A list of implemented tools
/Solar Accessibility (shadowcasting and skyviewfactor)
/Urban Visual Perception
/Urban Shape and Density indicators
1. Why was the technique created?
2. About the technique
3. How does the technique work
1. Why was the technique created?          [top]
Both aspects concerning the wellbeing of people in outdoor and indoor spaces are relevant, in order to achieve the environmental quality of urban spaces. In fact, the delicate relationship existing between the assessment of the urban fabric and the design of open spaces defines the urban environmental quality and assesses the success of a city. This wise balance inside the urban form is surprisingly tangible in numerous historical city centres and was generated through a long process of transformations over time. Today, cities evolve rapidly and the slow process of adaptation of urban shape to meet human needs and sustain ecological diversity is no longer feasible. As an alternative way aiming to manage the complex set of environmental variables in the frame of rapid urban changes, the proposed set of tools is presented. It allows to investigate simultaneously different environmental aspects, such as solar access, cross ventilation, energy consumption, etc., in relation to the arrangement of the urban fabric. Algorithms defined in the Matlab environment and derived from image processing, can work with very simple raster images of the urban texture stored in Bitmap format. Potential users might simply use the proposed set of tools or implement new algorithms to meet their needs and compare different design solutions from the environmental and morphological viewpoint. In fact, using this set of tools, a new paradigm for assessing the environmental consequences generated by the urban texture is investigated. This is centred on the relationship existing between environmental indicators and urban morphology: the question is if - and in what measure - the correct arrangement and the shape of the urban fabric alone might improve the environmental behaviour of the city. With the aim of making an effective environmental quality starting just from morphology, several design tools can be developed, assessing new potentialities related to the form of human settlements. For instance, the energy-based morphogenesis of the built environment could be intended as the first step towards the improvement of the sustainability of cities with no additional cost due to the application of complex technologies. The technique revealed itself to be useful for simulations on alternative design schemes over large-scale masterplans and for extensive and complex urban areas, helping to make decisions supported by measured quantification. In particular, the technique demonstrates the potential of digital urban models based on raster images for the analysis of the city, which brings with it many advantages such as fast computability, flexibility, precision and comparability of results obtained from several algorithms. The tools were initially created to compare the environmental behaviour of different urban configurations. In fact, the technique might be desirable in comparative studies, whereby environmental indicators can be mapped and visualised for different design projects, and consequently critical situations can easily emerge. Especially in the case of limited resources, the identification and quantification of environmental deficiencies on the urban texture could help in programming intervention phases more efficiently. In fact, the rapid measurability of several environmental indicators on each point of the urban space is simply based on the same digital support as the unique input, which is analysed and processed through a series of imposed algorithms. We focus on the city and its development scenarios for the future. Further work and applications of the proposed technique might promote a new concept of urban environmental architecture, based on new design strategies and generative rules for the prediction of innovative morpho-typological solutions derived by environmental indicators.
2. About the technique          [top]
Urban Environmental Quality (UEQ) indicators are mainly extracted from digital image processing (DIP) techniques based on the use of 2.5-D Urban Models, here called 2.5-Digital Urban Surface Models (2.5 DUSM).
For instance, a series of simple image processing operations are directly applied on digital urban models.
For instance, the 2.5-DUSMs reconstructed from remote sensing imagery, as well every type of 3-D digital model can be translated into a 2-D array, whereby each intensity value represents the height of each pixel. By implementing software algorithms derived from digital image processing techniques, it is possible to develop efficient strategic tools for analyzing and planning the sustainable urban form, measuring geometric parameters and assessing radiation exchange, energy consumption, wind porosity, visibility and spatial analyses, among others. Results are fast and accurate.
Pioneers in the use of image processing techniques for the analysis of environmental indicators and morphology of digital urban models was a group of researchers at the Martin Centre, University of Cambridge (Ratti and Richens 2004). This research was further improved at the Senseable City Lab at MIT, who proposed applications for assessing the solar admittance of the urban fabric through solar envelopes (Morello and Ratti 2009) and the visual perception of the urban open spaces through the use of 2-D and 3-D isovists (Morello and Ratti 2009).
3. How does the technique work          [top]
The technique is based on the image processing of Digital Elevation Models (DEMs). The DEM can be processed like a 2-D array containing the information related to heights at every pixel. The DEM can be processed as bitmap image and the pixel width is assigned depending on the physical scale of the DEM itself: typically, at the scale of neighbourhoods, a resolution of 1mx1m per pixel allows to compute most of the environmental indicators with sufficient precision. To each pixel a normalized height in meters is defined, based on the weighting of the greyscale map. Considering for example an area with average extension of 1kmx1km, the 2-D array of 1000x1000 pixels represents a good compromise in order to achieve a good precision of results avoiding time-consuming computations.
The simplest operations on DEMs through Matlab are explored in the next section (solar accessibility), starting from the fundamental algorithm for computing shadows (Ratti and Richens, 2004).
For instance, many professional packages allow the image processing of DEMs and the writing of dedicated codes, like for example the freely-available NIH-Image and Matlab. The latter is more powerful and permits more operations and was used for the development of the here presented set of tools.
4. Bibliography          [top]
Morello E., Ratti C., 2007, "Raster Cities: image processing techniques for environmental urban analysis", in Thwaites K., Porta S., Romice O. , M. Greaves (editors), Urban Sustainability through Environmental Design: approaches to time, people and place responsive urban spaces, Spon Press, London, UK, pp. 119-122.
Ratti, C., Richens, P., 2004, "Raster analysis of urban form", in Environment and Planning B: Planning and Design (31:2).
Ratti, C., Baker, N., Steemers, K., 2005, "Energy consumption and urban texture", in Energy and Buildings, 37.