Spatial Allocation of Future Residential Land Use in the Elbe River Basin

Hoymann, Jana

doi:10.1068/b36009

Cited by 27 publications

(12 citation statements)

References 21 publications

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“…Numerous studies using land use evolution models have been carried out in western Europe (Verburg et al, 2002(Verburg et al, , 2004Barredo et al, 2003;Antrop, 2004;Antoni, 2006;Overmars et al, 2007;Hoymann, 2010Hoymann, , 2011. Land use evolution models simulate complex interactions between bio-physical and socio-economic factors.…”

Section: Land Use Modellingmentioning

confidence: 99%

Contribution of land use changes to future flood damage along the river Meuse in the Walloon region

Beckers

Dewals²,

Erpicum³

et al. 2013

Nat. Hazards Earth Syst. Sci.

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Abstract. Managing flood risk in Europe is a critical issue because climate change is expected to increase flood hazard in many european countries. Beside climate change, land use evolution is also a key factor influencing future flood risk. The core contribution of this paper is a new methodology to model residential land use evolution. Based on two climate scenarios ("dry" and "wet"), the method is applied to study the evolution of flood damage by 2100 along the river Meuse. Nine urbanization scenarios were developed: three of them assume a "current trend" land use evolution, leading to a significant urban sprawl, while six others assume a dense urban development, characterized by a higher density and a higher diversity of urban functions in the urbanized areas. Using damage curves, the damage estimation was performed by combining inundation maps for the present and future 100 yr flood with present and future land use maps and specific prices. According to the dry scenario, the flood discharge is expected not to increase. In this case, land use changes increase flood damages by 1-40 %, to C 334-462 million in 2100. In the wet scenario, the relative increase in flood damage is 540-630 %, corresponding to total damages of C 2.1-2.4 billion. In this extreme scenario, the influence of climate on the overall damage is 3-8 times higher than the effect of land use change. However, for seven municipalities along the river Meuse, these two factors have a comparable influence. Consequently, in the "wet" scenario and at the level of the whole Meuse valley in the Walloon region, careful spatial planning would reduce the increase in flood damage by no more than 11-23 %; but, at the level of several municipalities, more sustainable spatial planning would reduce future flood damage to a much greater degree.

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Section: Land Use Modellingmentioning

confidence: 99%

Contribution of land use changes to future flood damage along the river Meuse in the Walloon region

Beckers

Dewals²,

Erpicum³

et al. 2013

Nat. Hazards Earth Syst. Sci.

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“…In the spatial allocation model, the relationships between land use and independent variables are evaluated using logistic regression. A spatially explicit procedure is used to create the Land Use Scanner model, in which the residential land use demand on spatial units is allocated [219,220]. In the Land Use Scanner model, a logistic regression is applied to empirically specify weights for the preparation of suitability maps.…”

Section: Linear/logistic Regressionmentioning

confidence: 99%

Urban Growth Prediction: A Review of Computational Models and Human Perceptions

Triantakonstantis¹,

Mountrakis²

2012

JGIS

122

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Human population continues to aggregate in urban centers. This inevitably increases the urban footprint with significant consequences for biodiversity, climate, and environmental resources. Urban growth prediction models have been extensively studied with the overarching goal to assist in sustainable management of urban centers. Despite the extensive body of research, these models are not frequently included in the decision making process. This review aims on bringing this gap by analyzing results from a survey investigating developer and user perceptions from the modeling and planning communities, respectively. An overview of existing models, including advantages and limitations, is also provided. A total of 156 manuscripts is identified. Analysis of aggregated statistics indicates that cellular automata are the prevailing modeling technique, present in the majority of published works. There is also a strong preference for local or regional studies, a choice possibly related to data availability. The survey found a strong recognition of the models’ potential in decision making, but also limited agreement that these models actually reach that potential in practice. Collaboration between planning and modeling communities is deemed essential for transitioning models into practice. Data availability is considered a stronger restraining factor by respondents with limited algorithmic experience, which may indicate that model input data are becoming more specialized, thus significantly limiting wide-spread applicability. This review assesses developer and user perceptions and critically discusses existing urban growth prediction models, acting as a reference for future model development. Specific guidelines are provided to facilitate transition of this relatively mature science into decision making activities <p> </p>

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“…• developed a land-use model to analyse water management implications of climate change in the Elbe catchment as part of the German Federal Ministry of Education and Research funded project GLOWA-ELBE Hoymann, 2010 …”

Section: Supporting International Model Developmentmentioning

confidence: 99%

Land Use and Climate Change

Orr

2008

Conservation Biology

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Spatial Allocation of Future Residential Land Use in the Elbe River Basin

Cited by 27 publications

References 21 publications

Contribution of land use changes to future flood damage along the river Meuse in the Walloon region

Contribution of land use changes to future flood damage along the river Meuse in the Walloon region

Urban Growth Prediction: A Review of Computational Models and Human Perceptions

Land Use and Climate Change

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