge growth and transit-oriented development, while spontaneous and cluster growth were not obvious. Second, the growth rate of built-up land in the urban area in all three scenarios exhibits emerging trends. The growth rate, according to the LESD scenario, is significantly lower than that for the HTD and TOD scenarios, and encroachment into natural ecological space (such as woodlands, water, and agricultural land) is less than that in the other two scenarios. This result indicates that the LESD scenario can protect natural ecological spaces effectively and can significantly reduce the ecological security risk. This aligns with the integration of smart growth and smart conservation. Third, integrating LESD into the SLEUTH model results in the ability to evaluate urban development policies and can help characterize development strategies for urban landscape ecological security. The results of this study provide reference data and a basis for decision-making for the future management of urban growth, urban planning, and land use planning