Academic literature on the topic 'City planning Australia Mathematical models'

The rapid growth of wireless communication technologies has increased the importance of a proper network planning. Before the actual installation of the network and to ensure that the network is adequately covered, network designers rely heavily on wave propagation models, which are a set of mathematical expressions, and graphs derived from comprehensive field measurements and it is used to represent radio wave properties of a particular environment. The research aims to find a mathematical model to predict the propagation path loss of radio waves in Sana'a city for the appropriate planning of cellular communication systems. In this sense, the researcher applied a practical study to the city of Sana'a by taking three cells (base station) in three different regions (urban and suburban areas and the open area). The research focuses on three stages (the stage of measurements, the stage of analysis and the stage of analysis and comparison). In the results, we obtained three values for path loss constants a and c for the three regions, through which we obtain the logarithmic curves, which in turn has been transformed into mathematical models to be used as a reference for radio planning engineers in the city of Sana'a, the capital of the Republic of Yemen.

The relevance of this study is determined by the need to develop technologies for effective urban systems management and resolution of urban planning conflicts. The paper presents an algorithm for analyzing urban planning conflicts. The material for the study was data from social networks, microblogging, blogs, instant messaging, forums, reviews, video hosting services, thematic portals, online media, print media and TV related to the construction of the North-Eastern Chord (NEC) in Moscow (RF). To analyze the content of social media, a multimodal approach was used. The paper presents the results of research on the development of methods and approaches for constructing mathematical and neural network models for analyzing the social media users’ perceptions based on their digital footprints. Artificial neural networks, differential equations, and mathematical statistics were involved in building the models. Differential equations of dynamic systems were based on observations enabled by machine learning. Mathematical models were developed to quickly detect, prevent, and address conflicts in urban planning in order to manage urban systems efficiently. In combination with mathematical and neural network model the developed approaches, made it possible to draw a conclusion about the tense situation around the construction of the NEC, identify complaints of residents to constructors and city authorities, and propose recommendations to resolve and prevent conflicts. Research data could be of use in solving similar problems in sociology, ecology, and economics.

A core contemporary planning approach is the promotion of transit-oriented developments (TODs) and in recent times cities have committed substantial financial investment to encourage sustainable precincts around public transport. Evaluation of the success of TODs is key for continuing the planning efforts. A frequently applied framework for characterizing TODs draws on Bertolini’s Node-Place (N-P) model, enriched through application in various contexts. We offer here an extension to the N-P model, using a case study in a low-density city, Perth, Western Australia. A typology of railway stations is developed using 43 indicators and then linear models are applied to ascertain the association between patronage and station precinct features. The results show that various types of measures are required to increase public transport ridership for the four clusters that emerged from the analysis. Density alone does not lead to increased use of public transport; it must be associated with city-wide accessibility, as well as access/egress to and from the station.

The article starts with looking into a treatment of the objects of city transport systems planning: administrative (determined) and systematic approach, that are of importance for the principles of planning and its quality. The major shortages of the traditional planning are the following: its determination, narrow functional attitude towards the processes of transportation, lack of evaluation of the interrelations between a city structure and its transport system. There are several obstacles to shift to the planning of higher quality, namely poorly arranged information supply, shortage of mathematical models for transport processes and relevant soft ware. Considering the gained experience of transport system planning and professional knowledge on transport systems, a new methodology of planning is presented. A major stress here is put on the complex of transport system functioning, the consequences and the price.

At the moment, there is a large number of dissertations and scientific works covering the issues of traction-speed and fuel-economic characteristics of vehicles, the results of which are presented in the form of: regression models, approximating dependencies, mathematical models based on multivariate analysis, including a number of additional coefficients. In this connection, the use of the results of these works in practice is limited, since it requires high qualifications of the МTЕ personnel and the use of special software and hardware. At the same time, at the department “Automobile transport” NSTU named after R. E. Alekseev developed a probabilistic-analytical method for predicting fuel consumption by road trains, considering the high-speed mode of movement, which shows a high convergence of results with actual average speeds only for uniform movement of buses with a constant average speed, which is not applicable to the assessment of fuel consumption of city buses. Based on the hypothesis put forward on the applicability of the Weibull-Gnedenko distribution for calculating the average speeds of city buses and the normal distribution for calculating accelerations during movement, the tasks of this study are formulated, expressed in the development of mathematical models reflecting the dependences of speeds and accelerations during bus movement in urban operating conditions, for planning their fuel consumption. To solve the set tasks, the following experimental studies were carried out: determination of the average coefficient of total road resistance; the actual distribution of speeds and accelerations when driving city buses; determination of the average actual value of fuel consumption when the bus is moving and when idle at stopping points. Based on the results of processing experimental studies, the possibility of using the Weibull-Gnedenko law to describe the actual speeds in urban conditions and the normal law to describe accelerations when driving city buses was confirmed, which allows planning fuel consumption using the analytical apparatus of the theory of probability and mathematical statistics and using the developed methodology in practice of motor transport enterprises. Based on experimental studies and theoretical studies in this area, an analytical method for planning fuel consumption for city buses, considering the speed of their movement, has been developed, which allows planning fuel consumption without additional experiments. Carrying out such studies for other types of motor vehicles and assessing unaccounted for indicators of road, transport and natural-climatic operating conditions will create a generalized analytical method for planning fuel consumption by vehicles in various operating conditions.

This paper compared two different models for predicting traffic counts based on land use and demographic variables for the City of Calgary. Land use and demographic characteristics were used as independent vari ables at the Dissemination Area (DA) (small geographic unit having a population range of 400–700) level in the City of Calgary. Traffic count data from the City of Calgary were used as the dependent variable to devel op statistical and Neural Network models. Negative Binomial count statistical models (with log-link) were developed, as data were observed to be over-dispersed. Neural Network models were developed based on a mul tilayered, feed-forward, back-propagation design for supervised learning. The results indicate that Neural Network models ensured fewer errors than the statistical model. Overall, the Neural Network model yielded better results in estimating traffic count than the Negative Binomial Regression approach also considered in this study. The Neural Network model can be particularly suitable for its better predictive capability. However, the statistical model could be used for mathematical formulation or for developing a better understanding of the role of explanatory variables in estimating traffic count.

Abstract. Urban digital twins have been increasingly adopted by cities worldwide. Digital twins, especially semantic 3D city models as key components, have quickly become a crucial platform for urban monitoring, planning, analyses and visualization. However, as the massive influx of data collected from cities accumulates quickly over time, one major problem arises as how to handle different temporal versions of a virtual city model. Many current city modelling deployments lack the capability for automatic and efficient change detection and often replace older city models completely with newer ones. Another crucial task is then to make sense of the detected changes to provide a deep understanding of the progresses made in the cities. Therefore, this research aims to provide a conceptual framework to better assist change detection and interpretation in virtual city models. Firstly, a detailed hierarchical model of all potential changes in semantic 3D city models is proposed. This includes appearance, semantic, geometric, topological, structural, Level of Detail (LoD), auxiliary and scoped changes. In addition, a conceptual approach to modelling most relevant stakeholders in smart cities is presented. Then, a model - reality graph is used to represent both the different groups of stakeholders and types of changes based on their relative interest and relevance. Finally, the study introduces two mathematical methods to represent the relevance relations between stakeholders and changes, namely the relevance graph and the relevance matrix.

In recent times, residential districts in modern cities face certain new and undesired problems related to antisocial behaviour by adolescents in its urban public spaces. In this study, we investigate the relationship between the design features of public spaces in residential areas and the problem of vandalism within the districts. This paper examines the current literature reviews on vandalism, the main reasons behind the increase of in the problem, types of vandalism, and a mathematical model for assessing visibility and accessibility in addition to proving the results of a field study conducted in a UAE city. We believe that visibility of vandalism-prone areas through dwelling windows, accessibility of such areas by residents through dwelling entrances, and recognition of ownership of such areas can definitely play a role in mitigating vandalism. Our findings indicated the following: (1) There is a strong relationship between vandalism and visibility through dwelling windows. (2) Residents' accessibility to dwelling entrances and recognition of ownership play an important role in reducing vandalism. (3) In areas where the visibility and accessibility by residents is low, the severity of the problem of vandalism increase if there is an increase in the percentage of adolescent residents. (4) The design characteristics of the housing areas, such as the height of the blocks or the limits of public spaces, do not have any influence on the occurrence of vandalism.

Tourism is the major industry in the Huangshan city. This paper examines time series of tourism to Huangshan from 1979 to 2004. The yearly data set comprises the total arrivals of tourists and total income. A mathematical model which is based on the polynomial approximation and radial basis function is set up to model the tourist flow. The total income and expenditure per tourist are also modeled. The established mathematical models can be used to forecast the tourist flow so that proper planning and management can be arranged.

The creation of augmented reality-related geographic information system (GIS) mapping applications has witnessed considerable advances in the technology of urban modeling; however, there are limitations to the technology that is currently used to create similar resources. The cost of the creation of the vehicle is an obstacle, and the rendering of textures of buildings is often lacking because of the distortion caused by the types of lenses that have been used. Generally, mobile mapping systems (MMSs) can extract detailed three-dimensional (3D) data with high quality texture information of the 3D building model. However, mapping urban areas by MMSs is expensive and requires advanced mathematical approaches with complicated steps. In particular, commercial MMS, which generally includes two GPS receivers, is an expensive device, costing ~$1 million. Thus, this research is aimed at developing a new MMS that semi-automatically produces high-quality texture information of 3D building models proposes a 3D urban model by hybrid approaches. Eventually, this study can support urban planners and people to improve their spatial perception and awareness of urban area for Smart City Planning.

[Formulae and special characters can only be approximated here. Please see the pdf version of the abstract for an accurate reproduction.] This thesis reviews, extends and applies to urban traffic analysis the entropy concept of Shannon and Luce's mathematical psychology in a fairly complex and mathematically demanding model of human decision making, if it is solved as a deeply nested structure of logit calculus. Recognising consumers' different preferences and the universal propensity to seek the best choice when going to some desired goal (k), a transparent mathematical program (MP) is developed: the equivalent of a nested multinomial logit model without its inherent computational difficulty. The MP model makes a statistical assessment of individual decisions based on a randomised (measurable) utility within a given choice structure: some path through a diagram (Rk, Dk), designed a priori, of a finite number of sequential choices. The Equivalence Theorem (ET) formalises the process and states a non-linear MP with linear constraints that maximises collective satisfaction: utility plus weighted entropy, where the weight (1/θn) is a behavioural parameter to be calibrated in each case, eg for the Perth CBD. An optimisation subject to feasible routes through the (Rk, Dk) network thus captures the rational behaviour of consumers on their individually different best-choice decision paths towards their respective goals (k). This theory has been applied to urban traffic assignment before: a Stochastic User Equi-librium (SUE). What sets this thesis apart is its focus on MP models that can be solved with standard Operations Research software (eg MINOS), models for which the ET is a conditio sine qua non. A brief list of SUE examples in the literature includes Fisk's logit SUE model in (impractically many) route flows. Dial's STOCH algorithm obviates path enumeration, yet is a logit multi-path assignment procedure, not an MP model; it is nei-ther destination oriented nor an optimisation towards a SUE. A revision of Dial's method is provided, named STOCH[k], that computes primal variables (node and link flows) and Lagrangian duals (the satisfaction difference n→k). Sheffi & Powell presented an unconstrained optimisation problem, but favoured a probit SUE, defying closed formulae and standard OR software. Their model corresponds to the (constrained) dual model here, yet the specifics of our primary MP model and its dual are possible only if one restricts himself to logit SUE models, including the ET, which is logit-specific. A real world application needs decomposition, and the Perth CBD example is iteratively solved by Partial Linearisation, switching from (measured) disutility minimisation to Sheffi & Powell's Method of Successive Averages near the optimum. The methodology is demonstrated on the Perth Central Business District (CBD). To that end, parameter Θ is calibrated on Main Roads' traffic count data over the years 1997/98 and 1998/99. The method is a revision of Liu & Fricker's simultaneous estimation of not only Θ but an appropriate trip matrix also. Our method handles the more difficult variable costs (congestion), incomplete data (missing observations) and observation errors (wrong data). Finally, again based on Main Roads' data (a sub-area trip matrix), a Perth CBD traffic assignment is computed, (a) as a logit SUE and - for comparison - (b) as a DUE (using the PARTAN method of Florian, Guélat and Spiess). The results are only superficially similar. In conclusion, the methodology has the potential to replace current DUE models and to deepen transport policy analysis, taking into account individual behaviour and a money-metric utility that quantifies 'social benefits', for instance in a cost-benefit-analysis.

Conservation science in rivers is still lagging behind its terrestrial and marine counterparts, despite increasing threats to freshwater biodiversity and extinction rates being estimated as five times higher than in terrestrial ecosystems. Internationally, most protected rivers have been assigned reserve status in the framework of terrestrial conservation plans, neglecting catchment effects of disturbance. While freshwater conservation tools are mainly index based (e.g. richness, rarity), modern terrestrial and marine conservation planning methods use complementarity-based algorithms - proven to be most efficient at protecting a large number of taxa for the least cost. The few complementarity-based lotic conservation efforts all use broad river classifications instead of biota as targets, a method heavily disputed in the literature. They also ignore current condition and future vulnerability. It was the aim of this thesis to develop a framework for conservation planning that: a) accounts for the connected nature of rivers b) is complementarity based and uses biota as targets c) integrates current status and future vulnerability I developed two different approaches using macroinvertebrate datasets from Australia, Canada and the USA. The first new method was a site/based two-tiered approach integrating condition and conservation value, based on RIVPACS/AUSRIVAS � a modelling technique that predicts macroinvertebrate composition. The condition stage assesses biodiversity loss by estimating a site-specific expected assemblage and comparing it to the actual observed assemblage. Sites with significant biodiversity loss are flagged for restoration, or other management actions. All other sites progress to the conservation stage, in which an index of site-specific taxonomic rarity is calculated. This second index (O/E BIODIV) assesses the number of rare taxa (as defined by <50% probability of occurrence). Using this approach on a dataset near Sydney, NSW, Australia, I was able to identify three regions: 1) an area in need of restoration; 2) a region of high conservation value and 3) an area that had high conservation potential if protection and restoration measures could counteract present disturbance. However, a second trial run with three datasets from the USA and Canada highlighted problems with O/E (BIODIV). If common taxa are predicted at lower probabilities of occurrence (p<50%) because of model error, they enter the index and change O/E (BIODIV). Therefore, despite an attractive theoretical grounding, the application of O/E (BIODIV) will be restricted to datasets where strong environmental gradients explain a large quantity of variation in the data and permit accurate predictions of rare taxa. It also requires extensive knowledge of regional species pools to ensure that introduced organisms are not counted in the index. The second approach was a proper adaptation of terrestrial complementarity algorithms and an extension to the Irreplaceability-Vulnerability framework by Margules and Pressey (2000). For this large-scale method, distributions for 400 invertebrate taxa were modeled across 1854 subcatchments in Victoria, Australia using Generalised Additive Models (GAMs). The best heuristic algorithm to estimate conservation value was determined by calculating the minimum area needed to cover all 400 taxa. Solutions were restricted to include rules for the protection of whole catchments upstream of a subcatchment that contained the target taxon. A summed rarity algorithm proved to be most efficient, beating the second best solution by 100 000 hectares. To protect 90% of the taxa, only 2% of the study area need to be protected. This increases to 10% of the study area when full representation of the targets is required. Irreplaceability was calculated by running the heuristic algorithm 1000 times with 90% of the catchments randomly removed. Two statistics were then estimated: f (the frequency of selection across 1000 runs) and average c (contribution to conservation targets). Four groups of catchments were identified: a) catchments that have high contributions and are always selected; b) catchments that have high contributions and are not always selected; c) catchments that are always chosen but do not contribute many taxa; d) catchments that are rarely chosen and did not contribute many taxa. Summed c, the sum of contributions over 1000 runs was chosen as an indicator of irreplaceability, integrating the frequency of selection and the number of taxa protected. Irreplaceability (I) was then linked to condition (C) and vulnerability (V) to create the ICVframework for river conservation planning. Condition was estimated using a stressor gradient approach (SGA), in which GIS layers of disturbance were summarised to three principal axes using principal components analysis (PCA). The main stressor gradient � agriculture � classified 75% of the study area as disturbed, a value consistent with existing assessments of river condition. Vulnerability was defined as the likelihood that land use in a catchment would intensify in the future. Hereby current tenure was compared to land capability. If a catchment would support a land use that would have a stronger effect on the rivers than its current tenure, it was classified as vulnerable. 79% of catchments contained more than 50% vulnerable land. When integrating the three estimators in the ICV-framework, seven percent of catchments were identified as highly irreplaceable but in degraded condition. These were flagged for urgent restoration. Unprotected, but highly irreplaceable and highly vulnerable catchments that were still in good condition made up 2.5% of the total area. These catchments are prime candidates for river reserves. The ICV framework developed here is the first method for systematic conservation planning in rivers that is complementarity-based, biota-driven but flexible to other conservation targets and accounts for catchment effects, thus fulfilling all the gaps outlined in the aims.

[Truncated abstract] Air pollution is increasingly perceived to be a serious intangible threat to humanity, with air quality continuing to deteriorate in most urban areas. The main sources of inner city pollution are motor vehicles, which generate emissions from the tail pipe as well as by evaporation. These contain toxic gaseous components which have adverse health effects. The major components are carbon monoxide (CO), nitrogen dioxide (NO2), nitric oxide (NO), sulphur dioxide (SO2), particulates (PM10), and volatile organic compounds (VOC). CO and oxides of nitrogen (NOx) are major emissions from cars. This study focuses on pollutant concentration in Perth city and has sought to develop measures to improve air quality. To estimate concentrations, the study develops air pollution models for CO and NOx; on the basis of the model estimates, effective policy is devised to improve the air quality by managing travel to the city. Two peaks, due to traffic, are observed in hourly CO and NOx concentrations. Unlike traffic, however, the morning peak does not reach the level of the afternoon peak. The reasons for this divergence are assessed and quantified. Separate causal models of hourly concentrations of CO and NOx explain their fluctuations accurately. They take account of the complex effects of the urban street canyon and winds in the city. The angle of incidence of the wind has significant impact on pollution level; a wind flow from the south-west increases pollution and wind from the north-east decreases it. The models have been shown to be equivalent to engineering and scientific models in estimating emission rate in the context of street canyons. However the study models are much more precise in the Perth context. ... The models are used to calculate the marginal effects for all attributes and elasticity for fuel price. In almost all attributes the non-work group is more responsive than the work group. Finally, the SP model results are integrated into an econometric model for the purpose of prediction. The travel behaviour prediction is used to estimate the policy impact on air quality. The benefit from the air quality improvement is reported in terms of life saved. The estimated relationships between probability of death and air pollution determines the number of lives that could be saved under various policy scenarios. A ratio of benefits to the financial and perceived sacrifices by drivers is calculated to compare the effectiveness of the suggested policies. A car size charge policy was found to be the most cost effective measure to ameliorate the environmental impact of cars in Perth, with a morning peak entry time charge being almost as cost effective. The study demonstrates the need for appropriate modelling of air pollution and travel behaviour. It brings together analytical methods at three levels of causality, vehicle to air pollution, charge to travel response, and air pollution to health.

Thesis (MSc (Geography and Environmental Studies))--Stellenbosch University, 2008.
Accelerating urban growth places increasing pressure not only on the efficiency of infrastructure and service provision, but also on the natural environment. City managers are delegated the task of identifying problem areas that arise from this phenomenon and planning the strategies with which to alleviate them. It is with this in mind that the research investigates the implementation of an urban growth model, SLEUTH, as a support tool in the planning and decision making process. These investigations are carried out on historical urban data for the region falling under the control of the Cape Metropolitan Authority. The primary aim of the research was to simulate future urban expansion of Cape Town based on past growth patterns by making use of cellular automata methodology in the SLEUTH modeling platform. The following objectives were explored, namely to: a) determine the impact of urbanization on the study area, b) identify strategies for managing urban growth from literature, c) apply cellular automata as a modeling tool and decision-making aid, d) formulate an urban growth policy based on strategies from literature, and e) justify SLEUTH as the desired modeling framework from literature. An extensive data base for the study area was acquired from the product of a joint initiative between the private and public sector, called “Urban Monitoring”. The data base included: a) five historical urban extent images (1977, 1988, 1993, 1996 and 1998); b) an official urban buffer zone or ‘urban edge’, c) a Metropolitan Open Space System (MOSS) database, d) two road networks, and d) a Digital Elevation Model (DEM). Each dataset was converted to raster format in ArcEdit and finally .gif images were created of each data layer for compliance with SLEUTH requirements. SLEUTH processed this historic data to calibrate the growth variables for best fit of observed historic growth. An urban growth forecast was run based on the calibration parameters. Findings suggest SLEUTH can be applied successfully and produce realistic projection of urban expansion. A comparison between modelled and real urban area revealed 76% model accuracy. The research then attempts to mimic urban growth policy in the modeling environment, with mixed results.

Submitted in fulfillment of the requirements of Doctor of Engineering, Durban University of Technology, Durban, South Africa, 2017.
The need to quantify and model transformations that have taken place in the cities of South Africa is one of the grand challenges linked to country’s transition to Democracy. Given the complexities associated with different stages of city transformation, it is imperative that models used to unpack processes of city transformation are novel. In this study it emerged that statistical methods alone are not adequate to fully present, in a comprehensible way, all facets of drivers of city transformation. As a result, statistical methods have been combined with mathematical and system dynamics models. Results revealed that city transformations derive from a number of triggers. Underlining these are income, migration and houses. The empirical data collected through questionnaire survey that was later incorporated into mathematical models demonstrated that income is a primary driver that fuels city migration. System Dynamic Models demonstrated that the availability of houses or accommodation serve as constraints that keep the city population within the limits of the carrying capacity of a city. In addition it was further confirmed, through mathematical models that income has varying effects on the attractiveness of cities. This was found to be linked to the shape of the distribution of income in the city. A normally distributed income with a peak in the middle results in a city being more attractive than an evenly distributed income that peaks either at very low or high income levels. This observation brought forth a need to test heterogeneity when analyzing city transformation using income as an index. Mathematical Models that incorporated heterogeneity demonstrated the usefulness of systems analysis in unpacking the mechanism of city transformation, a component of city management that requires serious consideration for planning, budgeting and provision of limited resources like houses in the cities. Success of methods used in this study led to a conclusion that these can be enhanced through other techniques like agent based models. With this call, improvements on this study that can be attained through these techniques are recommended. This will enrich the understanding of the transformation and dynamics of cities under different conditions than those that exist in South Africa.
D

Trees represent important living components in many urban parkland spaces. As living landscape entities, they have the capacity for potentially long life spans. As a result of these longevities, issues concerning tree death or senescence are not often engaged until the end of tree life spans have been reached, or are fast approaching. As organisms with finite life spans, tree senescence must be expected at some future point in time, and due consideration of this inevitable change is imperative within an urban parkland context. An understanding of tree longevity in urban parkland spaces must therefore be considered advantageous to subsequent design, management, and planning decisions enacted upon these landscapes. For appropriate decision-making to take place with regard to urban tree populations, figures reflecting expected tree longevity could purvey estimations of future tree senescence, and assist in providing practical information for all stakeholders of urban landscapes. In addition to this, developed models of parkland spaces supplying visual and spatial analysis of future tree senescence patterns could indicate potential landscape scenarios, and highlight tree populations most at risk of senescence within the near future. The development of models predicting possible future tree senescence patterns required a review of various fields of research in order to establish appropriate models for use, and to assign confidence levels based upon the knowledge of tree growth, longevity, and senescence in predicted landscapes. This thesis examined the subjects of tree longevity and senescence, with a particular focus upon the Adelaide Park Lands region in Adelaide, South Australia. Various tree growth parameters were collected from the field and combined with assigned tree ages to create matrix models that represented expected tree growth trends. Through the incorporation of curves fitted to these matrix models, tree ages could be assigned to tree specimens of unknown age, to determine dates of establishment based upon key growth parameters. Tree longevity figures for each taxon were sourced from a peer reference group survey conducted specifically for this purpose. Through the combination of calculated tree age and predicted tree longevity, senescence patterns for a region of the Adelaide Park Lands were modelled. Interactive structured query-based GIS software was incorporated to display these senescence patterns visually, and to provide interpretations of future landscape scenarios. Results obtained from the peer reference group survey provided a range of valuable figures representing expected tree longevities for 131 taxa from within the Adelaide Park Lands environment. These longevity figures, combined with matrix models and GIS simulations, revealed that considerable populations of established trees within Tuttangga/Park 17 in the Adelaide Park Lands are at a high risk of reaching senescence within the near future.
Thesis (Ph.D.) -- University of Adelaide, School of Architecture, Landscape Architecture, and Urban Design, 2008

Trees represent important living components in many urban parkland spaces. As living landscape entities, they have the capacity for potentially long life spans. As a result of these longevities, issues concerning tree death or senescence are not often engaged until the end of tree life spans have been reached, or are fast approaching. As organisms with finite life spans, tree senescence must be expected at some future point in time, and due consideration of this inevitable change is imperative within an urban parkland context. An understanding of tree longevity in urban parkland spaces must therefore be considered advantageous to subsequent design, management, and planning decisions enacted upon these landscapes. For appropriate decision-making to take place with regard to urban tree populations, figures reflecting expected tree longevity could purvey estimations of future tree senescence, and assist in providing practical information for all stakeholders of urban landscapes. In addition to this, developed models of parkland spaces supplying visual and spatial analysis of future tree senescence patterns could indicate potential landscape scenarios, and highlight tree populations most at risk of senescence within the near future. The development of models predicting possible future tree senescence patterns required a review of various fields of research in order to establish appropriate models for use, and to assign confidence levels based upon the knowledge of tree growth, longevity, and senescence in predicted landscapes. This thesis examined the subjects of tree longevity and senescence, with a particular focus upon the Adelaide Park Lands region in Adelaide, South Australia. Various tree growth parameters were collected from the field and combined with assigned tree ages to create matrix models that represented expected tree growth trends. Through the incorporation of curves fitted to these matrix models, tree ages could be assigned to tree specimens of unknown age, to determine dates of establishment based upon key growth parameters. Tree longevity figures for each taxon were sourced from a peer reference group survey conducted specifically for this purpose. Through the combination of calculated tree age and predicted tree longevity, senescence patterns for a region of the Adelaide Park Lands were modelled. Interactive structured query-based GIS software was incorporated to display these senescence patterns visually, and to provide interpretations of future landscape scenarios. Results obtained from the peer reference group survey provided a range of valuable figures representing expected tree longevities for 131 taxa from within the Adelaide Park Lands environment. These longevity figures, combined with matrix models and GIS simulations, revealed that considerable populations of established trees within Tuttangga/Park 17 in the Adelaide Park Lands are at a high risk of reaching senescence within the near future.
Thesis (Ph.D.) -- University of Adelaide, School of Architecture, Landscape Architecture, and Urban Design, 2008

Urban consumption is growing with every year and the studies of urban form, density, transportation, and infrastructure are becoming more popular research topics. Mixed-use development is widely recognized and discussed subject of urban sustainability. It helps to cope with energy and transportation related problems in urban environment, forms walking-friendly, economically and socially vital communities. Although mixed land use is the key planning principle of sustainable development and this term frequently appears in the urban planning strategies and literature, it is rarely elaborated upon with substantive and empirical support. Furthermore – the standard mathematical models and methods for quantifying this parameter in most cases are meant for macro-scale, e.g. comparison between cities, districts. This approach miss the human scale – the scale of walkable neighbourhood, and is not suitable to support local planning decisions and detailed measures. This study performs functional mix analysis of Klaipėda City (Lithuania) with emphasis on neighbourhood scale. The demonstrated model proves the importance of scale factor and adds another dimension to existing methods providing background for micro-scale studies of urban form.