Urban growth monitoring techniques for sustainable development

This paper discusses the role of advance techniques for monitoring urban growth and change for sustainable development of urban environment. It also presents results of a case study involving satellite data for land use/land cover classification of Lucknow city using IRS-1C multi-spectral features. Two classification algorithms have been used in the study. Experiments were conducted to see the level of improvement in digital classification of urban environment using Artificial Neural Network (ANN) technique.

Incorporating community history into urban redevelopment

A community history project must be relevant to each person within it so that they see themselves as part of the socio-cultural fabric of the area and feel a sense of ownership of their environment. The Mill Albion community history project is a diverse, multi-layered public history/art program that captures the social heritage of The Mill Albion and allows the community to contribute to their ongoing history. The Albion Flour Mill was built in 1930 at a time when Australia was feeling the effects of its worst economic depression and continued operations for more than 72 years. After ceasing operation in 2005 the site was left to deteriorate. The FKP Property Group purchased the land to undertake a new urban redevelopment project, drawing on the design principles of a traditional ‘village’, while valuing the importance of remembering the community that once included the Flour Mill. This paper reflects on the this project and showcases some of the culturally creative ways this community’s history was told, using methods such as digital stories, contemporary and historical photography and oral history.

Determination of a set of surrogate parameters to assess urban stormwater quality

This paper presents the outcomes of a research project, which focused on developing a set of surrogate parameters to evaluate urban stormwater quality using simulated rainfall. Use of surrogate parameters has the potential to enhance the rapid generation of urban stormwater quality data based on on-site measurements and thereby reduce resource intensive laboratory analysis. The samples collected from rainfall simulations were tested for a range of physico-chemical parameters which are key indicators of nutrients, solids and organic matter. The analysis revealed that [total dissolved solids (TDS) and dissolved organic carbon (DOC)]; [total solids (TS) and total organic carbon (TOC)]; [turbidity (TTU)]; [electrical conductivity (EC)]; [TTU and EC] as appropriate surrogate parameters for dissolved total nitrogen (DTN), total phosphorus (TP), total suspended solids (TSS), TDS and TS respectively. Relationships obtained for DTN-TDS, DTN-DOC, and TP-TS demonstrated good portability potential. The portability of the relationship developed for TP and TOC was found to be unsatisfactory. The relationship developed for TDS-EC and TS-EC also demonstrated poor portability.

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

Examination of relationships between urban form, household activities, and time allocation in the Atlanta Metropolitan Region

A substantial body of research is focused on understanding the relationships between socio-demographics, land-use characteristics, and mode specific attributes on travel mode choice and time-use patterns. Residential and commercial densities, inter-mixing of land uses, and route directness in conjunction with transportation performance characteristics interact to influence accessibility to destinations as well as time spent traveling and engaging in activities. This study uniquely examines the activity durations undertaken for out-of-home subsistence; maintenance, and discretionary activities. Also examined are total tour durations (summing all activity categories within a tour). Cross-sectional activities are obtained from household activity travel survey data from the Atlanta Metropolitan Region. Time durations allocated to weekdays and weekends are compared. The censoring and endogeneity between activity categories and within individuals are captured using multiple equations Tobit models. The analysis and modeling reveal that land-use characteristics such as net residential density and the number of commercial parcels within a kilometer of a residence are associated with differences in weekday and weekend time-use allocations. Household type and structure are significant predictors across the three activity categories, but not for overall travel times. Tour characteristics such as time-of-day and primary travel mode of the tours also affect traveler's out-of-home activity-tour time-use patterns.

Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

Modeling crash types: New insights into the effects of covariates on crashes at rural intersections

Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

Quality of child abuse information in emergency department injury surveillance data : linking hospital and child welfare data

Emergency departments (EDs) are often the first point of contact with an abused child. Despite legal mandate, the reporting of definite or suspected abusive injury to child safety authorities by ED clinicians varies due to a number of factors including training, access to child safety professionals, departmental culture and a fear of ‘getting it wrong’. This study examined the quality of documentation and coding of child abuse captured by ED based injury surveillance data and ED medical records in the state of Queensland and the concordance of these data with child welfare records. A retrospective medical record review was used to examine the clinical documentation of almost 1000 injured children included in the Queensland Injury Surveillance Unit database (QISU) from 10 hospitals in urban and rural centres. Independent experts re-coded the records based on their review of the notes. A data linkage methodology was then used to link these records with records in the state government’s child welfare database. Cases were sampled from three sub-groups according to the surveillance intent codes: Maltreatment by parent, Undetermined and Unintentional injury. Only 0.1% of cases coded as unintentional injury were recoded to maltreatment by parent, while 1.2% of cases coded as maltreatment by parent were reclassified as unintentional and 5% of cases where the intent was undetermined by the triage nurse were recoded as maltreatment by parent. Quality of documentation varied across type of hospital (tertiary referral centre, children’s, urban, regional and remote). Concordance of health data with child welfare data varied across patient subgroups. Outcomes from this research will guide initiatives to improve the quality of intentional child injury surveillance systems.

Fear and danger in nocturnal urban environments

At the centre of this research is an ethnographic study that saw the researcher embedded within the fabric of inner city life to better understand what characteristics of user activity and interaction could be enhanced by technology. The initial research indicated that the experience of traversing the city after dark unified an otherwise divergent user group through a shared concern for personal safety. Managing this fear and danger represented an important user need. We found that mobile social networking systems are not only integral for bringing people together, they can help in the process of users safely dispersing as well. We conclude, however, that at a time when the average iPhone staggers under the weight of a plethora of apps that do everything from acting as a carpenter’s level to a pregnancy predictor, we consider the potential for the functionality of a personal safety device to be embodied within a stand alone artifact.

Determinants of infant and young child feeding practices in Sri Lanka : secondary data analysis of demographic and health survey 2000

Background: Poor feeding practices in early childhood contribute to the burden of childhood malnutrition and morbidity. Objective: To estimate the key indicators of breastfeeding and complementary feeding and the determinants of selected feeding practices in Sri Lanka. Methods: The sample consisted of 1,127 children aged 0 to 23 months from the Sri Lanka Demographic and Health Survey 2000. The key infant feeding indicators were estimated and selected indicators were examined against a set of individual-, household-, and community- level variables using univariate and multivariate analyses. Results: Breastfeeding was initiated within the first hour after birth in 56.3% of infants, 99.7% had ever been breastfed, 85.0% were currently being breastfed, and 27.2% were being bottle-fed. Of infants under 6 months of age, 60.6% were fully breastfed, and of those aged 6 to 9 months, 93.4% received complementary foods. The likelihood of not initiating breastfeeding within the first hour after birth was higher for mothers who underwent cesarean delivery (OR = 3.23) and those who were not visited by a Public Health Midwife at home during pregnancy (OR = 1.81). The rate of full breastfeeding was significantly lower among mothers who did not receive postnatal home visits by a Public Health Midwife. Bottlefeeding rates were higher among infants whose mothers had ever been employed (OR = 1.86), lived in a metropolitan area (OR = 3.99), or lived in the South-Central Hill country (OR = 3.11) and were lower among infants of mothers with secondary education (OR = 0.27). Infants from the urban (OR = 8.06) and tea estate (OR = 12.63) sectors were less likely to receive timely complementary feeding than rural infants. Conclusions: Antenatal and postnatal contacts with Public Health Midwives were associated with improved breastfeeding practices. Breastfeeding promotion strategies should specifically focus on the estate and urban or metropolitan communities.

Strategising knowledge-based urban development : knowledge city transformations of Brisbane, Australia

In the global knowledge economy, knowledge-intensive industries and knowledge workers are extensively seen as the primary factors to improve the welfare and competitiveness of cities. To attract and retain such industries and workers, cities produce knowledge-based urban development strategies, and therefore such strategising has become an important development mechanism for cities and their economies. The paper discusses the critical connections between knowledge city foundations and integrated knowledge-based urban development mechanisms in both the local and regional level. In particular, the paper investigates Brisbane’s knowledge-based urban development strategies that support gentrification, attraction, and retention of investment and talent. Furthermore, the paper develops a knowledge-based urban development assessment framework to provide a clearer understanding of the local and regional policy frameworks, and relevant applications of Brisbane’s knowledge-based urban development experience, in becoming a prosperous knowledge city. The paper, with its knowledge-based urban development assessment framework, scrutinises Brisbane’s four development domains in detail: economy; society; institutional; built and natural environments. As part of the discussion of the case study findings, the paper describes the global orientation of Brisbane within the frame of regional and local level knowledge-based urban development strategies performing well. Although several good practices from Brisbane have already been internationally acknowledged, the research reveals that Brisbane is still in the early stages of its knowledge-based urban development implementation. Consequently, the development of a monitoring system for all knowledge-based urban development at all levels is highly crucial in accurately measuring the success and failure of specific knowledge-based urban development policies, and Brisbane’s progress towards a knowledge city transformation.

Load frequency control for rural distributed generation

In rural low-voltage networks, distribution lines are usually highly resistive. When many distributed generators are connected to such lines, power sharing among them is difficult when using conventional droop control, as the real and reactive power have strong coupling with each other. A high droop gain can alleviate this problem but may lead the system to instability. To overcome4 this, two droop control methods are proposed for accurate load sharing with frequency droop controller. The first method considers no communication among the distributed generators and regulates the output voltage and frequency, ensuring acceptable load sharing. The droop equations are modified with a transformation matrix based on the line R/X ration for this purpose. The second proposed method, with minimal low bandwidth communication, modifies the reference frequency of the distributed generators based on the active and reactive power flow in the lines connected to the points of common coupling. The performance of these two proposed controllers is compared with that of a controller, which includes an expensive high bandwidth communication system through time-domain simulation of a test system. The magnitude of errors in power sharing between these three droop control schemes are evaluated and tabulated.

The urban water cycle : towards integrated resource management and more sustainable water management systems

The increasing scarcity of water in the world, along with rapid population increase in urban areas, gives reason for concern and highlights the need for integrating water and wastewater management practices. The uncontrolled growth in urban areas has made planning, management and expansion of water and wastewater infrastructure systems very difficult and expensive. In order to achieve sustainable wastewater treatment and promote the conservation of water and nutrient resources, this chapter advocates the need for a closed-loop treatment system approach, and the transformation of the traditional linear treatment systems into integrated cyclical treatment systems. The recent increased understanding of integrated resource management and a shift towards sustainable management and planning of water and wastewater infrastructure are also discussed.

HCI & sustainable food culture : a design framework for engagement

The current food practices around the world raises concerns for food insecurity in the future. Urban / suburban / and peri-urban environments are particularly problematic in their segregation from rural areas where the natural food sources are grown and harvested. Soaring urban population growth only deteriorates the lack of understanding in and access to fresh produce for the people who live, work, and play in the city. This paper explores the role of Human-Computer Interaction (HCI) design in encouraging individual users to participate in creating sustainable food cultures in urban environments. The paper takes a disciplinary perspective of urban informatics and presents five core constituents of the HCI design framework to encourage sustainable food culture in the city via ubiquitous technologies: the perspective of transdisciplinarity; the domains of interest of people, place, and technology; and the perspective of design.

Knowledge infrastructure : managing the assets of creative urban regions

Urban infrastructure along the hard forms such as roads, electricity, water and sewers also includes the soft forms such as research, training, innovation and technology. Knowledge and creativity are keys to soft infrastructure and socioeconomic development. Many city administrations around the world adjust their endogenous development strategies increasingly by investing in soft infrastructure and aiming for a knowledge-based development. At this point, the mapping and management of knowledge asset of cities has become a critical issue for promoting creative urban regions. The chapter scrutinizes the relations between knowledge assets and urban infrastructures and examines the management model to improve soft infrastructure provision.