Modelling potential movement in constrained travel environments using rough space-time prisms

The widespread adoption of location-aware technologies (LATs) has afforded analysts new opportunities for efficiently collecting trajectory data of moving individuals. These technologies enable measuring trajectories as a finite sample set of time-stamped locations. The uncertainty related to both finite sampling and measurement errors makes it often difficult to reconstruct and represent a trajectory followed by an individual in space-time. Time geography offers an interesting framework to deal with the potential path of an individual in between two sample locations. Although this potential path may be easily delineated for travels along networks, this will be less straightforward for more nonnetwork-constrained environments. Current models, however, have mostly concentrated on network environments on the one hand and do not account for the spatiotemporal uncertainties of input data on the other hand. This article simultaneously addresses both issues by developing a novel methodology to capture potential movement between uncertain space-time points in obstacle-constrained travel environments

Individual accessibility and travel possibilities: A literature review on time geography

In the late 1960s, Torsten Hägerstrand introduced the conceptual framework of time geography which can be deemed an elegant tool for analysing individual movement in space and time. About a decade later, the auspicious time-geographic research has gradually lost favour, mainly due to the unavailability of robust geocomputational tools and the lack of georeferenced individual-level travel data. It was only from the early 1990s that new GISbased research gave evidence of resurgence in popularity of the field. From that time on, several researchers have steadily been publishing work at the intersection of time geography, disaggregate travel modeling, and GI-science. This paper reviews the most important timegeographic contributions. From this exercise, some prevailing research gaps are deduced and a way to deal with these gaps is presented. In particular, we focus on space-time accessibility measures, geovisualisation of activity patterns, human extensibility and fuzzy space-time prisms in relation to CAD

Strategies to mitigate greenhouse gas and nitrogen emissions in Swiss agriculture: the application of an integrated sector model

Environmental impacts of agricultural production, such as greenhouse gas (GHG) and nitrogen emissions, are of major concern for scientists and policy makers throughout the world. Global agricultural activities account for about 60% of nitrous oxide and about 50% of methane emissions. From a global perspective, methane and nitrous oxide constitute crucial GHGs. They contribute substantially to climate change due to their high potential for effecting global warming compared to carbon dioxide. Emissions of these gases depend on the extent of agricultural production and applied technologies. Therefore, analysis of potential mitigation opportunities is challenging and requires an integrated approach in order to link agricultural economic perspectives to environmental aspects. In view of this, a mathematical programming model has been developed which enables assessment of cost-effective strategies for mitigating GHG and nitrogen emissions in the agricultural sector in Switzerland. This model is applied to improve understanding of the agricultural sector and its behavior with changing conditions in technology and policy. The presented recursive-dynamic model mimics the structure and inter- dependencies of Swiss agriculture and links that framework to core sources of GHG and nitrogen emissions. Calculated results for evaluation and application indicate that employed flexibility constraints provide a feasible approach to sufficiently validate the described model. Recursive-dynamic elements additionally enable adequate modeling of both an endogenous development of livestock dynamics and investments in buildings and machinery, also taking sunk costs into account. The presented findings reveal that the specified model approach is suitable to accurately estimate agricultural structure, GHG and nitrogen emissions within a tolerable range. The model performance can therefore be described as sufficiently robust and satisfactory. Thus, the model described here appropriately models strategies for GHG and nitrogen abatement in Swiss agriculture. The results indicate that there are limits to the ability of Swiss agriculture to contribute substantially to the mitigation of GHG and nitrogen emissions. There is only a limited level of mitigation available through technical approaches, and these approaches have high cost.resource use, environmental economics, greenhouse gas emission, nitrogen emission, integrated modeling

Statistical modelling of software reliability

During the six-month period from 1 April 1991 to 30 September 1991 the following research papers in statistical modeling of software reliability appeared: (1) A Nonparametric Software Reliability Growth Model; (2) On the Use and the Performance of Software Reliability Growth Models; (3) Research and Development Issues in Software Reliability Engineering; (4) Special Issues on Software; and (5) Software Reliability and Safety

Impacts of the Farm Input Subsidy Programme in Malawi: Informal Rural Economy Modelling

This paper presents a partial equilibrium model of the impacts of the Malawi Farm Input Subsidy Programme on smallholder livelihoods in two major and contrasting livelihood zones over the period 2005/6 to 2010/11. Despite inherent difficulties in modelling the multi-scale and complex relationships that are involved, model findings show direct impacts on subsidy recipients (increasing maize production and real incomes), differences between poorer and less poor households (with poorer households normally gaining more proportionally but not necessarily absolutely from the same subsidy package), and differences between central and southern region maize growing areas with different rates of poverty incidence and land pressure (with greater absolute and proportional gains in poorer southern region areas). The results also show the impacts of the programme on wages and maize prices. However, a significant finding of model simulations is that beneficial indirect effects may be greater than direct impacts in maize growing areas with high rates of poverty incidence and high land pressure. These indirect effects arise through increases in the ratio of wages to maize prices, and benefit poorer households (who sell ganyu labour and buy maize) while potentially harming in the short term the incomes of less poor buyers of ganyu labour and sellers of maize (these households should however gain in the medium and long run from increased livelihood opportunities with wider economic growth). This finding has important implications for programme design, implementation and evaluation. Much more emphasis should be placed on ensuring that the programme and other policies are managed to maximise these indirect benefits, and on assessing these benefits in programme evaluation. There are particular implications for the design and management of area and household targeting and graduation