Alexander Siegmund

Multi-criteria spatial decision support system for valuation of open spaces for urban planning

One of the major accompaniments of the globalization is the rapid growing of urban areas. At the end of the 1970th only 38% of world lived in cities, this number increased to more than 50% by 2008. In 2030 two third of all people worldwide are expected to live in cities, many of them in megacities. Urban sprawl is a major environmental concern affecting cities and urban. Urban sprawl depends on the socio-economic situation in the cities. Thus, reducing migration, sustainable handling of the limited resources and “smart growth” are acknowledged as key tasks for urban planning. Coping with these tasks requires precise and adaptive planning instruments. The presented study is part of the research project GAUS (Gaining Additional Urban Space) aiming at inventorying the open space available in urban environments and, moreover, providing flexible multi-criteria spatial decision support system for its development. The method is based on VHR (Very high resolution) optical satellite data (QuickBird (QB) and IKONOS (IK)) which is applied on three study areas: Berlin, Istanbul, and Ruhr Area. Object-based image analysis is applied to map land cover and land use and derive metrics describing urban form and inner-urban structure on multiple scales. The workflow has been standardized and leads to comparable results across different test sites and datasets. In intersection with available GIS (Geographical Information System) and local ancillary data, the outputs of image analysis serve as input for a multi-criteria spatial decision support system. Flexible multi-criteria spatial decision support (MC-SDSS) tool has been created by using MATLAB (Matrix Laboratory) software and its tools (Mapping toolbox etc.). Users can change their weights and parameters with this tool for their different study areas. Urban planners can use final suitability maps of this tool. Thus complex decisions are supported by numerical calculation and spatial visualization in order to come to objective solutions. This work contribute to close the gap between remote sensing methods and applied urban planning.

Land use/land cover classification for applied urban planning - the challenge of automation

The number of remote sensing platforms increased during the last decades significantly and produced an ascend of geographical data availability at variable scale. The development of last generation satellites leads to a revival in sensor research. The highest spatial resolution commercial satellite systems even challenges the aerial photogrammetry. Increasing knowledge of methods for analyzing and processing remote sensing data is not equipollent to the outcomes of new remotely sensed geospatial data. Especially very high resolution (VHR) remote sensing data gains the application range for urban remote sensing (URS) and becomes therefore interesting for urban planners. Due to rapid urbanization processes and growth of population, urban sprawl becomes a challenging task for urban planners. Besides land cover, land use is one of the most important information for planning authorities and their decision-making procedure. A classification strategy for applied urban planning was developed to gain information about urban environment. In this context automation and transferability of algorithms are crucial factors for user oriented solutions. Therefore a problem-solving approach with object-based classification algorithms was elaborated. The developed classification procedure lead to land cover and land use maps in a semi-automated approach.

The key role of socio-demographic and socio-environmental factors in urban malaria occurrence and control – An illustration using the city of Yaoundé

Cities in developing countries are experiencing an unprecedented population growth that illustrates a demographic transition and a shift towards modernization with consequences on their epidemiological profiles. However, this change is characterized by an important rural-to-urban social and cultural transfer that can bias the expected epidemiological transition; at the same time, this transfer renders the understanding of the occurrence of communicable diseases more complex than it appears. Urban malaria occurrence was modeled for the city of Yaoundé in Cameroon. Retrospective interviews were conducted to describe a variety of epidemiological, social and environmental variables at the household level. Various ecological variables originating from remote sensing data were also integrated. Multivariate multilevel negative binomial analyses were developed to evaluate the distinct contributions of explanatory social and ecological variables. Spatial models based on the level of urbanity were implemented to understand the intelligence of urban malaria as characterized by those variables. The results showed an overall higher statistical importance of socio-environmental variables, particularly those describing rural origin socio-cultural features in terms of non-conventional housing types and urban agriculture (UA). The spatial patterns of the urban malaria occurrences displayed a complex combination of population density gradients and socio-environmental factors, illustrating the importance of conventional urban features over rural/non-conventional features in reducing the occurrence of urban malaria.

Monitoring statewide urban development using multitemporal multisensoral satellite data covering a 40-year time span in north Rhine-Westphalia (Germany)

Increasing population growth and growing ecological problems in urban areas require advanced remote sensing technology for the acquisition of detailed and accurate land-use information for urban management and planning issues. Surface consumption of 120 ha per day (2003) for traffic and settlement areas in Germany is far away from the 30 ha per day of the sustainability-strategy intended for the year 2020 by the Federal Environmental Ministry. With regard to the 50ies, imperviousness and sealing almost doubled. The presented study is embedded in a project in North Rhine-Westphalia (NRW), the most densely populated federal state in Germany. During the last decades, industrial transformation processes as well as strong economic and socio-structural changes have taken place, making NRW most suitable as an exemplary region to study and visualize dynamic developments in Europe. The examined time period of this work includes intense urban development and expansion in the suburban regions. LANDSAT data of three time slices (1975, 1984 & 2001) build the backbone to detect the changes taken place. Applying a multisensoral approach with improved spatial and even spectral resolution the focus is on the urban development of certain “hot spots” in NRW. CORONA, IKONOS as well as ASTER satellite data is used to allow a further characterization of urban land-use types and changes in more detail over the last four decades. Classical change detection methods as PCA are combined with classification of segmented urban land-use areas when evaluating the type of change.

The Heidelberg Inventory of Geographic System Competency Model

The concept “system” is fundamental to many disciplines. It has an especially prominent place in geography education, in which additionally, the spatial perspective is central. Empirically validated competency models dealing specifically with geographic systems—as well as adequate measurement instruments—are still lacking. Therefore, based on the theoretically-guided development of a Geographic System Competency (GSC) model, the aim was to build and evaluate such a measurement instrument, with the help of probabilistic measurement models. The competency model had three dimensions: (1) “comprehend and analyze systems”, (2) “act towards systems” and (3) “spatial thinking”, whereby dimension (2) was changed to “evaluating possibilities to act towards systems” after a thinking-aloud study. A Cognitive Lab (CogLab) and two quantitative studies (Q1 n = 110, Q2 n = 324) showed divergent results. Dimension (2) could not be identified in both quantitative studies. Whereas Dimensions (1) and (3) constituted separate dimensions in Q1, in Q2 the two-dimensional model did not fit significantly better than the one-dimensional model. Besides showing the close relationship between spatial and systemic thinking in geographic contexts, which are thus both needed in modeling GSC, the project highlights the need for more research in this central area of geography education.

Germany: Diverse GIS Implementations within a Diverse Educational Landscape

In this chapter, we describe the status of Geographic Information Systems (GIS) in the secondary schools of Germany. We discuss the current state of GIS in secondary school and teacher education, as well as two cases of GIS use. The chapter concludes with a discussion of the prospects of GIS implementation.

„Nachhaltigkeit lehren lernen“ – Innovative interdisziplinäre Lehr-Lern-Formate in der Lehramtsausbildung an Pädagogischer Hochschule und Universität Heidelberg

Bildung fur nachhaltige Entwicklung (BNE) gilt als Schlussel fur eine langfristige Verankerung der Ziele einer nachhaltigen Entwicklung. Fur eine erfolgreiche Implementierung dieser Ziele kommt der Ausbildung von Lehrkraften eine besondere Bedeutung zu. In einem hochschulubergreifenden Seminar von Padagogischer Hochschule Heidelberg und Universitat Heidelberg werden in Kooperation Lehramtsstudierende zu Nachhaltigkeits-Coaches ausgebildet, die ihr Wissen in ausgewahlten Projektschulen an Schulklassen weitergeben.

Heidelberg Center for the Environment (HCE) - Zentrale Aktivitäten

Das Heidelberg Center for the Environment wirkt als Netzwerk der Umweltwissenschaften an der Universitat Heidelberg. Im Film wird die Struktur des HCE vorgestellt und ein Einblick in aktuelle Aktivitaten gegeben. Institut/Arbeitsgruppe: Heidelberg Center for the Environment

Remote sensing and GIS based study of potential erosion and degradation areas on the island Fogo (Cape Verde Islands)

The Island of Fogo (Cape Verde) is affected by processes of erosion and degradation, caused mainly by a high population growth and global change. With its small scaled climatic, floristic and geo-ecological differentiation, the island of Fogo is an optimal research space for understanding semiarid island ecosystems in the marginal tropics and their behaviour to erosion and degradation processes. For that reason, a change detection analysis over the past two decades is generated, showing the level and direction of land cover and land use change. Two satellite images from 1984 and 2007 will classified by a Maximum Likelihood approach. In a further step, an image of 1974 will be also integrated in this change detection analysis, enlarging the study over the last three decades.