Abstract-This research explores urban growth based scenarios for the city of Nairobi using a cellular automata urban growth model (UGM). African cities have experienced rapid urbanization over the last decade due to increased population growth and high economic activities. We used multi-temporal Landsat imageries for 1976, 1986, 2000 and 2010 to investigate urban land-use changes in Nairobi. Our UGM used data from urban land-use of 1986 and 2010, road data, slope data and exclusion layer. Monte-Carlo technique was used for model calibration and Multi Resolution Validation (MRV) technique for validation. Simulation of urban land-use was done up to the year 2030 when Kenya plans to attain Vision 2030. Three scenarios were explored in the urban modelling process; unmanaged growth with no restriction on environmental areas, managed growth with moderate protection, and a managed growth with maximum protection on forest, agricultural areas, and urban green. Thus alternative scenario development using UGM is useful for planning purposes so as to ensure sustainable development is achieved. UGM provides quantitative, visual, spatial and temporal information which aid policy and decision makers can make informed decisions.
Remote sensing only plays a tangential role in schools, regardless of the political claims to strengthen the support for teaching on the subject. A lot of the computer software explicitly developed for school lessons has not yet been implemented due to its complexity. Thereby, the subject is either not at all integrated into the curriculum or does not pass the step of an interpretation of analogue images. In fact, the subject of remote sensing requires a consolidation of physics and mathematics as well as competences in the fields of media and methods apart from the mere visual interpretation of satellite images. In order to integrate remote sensing in a sustainable manner digital, interactive and interdisciplinary learning modules promoting media and method qualifications as well as independent working are provided.
Decision-makers in the fields of urban and regional planning in Germany face new challenges. High rates of urban sprawl need to be reduced by increased inner-urban development while settlements have to adapt to climate change and contribute to the reduction of greenhouse gas emissions at the same time.In this study, we analyze conflicts in the management of urban areas and develop integrated sustainable land use strategies for Germany. The spatial explicit land use change model Land Use Scanner is used to simulate alternative scenarios of land use change for Germany for 2030. A multi-criteria analysis is set up based on these scenarios and based on a set of indicators. They are used to measure whether the mitigation and adaptation objectives can be achieved and to uncover conflicts between these aims. The results show that the built-up and transport area development can be influenced both in terms of magnitude and spatial distribution to contribute to climate change mitigation and adaptation. Strengthening the inner-urban development is particularly effective in terms of reducing built-up and transport area development. It is possible to reduce built-up and transport area development to approximately 30 ha per day in 2030, which matches the sustainability objective of the German Federal Government for the year 2020. In the case of adaptation to climate change, the inclusion of extreme flood events in the context of spatial planning requirements may contribute to a reduction of the damage potential.
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