Suchergebnisse

The land market in the Netherlands seems to get much attention the last few years. Increasing land use pressure caused by a high population density and an increasing economic growth and prosperity result in competing land use claims from a range of sectors. Strict planning schemes segment the land market into sub markets and create an artificial scarcity of land for some land use types, which results in large price differences between the segments. Decisions of the government for designating housing areas, creating nature areas and expanding infrastructure aim at optimal land use with the least negative externalities, but result sometimes in speculation or unwanted situations on the land market. Additionally, the impact of European policies on the land market is still increasing. This raises discussions on the functioning of the land market. In order to get a better understanding of the land market, this study aims at developing a GIS-based explanatory model for rural land prices. Factors that affect rural land prices are collected, analysed, categorised, and used to explain spatial differences in prices of parcels of land in rural areas. Special attention is paid to modelling the effect of governmental policies like zoning and taxing can be analysed with the model. The current model is based on data for the province of Noord-Brabant in the southern part of the Netherlands. For this province data on parcel level is available. Using a geographical information system (GIS) this data can be combined with a rich set of spatial data. The resulting model can be used to carry out case studies like studying the effect of relocation of farmers or the effect of land purchases by the government.

Governments face the daunting task of developing policies and making investment decisions for climate change adaptation in an environment that consist of complex, interlinked systems with manifold uncertainties. Instead of responding to surprises and making decisions on ad hoc basis, a structured approach to deal with complex systems and uncertainties can provide indispensable support for policy making. This contribution proposes a structured approach for designing climate adaptation policies based on the concepts of Adaptation Pathways, Adaptive Policy Making, and Real Options Analysis. Such an approach results in incorporation of flexibility that allows change over time in response to how the future unfolds, what is learned about the system, and changes in societal preferences. The approach is illustrated by looking at drainage policies and measures to address flooding in Singapore.

Complex engineering systems are usually designed to last for many years. Such systems will face many uncertainties in the future. Hence the design and deployment of these systems should not be based on a single scenario, but should incorporate flexibility. Flexibility can be incorporated in system architectures in the form of options that can be exercised in the future when new information is available. Incorporating flexibility comes, however, at a cost. To evaluate if this cost is worth the investment a real options analysis can be carried out. This approach is demonstrated through analysis of a case study of a previously developed static system‐of‐systems for maritime domain protection in the Straits of Malacca. This article presents a framework for dynamic strategic planning of engineering systems using real options analysis and demonstrates that flexibility adds considerable value over a static design. In addition to this it is shown that Monte Carlo analysis and genetic algorithms can be successfully combined to find solutions in a case with a very large number of possible futures and system designs.

Abstract
Showering is one of the most water-intensive behaviours in urban households, accounting for 20–30% of water use. Real-time feedback from smart devices has been proven to significantly reduce water consumption in showers. Still, it is not known whether these devices have spillover effects on other water use behaviours. For the first time, we provide empirical evidence for a significant and negative within-domain spillover effect from the use of such devices, showing an increase in water use in other activities by 2.5% per day per household. Up to one-third of conservation effects are eroded by such spillovers, resulting in a two steps forward, one step back situation. Overall, however, net water use is still reduced by 4.7% in the 385 households that were observed. This study points out an important behavioural limit on the use of such smart shower devices and suggests that such use be accompanied by informational or other campaigns to reduce the large negative spillovers.