Urban sprawl is a process that shapes contemporary urban spaces. Generally, this process is associated with negative effects due to the generation of high costs. However, not all the effects of urban sprawl should be considered in the context of the increasing costs of the use of space; some of them should be regarded as cost cutting factors, for example, the possibility of the use of roofed areas in generating energy from sunlight. Solar energy is believed to be one of the sources of clean energy that reduce pollution and greenhouse gas emissions into the atmosphere. However, solar energy generation necessitates the development of large areas for the purpose of installing photovoltaic modules and substantial funds for creating large solar farms. For this reason, a significant role in state energy policies is played by small dispersed installations mounted on the roofs of buildings. There is a gap in existing research on the assessment of urban sprawl in terms of the potential use of rooftops for solar installations in suburban areas. This research gap has not yet been filled, either conceptually and methodologically. Hence, the contribution of the research to the development of the current state of knowledge involves the identification of economic and environmental benefits of usually negatively perceived urban sprawl. The proposal of a method for the identification of suburban housing potential for solar energy generation constitutes another addition to the state of knowledge. The main objective of this article is to analyse the energy generating potential of buildings located in suburban and urban areas characterised by the confirmed occurrence of urban sprawl phenomena. CityGML data were used to conduct an analysis of the exposure of roofs to sunlight using algorithms based on vector data. The authors estimated the dynamics of changes in time and referred the existing photovoltaic installations to the total potential of a selected area. The use of the energy potential of the analysed roofs of buildings was used to evaluate the external costs and benefits of spatial planning. The discussion presented the current conditions of the energy sector and energy policies in Poland and the EU. In addition, recommendations were proposed for local spatial policies concerning the mitigation of the effects of suburbanization in the context of developing the system of PV micro-installations.
Browsing the possibilities posed by GIS and CAD programs in the modeling analysis results we can find many similarities and differences. Features arise from aims for which these types of programs have been developed. Goal of GIS software is to do different types of spatial analysis. A secondary aim is to do visualization of the results generated. A secondary aim is to doing visualization of the results generated. CAD software is taking data presentation proposed as an overriding goal, however, analysis tools, topology and relationship to the database are limited to special overlays to the main program or did not exist. Knowing how to do the main task of particular programs we can say that the CAD software is better suited for the visualization of data than GIS applications.We will attempt to analyze possibility of these two types of software with regard to ArcGIS Version 10 and CAD graphics software Cinema4D R13.For visualization in the program ArcGIS we can use two 3D environments: ArcGlobe and ArcScene. They are designed for different uses. After starting ArcGlobe application, we can see the globe, suggests to us, that all analysis and visualization will involve a large area of land. The data can be presented on a sphere Earth. ArcScene is designed for analysis and visualization covering a small area of land. Data are presented on the local reference plane. Differences also include data that we can use for analysis and visualization. In ArcGlobe, all data can be displayed in the specified simplification, depending on the magnification. This eliminates the problem of overloading the computer memory, we do not have to resign from less important data available. In ArcScene, all available data are automatically stored in the computer memory, we have quick access to them. The downside of
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