Iris Lehmann

Urban Green Spaces: Potentials and Constraints for Urban Adaptation to Climate Change

Urban development has to meet the challenge of establishing adaptation strategies in response to climate change. In view of its potential to regulate urban climates, green infrastructure will assume a critical role in these strategies. In addition to their positive microclimatic effects, as a source of cooling in dense, hot cities urban green spaces can contribute to mitigation. They can operate as carbon sinks or can reduce energy consumption for air conditioning by providing shade by urban trees or roof-top greenery. Thus, urban green spaces should be incorporated as a significant component into both adaptation and mitigation strategies. This paper focuses on the potentials and constraints of various types and structures of urban green spaces and vegetation in influencing climatic conditions in urban areas. It examines the ability of urban green spaces to counter the urban heat island effect and other impacts of climate change. The scientific findings discussed are based on urban vegetation analysis and climate modelling as well as analysis of planning approaches and instruments in German cities. They will be analysed in the context of the future relevance of greens spaces, and within the framework of current urban planning and development mechanisms.

Urbane Metrik – Ein Messkonzept zur Physiognomie der Stadt

Im Kontext eines Messkonzepts zur Physiognomie der Stadt nehmen Daten, Messgrosen und Bewertungsansatze eine Schlusselposition ein.

Physiognomie des Urbanen

Die physischen Auspragungen der Stadt sind bauliches Resultat aus wirtschaftlicher Aktivitat, Planung, Verwaltung, Politik, Konsum. Die Physis ist „sedimentierte“ Geschichte im wahrsten Sinne des Wortes. Zugleich ist die Physis selbst Wirkfaktor fur stadtisches Leben, ist Grundlage okologischer und okonomischer Leistungsfahigkeit, die sich in Kennzahlen wie Bruttowertschopfung, Verkehrsleistung, Bodenversiegelung oder in der Biodiversitat ausdruckt.

Effizienzbewertung von Städten auf der Grundlage von Data Envelopment Analysis

Efficiency aims among others to achieve with the same effort the maximum benefit. For measuring the efficiency of products and processes there are various economic models. This raises the question, whether and to which extent such models can be used to measure the efficiency of cities. In this context, the Data Envelopment Analysis (DEA), commonly used in the field of economics production, has been tested to its applicability to cities. The DEA is a nonparametric, deterministic method to measure the efficiency of economic production, in which the relative efficiency of decision units (DMU) is calculated. In the presented investigation, 116 urban municipalities in Germany were taken as DMUs of the DEA. A discussion about possible values to indicate efficiency of the cities in conjunction with first calculation tests led to a model, by which the economic and the ecological point of view is calculated separately by DEA. Hypotheses were established for both perspectives. Central assumption was: In the economic and ecological model we are looking for cities with least input of the resource “land use” and with high economic resp. ecological performance on output side. The selected input and output values are indicators to deliver an image of prospected correlations. The results allowed a ranking related to economic and ecological efficiency of cities as well as an assessment of the proportions of economic and ecological efficiency of the analyzed cities, realised with the aid of a nine-area-matrix (portfolio). The analysis showed that small and middle sized cities with low population, a medium settlement density and land productivity per unit area as well as a high ecological performance will meet the chosen efficiency criteria most likely. Based on the experience with these still very simple models, DEA appears to be an inspiring heuristic instrument for the attempt to draw near to a concept of an efficient city. English Title: Assessment of the efficiency of cities by using Data Envelopment Analysis