Table 1. Example of available tools for the extraction of urban environmental quality UEQ indicators. Figure 2. Data used and general structure related to the construction of the following digital urban models: 1 - normalized 2. In the next two sections of this paper, two examples related to urban morphology and solar analysis are briefly presented.
The 2. Using the normalized 2. Other minor indicators can be then 4. Extracting urban environment derived: quality UEQ indicators - General morphological indicators: the total 4.
This indicator is used in biology as well in architecture as one of the most relevant shape related property of objects. From the comparison between the 2 images, we can state that the 3-D representation reveals itself to be very important in cases where the perception of the volume component cannot be ignored. In other words, the 2-D representation does not allow the verification of the correctness of the map since we do not have a visual confirmation of the actual volumes of the represented objects.
Two maps illustrating the surface to volume ratios visualized in a 2-D image above and a 3-D image building roofs below representation for a neighbourhood Chavannes of These indicators address analysis on solar radiation the city of Lausanne. According to [28], the most Given that roof outlines do not necessarily accurate surfaces are created using a grid with a correspond to building outlines due to the existence sampling size that relates as close as possible to the of front-roofs in some cases, the 2.
It is important to note that points per square meter for example, in the pilot when the 2-D projection of roof lines existing in 3-D zones of the city of Geneva and a sampling size of 1 city models is not available the construction of the by 1 meter was used for a density of LiDAR points 2. In this case, around 1 point per square meter for example, in the the 2. The technique used for the calculation of analysis With regards to solar radiation analysis, solar outputs related to solar radiation is based on the geometry formulae allow the derivation of both the image processing of the 2.
These images result from the specific location, for every orientation and inclination transformation of all the information attributes of surface starting from the previous mentioned needed into masks: 2. In the particular case of facades, the falling on the second storey of vertical urban model is sliced at every storey, so as to surfaces. Such a map can be displayed for consider which part of the facade is affected by every storey, which can be useful for focused overshadowing.
But this of solar radiation analysis, from to of the representation needs several maps 15th of December, at the pixel unit scale for a pilot considering various view origins in order to zone of the city of Lisbon - in this figure, each row of visualize the values of all the facades of a pictures represent independent information, presented building.
Therefore the 2-D form with one as follows: single map is more synthetic and preferable 1. Shadow casting; similar to the map shown in Figure 7 , which 2. Solar irradiation on the second storey of several end-users of the city of Geneva [29]. Percentage of solar beam irradiation on the to refine the map by showing the results by second storey of vertical facades of storey and thus the vertical variation of buildings; radiation with the elevation.
Figure 5. The pixel-based simulation presented was made for the 15th of December, from 9 AM until 16 PM hourly analysis. Figure 6. The 3-D map shown in Figure 9 is adequate to make a quick selection of suitable roof sections in a given urban area. Figure 9. Figure 7. The mean solar irradiance collected by the In large roof sections, the irradiation may be very second storey of each facade on the 10th of December at 12 PM, considering both beam and diffuse contributions for a heterogeneous due the local variation of neighbourhood business area of the city of Geneva.
In consequence, for more detailed analysis, a mix between raster and vector representation would enable to select suitable parts of roof sections; it consists of identifying clusters of pixels that share homogenous irradiation values through classification techniques , as shown in Figure Figure 8. The potential user would be in principle rather interested in assessing which section of the roofs Figure This paper introduces several tools that use different [6] Ratti C.
Environment and Planning B: Planning and built fabric. As emerged, both the accuracy and Design, Vol. Computers, Environment and various urban applications. The morphological Urban Systems, Vol. Dutch urban morphology. Environment and Planning B, calculation of thermal and electrical potential for sun Vol. Moreover, the improvement Design, Vol. Effects of ground surface Design, Vol. Cartography, Edited by Sara Irina Fabrikant and MIT Press, Heidelberg, , pp. Cambridge MA, Energy and building, Vol.
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