A travel time-based variable grid approach for an activity-based cellular automata model

Urban growth and population growth are used in numerous models to determine their potential impacts on both the natural and the socio-economic systems. Cellular automata (CA) land-use models became popular for urban growth modelling since they predict spatial interactions between different land uses in an explicit and straightforward manner. A common deficiency of land-use models is that they only deal with abstract categories, while in reality, several activities are often hosted at one location (e.g. population, employment, agricultural yield, nature…). Recently, a multiple activity-based variable grid CA model was proposed to represent several urban activities (population and economic activities) within single model cells. The distance-decay influence rules of the model included both short- and long-distance interactions, but all distances between cells were simply Euclidean distances. The geometry of the real transportation system, as well as its interrelations with the evolving activities, were therefore not taken into account. To improve this particular model, we make the influence rules functions of time travelled on the transportation system. Specifically, the new algorithm computes and stores all travel times needed for the variable grid CA. This approach provides fast run times, and it has a higher resolution and more easily modified parameters than the alternative approach of coupling the activity-based CA model to an external transportation model. This paper presents results from one Euclidean scenario and four different transport network scenarios to show the effects on land-use and activity change in an application to Belgium. The approach can add value to urban scenario analysis and the development of transport- and activity-related spatial indicators, and constitutes a general improvement of the activity-based CA model

High-resolution simulations of population-density change with an activity-based cellular automata land-use model

The MOLAND model is a cellular automata (CA) land-use change model that has often been applied to simulate urban growth. A more recent alternative model makes the simulations more multifunctional by also computing different activities (population and employment) for every cell. However, the equation to update population density in time in this activity-based CA model could not deal with high population growth rates in some existing urban centres. Therefore, we experimented with two alternative equations. A semi-automated calibration routine was used to compare errors of the different model versions at a continuous range of resolutions in two study areas: the Greater Dublin Region, Ireland, and Flanders and Brussels, Belgium. The two new population density equations turn out to solve the particular problem of fast changes in high-density neighbourhoods and generally improve regional errors in the Belgian application, but can unfortunately introduce larger errors in low-density areas or in the land-use simulations

Eutrophication problems, causes and potential solutions, and exchange of reusable model building components for the integrated simulation of coastal eutrophication. ISECA Final Report D3.2

This report summarizes the stages of coastal and offshore eutrophication, followed by a description of the European indicators and institutional framework for marine eutrophication assessment. A summary is given of a number of biogeochemical models available to describe the process of eutrophication in the North Sea, and the model for atmospheric inputs which was developed in the ISECA project (see the Action 3 Report – Atmospheric Modelling for more details on this work). Furthermore, the report compares different solutions aimed at reducing the nitrogen inputs from the Scheldt basin, using the nitrogen apportionment model which was developed in the EU-FP6 project SPICOSA (www.spicosa.eu). The report is concluded with a discussion on the principles of component-based modelling and model libraries, using examples for the Scheldt model, and a general discussion on some challenges of modelling marine eutrophication

Подсистема автономного программно-аппаратного комплекса для индуктивного долгосрочного прогноза осредненных значений метеопараметров

The research of the inductive method of long-term (forestalling to 0,5 year) prognosis of average decade air s temperature on the basis of principle of analogies was executed and it s sufficient was shown. The research of the offered approach was also conducted: in the base of spatial models without principle of analogies; in the polynomial harmonic base; the analysis of middle quality of the inductive prognostic method for cases of the analogue principle usage and without it

Further developments of a fuzzy set map comparison approach

Fuzzy set map comparison offers a novel approach to map comparison. The approach is specifically aimed at categorical raster maps and applies fuzzy set techniques, accounting for fuzziness of location and fuzziness of category, to create a similarity map as well as an overall similarity statistic: the Fuzzy Kappa. To date, the calculation of the Fuzzy Kappa (or K-fuzzy) has not been formally derived, and the documented procedure was only valid for cases without fuzziness of category. Furthermore, it required an infinitely large, edgeless map. This paper presents the full derivation of the Fuzzy Kappa; the method is now valid for comparisons considering fuzziness of both location and category and does not require further assumptions. This theoretical completion opens opportunities for use of the technique that surpass the original intentions. In particular, the categorical similarity matrix can be applied to highlight or disregard differences pertaining to selected categories or groups of categories and to distinguish between differences due to omission and commission

Further developments of a fuzzy set map comparison approach

Fuzzy set map comparison offers a novel approach to map comparison. The approach is specifically aimed at categorical raster maps and applies fuzzy set techniques, accounting for fuzziness of location and fuzziness of category, to create a similarity map as well as an overall similarity statistic: the Fuzzy Kappa. To date, the calculation of the Fuzzy Kappa (or K-fuzzy) has not been formally derived, and the documented procedure was only valid for cases without fuzziness of category. Furthermore, it required an infinitely large, edgeless map. This paper presents the full derivation of the Fuzzy Kappa; the method is now valid for comparisons considering fuzziness of both location and category and does not require further assumptions. This theoretical completion opens opportunities for use of the technique that surpass the original intentions. In particular, the categorical similarity matrix can be applied to highlight or disregard differences pertaining to selected categories or groups of categories and to distinguish between differences due to omission and commission

The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics

A cellular automaton is specified to give a spatially detailed represenation of the evolution of urban land-use patterns. Cell states represent land uses, and transition rules express the likelihood of a change from one state to another as a function both of existing land use in the 113-cell neighbourhood of the cell and of the inherent suitability of the cell for each possible use. The model is used to simulate the land-use pattern of Cincinnati, Ohio. The simulation results are realistic and sensitivity analysis shows that the predictions of the model are relatively accurate and reproducible, thus suggesting that cellular automata - based models may be useful in a planning context.

Development of an Activity-based Cellular Automata Land-use Model: the case of Flanders, Belgium

Cellular automata (CA) models are increasingly applied for simulating land-use change in urban areas. However, in areas with strongly mixed land uses, like Flanders, Belgium, different types and intensities of human activity occur within a single dominant land use. This is in conflict with the discrete and dominant land-use states applied in CA. The direct modelling of the intensity of activities (population density and employment in different sectors) within a CA grid environment is an interesting alternative to model mixed and multifunctional land use. In this research, an activity-based cellular automata (ACA) model, developed by White et al. [2012] will be further enhanced, applied and calibrated for Flanders. Its resolution will be increased to 1 ha to effectively address environmental, socio-economic and spatial planning problems. It should be able to cope with the complex multi-nodal structure and messy urbanised morphology of Flanders, typified as it is by multifunctional land use and diffuse, fragmented urban development strung out along roads. This paper shows the results of an initial application of the model of White et al. to a sub-region of Flanders and discusses how the model should be further developed in the future. The effect of diseconomies of agglomeration, accounting for high costs and congestion in dense urban areas, was investigated, as well as the capacity of the ACA to allocate both activity-based land uses and non-activity based land uses (e.g. protected nature)

The Environment Explorer. Technical Documentation

This report forms the technical documentation of the Environment Explorer version 2.0. The Environment Explorer is being developed for rapid, integrated assessments of the effects of different spatial policy options based on economic, social and ecological values. It works by sketching the spatial developments, land-use transformations and effects for the Netherlands on a set of indicators up to 2030 under given demographic and economic prognoses.Dit rapport vormt de technische documentatie van de LeefOmgevingsVerkenner, versie 2.0. De LeefOmgevingsVerkenner wordt ontwikkeld in opdracht van de directie van het RIVM. Het beoogt een modelsysteem te zijn om snel, interactief de effecten van (alternatieve) beleidsopties en autonome ontwikkeling op de kwaliteit van de leefomgeving te verkennen. Hiertoe schetst de LeefOmgevingsVerkenner eerst de ruimtelijke ontwikkeling van Nederland: wie doet wat waar? Waarna de mogelijke positieve of negatieve effecten van deze activiteiten op de leefomgeving bepaald kunnen worden. Er wordt een beschrijving gegeven van de belangrijkste uitgangspunten en overwegingen die in de opzet van het systeem zijn meegenomen, de werking van het macromodel, het micromodel, de huidige set met indicatoren alsook de operationalisatie van het systeem zoals die in het project Kaartbeelden is toegepast