Urban Parks as Perceived by City Residents with Mobility Difficulties: A Qualitative Study with In-Depth Interviews

Urban green spaces make an invaluable contribution to the health and well-being of all city residents. Therefore, urban park quality and accessibility are crucial factors in stimulating physical and mental health benefits. This study aimed to assess the quality of urban parks and their accessibility as reported by people with mobility difficulties (seniors, blind and partially sighted people). Four key features of a place (accessibility and linkages, comfort and image, uses and activities and sociability) were considered in an in-depth-interviews (IDI) and “walk-and-talk” interviews. Study results indicate a problem of accessibility of urban parks for people with mobility difficulties (uneven gravel surfaces). However, non-physical aspects of park visits (social activities, cultural events, place branding) were reported as essential factors in explaining the motivation for park visits. Despite individual preferences, experience or reported difficulties, all respondents’ attitudes towards park trips were positive. Therefore, we assume that accessibility is more than just physical comfort. Cultural and social activities play an important role in motivating people with a disability to visit a park.

Modeling Future Land Use Development: A Lithuanian Case

Effective management decisions regarding greenhouse gas (GHG) emissions may be hampered by the lack of scientific tools for modeling future land use change. This study addresses methodological principles for land use development scenario modeling assumed for use in processes of GHG accounting and management. Associated land use policy implications in Lithuania are also discussed. Data on land uses, available from the National Forest Inventory (NFI) and collected for GHG accounting from the land use, land use change and forestry (LULUCF) sector in the country, as well as freely available geographic information, were tested as an input for modeling land use development in the country. The modeling was implemented using the TerrSet Land Change Modeler. Calibration of the modeling approach using historical land use data indicated that land use types important for GHG management in the LULUCF sector were predicted with an accuracy above 80% during a five-year period into the future, while the prediction accuracy for forest and built-up land was 96% or more. Based on several land management scenarios tested, it was predicted that the LULUCF sector in Lithuania will accumulate CO2, with the forest land use type contributing most to CO2 absorption. Key measures to improve the GHG balance and carbon stock changes were suggested to be the afforestation of abandoned or unused agricultural land and prevention of the conversion of grassland into producing land.

The Influence of the Calibration Interval on Simulating Non-Stationary Urban Growth Dynamic Using CA-Markov Model

The temporal non-stationarity of land use and cover change (LUCC) processes is one of the main sources of uncertainty that may influence the calibration and the validation of spatial path-dependent LUCC models. In relation to that, this research aims to investigate the influence of the temporal non-stationarity of land change on urban growth modeling accuracy based on an empirical approach that uses past LUCC. Accordingly, the urban development in Rennes Metropolitan (France) was simulated using fifteen past calibration intervals which are set from six training dates. The study used Idrisi’s Cellular Automata-Markov model (CA-Markov) which is an inductive pattern-based LUCC software package. The land demand for the simulation year was estimated using the Markov Chain method. Model validation was carried out by assessing the quantity of change, allocation, and spatial patterns accuracy. The quantity disagreement was analyzed by taking into consideration the temporal non-stationarity of change rate over the calibration and the prediction intervals, the model ability to reproduce the past amount of change in the future, and the time duration of the prediction interval. The results show that the calibration interval significantly influenced the amount and the spatial allocation of the estimated change. In addition to that, the spatial allocation of change using CA-Markov depended highly on the basis land cover image rather than the observed transition during the calibration period. Therefore, this study provides useful insights on the role of the training dates in the simulation of non-stationary LUCC.

Lessons Learned from Applying an Integrated Land Use Transport Planning Model to Address Issues of Social and Economic Exclusion of Marginalised Groups: The Case of Cape Town, South Africa

The Group Areas Act of 1950 has resulted in post-apartheid South African cities being characterised by spatial patterns with limited access to social and economic opportunities for the black and coloured population. Typically, high-density low-income housing is located peripherally, while low density high-income housing is located in accessible central areas. With increased rural-to-urban migration, the demand for formal housing has historically surpassed supply, which has increased the growth of informal settlements. Current discourse within South African land use policy suggests that in-situ upgrading of informal housing is a viable response to integrate informal settlements into the formal city. In parallel, it is proposed that new low-income residential areas and employment-generating land uses should be located along transport corridors to improve access to transport, its infrastructure and the opportunities it provides for previously marginalised groups. This study uses Cape Town as a case city to explore two land-use driven development strategies directed at informal settlements and low-income housing. A dynamic land use transport model based on a cellular automata land use model and a four-stage transport model was used to simulate land use and transport changes. Specifically, in-situ upgrading of informal settlements and strategically locating new low-income residential and employment generating land uses along transport corridors were considered. The results from the analysis suggest that in-situ upgrading is a viable option only if new informal settlements are in areas with easy access to economic centres. With regards to low-income housing, targeted interventions aimed at ‘unlocking’ low-income housing activities along transport corridors were found to be useful. However, it was also observed that middle-income residential development and employment generating activities were also attracted to the same corridors, thus, resulting in mixed land uses, which is beneficial but can potentially result in rental bids between low and middle-income earners thus displacing low-income earners away from these areas.

Complex Networks: a Mini-review

Network analysis is a powerful tool that provides us a fruitful framework to describe phenomena related to social, technological, and many other real-world complex systems. In this paper, we present a brief review about complex networks including fundamental quantities, examples of network models, and the essential role of network topology in the investigation of dynamical processes as epidemics, rumor spreading, and synchronization. A quite of advances have been provided in this field, and many other authors also review the main contributions in this area over the years. However, we show an overview from a different perspective. Our aim is to provide basic information to a broad audience and more detailed references for those who would like to learn deeper the topic.

Identifying Efficient Operating Rules for Hydropower Reservoirs Using System Dynamics Approach—A Case Study of Three Gorges Reservoir, China

In the long-term operation of hydropower reservoirs, operating rules have been used widely to decide reservoir operation because they can help operators make an approximately optimal decision with limited runoff information. However, the problems faced by reservoir managers is how to make and select an efficient operating rule properly. This study focuses on identifying efficient and reliable operating rules for the long-term operation of hydropower reservoirs using system dynamics (SD) approach. A stochastic hydrological model of reservoir inflow time series was established and used to generate a large number of inflow scenarios. A deterministic optimization operation model of hydropower reservoirs was constructed and then resolved using dynamic programming (DP) algorithm. Simultaneously, within implicit stochastic optimization (ISO) framework, different operating rules were derived using linear fitting methods. Finally, the most efficient one of the existing operating rules was identified based on SD simulation coupled with the operating rules. The Three Gorges Reservoir (TGR) in central China was used as a case study. The results show that the SD simulation is an efficient way to simulate a complicated reservoir system using feedback and causal loops. Moreover, it can directly and efficiently guide reservoir managers to make and identify efficient operating rules for the long-term operation of hydropower reservoirs.

Modeling Patterns of Land Use in Chinese Cities Using an Integrated Cellular Automata Model

This paper introduces an urban growth simulation model applied to the full scope of China. The model uses a multicriteria decision analysis to calculate the land conversion probability and then integrates it with a cellular automata model. A nonlinear relationship is incorporated in to the model to interpret the impacts of different Land Use and Cover Change driving forces. The Analytical Hierarchical Process is also implemented to compute the variance between weights of different factors. Multiple sizes of neighborhood and different urban ratios in the model rules are tested, and a 5 × 5 neighborhood and an urban threshold of 0.33 are chosen. The study demonstrates the importance of spatial analysis on socioeconomic factors, population, and Gross Domestic Product in land use change simulation modeling. The model fills the gap between the purely economic theory simulation model and the geographic simulation model. The nationwide urban simulation is an example that addresses the lack of urban simulation studies in China and among large-scale simulation models.

Simulating Demography and Housing Demand in an Urban Region under Scenarios of Growth and Shrinkage

After the fall of the Berlin wall in 1989, demographic decline and urban shrinkage brought massive changes in the housing stock in East German cities. Urban planners and policy makers face complex problems caused by the resulting vacancies and demolitions and the handling of urban brownfields in the inner city. At the same time, cities are under ongoing pressure of suburbanisation. Because existing models focus mainly on demographic and urban growth and their impact on housing stocks, we present a simulation model that is able to compute both growth and shrinkage processes. We uncover nonlinear dynamics and feedbacks between demography, housing preference, and supply of housing space. The simulation results show that, despite population decline, the increasing number of single households leads to a growing total housing demand in the central parts of the study area. Beyond this area, residential vacancies in multistorey housing segments will remain regardless of population growth. At the same time, the simulations show that, despite population shrinkage and an overall oversupply of flats, there is a negative net demand for flats in affordable prefabricated housing estates as the percentage of low-income households increases. These findings will help planners modify or adapt their visions of the residential function in shrinking cities and to adjust current programmes of renewal and restructuring.