2. Theory
3.1. Multi‐Criteria Assessment (MCA)
The methodological core of this study is a spatial and GIS‐supported MCA. Basically, the field of MCA is broad and associated literature on multicriteria decision making abundant169. Most of the literature in this field focuses on the mathematical core of the MCA, its decision rules and associated methods.
In contrast to that, the application of spatial MCA is “a relatively new but growing field which is still developing with the further improvement of GIS”170. MCA allows the integration of manifold aspects of a problem and considers conflicts of points of view and interests of different stakeholders (e.g.
residents) within a planning process171. It is a helpful instrument to realize sustainable settlement development when being integrated into spatial planning172.
The conceptual structure of the MCA of this thesis harks back to the concepts of QoP, QoL and associated UES. Essential interconnections between urban development and the central concepts of this study QoP, QoL and UES were highlighted in figure 5. Figure 11 refers to that and introduces the methodological determinants of the two steps of the MCA. Moreover, the integration of both ecological and social aspects into one MCA and into decision making is an essential innovative approach of this concept. Regarding its spatial and executive reference, the MCA is strictly related to the structure of German land use planning. It considers both the preparatory land use planning on the level of a land use plan and the binding land use planning at the level of a legally binding land‐use
169 see MEYER ET AL. 2008 for a concise analysis
170 MEYER ET AL. 2008, p. 19; see also the concise overview of MALCZEWSKI (2006) highlighting the potentials of linking MCDA and GIS‐techniques and further research on a close “understanding of the benefits of such integration” (p. 718)
171 NIJKAMP ET AL. 2002, SCHETKE & HAASE 2008
172 NIJKAMP & OUWERSLOOT 2003; THÉRIVEL 2004
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39 plan (see fig. 11 below). The systematization and development of indicators for both steps of the MCA were executed according to empirical evidence as discussed in scientific literature and substantiation by communal GIS‐datasets. Individual technical and content‐related prerequisites of indicators, their relevance for the analysis and their significance will be discussed within the next sub‐
chapters.
Figure 11 Scheme and content‐related specifications of the MCA (author´s draft)
Step 1:
The first step of the MCA provides an assessment of socio‐environmental prerequisites and objective framework‐conditions for future housing‐sites, which are displayed in the land use plan of the City of Essen. These framework‐conditions – in the following referred to as QoP‐ are analyzed under the premise of the contribution of the respective future housing estates to a sustainable and resource‐
protecting settlement‐development. The focal points of the analysis of ecological and social framework‐conditions are displayed in figure 11 and were outlined in chapter 2. The indicator‐setup itself is strongly oriented towards the applicability of all indicators within the planning process and their transparency and communicability towards urban planners as the aspired user‐group (further outlines in chapter 3.2)173.
173 According to KÖTTER ET AL. 2009b, SCHETKE ET AL. 2009a, SCHETKE ET AL. (in prep.)
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As the land use plan describes the strategic level of German land use planning and performs steering effects for settlement development, the assessment of socio‐environmental prerequisites (QoP) as the first step of the MCA – physiocentric in nature – on that level can point out, which future housing estates contribute to a sustainable and resource‐preserving settlement development.
Simultaneously, it depicts the fields and areas of a city where settlement‐development and urban planning itself follows the unintended negative trend of ongoing land‐consumption and the current paradox of settlement‐ growth as outlined in chapter 2.
Step 2:
After a first assessment of socio‐environmental framework conditions (QoP), the second step of the MCA assesses concrete socio‐environmental impacts of housing‐development. The intensity of these impacts alters according to different housing‐densities and modified land uses at each future housing site of the case‐study. Three scenarios, which represent different housing densities, will be used for the assessment.
The concepts of QoL and UES are used as target systems to provide an objective, scenario‐based and quantifiable analysis of future impacts due to housing‐development. As outlined in chapter 2, the sensitivity of QoL and UES against housing‐development and each change of the built environment is to be analyzed using the significant contribution of urban green to the two systems and its modification under processes of settlement‐growth.
Three main needs as determinants of QoL were extracted from a broad literature review (see chapter 2.5). The provision with uniform and quantifiable indicators, which link QoL and UES as described in SCHETKE ET AL.*, are entirely based on official, communal data‐sets.
Compared to the assessment of QoP, this second level of the MCA is anthropocentric in nature. It provides a different indicator‐set compared to step 1. This is not only emphasized by an analytical focus on two highly human‐related concepts of land use development such as QoL and UES.
Moreover, both the impact assessment and its quantification of land use change are bound to the housing areas itself together with its closer living surroundings. It is expected that a direct land use change at a housing site will also have eradiating effects on its surroundings. In current planning literature “closer living surroundings” or “free space close to living to apartment” are set as a radius of 500m around a site174.
174 The definitions of closer living surroundings are deriving from planning standards. The CITY OF LEIPZIG (2004, p. 27) defines a walking distance of 500m to green spaces of closer living surroundings. This implies a smaller air‐line distance taken into account for GIS‐analysis. Compared to that, the CITY OF BERLIN (Umweltatlas Berlin 2009) calculates an air‐line distance of 450m including approximately 10%‐deduction from walking distance. According to these notions a walking distance of 500m was taken as a reference for closer living surroundings. To derive the correct air‐line distance a distance coefficient of 1.2 (KORDA 2005, p. 289) has been applied for GIS‐analysis leading to an air‐line distance of 416.67m.
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